{"id":3835,"date":"2023-07-15T06:06:23","date_gmt":"2023-07-15T06:06:23","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae-2-%e3%81%a4%e3%81%ae%e7%b8%a6%e6%a3%92%e3%82%af%e3%82%99%e3%83%a9%e3%83%95\/"},"modified":"2023-07-15T06:06:23","modified_gmt":"2023-07-15T06:06:23","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae-2-%e3%81%a4%e3%81%ae%e7%b8%a6%e6%a3%92%e3%82%af%e3%82%99%e3%83%a9%e3%83%95","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae-2-%e3%81%a4%e3%81%ae%e7%b8%a6%e6%a3%92%e3%82%af%e3%82%99%e3%83%a9%e3%83%95\/","title":{"rendered":"Pandas dataframe \u304b\u3089 2 \u3064\u306e\u5217\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"

<\/p>\n

\n

pandas DataFrame \u306e 2 \u3064\u306e\u5217\u306e\u5024\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u306b\u306f\u3001\u6b21\u306e 2 \u3064\u306e\u4e00\u822c\u7684\u306a\u65b9\u6cd5\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n

\u65b9\u6cd5 1: 2 \u3064\u306e\u5217\u3092\u6563\u5e03\u56f3\u4e0a\u306e\u70b9\u3068\u3057\u3066\u30d7\u30ed\u30c3\u30c8\u3059\u308b<\/strong><\/span><\/p>\n

 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt\n\nplt. scatter<\/span> (df[' column1<\/span> '], df[' column2<\/span> '])<\/strong><\/span><\/pre>\n
\u65b9\u6cd5 2: 2 \u3064\u306e\u5217\u3092\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u306b\u7dda\u3068\u3057\u3066\u30d7\u30ed\u30c3\u30c8\u3059\u308b<\/strong><\/span><\/p>\n
 df. plot<\/span> (x=' column1<\/span> ',y=[' column2<\/span> ',' column3<\/span> '])\n<\/strong><\/span><\/pre>\n
\u6b21\u306e\u4f8b\u306f\u3001\u5404\u30e1\u30bd\u30c3\u30c9\u3092\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
\u4f8b 1: \u6563\u5e03\u56f3\u306b 2 \u3064\u306e\u5217\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b<\/strong><\/span><\/h2>\n
\u3055\u307e\u3056\u307e\u306a\u30d0\u30b9\u30b1\u30c3\u30c8\u30dc\u30fc\u30eb\u9078\u624b\u306b\u95a2\u3059\u308b\u60c5\u5831\u3092\u542b\u3080\u6b21\u306e\u30d1\u30f3\u30c0 \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team points assists\n0 to 18 5\n1 B 22 7\n2 C 19 7\n3 D 14 9\n4 E 14 12\n5 F 11 9\n6 G 20 9\n7:28 a.m. 4<\/strong><\/span><\/pre>\n
\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3001x \u8ef8\u306b\u30dd\u30a4\u30f3\u30c8<\/strong>\u5217\u3001y \u8ef8\u306b\u30a2\u30b7\u30b9\u30c8<\/strong>\u5217\u3092\u8868\u793a\u3059\u308b\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/span> <\/p>\n
 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt\n\n#create scatterplot\n<\/span>plt. scatter<\/span> (df[' points<\/span> '], df[' assists<\/span> '])\n\n#add axis labels\n<\/span>plt. xlabel<\/span> (' Points<\/span> ')\nplt. ylabel<\/span> (' Assists<\/span> ')<\/strong><\/span> <\/pre>\n
\"\u30d1\u30f3\u30c0\u306f\u6563\u5e03\u56f3\u306b<\/p>\n
 X \u8ef8\u306b\u306f\u30dd\u30a4\u30f3\u30c8<\/strong>\u5217\u306e\u5024\u304c\u542b\u307e\u308c\u3001Y \u8ef8\u306b\u306f\u30a2\u30b7\u30b9\u30c8<\/strong>\u5217\u306e\u5024\u304c\u542b\u307e\u308c\u307e\u3059\u3002<\/span><\/p>\n
\u4f8b 2: \u6298\u308c\u7dda\u30b0\u30e9\u30d5\u306b 2 \u3064\u306e\u5217\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b<\/strong><\/span><\/h2>\n
6 \u3064\u306e\u7570\u306a\u308b\u8a66\u5408\u3067\u30d0\u30b9\u30b1\u30c3\u30c8\u30dc\u30fc\u30eb \u30c1\u30fc\u30e0\u304c\u7372\u5f97\u3057\u305f\u30dd\u30a4\u30f3\u30c8\u3068\u8a31\u53ef\u3055\u308c\u305f\u30dd\u30a4\u30f3\u30c8\u306b\u95a2\u3059\u308b\u60c5\u5831\u3092\u542b\u3080\u6b21\u306e\u30d1\u30f3\u30c0 \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' game<\/span> ': [1, 2, 3, 4, 5, 6],\n                   ' points_for<\/span> ': [99, 94, 92, 90, 87, 85],\n                   ' points_against<\/span> ': [89, 76, 78, 78, 85, 87]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n   game points_for points_against\n0 1 99 89\n1 2 94 76\n2 3 92 78\n3 4 90 78\n4 5 87 85\n5 6 85 87\n<\/strong><\/span><\/pre>\n
\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3001x \u8ef8\u306bgame<\/strong>\u306e\u5024\u3092\u4f7f\u7528\u3057\u306a\u304c\u3089\u3001 point_for<\/strong>\u306e\u5024\u3092 1 \u3064\u306e\u7dda\u306b\u8868\u793a\u3057\u3001 points_against<\/strong>\u306e\u5024\u3092\u5225\u306e\u7dda\u306b\u8868\u793a\u3059\u308b\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/span> <\/p>\n
 #plot points_for and points_against columns on same y-axis\n<\/span>df. plot<\/span> (x=' game<\/span> ', y=[' points_for<\/span> ', ' points_against<\/span> '])<\/strong><\/span> <\/pre>\n
\"\"<\/p>\n
\u9752\u3044\u7dda\u306f\u5404\u30b2\u30fc\u30e0\u306epoints_for<\/strong>\u5217\u306e\u5024\u3092\u8868\u3057\u3001\u30aa\u30ec\u30f3\u30b8\u8272\u306e\u7dda\u306f\u5404\u30b2\u30fc\u30e0\u306epoints_against<\/strong>\u5217\u306e\u5024\u3092\u8868\u3057\u307e\u3059\u3002<\/span><\/p>\n
\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h2>\n
\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u30d1\u30f3\u30c0\u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n
 Pandas \u3067 Groupby \u3068 Plot \u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5<\/a>
Pandas\u3067\u5217\u5024\u306e\u5206\u5e03\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5<\/a>
\u30d1\u30f3\u30c0\u30d7\u30ed\u30c3\u30c8\u306e\u56f3\u306e\u30b5\u30a4\u30ba\u3092\u8abf\u6574\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
pandas DataFrame \u306e 2 \u3064\u306e\u5217\u306e\u5024\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u306b\u306f\u3001\u6b21\u306e 2 \u3064\u306e\u4e00\u822c\u7684\u306a\u65b9\u6cd5\u304c\u3042\u308a\u307e\u3059\u3002 \u65b9\u6cd5 1: 2 \u3064\u306e\u5217\u3092\u6563\u5e03\u56f3\u4e0a\u306e\u70b9\u3068\u3057\u3066\u30d7\u30ed\u30c3\u30c8\u3059\u308b import matplotlib. pyplot  […]<\/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-3835","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nPandas DataFrame \u304b\u3089 2 \u3064\u306e\u5217\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas DataFrame \u304b\u3089 2 \u3064\u306e\u5217\u3092\u30d7\u30ed\u30c3\u30c8\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\/\u30cf\u309a\u30f3\u30bf\u3099\u306e-2-\u3064\u306e\u7e26\u68d2\u30af\u3099\u30e9\u30d5\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas DataFrame \u304b\u3089 2 \u3064\u306e\u5217\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5 \u2013 Statorials\" \/>\n<meta property=\"og:description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas DataFrame \u304b\u3089 2 \u3064\u306e\u5217\u3092\u30d7\u30ed\u30c3\u30c8\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\/\u30cf\u309a\u30f3\u30bf\u3099\u306e-2-\u3064\u306e\u7e26\u68d2\u30af\u3099\u30e9\u30d5\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-15T06:06:23+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/deux1.jpg\" \/>\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\" 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