{"id":74185,"date":"2018-10-02T20:53:29","date_gmt":"2018-10-02T11:53:29","guid":{"rendered":"https:\/\/www.sejuku.net\/blog\/?p=74185"},"modified":"2024-05-06T11:52:27","modified_gmt":"2024-05-06T02:52:27","slug":"%e3%80%90python%e3%80%91matplotlib%e3%81%a7%e8%89%b2%e3%82%93%e3%81%aa%e7%a8%ae%e9%a1%9e%e3%81%ae%e6%a3%92%e3%82%b0%e3%83%a9%e3%83%95%e3%82%92%e8%a1%a8%e7%a4%ba%e3%81%99%e3%82%8b%e6%96%b9%e6%b3%95","status":"publish","type":"post","link":"https:\/\/www.sejuku.net\/blog\/74185","title":{"rendered":"\u3010Python\u3011matplotlib\u3067\u8272\u3093\u306a\u7a2e\u985e\u306e\u68d2\u30b0\u30e9\u30d5\u3092\u8868\u793a\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"\n

\u300c\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u3067\u30c7\u30fc\u30bf\u3092\u53ef\u8996\u5316\u3057\u305f\u3044\u300d
\u300c\u68d2\u30b0\u30e9\u30d5\u3092\u30d7\u30ed\u30b0\u30e9\u30e0\u3067\u63cf\u753b\u3057\u305f\u3044\u300d<\/p>\n\n\n\n

\u305d\u3093\u306a\u3053\u3068\u3092\u8003\u3048\u305f\u3053\u3068\u306f\u3042\u308a\u307e\u305b\u3093\u304b\uff1f<\/p>\n\n\n\n

\u3053\u306e\u8a18\u4e8b\u3067\u306fPython\u3092\u4f7f\u3063\u3066\u3001\u30c7\u30fc\u30bf\u3092\u68d2\u30b0\u30e9\u30d5\u3067\u63cf\u753b\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u89e3\u8aac\u3057\u307e\u3059\u3002<\/p>\n\n\n\n


\u3010\u57fa\u790e\u3011\u7c21\u5358\u306a\u68d2\u30b0\u30e9\u30d5\u306e\u63cf\u753b\u65b9\u6cd5
\u3010\u57fa\u790e\u3011\u8272\u3084\u592a\u3055\u306a\u3069\u306e\u7d30\u304b\u3044\u8abf\u6574\u65b9\u6cd5
\u3010\u767a\u5c55\u30112D\u3060\u3051\u3067\u306a\u304f3D\u3067\u68d2\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u65b9\u6cd5
<\/p>\n\n\n\n

\u3068\u3044\u3063\u305f\u57fa\u790e\u304b\u3089\u5b9f\u8df5\u307e\u3067\u5f79\u7acb\u3064\u767a\u5c55\u7684\u306a\u5185\u5bb9\u3082\u89e3\u8aac\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

\u203b \u3053\u306e\u8a18\u4e8b\u306e\u30b3\u30fc\u30c9\u306fPython 3.7\u3067\u52d5\u4f5c\u78ba\u8a8d\u3057\u307e\u3057\u305f\u3002<\/strong><\/span><\/p>\n\n\n\n

\u672c\u8a18\u4e8b\u3092\u8aad\u3080\u524d\u306b\u3001Python\u304c\u3069\u3093\u306a\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u306a\u306e\u304b\u3092\u304a\u3055\u3089\u3044\u3057\u3066\u304a\u304d\u305f\u3044\u4eba\u306f\u6b21\u306e\u8a18\u4e8b\u3092\u53c2\u8003\u306b\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n

\u2192 Python\u3068\u306f\uff1f\u7279\u5fb4\u3084\u3067\u304d\u308b\u3053\u3068\u3001\u6d3b\u7528\u4f8b\u3092\u308f\u304b\u308a\u3084\u3059\u304f\u7c21\u5358\u306b\u89e3\u8aac<\/a><\/p>\n\n\n\n

\u306a\u304a\u3001\u305d\u306e\u4ed6\u306ePython\u306e\u8a18\u4e8b\u306b\u3064\u3044\u3066\u306f\u3053\u3061\u3089<\/a>\u306b\u307e\u3068\u3081\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

python\u3067\u68d2\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u3066\u307f\u3088\u3046<\/h2>\n\n\n\n

Excel\u7b49\u306e\u30bd\u30d5\u30c8\u3092\u4f7f\u3048\u3070\u7c21\u5358\u306b\u68d2\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n

\u3057\u304b\u3057\u3042\u308b\u30c7\u30fc\u30bf\u306b\u5bfe\u3057\u3066\u68d2\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3057\u3088\u3046\u3068\u8003\u3048\u305f\u3068\u304d\u3001\u308f\u3056\u308f\u3056\u8868\u8a08\u7b97\u30bd\u30d5\u30c8\u306b\u30c7\u30fc\u30bf\u3092\u79fb\u3057\u3066\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3059\u308b\u3088\u308a\u3082\u3001\u30d7\u30ed\u30b0\u30e9\u30e0\u304b\u3089\u76f4\u63a5\u4f5c\u6210\u3067\u304d\u305f\u65b9\u304c\u4fbf\u5229\u3067\u3059\u3002<\/p>\n\n\n\n

Python\u3092\u4f7f\u3063\u305f\u30b0\u30e9\u30d5\u306e\u4f5c\u6210\u3082\u3001\u4fbf\u5229\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u3046\u3053\u3068\u3067\u7c21\u5358\u306b\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n

\u305d\u3053\u3067Python\u3067\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u3068\u304d\u306b\u3088\u304f\u4f7f\u308f\u308c\u308bmatplotlib\u3068\u3044\u3046\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u3063\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n\n\n\n

matplotlib\u3068\u306f\uff1f<\/h3>\n\n\n\n

matplotlib\u3092\u4f7f\u3046\u3053\u3068\u3067\u3001\u7c21\u5358\u306b\u30c7\u30fc\u30bf\u3092\u30b0\u30e9\u30d5\u306b\u30d7\u30ed\u30c3\u30c8\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n\n\n

\u3082\u3057\u304a\u4f7f\u3044\u306ePC\u306bmatplotlib\u304c\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3066\u3044\u306a\u3051\u308c\u3070\u3001\u307e\u305a\u306f\u30bf\u30fc\u30df\u30ca\u30eb\u4e0a\u3067\u6b21\u306e\u30b3\u30de\u30f3\u30c9\u3092\u6253\u3061\u307e\u3057\u3087\u3046\u3002<\/p>\n\n\n\n

\uff08\u203bPython\u30d7\u30ed\u30b0\u30e9\u30e0\u4e2d\u3067import matplotlib\u3068\u66f8\u3044\u305f\u3068\u304d\u306bModuleNotFoundError<\/strong><\/span>\u304c\u51fa\u308c\u3070\u3001\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3066\u3044\u306a\u3044\u53ef\u80fd\u6027\u304c\u9ad8\u3044\u3067\u3059\uff09<\/p>\n\n\n\n

pip install matplotlib<\/pre>\n\n\n\n
\u6700\u8fd1\u306fPython\u3092\u76f4\u63a5\u5165\u308c\u305a\u306bAnaconda\u3068\u3044\u3046\u30c7\u30fc\u30bf\u5206\u6790\u306b\u95a2\u3059\u308b\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u542b\u3093\u3060\u958b\u767a\u74b0\u5883\u3092\u4e38\u3054\u3068\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u3053\u3068\u304c\u591a\u304f\u306a\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n
Anaconda\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u3066\u3044\u308c\u3070matplotlib\u3082\u540c\u6642\u306b\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3066\u3044\u308b\u305f\u3081\u3001\u308f\u3056\u308f\u3056matplotlib\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u5fc5\u8981\u306f\u3042\u308a\u307e\u305b\u3093\u3002<\/p>\n\n\n\n
matplotlib\u3092\u4f7f\u3046\u306b\u306f\u3001\u30d7\u30ed\u30b0\u30e9\u30e0\u306b\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u8a18\u8ff0\u304c\u5fc5\u8981\u3067\u3059\u3002<\/p>\n\n\n\n
\u65e9\u901fmatplotlib\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3066\u307f\u307e\u3057\u3087\u3046\uff01<\/p>\n\n\n\n
import matplotlib.pyplot as plt<\/pre>\n\n\n\n
\u3053\u308c\u306fmatplotlib.pyplot\u30e2\u30b8\u30e5\u30fc\u30eb\u3092plt\u3068\u3044\u3046\u540d\u524d\u3067\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n
\u30a4\u30f3\u30dd\u30fc\u30c8\u306f\u30d7\u30ed\u30b0\u30e9\u30e0\u306e\u6700\u521d\u306b\u66f8\u3051\u3070\u826f\u3044\u305f\u3081\u3001\u4f55\u5ea6\u3082\u540c\u3058\u30b3\u30fc\u30c9\u3092\u66f8\u304f\u5fc5\u8981\u306f\u3042\u308a\u307e\u305b\u3093\u3002<\/p>\n\n\n\n
\u3067\u3059\u304c\u3001\u4ee5\u964d\u306e\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9\u306f\u5225\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\uff08\u30e2\u30b8\u30e5\u30fc\u30eb\uff09\u3067\u3042\u308b\u3053\u3068\u3092\u60f3\u5b9a\u3057\u3066\u3044\u308b\u305f\u3081\u3001\u6bce\u56deimport\u3092\u884c\u3063\u3066\u3044\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n
\u7c21\u5358\u306a\u68d2\u30b0\u30e9\u30d5<\/h3>\n\n\n\n
\u305d\u308c\u3067\u306f\u65e9\u901f\u3001\u68d2\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u3066\u307f\u307e\u3057\u3087\u3046\uff01<\/p>\n\n\n\n
import matplotlib.pyplot as plt\n\nleft = [1, 2, 3]  # \u30b0\u30e9\u30d5\u306e\u6a2a\u8ef8\uff08X\u8ef8\uff09\nheight = [3, 5, 0]  # \u5024\uff08Y\u8ef8\uff09\n\nplt.bar(left, height)\nplt.show()<\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\u3053\u306e\u30b3\u30fc\u30c9\u3067\u306f\u5909\u6570left\u306b\u6a2a\u5ea7\u6a19\u3001\u5909\u6570height\u306b\u7e26\u5ea7\u6a19\u3092\u5165\u308c\u3001plt.bar()\u306e\u5f15\u6570\u3068\u3057\u3066\u3044\u307e\u3059\u3002\u68d2\u30b0\u30e9\u30d5\u306e\u898b\u305f\u76ee\u3092\u5909\u66f4\u3059\u308b\u306b\u306f\u3001\u540c\u3058\u3088\u3046\u306bbar\u95a2\u6570\u306e\u5f15\u6570\u3092\u6307\u5b9a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
\u8a66\u3057\u306b\u3001\u540c\u3058\u30c7\u30fc\u30bf\u3067\u68d2\u30b0\u30e9\u30d5\u3092\u8d64\u8272\u306b\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n\n\n\n
import matplotlib.pyplot as plt\n\nleft = [1, 2, 3]  # \u30b0\u30e9\u30d5\u306e\u6a2a\u8ef8\uff08X\u8ef8\uff09\nheight = [3, 5, 0]  # \u5024\uff08Y\u8ef8\uff09\n\nplt.bar(left, height, color='r')\nplt.show()<\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
bar\u95a2\u6570\u306e\u5f15\u6570\u3068\u3057\u3066color\u3092r\uff08red\uff09\u306b\u3057\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
\u4ed6\u306b\u3082<\/p>\n\n\n\n

width\u3067\u68d2\u306e\u5e45
edgecolor\u3067\u67a0\u7dda\u306e\u8272
linewidth\u3067\u67a0\u7dda\u306e\u592a\u3055
tick_label\u3067\u6a2a\u8ef8\u306e\u30e9\u30d9\u30eb
<\/p>\n\n\n\n
\u306a\u3069\u304c\u6307\u5b9a\u3067\u304d\u307e\u3059\uff01<\/p>\n\n\n\n
\u3067\u306f\u5b9f\u969b\u306b\u30b3\u30fc\u30c9\u3092\u66f8\u3044\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n\n\n\n
import matplotlib.pyplot as plt\n\nleft = [1, 2, 3, 4, 5]\nheight = [80, 65, 100, 42, 54]  # \u70b9\u6570\nlabels = ['Japanese', 'Math', 'Science', 'Social', 'English']\n\nplt.bar(left, height, width=0.5, color='#0096c8',\n        edgecolor='b', linewidth=2, tick_label=labels)\nplt.show()<\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\u3053\u306e\u30b5\u30f3\u30d7\u30eb\u306f5\u6559\u79d1\u306e\u70b9\u6570\u3092\u68d2\u30b0\u30e9\u30d5\u3067\u8868\u793a\u3057\u3066\u3044\u307e\u3059\u3002labels\u3068\u3044\u3046\u5909\u6570\u306b5\u6559\u79d1\u306e\u540d\u79f0\u3092\u5165\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n
\u307e\u305f\u3001\u5148\u307b\u3069\u3068\u306f\u9055\u3044color\u306br\u3084b\u306a\u3069\u3067\u306f\u306a\u304f\u3001\u30ab\u30e9\u30fc\u30b3\u30fc\u30c9\u3092\u76f4\u63a5\u6307\u5b9a\u3057\u3066\u3044\u307e\u3059\u306d\u3002\u30ab\u30e9\u30fc\u30b3\u30fc\u30c9\u3092\u76f4\u63a5\u6307\u5b9a\u3059\u308c\u3070\u7d30\u304b\u3044\u8272\u306e\u8abf\u7bc0\u3082\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
\u3053\u3053\u3067\u306fplt.bar()\u306e\u5f15\u6570\u306balign\u3092\u6307\u5b9a\u3057\u3066\u3044\u307e\u305b\u3093\u3002\u3082\u3057\u540c\u3058\u3088\u3046\u306a\u30b0\u30e9\u30d5\u306b\u306a\u3089\u305a\u3001\u68d2\u30b0\u30e9\u30d5\u304c\u5de6\u306b\u5bc4\u3063\u3066\u3044\u305f\u308a\u3059\u308b\u5834\u5408\u306b\u306falign=\u2019center\u2019\u3092\u5f15\u6570\u306b\u8ffd\u52a0\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n
\u8272\u3093\u306a\u5f62\u3067\u63cf\u753b\u3057\u3066\u307f\u3088\u3046<\/h2>\n\n\n\n
\u3053\u3053\u307e\u3067\u68d2\u30b0\u30e9\u30d5\u306e\u8272\u3084\u592a\u3055\u306e\u6307\u5b9a\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u3066\u304d\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
\u6b21\u306f\u30c7\u30fc\u30bf\u3092\u8907\u6570\u4f7f\u3063\u3066\u63cf\u753b\u3059\u308b\u65b9\u6cd5\u3092\u898b\u3066\u3044\u304d\u307e\u3057\u3087\u3046\uff01<\/p>\n\n\n\n
\u8907\u6570\u306e\u68d2\u30b0\u30e9\u30d5\u3092\u6a2a\u306b\u4e26\u3079\u308b<\/h3>\n\n\n\n
\u5148\u7a0b\u3068\u540c\u3058\u3088\u3046\u306b\u30015\u6559\u79d1\u306e\u70b9\u6570\u3092\u68d2\u30b0\u30e9\u30d5\u3067\u63cf\u753b\u3057\u305f\u3044\u3068\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n\n\n\n
\u3053\u306e\u3068\u304d\u3001\u4ed6\u306e\u4eba\u3068\u70b9\u6570\u3092\u6bd4\u3079\u305f\u3044\u3068\u601d\u3063\u305f\u3089\u3001\u6a2a\u306b\u30b0\u30e9\u30d5\u304c2\u3064\u4e26\u3093\u3067\u3044\u305f\u65b9\u304c\u4fbf\u5229\u3067\u3059\u3088\u306d\uff1f<\/p>\n\n\n\n
\u305d\u308c\u3067\u306f\u65e9\u901f\u30012\u3064\u306e\u30c7\u30fc\u30bf\u304b\u3089\u68d2\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3057\u3066\u307f\u307e\u3057\u3087\u3046\uff01<\/p>\n\n\n\n
\u65b0\u3057\u3044\u30d7\u30ed\u30b0\u30e9\u30e0\u304c\u3044\u304f\u3064\u304b\u51fa\u3066\u304d\u307e\u3059\u304c\u3001\u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u63d0\u793a\u3057\u305f\u5f8c\u306b\u89e3\u8aac\u3057\u307e\u3059\u306e\u3067\u3001\u8aad\u307f\u9032\u3081\u3066\u307f\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n
import matplotlib.pyplot as plt\nimport numpy as np\n\nheight1 = [80, 65, 100, 42, 54]  # \u70b9\u65701\nheight2 = [55, 100, 98, 30, 21]  # \u70b9\u65702\n\nleft = np.arange(len(height1))  # numpy\u3067\u6a2a\u8ef8\u3092\u8a2d\u5b9a\nlabels = ['Japanese', 'Math', 'Science', 'Social', 'English']\n\nwidth = 0.3\n\nplt.bar(left, height1, color='r', width=width, align='center')\nplt.bar(left+width, height2, color='b', width=width, align='center')\n\nplt.xticks(left + width\/2, labels)\nplt.show()<\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
2\u4eba\u306e\u70b9\u6570\u304c\u6a2a\u306b\u4e26\u3093\u3067\u3044\u307e\u3059\u306d\uff01<\/p>\n\n\n\n
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\u305d\u3053\u3067np.arange()\u3092\u4f7f\u3063\u3066height1\u306e\u8981\u7d20\u306e\u6570\u3060\u3051\u9023\u756a\u3092\u4f5c\u6210\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n
\u307e\u305f\u3001plt.xticks()\u3092\u4f7f\u3063\u3066left\u3092\u68d2\u30b0\u30e9\u30d5\u306e\u5e45\u306e1\/2\u3060\u3051\u8db3\u3059\u3053\u3068\u306b\u3088\u3063\u3066\u3001\u30e9\u30d9\u30eb\u306e\u4f4d\u7f6e\u30922\u3064\u306e\u68d2\u30b0\u30e9\u30d5\u306e\u4e2d\u5fc3\u306b\u306a\u308b\u3088\u3046\u306b\u8a2d\u5b9a\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n
\u6a2a\u5411\u304d\u306b\u68d2\u30b0\u30e9\u30d5\u3092\u8868\u793a\u3059\u308b<\/h3>\n\n\n\n
\u6b21\u306f\u6a2a\u5411\u304d\u306b\u68d2\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n\n\n\n
import matplotlib.pyplot as plt\nimport numpy as np\n\nheight1 = [80, 65, 100, 42, 54]  # \u70b9\u65701\nheight2 = [55, 100, 98, 30, 21]  # \u70b9\u65702\n\nleft = np.arange(len(height1))  # numpy\u3067\u6a2a\u8ef8\u3092\u8a2d\u5b9a\nlabels = ['Japanese', 'Math', 'Science', 'Social', 'English']\n\nheight = 0.3\n\nplt.barh(left, height1, color='r', height=height, align='center')\nplt.barh(left+height, height2, color='b', height=height, align='center')\n\nplt.yticks(left + height\/2, labels)\nplt.show()<\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\u5148\u7a0b\u306e\u30b3\u30fc\u30c9\u3068\u307b\u307c\u540c\u3058\u3067\u3059\u3002\u9055\u3046\u306e\u306fplt.bar()\u3067\u306f\u306a\u304fplt.barh()\u3092\u4f7f\u3063\u3066\u3044\u308b\u3068\u3044\u3046\u3053\u3068\u3067\u3059\u3002\u3053\u308c\u306b\u3088\u3063\u3066\u6a2a\u5411\u304d\u306e\u30b0\u30e9\u30d5\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
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3D\u3067\u68d2\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3057\u3066\u307f\u3088\u3046<\/h2>\n\n\n\n
\u4eca\u307e\u3067X,Y\u8ef8\u306e\u307f\u3067\u30b0\u30e9\u30d5\u3092\u8868\u793a\u3057\u3066\u304d\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
\u6700\u5f8c\u306bZ\u8ef8\u3092\u5897\u3084\u3057\u3066\u30b0\u30e9\u30d5\u3092\u8868\u793a\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n\n\n\n
from mpl_toolkits.mplot3d import Axes3D\nimport numpy as np\n\nleft = [1, 2, 3, 4, 5]\nheight = [2, 4, 8, 16, 32]\n\nfig = plt.figure()\nax = fig.add_subplot(111, projection='3d')\n\nax.bar(left, height, zs=0, zdir='y')\n\nax.set_xlabel('X')\nax.set_ylabel('Y')\nax.set_zlabel('Z')\n\nplt.show()<\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
3D\u3067\u63cf\u753b\u3059\u308b\u305f\u3081\u306bAxes3D\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002Axes3D\u3092\u4f7f\u3046\u305f\u3081\u306b\u6700\u521d\u306bfig\u3068ax\u3092\u5ba3\u8a00\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n
\u68d2\u30b0\u30e9\u30d5\u306f\u4eca\u307e\u3067\u3068\u540c\u69d8\u306bbar()\u3067\u63cf\u753b\u3067\u304d\u307e\u3059\u3002\u305f\u3060\u3057ax.bar()\u3067\u3059\u306d\u3002<\/p>\n\n\n\n
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mplot3d\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb<\/a><\/p>\n\n\n\n
\u307e\u3068\u3081<\/h2>\n\n\n\n
\u4eca\u56de\u306f\u3001python\u306ematplotlib\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u3063\u3066\u68d2\u30b0\u30e9\u30d5\u3092\u63cf\u753b\u3059\u308b\u65b9\u6cd5\u3092\u7d39\u4ecb\u3057\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
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[…]<\/p>\n","protected":false},"author":4,"featured_media":74602,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"swell_btn_cv_data":"","footnotes":""},"categories":[2350],"tags":[],"class_list":["post-74185","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python-study"],"acf":[],"yoast_head":"\n\u3010Python\u3011matplotlib\u3067\u8272\u3093\u306a\u7a2e\u985e\u306e\u68d2\u30b0\u30e9\u30d5\u3092\u8868\u793a\u3059\u308b\u65b9\u6cd5 | \u4f8d\u30a8\u30f3\u30b8\u30cb\u30a2\u30d6\u30ed\u30b0<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u8a18\u4e8b\u3067\u306f\u300c \u3010Python\u3011matplotlib\u3067\u8272\u3093\u306a\u7a2e\u985e\u306e\u68d2\u30b0\u30e9\u30d5\u3092\u8868\u793a\u3059\u308b\u65b9\u6cd5 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