{"id":1326,"date":"2023-07-26T20:52:11","date_gmt":"2023-07-26T20:52:11","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/"},"modified":"2023-07-26T20:52:11","modified_gmt":"2023-07-26T20:52:11","slug":"%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/","title":{"rendered":"Matplotlib \u3067\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"

<\/p>\n

\n

\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001\u5358\u4e00\u306e Matplotlib \u30d7\u30ed\u30c3\u30c8\u306b\u8907\u6570\u306e\u884c\u3092\u8868\u793a\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt\n\nplt. plot<\/span> (df[' column1<\/span> '])\nplt. plot<\/span> (df[' column2<\/span> '])\nplt. plot<\/span> (df[' column3<\/span> '])\n\n...\nplt. show<\/span> ()\n<\/strong><\/pre>\n
\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u6b21\u306e pandas DataFrame \u3092\u4f7f\u7528\u3057\u3066\u30c1\u30e3\u30fc\u30c8\u306b\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5\u306e\u4f8b\u3092\u3044\u304f\u3064\u304b\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n
 import numpy<\/span> as np<\/span> \nimport<\/span> pandas as<\/span> pd\n\n#make this example reproducible\n<\/span>n.p. random<\/span> . seeds<\/span> (0)\n\n#create dataset\n<\/span>period = np. arange<\/span> (1, 101, 1)\nleads = np. random<\/span> . uniform<\/span> (1, 50, 100)\nprospects = np. random<\/span> . uniform<\/span> (40, 80, 100)\nsales = 60 + 2*period + np. random<\/span> . normal<\/span> (loc=0, scale=.5*period, size=100)\ndf = pd. DataFrame<\/span> ({' period<\/span> ': period, \n                   ' leads<\/span> ': leads,\n                   ' prospects<\/span> ': prospects,\n                   ' sales<\/span> ': sales})\n\n#view first 10 rows\n<\/span>df. head<\/span> (10)\n\n\n        period leads sales prospects\n0 1 27.891862 67.112661 62.563318\n1 2 36.044279 50.800319 62.920068\n2 3 30.535405 69.407761 64.278797\n3 4 27.699276 78.487542 67.124360\n4 5 21.759085 49.950126 68.754919\n5 6 32.648812 63.046293 77.788596\n6 7 22.441773 63.681677 77.322973\n7 8 44.696877 62.890076 76.350205\n8 9 48.219475 48.923265 72.485540\n9 10 19.788634 78.109960 84.221815\n<\/strong><\/pre>\n
 Matplotlib \u3067\u8907\u6570\u306e\u884c\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b<\/strong><\/span><\/h3>\n
\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001matplotlib \u306e 1 \u3064\u306e\u30d7\u30ed\u30c3\u30c8\u306b 3 \u3064\u306e\u500b\u5225\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span> <\/p>\n
 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt<\/span>\n\n#plot individual lines<\/span>\nplt. plot<\/span> (df[' leads<\/span> '])<\/span>\nplt. plot<\/span> (df[' prospects<\/span> '])<\/span>\nplt. plot<\/span> (df[' sales<\/span> '])\n\n<\/span>#displayplot<\/span>\nplt. show<\/span> ()<\/span>\n<\/span><\/strong><\/pre>\n
\"Matplotlib<\/p>\n
 Matplotlib \u306e\u884c\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b<\/strong><\/span><\/h3>\n
\u5404\u7dda\u306e\u8272\u3001\u30b9\u30bf\u30a4\u30eb\u3001\u5e45\u3092\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span> <\/p>\n
 #plot individual lines with custom colors, styles, and widths<\/span>\nplt. plot<\/span> (df[' leads<\/span> '], color=' green<\/span> ')\nplt. plot<\/span> (df[' prospects<\/span> '], color=' steelblue<\/span> ', linewidth= 4<\/span> )\nplt. plot<\/span> (df[' sales<\/span> '], color=' purple<\/span> ', linestyle=' dashed<\/span> ')\n\n<\/span>#displayplot<\/span>\nplt. show<\/span> ()<\/span><\/span><\/strong> <\/pre>\n
\"Matplotlib<\/p>\n
 Matplotlib \u306b\u51e1\u4f8b\u3092\u8ffd\u52a0\u3059\u308b<\/strong><\/span><\/h3>\n
\u884c\u3092\u533a\u5225\u3059\u308b\u305f\u3081\u306b\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u3092\u8ffd\u52a0\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span> <\/p>\n
 #plot individual lines with custom colors, styles, and widths<\/span>\nplt. plot<\/span> (df[' leads<\/span> '], label=' Leads<\/span> ', color=' green<\/span> ')\nplt. plot<\/span> (df[' prospects<\/span> '], label=' Prospects<\/span> ', color=' steelblue<\/span> ', linewidth= 4<\/span> )\nplt. plot<\/span> (df[' sales<\/span> '], label=' Sales<\/span> ', color=' purple<\/span> ', linestyle=' dashed<\/span> ')\n\n#add legend\nplt. legend<\/span> ()<\/span>\n\n<\/span><\/span>#displayplot<\/span>\nplt. show<\/span> ()<\/span><\/span><\/strong> <\/pre>\n
\"Matplotlib<\/p>\n
 Matplotlib \u306b\u8ef8\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3059\u308b<\/strong><\/span><\/h3>\n
\u6700\u5f8c\u306b\u3001\u8ef8\u30e9\u30d9\u30eb\u3068\u30bf\u30a4\u30c8\u30eb\u3092\u8ffd\u52a0\u3057\u3066\u30d7\u30ed\u30c3\u30c8\u3092\u5b8c\u6210\u3055\u305b\u307e\u3059\u3002<\/span> <\/p>\n
 #plot individual lines with custom colors, styles, and widths<\/span>\nplt. plot<\/span> (df[' leads<\/span> '], label=' Leads<\/span> ', color=' green<\/span> ')\nplt. plot<\/span> (df[' prospects<\/span> '], label=' Prospects<\/span> ', color=' steelblue<\/span> ', linewidth= 4<\/span> )\nplt. plot<\/span> (df[' sales<\/span> '], label=' Sales<\/span> ', color=' purple<\/span> ', linestyle=' dashed<\/span> ')\n\n#add legend\nplt.<\/span> legend<\/span> ()<\/span>\n\n#add axis labels and a title\nplt. ylabel<\/span> (' Sales<\/span> ', fontsize= 14<\/span> )<\/span>\nplt. xlabel<\/span> (' Period<\/span> ', fontsize= 14<\/span> )<\/span>\nplt. title<\/span> (' Company Metrics<\/span> ', fontsize= 16<\/span> )<\/span>\n\n<\/span><\/span>#displayplot<\/span>\nplt. show<\/span> ()<\/span><\/span><\/strong> <\/pre>\n
\"\"<\/p>\n
 \u3053\u3053\u3067<\/a>\u305d\u306e\u4ed6\u306e Matplotlib \u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001\u5358\u4e00\u306e Matplotlib \u30d7\u30ed\u30c3\u30c8\u306b\u8907\u6570\u306e\u884c\u3092\u8868\u793a\u3067\u304d\u307e\u3059\u3002 import matplotlib. pyplot as plt plt. plot (df[‘ column1 ‘]) plt. p […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1326","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nMatplotlib \u3067\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5 - Statorials<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Matplotlib \u3067\u8907\u6570\u306e\u884c\u3092\u30d7\u30ed\u30c3\u30c8\u304a\u3088\u3073\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ja\/\u8907\u6570\u306e\u884c\u3092\u30d5\u309a\u30ed\u30c3\u30c8\u3059\u308b\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Matplotlib \u3067\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5 - Statorials\" \/>\n<meta property=\"og:description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Matplotlib \u3067\u8907\u6570\u306e\u884c\u3092\u30d7\u30ed\u30c3\u30c8\u304a\u3088\u3073\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ja\/\u8907\u6570\u306e\u884c\u3092\u30d5\u309a\u30ed\u30c3\u30c8\u3059\u308b\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-26T20:52:11+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/multmatplotlib1.png\" \/>\n<meta name=\"author\" content=\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u57f7\u7b46\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593\" \/>\n\t<meta name=\"twitter:data2\" content=\"2\u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/\",\"url\":\"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/\",\"name\":\"Matplotlib \u3067\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5 - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/ja\/#website\"},\"datePublished\":\"2023-07-26T20:52:11+00:00\",\"dateModified\":\"2023-07-26T20:52:11+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83\"},\"description\":\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Matplotlib \u3067\u8907\u6570\u306e\u884c\u3092\u30d7\u30ed\u30c3\u30c8\u304a\u3088\u3073\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/#breadcrumb\"},\"inLanguage\":\"ja\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"\u5bb6\",\"item\":\"https:\/\/statorials.org\/ja\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Matplotlib \u3067\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/ja\/#website\",\"url\":\"https:\/\/statorials.org\/ja\/\",\"name\":\"Statorials\",\"description\":\"\u7d71\u8a08\u80fd\u529b\u3078\u306e\u30ac\u30a4\u30c9\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/ja\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"ja\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83\",\"name\":\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ja\",\"@id\":\"https:\/\/statorials.org\/ja\/#\/schema\/person\/image\/\",\"url\":\"http:\/\/statorials.org\/ja\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"http:\/\/statorials.org\/ja\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\"},\"description\":\"\u79c1\u306f\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u3067\u3059\u3002\u9000\u8077\u3057\u305f\u7d71\u8a08\u6559\u6388\u304b\u3089\u3001\u5c02\u4efb\u306e Statorials \u6559\u80b2\u8005\u306b\u306a\u308a\u307e\u3057\u305f\u3002 \u7d71\u8a08\u5206\u91ce\u306b\u304a\u3051\u308b\u8c4a\u5bcc\u306a\u7d4c\u9a13\u3068\u5c02\u9580\u77e5\u8b58\u3092\u6d3b\u304b\u3057\u3066\u3001\u79c1\u306f Statorials \u3092\u901a\u3058\u3066\u5b66\u751f\u306b\u529b\u3092\u4e0e\u3048\u308b\u305f\u3081\u306b\u81ea\u5206\u306e\u77e5\u8b58\u3092\u5171\u6709\u3059\u308b\u3053\u3068\u306b\u5c3d\u529b\u3057\u3066\u3044\u307e\u3059\u3002\u3082\u3063\u3068\u77e5\u308b\",\"sameAs\":[\"http:\/\/statorials.org\/ja\"]}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Matplotlib \u3067\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5 - Statorials","description":"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Matplotlib \u3067\u8907\u6570\u306e\u884c\u3092\u30d7\u30ed\u30c3\u30c8\u304a\u3088\u3073\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/statorials.org\/ja\/\u8907\u6570\u306e\u884c\u3092\u30d5\u309a\u30ed\u30c3\u30c8\u3059\u308b\/","og_locale":"ja_JP","og_type":"article","og_title":"Matplotlib \u3067\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5 - Statorials","og_description":"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Matplotlib \u3067\u8907\u6570\u306e\u884c\u3092\u30d7\u30ed\u30c3\u30c8\u304a\u3088\u3073\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002","og_url":"https:\/\/statorials.org\/ja\/\u8907\u6570\u306e\u884c\u3092\u30d5\u309a\u30ed\u30c3\u30c8\u3059\u308b\/","og_site_name":"Statorials","article_published_time":"2023-07-26T20:52:11+00:00","og_image":[{"url":"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/multmatplotlib1.png"}],"author":"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb","twitter_card":"summary_large_image","twitter_misc":{"\u57f7\u7b46\u8005":"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb","\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593":"2\u5206"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/","url":"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/","name":"Matplotlib \u3067\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5 - Statorials","isPartOf":{"@id":"https:\/\/statorials.org\/ja\/#website"},"datePublished":"2023-07-26T20:52:11+00:00","dateModified":"2023-07-26T20:52:11+00:00","author":{"@id":"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83"},"description":"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Matplotlib \u3067\u8907\u6570\u306e\u884c\u3092\u30d7\u30ed\u30c3\u30c8\u304a\u3088\u3073\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002","breadcrumb":{"@id":"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/#breadcrumb"},"inLanguage":"ja","potentialAction":[{"@type":"ReadAction","target":["https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/statorials.org\/ja\/%e8%a4%87%e6%95%b0%e3%81%ae%e8%a1%8c%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"\u5bb6","item":"https:\/\/statorials.org\/ja\/"},{"@type":"ListItem","position":2,"name":"Matplotlib \u3067\u8907\u6570\u306e\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5"}]},{"@type":"WebSite","@id":"https:\/\/statorials.org\/ja\/#website","url":"https:\/\/statorials.org\/ja\/","name":"Statorials","description":"\u7d71\u8a08\u80fd\u529b\u3078\u306e\u30ac\u30a4\u30c9","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/statorials.org\/ja\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"ja"},{"@type":"Person","@id":"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83","name":"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb","image":{"@type":"ImageObject","inLanguage":"ja","@id":"https:\/\/statorials.org\/ja\/#\/schema\/person\/image\/","url":"http:\/\/statorials.org\/ja\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg","contentUrl":"http:\/\/statorials.org\/ja\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg","caption":"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb"},"description":"\u79c1\u306f\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u3067\u3059\u3002\u9000\u8077\u3057\u305f\u7d71\u8a08\u6559\u6388\u304b\u3089\u3001\u5c02\u4efb\u306e Statorials \u6559\u80b2\u8005\u306b\u306a\u308a\u307e\u3057\u305f\u3002 \u7d71\u8a08\u5206\u91ce\u306b\u304a\u3051\u308b\u8c4a\u5bcc\u306a\u7d4c\u9a13\u3068\u5c02\u9580\u77e5\u8b58\u3092\u6d3b\u304b\u3057\u3066\u3001\u79c1\u306f Statorials \u3092\u901a\u3058\u3066\u5b66\u751f\u306b\u529b\u3092\u4e0e\u3048\u308b\u305f\u3081\u306b\u81ea\u5206\u306e\u77e5\u8b58\u3092\u5171\u6709\u3059\u308b\u3053\u3068\u306b\u5c3d\u529b\u3057\u3066\u3044\u307e\u3059\u3002\u3082\u3063\u3068\u77e5\u308b","sameAs":["http:\/\/statorials.org\/ja"]}]}},"yoast_meta":{"yoast_wpseo_title":"","yoast_wpseo_metadesc":"","yoast_wpseo_canonical":""},"_links":{"self":[{"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/posts\/1326","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/comments?post=1326"}],"version-history":[{"count":0,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/posts\/1326\/revisions"}],"wp:attachment":[{"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/media?parent=1326"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/categories?post=1326"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/tags?post=1326"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}