{"id":1959,"date":"2023-04-28T11:04:42","date_gmt":"2023-04-28T02:04:42","guid":{"rendered":"https:\/\/edu.ujhb.org\/?p=1959"},"modified":"2023-04-28T11:04:43","modified_gmt":"2023-04-28T02:04:43","slug":"matplotlib%e5%85%a5%e9%96%80%ef%bc%88%e6%97%a5%e6%9c%ac%e8%aa%9e%e7%89%88%ef%bc%89","status":"publish","type":"post","link":"https:\/\/edu.ujhb.org\/?p=1959","title":{"rendered":"Matplotlib\u5165\u9580\uff08\u65e5\u672c\u8a9e\u7248\uff09"},"content":{"rendered":"\n

\u30c8\u30ea\u30a2\u30eb\u306e\u30c6\u30ad\u30b9\u30c8 \u30b3\u30f3\u30c6\u30f3\u30c4\u3092\u30a6\u30a7\u30d6\u30b5\u30a4\u30c8\u306e\u30b3\u30f3\u30c6\u30f3\u30c4\u306b\u5408\u308f\u305b\u3066\u30a2\u30ec\u30f3\u30b8\u3057\u3066\u3082\u3089\u3048\u307e\u3059\u304b\u3002Matplotlib \u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u304b\u3089\u59cb\u3081\u307e\u3057\u3087\u3046\u3002\u3053\u308c\u304b\u3089\u8aac\u660e\u3059\u308b\u5185\u5bb9\u306e\u6982\u8981\u3092\u6559\u3048\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n

\u3082\u3061\u308d\u3093\uff01\u4ee5\u4e0b\u306f\u3001Matplotlib \u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306e\u30d3\u30c7\u30aa \u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306e\u6982\u8981\u3067\u3059\u3002\u3053\u306e\u6982\u8981\u306b\u57fa\u3065\u3044\u3066\u3001IT \u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb \u30d3\u30c7\u30aa\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n

    \n
  1. Matplotlib 1.1 \u306e\u7d39\u4ecb. Matplotlib \u3068\u306f 1.2. \u306a\u305c Matplotlib 1.3. Matplotlib \u3068\u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u306e\u6bd4\u8f03<\/li>\n\n\n\n
  2. \u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3068\u69cb\u6210 2.1. Matplotlib \u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb 2.2. \u74b0\u5883\u306e\u69cb\u6210 2.3. \u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306e\u30c6\u30b9\u30c8<\/li>\n\n\n\n
  3. \u57fa\u672c\u7684\u306a\u63cf\u753b 3.1. \u30b0\u30e9\u30d5\u3068\u8ef8\u306e\u4f5c\u6210 3.2. \u6298\u308c\u7dda\u30b0\u30e9\u30d5\u306e\u63cf\u753b 3.3. \u6563\u5e03\u56f3\u306e\u63cf\u753b 3.4. \u7e26\u68d2\u30b0\u30e9\u30d5\u306e\u63cf\u753b 3.5. \u5186\u30b0\u30e9\u30d5\u306e\u63cf\u753b<\/li>\n\n\n\n
  4. \u30b0\u30e9\u30d5\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b4.1. \u30bf\u30a4\u30c8\u30eb\u3068\u8ef8\u30e9\u30d9\u30eb\u3092\u8a2d\u5b9a\u3059\u308b4.2. \u51e1\u4f8b\u3092\u8a2d\u5b9a\u3059\u308b4.3. \u8ef8\u7bc4\u56f2\u3092\u8abf\u6574\u3059\u308b4.4. \u7dda\u306e\u30b9\u30bf\u30a4\u30eb\u3068\u8272\u3092\u5909\u66f4\u3059\u308b4.5. \u30b0\u30ea\u30c3\u30c9\u7dda\u3068\u80cc\u666f\u8272\u3092\u8ffd\u52a0\u3059\u308b<\/li>\n\n\n\n
  5. \u8907\u6570\u306e\u30d7\u30ed\u30c3\u30c8\u3068\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8 5.1. \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u4f5c\u6210 5.2. \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u9593\u9694\u306e\u8abf\u6574 5.3. \u8ef8\u306e\u5171\u6709 5.4. \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u30bf\u30a4\u30c8\u30eb\u306e\u8ffd\u52a0<\/li>\n\n\n\n
  6. 3D \u30d7\u30ed\u30c3\u30c8 6.1. 3D \u6563\u5e03\u56f3 6.2. 3D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0 6.3. 3D \u66f2\u9762\u30b0\u30e9\u30d5<\/li>\n\n\n\n
  7. \u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3068\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u63cf\u753b 7.1. \u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u306e\u4f5c\u6210 7.2. \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u306e\u66f4\u65b0 7.3. \u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u306e\u4fdd\u5b58 7.4. \u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u63cf\u753b\u3068\u30a4\u30d9\u30f3\u30c8\u51e6\u7406<\/li>\n\n\n\n
  8. \u30c7\u30fc\u30bf\u306e\u30a4\u30f3\u30dd\u30fc\u30c8\u3068\u30a8\u30af\u30b9\u30dd\u30fc\u30c8 8.1. CSV \u30d5\u30a1\u30a4\u30eb\u304b\u3089\u306e\u30c7\u30fc\u30bf\u306e\u30a4\u30f3\u30dd\u30fc\u30c8 8.2. Excel \u30d5\u30a1\u30a4\u30eb\u304b\u3089\u306e\u30c7\u30fc\u30bf\u306e\u30a4\u30f3\u30dd\u30fc\u30c8 8.3. \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u30d4\u30af\u30c1\u30e3\u3068\u3057\u3066\u30a8\u30af\u30b9\u30dd\u30fc\u30c8<\/li>\n\n\n\n
  9. \u5b9f\u8df5\u4e8b\u4f8b 9.1. \u6642\u7cfb\u5217\u5206\u6790 9.2. \u76f8\u95a2\u5206\u6790 9.3. \u5730\u7406\u7684\u30c7\u30fc\u30bf\u306e\u8996\u899a\u5316<\/li>\n\n\n\n
  10. \u307e\u3068\u3081 10.1. Matplotlib \u306e\u5236\u9650 10.2. \u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u306e\u63a2\u7d22 10.3. \u30ea\u30bd\u30fc\u30b9\u3068\u3055\u3089\u306a\u308b\u5b66\u7fd2<\/li>\n<\/ol>\n\n\n\n

    \u3053\u306e\u30a2\u30a6\u30c8\u30e9\u30a4\u30f3\u306b\u57fa\u3065\u3044\u3066\u3001Matplotlib \u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb \u30d3\u30c7\u30aa\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059. \u4ed6\u306b\u5fc5\u8981\u306a\u5834\u5408\u306f\u3001\u3044\u3064\u3067\u3082\u79c1\u306b\u8a00\u3063\u3066\u304f\u3060\u3055\u3044. \u30a2\u30a6\u30c8\u30e9\u30a4\u30f3\u306e\u8abf\u6574\u3068\u6539\u5584\u3092\u304a\u624b\u4f1d\u3044\u3057\u307e\u3059. \u5236\u4f5c\u9811\u5f35\u3063\u3066\u304f\u3060\u3055\u3044\uff01<\/p>\n\n\n\n

    \"\"\/<\/figure>\n\n\n\n
    \"gun<\/figure>\n\n\n\n

    Matplotlib \u3068\u306f\u4f55\u304b\u3092\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n

    \u3053\u306e\u4f1a\u8a71\u3067\u4f7f\u7528\u3055\u308c\u305f\u4ee5\u524d\u306e\u30e2\u30c7\u30eb\u306f\u4f7f\u7528\u3067\u304d\u307e\u305b\u3093\u3002\u6700\u65b0\u306e\u30c7\u30d5\u30a9\u30eb\u30c8 \u30e2\u30c7\u30eb\u306b\u5207\u308a\u66ff\u3048\u307e\u3057\u305f<\/p>\n\n\n\n

    Matplotlib \u306f\u3001\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3001\u6563\u5e03\u56f3\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3001\u5186\u30b0\u30e9\u30d5\u30013D \u30b0\u30e9\u30d5\u306a\u3069\u3001\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306e Python \u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3059\u3002MATLAB \u306e\u3088\u3046\u306a\u30d7\u30ed\u30c3\u30c8 \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u3092\u63d0\u4f9b\u3057\u3001\u30c7\u30fc\u30bf \u30b5\u30a4\u30a8\u30f3\u30b9\u3068\u30c7\u30fc\u30bf\u8996\u899a\u5316\u306e\u5206\u91ce\u3067\u6700\u3082\u4e00\u822c\u7684\u306b\u4f7f\u7528\u3055\u308c\u308b\u30e9\u30a4\u30d6\u30e9\u30ea\u306e 1 \u3064\u3067\u3059\u3002<\/p>\n\n\n\n

    Matplotlib \u306f\u5358\u306a\u308b\u30d7\u30ed\u30c3\u30c8 \u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u306f\u306a\u304f\u3001NumPy \u3084 Pandas \u306a\u3069\u306e Python \u79d1\u5b66\u8a08\u7b97\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u4f75\u7528\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002Matplotlib \u306b\u306f\u3001\u8272\u3001\u7dda\u306e\u7a2e\u985e\u3001\u30d5\u30a9\u30f3\u30c8\u3001\u8ef8\u306e\u7bc4\u56f2\u3001\u51e1\u4f8b\u306a\u3069\u3001\u30b0\u30e9\u30d5\u306e\u3055\u307e\u3056\u307e\u306a\u5074\u9762\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b\u305f\u3081\u306e\u591a\u6570\u306e\u30ab\u30b9\u30bf\u30de\u30a4\u30ba \u30aa\u30d7\u30b7\u30e7\u30f3\u304c\u7528\u610f\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u3055\u3089\u306b\u3001Matplotlib \u306f\u3001PDF\u3001SVG\u3001JPG\u3001PNG \u306a\u3069\u3001\u3055\u307e\u3056\u307e\u306a\u51fa\u529b\u5f62\u5f0f\u3082\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

    Matplotlib \u306f\u30012003 \u5e74\u306b John Hunter \u306b\u3088\u3063\u3066\u8a2d\u7acb\u3055\u308c\u305f\u30aa\u30fc\u30d7\u30f3 \u30bd\u30fc\u30b9 \u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3059\u3002\u305d\u308c\u4ee5\u6765\u3001Matplotlib \u306f\u5f37\u529b\u3067\u4f7f\u3044\u3084\u3059\u3044\u30e9\u30a4\u30d6\u30e9\u30ea\u306b\u6210\u9577\u3057\u3001\u91d1\u878d\u3001\u30e9\u30a4\u30d5 \u30b5\u30a4\u30a8\u30f3\u30b9\u3001\u7269\u7406\u5b66\u3001\u5730\u7406\u60c5\u5831\u30b7\u30b9\u30c6\u30e0\u306a\u3069\u3001\u3055\u307e\u3056\u307e\u306a\u5206\u91ce\u306e\u30c7\u30fc\u30bf\u5206\u6790\u304a\u3088\u3073\u8996\u899a\u5316\u30bf\u30b9\u30af\u306b\u5e83\u304f\u4f7f\u7528\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

    \u8981\u3059\u308b\u306b, Matplotlib \u306f Python \u30c7\u30fc\u30bf\u8996\u899a\u5316\u306e\u305f\u3081\u306e\u57fa\u672c\u7684\u306a\u30c4\u30fc\u30eb\u3067\u3059. \u5e45\u5e83\u3044\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3068\u30d7\u30ed\u30c3\u30c8 \u30aa\u30d7\u30b7\u30e7\u30f3\u3092\u63d0\u4f9b\u3057, \u30e6\u30fc\u30b6\u30fc\u306f\u7c21\u5358\u306a\u30b3\u30fc\u30c9\u3067\u30d7\u30ed\u30ec\u30d9\u30eb\u306e\u30c7\u30fc\u30bf\u8996\u899a\u5316\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059. \u307e\u305f, \u63a2\u7d22\u7684\u30c7\u30fc\u30bf\u5206\u6790\u3068\u30c7\u30fc\u30bf\u306b\u3082\u975e\u5e38\u306b\u9069\u3057\u3066\u3044\u307e\u3059.\u8996\u899a\u5316 \u8996\u899a\u7684\u306a\u6559\u80b2\u3068\u5b66\u7fd2\u3002<\/p>\n\n\n\n

    \"\"\/<\/figure>\n\n\n\n
    \"gun<\/figure>\n\n\n\n

    Matplotlib \u304c\u9078\u3070\u308c\u305f\u7406\u7531\u3092\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n

    Matplotlib \u3092\u9078\u629e\u3059\u308b\u7406\u7531\u306f\u305f\u304f\u3055\u3093\u3042\u308a\u307e\u3059\u304c\u3001\u4e3b\u306a\u3082\u306e\u3092\u3044\u304f\u3064\u304b\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

      \n
    1. \u7121\u6599\u3067\u30aa\u30fc\u30d7\u30f3 \u30bd\u30fc\u30b9: Matplotlib \u306f\u7121\u6599\u3067\u30aa\u30fc\u30d7\u30f3 \u30bd\u30fc\u30b9\u306e\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u3067\u3042\u308b\u305f\u3081\u3001\u8ab0\u3067\u3082\u4f7f\u7528\u3057\u3066\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u4f5c\u6210\u3067\u304d\u3001\u6709\u6599\u306e\u30d7\u30ed \u30e9\u30a4\u30bb\u30f3\u30b9\u306f\u5fc5\u8981\u3042\u308a\u307e\u305b\u3093\u3002<\/li>\n\n\n\n
    2. \u4f7f\u3044\u3084\u3059\u3055: Matplotlib \u306f\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u5358\u7d14\u306a Python \u30b3\u30fc\u30c9\u3067\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3092\u4f5c\u6210\u3067\u304d\u308b\u76f4\u611f\u7684\u306a API \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u30b3\u30fc\u30c9\u306f\u901a\u5e38\u3001\u975e\u5e38\u306b\u7406\u89e3\u3057\u3084\u3059\u3044\u3082\u306e\u3067\u3059\u3002<\/li>\n\n\n\n
    3. \u5f37\u529b\u306a\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u53ef\u80fd\u6027: Matplotlib \u306f\u3001\u7dda\u7a2e\u3001\u8272\u3001\u30e9\u30d9\u30eb\u3001\u30d5\u30a9\u30f3\u30c8\u3001\u8ef8\u7bc4\u56f2\u3001\u51e1\u4f8b\u306a\u3069\u3092\u542b\u3080\u591a\u6570\u306e\u30ab\u30b9\u30bf\u30de\u30a4\u30ba \u30aa\u30d7\u30b7\u30e7\u30f3\u3092\u63d0\u4f9b\u3059\u308b\u305f\u3081\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u7c21\u5358\u306b\u8abf\u6574\u3067\u304d\u307e\u3059\u3002<\/li>\n\n\n\n
    4. \u8907\u6570\u306e\u51fa\u529b\u5f62\u5f0f: Matplotlib \u306f\u3001PDF\u3001SVG\u3001JPG\u3001PNG \u306a\u3069\u306e\u8907\u6570\u306e\u51fa\u529b\u5f62\u5f0f\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u308b\u305f\u3081\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u3055\u307e\u3056\u307e\u306a\u5834\u9762\u3067\u4f7f\u7528\u3059\u308b\u305f\u3081\u306b\u3055\u307e\u3056\u307e\u306a\u5f62\u5f0f\u3067\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u51fa\u529b\u3067\u304d\u307e\u3059\u3002<\/li>\n\n\n\n
    5. \u5e83\u7bc4\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3068\u30b3\u30df\u30e5\u30cb\u30c6\u30a3 \u30b5\u30dd\u30fc\u30c8: Matplotlib \u306b\u306f\u5e83\u7bc4\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3068\u30b3\u30df\u30e5\u30cb\u30c6\u30a3 \u30b5\u30dd\u30fc\u30c8\u304c\u3042\u308a\u307e\u3059. \u30e6\u30fc\u30b6\u30fc\u306f\u3001\u516c\u5f0f Web \u30b5\u30a4\u30c8\u3067\u8a73\u7d30\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3068\u4f8b\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059. \u307e\u305f\u3001\u3055\u307e\u3056\u307e\u306a\u30bd\u30fc\u30b7\u30e3\u30eb \u30e1\u30c7\u30a3\u30a2 \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3067 Matplotlib \u306b\u95a2\u9023\u3059\u308b\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3068\u30d8\u30eb\u30d7\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059.<\/li>\n\n\n\n
    6. Python \u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u3068\u306e\u7dca\u5bc6\u306a\u7d71\u5408: Matplotlib \u306f\u3001NumPy\u3001Pandas\u3001SciPy \u306a\u3069\u306e Python \u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u306e\u4ed6\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u7dca\u5bc6\u306b\u7d71\u5408\u3055\u308c\u3066\u3044\u308b\u305f\u3081\u3001\u30c7\u30fc\u30bf\u5206\u6790\u3084\u79d1\u5b66\u8a08\u7b97\u30bf\u30b9\u30af\u3067\u306e\u4f7f\u7528\u304c\u4fbf\u5229\u3067\u3059\u3002<\/li>\n<\/ol>\n\n\n\n

      \u8981\u3059\u308b\u306b\u3001Matplotlib \u3092\u9078\u629e\u3059\u308b\u7406\u7531\u306f\u3001\u5f37\u529b\u3067\u67d4\u8edf\u6027\u304c\u3042\u308a\u3001\u4f7f\u3044\u3084\u3059\u304f\u3001\u7121\u6599\u306e\u30c7\u30fc\u30bf\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3042\u308a\u3001\u5e45\u5e83\u3044\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3068\u30d7\u30ed\u30c3\u30c8 \u30aa\u30d7\u30b7\u30e7\u30f3\u3092\u63d0\u4f9b\u3057\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u30d7\u30ed \u30ec\u30d9\u30eb\u306e\u30c7\u30fc\u30bf\u8996\u899a\u5316\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u4f5c\u6210\u3067\u304d\u308b\u3088\u3046\u306b\u3059\u308b\u305f\u3081\u3067\u3059\u3002\u307e\u305f\u3001Matplotlib \u306f\u3001\u63a2\u7d22\u7684\u30c7\u30fc\u30bf\u5206\u6790\u3068\u30c7\u30fc\u30bf\u8996\u899a\u5316\u306e\u6559\u80b2\u3068\u5b66\u7fd2\u306b\u3082\u9069\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

      \"\"\/<\/figure>\n\n\n\n
      \"gun<\/figure>\n\n\n\n

      Matplotlib \u304c\u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3068\u3069\u306e\u3088\u3046\u306b\u6bd4\u8f03\u3055\u308c\u308b\u304b\u3092\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n

      Matplotlib \u306f\u3001\u5e83\u304f\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b Python \u7528\u306e\u30c7\u30fc\u30bf\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3059\u304c\u3001\u4ed6\u306b\u3082\u3044\u304f\u3064\u304b\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3092\u5229\u7528\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u3001Matplotlib \u3068\u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3068\u306e\u6bd4\u8f03\u3067\u3059\u3002<\/p>\n\n\n\n

        \n
      1. Seaborn: Seaborn \u306f\u3001Matplotlib \u306e\u4e0a\u306b\u69cb\u7bc9\u3055\u308c\u305f\u5225\u306e Python \u30c7\u30fc\u30bf\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3042\u308a\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u3088\u308a\u8fc5\u901f\u306b\u4f5c\u6210\u3067\u304d\u308b\u3088\u3046\u306b\u3059\u308b\u3001\u3088\u308a\u9ad8\u30ec\u30d9\u30eb\u306e\u30b0\u30e9\u30d5\u30a3\u30ab\u30eb \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u3068\u30d7\u30ea\u30bb\u30c3\u30c8 \u30b9\u30bf\u30a4\u30eb\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002Seaborn \u306f Matplotlib \u3088\u308a\u3082\u30b0\u30e9\u30d5 \u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u306e\u30aa\u30d7\u30b7\u30e7\u30f3\u304c\u5c11\u306a\u3044\u304b\u3082\u3057\u308c\u307e\u305b\u3093\u304c\u3001\u5834\u5408\u306b\u3088\u3063\u3066\u306f Seaborn \u306e\u65b9\u304c\u4f7f\u3044\u3084\u3059\u3044\u304b\u3082\u3057\u308c\u307e\u305b\u3093\u3002<\/li>\n\n\n\n
      2. Plotly: Plotly \u306f\u3001\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3068\u52d5\u7684\u52b9\u679c\u3092\u63d0\u4f9b\u3059\u308b JavaScript \u30d9\u30fc\u30b9\u306e\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3059\u3002Plotly \u306f\u3001Matplotlib \u3088\u308a\u3082\u9b45\u529b\u7684\u306a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3092\u63d0\u4f9b\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u3001\u305d\u306e\u8996\u899a\u5316\u306f\u3088\u308a\u30e2\u30c0\u30f3\u3067\u3059\u3002\u305f\u3060\u3057\u3001Plotly \u306f\u6709\u6599\u306e\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb \u30e9\u30a4\u30bb\u30f3\u30b9\u3092\u4f7f\u7528\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u5546\u7528\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u3067\u3042\u308b\u305f\u3081\u3001Matplotlib \u3084 Seaborn \u307b\u3069\u5e83\u304f\u4f7f\u7528\u3055\u308c\u3066\u3044\u307e\u305b\u3093\u3002<\/li>\n\n\n\n
      3. ggplot: ggplot \u306f\u3001\u69cb\u6587\u30d9\u30fc\u30b9\u306e\u30d7\u30ed\u30c3\u30c8\u306e\u6982\u5ff5\u306b\u57fa\u3065\u3044\u3066\u69cb\u7bc9\u3055\u308c\u3001Seaborn \u306b\u4f3c\u305f\u9ad8\u30ec\u30d9\u30eb\u306e\u30b0\u30e9\u30d5\u30a3\u30ab\u30eb \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u3092\u63d0\u4f9b\u3059\u308b R \u8a00\u8a9e\u306e\u30c7\u30fc\u30bf\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3059\u3002Matplotlib \u3068\u6bd4\u8f03\u3057\u3066\u3001ggplot \u306b\u3088\u3063\u3066\u63d0\u4f9b\u3055\u308c\u308b\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u306f\u3088\u308a\u7f8e\u3057\u304f\u3001\u8996\u899a\u5316\u69cb\u6587\u306f\u3088\u308a\u76f4\u611f\u7684\u3067\u3059\u3002\u305f\u3060\u3057\u3001ggplot \u306f R \u3067\u306e\u307f\u4f7f\u7528\u3067\u304d\u308b\u305f\u3081\u3001Python \u3092\u4f7f\u7528\u3059\u308b\u5834\u5408\u306f\u3001Matplotlib \u306e\u65b9\u304c\u9069\u3057\u3066\u3044\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/li>\n\n\n\n
      4. D3.js: D3.js \u306f\u3001\u9ad8\u5ea6\u306b\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3055\u308c\u305f\u30b0\u30e9\u30d5\u30a3\u30ab\u30eb \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u3068\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u52b9\u679c\u3092\u63d0\u4f9b\u3059\u308b JavaScript \u30d9\u30fc\u30b9\u306e\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3059\u3002Matplotlib \u3068\u6bd4\u8f03\u3057\u3066\u3001D3.js \u304c\u63d0\u4f9b\u3059\u308b\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u52b9\u679c\u306f\u3088\u308a\u4eba\u76ee\u3092\u5f15\u304d\u3001\u305d\u306e\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u52b9\u679c\u306f\u3088\u308a\u8c4a\u5bcc\u3067\u3059\u3002\u305f\u3060\u3057\u3001D3.js \u306b\u306f\u3088\u308a\u591a\u304f\u306e\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u4f5c\u696d\u304c\u5fc5\u8981\u3067\u3042\u308a\u3001\u305d\u306e\u5b66\u7fd2\u66f2\u7dda\u306f\u6025\u52fe\u914d\u306b\u306a\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n

        \u7c21\u5358\u306b\u8a00\u3048\u3070\u3001Matplotlib \u306f\u3001\u5f37\u529b\u3067\u67d4\u8edf\u6027\u304c\u3042\u308a\u3001\u4f7f\u3044\u3084\u3059\u304f\u3001\u7121\u6599\u306e\u30c7\u30fc\u30bf\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3042\u308a\u3001\u5e45\u5e83\u3044\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3068\u63cf\u753b\u30aa\u30d7\u30b7\u30e7\u30f3\u3092\u63d0\u4f9b\u3057\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u7c21\u5358\u306a\u30b3\u30fc\u30c9\u3067\u30d7\u30ed\u30ec\u30d9\u30eb\u306e\u30c7\u30fc\u30bf\u8996\u899a\u5316\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u4f5c\u6210\u3067\u304d\u308b\u3088\u3046\u306b\u3057\u307e\u3059\u3002Matplotlib \u306f\u63a2\u7d22\u7684\u30c7\u30fc\u30bf\u5206\u6790\u3068\u30c7\u30fc\u30bf\u8996\u899a\u5316\u306e\u6559\u80b2\u3068\u5b66\u7fd2\u306b\u3082\u975e\u5e38\u306b\u9069\u3057\u3066\u3044\u307e\u3059\u3002\u305f\u3060\u3057\u3001\u30cb\u30fc\u30ba\u3084\u597d\u307f\u306b\u3088\u3063\u3066\u306f\u3001\u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u306e\u65b9\u304c\u4f5c\u696d\u306b\u9069\u3057\u3066\u3044\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

        \"\"\/<\/figure>\n\n\n\n
        \"gun<\/figure>\n\n\n\n

        Matplotlib \u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n

        \u901a\u5e38\u3001Matplotlib \u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306f\u7c21\u5358\u3067\u3059\u3002Windows\u3001macOS\u3001\u304a\u3088\u3073 Linux \u306b Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u624b\u9806\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/p>\n\n\n\n

          \n
        1. Windows \u306b Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u306b\u306f: 1.1 \u30b3\u30de\u30f3\u30c9 \u30d7\u30ed\u30f3\u30d7\u30c8\u307e\u305f\u306f PowerShell \u3092\u958b\u304d\u3001pip \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066 Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002pip install matplotlib<\/code>1.2 Anaconda \u30c7\u30a3\u30b9\u30c8\u30ea\u30d3\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u4f7f\u7528\u3057\u3066\u3044\u308b\u5834\u5408\u306f\u3001conda \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066 Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3067\u304d\u307e\u3059\u3002conda install matplotlib<\/code><\/li>\n\n\n\n
        2. macOS \u306b Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059: 2.1 \u30bf\u30fc\u30df\u30ca\u30eb\u3092\u958b\u304d\u3001pip \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066 Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059: pip install matplotlib<\/code>2.2 Anaconda \u30c7\u30a3\u30b9\u30c8\u30ea\u30d3\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u4f7f\u7528\u3057\u3066\u3044\u308b\u5834\u5408\u306f\u3001conda \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066 Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3067\u304d\u307e\u3059\u3002conda install matplotlib<\/code><\/li>\n\n\n\n
        3. Linux \u306b Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b: 3.1 \u30bf\u30fc\u30df\u30ca\u30eb\u3092\u958b\u304d\u3001pip \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066 Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059: pip install matplotlib<\/code>3.2 Anaconda \u30c7\u30a3\u30b9\u30c8\u30ea\u30d3\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u4f7f\u7528\u3057\u3066\u3044\u308b\u5834\u5408\u306f\u3001conda \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066 Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3067\u304d\u307e\u3059: 3.3 conda install matplotlib<\/code>Ubuntu \u306a\u3069\u306e Debian \u30d9\u30fc\u30b9\u306e Linux \u3092\u4f7f\u7528\u3057\u3066\u3044\u308b\u5834\u5408sudo apt-get install python3-matplotlib<\/code>Fedora \u3084 CentOS \u306a\u3069\u306e Red Hat \u30d9\u30fc\u30b9\u306e Linux \u30c7\u30a3\u30b9\u30c8\u30ea\u30d3\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u4f7f\u7528\u3057\u3066\u3044\u308b\u5834\u5408\u306f\u3001dnf \u307e\u305f\u306f yum \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066 Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3067\u304d\u307e\u3059sudo dnf install python3-matplotlib<\/code>\u3002sudo yum install python3-matplotlib<\/code><\/li>\n<\/ol>\n\n\n\n

          \u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u304c\u5b8c\u4e86\u3057\u305f\u3089\u3001Matplotlib \u30e9\u30a4\u30d6\u30e9\u30ea\u3092 Python \u30b3\u30fc\u30c9\u306b\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3001\u305d\u308c\u3092\u4f7f\u7528\u3057\u3066\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u554f\u984c\u3084\u30a8\u30e9\u30fc\u304c\u767a\u751f\u3057\u305f\u5834\u5408\u306f\u3001\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u307e\u305f\u306f\u30b3\u30df\u30e5\u30cb\u30c6\u30a3 \u30b5\u30dd\u30fc\u30c8\u3092\u53c2\u7167\u3059\u308b\u304b\u3001Stack Overflow \u306a\u3069\u306e\u30b5\u30a4\u30c8\u3067\u30d8\u30eb\u30d7\u3092\u6c42\u3081\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n

          \"\"\/<\/figure>\n\n\n\n
          \"gun<\/figure>\n\n\n\n

          \u74b0\u5883\u306e\u8a2d\u5b9a\u65b9\u6cd5\u3092\u8a73\u3057\u304f\u6559\u3048\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n

          \u74b0\u5883\u306e\u69cb\u6210\u306f\u901a\u5e38\u3001\u30b7\u30b9\u30c6\u30e0\u304c\u5b9f\u884c\u3055\u308c\u3001Matplotlib \u3092\u6b63\u3057\u304f\u4f7f\u7528\u3067\u304d\u308b\u3088\u3046\u306b\u3059\u308b\u305f\u3081\u306b\u884c\u308f\u308c\u307e\u3059\u3002\u4ee5\u4e0b\u306b\u3001\u4e00\u822c\u7684\u306a\u74b0\u5883\u69cb\u6210\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

            \n
          1. Python \u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u3092\u78ba\u8a8d\u3057\u3066\u304f\u3060\u3055\u3044: Matplotlib \u306b\u306f Python 3.5 \u4ee5\u964d\u304c\u5fc5\u8981\u3067\u3059\u3002Python \u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u304c\u3053\u306e\u8981\u4ef6\u3088\u308a\u3082\u4f4e\u3044\u5834\u5408\u306f\u3001\u6700\u521d\u306b\u6700\u65b0\u30d0\u30fc\u30b8\u30e7\u30f3\u306b\u30a2\u30c3\u30d7\u30b0\u30ec\u30fc\u30c9\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/li>\n\n\n\n
          2. \u4f9d\u5b58\u95a2\u4fc2\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb: Matplotlib \u306f\u3001NumPy\u3001Pillow \u306a\u3069\u306e\u4ed6\u306e Python \u30e9\u30a4\u30d6\u30e9\u30ea\u306b\u4f9d\u5b58\u3057\u3066\u3044\u307e\u3059\u3002Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u524d\u306b\u3001\u3053\u308c\u3089\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u6b63\u3057\u304f\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3057\u3066\u304f\u3060\u3055\u3044\u3002pip install numpy<\/code>pip \u307e\u305f\u306f conda \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3001\u6b21\u306e\u3088\u3046\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3067\u304d\u307e\u3059conda install numpy<\/code>\u3002<\/li>\n\n\n\n
          3. Matplotlib \u306e\u30d0\u30c3\u30af\u30a8\u30f3\u30c9\u3092\u30bb\u30c3\u30c8\u30a2\u30c3\u30d7\u3059\u308b: Matplotlib \u306b\u306f\u3001\u30b0\u30e9\u30d5\u30a3\u30c3\u30af \u30ec\u30f3\u30c0\u30ea\u30f3\u30b0\u3084\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u8868\u793a\u306a\u3069\u306e\u30bf\u30b9\u30af\u3092\u51e6\u7406\u3059\u308b\u305f\u3081\u306e\u3055\u307e\u3056\u307e\u306a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af \u30d0\u30c3\u30af\u30a8\u30f3\u30c9\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u69cb\u6210\u30d5\u30a1\u30a4\u30eb\u3067\u30c7\u30d5\u30a9\u30eb\u30c8\u306e\u30d0\u30c3\u30af\u30a8\u30f3\u30c9\u3092\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002\u30c7\u30d5\u30a9\u30eb\u30c8\u3067\u306f\u3001Matplotlib \u306f TkAgg \u30d0\u30c3\u30af\u30a8\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002Python \u30b9\u30af\u30ea\u30d7\u30c8\u306b\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u8ffd\u52a0\u3059\u308b\u3053\u3068\u3067\u3001\u30c7\u30d5\u30a9\u30eb\u30c8\u306e\u30d0\u30c3\u30af\u30a8\u30f3\u30c9\u3092\u78ba\u8a8d\u304a\u3088\u3073\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002import matplotlib print(matplotlib.get_backend()) # \u6253\u5370\u5f53\u524d\u7684\u540e\u7aef matplotlib.use('agg') # \u8bbe\u7f6e\u540e\u7aef\u4e3aagg<\/code><\/li>\n\n\n\n
          4. Matplotlib \u306e\u30b9\u30bf\u30a4\u30eb\u3092\u69cb\u6210\u3059\u308b: Matplotlib \u306b\u306f\u3001\u30b0\u30e9\u30d5\u306e\u8272\u3001\u30d5\u30a9\u30f3\u30c8\u3001\u30e9\u30d9\u30eb\u306a\u3069\u3092\u3059\u3070\u3084\u304f\u8a2d\u5b9a\u3067\u304d\u308b\u3055\u307e\u3056\u307e\u306a\u7d44\u307f\u8fbc\u307f\u306e\u30b9\u30bf\u30a4\u30eb \u30aa\u30d7\u30b7\u30e7\u30f3\u304c\u7528\u610f\u3055\u308c\u3066\u3044\u307e\u3059\u3002Python \u30b9\u30af\u30ea\u30d7\u30c8\u306b\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u8ffd\u52a0\u3059\u308b\u3053\u3068\u3067\u3001\u7279\u5b9a\u306e\u30b9\u30bf\u30a4\u30eb\u3092\u6709\u52b9\u306b\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9import matplotlib.pyplot as plt plt.style.use('ggplot') # \u542f\u7528ggplot\u6837\u5f0f <\/code>\u69cb\u6210\u30d5\u30a1\u30a4\u30eb\u3067\u30c7\u30d5\u30a9\u30eb\u30c8\u306e\u30b9\u30bf\u30a4\u30eb \u30aa\u30d7\u30b7\u30e7\u30f3\u3092\u8a2d\u5b9a\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/li>\n\n\n\n
          5. Matplotlib \u306e\u30d5\u30a9\u30f3\u30c8\u3092\u8a2d\u5b9a\u3059\u308b: \u5834\u5408\u306b\u3088\u3063\u3066\u306f\u3001Matplotlib \u306e\u65e2\u5b9a\u306e\u30d5\u30a9\u30f3\u30c8\u3092\u5909\u66f4\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u69cb\u6210\u30d5\u30a1\u30a4\u30eb\u3067\u30d5\u30a9\u30f3\u30c8 \u30aa\u30d7\u30b7\u30e7\u30f3\u3092\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u3092 Matplotlib \u306e\u69cb\u6210\u30d5\u30a1\u30a4\u30eb\u306b\u8ffd\u52a0\u3067\u304d\u307e\u3059: yamlCopy \u30b3\u30fc\u30c9font.family : sans-serif font.sans-serif : Arial, Helvetica, sans-serif <\/code>\u3053\u308c\u306b\u3088\u308a\u3001\u30d5\u30a9\u30f3\u30c8\u304c\u3001Arial\u3001Helvetica \u306a\u3069\u306e\u4e00\u822c\u7684\u306b\u4f7f\u7528\u3055\u308c\u308b\u30b5\u30f3\u30bb\u30ea\u30d5 \u30d5\u30a9\u30f3\u30c8\u306b\u8a2d\u5b9a\u3055\u308c\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n

            \u3053\u308c\u3089\u306f\u3044\u304f\u3064\u304b\u306e\u4e00\u822c\u7684\u306a\u74b0\u5883\u8a2d\u5b9a\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u3001\u7279\u5b9a\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u4ed6\u306e\u8a2d\u5b9a\u3084\u8abf\u6574\u3092\u884c\u3046\u5fc5\u8981\u304c\u3042\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306b\u306f\u3001\u3088\u308a\u8a73\u7d30\u306a\u74b0\u5883\u8a2d\u5b9a\u30ac\u30a4\u30c9\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

            \"\"\/<\/figure>\n\n\n\n
            \"gun<\/figure>\n\n\n\n

            \u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3092\u30c6\u30b9\u30c8\u3059\u308b\u65b9\u6cd5\u3092\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n

            Matplotlib \u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u305f\u5f8c\u3001\u3044\u304f\u3064\u304b\u306e\u7c21\u5358\u306a\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3057\u3066\u3001Matplotlib \u304c\u6b63\u3057\u304f\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u304a\u3088\u3073\u69cb\u6210\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3059\u308b\u3053\u3068\u3092\u304a\u52e7\u3081\u3057\u307e\u3059\u3002Matplotlib \u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3092\u30c6\u30b9\u30c8\u3059\u308b\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

              \n
            1. Matplotlib \u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3066\u30d0\u30fc\u30b8\u30e7\u30f3\u3092\u78ba\u8a8d\u3059\u308b: Python \u306e\u5bfe\u8a71\u578b\u30b3\u30de\u30f3\u30c9 \u30e9\u30a4\u30f3\u3067\u3001\u6b21\u306e\u30b3\u30de\u30f3\u30c9\u3092\u5165\u529b\u3057\u3066 Matplotlib \u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3001\u305d\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u3092\u78ba\u8a8d\u3057\u307e\u3059: pythonCopy import matplotlib print(matplotlib.__version__) <\/code>code\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306b\u6210\u529f\u3057\u307e\u3057\u305f\u3002<\/li>\n\n\n\n
            2. \u5358\u7d14\u306a\u30b0\u30e9\u30d5\u3092\u63cf\u304f: Python \u306e\u5bfe\u8a71\u578b\u30b3\u30de\u30f3\u30c9 \u30e9\u30a4\u30f3\u3067\u3001\u6b21\u306e\u30b3\u30de\u30f3\u30c9\u3092\u5165\u529b\u3057\u3066\u5358\u7d14\u306a\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3057\u307e\u3059import matplotlib.pyplot as plt plt.plot([1, 2, 3, 4]) plt.ylabel('some numbers') plt.show() <\/code>\u3002<\/li>\n\n\n\n
            3. Matplotlib \u306e\u30b5\u30f3\u30d7\u30eb \u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u5b9f\u884c\u3059\u308b: Matplotlib \u306b\u306f\u3001Matplotlib \u3092\u4f7f\u7528\u3057\u3066\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u3092\u5b66\u7fd2\u3059\u308b\u306e\u306b\u5f79\u7acb\u3064\u591a\u6570\u306e\u30b5\u30f3\u30d7\u30eb \u30d7\u30ed\u30b0\u30e9\u30e0\u304c\u7528\u610f\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u30b5\u30f3\u30d7\u30eb \u30d7\u30ed\u30b0\u30e9\u30e0\u306f\u3001Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306b\u3042\u308a\u307e\u3059\u3002\u30b3\u30de\u30f3\u30c9 \u30e9\u30a4\u30f3\u304b\u3089\u6b21\u306e\u3088\u3046\u306b\u5165\u529b\u3059\u308b\u3068\u3001Matplotlib \u306e\u30b5\u30f3\u30d7\u30eb \u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u8868\u793a\u3067\u304d\u307e\u3059python -m matplotlib.pyplot --examples <\/code>\u3002<\/li>\n<\/ol>\n\n\n\n

              \u3053\u308c\u3089\u306f Matplotlib \u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3092\u30c6\u30b9\u30c8\u3059\u308b\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306b\u306f\u3001\u30b1\u30fc\u30b9\u30d0\u30a4\u30b1\u30fc\u30b9\u3067\u4ed6\u306e\u30c6\u30b9\u30c8\u3084\u8abf\u6574\u3092\u5b9f\u884c\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002\u554f\u984c\u3084\u30a8\u30e9\u30fc\u304c\u767a\u751f\u3057\u305f\u5834\u5408\u306f\u3001Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u307e\u305f\u306f\u30b3\u30df\u30e5\u30cb\u30c6\u30a3 \u30b5\u30dd\u30fc\u30c8\u3092\u53c2\u7167\u3059\u308b\u304b\u3001Stack Overflow \u306a\u3069\u306e\u30b5\u30a4\u30c8\u3067\u30d8\u30eb\u30d7\u3092\u6c42\u3081\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n

              \"\"\/<\/figure>\n\n\n\n
              \"gun<\/figure>\n\n\n\n

              \u56f3\u5f62\u3068\u8ef8\u306e\u4f5c\u6210\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n

              Matplotlib \u3067\u306f\u3001Figure \u3068 Axes \u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u3001Figure \u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306e\u57fa\u672c\u7684\u306a\u624b\u9806\u3067\u3059\u3002Figure \u3068 Axes \u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306e\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

                \n
              1. \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001plt.figure()<\/code>\u95a2\u6570\u3092\u547c\u3073\u51fa\u3057\u3066\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u6b21\u306efig<\/code>\u540d\u524d\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002import matplotlib.pyplot as plt fig = plt.figure()<\/code><\/li>\n\n\n\n
              2. \u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001fig.add_subplot()<\/code>\u95a2\u6570\u3092\u547c\u3073\u51fa\u3057\u3066\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u6b21\u306eax<\/code>\u540d\u524d\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059: pythonCopy \u30b3\u30fc\u30c9ax = fig.add_subplot(111) <\/code>111<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u306f\u3001\u30b0\u30e9\u30d5\u3092 1 \u884c 1 \u5217\u306e 1 \u3064\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306b\u5206\u5272\u3057\u3001ax<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092 1 \u756a\u76ee\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306b\u914d\u7f6e\u3059\u308b\u3053\u3068\u3092\u610f\u5473\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
              3. \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306e\u63cf\u753b: Matplotlib \u3067\u306f\u3001ax.plot()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7dda\u3092\u63cf\u753b\u3057\u307e\u3059: pythonCopy codeax.plot([1, 2, 3, 4], [1, 4, 2, 3]) <\/code>\u3053\u308c\u306f\u3001\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30aa\u30d6\u30b8\u30a7\u30af\u30c8fig<\/code>\u306baxes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3057ax<\/code>\u3001ax<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7dda\u3092\u63cf\u753b\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
              4. \u8ef8\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30eb\u306e\u8a2d\u5b9a: Matplotlib \u3067\u306f\u3001\u95a2\u6570\u3068\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066ax.set_xlabel()<\/code>\u8ef8ax.set_ylabel()<\/code>\u30e9\u30d9\u30ebax.set_title()<\/code>\u3068\u30bf\u30a4\u30c8\u30eb\u3092\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u8ef8\u306e\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30ebax.set_xlabel('x label') ax.set_ylabel('y label') ax.set_title('title') <\/code>\u3092ax<\/code>\u8a2d\u5b9a\u3057x label<\/code>\u307e\u3059\u3002y label<\/code>title<\/code><\/li>\n\n\n\n
              5. \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u306e\u8868\u793a: Matplotlib \u3067\u306f\u3001plt.show()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u8868\u793a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30b0\u30e9\u30d5\u30a3\u30c3\u30af \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u8868\u793a\u3057\u307e\u3059fig<\/code>\u3002plt.show()<\/code><\/li>\n<\/ol>\n\n\n\n

                \u3053\u308c\u3089\u306f\u30b0\u30e9\u30d5\u3084\u8ef8\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306e\u57fa\u672c\u7684\u306a\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u3001\u7279\u5b9a\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u4ed6\u306e\u64cd\u4f5c\u3084\u8abf\u6574\u304c\u5fc5\u8981\u306b\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306b\u306f\u3001Figure \u3068 Axes \u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

                \"\"\/<\/figure>\n\n\n\n
                \"gun<\/figure>\n\n\n\n

                \u6298\u308c\u7dda\u30b0\u30e9\u30d5\u306e\u63cf\u304d\u65b9\u3092\u8a73\u3057\u304f\u6559\u3048\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n

                Matplotlib \u3067\u306f\u3001plot()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

                  \n
                1. \u5358\u7d14\u306a\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u306e\u63cf\u753b: Matplotlib \u3067\u306f\u3001plot()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u5358\u7d14\u306a\u7dda\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001axes\u30aa\u30d6\u30b8\u30a7\u30af\u30c8ax<\/code>\u306b 4 \u3064\u306e\u70b9\u3092\u6301\u3064\u7dda\u3092\u63cf\u753b\u3057\u307e\u3059ax.plot([1, 2, 3, 4], [1, 4, 2, 3]) <\/code>\u3002ax<\/code>(1, 1)<\/code>(2, 4)<\/code>(3, 2)<\/code>(4, 3)<\/code><\/li>\n\n\n\n
                2. \u8907\u6570\u306e\u7dda\u306e\u63cf\u753b: Matplotlib \u3067\u306f\u3001\u540c\u3058\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u8907\u6570\u306e\u7dda\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001 axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b2\u672c\u306e\u7dda\u3092\u63cf\u753b\u3057\u307e\u3059: pythonCopy ax<\/code>codeax.plot([1, 2, 3, 4], [1, 4, 2, 3]) ax.plot([1, 2, 3, 4], [5, 2, 4, 1]) <\/code>\u3053\u308c\u306fax<\/code>\u3001axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b 2 \u672c\u306e\u7dda\u3092(1, 1)<\/code>\u63cf\u753b\u3057\u307e\u3059\u3002(2, 4)<\/code>(3, 2)<\/code>(4, 3)<\/code>(1, 5)<\/code>(2, 2)<\/code>(3, 4)<\/code>(4, 1)<\/code><\/li>\n\n\n\n
                3. \u7dda\u306e\u8272\u3001\u7dda\u306e\u30b9\u30bf\u30a4\u30eb\u3001\u304a\u3088\u3073\u30de\u30fc\u30ab\u30fc\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b: Matplotlib \u3067\u306f\u3001 \u304a\u3088\u3073\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066color<\/code>\u3001\u7dda\u306e\u8272\u3001\u7dda\u306e\u30b9\u30bf\u30a4\u30eb\u3001\u304a\u3088\u3073\u30de\u30fc\u30ab\u30fc\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u5186\u30de\u30fc\u30ab\u30fc\u3067\u8d64\u3044\u7834\u7dda\u3092\u63cf\u753b\u3057\u307e\u3059\u3002linestyle<\/code>marker<\/code>ax.plot([1, 2, 3, 4], [1, 4, 2, 3], color='r', linestyle='--', marker='o')<\/code><\/li>\n\n\n\n
                4. \u8ef8\u306e\u7bc4\u56f2\u3068\u76ee\u76db\u308a\u306e\u8a2d\u5b9a: Matplotlib \u3067\u306f\u3001ax.set_xlim()<\/code>\u95a2\u6570\u3068ax.set_ylim()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u8ef8\u306e\u7bc4\u56f2\u3092\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f x \u8ef8\u306e\u7bc4\u56f2\u3092 \u306b\u3001 y\u8ef8[0, 5]<\/code>\u306e\u7bc4\u56f2\u3092 \u306b\u8a2d\u5b9a\u3057\u307e\u3059[0, 6]<\/code>\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f x \u8ef8\u306e\u76ee\u76db\u308a\u3092 \u306b\u3001y \u8ef8\u306e\u76ee\u76db\u308a\u3092 \u306b\u8a2d\u5b9a\u3057\u307e\u3059\u3002ax.set_xlim([0, 5]) ax.set_ylim([0, 6]) <\/code>ax.set_xticks()<\/code>ax.set_yticks()<\/code>[0, 1, 2, 3, 4, 5]<\/code>[0, 2, 4, 6]<\/code>ax.set_xticks([0, 1, 2, 3, 4, 5]) ax.set_yticks([0, 2, 4, 6])<\/code><\/li>\n<\/ol>\n\n\n\n

                  \u4ee5\u4e0a\u304c\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u306e\u57fa\u672c\u7684\u306a\u63cf\u304d\u65b9\u3067\u3059\u304c\u3001\u5b9f\u969b\u306b\u306f<\/p>\n\n\n\n

                  \"\"\/<\/figure>\n\n\n\n
                  \"gun<\/figure>\n\n\n\n

                  \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n

                  \u4ee5\u4e0a\u304c\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u306e\u57fa\u672c\u7684\u306a\u63cf\u753b\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u5225\u306e\u64cd\u4f5c\u3084\u8abf\u6574\u304c\u5fc5\u8981\u306b\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306b\u306f\u3001\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u304c\u3042\u308a\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u3001\u5358\u7d14\u306a\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306e\u5b8c\u5168\u306a\u30b5\u30f3\u30d7\u30eb \u30b3\u30fc\u30c9\u3067\u3059\u3002<\/p>\n\n\n\n

                  python\u30b3\u30fc\u30c9\u3092\u30b3\u30d4\u30fc\u3059\u308bimport matplotlib.pyplot as plt\n\n# \u521b\u5efa\u56fe\u5f62\u5bf9\u8c61\u548c\u8f74\u5bf9\u8c61\nfig, ax = plt.subplots()\n\n# \u7ed8\u5236\u4e00\u6761\u7b80\u5355\u7684\u7ebf\nax.plot([1, 2, 3, 4], [1, 4, 2, 3])\n\n# \u8bbe\u7f6e\u8f74\u7684\u6807\u7b7e\u548c\u6807\u9898\nax.set_xlabel('x label')\nax.set_ylabel('y label')\nax.set_title('title')\n\n# \u8bbe\u7f6e\u8f74\u7684\u8303\u56f4\u548c\u523b\u5ea6\nax.set_xlim([0, 5])\nax.set_ylim([0, 6])\nax.set_xticks([0, 1, 2, 3, 4, 5])\nax.set_yticks([0, 2, 4, 6])\n\n# \u663e\u793a\u56fe\u5f62\nplt.show()\n<\/code><\/pre>\n\n\n\n
                  \u3053\u308c\u306b\u3088\u308a\u3001x \u8ef8\u3068 y \u8ef8\u306e\u30e9\u30d9\u30eb\u3001\u30bf\u30a4\u30c8\u30eb\u3001\u7bc4\u56f2\u3001\u76ee\u76db\u308a\u304c\u30b0\u30e9\u30d5\u306b\u8ffd\u52a0\u3055\u308c\u305f\u5358\u7d14\u306a\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u304c\u4f5c\u6210\u3055\u308c\u307e\u3059\u3002\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u30b3\u30fc\u30c9\u3092\u5909\u66f4\u3057\u3066\u3001\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                  \"\"\/<\/figure>\n\n\n\n
                  \"gun<\/figure>\n\n\n\n
                  \u6563\u5e03\u56f3\u306e\u63cf\u304d\u65b9\u3092\u8a73\u3057\u304f\u6559\u3048\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                  Matplotlib \u3067\u306f\u3001scatter()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3059\u308b\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                    \n
                  1. \u5358\u7d14\u306a\u6563\u5e03\u56f3\u306e\u63cf\u753b: Matplotlib \u3067\u306f\u3001scatter()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u5358\u7d14\u306a\u4e00\u9023\u306e\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b 4 \u70b9\u306e\u6563\u5e03\u30bb\u30c3\u30c8\u3092\u63cf\u753b\u3057\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9ax.scatter([1, 2, 3, 4], [1, 4, 2, 3]) <\/code>\u3053\u308c\u306f\u3001ax<\/code>Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b 4 \u70b9\u306e\u6563\u5e03\u30bb\u30c3\u30c8\u3092\u63cf\u753b\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                  2. \u8272\u3068\u30b5\u30a4\u30ba\u3067\u6563\u5e03\u56f3\u3092\u63cf\u304f: Matplotlib \u3067\u306f\u3001 \u30d1\u30e9\u30e1\u30fc\u30bfc<\/code>\u3068s<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066\u3001\u6563\u5e03\u56f3\u306e\u8272\u3068\u30b5\u30a4\u30ba\u3092\u5236\u5fa1\u3067\u304d\u307e\u3059\u3002ax.scatter([1, 2, 3, 4], [1, 4, 2, 3], c=['r', 'g', 'b', 'y'], s=[20, 50, 100, 200]) <\/code>\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u8272\u3068\u30b5\u30a4\u30ba\u306e\u6563\u5e03\u70b9\u306e\u30bb\u30c3\u30c8\u3092\u63cf\u753b\u3057\u307e\u3059ax<\/code>\u3002<\/li>\n\n\n\n
                  3. \u6563\u5e03\u56f3\u306e\u5f62\u72b6\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b: Matplotlib \u3067\u306f\u3001marker<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u6563\u5e03\u56f3\u306e\u5f62\u72b6\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u661f\u3067\u8868\u3055\u308c\u308b\u4e00\u9023\u306e\u6563\u5e03\u70b9\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3059\u3002ax.scatter([1, 2, 3, 4], [1, 4, 2, 3], marker='*')<\/code><\/li>\n\n\n\n
                  4. \u6563\u5e03\u70b9\u306e\u30e9\u30d9\u30eb\u3068\u6ce8\u91c8\u306e\u8a2d\u5b9a: Matplotlib \u3067\u306f\u3001ax.text()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u6563\u5e03\u70b9\u306b\u30e9\u30d9\u30eb\u3068\u6ce8\u91c8\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>\u30e9\u30d9\u30eb\u3068\u6ce8\u91c8\u3092\u4f7f\u7528\u3057\u3066\u3001ax.scatter([1, 2, 3, 4], [1, 4, 2, 3]) ax.text(1, 1, 'point 1') ax.text(2, 4, 'point 2') ax.text(3, 2, 'point 3') ax.text(4, 3, 'point 4') <\/code>Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8ax<\/code>\u306b 4 \u3064\u306e\u30dd\u30a4\u30f3\u30c8\u306e\u6563\u5e03\u30bb\u30c3\u30c8\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                    \u4ee5\u4e0a\u304c\u6563\u5e03\u56f3\u306e\u57fa\u672c\u7684\u306a\u63cf\u753b\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306e\u4f7f\u7528\u306b\u3042\u305f\u3063\u3066\u306f\u3001\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u5225\u306e\u64cd\u4f5c\u3084\u8abf\u6574\u304c\u5fc5\u8981\u306b\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                    \"\"\/<\/figure>\n\n\n\n
                    \"gun<\/figure>\n\n\n\n
                    \u63cf\u753b\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                    Matplotlib \u3067\u306f\u3001\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3067\u304d\u307e\u3059bar()<\/code>\u3002\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306e\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                      \n
                    1. \u5358\u7d14\u306a\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u63cf\u753b: Matplotlib \u3067\u306f\u3001bar()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u4e00\u9023\u306e\u5358\u7d14\u306a\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b 4 \u672c\u306e\u30d0\u30fc\u3092\u6301\u3064\u4e00\u9023\u306e\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3057\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9ax.bar([1, 2, 3, 4], [1, 4, 2, 3]) <\/code>\u3053\u308c\u306f\u3001ax<\/code>\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b 4 \u672c\u306e\u30d0\u30fc\u3092\u6301\u3064\u4e00\u9023\u306e\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                    2. \u7a4d\u307f\u4e0a\u3052\u7e26\u68d2\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b: Matplotlib \u3067\u306f\u3001bottom<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u7a4d\u307f\u4e0a\u3052\u7e26\u68d2\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7a4d\u307f\u4e0a\u3052\u3089\u308c\u305f\u4e00\u9023\u306e\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3057\u307e\u3059ax<\/code>\u3002ax.bar([1, 2, 3, 4], [1, 4, 2, 3], bottom=[0, 1, 2, 3]) <\/code>ax<\/code>y=1<\/code>y=2<\/code><\/li>\n\n\n\n
                    3. \u6c34\u5e73\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u63cf\u753b: Matplotlib \u3067\u306f\u3001barh()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u6c34\u5e73\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u4e00\u9023\u306e\u6c34\u5e73\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3057\u307e\u3059\u3002ax.barh([1, 2, 3, 4], [1, 4, 2, 3])<\/code><\/li>\n\n\n\n
                    4. \u5217\u306e\u8272\u3068\u5e45\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b: Matplotlib \u3067\u306f\u3001\u30d1\u30e9\u30e1\u30fc\u30bf\u30fccolor<\/code>\u3068 \u3092\u4f7f\u7528\u3057\u3066width<\/code>\u3001\u5217\u306e\u8272\u3068\u5e45\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u5e45 0.5 \u306e\u9752\u8272\u306e\u4e00\u9023\u306e\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3057\u307e\u3059\u3002ax.bar([1, 2, 3, 4], [1, 4, 2, 3], color='b', width=0.5)<\/code><\/li>\n<\/ol>\n\n\n\n
                      \u4ee5\u4e0a\u304c\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u57fa\u672c\u7684\u306a\u63cf\u753b\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u5225\u306e\u64cd\u4f5c\u3084\u8abf\u6574\u304c\u5fc5\u8981\u306b\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                      \"\"\/<\/figure>\n\n\n\n
                      \"gun<\/figure>\n\n\n\n
                      \u5186\u30b0\u30e9\u30d5\u306e\u63cf\u753b\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                      Matplotlib \u3067\u306f\u3001pie()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306e\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                        \n
                      1. \u5358\u7d14\u306a\u5186\u30b0\u30e9\u30d5\u306e\u63cf\u753b: Matplotlib \u3067\u306f\u3001pie()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u4e00\u9023\u306e\u5358\u7d14\u306a\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b 3 \u3064\u306e\u30b9\u30e9\u30a4\u30b9\u3092\u6301\u3064\u4e00\u9023\u306e\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u307e\u3059\u3002 pythonCopy codeax.pie([30, 50, 20]) <\/code>\u3053\u308c\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b 3 \u3064\u306e\u30b9\u30e9\u30a4\u30b9\u3092\u6301\u3064\u4e00\u9023\u306e\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                      2. \u30e9\u30d9\u30eb\u3068\u6ce8\u91c8\u3092\u4f7f\u7528\u3057\u305f\u5186\u30b0\u30e9\u30d5\u306e\u63cf\u753b: Matplotlib \u3067\u306f\u3001labels<\/code>\u304a\u3088\u3073autopct<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066\u3001\u5186\u30b0\u30e9\u30d5\u306b\u30e9\u30d9\u30eb\u3068\u6ce8\u91c8\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002ax.pie([30, 50, 20], labels=['A', 'B', 'C'], autopct='%1.1f%%') <\/code>\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u30e9\u30d9\u30eb\u3068\u6ce8\u91c8\u4ed8\u304d\u306e\u4e00\u9023\u306e\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u307e\u3059ax<\/code>\u3002<\/li>\n\n\n\n
                      3. \u5186\u30b0\u30e9\u30d5\u306e\u8272\u3068\u958b\u59cb\u89d2\u5ea6\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b: Matplotlib \u3067\u306f\u3001\u30d1\u30e9\u30e1\u30fc\u30bf\u30fccolors<\/code>\u3092\u4f7f\u7528\u3057\u3066startangle<\/code>\u3001\u5186\u30b0\u30e9\u30d5\u306e\u8272\u3068\u958b\u59cb\u89d2\u5ea6\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002ax.pie([30, 50, 20], colors=['r', 'g', 'b'], startangle=90) <\/code>\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u8272\u3068\u958b\u59cb\u89d2\u5ea6\u3092\u6301\u3064\u4e00\u9023\u306e\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u307e\u3059ax<\/code>\u3002<\/li>\n\n\n\n
                      4. \u30c9\u30fc\u30ca\u30c4\u5186\u30b0\u30e9\u30d5\u306e\u63cf\u753b: Matplotlib \u3067\u306f\u3001wedgeprops<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30c9\u30fc\u30ca\u30c4\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u4e00\u9023\u306e\u30c9\u30fc\u30ca\u30c4\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u307e\u3059\u3002 pythonCopy codeax.pie([30, 50, 20], wedgeprops={'width': 0.5}) <\/code>\u3053\u308c\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b 3 \u3064\u306e\u6247\u5f62\u3092\u6301\u3064\u4e00\u9023\u306e\u30c9\u30fc\u30ca\u30c4\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                        \u4ee5\u4e0a\u304c\u5186\u30b0\u30e9\u30d5\u306e\u57fa\u672c\u7684\u306a\u63cf\u753b\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u5225\u306e\u64cd\u4f5c\u3084\u8abf\u6574\u304c\u5fc5\u8981\u306b\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u5186\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                        \"\"\/<\/figure>\n\n\n\n
                        \"gun<\/figure>\n\n\n\n
                        \u30bf\u30a4\u30c8\u30eb\u3068\u8ef8\u30e9\u30d9\u30eb\u306e\u8a2d\u5b9a\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                        Matplotlib \u3067\u306f\u3001set_title()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066 Figure \u306e\u30bf\u30a4\u30c8\u30eb\u3092\u8a2d\u5b9a\u3057\u3001 andset_xlabel()<\/code>\u95a2\u6570set_ylabel()<\/code>\u3092\u4f7f\u7528\u3057\u3066\u8ef8\u306e\u30e9\u30d9\u30eb\u3092\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u30b0\u30e9\u30d5\u306e\u30bf\u30a4\u30c8\u30eb\u3092 \u306bMy Plot<\/code>\u3001x \u8ef8\u306e\u30e9\u30d9\u30eb\u3092 \u306bX<\/code>\u3001y \u8ef8\u306e\u30e9\u30d9\u30eb\u3092 \u306b\u8a2d\u5b9a\u3057\u307e\u3059Y<\/code>\u3002<\/p>\n\n\n\n
                        python\u30b3\u30fc\u30c9\u3092\u30b3\u30d4\u30fc\u3059\u308bimport matplotlib.pyplot as plt\n\nfig, ax = plt.subplots()\nax.plot([1, 2, 3, 4], [1, 4, 2, 3])\n\nax.set_title('My Plot')\nax.set_xlabel('X')\nax.set_ylabel('Y')\n\nplt.show()\n<\/code><\/pre>\n\n\n\n
                        \u3053\u308c\u306b\u3088\u308a\u3001\u30bf\u30a4\u30c8\u30eb\u3068\u8ef8\u30e9\u30d9\u30eb\u304c\u30b0\u30e9\u30d5\u306b\u8ffd\u52a0\u3055\u308c\u305f\u5358\u7d14\u306a\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u304c\u4f5c\u6210\u3055\u308c\u307e\u3059\u3002\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u3001\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u30bf\u30a4\u30c8\u30eb\u3068\u30e9\u30d9\u30eb\u306e\u5185\u5bb9\u3068\u30b9\u30bf\u30a4\u30eb\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001fontsize<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30bf\u30a4\u30c8\u30eb\u3068\u30e9\u30d9\u30eb\u306e\u30d5\u30a9\u30f3\u30c8 \u30b5\u30a4\u30ba\u3092\u8a2d\u5b9a\u3057\u305f\u308a\u3001fontweight<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30d5\u30a9\u30f3\u30c8\u306e\u592a\u3055\u3092\u8a2d\u5b9a\u3057\u305f\u308a\u3001color<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30d5\u30a9\u30f3\u30c8\u306e\u8272\u3092\u8a2d\u5b9a\u3057\u305f\u308a\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                        Matplotlib \u3067\u306f\u3001ax<\/code>Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3068 Figure \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u30bf\u30a4\u30c8\u30eb\u3068\u30e9\u30d9\u30eb\u3092\u8a2d\u5b9a\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044fig<\/code>\u3002\u3059\u3079\u3066\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u540c\u3058\u30bf\u30a4\u30c8\u30eb\u3068\u30e9\u30d9\u30eb\u3092\u8a2d\u5b9a\u3059\u308b\u5834\u5408\u306f\u3001fig<\/code>\u30b0\u30e9\u30d5 \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3067\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u30bf\u30a4\u30c8\u30eb\u3068\u30e9\u30d9\u30eb\u306e\u307f\u3092\u8a2d\u5b9a\u3059\u308b\u5834\u5408\u306f\u3001ax<\/code>\u305d\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3067\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                        \"\"\/<\/figure>\n\n\n\n
                        \"gun<\/figure>\n\n\n\n
                        \u30bb\u30c3\u30c8\u30a2\u30c3\u30d7\u306e\u51e1\u4f8b\u3092\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                        Matplotlib \u3067\u306f\u3001legend()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u51e1\u4f8b\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002\u51e1\u4f8b\u306f\u3001\u901a\u5e38\u3001\u3055\u307e\u3056\u307e\u306a\u7dda\u3001\u8272\u3001\u307e\u305f\u306f\u30b9\u30bf\u30a4\u30eb\u3092\u533a\u5225\u3059\u308b\u305f\u3081\u306b\u3001\u30b0\u30e9\u30d5\u306e\u3055\u307e\u3056\u307e\u306a\u90e8\u5206\u3092\u8b58\u5225\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u308b\u8aac\u660e\u3067\u3059\u3002\u51e1\u4f8b\u3092\u8ffd\u52a0\u3059\u308b\u306b\u306f\u3001\u6b21\u306e\u65b9\u6cd5\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
                          \n
                        1. \u7dda\u3078\u306e\u51e1\u4f8b\u306e\u8ffd\u52a0: Matplotlib \u3067\u306f\u3001label<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u7dda\u306b\u30e9\u30d9\u30eb\u3092\u4ed8\u3051\u3001legend()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u51e1\u4f8b\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7dda\u3092\u63cf\u753b\u3057\u3001\u305d\u306e\u7dda\u306b\u30e9\u30d9\u30eb\u3092\u8ffd\u52a0\u3057\u307e\u3059line1<\/code>: pythonCopy codeax.plot([1, 2, 3, 4], [1, 4, 2, 3], label='line1') ax.legend() <\/code>\u3053\u308c\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7dda\u3092\u63cf\u753b\u3057\u3001\u51e1\u4f8b\u306b\u30e9\u30d9\u30eb\u3092\u8ffd\u52a0\u3057\u307e\u3059line1<\/code>\u3002<\/li>\n\n\n\n
                        2. \u7570\u306a\u308b\u8272\u306e\u7dda\u3078\u306e\u51e1\u4f8b\u306e\u8ffd\u52a0: \u30b0\u30e9\u30d5\u3067\u7570\u306a\u308b\u8272\u306e\u8907\u6570\u306e\u7dda\u3092\u4f7f\u7528\u3059\u308b\u5834\u5408\u3001label<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u5404\u7dda\u306b\u30e9\u30d9\u30eb\u3092\u8ffd\u52a0\u3057\u3001legend()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u51e1\u4f8b\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001axesax<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7570\u306a\u308b\u8272\u306e 2 \u3064\u306e\u7dda\u3092\u63cf\u753b\u3057\u30012 \u3064\u306e\u7dda\u306b\u30e9\u30d9\u30ebline1<\/code>\u3068\u5408\u8a08\u3092\u8ffd\u52a0\u3057\u307e\u3059line2<\/code>: pythonCopy codeax.plot([1, 2, 3, 4], [1, 4, 2, 3], 'r', label='line1') ax.plot([1, 2, 3, 4], [3, 2, 4, 1], 'g', label='line2') ax.legend() <\/code>\u3053\u308c\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7570\u306a\u308b\u8272\u306e 2 \u3064\u306e\u7dda\u3092\u63cf\u753b\u3057\u3001Add \u30bf\u30b0line1<\/code>\u3068line2<\/code><\/li>\n\n\n\n
                        3. \u51e1\u4f8b\u306e\u4f4d\u7f6e\u3068\u30b9\u30bf\u30a4\u30eb\u3092\u8a2d\u5b9a\u3059\u308b: Matplotlib \u3067\u306f\u3001loc<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u51e1\u4f8b\u306e\u4f4d\u7f6e\u3092\u8a2d\u5b9a\u3057\u305f\u308a\u3001frameon<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u51e1\u4f8b\u306e\u5883\u754c\u3092\u5236\u5fa1\u3057\u305f\u308a\u3001fontsize<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u51e1\u4f8b\u306e\u30d5\u30a9\u30f3\u30c8 \u30b5\u30a4\u30ba\u3092\u8a2d\u5b9a\u3057\u305f\u308a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u5de6\u4e0a\u9685\u306b\u5883\u754c\u7dda\u306e\u306a\u3044\u51e1\u4f8b\u3092\u63cf\u753b\u3057\u307e\u3059\u3002\u51e1\u4f8b\u306e\u30d5\u30a9\u30f3\u30c8 \u30b5\u30a4\u30ba\u306f 10 \u3067\u3059\u3002ax.legend(loc='upper left', frameon=False, fontsize=10)<\/code><\/li>\n<\/ol>\n\n\n\n
                          \u3053\u308c\u3089\u306f\u51e1\u4f8b\u3092\u8ffd\u52a0\u3059\u308b\u305f\u3081\u306e\u57fa\u672c\u7684\u306a\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u3001\u7279\u5b9a\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u4ed6\u306e\u64cd\u4f5c\u3084\u8abf\u6574\u304c\u5fc5\u8981\u306b\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u51e1\u4f8b\u3092\u8ffd\u52a0\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                          \"\"\/<\/figure>\n\n\n\n
                          \"gun<\/figure>\n\n\n\n
                          \u8ef8\u7bc4\u56f2\u306e\u8abf\u6574\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u6559\u3048\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                          Matplotlib \u3067\u306f\u3001set_xlim()<\/code>\u95a2\u6570\u3068set_ylim()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u8ef8\u306e\u7bc4\u56f2\u3092\u8abf\u6574\u3067\u304d\u307e\u3059\u3002\u3053\u308c\u3089 2 \u3064\u306e\u95a2\u6570\u306f\u3001\u305d\u308c\u305e\u308c\u5ea7\u6a19\u8ef8\u306e\u958b\u59cb\u4f4d\u7f6e\u3068\u7d42\u4e86\u4f4d\u7f6e\u3092\u793a\u3059 2 \u3064\u306e\u8981\u7d20\u3092\u542b\u3080\u30ea\u30b9\u30c8\u307e\u305f\u306f\u30bf\u30d7\u30eb\u3092\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3068\u3057\u3066\u53d7\u3051\u5165\u308c\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001x \u8ef8\u306e\u7bc4\u56f2\u3092 \u306b[0, 5]<\/code>\u3001y \u8ef8\u306e\u7bc4\u56f2\u3092 \u306b\u8a2d\u5b9a\u3057\u307e\u3059[0, 10]<\/code>\u3002<\/p>\n\n\n\n
                          python\u30b3\u30fc\u30c9\u3092\u30b3\u30d4\u30fc\u3059\u308bimport matplotlib.pyplot as plt\n\nfig, ax = plt.subplots()\nax.plot([1, 2, 3, 4], [1, 4, 2, 3])\n\nax.set_xlim([0, 5])\nax.set_ylim([0, 10])\n\nplt.show()\n<\/code><\/pre>\n\n\n\n
                          \u3053\u308c\u306b\u3088\u308a\u3001\u5358\u7d14\u306a\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u304c\u4f5c\u6210\u3055\u308c\u3001x \u8ef8\u3068 y \u8ef8\u306e\u7bc4\u56f2\u304c \u3068 \u306b\u8a2d\u5b9a\u3055\u308c[0, 5]<\/code>\u307e\u3059[0, 10]<\/code>\u3002<\/p>\n\n\n\n
                          \u8ef8\u306e 1 \u3064\u306e\u7bc4\u56f2\u306e\u307f\u3092\u8abf\u6574\u3059\u308b\u5834\u5408\u306f\u3001\u4ed6\u306e\u8ef8\u306e\u7bc4\u56f2\u3092 \u306b\u8a2d\u5b9a\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044None<\/code>\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001y \u8ef8\u306e\u7bc4\u56f2\u306e\u307f\u3092\u8abf\u6574\u3057\u3001x \u8ef8\u306e\u7bc4\u56f2\u3092\u30c7\u30d5\u30a9\u30eb\u30c8\u5024\u306b\u8a2d\u5b9a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                          python\u30b3\u30fc\u30c9\u3092\u30b3\u30d4\u30fc\u3059\u308bax.set_xlim([None, 5])\nax.set_ylim([0, 10])\n<\/code><\/pre>\n\n\n\n
                          set_xlim()<\/code>and\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3060\u3051\u3067\u306a\u304fset_ylim()<\/code>\u3001xlim()<\/code>andylim()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u73fe\u5728\u306e\u5ea7\u6a19\u8ef8\u306e\u7bc4\u56f2\u3092\u53d6\u5f97\u3057\u305f\u308a\u3001autoscale()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u5ea7\u6a19\u8ef8\u306e\u7bc4\u56f2\u3092\u81ea\u52d5\u8abf\u6574\u3057\u305f\u308a\u3001tight_layout()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u30ec\u30a4\u30a2\u30a6\u30c8\u3092\u81ea\u52d5\u8abf\u6574\u3057\u305f\u308a\u3001\u7b49\u3005\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u8ef8\u306e\u7bc4\u56f2\u3092\u8abf\u6574\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                          \"\"\/<\/figure>\n\n\n\n
                          \"gun<\/figure>\n\n\n\n
                          \u7dda\u7a2e\u3068\u8272\u306e\u5909\u66f4\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                          Matplotlib \u3067\u306f\u3001plot()<\/code>\u95a2\u6570\u306e 3 \u756a\u76ee\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u3001\u7dda\u306e\u30b9\u30bf\u30a4\u30eb\u3068\u8272\u3092\u6307\u5b9a\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u306f\u3001\u30b9\u30bf\u30a4\u30eb\u307e\u305f\u306f\u8272\u3092\u8868\u3059 1 \u3064\u4ee5\u4e0a\u306e\u6587\u5b57\u3067\u69cb\u6210\u3055\u308c\u308b\u6587\u5b57\u5217\u3067\u3059\u3002\u7dda\u306e\u30b9\u30bf\u30a4\u30eb\u3068\u8272\u3092\u5909\u66f4\u3059\u308b\u306b\u306f\u3001\u6b21\u306e\u65b9\u6cd5\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
                            \n
                          1. \u7dda\u306e\u8272\u306e\u5909\u66f4: Matplotlib \u3067\u306f\u3001\u6b21\u306e\u6587\u5b57\u3092\u4f7f\u7528\u3057\u3066\u7dda\u306e\u8272\u3092\u6307\u5b9a\u3067\u304d\u307e\u3059\u3002
                            • 'b'<\/code>\uff1a\u9752<\/li>
                            • 'g'<\/code>\uff1a\u7dd1<\/li>
                            • 'r'<\/code>\uff1a\u8d64<\/li>
                            • 'c'<\/code>\uff1a\u9752\u8272<\/li>
                            • 'm'<\/code>\uff1a\u54c1\u7ea2\u8272<\/li>
                            • 'y'<\/code>\uff1a\u9ec4\u8272<\/li>
                            • 'k'<\/code>\uff1a\u9ed2<\/li>
                            • 'w'<\/code>\uff1a\u767d\u8272<\/li><\/ul>\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u9752\u3044\u7dda\u3092\u63cf\u753b\u3057\u307e\u3059: pythonCopy codeax.plot([1, 2, 3, 4], [1, 4, 2, 3], 'b')<\/code><\/li>\n\n\n\n
                            • \u7dda\u306e\u30b9\u30bf\u30a4\u30eb\u3092\u5909\u66f4\u3059\u308b: Matplotlib \u3067\u306f\u3001\u6b21\u306e\u6587\u5b57\u3092\u4f7f\u7528\u3057\u3066\u7dda\u306e\u30b9\u30bf\u30a4\u30eb\u3092\u6307\u5b9a\u3067\u304d\u307e\u3059\u3002
                              • '-'<\/code>\uff1a\u5b9f\u7dda<\/li>
                              • '--'<\/code>\uff1a\u70b9\u7dda<\/li>
                              • ':'<\/code>\uff1a\u70b9\u7dda<\/li>
                              • '-.'<\/code>\uff1a \u70b9\u7dda<\/li><\/ul>\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u8d64\u3044\u7834\u7dda\u3092\u63cf\u753b\u3057\u307e\u3059: pythonCopy codeax.plot([1, 2, 3, 4], [1, 4, 2, 3], 'r--')<\/code><\/li>\n\n\n\n
                              • \u7dda\u5e45\u306e\u5909\u66f4: Matplotlib \u3067\u306f\u3001linewidth<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u7dda\u5e45\u3092\u6307\u5b9a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u5e45 2 \u306e\u7dd1\u306e\u5b9f\u7dda\u3092\u63cf\u753b\u3057\u307e\u3059\u3002ax.plot([1, 2, 3, 4], [1, 4, 2, 3], 'g-', linewidth=2)<\/code><\/li>\n<\/ol>\n\n\n\n
                                \u3053\u308c\u3089\u306f\u7dda\u7a2e\u3084\u8272\u3092\u5909\u66f4\u3059\u308b\u57fa\u672c\u7684\u306a\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u4ed6\u306e\u64cd\u4f5c\u3084\u8abf\u6574\u304c\u5fc5\u8981\u306b\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u7dda\u306e\u30b9\u30bf\u30a4\u30eb\u3068\u8272\u3092\u5909\u66f4\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u30e9\u30a4\u30f3\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                \"\"\/<\/figure>\n\n\n\n
                                \"gun<\/figure>\n\n\n\n
                                \u30b0\u30ea\u30c3\u30c9\u7dda\u3068\u80cc\u666f\u8272\u306e\u8ffd\u52a0\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                Matplotlib \u3067\u306f\u3001grid()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30b0\u30ea\u30c3\u30c9\u7dda\u3092\u8ffd\u52a0\u3057\u3001set_facecolor()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u80cc\u666f\u8272\u3092\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002\u30b0\u30ea\u30c3\u30c9\u7dda\u3068\u80cc\u666f\u8272\u3092\u8ffd\u52a0\u3059\u308b\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                  \n
                                1. \u6c34\u5e73\u304a\u3088\u3073\u5782\u76f4\u306e\u30b0\u30ea\u30c3\u30c9\u7dda\u306e\u8ffd\u52a0: Matplotlib \u3067\u306f\u3001grid()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u6c34\u5e73\u304a\u3088\u3073\u5782\u76f4\u306e\u30b0\u30ea\u30c3\u30c9\u7dda\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002\u30c7\u30d5\u30a9\u30eb\u30c8\u3067\u306f\u3001\u30b0\u30ea\u30c3\u30c9\u7dda\u306f\u7070\u8272\u3067\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7dda\u3092\u63cf\u753b\u3057\u3001\u6c34\u5e73\u304a\u3088\u3073\u5782\u76f4\u306e\u30b0\u30ea\u30c3\u30c9\u7dda\u3092\u8ffd\u52a0\u3057\u307e\u3059: pythonCopy codeax.plot([1, 2, 3, 4], [1, 4, 2, 3]) ax.grid() <\/code>\u3053\u308c\u306f\u3001axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7dda\u3092\u63cf\u753b\u3057ax<\/code>\u3001\u6c34\u5e73\u304a\u3088\u3073\u5782\u76f4\u306e\u30b0\u30ea\u30c3\u30c9\u7dda\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                2. \u30b0\u30ea\u30c3\u30c9 \u30e9\u30a4\u30f3\u306e\u30b9\u30bf\u30a4\u30eb\u3068\u8272\u3092\u5909\u66f4\u3059\u308b: Matplotlib \u3067\u306f\u3001grid()<\/code>\u95a2\u6570\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u3001\u30b0\u30ea\u30c3\u30c9 \u30e9\u30a4\u30f3\u306e\u30b9\u30bf\u30a4\u30eb\u3068\u8272\u3092\u5909\u66f4\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7dda\u3092\u63cf\u753b\u3057\u3001\u6c34\u5e73\u304a\u3088\u3073\u5782\u76f4\u30b0\u30ea\u30c3\u30c9 \u30e9\u30a4\u30f3\u306e\u30b9\u30bf\u30a4\u30ebax<\/code>\u3092\u7834\u7dda\u306b\u3001\u8272\u3092\u9ed2\u306b\u8a2d\u5b9a\u3057\u307e\u3059\u3002 grid lines to\u30b0\u30ea\u30c3\u30c9 \u30e9\u30a4\u30f3\u306e\u30b9\u30bf\u30a4\u30eb\u306f Dashed \u306b\u8a2d\u5b9a\u3055\u308c\u3001\u8272\u306f\u9ed2\u306b\u8a2d\u5b9a\u3055\u308c\u307e\u3059\u3002ax.plot([1, 2, 3, 4], [1, 4, 2, 3]) ax.grid(linestyle='--', color='k') <\/code>ax<\/code><\/li>\n\n\n\n
                                3. Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u80cc\u666f\u8272\u3092\u5909\u66f4\u3059\u308b: Matplotlib \u3067\u306f\u3001set_facecolor()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066 Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u80cc\u666f\u8272\u3092\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7dda\u3092\u63cf\u753b\u3057\u3001axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u80cc\u666f\u8272\u3092\u9ec4\u8272\u306b\u8a2d\u5b9a\u3057\u307e\u3059\u3002 pythonCopy codeax.plot([1, 2, 3, 4], [1, 4, 2, 3]) ax.set_facecolor('yellow') <\/code>\u3053\u308c\u306f\u3001ax<\/code>axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u7dda\u3092\u63cf\u753b\u3057\u3001axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u80cc\u666f\u8272\u3092\u9ec4\u8272\u306b\u8a2d\u5b9a\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                                  fig<\/code>Matplotlib \u3067\u306f\u3001\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3060\u3051\u3067\u306a\u304f\u3001Figure \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u3082\u30b0\u30ea\u30c3\u30c9\u7dda\u3068\u80cc\u666f\u8272\u3092\u8a2d\u5b9a\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044ax<\/code>\u3002\u3059\u3079\u3066\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u540c\u3058\u30b0\u30ea\u30c3\u30c9\u7dda\u3068\u80cc\u666f\u8272\u3092\u8a2d\u5b9a\u3059\u308b\u5834\u5408\u306f\u3001fig<\/code>\u30b0\u30e9\u30d5 \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3067\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u7279\u5b9a\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u30b0\u30ea\u30c3\u30c9\u7dda\u3068\u80cc\u666f\u8272\u306e\u307f\u3092\u8a2d\u5b9a\u3059\u308b\u5834\u5408\u306f\u3001ax<\/code>\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                  \"\"\/<\/figure>\n\n\n\n
                                  \"gun<\/figure>\n\n\n\n
                                  \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u4f5c\u6210\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                  Matplotlib \u3067\u306f\u3001subplots()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306f\u30011 \u3064\u306e Figure \u306b\u8907\u6570\u306e Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5\u3067\u3042\u308a\u3001\u305d\u308c\u305e\u308c\u304c\u7570\u306a\u308b\u30c7\u30fc\u30bf\u3092\u30d7\u30ed\u30c3\u30c8\u3067\u304d\u307e\u3059\u3002\u30b5\u30d6\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3059\u308b\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                    \n
                                  1. \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001subplots()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002import matplotlib.pyplot as plt fig, ax = plt.subplots() ax.plot([1, 2, 3, 4], [1, 4, 2, 3]) plt.show()<\/code><\/li>\n\n\n\n
                                  2. \u8907\u6570\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001subplots()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u8907\u6570\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9import matplotlib.pyplot as plt fig, axs = plt.subplots(2) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) plt.show() <\/code>\u3053\u308c\u306f\u3001\u305d\u308c\u305e\u308c\u304c\u7570\u306a\u308b\u30c7\u30fc\u30bf\u3092\u30d7\u30ed\u30c3\u30c8\u3067\u304d\u308b 2 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                  3. \u30ab\u30b9\u30bf\u30e0 \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8 \u30ec\u30a4\u30a2\u30a6\u30c8: Matplotlib \u3067\u306f\u3001subplots()<\/code>\u95a2\u6570\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u30ec\u30a4\u30a2\u30a6\u30c8\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066nrows<\/code>\u30b5\u30d6ncols<\/code>\u30d7\u30ed\u30c3\u30c8\u306e\u884c\u6570\u3068\u5217\u6570\u3092\u6307\u5b9a\u3057\u305f\u308a\u3001gridspec_kw<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u30ec\u30a4\u30a2\u30a6\u30c8\u3092\u6307\u5b9a\u3057\u305f\u308a\u3001figsize<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u30b5\u30a4\u30ba\u3092\u6307\u5b9a\u3057\u305f\u308a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f 2 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002\u6700\u521d\u306e\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306f\u6700\u521d\u306e\u884c\u5168\u4f53\u306b\u307e\u305f\u304c\u308a\u30012 \u3064\u76ee\u306f 2 \u756a\u76ee\u306e\u884c\u5168\u4f53\u306b\u307e\u305f\u304c\u308a\u307e\u3059: pythonCopy \u30b3\u30fc\u30c9 \u3053\u308c\u306b\u3088\u308a\u30012 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u304c\u4f5c\u6210\u3055\u308c\u307e\u3059import matplotlib.pyplot as plt fig, axs = plt.subplots(nrows=2, ncols=1, gridspec_kw={'height_ratios': [2, 1]}, figsize=(6, 6)) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) plt.show() <\/code>\u3002\u306f\u6700\u521d\u306e\u884c\u5168\u4f53\u306b\u307e\u305f\u304c\u308a\u30012 \u756a\u76ee\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306f 2 \u756a\u76ee\u306e\u884c\u5168\u4f53\u306b\u307e\u305f\u304c\u308a\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u30b5\u30a4\u30ba\u306f \u3067\u3059(6, 6)<\/code>\u3002<\/li>\n<\/ol>\n\n\n\n
                                    \u4ee5\u4e0a\u304c\u90e8\u5206\u30b0\u30e9\u30d5\u4f5c\u6210\u306e\u57fa\u672c\u7684\u306a\u65b9\u6cd5\u3067\u3059\u304c\u3001\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u969b\u306b\u306f\u3001\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u4ed6\u306e\u64cd\u4f5c\u3084\u8abf\u6574\u304c\u5fc5\u8981\u306b\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                    \"\"\/<\/figure>\n\n\n\n
                                    \"gun<\/figure>\n\n\n\n
                                    \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u9694\u306e\u8abf\u6574\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                    Matplotlib \u3067\u306f\u3001subplots_adjust()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u9593\u9694\u3092\u8abf\u6574\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u95a2\u6570\u306f\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u5782\u76f4\u65b9\u5411\u3068\u6c34\u5e73\u65b9\u5411\u306e\u9593\u9694\u3092\u5236\u5fa1\u3059\u308b\u3044\u304f\u3064\u304b\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u53d7\u3051\u5165\u308c\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u9593\u9694\u3092\u8abf\u6574\u3059\u308b\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                      \n
                                    1. \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u6c34\u5e73\u65b9\u5411\u306e\u9593\u9694\u3092\u8abf\u6574\u3059\u308b: Matplotlib \u3067\u306f\u3001wspace<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u6c34\u5e73\u65b9\u5411\u306e\u9593\u9694\u3092\u8abf\u6574\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u5024\u306f\u3001\u30b5\u30d6\u30a4\u30e1\u30fc\u30b8\u306e\u5e45\u306e\u6bd4\u7387\u3067\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u5024\u304c \u306e\u5834\u5408\u3001wspace<\/code>\u96a3\u63a50.5<\/code>\u3059\u308b 2 \u3064\u306e\u30b5\u30d6\u30a4\u30e1\u30fc\u30b8\u9593\u306e\u6c34\u5e73\u65b9\u5411\u306e\u30b9\u30da\u30fc\u30b9\u306f\u3001\u305d\u308c\u3089\u306e\u5e45\u306e\u500d\u306b\u306a\u308a\u307e\u30590.5<\/code>\u3002import matplotlib.pyplot as plt fig, axs = plt.subplots(2) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) plt.subplots_adjust(wspace=0.5) plt.show() <\/code>\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u6c34\u5e73\u65b9\u5411\u306e\u9593\u9694\u3092\u8abf\u6574\u3057\u307e\u30590.5<\/code>\u3002<\/li>\n\n\n\n
                                    2. \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u5782\u76f4\u65b9\u5411\u306e\u9593\u9694\u3092\u8abf\u6574\u3059\u308b: Matplotlib \u3067\u306f\u3001hspace<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u5782\u76f4\u65b9\u5411\u306e\u9593\u9694\u3092\u8abf\u6574\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u5024\u306f\u3001\u30b5\u30d6\u30d4\u30af\u30c1\u30e3\u306e\u9ad8\u3055\u306e\u6bd4\u7387\u3067\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u5024\u304c \u306e\u5834\u5408hspace<\/code>\u30010.5<\/code>\u96a3\u63a5\u3059\u308b 2 \u3064\u306e\u30b5\u30d6\u30d4\u30af\u30c1\u30e3\u9593\u306e\u5782\u76f4\u65b9\u5411\u306e\u30b9\u30da\u30fc\u30b9\u306f\u3001\u305d\u308c\u3089\u306e\u9ad8\u3055\u306e\u500d\u306b\u306a\u308a\u307e\u30590.5<\/code>\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u5782\u76f4\u65b9\u5411\u306e\u9593\u9694\u3092\u8abf\u6574\u3057import matplotlib.pyplot as plt fig, axs = plt.subplots(2) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) plt.subplots_adjust(hspace=0.5) plt.show() <\/code>\u307e\u30590.5<\/code>\u3002<\/li>\n<\/ol>\n\n\n\n
                                      subplots_adjust()<\/code>Matplotlib \u3067\u306f\u3001\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u9593\u9694\u3092\u8abf\u6574\u3057\u305f\u308a\u3001tight_layout()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u9593\u9694\u3092\u81ea\u52d5\u7684\u306b\u8abf\u6574\u3057\u305f\u308a\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002tight_layout()<\/code>\u3053\u306e\u95a2\u6570\u306f\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u6700\u5c0f\u9593\u9694\u3092\u81ea\u52d5\u7684\u306b\u8a08\u7b97\u3057\u3066\u3001\u3059\u3079\u3066\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u304c\u30b0\u30e9\u30d5\u306b\u5b8c\u5168\u306b\u8868\u793a\u3055\u308c\u308b\u3088\u3046\u306b\u3057\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u9593\u9694\u3092\u8abf\u6574\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u624b\u9806\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059<\/p>\n\n\n\n
                                      \"\"\/<\/figure>\n\n\n\n
                                      \"gun<\/figure>\n\n\n\n
                                      \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                      \u65b9\u6cd5\u3068\u624b\u9806\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/p>\n\n\n\n
                                        \n
                                      1. \u6c34\u5e73\u65b9\u5411\u3068\u5782\u76f4\u65b9\u5411\u306e\u9593\u9694\u3092\u540c\u6642\u306b\u8abf\u6574\u3059\u308b: Matplotlib \u3067\u306f\u3001wspace<\/code>\u3068hspace<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u4e21\u65b9\u3092\u4f7f\u7528\u3057\u3066\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u6c34\u5e73\u65b9\u5411\u3068\u5782\u76f4\u65b9\u5411\u306e\u9593\u9694\u3092\u8abf\u6574\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012 \u3064\u306e axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306eimport matplotlib.pyplot as plt fig, axs = plt.subplots(2) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) plt.subplots_adjust(wspace=0.5, hspace=0.5) plt.show() <\/code>\u6c34\u5e73\u304a\u3088\u3073\u5782\u76f4\u306e\u9593\u9694\u3092\u8abf\u6574\u3057\u307e\u30590.5<\/code>\u3002<\/li>\n\n\n\n
                                      2. \u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u30ab\u30b9\u30bf\u30e0\u9593\u9694: Matplotlib \u3067\u306f\u3001subplots_adjust()<\/code>\u95a2\u6570\u306b\u8ffd\u52a0\u306e\u5f15\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u9593\u9694\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001left<\/code>\u3001right<\/code>\u3001bottom<\/code>\u304a\u3088\u3073top<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30b0\u30e9\u30d5\u306e\u5883\u754c\u7dda\u306e\u30b5\u30a4\u30ba\u3068\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u4f4d\u7f6e\u3092\u5236\u5fa1\u3057\u305f\u308a\u3001w_pad<\/code>\u304a\u3088\u3073h_pad<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u6c34\u5e73\u304a\u3088\u3073\u5782\u76f4\u306e\u9593\u9694\u3092\u5236\u5fa1\u3057\u305f\u308a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u9593\u9694\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3057\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9import matplotlib.pyplot as plt fig, axs = plt.subplots(2) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) plt.subplots_adjust(left=0.1, right=0.9, bottom=0.1, top=0.9, wspace=0.5, hspace=0.5) plt.show() <\/code>\u3053\u308c\u306f\u30012 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3001\u305d\u308c\u3089\u306e\u9593\u306e\u9593\u9694\u3068\u4f4d\u7f6e\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                                        Matplotlib \u3067\u306f\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u9593\u9694\u3092\u8abf\u6574\u3059\u308b\u5834\u5408\u3001\u7279\u5b9a\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u64cd\u4f5c\u304a\u3088\u3073\u8abf\u6574\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u3001\u3088\u308a\u8907\u96d1\u306a\u8abf\u6574\u3092\u884c\u3046\u305f\u3081\u306b\u3001\u4ed6\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3084\u6a5f\u80fd\u3092\u7d44\u307f\u5408\u308f\u305b\u308b\u5fc5\u8981\u304c\u3042\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306e\u9593\u9694\u3092\u8abf\u6574\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                        \"\"\/<\/figure>\n\n\n\n
                                        \"gun<\/figure>\n\n\n\n
                                        \u5171\u6709\u8ef8\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u6559\u3048\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                        Matplotlib \u3067\u306f\u3001subplots()<\/code>\u95a2\u6570sharex<\/code>\u3068sharey<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u8ef8\u3092\u5171\u6709\u3067\u304d\u307e\u3059\u3002\u8ef8\u3092\u5171\u6709\u3059\u308b\u3068\u3001\u8907\u6570\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u3067\u8ef8\u306e\u4e00\u8cab\u6027\u3092\u4fdd\u3064\u3053\u3068\u304c\u3067\u304d\u3001\u6bd4\u8f03\u3068\u5206\u6790\u304c\u5411\u4e0a\u3057\u307e\u3059\u3002\u8ef8\u3092\u5171\u6709\u3059\u308b\u305f\u3081\u306e\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                          \n
                                        1. \u5171\u6709 x \u8ef8: Matplotlib \u3067\u306f\u3001sharex<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u3067 x \u8ef8\u3092\u5171\u6709\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u306f\u3001\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u5024\u3068\u3057\u3066\u53d7\u3051\u5165\u308c\u3066\u3001\u3069\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e x \u8ef8\u3092\u5171\u6709\u3059\u308b\u304b\u3092\u6307\u5b9a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001x \u8ef8\u3092\u5171\u6709\u3059\u308b 2 \u3064\u306eaxes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059import matplotlib.pyplot as plt fig, axs = plt.subplots(2, sharex=True) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) plt.show() <\/code>\u3002<\/li>\n\n\n\n
                                        2. \u5171\u6709 y \u8ef8: Matplotlib \u3067\u306f\u3001sharey<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u3067 y \u8ef8\u3092\u5171\u6709\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u306f\u3001\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u5024\u3068\u3057\u3066\u53d7\u3051\u5165\u308c\u3066\u3001\u3069\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e y \u8ef8\u3092\u5171\u6709\u3059\u308b\u304b\u3092\u6307\u5b9a\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001y \u8ef8\u3092\u5171\u6709\u3059\u308b 2 \u3064\u306eaxes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059import matplotlib.pyplot as plt fig, axs = plt.subplots(2, sharey=True) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) plt.show() <\/code>\u3002<\/li>\n\n\n\n
                                        3. x \u8ef8\u3068 y \u8ef8\u3092\u540c\u6642\u306b\u5171\u6709\u3059\u308b: Matplotlib \u3067\u306f\u3001sharex<\/code>\u3068sharey<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u4e21\u65b9\u3092\u4f7f\u7528\u3057\u3066\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u3067 x \u8ef8\u3068 y \u8ef8\u3092\u5171\u6709\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3001\u305d\u308c\u3089\u306e\u9593\u3067 x \u8ef8\u3068 y \u8ef8\u3092\u5171\u6709\u3057\u307e\u3059import matplotlib.pyplot as plt fig, axs = plt.subplots(2, sharex=True, sharey=True) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) plt.show() <\/code>\u3002<\/li>\n<\/ol>\n\n\n\n
                                          \u8ef8\u3092\u5171\u6709\u3059\u308b\u5834\u5408\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u30c7\u30fc\u30bf\u7bc4\u56f2\u306f\u6b21\u306e\u3088\u3046\u306b\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n
                                          \"\"\/<\/figure>\n\n\n\n
                                          \"gun<\/figure>\n\n\n\n
                                          \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                          \u3088\u308a\u826f\u3044\u6bd4\u8f03\u3068\u5206\u6790\u306e\u305f\u3081\u306b\u3001\u53ef\u80fd\u306a\u9650\u308a\u540c\u3058\u306b\u3057\u307e\u3059\u3002\u516c\u5f0f\u306e Matplotlib \u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u3001\u8ef8\u3092\u5171\u6709\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3055\u3089\u306b\u3001subplots()<\/code>\u95a2\u6570\u306esharex<\/code>\u304a\u3088\u3073sharey<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066\u5ea7\u6a19\u8ef8\u3092\u5171\u6709\u3059\u308b\u3053\u3068\u306b\u52a0\u3048\u3066\u3001Matplotlib \u306f\u3001 \u3001 \u3001 \u306a\u3069\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u9593\u306e\u5ea7\u6a19\u8ef8\u3092\u3088\u308a\u67d4\u8edf\u304b\u3064\u304d\u3081\u7d30\u304b\u304f\u5236\u5fa1\u3059\u308b\u305f\u3081\u306e\u4ed6\u306e\u95a2\u6570\u3068\u30e1\u30bd\u30c3\u30c9\u3082\u63d0\u4f9bAxesGrid<\/code>\u3057make_axes_locatable()<\/code>\u307e\u3059GridSpec<\/code>\u3002\u5b9f\u969b\u306e\u4f7f\u7528\u3067\u306f\u3001\u7279\u5b9a\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u3055\u307e\u3056\u307e\u306a\u65b9\u6cd5\u3068\u30c4\u30fc\u30eb\u3092\u9078\u629e\u3057\u3066\u3001\u5171\u6709\u5ea7\u6a19\u8ef8\u3084\u305d\u306e\u4ed6\u306e\u8981\u4ef6\u3092\u5b9f\u73fe\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                          \"\"\/<\/figure>\n\n\n\n
                                          \"gun<\/figure>\n\n\n\n
                                          \u30b5\u30d6\u30d5\u30a3\u30ae\u30e5\u30a2\u306e\u30bf\u30a4\u30c8\u30eb\u306e\u8ffd\u52a0\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                          Matplotlib \u3067\u306f\u3001set_title()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306b\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30e1\u30bd\u30c3\u30c9\u306f\u3001\u30bf\u30a4\u30c8\u30eb\u306e\u30c6\u30ad\u30b9\u30c8 \u30b3\u30f3\u30c6\u30f3\u30c4\u3068\u3057\u3066\u6587\u5b57\u5217\u3092\u53d7\u3051\u5165\u308c\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3053\u308c\u306f\u3001\u30b5\u30d6\u30b0\u30e9\u30d5\u306b\u3088\u3063\u3066\u8868\u3055\u308c\u308b\u30c7\u30fc\u30bf\u307e\u305f\u306f\u60c5\u5831\u3092\u8aac\u660e\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002\u30b5\u30d6\u30d5\u30a3\u30ae\u30e5\u30a2\u306e\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                            \n
                                          1. \u500b\u3005\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3078\u306e\u30bf\u30a4\u30c8\u30eb\u306e\u8ffd\u52a0: Matplotlib \u3067\u306f\u3001set_title()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u500b\u3005\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306b\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9import matplotlib.pyplot as plt fig, ax = plt.subplots() ax.plot([1, 2, 3, 4], [1, 4, 2, 3]) ax.set_title('Line Plot') plt.show() <\/code>\u3053\u308c\u306f\u3001Axes \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3001\u305d\u308c\u306b\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                          2. \u8907\u6570\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3078\u306e\u30bf\u30a4\u30c8\u30eb\u306e\u8ffd\u52a0: Matplotlib \u3067\u306f\u3001set_title()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u8907\u6570\u306e\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306b\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u306b\u500b\u5225\u306e\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9import matplotlib.pyplot as plt fig, axs = plt.subplots(2) axs[0].plot([1, 2, 3, 4], [1, 4, 2, 3]) axs[0].set_title('Line Plot 1') axs[1].plot([1, 2, 3, 4], [4, 2, 3, 1]) axs[1].set_title('Line Plot 2') plt.show() <\/code>\u3053\u308c\u306f\u30012 \u3064\u306e\u8ef8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u542b\u3080\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3001\u305d\u308c\u3089\u306b\u500b\u5225\u306e\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                                            Matplotlib \u3067\u306f\u3001\u30b5\u30d6\u30b0\u30e9\u30d5 \u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3059\u308b\u5834\u5408\u3001\u7279\u5b9a\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u64cd\u4f5c\u304a\u3088\u3073\u8abf\u6574\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u30b5\u30d6\u30b0\u30e9\u30d5\u304c\u591a\u3059\u304e\u308b\u5834\u5408\u306f\u3001GridSpec<\/code>\u3001subplots_adjust()<\/code>\u3001 \u306a\u3069\u306e\u4ed6\u306e\u30ec\u30a4\u30a2\u30a6\u30c8 \u30c4\u30fc\u30eb\u3084\u6a5f\u80fd\u3092\u4f7f\u7528\u3057\u3066\u3001tight_layout()<\/code>\u30b5\u30d6\u30b0\u30e9\u30d5\u306e\u30ec\u30a4\u30a2\u30a6\u30c8\u3068\u8868\u793a\u52b9\u679c\u3092\u6700\u9069\u5316\u3059\u308b\u3053\u3068\u3092\u691c\u8a0e\u3067\u304d\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u30b5\u30d6\u30d7\u30ed\u30c3\u30c8 \u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3059\u308b\u305f\u3081\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                            \"\"\/<\/figure>\n\n\n\n
                                            \"gun<\/figure>\n\n\n\n
                                            3D\u6563\u5e03\u56f3\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                            3D \u6563\u5e03\u56f3\u306f\u3001\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u3092 3 \u6b21\u5143\u3067\u8868\u793a\u3059\u308b\u30d3\u30b8\u30e5\u30a2\u30e9\u30a4\u30bc\u30fc\u30b7\u30e7\u30f3\u3067\u3059\u3002\u3053\u308c\u306f\u3001\u5404\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u304c 3 \u3064\u306e\u5024\u3067\u69cb\u6210\u3055\u308c\u308b 3 \u3064\u306e\u5909\u6570\u9593\u306e\u95a2\u4fc2\u3092\u793a\u3059\u305f\u3081\u306b\u3088\u304f\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002Matplotlib \u3067\u306f\u3001mplot3d<\/code>\u30c4\u30fc\u30eb\u30ad\u30c3\u30c8Axes3D<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f7f\u7528\u3057\u3066 3D \u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u30023D \u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306e\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                              \n
                                            1. mplot3d<\/code>\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b: Matplotlib \u3067\u306f\u30013D \u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306b\u3001\u30c4\u30fc\u30eb\u30ad\u30c3\u30c8Axes3D<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3068\u305d\u306e\u4ed6\u306e\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import numpy as np<\/code><\/li>\n\n\n\n
                                            2. \u30c7\u30fc\u30bf\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u6563\u5e03\u56f3\u306e\u4f4d\u7f6e\u3068\u30b5\u30a4\u30ba\u3092\u8868\u3059\u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30e9\u30f3\u30c0\u30e0\u306a 3D \u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002np.random.seed(123) x = np.random.normal(size=500) y = np.random.normal(size=500) z = np.random.normal(size=500)<\/code><\/li>\n\n\n\n
                                            3. 3D \u6563\u5e03\u56f3\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001scatter()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066 3D \u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30e1\u30bd\u30c3\u30c9\u306f\u3001\u5404\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u306e x\u3001y\u3001z \u5ea7\u6a19\u3092\u6307\u5b9a\u3059\u308b\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3068\u3057\u3066 3 \u3064\u306e\u914d\u5217\u3092\u53d7\u3051\u53d6\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f 3D \u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3057\u3001\u30e9\u30f3\u30c0\u30e0\u306b\u751f\u6210\u3055\u308c\u305f\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u3092\u8868\u793a\u3057\u307e\u3059fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.scatter(x, y, z) ax.set_xlabel('X Label') ax.set_ylabel('Y Label') ax.set_zlabel('Z Label') plt.show() <\/code>\u3002<\/li>\n\n\n\n
                                            4. 3D \u6563\u5e03\u56f3\u306e\u30ab\u30b9\u30bf\u30de\u30a4\u30ba: Matplotlib \u3067\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u30e1\u30bd\u30c3\u30c9\u3068\u30d7\u30ed\u30d1\u30c6\u30a3\u3092\u4f7f\u7528\u3057\u3066\u3001\u6563\u5e03\u70b9\u306e\u30b5\u30a4\u30ba\u3001\u8272\u3001\u900f\u660e\u5ea6\u306e\u8abf\u6574\u3001\u8ef8\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30eb\u306e\u8ffd\u52a0\u306a\u3069\u30013D \u6563\u5e03\u56f3\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f 3D \u6563\u5e03\u56f3\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3057\u3001\u6563\u5e03\u56f3\u306e\u30b5\u30a4\u30ba\u3001\u8272\u3001\u900f\u660e\u5ea6\u3092\u30e9\u30f3\u30c0\u30e0\u306a\u5024\u306b\u8abf\u6574\u3057\u307e\u3059fig = plt.figure() ax = fig.add_subplot(111, projection='3d') c = np.random.randint(0, 10, size=500) s = np.random.randint(100, 1000, size=500) alpha = np.random.uniform(0.5, 1, size=500) ax.scatter(x, y, z, c=c, s=s, alpha=alpha) ax.set_xlabel('X Label') ax.set_ylabel('Y Label') ax.set_zlabel('Z Label') ax.set_title('3D Scatter Plot') plt.show() <\/code>\u3002<\/li>\n<\/ol>\n\n\n\n
                                              \"\"\/<\/figure>\n\n\n\n
                                              \"gun<\/figure>\n\n\n\n
                                              \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                              \u30b5\u30a4\u30ba\u3001\u8272\u3001\u900f\u660e\u5ea6\u304c\u30e9\u30f3\u30c0\u30e0\u306a\u5024\u306b\u8abf\u6574\u3055\u308c\u3001x\u3001y\u3001z \u8ef8\u306e\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30eb\u304c\u8ffd\u52a0\u3055\u308c\u305f\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u306e 3D \u6563\u5e03\u56f3\u3002<\/p>\n\n\n\n
                                              Matplotlib \u3067 3D \u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3059\u308b\u306b\u306f\u3001\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u306e\u4f4d\u7f6e\u3068\u30b5\u30a4\u30ba\u3001\u304a\u3088\u3073\u30c7\u30fc\u30bf\u306e\u5f62\u5f0f\u3068\u7a2e\u985e\u3092\u3042\u308b\u7a0b\u5ea6\u628a\u63e1\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u3055\u3089\u306b\u3001Matplotlib \u306f\u30013D \u6298\u308c\u7dda\u30b0\u30e9\u30d5\u30013D \u7b49\u9ad8\u7dda\u30b0\u30e9\u30d5\u30013D \u68d2\u30b0\u30e9\u30d5\u306a\u3069\u3001\u4ed6\u306e\u7a2e\u985e\u306e 3D \u30b0\u30e9\u30d5\u3082\u63d0\u4f9b\u3057\u307e\u3059\u3002\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u3092\u9078\u629e\u3057\u3066\u3001\u7279\u5b9a\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u30c7\u30fc\u30bf\u3092\u8868\u793a\u304a\u3088\u3073\u5206\u6790\u3067\u304d\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u30013D \u30c1\u30e3\u30fc\u30c8\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                              \"\"\/<\/figure>\n\n\n\n
                                              \"gun<\/figure>\n\n\n\n
                                              3D\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                              3D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306f\u3001\u30c7\u30fc\u30bf\u3092 3 \u6b21\u5143\u3067\u8868\u793a\u3059\u308b\u30d3\u30b8\u30e5\u30a2\u30eb \u30c1\u30e3\u30fc\u30c8\u3067\u3059\u3002\u5404\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u304c 3 \u3064\u306e\u5024\u3067\u69cb\u6210\u3055\u308c\u308b 3 \u3064\u306e\u5909\u6570\u9593\u306e\u95a2\u4fc2\u3092\u793a\u3059\u305f\u3081\u306b\u3088\u304f\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002Matplotlib \u3067\u306f\u3001mplot3d<\/code>\u30c4\u30fc\u30eb\u30ad\u30c3\u30c8Axes3D<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f7f\u7528\u3057\u3066 3D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u30023D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                                \n
                                              1. mplot3d<\/code>\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b: Matplotlib \u3067\u306f\u30013D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306b\u3001\u30c4\u30fc\u30eb\u30ad\u30c3\u30c8Axes3D<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3068\u305d\u306e\u4ed6\u306e\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import numpy as np<\/code><\/li>\n\n\n\n
                                              2. \u30c7\u30fc\u30bf\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001\u63cf\u753b\u3059\u308b\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u4f4d\u7f6e\u3001\u9ad8\u3055\u3001\u5e45\u3092\u8868\u3059\u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30e9\u30f3\u30c0\u30e0\u306a 3D \u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002np.random.seed(123) x = np.random.randint(1, 10, size=10) y = np.random.randint(1, 10, size=10) z = np.random.randint(1, 10, size=10)<\/code><\/li>\n\n\n\n
                                              3. 3D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001bar3d()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066 3D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30e1\u30bd\u30c3\u30c9\u306f\u3001\u5404\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e x\u200b\u200b\u3001y\u3001z \u5ea7\u6a19\u3001\u9ad8\u3055\u3001\u304a\u3088\u3073\u5e45\u3092\u6307\u5b9a\u3059\u308b\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3068\u3057\u3066 6 \u3064\u306e\u914d\u5217\u3092\u53d7\u3051\u5165\u308c\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f 3D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u4f5c\u6210\u3057\u3001\u30e9\u30f3\u30c0\u30e0\u306b\u751f\u6210\u3055\u308c\u305f\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u3092\u8868\u793a\u3057\u307e\u3059fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.bar3d(x, y, np.zeros(len(z)), 0.5, 0.5, z) ax.set_xlabel('X Label') ax.set_ylabel('Y Label') ax.set_zlabel('Z Label') plt.show() <\/code>\u3002<\/li>\n\n\n\n
                                              4. 3D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u30ab\u30b9\u30bf\u30de\u30a4\u30ba: Matplotlib \u3067\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u30e1\u30bd\u30c3\u30c9\u3068\u30d7\u30ed\u30d1\u30c6\u30a3\u3092\u4f7f\u7528\u3057\u3066\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u8272\u3001\u900f\u660e\u5ea6\u3001\u5f71\u306e\u8abf\u6574\u3001\u8ef8\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30eb\u306e\u8ffd\u52a0\u306a\u3069\u30013D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f 3D \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3057\u3001\u305d\u306e\u8272\u3068\u900f\u660e\u5ea6\u3092\u30e9\u30f3\u30c0\u30e0\u306a\u5024\u306b\u8abf\u6574\u3057\u307e\u3059\u3002fig = plt.figure() ax = fig.add_subplot(111, projection='3d') c = np.random.randint(0, 10, size=10) alpha = np.random.uniform(0.5, 1, size=10) ax.bar3d(x, y, np.zeros(len(z)), 0.5, 0.5, z, color=c<\/code><\/li>\n<\/ol>\n\n\n\n
                                                \"\"\/<\/figure>\n\n\n\n
                                                \"gun<\/figure>\n\n\n\n
                                                3D \u30b5\u30fc\u30d5\u30a7\u30b9 \u30d7\u30ed\u30c3\u30c8\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                3D \u7b49\u9ad8\u7dda\u30b0\u30e9\u30d5\u306f\u3001\u30c7\u30fc\u30bf\u3092 3 \u6b21\u5143\u3067\u8868\u793a\u3059\u308b\u8996\u899a\u7684\u306a\u30b0\u30e9\u30d5\u3067\u3059\u3002\u5404\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u304c 3 \u3064\u306e\u5024\u3067\u69cb\u6210\u3055\u308c\u308b 3 \u3064\u306e\u5909\u6570\u9593\u306e\u95a2\u4fc2\u3092\u793a\u3059\u305f\u3081\u306b\u3088\u304f\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002Matplotlib \u3067\u306f\u3001mplot3d<\/code>\u30c4\u30fc\u30eb\u30ad\u30c3\u30c8Axes3D<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f7f\u7528\u3057\u3066 3D \u8868\u9762\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u30023D \u30b5\u30fc\u30d5\u30a7\u30b9 \u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                                  \n
                                                1. mplot3d<\/code>\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b: Matplotlib \u3067\u306f\u30013D \u30b5\u30fc\u30d5\u30a7\u30b9 \u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306b\u3001\u30c4\u30fc\u30eb\u30ad\u30c3\u30c8Axes3D<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3068\u305d\u306e\u4ed6\u306e\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import numpy as np<\/code><\/li>\n\n\n\n
                                                2. \u30c7\u30fc\u30bf\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u9762\u306e\u4f4d\u7f6e\u3068\u9ad8\u3055\u3092\u8868\u3059\u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30e9\u30f3\u30c0\u30e0\u306a 3D \u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002np.random.seed(123) x = np.linspace(-5, 5, 100) y = np.linspace(-5, 5, 100) X, Y = np.meshgrid(x, y) Z = np.sin(np.sqrt(X ** 2 + Y ** 2))<\/code><\/li>\n\n\n\n
                                                3. 3D \u8868\u9762\u30d7\u30ed\u30c3\u30c8\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001plot_surface()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066 3D \u8868\u9762\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30e1\u30bd\u30c3\u30c9\u306f\u3001\u5404\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u306e x\u3001y\u3001z \u5ea7\u6a19\u3092\u6307\u5b9a\u3059\u308b\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3068\u3057\u3066 3 \u3064\u306e\u914d\u5217\u3092\u53d7\u3051\u53d6\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f 3D \u30b5\u30fc\u30d5\u30a7\u30b9 \u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3001\u30e9\u30f3\u30c0\u30e0\u306b\u751f\u6210\u3055\u308c\u305f\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u3092\u8868\u793a\u3057\u307e\u3059fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.plot_surface(X, Y, Z) ax.set_xlabel('X Label') ax.set_ylabel('Y Label') ax.set_zlabel('Z Label') plt.show() <\/code>\u3002<\/li>\n\n\n\n
                                                4. 3D \u66f2\u9762\u30b0\u30e9\u30d5\u306e\u30ab\u30b9\u30bf\u30de\u30a4\u30ba: Matplotlib \u3067\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u30e1\u30bd\u30c3\u30c9\u3068\u30d7\u30ed\u30d1\u30c6\u30a3\u3092\u4f7f\u7528\u3057\u3066\u3001\u66f2\u9762\u30b0\u30e9\u30d5\u306e\u8272\u3001\u900f\u660e\u5ea6\u3001\u5f71\u306e\u8abf\u6574\u3001\u8ef8\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30eb\u306e\u8ffd\u52a0\u306a\u3069\u30013D \u66f2\u9762\u30b0\u30e9\u30d5\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f 3D \u30b5\u30fc\u30d5\u30a7\u30b9 \u30d7\u30ed\u30c3\u30c8\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3057\u3001\u305d\u306e\u8272\u3068\u900f\u660e\u5ea6\u3092\u30e9\u30f3\u30c0\u30e0\u306a\u5024\u306b\u8abf\u6574\u3057\u307e\u3059fig = plt.figure() ax = fig.add_subplot(111, projection='3d') c = np.random.randint(0, 10, size=10000) alpha = np.random.uniform(0.5, 1, size=10000) ax.plot_surface(X, Y, Z, color=c, alpha=alpha) ax.set_xlabel('X Label') ax.set_ylabel('Y Label') ax.set_zlabel('Z Label') ax.set_title('3D Surface Plot') plt.show() <\/code>\u3002<\/li>\n<\/ol>\n\n\n\n
                                                  \"\"\/<\/figure>\n\n\n\n
                                                  \"gun<\/figure>\n\n\n\n
                                                  \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                  \u30e9\u30f3\u30c0\u30e0\u306b\u751f\u6210\u3055\u308c\u305f\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u3067 3D \u30b5\u30fc\u30d5\u30a7\u30b9 \u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3001\u305d\u308c\u3089\u306e\u8272\u3068\u900f\u660e\u5ea6\u3092\u30e9\u30f3\u30c0\u30e0\u306a\u5024\u306b\u8abf\u6574\u3057\u3001x\u3001y\u3001z \u8ef8\u306e\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                                  Matplotlib \u3067 3D \u66f2\u9762\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3059\u308b\u306b\u306f\u3001\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u306e\u4f4d\u7f6e\u3068\u30b5\u30a4\u30ba\u3001\u304a\u3088\u3073\u30c7\u30fc\u30bf\u306e\u5f62\u5f0f\u3068\u7a2e\u985e\u3092\u3042\u308b\u7a0b\u5ea6\u628a\u63e1\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002In addition, Matplotlib also provides other types of 3D charts, such as 3D scatter plots, 3D histograms, and 3D bar charts. \u3055\u307e\u3056\u307e\u306a\u30c1\u30e3\u30fc\u30c8 \u30bf\u30a4\u30d7\u3092\u9078\u629e\u3057\u3066\u3001\u7279\u5b9a\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u30c7\u30fc\u30bf\u3092\u8868\u793a\u304a\u3088\u3073\u5206\u6790\u3067\u304d\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u30013D \u30c1\u30e3\u30fc\u30c8\u306e\u3088\u308a\u8a73\u7d30\u306a\u30ac\u30a4\u30c9\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                                  \"\"\/<\/figure>\n\n\n\n
                                                  \"gun<\/figure>\n\n\n\n
                                                  \u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u306e\u4f5c\u308a\u65b9\u3092\u8a73\u3057\u304f\u6559\u3048\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                  Matplotlib \u3067\u306f\u3001FuncAnimation<\/code>1 \u3064\u4ee5\u4e0a\u306e\u95a2\u6570\u3068\u305d\u306e\u4ed6\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u5165\u529b\u3068\u3057\u3066\u53d6\u308a\u3001\u6307\u5b9a\u3055\u308c\u305f\u6642\u9593\u7bc4\u56f2\u306b\u308f\u305f\u3063\u3066\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u751f\u6210\u3059\u308b\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306e\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                                    \n
                                                  1. animation<\/code>\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b: Matplotlib \u3067\u306f\u3001\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306b\u3001\u30e2\u30b8\u30e5\u30fc\u30eb\u3001\u30e2\u30b8\u30e5\u30fc\u30eb\u3001\u304a\u3088\u3073\u305d\u306e\u4ed6\u306e\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059pyplot<\/code>\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation import numpy as np<\/code><\/li>\n\n\n\n
                                                  2. \u30c7\u30fc\u30bf\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3067\u63cf\u753b\u3055\u308c\u308b\u30b0\u30e9\u30d5\u3092\u8868\u3059\u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30e9\u30f3\u30c0\u30e0 \u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002np.random.seed(123) x = np.linspace(0, 2 * np.pi, 100) y = np.sin(x)<\/code><\/li>\n\n\n\n
                                                  3. \u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u95a2\u6570\u3092\u4f5c\u6210\u3059\u308b: Matplotlib \u3067\u306f\u3001\u6642\u9593\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3068\u305d\u306e\u4ed6\u306e\u5fc5\u8981\u306a\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u53d7\u3051\u53d6\u308a\u3001\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3067\u63cf\u753b\u3055\u308c\u308b\u56f3\u3092\u8fd4\u3059\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u95a2\u6570\u3092\u4f5c\u6210\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u5404\u30bf\u30a4\u30e0 \u30b9\u30c6\u30c3\u30d7\u3067\u30e9\u30f3\u30c0\u30e0\u306a\u5024\u3092 y \u5024\u306b\u8ffd\u52a0\u3057\u3001\u65b0\u3057\u3044\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u95a2\u6570\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002def update(frame): y = np.sin(x) + np.random.normal(0, 0.1, size=len(x)) line.set_ydata(y) return line,<\/code><\/li>\n\n\n\n
                                                  4. \u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u306e\u4f5c\u6210: Matplotlib \u3067\u306f\u3001FuncAnimation<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u95a2\u6570\u306f\u3001\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3001\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u95a2\u6570\u3001\u6642\u9593\u7bc4\u56f2\u3001\u6642\u9593\u30b9\u30c6\u30c3\u30d7\u3001\u304a\u3088\u3073\u305d\u306e\u4ed6\u306e\u5fc5\u8981\u306a\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u542b\u3080\u8907\u6570\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u53d7\u3051\u5165\u308c\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4f5c\u6210\u3057\u3001 function FuncAnimation<\/code>:\u4f7f\u7528\u3057\u3066\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u95a2\u6570\u306b\u63a5\u7d9a\u3057\u307e\u3059\u3002fig, ax = plt.subplots() line, = ax.plot(x, y) ani = FuncAnimation(fig, update, frames=np.linspace(0, 2*np.pi, 100), interval=50) plt.show()<\/code><\/li>\n\n\n\n
                                                  5. \u30ab\u30b9\u30bf\u30e0 \u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3: Matplotlib \u3067\u306f\u3001\u30b0\u30e9\u30d5\u306e\u8272\u3001\u7dda\u306e\u7a2e\u985e\u3001\u30e9\u30d9\u30eb\u306e\u8abf\u6574\u3001\u8ef8\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30eb\u306e\u8ffd\u52a0\u3001\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u306e\u901f\u5ea6\u3068\u30eb\u30fc\u30d7\u306e\u8abf\u6574\u306a\u3069\u3001\u3055\u307e\u3056\u307e\u306a\u30e1\u30bd\u30c3\u30c9\u3068\u30d7\u30ed\u30d1\u30c6\u30a3\u3092\u4f7f\u7528\u3057\u3066\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3057\u3001\u7dda\u306e\u8272\u3068\u30e9\u30d9\u30eb\u3092\u30e9\u30f3\u30c0\u30e0\u306a\u5024\u306b\u8abf\u6574\u3057\u307e\u3059\u3002fig, ax = plt.subplots() line, = ax.plot(x, y, color='blue', label='sin(x)') def update(frame): y = np.sin(x + frame \/ 10.0) + np.random.normal(0, 0.1, size=len(x)) line.set_ydata(y) line.set_color(np.random.rand(3)) line.set_label('sin(x+t)') return line, ani = FuncAnimation(fig, update,<\/code><\/li>\n<\/ol>\n\n\n\n
                                                    \"\"\/<\/figure>\n\n\n\n
                                                    \"gun<\/figure>\n\n\n\n
                                                    \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                    \u30d5\u30ec\u30fc\u30e0=np.linspace(0, 2*np.pi, 100), \u9593\u9694=50)<\/p>\n\n\n\n
                                                    ax.set_xlabel(‘X \u30e9\u30d9\u30eb’) ax.set_ylabel(‘Y \u30e9\u30d9\u30eb’) ax.set_title(‘\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3 \u30c7\u30e2’) ax.legend()<\/p>\n\n\n\n
                                                    plt.show()<\/p>\n\n\n\n
                                                    \u30b3\u30fc\u30c9\u3092\u30b3\u30d4\u30fc\n\u8fd9\u5c06\u521b\u5efa\u4e00\u4e2a\u81ea\u5b9a\u4e49\u7684\u52a8\u753b\uff0c\u8be5\u52a8\u753b\u5c06\u5728\u6bcf\u4e2a\u65f6\u95f4\u6b65\u957f\u4e2d\u5411y\u503c\u4e2d\u6dfb\u52a0\u4e00\u4e2a\u968f\u673a\u503c\uff0c\u5e76\u5c06\u7ebf\u6761\u989c\u8272\u548c\u6807\u7b7e\u8c03\u6574\u4e3a\u968f\u673a\u503c\uff0c\u5e76\u6dfb\u52a0\u4e86x\u3001y\u3001\u6807\u9898\u548c\u6807\u7b7e\u3002\n\n\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u5728Matplotlib\u4e2d\uff0c\u521b\u5efa\u52a8\u753b\u9700\u8981\u5bf9\u6570\u636e\u70b9\u7684\u4f4d\u7f6e\u548c\u5927\u5c0f\u6709\u4e00\u5b9a\u7684\u4e86\u89e3\uff0c\u5e76\u5bf9\u6570\u636e\u7684\u683c\u5f0f\u548c\u7c7b\u578b\u6709\u4e00\u5b9a\u7684\u638c\u63e1\u3002\u53e6\u5916\uff0cMatplotlib\u8fd8\u63d0\u4f9b\u4e86\u5176\u4ed6\u7c7b\u578b\u7684\u52a8\u753b\uff0c\u4f8b\u5982\u4f7f\u7528blit\u52a0\u901f\u52a8\u753b\uff0c\u6216\u8005\u5728\u56fe\u5f62\u4e2d\u6dfb\u52a0\u6ed1\u5757\u63a7\u5236\u52a8\u753b\u7684\u65f6\u95f4\u7b49\u7b49\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u60c5\u51b5\u9009\u62e9\u4e0d\u540c\u7684\u52a8\u753b\u7c7b\u578b\u6765\u5c55\u793a\u548c\u5206\u6790\u6570\u636e\u3002\u5728Matplotlib\u7684\u5b98\u65b9\u6587\u6863\u4e2d\uff0c\u4f60\u53ef\u4ee5\u627e\u5230\u66f4\u8be6\u7ec6\u7684\u52a8\u753b\u6307\u5357\u3002\n<\/code><\/pre>\n\n\n\n
                                                    \"\"\/<\/figure>\n\n\n\n
                                                    \"gun<\/figure>\n\n\n\n
                                                    \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u306e\u66f4\u65b0\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                    Matplotlib \u3067\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u30e1\u30bd\u30c3\u30c9\u3068\u30d7\u30ed\u30d1\u30c6\u30a3\u3092\u4f7f\u7528\u3057\u3066\u3001\u66f4\u65b0\u66f2\u7dda\u3001\u6563\u5e03\u56f3\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3001\u5186\u30b0\u30e9\u30d5\u3001\u30b0\u30e9\u30d5\u306a\u3069\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u66f4\u65b0\u3067\u304d\u307e\u3059\u3002\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u66f4\u65b0\u3059\u308b\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                                      \n
                                                    1. \u66f2\u7dda\u306e\u66f4\u65b0: Matplotlib \u3067\u306f\u3001set_data()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u66f2\u7dda\u306e x \u304a\u3088\u3073 y \u30c7\u30fc\u30bf\u3092\u66f4\u65b0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u65e2\u5b58\u306e\u66f2\u7dda\u3092\u66f4\u65b0\u3057\u3001\u305d\u306e y \u5024\u3092 2 \u500d\u306b\u3057\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9x = np.linspace(0, 2*np.pi, 100) y = np.sin(x) fig, ax = plt.subplots() line, = ax.plot(x, y) y_new = 2 * y line.set_data(x, y_new) plt.show() <\/code>\u3053\u308c\u306f\u6b63\u5f26\u6ce2\u3092\u4f5c\u6210\u3057\u3001\u305d\u306e y \u5024\u3092 2 \u500d\u306b\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                    2. set_offsets()<\/code>\u6563\u5e03\u56f3\u306e\u66f4\u65b0: Matplotlib \u3067\u306f\u3001\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u6563\u5e03\u56f3\u306e x \u304a\u3088\u3073 y \u30c7\u30fc\u30bf\u3092\u66f4\u65b0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u65e2\u5b58\u306e\u6563\u5e03\u56f3\u3092\u66f4\u65b0\u3057\u3001\u305d\u306e x \u3068 y \u306e\u5024\u3092 2 \u500d\u306b\u3057x = np.random.rand(100) y = np.random.rand(100) fig, ax = plt.subplots() scat = ax.scatter(x, y) x_new = 2 * x y_new = 2 * y scat.set_offsets(np.c_[x_new, y_new]) plt.show() <\/code>\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9 \u3053\u308c\u306f\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3057\u3001\u305d\u306e x \u3068 y \u306e\u5024\u3092 2 \u500d\u306b\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                    3. \u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u66f4\u65b0: Matplotlib \u3067\u306f\u3001set_height()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u9ad8\u3055\u30c7\u30fc\u30bf\u3092\u66f4\u65b0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u65e2\u5b58\u306e\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u66f4\u65b0\u3057\u3001\u305d\u306e\u9ad8\u3055\u306e\u5024\u3092 2 \u500d\u306b\u3057x = ['A', 'B', 'C', 'D'] y = [1, 2, 3, 4] fig, ax = plt.subplots() bars = ax.bar(x, y) y_new = [2 * i for i in y] for bar, height in zip(bars, y_new): bar.set_height(height) plt.show() <\/code>\u307e\u3059\u3002 pythonCopy code \u3053\u308c\u306f\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u4f5c\u6210\u3057\u3001\u305d\u306e\u9ad8\u3055\u306e\u5024\u3092 2 \u500d\u306b\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                    4. \u5186\u30b0\u30e9\u30d5\u306e\u66f4\u65b0: Matplotlib \u3067\u306f\u3001set_sizes()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u5186\u30b0\u30e9\u30d5\u306e\u30b5\u30a4\u30ba \u30c7\u30fc\u30bf\u3092\u66f4\u65b0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u65e2\u5b58\u306e\u5186\u30b0\u30e9\u30d5\u3092\u66f4\u65b0\u3057\u3001\u305d\u306e\u30b5\u30a4\u30ba\u306e\u5024\u3092 2 \u500d\u306b\u3057sizes = [15, 30, 45, 10] fig, ax = plt.subplots() wedges, labels, _ = ax.pie(sizes) sizes_new = [2 * size for size in sizes] for wedge, size in zip(wedges, sizes_new): wedge.set_sizes([size]) plt.show() <\/code>\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9 \u3053\u308c\u306f\u5186\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3057\u3001\u305d\u306e\u30b5\u30a4\u30ba\u306e\u5024\u3092 2 \u500d\u306b\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                    5. \u30c1\u30e3\u30fc\u30c8\u306e\u66f4\u65b0: Matplotlib \u3067\u306f\u3001set_data()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30c1\u30e3\u30fc\u30c8\u306e\u30c7\u30fc\u30bf\u3092\u66f4\u65b0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u65e2\u5b58\u306e\u30c1\u30e3\u30fc\u30c8\u3092\u66f4\u65b0\u3057\u3001x \u3068 y \u306e\u5024\u3092 2 \u500d\u306b\u3057\u307e\u3059\u3002x = np.linspace(0, 2*np.pi, 100) y = np.sin(x) fig, ax =<\/code><\/li>\n<\/ol>\n\n\n\n
                                                      \"\"\/<\/figure>\n\n\n\n
                                                      \"gun<\/figure>\n\n\n\n
                                                      \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                      plt.subplots() ax.plot(x, y)<\/p>\n\n\n\n
                                                      x_new = 2 * x y_new = 2 * y ax.lines[0].set_data(x_new, y_new)<\/p>\n\n\n\n
                                                      plt.show()<\/p>\n\n\n\n
                                                      \u30b3\u30fc\u30c9\u3092\u30b3\u30d4\u30fc\n\u8fd9\u5c06\u521b\u5efa\u4e00\u4e2a\u56fe\u8868\uff0c\u5e76\u5c06\u5176x\u548cy\u503c\u52a0\u500d\u3002\n\n\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u5728Matplotlib\u4e2d\uff0c\u66f4\u65b0\u56fe\u5f62\u9700\u8981\u5bf9\u6570\u636e\u70b9\u7684\u4f4d\u7f6e\u548c\u5927\u5c0f\u6709\u4e00\u5b9a\u7684\u4e86\u89e3\uff0c\u5e76\u5bf9\u6570\u636e\u7684\u683c\u5f0f\u548c\u7c7b\u578b\u6709\u4e00\u5b9a\u7684\u638c\u63e1\u3002\u53e6\u5916\uff0cMatplotlib\u8fd8\u63d0\u4f9b\u4e86\u5176\u4ed6\u7c7b\u578b\u7684\u56fe\u5f62\uff0c\u4f8b\u5982\u7b49\u9ad8\u7ebf\u56fe\u3001\u6781\u5750\u6807\u56fe\u548c\u5730\u56fe\u7b49\u7b49\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u60c5\u51b5\u9009\u62e9\u4e0d\u540c\u7684\u56fe\u5f62\u7c7b\u578b\u6765\u5c55\u793a\u548c\u5206\u6790\u6570\u636e\u3002\u5728Matplotlib\u7684\u5b98\u65b9\u6587\u6863\u4e2d\uff0c\u4f60\u53ef\u4ee5\u627e\u5230\u66f4\u8be6\u7ec6\u7684\u56fe\u5f62\u66f4\u65b0\u6307\u5357\u3002\n<\/code><\/pre>\n\n\n\n
                                                      \"\"\/<\/figure>\n\n\n\n
                                                      \"gun<\/figure>\n\n\n\n
                                                      \u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u306e\u4fdd\u5b58\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                      Matplotlib \u3067\u306f\u3001Animation.save()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4fdd\u5b58\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u65b9\u6cd5\u3067\u306f\u3001\u30d5\u30a1\u30a4\u30eb\u540d\u3068\u3001\u30d5\u30ec\u30fc\u30e0 \u30ec\u30fc\u30c8\u3001\u30b3\u30fc\u30c7\u30c3\u30af\u3001\u30d3\u30c3\u30c8 \u30ec\u30fc\u30c8\u3001\u89e3\u50cf\u5ea6\u306a\u3069\u306e\u305d\u306e\u4ed6\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u6307\u5b9a\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4fdd\u5b58\u3059\u308b\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                                        \n
                                                      1. GIF \u3068\u3057\u3066\u4fdd\u5b58: Matplotlib \u3067\u306f\u3001animation.PillowWriter<\/code>\u30b3\u30fc\u30c7\u30c3\u30af\u3092\u4f7f\u7528\u3057\u3066\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092 GIF \u3068\u3057\u3066\u4fdd\u5b58\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4fdd\u5b58\u3057\u3001my_animation.gif<\/code>\u30d5\u30a1\u30a4\u30eb\u3068\u3057\u3066\u4fdd\u5b58\u3057\u307e\u3059\u3002 pythonCopy codefig, ax = plt.subplots() line, = ax.plot([], [], lw=2) def init(): line.set_data([], []) return line, def animate(i): x = np.linspace(0, 2*np.pi, 100) y = np.sin(2 * np.pi * (x - 0.01 * i)) line.set_data(x, y) return line, ani = animation.FuncAnimation(fig, animate, init_func=init, frames=100, interval=50, blit=True) writer = animation.PillowWriter(fps=30) ani.save('my_animation.gif', writer=writer) <\/code>\u3053\u308c\u306f\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4f5c\u6210\u3057\u3001my_animation.gif<\/code>\u30d5\u30a1\u30a4\u30eb\u3068\u3057\u3066\u4fdd\u5b58\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                      2. MP4 \u5f62\u5f0f\u3067\u306e\u4fdd\u5b58: Matplotlib \u3067\u306f\u3001animation.FFMpegWriter<\/code>\u30b3\u30fc\u30c7\u30c3\u30af\u3092\u4f7f\u7528\u3057\u3066\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092 MP4 \u5f62\u5f0f\u3067\u4fdd\u5b58\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4fdd\u5b58\u3057\u3001my_animation.mp4<\/code>\u30d5\u30a1\u30a4\u30eb\u3068\u3057\u3066\u4fdd\u5b58\u3057\u307e\u3059\u3002 pythonCopy codefig, ax = plt.subplots() line, = ax.plot([], [], lw=2) def init(): line.set_data([], []) return line, def animate(i): x = np.linspace(0, 2*np.pi, 100) y = np.sin(2 * np.pi * (x - 0.01 * i)) line.set_data(x, y) return line, ani = animation.FuncAnimation(fig, animate, init_func=init, frames=100, interval=50, blit=True) writer = animation.FFMpegWriter(fps=30) ani.save('my_animation.mp4', writer=writer) <\/code>\u3053\u308c\u306f\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4f5c\u6210\u3057\u3001my_animation.mp4<\/code>\u30d5\u30a1\u30a4\u30eb\u3068\u3057\u3066\u4fdd\u5b58\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                                                        \u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4fdd\u5b58\u3059\u308b\u524d\u306b\u3001\u5fc5\u8981\u306a\u30b3\u30fc\u30c7\u30c3\u30af\u304c\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u304a\u3088\u3073\u69cb\u6210\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u3055\u3089\u306b\u3001\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u3092\u4fdd\u5b58\u3059\u308b\u306b\u306f\u3001\u30d5\u30a1\u30a4\u30eb\u5f62\u5f0f\u3001\u30d5\u30a1\u30a4\u30eb\u540d\u3001\u304a\u3088\u3073\u305d\u306e\u4ed6\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u306b\u95a2\u3059\u308b\u77e5\u8b58\u304c\u5fc5\u8981\u3067\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306b\u306f\u3001\u3088\u308a\u8a73\u7d30\u306a\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u4fdd\u5b58\u30ac\u30a4\u30c9\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
                                                        \"\"\/<\/figure>\n\n\n\n
                                                        \"gun<\/figure>\n\n\n\n
                                                        \u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u63cf\u753b\u3068\u30a4\u30d9\u30f3\u30c8\u51e6\u7406\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                        Matplotlib \u3067\u306f\u3001\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30d7\u30ed\u30c3\u30c8\u3092\u4f7f\u7528\u3057\u3066\u3001\u30de\u30a6\u30b9 \u30af\u30ea\u30c3\u30af\u3001\u30de\u30a6\u30b9\u306e\u52d5\u304d\u3001\u30ad\u30fc\u30dc\u30fc\u30c9\u306e\u30ad\u30fc\u30b9\u30c8\u30ed\u30fc\u30af\u306a\u3069\u306e\u30e6\u30fc\u30b6\u30fc\u5165\u529b\u306b\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u5fdc\u7b54\u3055\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u63cf\u753b\u3068\u30a4\u30d9\u30f3\u30c8\u51e6\u7406\u306e\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                                          \n
                                                        1. \u30de\u30a6\u30b9 \u30af\u30ea\u30c3\u30af \u30a4\u30d9\u30f3\u30c8: Matplotlib \u3067\u306f\u3001Figure.canvas.mpl_connect()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30de\u30a6\u30b9 \u30af\u30ea\u30c3\u30af \u30a4\u30d9\u30f3\u30c8\u3092\u767b\u9332\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3057\u3001\u30de\u30a6\u30b9 \u30af\u30ea\u30c3\u30af \u30a4\u30d9\u30f3\u30c8\u3092\u767b\u9332\u3057\u307e\u3059\u3002\u30de\u30a6\u30b9\u304c\u30af\u30ea\u30c3\u30af\u3055\u308c\u308b\u3068\u3001\u30de\u30a6\u30b9 \u30af\u30ea\u30c3\u30af\u306e\u4f4d\u7f6e\u3068\u6563\u5e03\u56f3\u306e\u305d\u306e\u4f4d\u7f6e\u306b\u3042\u308b\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u304c\u51fa\u529b\u3055\u308c\u307e\u3059\u3002x = np.random.rand(100) y = np.random.rand(100) fig, ax = plt.subplots() scat = ax.scatter(x, y) def on_click(event): if event.inaxes is not None: print('x = {}, y = {}'.format(event.xdata, event.ydata)) index = np.argmin((x - event.xdata)**2 + (y - event.ydata)**2) print('value = {}'.format(scat.get_offsets()[index])) fig.canvas.mpl_connect('button_press_event', on_click) plt.show() <\/code>\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3057\u3001\u30de\u30a6\u30b9 \u30af\u30ea\u30c3\u30af \u30a4\u30d9\u30f3\u30c8\u3092\u767b\u9332\u3057\u307e\u3059\u3002\u30de\u30a6\u30b9\u304c\u30af\u30ea\u30c3\u30af\u3055\u308c\u308b\u3068\u3001\u30de\u30a6\u30b9 \u30af\u30ea\u30c3\u30af\u306e\u4f4d\u7f6e\u3068\u6563\u5e03\u56f3\u306e\u305d\u306e\u4f4d\u7f6e\u306e\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u304c\u51fa\u529b\u3055\u308c\u307e\u3059\u3002<\/li>\n\n\n\n
                                                        2. Mousemove \u30a4\u30d9\u30f3\u30c8: Matplotlib \u3067\u306f\u3001Figure.canvas.mpl_connect()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066 mousemove \u30a4\u30d9\u30f3\u30c8\u3092\u767b\u9332\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3057\u3001mousemove \u30a4\u30d9\u30f3\u30c8\u3092\u767b\u9332\u3057\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u30de\u30a6\u30b9\u304c\u79fb\u52d5\u3057\u305f\u3068\u304d\u306b\u30de\u30a6\u30b9\u304c\u914d\u7f6e\u3055\u308c\u3066\u3044\u308b\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u304c\u5f37\u8abf\u8868\u793a\u3055\u308c\u307e\u3059: pythonCopy code \u3053\u308c\u306f\u3001\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3057\u3001mousemove \u30a4\u30d9\u30f3\u30c8\u3092\u767b\u9332\u3057\u307e\u3059. \u30de\u30a6\u30b9\u304c\u79fb\u52d5\u3059\u308b\u3068x = np.random.rand(100) y = np.random.rand(100) fig, ax = plt.subplots() scat = ax.scatter(x, y) def on_move(event): if event.inaxes is not None: index = np.argmin((x - event.xdata)**2 + (y - event.ydata)**2) offsets = scat.get_offsets() offsets[:, 2] = 0.3 offsets[index, 2] = 1 scat.set_offsets(offsets) fig.canvas.draw_idle() fig.canvas.mpl_connect('motion_notify_event', on_move) plt.show() <\/code>,\u30de\u30a6\u30b9\u304c\u7f6e\u304b\u308c\u3066\u3044\u308b\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u304c\u5f37\u8abf\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/li>\n\n\n\n
                                                        3. \u30ad\u30fc\u30dc\u30fc\u30c9 \u30ad\u30fc \u30a4\u30d9\u30f3\u30c8: Matplotlib \u3067\u306f\u3001Figure.canvas.mpl_connect()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30ad\u30fc\u30dc\u30fc\u30c9 \u30ad\u30fc \u30a4\u30d9\u30f3\u30c8\u3092\u767b\u9332\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3057\u3001\u30ad\u30fc\u30dc\u30fc\u30c9\u306e\u30ad\u30fc \u30a4\u30d9\u30f3\u30c8\u3092\u767b\u9332\u3057\u307e\u3059\u3002\u30ad\u30fc\u30dc\u30fc\u30c9\u306e\u4e0a\u77e2\u5370\u30ad\u30fc\u304c\u62bc\u3055\u308c\u308b\u3068\u3001\u30b0\u30e9\u30d5\u304c\u7acb\u3061\u4e0a\u304c\u308a\u3001\u30b0\u30e9\u30d5\u304c\u518d\u63cf\u753b\u3055\u308c\u307e\u3059\u3002x = np.linspace(0, 2*np.pi, 100) y = np.sin(x) fig, ax = plt.subplots() line, = ax.plot(x, y) def on_key<\/code><\/li>\n<\/ol>\n\n\n\n
                                                          \"\"\/<\/figure>\n\n\n\n
                                                          \"gun<\/figure>\n\n\n\n
                                                          \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                          (\u30a4\u30d9\u30f3\u30c8): if event.key == ‘up’: y_new = y + 0.1 line.set_ydata(y_new) fig.canvas.draw_idle()<\/p>\n\n\n\n
                                                          fig.canvas.mpl_connect(‘key_press_event’, on_key)<\/p>\n\n\n\n
                                                          plt.show()<\/p>\n\n\n\n
                                                          \u30b3\u30fc\u30c9\u3092\u30b3\u30d4\u30fc\n\u8fd9\u5c06\u521b\u5efa\u4e00\u4e2a\u66f2\u7ebf\u56fe\uff0c\u5e76\u6ce8\u518c\u4e00\u4e2a\u952e\u76d8\u6309\u952e\u4e8b\u4ef6\uff0c\u5f53\u6309\u4e0b\u952e\u76d8\u4e0a\u7684\u5411\u4e0a\u7bad\u5934\u952e\u65f6\uff0c\u5c06\u5c06\u66f2\u7ebf\u4e0a\u5347\uff0c\u5e76\u91cd\u7ed8\u66f2\u7ebf\u56fe\u3002\n\n\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u5728Matplotlib\u4e2d\uff0c\u4ea4\u4e92\u5f0f\u7ed8\u56fe\u9700\u8981\u5bf9\u4e8b\u4ef6\u7684\u7c7b\u578b\u3001\u5750\u6807\u7cfb\u3001\u6570\u636e\u70b9\u548c\u7ed8\u56fe\u5bf9\u8c61\u7b49\u6709\u4e00\u5b9a\u7684\u4e86\u89e3\uff0c\u624d\u80fd\u5bf9\u7528\u6237\u8f93\u5165\u505a\u51fa\u6b63\u786e\u7684\u54cd\u5e94\u3002\u53e6\u5916\uff0cMatplotlib\u8fd8\u63d0\u4f9b\u4e86\u5176\u4ed6\u7c7b\u578b\u7684\u4e8b\u4ef6\u548c\u4ea4\u4e92\u5f0f\u5de5\u5177\uff0c\u4f8b\u5982\u6ed1\u5757\u3001\u6309\u94ae\u3001\u6587\u672c\u6846\u548c\u83dc\u5355\u7b49\u7b49\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u60c5\u51b5\u9009\u62e9\u4e0d\u540c\u7684\u5de5\u5177\u6765\u589e\u5f3a\u56fe\u5f62\u7684\u4ea4\u4e92\u6027\u3002\u5728Matplotlib\u7684\u5b98\u65b9\u6587\u6863\u4e2d\uff0c\u4f60\u53ef\u4ee5\u627e\u5230\u66f4\u8be6\u7ec6\u7684\u4ea4\u4e92\u5f0f\u7ed8\u56fe\u548c\u4e8b\u4ef6\u5904\u7406\u6307\u5357\u3002\n<\/code><\/pre>\n\n\n\n
                                                          \"\"\/<\/figure>\n\n\n\n
                                                          \"gun<\/figure>\n\n\n\n
                                                          CSV\u30d5\u30a1\u30a4\u30eb\u304b\u3089\u306e\u30c7\u30fc\u30bf\u53d6\u308a\u8fbc\u307f\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u6559\u3048\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                          Matplotlib \u3067\u306f\u3001numpy<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570loadtxt()<\/code>\u307e\u305f\u306fpandas<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066read_csv()<\/code>\u3001CSV \u30d5\u30a1\u30a4\u30eb\u304b\u3089\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3067\u304d\u307e\u3059\u3002CSV \u30d5\u30a1\u30a4\u30eb\u304b\u3089\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
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                                                          1. \u95a2\u6570\u306e\u4f7f\u7528numpy.loadtxt()<\/code>:numpy<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u306f\u3001loadtxt()<\/code>CSV \u30d5\u30a1\u30a4\u30eb\u304b\u3089\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3067\u304d\u308b\u95a2\u6570\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001data.csv<\/code>\u30d5\u30a1\u30a4\u30eb\u304b\u3089 2 \u5217\u306e\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3001\u305d\u308c\u3089\u306e\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3057\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9import numpy as np import matplotlib.pyplot as plt data = np.loadtxt('data.csv', delimiter=',', skiprows=1) x = data[:, 0] y = data[:, 1] fig, ax = plt.subplots() ax.scatter(x, y) plt.show() <\/code>\u3053\u308c\u306f\u3001data.csv<\/code>\u30d5\u30a1\u30a4\u30eb\u304b\u3089 2 \u5217\u306e\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3001\u305d\u308c\u3089\u306e\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                          2. \u95a2\u6570\u306e\u4f7f\u7528pandas.read_csv()<\/code>:pandas<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u306b\u306f\u3001read_csv()<\/code>CSV \u30d5\u30a1\u30a4\u30eb\u304b\u3089\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3066DataFrame<\/code>\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u5909\u63db\u3067\u304d\u308b\u95a2\u6570\u304c\u7528\u610f\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001data.csv<\/code>\u30d5\u30a1\u30a4\u30eb\u304b\u3089 2 \u5217\u306e\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3066\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9import pandas as pd import matplotlib.pyplot as plt data = pd.read_csv('data.csv') x = data['x'] y = data['y'] fig, ax = plt.subplots() ax.plot(x, y) plt.show() <\/code>\u3053\u308c\u306f\u3001data.csv<\/code>\u30d5\u30a1\u30a4\u30eb\u304b\u3089 2 \u5217\u306e\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3066\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                                                            loadtxt()<\/code>\u95a2\u6570\u307e\u305f\u306fread_csv()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u5834\u5408\u3001\u30c7\u30fc\u30bf\u3092\u6b63\u3057\u304f\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u306b\u306f\u3001CSV \u30d5\u30a1\u30a4\u30eb\u306e\u5f62\u5f0f\u3068\u5185\u5bb9\u3092\u7406\u89e3\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3059\u308b\u3053\u3068\u304c\u91cd\u8981\u3067\u3059\u3002\u307e\u305f\u3001\u30c7\u30fc\u30bf\u3092\u6b63\u3057\u304f\u8868\u793a\u30fb\u5206\u6790\u3059\u308b\u306b\u306f\u3001\u30c7\u30fc\u30bf\u306e\u5f62\u5f0f\u3084\u7a2e\u985e\u3092\u3042\u308b\u7a0b\u5ea6\u628a\u63e1\u3057\u3066\u304a\u304f\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u3088\u308a\u8a73\u7d30\u306a\u30c7\u30fc\u30bf\u306e\u30a4\u30f3\u30dd\u30fc\u30c8\u3068\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u306e\u30ac\u30a4\u30c9\u30e9\u30a4\u30f3\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                                            \"\"\/<\/figure>\n\n\n\n
                                                            \"gun<\/figure>\n\n\n\n
                                                            Excel\u30d5\u30a1\u30a4\u30eb\u304b\u3089\u306e\u30c7\u30fc\u30bf\u306e\u30a4\u30f3\u30dd\u30fc\u30c8\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                            Matplotlib \u3067\u306f\u3001pandas<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066read_excel()<\/code>\u3001Excel \u30d5\u30a1\u30a4\u30eb\u304b\u3089\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3067\u304d\u307e\u3059\u3002DataFrame<\/code>Excel\u30d5\u30a1\u30a4\u30eb\u5185\u306e\u30c7\u30fc\u30bf\u3092\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3068\u3057\u3066\u8aad\u307f\u8fbc\u3081\u308b\u6a5f\u80fd\u3067\u3001\u305d\u306e\u5f8c\u306e\u30c7\u30fc\u30bf\u89e3\u6790\u3084\u63cf\u753b\u306b\u4fbf\u5229\u3067\u3059\u3002Excel \u30d5\u30a1\u30a4\u30eb\u304b\u3089\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
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                                                            1. 1 \u3064\u306e\u30ef\u30fc\u30af\u30b7\u30fc\u30c8\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b: Excel \u30d5\u30a1\u30a4\u30eb\u306b 1 \u3064\u306e\u30ef\u30fc\u30af\u30b7\u30fc\u30c8\u3057\u304b\u542b\u307e\u308c\u3066\u3044\u306a\u3044\u5834\u5408\u306f\u3001pandas.read_excel()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u305d\u308c\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u30d5\u30a1\u30a4\u30eb\u304b\u3089\u6307\u5b9a\u3055\u308c\u305f\u30ef\u30fc\u30af\u30b7\u30fc\u30c8\u3092data.xlsx<\/code>\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3001\u305d\u306e\u30c7\u30fc\u30bf\u306e\u6563\u5e03\u56f3\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3059\u3002 pythonCopy code\u3053\u308c\u306f\u3001\u30d5\u30a1\u30a4\u30eb\u304b\u3089\u6307\u5b9a\u3055\u308c\u305f\u30ef\u30fc\u30af\u30b7\u30fc\u30c8\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3001\u305d\u306e\u30c7\u30fc\u30bf\u306e\u6563\u5e03\u56f3\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3059\u3002Sheet1<\/code>import pandas as pd import matplotlib.pyplot as plt data = pd.read_excel('data.xlsx', sheet_name='Sheet1') x = data['x'] y = data['y'] fig, ax = plt.subplots() ax.scatter(x, y) plt.show() <\/code>data.xlsx<\/code>Sheet1<\/code><\/li>\n\n\n\n
                                                            2. \u8907\u6570\u306e\u30ef\u30fc\u30af\u30b7\u30fc\u30c8\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b: Excel \u30d5\u30a1\u30a4\u30eb\u306b\u8907\u6570\u306e\u30ef\u30fc\u30af\u30b7\u30fc\u30c8\u304c\u542b\u307e\u308c\u3066\u3044\u308b\u5834\u5408\u3001pandas.read_excel()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u305d\u308c\u3089\u3092\u8f9e\u66f8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3068\u3057\u3066\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3001\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u5bfe\u5fdc\u3059\u308b\u30ef\u30fc\u30af\u30b7\u30fc\u30c8\u3092\u9078\u629e\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001data.xlsx<\/code>\u30d5\u30a1\u30a4\u30eb\u304b\u3089\u3059\u3079\u3066\u306e\u30ef\u30fc\u30af\u30b7\u30fc\u30c8\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3001\u305d\u308c\u3089\u306e\u30c7\u30fc\u30bf\u306e\u6563\u5e03\u56f3\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3059\u3002 pythonCopy codeimport pandas as pd import matplotlib.pyplot as plt data_dict = pd.read_excel('data.xlsx', sheet_name=None) fig, axs = plt.subplots(nrows=len(data_dict), figsize=(6, 3*len(data_dict))) for i, (name, sheet) in enumerate(data_dict.items()): x = sheet['x'] y = sheet['y'] axs[i].scatter(x, y) axs[i].set_title(name) plt.show() <\/code>\u3053\u308c\u306f\u3001data.xlsx<\/code>\u30d5\u30a1\u30a4\u30eb\u304b\u3089\u3059\u3079\u3066\u306e\u30ef\u30fc\u30af\u30b7\u30fc\u30c8\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3001\u305d\u308c\u3089\u306e\u30c7\u30fc\u30bf\u306e\u6563\u5e03\u56f3\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                                                              read_excel()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u5834\u5408\u306f\u3001\u5fc5\u8981\u306a Excel \u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3001\u69cb\u6210\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057openpyxl<\/code>\u3066\u304f\u3060\u3055\u3044\u3002\u3055\u3089\u306b\u3001\u30c7\u30fc\u30bf\u3092\u6b63\u3057\u304f\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u306b\u306f\u3001Excel \u30d5\u30a1\u30a4\u30eb\u306e\u69cb\u9020\u3068\u5185\u5bb9\u306b\u3064\u3044\u3066\u3042\u308b\u7a0b\u5ea6\u306e\u77e5\u8b58\u304c\u5fc5\u8981\u3067\u3059\u3002Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u3001\u3088\u308a\u8a73\u7d30\u306a\u30c7\u30fc\u30bf\u306e\u30a4\u30f3\u30dd\u30fc\u30c8\u3068\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u306e\u30ac\u30a4\u30c9\u30e9\u30a4\u30f3\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002xlrd<\/code>xlsxwriter<\/code><\/p>\n\n\n\n
                                                              \"\"\/<\/figure>\n\n\n\n
                                                              \"gun<\/figure>\n\n\n\n
                                                              \u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044 \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3092\u5199\u771f\u3068\u3057\u3066\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3059\u308b<\/p>\n\n\n\n
                                                              Matplotlib \u3067\u306f\u3001savefig()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u63cf\u753b\u3055\u308c\u305f\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3092\u753b\u50cf\u30d5\u30a1\u30a4\u30eb\u3068\u3057\u3066\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u95a2\u6570\u306f\u3001PNG\u3001JPG\u3001PDF\u3001SVG \u306a\u3069\u306e\u3055\u307e\u3056\u307e\u306a\u753b\u50cf\u5f62\u5f0f\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u753b\u50cf\u3068\u3057\u3066\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3059\u308b\u65b9\u6cd5\u3068\u624b\u9806\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
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                                                              1. PNG \u5f62\u5f0f\u3078\u306e\u30a8\u30af\u30b9\u30dd\u30fc\u30c8: \u63cf\u753b\u3057\u305f\u30b0\u30e9\u30d5\u3092 PNG \u5f62\u5f0f\u306e\u753b\u50cf\u3068\u3057\u3066\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3059\u308b\u5834\u5408\u306f\u3001savefig()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30d5\u30a1\u30a4\u30eb\u540d\u306e\u62e1\u5f35\u5b50\u3092\u6307\u5b9a\u3067\u304d\u307e\u3059.png<\/code>\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3057\u3001scatter.png<\/code>PNG \u753b\u50cf\u3068\u3057\u3066\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002 pythonCopy codeimport numpy as np import matplotlib.pyplot as plt x = np.random.rand(100) y = np.random.rand(100) fig, ax = plt.subplots() ax.scatter(x, y) fig.savefig('scatter.png') <\/code>\u3053\u308c\u306f\u3001\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3057\u3001scatter.png<\/code>PNG \u753b\u50cf\u3068\u3057\u3066\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                              2. PDF \u5f62\u5f0f\u3078\u306e\u30a8\u30af\u30b9\u30dd\u30fc\u30c8: \u63cf\u753b\u3057\u305f\u30b0\u30e9\u30d5\u3092 PDF \u5f62\u5f0f\u306e\u753b\u50cf\u3068\u3057\u3066\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3059\u308b\u5834\u5408\u306f\u3001savefig()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u30d5\u30a1\u30a4\u30eb\u540d\u306e\u62e1\u5f35\u5b50\u3092\u6307\u5b9a\u3067\u304d\u307e\u3059.pdf<\/code>\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u3001line.pdf<\/code>PDF\u5f62\u5f0f\u306e\u753b\u50cfimport numpy as np import matplotlib.pyplot as plt x = np.linspace(0, 2*np.pi, 100) y = np.sin(x) fig, ax = plt.subplots() ax.plot(x, y) fig.savefig('line.pdf') <\/code>\u3068\u3057\u3066\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3057\u307e\u3059line.pdf<\/code>\u3002<\/li>\n<\/ol>\n\n\n\n
                                                                savefig()<\/code>\u3053\u306e\u6a5f\u80fd\u3092\u4f7f\u7528\u3059\u308b\u969b\u306b\u306f\u3001\u30cb\u30fc\u30ba\u306b\u5408\u3063\u305f\u51fa\u529b\u3092\u5f97\u308b\u305f\u3081\u306b\u3001\u51fa\u529b\u753b\u50cf\u306e\u5f62\u5f0f\u3001\u30b5\u30a4\u30ba\u3001\u89e3\u50cf\u5ea6\u306a\u3069\u306b\u3064\u3044\u3066\u4e00\u5b9a\u306e\u7406\u89e3\u304c\u5fc5\u8981\u3067\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u3055\u3089\u306b\u3001\u753b\u50cf\u306e\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u4e2d\u306b\u554f\u984c\u304c\u767a\u751f\u3057\u305f\u5834\u5408\u306f\u3001Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u63d0\u4f9b\u3055\u308c\u3066\u3044\u308b\u30c7\u30d0\u30c3\u30b0\u65b9\u6cd5\u3068\u30c4\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u3001\u554f\u984c\u306e\u30c8\u30e9\u30d6\u30eb\u30b7\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u3068\u89e3\u6c7a\u3092\u8a66\u307f\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                \"\"\/<\/figure>\n\n\n\n
                                                                \"gun<\/figure>\n\n\n\n
                                                                \u5b9f\u6226\u6642\u7cfb\u5217\u5206\u6790\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u6559\u3048\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                                \u6642\u7cfb\u5217\u5206\u6790\u3068\u306f\u3001\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u30e2\u30c7\u30eb\u5316\u3001\u4e88\u6e2c\u3001\u304a\u3088\u3073\u5206\u6790\u3059\u308b\u65b9\u6cd5\u3092\u6307\u3057\u307e\u3059\u3002Matplotlib \u3067\u306f\u3001pandas<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306eread_csv()<\/code>\u95a2\u6570\u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u7528\u3057datetime<\/code>\u3066\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u53d6\u3063\u3066\u51e6\u7406\u3057\u3001matplotlib.dates<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3068pyplot<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u6642\u7cfb\u5217\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u304a\u3088\u3073\u8868\u793a\u3057\u3001statsmodels<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u3066ARIMA<\/code>\u6642\u7cfb\u5217\u5206\u6790\u3068\u4e88\u6e2c\u3092\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                \u4ee5\u4e0b\u306f\u3001\u6642\u7cfb\u5217\u5206\u6790\u306e\u305f\u3081\u306b Matplotlib \u3068\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u7c21\u5358\u306a\u5b9f\u969b\u306e\u30b1\u30fc\u30b9\u3067\u3059ARIMA<\/code>\u3002<\/p>\n\n\n\n
                                                                  \n
                                                                1. pandas<\/code>\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u8aad\u307f\u53d6\u308a: \u307e\u305a\u3001\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u53d6\u308aread_csv()<\/code>\u3001\u6642\u9593\u5217\u3092datetime<\/code>\u578b\u306b\u5909\u63db\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u304c\u6b21\u306edata.csv<\/code>\u5f62\u5f0f\u3067\u30d5\u30a1\u30a4\u30eb\u306b\u4fdd\u5b58\u3055\u308c\u3066\u3044\u308b\u3068\u4eee\u5b9a\u3059\u308b\u3068\u3001YYYY-MM-DD, value<\/code>\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u53d6\u308a\u3001\u6642\u9593\u5217\u3092\u5909\u63db\u3057import pandas as pd data = pd.read_csv('data.csv', parse_dates=[0], index_col=[0]) <\/code>\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9 \u3053\u308c\u306fdata.csv<\/code>\u30d5\u30a1\u30a4\u30eb\u5185\u306e\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u53d6\u308a\u3001\u6642\u9593\u5217\u3092datetime<\/code>\u30bf\u30a4\u30d7\u3002<\/li>\n\n\n\n
                                                                2. \u6642\u7cfb\u5217\u306e\u30b0\u30e9\u30d5\u5316: \u6b21\u306b\u3001matplotlib.dates<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3068pyplot<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u6642\u7cfb\u5217\u3092\u30b0\u30e9\u30d5\u5316\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u3001\u30bf\u30a4\u30c8\u30eb\u3001\u8ef8\u30e9\u30d9\u30eb\u3001\u304a\u3088\u3073\u51e1\u4f8b\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002 pythonCopy code \u3053\u308c\u306f\u3001\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u3001\u30bf\u30a4\u30c8\u30eb\u3001import matplotlib.pyplot as plt from matplotlib.dates import DateFormatter fig, ax = plt.subplots() ax.plot(data.index, data['value'], label='Value') ax.set_title('Time Series Analysis') ax.set_xlabel('Date') ax.set_ylabel('Value') ax.legend() date_format = DateFormatter('%Y-%m-%d') ax.xaxis.set_major_formatter(date_format) fig.autofmt_xdate() plt.show() <\/code>\u8ef8\u30e9\u30d9\u30eb\u3001\u304a\u3088\u3073\u51e1\u4f8b\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002 . DateFormatter<\/code>\u3053\u3053\u3067\u306fsum\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001autofmt_xdate()<\/code>\u8868\u793a\u5f62\u5f0f\u3068\u6642\u9593\u8ef8\u306e\u9593\u9694\u3092\u8abf\u6574\u3057\u3066\u3044\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                3. \u6642\u7cfb\u5217\u5206\u6790\u306e\u5b9f\u884c: \u6700\u5f8c\u306b\u3001statsmodels<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u3066ARIMA<\/code>\u3001\u6642\u7cfb\u5217\u5206\u6790\u3068\u4e88\u6e2c\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001ARIMA<\/code>\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u3066\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u30e2\u30c7\u30eb\u5316\u3057\u3001\u6b21\u306e 7 \u65e5\u9593\u306e\u5024\u3092\u4e88\u6e2c\u3057from statsmodels.tsa.arima.model import ARIMA model = ARIMA(data['value'], order=(1, 1, 1)) result = model.fit() forecast = result.forecast(steps=7) print(forecast) <\/code>\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9 \u3053\u308c\u306f\u3001ARIMA<\/code>\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u3066\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u30e2\u30c7\u30eb\u5316\u3057\u3001\u6b21\u306e 7 \u65e5\u9593\u306e\u5024\u3092\u4e88\u6e2c\u3057\u307e\u3059\u3002(1, 1, 1)<\/code>\u3053\u3053\u3067\u306f\u30e2\u30c7\u30eb\u306e\u9806\u5e8f\u304c\u4f7f\u7528\u3055\u308c\u3066\u304a\u308a\u3001\u5b9f\u969b\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u8abf\u6574\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/li>\n<\/ol>\n\n\n\n
                                                                  \u6642\u7cfb\u5217\u5206\u6790\u306f\u8907\u96d1\u3067\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                  \"\"\/<\/figure>\n\n\n\n
                                                                  \"gun<\/figure>\n\n\n\n
                                                                  \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                                  \u9069\u5207\u306b\u30e2\u30c7\u30eb\u5316\u3001\u4e88\u6e2c\u3001\u5206\u6790\u3059\u308b\u305f\u3081\u306b\u3001\u6642\u7cfb\u5217\u306e\u7279\u6027\u3001\u50be\u5411\u3001\u5b63\u7bc0\u6027\u306a\u3069\u3092\u3042\u308b\u7a0b\u5ea6\u7406\u89e3\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u5206\u91ce\u3002numpy<\/code>\u6642\u7cfb\u5217\u5206\u6790\u3092\u884c\u3046\u5834\u5408\u3001 \u3001scipy<\/code>\u306a\u3069\u306e\u4ed6\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u3084\u30c4\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066pandas_datareader<\/code>\u3001\u30c7\u30fc\u30bf\u3092\u51e6\u7406\u304a\u3088\u3073\u5206\u6790\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u5834\u5408\u3082\u3042\u308a\u307e\u3059\u3002\u3055\u3089\u306b\u3001\u95a2\u9023\u3059\u308b\u30e2\u30c7\u30eb\u3068\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u7406\u89e3\u3057\u3066\u4f7f\u7528\u3059\u308b\u305f\u3081\u306b\u3001\u7d71\u8a08\u3068\u6570\u5b66\u306e\u57fa\u790e\u306b\u3064\u3044\u3066\u3042\u308b\u7a0b\u5ea6\u306e\u77e5\u8b58\u304c\u5fc5\u8981\u3067\u3059\u3002<\/p>\n\n\n\n
                                                                  \u4e00\u822c\u306b\u3001Matplotlib \u3092\u4f7f\u7528\u3057\u305f\u6642\u7cfb\u5217\u5206\u6790\u306b\u306f\u3001\u6b21\u306e\u624b\u9806\u304c\u5fc5\u8981\u3067\u3059\u3002<\/p>\n\n\n\n
                                                                    \n
                                                                  1. \u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u53d6\u308a\u3001\u6642\u9593\u5217\u3092datetime<\/code>\u578b\u306b\u5909\u63db\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                  2. \u6642\u7cfb\u5217\u30b0\u30e9\u30d5\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u3001\u30bf\u30a4\u30c8\u30eb\u3001\u8ef8\u30e9\u30d9\u30eb\u3001\u304a\u3088\u3073\u51e1\u4f8b\u3092\u8ffd\u52a0\u3057\u3001\u6642\u9593\u8ef8\u306e\u8868\u793a\u5f62\u5f0f\u3068\u9593\u9694\u3092\u8abf\u6574\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                  3. \u30e2\u30c7\u30eb\u3092\u6642\u7cfb\u5217\u5206\u6790\u3068\u4e88\u6e2c\u306b\u4f7f\u7528\u3057ARIMA<\/code>\u3001\u30e2\u30c7\u30eb\u306e\u9806\u5e8f\u3068\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u8abf\u6574\u3057\u3066\u3001\u30e2\u30c7\u30eb\u306e\u30d5\u30a3\u30c3\u30c6\u30a3\u30f3\u30b0\u52b9\u679c\u3068\u4e88\u6e2c\u7cbe\u5ea6\u3092\u8a55\u4fa1\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                                                                    \u6642\u7cfb\u5217\u5206\u6790\u3092\u5b9f\u884c\u3059\u308b\u5834\u5408\u3001\u9069\u5207\u306a\u30e2\u30c7\u30eb\u3068\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u9078\u629e\u3057\u3066\u6b63\u3057\u304f\u9069\u7528\u3059\u308b\u305f\u3081\u306b\u3001\u30c7\u30fc\u30bf\u306e\u6027\u8cea\u3068\u7279\u6027\u3092\u614e\u91cd\u306b\u5206\u6790\u304a\u3088\u3073\u5224\u65ad\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u540c\u6642\u306b\u3001\u9069\u5207\u306a\u30c7\u30fc\u30bf\u51e6\u7406\u3068\u30af\u30ea\u30fc\u30cb\u30f3\u30b0\u3092\u5b9f\u884c\u3057\u3066\u3001\u30c7\u30fc\u30bf\u306e\u54c1\u8cea\u3068\u6b63\u78ba\u6027\u3092\u78ba\u4fdd\u3059\u308b\u5fc5\u8981\u3082\u3042\u308a\u307e\u3059\u3002\u6642\u7cfb\u5217\u5206\u6790\u306e\u5b9f\u884c\u4e2d\u306b\u554f\u984c\u304c\u767a\u751f\u3057\u305f\u5834\u5408\u306f\u3001Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3084\u305d\u306e\u4ed6\u306e\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u3092\u53c2\u7167\u3059\u308b\u304b\u3001\u95a2\u9023\u5206\u91ce\u306e\u5c02\u9580\u5bb6\u306b\u52a9\u3051\u3092\u6c42\u3081\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                    \"\"\/<\/figure>\n\n\n\n
                                                                    \"gun<\/figure>\n\n\n\n
                                                                    \u5b9f\u969b\u306e\u4e8b\u4f8b\u76f8\u95a2\u5206\u6790\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                                    \u76f8\u95a2\u5206\u6790\u3068\u306f\u30012 \u3064\u4ee5\u4e0a\u306e\u5909\u6570\u9593\u306e\u76f8\u95a2\u3092\u6e2c\u5b9a\u304a\u3088\u3073\u5206\u6790\u3059\u308b\u3053\u3068\u3067\u3059\u3002Matplotlib \u3067\u306f\u3001pandas<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066read_csv()<\/code>\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u53d6\u308a\u3001numpy<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570corrcoef()<\/code>\u3068matplotlib<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057scatter()<\/code>\u3066\u76f8\u95a2\u5206\u6790\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u3001seaborn<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057heatmap()<\/code>\u3066\u76f8\u95a2\u30d2\u30fc\u30c8 \u30de\u30c3\u30d7\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                    \u4ee5\u4e0b\u306f\u3001\u76f8\u95a2\u5206\u6790\u306b Matplotlib \u3068\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u7c21\u5358\u306a\u5b9f\u969b\u306e\u30b1\u30fc\u30b9\u3067\u3059seaborn<\/code>\u3002<\/p>\n\n\n\n
                                                                      \n
                                                                    1. pandas<\/code>\u30c7\u30fc\u30bf\u306e\u8aad\u307f\u53d6\u308a: \u307e\u305a\u3001\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306eread_csv()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u53d6\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u30c7\u30fc\u30bf\u304cdata.csv<\/code>\u306e\u5f62\u5f0f\u3067\u30d5\u30a1\u30a4\u30eb\u306b\u4fdd\u5b58\u3055\u308c\u3066\u3044\u308b\u3068\u4eee\u5b9a\u3059\u308b\u3068x1, x2, y<\/code>\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u3067\u30c7\u30fc\u30bf\u304c\u8aad\u307f\u53d6\u3089\u308c\u307e\u3059\u3002 pythonCopy \u30b3\u30fc\u30c9\u3053\u308c\u306b\u3088\u308a\u3001\u30d5\u30a1\u30a4\u30eb\u5185\u306e\u30c7\u30fc\u30bf\u304cimport pandas as pd data = pd.read_csv('data.csv') <\/code>\u8aad\u307f\u53d6\u3089\u308c\u307e\u3059\u3002data.csv<\/code><\/li>\n\n\n\n
                                                                    2. numpy<\/code>\u6563\u5e03\u56f3\u3092\u63cf\u304f: \u6b21\u306b\u3001\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066 2 \u3064\u306e\u5909\u6570\u9593\u306e\u76f8\u95a2\u4fc2\u6570\u3092\u8a08\u7b97\u3057corrcoef()<\/code>\u3001\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u6563\u5e03\u56f3\u3092\u63cf\u304fmatplotlib<\/code>\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002scatter()<\/code>\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f 2 \u3064\u306e\u5909\u6570\u306e\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3057\u3001\u30bf\u30a4\u30c8\u30eb\u3001\u8ef8\u30e9\u30d9\u30eb\u3001\u304a\u3088\u3073\u51e1\u4f8b\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002 pythonCopy code \u3053\u308c\u306f\u30012 \u3064\u306e\u5909\u6570\u306eimport numpy as np import matplotlib.pyplot as plt x1 = data['x1'] x2 = data['x2'] y = data['y'] corr = np.corrcoef(x1, x2)[0, 1] fig, ax = plt.subplots() ax.scatter(x1, x2, c=y) ax.set_title('Scatter Plot (Corr = {})'.format(corr)) ax.set_xlabel('X1') ax.set_ylabel('X2') fig.colorbar(ax.scatter(x1, x2, c=y), label='Y') plt.show() <\/code>\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3057\u3001\u30bf\u30a4\u30c8\u30eb\u3001\u8ef8\u30e9\u30d9\u30eb\u3001\u304a\u3088\u3073\u51e1\u4f8b\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002\u3053\u306e\u95a2\u6570\u306f\u3001corrcoef()<\/code>2 \u3064\u306e\u5909\u6570\u9593\u306e\u76f8\u95a2\u4fc2\u6570\u3092\u8a08\u7b97\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u3001\u30bf\u30a4\u30c8\u30eb\u306e\u4e00\u90e8\u3068\u3057\u3066\u8868\u793a\u3055\u308c\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002scatter()<\/code>\u3055\u3089\u306b\u3001\u95a2\u6570\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066c<\/code>\u8272\u5909\u6570\u3092\u6307\u5b9a\u3057\u3001colorbar()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30ab\u30e9\u30fc \u30d0\u30fc\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                    3. \u30d2\u30fc\u30c8 \u30de\u30c3\u30d7\u3092\u63cf\u753b\u3059\u308b: \u8907\u6570\u306e\u5909\u6570\u9593\u306e\u76f8\u95a2\u4fc2\u6570\u306e\u30de\u30c8\u30ea\u30c3\u30af\u30b9\u304c\u3042\u308b\u5834\u5408\u306f\u3001seaborn<\/code>\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066heatmap()<\/code>\u76f8\u95a2\u30d2\u30fc\u30c8 \u30de\u30c3\u30d7\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u5909\u6570\u9593\u306e\u76f8\u95a2\u4fc2\u6570\u306e\u30de\u30c8\u30ea\u30c3\u30af\u30b9\u3092\u8a08\u7b97\u3057\u3001\u76f8\u95a2\u30d2\u30fc\u30c8\u30de\u30c3\u30d7\u3092\u63cf\u753b\u3057\u307e\u3059\u3002 pythonCopy codeimport seaborn as sns corr_matrix = data.corr() sns.heatmap(corr_matrix, annot=True) plt.show() <\/code>\u3053\u308c\u306f\u3001\u5909\u6570\u9593\u306e\u76f8\u95a2\u4fc2\u6570\u306e\u30de\u30c8\u30ea\u30c3\u30af\u30b9\u3092\u8a08\u7b97\u3057\u3001\u76f8\u95a2\u30d2\u30fc\u30c8\u30de\u30c3\u30d7\u3092\u63cf\u753b\u3057\u307e\u3059\u3002annot=True<\/code>\u3053\u3053\u3067\u306f\u3001\u76f8\u95a2\u4fc2\u6570\u884c\u5217\u306e\u5024\u3092\u8868\u793a\u3059\u308b\u305f\u3081\u306b\u30d1\u30e9\u30e1\u30fc\u30bf\u304c\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/li>\n<\/ol>\n\n\n\n
                                                                      \u6ce8\u610f\u304c\u5fc5\u8981<\/p>\n\n\n\n
                                                                      \"\"\/<\/figure>\n\n\n\n
                                                                      \"gun<\/figure>\n\n\n\n
                                                                      \u7d9a\u3051\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                                      \u6b8b\u5ff5\u306a\u304c\u3089\u3001\u76f8\u95a2\u5206\u6790\u306f\u56e0\u679c\u95a2\u4fc2\u3092\u610f\u5473\u3059\u308b\u3082\u306e\u3067\u306f\u306a\u304f\u3001\u5909\u6570\u9593\u306e\u76f8\u95a2\u306e\u7a0b\u5ea6\u306e\u307f\u3092\u610f\u5473\u3057\u307e\u3059\u3002\u3057\u305f\u304c\u3063\u3066\u3001\u76f8\u95a2\u5206\u6790\u3092\u884c\u3046\u969b\u306b\u306f\u3001\u5206\u6790\u7d50\u679c\u3092\u6b63\u3057\u304f\u89e3\u91c8\u3057\u3066\u9069\u7528\u3059\u308b\u305f\u3081\u306b\u3001\u30c7\u30fc\u30bf\u306e\u6027\u8cea\u3068\u7279\u6027\u3092\u614e\u91cd\u306b\u5206\u6790\u304a\u3088\u3073\u5224\u65ad\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u540c\u6642\u306b\u3001\u9069\u5207\u306a\u30c7\u30fc\u30bf\u51e6\u7406\u3068\u30af\u30ea\u30fc\u30cb\u30f3\u30b0\u3092\u5b9f\u884c\u3057\u3066\u3001\u30c7\u30fc\u30bf\u306e\u54c1\u8cea\u3068\u6b63\u78ba\u6027\u3092\u78ba\u4fdd\u3059\u308b\u5fc5\u8981\u3082\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                      \u76f8\u95a2\u5206\u6790\u306e\u5b9f\u884c\u4e2d\u306b\u554f\u984c\u304c\u767a\u751f\u3057\u305f\u5834\u5408\u306f\u3001seaborn<\/code>Matplotlib \u3068 Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3084\u305d\u306e\u4ed6\u306e\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u3092\u53c2\u7167\u3059\u308b\u304b\u3001\u95a2\u9023\u5206\u91ce\u306e\u5c02\u9580\u5bb6\u306b\u52a9\u3051\u3092\u6c42\u3081\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                      \"\"\/<\/figure>\n\n\n\n
                                                                      \"gun<\/figure>\n\n\n\n
                                                                      \u5730\u7406\u30c7\u30fc\u30bf\u53ef\u8996\u5316\u306e\u5b9f\u6226\u4e8b\u4f8b\u3092\u8a73\u3057\u304f\u6559\u3048\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                                      \u5730\u7406\u30c7\u30fc\u30bf\u306e\u8996\u899a\u5316\u3068\u306f\u3001\u5730\u7406\u7684\u4f4d\u7f6e\u3068\u95a2\u9023\u30c7\u30fc\u30bf\u3092\u7d44\u307f\u5408\u308f\u305b\u3066\u30de\u30c3\u30d7\u306e\u5f62\u5f0f\u3067\u8868\u793a\u3059\u308b\u3053\u3068\u3092\u6307\u3057\u307e\u3059\u3002Matplotlib \u3067\u306f\u3001Basemap<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3068cartopy<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u30de\u30c3\u30d7\u3092\u63cf\u753b\u3057\u3001pyplot<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u3068\u30e9\u30d9\u30eb\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                      \u4ee5\u4e0b\u306f\u3001\u5730\u7406\u30c7\u30fc\u30bf\u306e\u8996\u899a\u5316\u306b Matplotlib \u3068\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u306e\u7c21\u5358\u3067\u5b9f\u7528\u7684\u306a\u4f8b\u3067\u3059Basemap<\/code>\u3002<\/p>\n\n\n\n
                                                                        \n
                                                                      1. Basemap<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb: \u307e\u305a\u3001Basemap<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002conda<\/code>\u307e\u305f\u306f\u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3067\u304d\u307e\u3059pip<\/code>\u3002\u305f\u3068\u3048\u3070\u3001bashCopy \u30b3\u30fc\u30c9conda install -c anaconda basemap <\/code>\u307e\u305f\u306f bashCopy \u30b3\u30fc\u30c9\u3067\u3059\u3002pip install basemap<\/code><\/li>\n\n\n\n
                                                                      2. \u5730\u56f3\u3092\u63cf\u304f: \u6b21\u306b\u3001Basemap<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u5730\u56f3\u3092\u63cf\u304f\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u4e2d\u56fd\u306e\u56fd\u5883\u3068\u7701\u3092\u793a\u3059\u5730\u56f3\u3092\u63cf\u753b\u3057\u307e\u3059: pythonCopy codefrom mpl_toolkits.basemap import Basemap import matplotlib.pyplot as plt m = Basemap(projection='merc', resolution='l', llcrnrlon=73, llcrnrlat=15, urcrnrlon=135, urcrnrlat=55) m.drawcoastlines() m.drawcountries() m.drawstates() plt.show() <\/code>\u3053\u308c\u306f\u4e2d\u56fd\u306e\u56fd\u5883\u3068\u7701\u3092\u793a\u3059\u5730\u56f3\u3092\u63cf\u753b\u3057\u307e\u3059\u3002merc<\/code>\u6295\u5f71\u65b9\u6cd5\u3068\u89e3\u50cf\u5ea6\u306f\u3053\u3053\u3067\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044l<\/code>\u3002\u5b9f\u969b\u306e\u72b6\u6cc1\u306b\u5fdc\u3058\u3066\u8abf\u6574\u3067\u304d\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                      3. \u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u3068\u30e9\u30d9\u30eb\u306e\u8ffd\u52a0: \u6700\u5f8c\u306b\u3001pyplot<\/code>\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u3068\u30e9\u30d9\u30eb\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u90fd\u5e02\u306e\u7def\u5ea6\u3068\u7d4c\u5ea6\u3001\u304a\u3088\u3073\u4eba\u53e3\u30c7\u30fc\u30bf\u304c\u3042\u308b\u3068\u4eee\u5b9a\u3059\u308b\u3068\u3001scatter()<\/code>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u90fd\u5e02\u306e\u4f4d\u7f6e\u3068\u4eba\u53e3\u898f\u6a21\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u3001\u95a2\u6570\u3092\u4f7f\u7528\u3057annotate()<\/code>\u3066\u90fd\u5e02\u540d\u3068\u4eba\u53e3\u3092\u8ffd\u52a0import pandas as pd data = pd.read_csv('cities.csv') x, y = m(data['lon'].values, data['lat'].values) size = data['pop'].values \/ 1000 m.scatter(x, y, s=size, alpha=0.5, color='red') for i, row in data.iterrows(): plt.annotate(row['city'], xy=(x[i], y[i]), xytext=(5, 5), textcoords='offset points') plt.annotate(row['pop'], xy=(x[i], y[i]), xytext=(5, -10), textcoords='offset points', fontsize=8) plt.show() <\/code>\u3067\u304d\u307e\u3059\u3002scatter()<\/code>\u90fd\u5e02\u306e\u4f4d\u7f6e\u3068\u4eba\u53e3\u898f\u6a21\u3001\u7528\u9014annotate()<\/code>\u95a2\u6570\u306f\u90fd\u5e02\u540d\u3068\u4eba\u53e3\u3092\u8ffd\u52a0\u3057\u307e\u3059\u3002\u3053\u3053\u3067\u306f\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066iterrows()<\/code>\u30c7\u30fc\u30bf\u884c\u3092\u53cd\u5fa9\u51e6\u7406\u3057\u3001xy<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3068xytext<\/code>\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u3066\u6ce8\u91c8\u306e\u4f4d\u7f6e\u3068\u30aa\u30d5\u30bb\u30c3\u30c8\u3092\u6307\u5b9a\u3059\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/li>\n<\/ol>\n\n\n\n
                                                                        \u5730\u7406\u30c7\u30fc\u30bf\u3092\u8996\u899a\u5316\u3059\u308b\u5834\u5408\u3001\u30de\u30c3\u30d7\u3068\u30c7\u30fc\u30bf\u3092\u6b63\u3057\u304f\u8868\u793a\u3059\u308b\u306b\u306f\u3001\u9069\u5207\u306a\u6295\u5f71\u65b9\u6cd5\u3001\u89e3\u50cf\u5ea6\u3001\u304a\u3088\u3073\u5883\u754c\u7bc4\u56f2\u3092\u9078\u629e\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u540c\u6642\u306b\u3001\u6b21\u306e\u3053\u3068\u3082\u5fc5\u8981\u3067\u3059\u3002<\/p>\n\n\n\n
                                                                        \"\"\/<\/figure>\n\n\n\n
                                                                        \"gun<\/figure>\n\n\n\n
                                                                        Matplotlib \u306e\u5236\u9650\u3092\u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                                        Matplotlib \u306f\u5f37\u529b\u3067\u5e83\u304f\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3067\u3059\u304c\u3001\u3044\u304f\u3064\u304b\u306e\u5236\u9650\u304c\u3042\u308a\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u3001Matplotlib \u306e\u5236\u9650\u306e\u4e00\u90e8\u3067\u3059\u3002<\/p>\n\n\n\n
                                                                          \n
                                                                        1. \u5bfe\u8a71\u6027\u306e\u6b20\u5982: Matplotlib \u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306f\u9759\u7684\u3067\u3042\u308a\u3001\u5bfe\u8a71\u6027\u304c\u6b20\u5982\u3057\u3066\u304a\u308a\u3001\u8907\u96d1\u306a\u5bfe\u8a71\u64cd\u4f5c\u3092\u5b9f\u73fe\u3067\u304d\u307e\u305b\u3093\u3002<\/li>\n\n\n\n
                                                                        2. \u8907\u96d1\u306a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306e\u63cf\u753b\u304c\u96e3\u3057\u3044: Matplotlib \u306f\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u304c\u3001\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u56f3\u3001\u30c4\u30ea\u30fc\u56f3\u306a\u3069\u306e\u4e00\u90e8\u306e\u8907\u96d1\u306a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306b\u3064\u3044\u3066\u306f\u3001\u4ed6\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u7528\u3059\u308b\u304b\u3001\u624b\u52d5\u3067\u5b9f\u88c5\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                        3. \u7f8e\u5b66\u3092\u6539\u5584\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059: Matplotlib \u306e\u30c7\u30d5\u30a9\u30eb\u30c8 \u30b9\u30bf\u30a4\u30eb\u306f\u6bd4\u8f03\u7684\u5358\u7d14\u3067\u3001\u7f8e\u5b66\u304c\u4f4e\u304f\u3001\u7f8e\u3057\u3044\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3092\u53d6\u5f97\u3059\u308b\u306b\u306f\u3001\u8272\u3001\u7dda\u7a2e\u3001\u30d5\u30a9\u30f3\u30c8\u306a\u3069\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc\u3092\u624b\u52d5\u3067\u8abf\u6574\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                        4. \u81a8\u5927\u306a\u30c7\u30fc\u30bf\u3078\u306e\u5bfe\u5fdc\u4e0d\u8db3\uff1a\u30c7\u30fc\u30bf\u91cf\u304c\u591a\u3044\u5834\u5408\u3001Matplotlib \u306e\u63cf\u753b\u901f\u5ea6\u304c\u9045\u304f\u306a\u3063\u305f\u308a\u3001\u30c7\u30fc\u30bf\u306e\u30d6\u30ed\u30c3\u30af\u63cf\u753b\u306b\u5bfe\u5fdc\u3057\u3066\u3044\u306a\u3044\u305f\u3081\u3001\u30e1\u30e2\u30ea\u4e0d\u8db3\u306a\u3069\u306e\u554f\u984c\u304c\u767a\u751f\u3059\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                        5. 3D \u8996\u899a\u5316\u306e\u30b5\u30dd\u30fc\u30c8\u304c\u4e0d\u5341\u5206: Matplotlib \u306f 3D \u8996\u899a\u5316\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u304c\u3001\u8907\u96d1\u306a 3D \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306e\u5834\u5408\u3001\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u304c\u4f4e\u304f\u3001\u63cf\u753b\u901f\u5ea6\u304c\u9045\u304f\u3001\u3088\u308a\u591a\u304f\u306e\u30b3\u30fc\u30c9\u3092\u8a18\u8ff0\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                        6. \u30c7\u30fc\u30bf\u5206\u6790\u306e\u30b5\u30dd\u30fc\u30c8\u304c\u4e0d\u5341\u5206: Matplotlib \u306f\u3055\u307e\u3056\u307e\u306a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u3092\u63cf\u753b\u3067\u304d\u307e\u3059\u304c\u3001\u30c7\u30fc\u30bf\u306e\u96c6\u8a08\u3084\u7d71\u8a08\u306a\u3069\u306e\u30c7\u30fc\u30bf\u5206\u6790\u6a5f\u80fd\u304c\u7d44\u307f\u8fbc\u307e\u308c\u3066\u3044\u307e\u305b\u3093\u3002<\/li>\n<\/ol>\n\n\n\n
                                                                          \u4e00\u822c\u306b\u3001Matplotlib \u306f\u512a\u308c\u305f\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3067\u3059\u304c\u3001\u9069\u7528\u30d7\u30ed\u30bb\u30b9\u4e2d\u306b\u305d\u306e\u5236\u9650\u306b\u6ce8\u610f\u3092\u6255\u3046\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u540c\u6642\u306b\u3001\u3088\u308a\u826f\u3044\u7d50\u679c\u3092\u5f97\u308b\u305f\u3081\u306b\u3001\u7279\u5b9a\u306e\u30cb\u30fc\u30ba\u306b\u5fdc\u3058\u3066\u9069\u5207\u306a\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3092\u9078\u629e\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                          \"\"\/<\/figure>\n\n\n\n
                                                                          \"gun<\/figure>\n\n\n\n
                                                                          \u8a73\u3057\u304f\u8aac\u660e\u3057\u3066\u304f\u3060\u3055\u3044 \u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3092\u8abf\u3079\u308b<\/p>\n\n\n\n
                                                                          Matplotlib \u306b\u52a0\u3048\u3066\u3001\u4f7f\u7528\u3067\u304d\u308b\u4ed6\u306e\u591a\u304f\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u304c\u3042\u308a\u307e\u3059\u3002\u4e00\u822c\u7684\u306a\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                            \n
                                                                          1. Seaborn<\/code>: Seaborn \u306f\u3001Matplotlib \u306b\u57fa\u3065\u304f\u9ad8\u5ea6\u306a\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3042\u308a\u3001\u3088\u308a\u591a\u304f\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9 \u30bf\u30a4\u30d7\u3068\u30b9\u30bf\u30a4\u30eb\u3092\u63d0\u4f9b\u3057\u3001\u3088\u308a\u8907\u96d1\u306a\u63cf\u753b\u8981\u4ef6\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3001Pandas \u3084 Numpy \u306a\u3069\u306e\u30c7\u30fc\u30bf\u5206\u6790\u30c4\u30fc\u30eb\u3068\u3046\u307e\u304f\u7d71\u5408\u3067\u304d\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                          2. Plotly<\/code>: Plotly \u306f\u3001\u6563\u5e03\u56f3\u3001\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3001\u30d2\u30fc\u30c8 \u30de\u30c3\u30d7\u30013D \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306a\u3069\u3001\u3055\u307e\u3056\u307e\u306a\u30bf\u30a4\u30d7\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306e\u63cf\u753b\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3001Web \u30da\u30fc\u30b8\u3092\u4ecb\u3057\u3066\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306b\u64cd\u4f5c\u3067\u304d\u3001Python\u3001R\u3001JavaScript \u304a\u3088\u3073\u305d\u306e\u4ed6\u306e\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u3092\u30b5\u30dd\u30fc\u30c8\u3059\u308b\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3067\u3059\u3002 .<\/li>\n\n\n\n
                                                                          3. Bokeh<\/code>: Bokeh \u306f\u3001Python \u30d9\u30fc\u30b9\u306e\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3001\u6563\u5e03\u56f3\u3001\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3001\u30d2\u30fc\u30c8 \u30de\u30c3\u30d7\u30013D \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306a\u3069\u3001\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306e\u63cf\u753b\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3001Python\u3001R\u3001Scala\u3001\u7b49 \u8907\u6570\u306e\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u3002<\/li>\n\n\n\n
                                                                          4. Altair<\/code>: Altair \u306f Python \u30d9\u30fc\u30b9\u306e\u5ba3\u8a00\u578b\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3001\u6563\u5e03\u56f3\u3001\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3001\u30d2\u30fc\u30c8 \u30de\u30c3\u30d7\u306a\u3069\u3001\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306e\u63cf\u753b\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3001\u4f7f\u3044\u3084\u3059\u304f\u8aad\u307f\u3084\u3059\u3044\u6a5f\u80fd\u3092\u5099\u3048\u305f Vega-Lite \u69cb\u6587\u3067\u69cb\u6210\u3067\u304d\u307e\u3059\u3002 .<\/li>\n\n\n\n
                                                                          5. ggplot<\/code>: ggplot \u306f R \u8a00\u8a9e\u306b\u57fa\u3065\u304f\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3042\u308a\u3001ggplot2 \u3068\u540c\u69d8\u306e\u69cb\u6587\u3068\u30b9\u30bf\u30a4\u30eb\u3092\u63d0\u4f9b\u3057\u3001\u6563\u5e03\u56f3\u3001\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306a\u3069\u3092\u542b\u3080\u3055\u307e\u3056\u307e\u306a\u7a2e\u985e\u306e\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u306e\u63cf\u753b\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                          6. D3.js<\/code>: D3.js \u306f\u3001Web \u6a19\u6e96\u3068\u6700\u65b0\u306e\u30d6\u30e9\u30a6\u30b6\u30fc\u3092\u30b5\u30dd\u30fc\u30c8\u3059\u308b\u3001\u3055\u307e\u3056\u307e\u306a\u30bf\u30a4\u30d7\u306e\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3068\u30a2\u30cb\u30e1\u30fc\u30b7\u30e7\u30f3\u52b9\u679c\u3092\u4f5c\u6210\u3067\u304d\u308b JavaScript \u30d9\u30fc\u30b9\u306e\u30c7\u30fc\u30bf\u8996\u899a\u5316\u30e9\u30a4\u30d6\u30e9\u30ea\u30fc\u3067\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                                                                            \u8996\u899a\u5316\u30c4\u30fc\u30eb\u306b\u306f\u305d\u308c\u305e\u308c\u7279\u5fb4\u304c\u3042\u308a\u3001\u9577\u6240\u3068\u77ed\u6240\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044.\u9069\u5207\u306a\u30c4\u30fc\u30eb\u3092\u9078\u629e\u3059\u308b\u306b\u306f\u3001\u5b9f\u969b\u306e\u30cb\u30fc\u30ba\u3001\u30c7\u30fc\u30bf\u306e\u7a2e\u985e\u3001\u30c7\u30fc\u30bf\u91cf\u306a\u3069\u306e\u8981\u56e0\u3092\u8003\u616e\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059. \u540c\u6642\u306b\u3001\u3055\u307e\u3056\u307e\u306a\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3092\u7fd2\u5f97\u3059\u308b\u3053\u3068\u3067\u3001\u30c7\u30fc\u30bf\u5206\u6790\u3068\u8996\u899a\u5316\u30bf\u30b9\u30af\u3092\u3088\u308a\u9069\u5207\u306b\u5b8c\u4e86\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                            \"\"\/<\/figure>\n\n\n\n
                                                                            \"gun<\/figure>\n\n\n\n
                                                                            \u30ea\u30bd\u30fc\u30b9\u3092\u8aac\u660e\u3057\u3001\u3055\u3089\u306b\u8a73\u3057\u304f\u8abf\u3079\u3066\u304f\u3060\u3055\u3044<\/p>\n\n\n\n
                                                                            Matplotlib \u3092\u6df1\u304f\u5b66\u3073\u305f\u3044\u5834\u5408\u306f\u3001\u5b66\u7fd2\u30ea\u30bd\u30fc\u30b9\u3068\u63d0\u6848\u3092\u4ee5\u4e0b\u306b\u793a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
                                                                              \n
                                                                            1. \u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8: Matplotlib \u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306b\u306f\u3001\u8a73\u7d30\u306a\u4f7f\u7528\u624b\u9806\u3068\u30b5\u30f3\u30d7\u30eb \u30b3\u30fc\u30c9\u304c\u542b\u307e\u308c\u3066\u304a\u308a\u3001\u3059\u3050\u306b\u958b\u59cb\u3057\u3066\u8a73\u7d30\u3092\u5b66\u7fd2\u3059\u308b\u306e\u306b\u5f79\u7acb\u3061\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                            2. \u30aa\u30f3\u30e9\u30a4\u30f3 \u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb: YouTube \u306e\u6559\u80b2\u30d3\u30c7\u30aa\u3084 GitHub \u306e\u30b5\u30f3\u30d7\u30eb \u30b3\u30fc\u30c9\u306a\u3069\u3001Matplotlib \u306e\u7406\u89e3\u3068\u9069\u7528\u306b\u5f79\u7acb\u3064\u591a\u304f\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3068 Matplotlib \u306e\u4f8b\u3092\u30a4\u30f3\u30bf\u30fc\u30cd\u30c3\u30c8\u3067\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                            3. \u66f8\u7c4d: \u300cPython Data Visualization Technology in Practice\u300d\u3084\u300cPython Data Analysis and Mining in Practice\u300d\u306a\u3069\u3001Matplotlib \u3068\u30c7\u30fc\u30bf\u306e\u8996\u899a\u5316\u3092\u5b66\u3076\u306e\u306b\u5f79\u7acb\u3064\u512a\u308c\u305f\u66f8\u7c4d\u304c\u591a\u6570\u3042\u308a\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                            4. \u5b9f\u8df5\u30d7\u30ed\u30b8\u30a7\u30af\u30c8: \u90fd\u5e02\u306e\u6c17\u8c61\u30c7\u30fc\u30bf\u306e\u30d7\u30ed\u30c3\u30c8\u3001\u682a\u5f0f\u30c7\u30fc\u30bf\u306e\u30d7\u30ed\u30c3\u30c8\u306a\u3069\u3001\u3044\u304f\u3064\u304b\u306e\u5b9f\u8df5\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3092\u5b8c\u4e86\u3057\u3066\u307f\u3066\u304f\u3060\u3055\u3044\u3002\u3053\u308c\u306f\u3001\u5b66\u3093\u3060\u3053\u3068\u3092\u7d71\u5408\u3057\u3001Matplotlib \u306e\u7406\u89e3\u3092\u6df1\u3081\u308b\u306e\u306b\u5f79\u7acb\u3061\u307e\u3059\u3002<\/li>\n\n\n\n
                                                                            5. \u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u306e\u5b66\u7fd2: Matplotlib \u306f\u5f37\u529b\u306a\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3067\u3059\u304c\u3001\u5b9f\u969b\u306e\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u3067\u306f\u3001\u30bf\u30b9\u30af\u3092\u5b8c\u4e86\u3059\u308b\u305f\u3081\u306b\u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3092\u4f7f\u7528\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002\u3057\u305f\u304c\u3063\u3066\u3001Seaborn\u3001Plotly\u3001Bokeh \u306a\u3069\u306e\u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3092\u5b66\u7fd2\u3059\u308b\u3068\u3001\u30c7\u30fc\u30bf\u8996\u899a\u5316\u30bf\u30b9\u30af\u3092\u3088\u308a\u9069\u5207\u306b\u5b8c\u4e86\u3059\u308b\u306e\u306b\u5f79\u7acb\u3061\u307e\u3059\u3002<\/li>\n<\/ol>\n\n\n\n
                                                                              \u8981\u3059\u308b\u306b\u3001Matplotlib \u3092\u7fd2\u5f97\u3059\u308b\u306b\u306f\u7d99\u7d9a\u7684\u306a\u5b9f\u8df5\u3068\u5b66\u7fd2\u304c\u5fc5\u8981\u3067\u3042\u308a\u3001\u7d99\u7d9a\u7684\u306a\u5b9f\u8df5\u3068\u5b9f\u8df5\u3092\u901a\u3058\u3066 Matplotlib \u306e\u4f7f\u7528\u6cd5\u3068\u7279\u6027\u3092\u6df1\u304f\u7406\u89e3\u3057\u3001\u540c\u6642\u306b\u4ed6\u306e\u8996\u899a\u5316\u30c4\u30fc\u30eb\u3092\u5b66\u7fd2\u3057\u3066\u3001\u3055\u307e\u3056\u307e\u306a\u30c7\u30fc\u30bf\u306b\u5bfe\u5fdc\u3067\u304d\u308b\u3088\u3046\u306b\u3059\u308b\u3053\u3068\u3092\u304a\u52e7\u3081\u3057\u307e\u3059\u3002\u53ef\u8996\u5316\u30bf\u30b9\u30af<\/p>\n","protected":false},"excerpt":{"rendered":"
                                                                              \u30c8\u30ea\u30a2\u30eb\u306e\u30c6\u30ad\u30b9\u30c8 \u30b3\u30f3\u30c6\u30f3\u30c4\u3092\u30a6\u30a7\u30d6\u30b5 … <\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_mi_skip_tracking":false,"footnotes":""},"categories":[23],"tags":[],"class_list":["post-1959","post","type-post","status-publish","format-standard","hentry","category-material"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=\/wp\/v2\/posts\/1959","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1959"}],"version-history":[{"count":1,"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=\/wp\/v2\/posts\/1959\/revisions"}],"predecessor-version":[{"id":1960,"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=\/wp\/v2\/posts\/1959\/revisions\/1960"}],"wp:attachment":[{"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1959"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1959"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/edu.ujhb.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1959"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}