{"id":28600,"date":"2024-03-18T18:18:00","date_gmt":"2024-03-18T09:18:00","guid":{"rendered":"https:\/\/www.silicloud.com\/ja\/blog\/python%e3%81%aeplt-hist%e9%96%a2%e6%95%b0%e3%81%ae%e4%bd%bf%e3%81%84%e6%96%b9%e3%81%af%e4%bd%95%e3%81%a7%e3%81%99%e3%81%8b%ef%bc%9f\/"},"modified":"2024-03-22T18:58:54","modified_gmt":"2024-03-22T09:58:54","slug":"python%e3%81%aeplt-hist%e9%96%a2%e6%95%b0%e3%81%ae%e4%bd%bf%e3%81%84%e6%96%b9%e3%81%af%e4%bd%95%e3%81%a7%e3%81%99%e3%81%8b%ef%bc%9f","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/ja\/blog\/python%e3%81%aeplt-hist%e9%96%a2%e6%95%b0%e3%81%ae%e4%bd%bf%e3%81%84%e6%96%b9%e3%81%af%e4%bd%95%e3%81%a7%e3%81%99%e3%81%8b%ef%bc%9f\/","title":{"rendered":"Python\u306eplt.hist\u95a2\u6570\u306e\u4f7f\u3044\u65b9\u306f\u4f55\u3067\u3059\u304b\uff1f"},"content":{"rendered":"

Python\u306eplt.hist()\u306f\u3001matplotlib\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3067\u3042\u308a\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306f\u3001\u30c7\u30fc\u30bf\u306e\u5206\u5e03\u3092\u8868\u3059\u7d71\u8a08\u30b0\u30e9\u30d5\u306e\u4e00\u7a2e\u3067\u3059\u3002<\/p>\n

plt.hist() \u95a2\u6570\u306e\u4f7f\u7528\u6cd5\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\uff1a<\/p>\n

x\u3092\u542b\u3080\u30c7\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002bins\u306b\u306f\u30d3\u30f3\u306e\u6570\u3092\u6307\u5b9a\u3057\u3001range\u306b\u306f\u30c7\u30fc\u30bf\u306e\u7bc4\u56f2\u3092\u6307\u5b9a\u3057\u307e\u3059\u3002density\u3084weights\u3092\u4f7f\u7528\u3057\u3066\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u5f62\u72b6\u3092\u8abf\u6574\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002cumulative\u3092True\u306b\u3059\u308b\u3068\u7d2f\u7a4d\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306b\u306a\u308a\u307e\u3059\u3002histtype\u3067\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u5f62\u5f0f\u3092\u6307\u5b9a\u3057\u3001\u8272\u3084\u30e9\u30d9\u30eb\u306a\u3069\u3082\u8a2d\u5b9a\u3067\u304d\u307e\u3059\u3002<\/p>\n

\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u8aac\u660e\uff1a<\/p>\n

    \n
  1. x: \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306f\u3001\u4e00\u6b21\u5143\u914d\u5217\u307e\u305f\u306f\u30b7\u30fc\u30b1\u30f3\u30b9\u306e\u30b3\u30ec\u30af\u30b7\u30e7\u30f3\u3067\u3042\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/li>\n
  2. bins\u306e\u5024\u306f\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u68d2\u306e\u6570\u3067\u3042\u308a\u3001\u30c7\u30d5\u30a9\u30eb\u30c8\u306f10\u3067\u3059\u3002<\/li>\n
  3. \u7bc4\u56f2\uff1a\u6307\u5b9a\u3055\u308c\u305f\u30c7\u30fc\u30bf\u306e\u7bc4\u56f2\u3001\u30c7\u30d5\u30a9\u30eb\u30c8\u306fNone\u3067\u3042\u308a\u3001\u30c7\u30fc\u30bf\u306e\u6700\u5927\u5024\u3068\u6700\u5c0f\u5024\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/li>\n
  4. \u5bc6\u5ea6\uff1a\u76f4\u65b9\u30b0\u30e9\u30e0\u306e\u5ea6\u6570\u3092\u78ba\u7387\u5bc6\u5ea6\u306b\u5909\u63db\u3059\u308b\u304b\u3069\u3046\u304b\u3002\u30c7\u30d5\u30a9\u30eb\u30c8\u306fFalse\u3067\u3059\u3002<\/li>\n
  5. weights: \u6307\u5b9a\u306e\u68d2\u30b0\u30e9\u30d5\u306e\u91cd\u307f\u3001\u30c7\u30d5\u30a9\u30eb\u30c8\u306fNone\u3002<\/li>\n
  6. \u7d2f\u7a4d\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3059\u308b\u304b\u3069\u3046\u304b\u3001\u30c7\u30d5\u30a9\u30eb\u30c8\u306fFalse\u3067\u3059\u3002<\/li>\n
  7. \u5e95\u90e8\uff1a\u67f1\u306e\u958b\u59cb\u4f4d\u7f6e\u306e\u30c7\u30d5\u30a9\u30eb\u30c8\u306fNone\u3067\u3059\u3002<\/li>\n
  8. histtype\uff1a\u76f4\u65b9\u56f3\u306e\u7a2e\u985e\u3002\u30c7\u30d5\u30a9\u30eb\u30c8\u5024\u306f’bar’\u3067\u3001\u9078\u629e\u80a2\u306f’bar’\u3001’barstacked’\u3001’step’\u3001’stepfilled’\u304c\u3042\u308a\u307e\u3059\u3002<\/li>\n
  9. alignment: \u57fa\u6e96\u3068\u306a\u308b\u67f1\u306e\u4f4d\u7f6e\u63c3\u3048\u65b9\u3002\u30c7\u30d5\u30a9\u30eb\u30c8\u306f\u300cmid\u300d\u3067\u3001\u30aa\u30d7\u30b7\u30e7\u30f3\u5024\u306f\u300cleft\u300d\u300cmid\u300d\u300cright\u300d\u304c\u9078\u3079\u307e\u3059\u3002<\/li>\n
  10. \u65b9\u5411\uff1a\u67f1\u306e\u65b9\u5411\u3001\u30c7\u30d5\u30a9\u30eb\u30c8\u306f\u300cvertical\u300d\u3067\u3001\u9078\u629e\u80a2\u306f\u300chorizontal\u300d\u3067\u3059\u3002<\/li>\n
  11. rwidth\uff1a\u30c7\u30d5\u30a9\u30eb\u30c8\u306fNone\u3067\u3001\u68d2\u30b0\u30e9\u30d5\u306e\u5e45\u306e\u5272\u5408\u3092\u6307\u5b9a\u3057\u307e\u3059\u3002<\/li>\n
  12. \u30ed\u30b0\uff1a\u8ef8\u3092\u5bfe\u6570\u30b9\u30b1\u30fc\u30eb\u306b\u8a2d\u5b9a\u3057\u307e\u3059\u304b\uff1f\u30c7\u30d5\u30a9\u30eb\u30c8\u306fFalse\u3067\u3059\u3002<\/li>\n
  13. \u8272\uff1a\u67f1\u306e\u3088\u3046\u306a\u8272\u3002<\/li>\n
  14. \u30e9\u30d9\u30eb\uff1a\u30bf\u30b0\u306e\u30c6\u30ad\u30b9\u30c8\u3002<\/li>\n
  15. \u30b9\u30bf\u30c3\u30af\u3055\u308c\u3066\u3044\u308b\uff1a\u68d2\u30b0\u30e9\u30d5\u3092\u7a4d\u307f\u91cd\u306d\u308b\u304b\u3069\u3046\u304b\u3001\u30c7\u30d5\u30a9\u30eb\u30c8\u306fFalse\u3067\u3059\u3002<\/li>\n
  16. normed\uff1a\u3053\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306f\u5ec3\u6b62\u3055\u308c\u307e\u3057\u305f\u3002\u4ee3\u308f\u308a\u306bdensity\u3092\u4f7f\u7528\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/li>\n<\/ol>\n

    \u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9\uff1a<\/p>\n

    import<\/span> matplotlib.pyplot as<\/span> plt\r\nimport<\/span> numpy as<\/span> np\r\n\r\n# \u751f\u6210\u968f\u673a\u6570\u636e<\/span>\r\nnp.random.seed(0<\/span>)\r\ndata = np.random.randn(1000<\/span>)\r\n\r\n# \u7ed8\u5236\u76f4\u65b9\u56fe<\/span>\r\nplt.hist(data, bins=30<\/span>, density=True<\/span>, alpha=0.7<\/span>, color='steelblue'<\/span>, edgecolor='black'<\/span>)\r\n\r\n# \u8bbe\u7f6e\u6807\u9898\u548c\u8f74\u6807\u7b7e<\/span>\r\nplt.title('Histogram'<\/span>)\r\nplt.xlabel('Value'<\/span>)\r\nplt.ylabel('Frequency'<\/span>)\r\n\r\n# \u663e\u793a\u56fe\u5f62<\/span>\r\nplt.show()\r\n<\/code><\/pre>\n
    \u3053\u306e\u30b3\u30fc\u30c9\u306f\u30011000\u500b\u306e\u30e9\u30f3\u30c0\u30e0\u30c7\u30fc\u30bf\u3092\u542b\u3080\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u751f\u6210\u3057\u307e\u3059\u3002data\u306f\u5165\u529b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u3001bins\u306f\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u30d0\u30fc\u306e\u6570\u3092\u6307\u5b9a\u3057\u3001density\u306f\u5ea6\u6570\u3092\u78ba\u7387\u5bc6\u5ea6\u306b\u5909\u63db\u3057\u3001alpha\u306f\u30d0\u30fc\u306e\u900f\u660e\u5ea6\u3092\u6307\u5b9a\u3057\u3001color\u306f\u30d0\u30fc\u306e\u8272\u3092\u6307\u5b9a\u3057\u3001edgecolor\u306f\u30d0\u30fc\u306e\u67a0\u7dda\u306e\u8272\u3092\u6307\u5b9a\u3057\u307e\u3059\u3002\u6700\u5f8c\u306b\u3001\u30bf\u30a4\u30c8\u30eb\u3068\u8ef8\u30e9\u30d9\u30eb\u3092\u8a2d\u5b9a\u3057\u3001plt.show()\u95a2\u6570\u3092\u547c\u3073\u51fa\u3057\u3066\u30b0\u30e9\u30d5\u3092\u8868\u793a\u3057\u307e\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
    Python\u306eplt.hist()\u306f\u3001matplotlib\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3067\u3042\u308a\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306f\u3001\u30c7\u30fc\u30bf\u306e\u5206\u5e03\u3092\u8868\u3059\u7d71\u8a08\u30b0\u30e9\u30d5\u306e\u4e00\u7a2e\u3067\u3059\u3002 plt.hist() \u95a2\u6570\u306e\u4f7f\u7528\u6cd5\u306f […]<\/p>\n","protected":false},"author":11,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-28600","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\nPython\u306eplt.hist\u95a2\u6570\u306e\u4f7f\u3044\u65b9\u306f\u4f55\u3067\u3059\u304b\uff1f - Blog - Silicon Cloud<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.silicloud.com\/ja\/blog\/python\u306eplt-hist\u95a2\u6570\u306e\u4f7f\u3044\u65b9\u306f\u4f55\u3067\u3059\u304b\uff1f\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python\u306eplt.hist\u95a2\u6570\u306e\u4f7f\u3044\u65b9\u306f\u4f55\u3067\u3059\u304b\uff1f\" \/>\n<meta property=\"og:description\" content=\"Python\u306eplt.hist()\u306f\u3001matplotlib\u30e9\u30a4\u30d6\u30e9\u30ea\u5185\u306e\u95a2\u6570\u3067\u3042\u308a\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u63cf\u753b\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306f\u3001\u30c7\u30fc\u30bf\u306e\u5206\u5e03\u3092\u8868\u3059\u7d71\u8a08\u30b0\u30e9\u30d5\u306e\u4e00\u7a2e\u3067\u3059\u3002 plt.hist() \u95a2\u6570\u306e\u4f7f\u7528\u6cd5\u306f […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.silicloud.com\/ja\/blog\/python\u306eplt-hist\u95a2\u6570\u306e\u4f7f\u3044\u65b9\u306f\u4f55\u3067\u3059\u304b\uff1f\/\" \/>\n<meta property=\"og:site_name\" content=\"Blog - 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