{"id":3326,"date":"2023-03-17T18:44:08","date_gmt":"2023-03-17T09:44:08","guid":{"rendered":"https:\/\/blog.since2020.jp\/?p=3326"},"modified":"2023-03-18T02:31:41","modified_gmt":"2023-03-17T17:31:41","slug":"%e3%80%90python%e3%80%91y%e8%bb%b8%e3%82%92%e5%9b%ba%e5%ae%9a%e3%81%97%e3%80%81%e3%82%b0%e3%83%a9%e3%83%95%e4%bd%8d%e7%bd%ae%e3%82%82%e6%8c%87%e5%ae%9a%e3%81%97%e3%81%a6%e6%95%a3%e5%b8%83%e5%9b%b3","status":"publish","type":"post","link":"https:\/\/since2020.jp\/media\/%e3%80%90python%e3%80%91y%e8%bb%b8%e3%82%92%e5%9b%ba%e5%ae%9a%e3%81%97%e3%80%81%e3%82%b0%e3%83%a9%e3%83%95%e4%bd%8d%e7%bd%ae%e3%82%82%e6%8c%87%e5%ae%9a%e3%81%97%e3%81%a6%e6%95%a3%e5%b8%83%e5%9b%b3\/","title":{"rendered":"\u3010Python\u3011Y\u8ef8\u3092\u56fa\u5b9a\u3057\u3001\u30b0\u30e9\u30d5\u4f4d\u7f6e\u3082\u6307\u5b9a\u3057\u3066\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"\n

\u3010Python\u3011Y\u8ef8\u3092\u56fa\u5b9a\u3057\u3001\u30b0\u30e9\u30d5\u4f4d\u7f6e\u3082\u6307\u5b9a\u3057\u3066\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5<\/p>\n\n\n

\u306f\u3058\u3081\u306b<\/h2>\nPython\u3067\u306f\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3059\u308b\u969b\u306b\u3001seaborn\u306epairplot\u95a2\u6570\u306a\u3069\u3092\u4f7f\u7528\u3057\u3066\u4e00\u6c17\u306b\u63cf\u753b\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\r\n\r\n\u4ee5\u4e0b\u306f\u3001seaborn\u306epairplot\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u4e00\u6c17\u306b\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3059\u308b\u4f8b\u3067\u3059\u3002\r\n
\r\n
import seaborn as sns\r\nsns.set(style=\"ticks\")\r\n\r\n# iris\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u8aad\u307f\u8fbc\u307f\r\niris = sns.load_dataset(\"iris\")\r\n\r\n# pairplot\u95a2\u6570\u3067\u6563\u5e03\u56f3\u3092\u4f5c\u6210\r\nsns.pairplot(iris, hue=\"species\")<\/code><\/pre>\r\n\u3053\u306e\u30b3\u30fc\u30c9\u3067\u306f\u3001iris\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u8aad\u307f\u8fbc\u3093\u3067\u3001hue\u30aa\u30d7\u30b7\u30e7\u30f3\u3067\u82b1\u306e\u7a2e\u985e\u3054\u3068\u306b\u8272\u5206\u3051\u3055\u308c\u305f\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3057\u3066\u3044\u307e\u3059\u3002\r\n\r\n\"iris\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u76f8\u95a2\u56f3\"\r\n\r\n\u3057\u304b\u3057\u3001\u4eca\u56de\u306fY\u8ef8\u306b\u4f7f\u7528\u3059\u308b\u5909\u6570\u3092\u56fa\u5b9a<\/strong>\u3057\u3001\u30ec\u30a4\u30a2\u30a6\u30c8\u3082\u6307\u5b9a<\/strong>\u3057\u3066\u6563\u5e03\u56f3\u3092\u4e00\u6c17\u306b\u4f5c\u6210\u3057\u305f\u3044\u3068\u601d\u3044\u307e\u3059\u3002\r\n\r\n\u30c7\u30fc\u30bf\u306e\u5217\u304c\u591a\u3044\u6642\u306b\u306f\u5fc5\u8981\u306aY\u8ef8\u306e\u5024\u306e\u307f\u306e\u6563\u5e03\u56f3\u3092\u53d6\u308a\u51fa\u3057\u305f\u3044\u3067\u3059\u3082\u3093\u306d\u3002\r\n\r\n<\/div>\n\n
Y\u8ef8\u3092\u56fa\u5b9a<\/h2>\nY\u8ef8\u3092\u56fa\u5b9a\u3059\u308b\u305f\u3081\u306b\u306fpairplot\u95a2\u6570\u306ex_vars\u3068y_vars\u306b\u30ab\u30e9\u30e0\u540d\u3092\u6307\u5b9a\u3057\u3066\u3042\u3052\u307e\u3059\u3002\r\n\r\n\u3053\u3053\u3067\u306f\u307f\u306a\u3055\u3093\u81ea\u7531\u306b\u8a2d\u5b9a\u3057\u3066\u307f\u3066\u304f\u3060\u3055\u3044\u3002\r\n
\r\n
x_name_list=iris.columns\r\ny_name='petal_width'\r\n\r\n# pairplot\u95a2\u6570\u3067\u6563\u5e03\u56f3\u3092\u4f5c\u6210\r\nsns.pairplot(iris,\r\nx_vars = x_name_list, # x\u8ef8\u306e\u30ab\u30e9\u30e0\r\ny_vars = y_name, # y\u8ef8\u306e\u30ab\u30e9\u30e0\r\nhue=\"species\")<\/code><\/pre>\r\n<\/div>\n\n
\u6563\u5e03\u56f3\u306e\u30ec\u30a4\u30a2\u30a6\u30c8\u3092\u6307\u5b9a<\/h2>\n\u307e\u305a\u6563\u5e03\u56f3\u306e\u30ec\u30a4\u30a2\u30a6\u30c8\u5909\u66f4\u3067\u306fsearbon\u3092\u4f7f\u308f\u305a\u306b\u4f5c\u308a\u307e\u3057\u305f\u3002\r\n\r\n\u4ed6\u306b\u3082\u8a66\u3057\u305f\u3068\u3053\u308d\u3001\u3053\u308c\u304c\u4e00\u756a\u4e0a\u624b\u304f\u3044\u3063\u305f\u306e\u3067\u7d39\u4ecb\u3057\u307e\u3059\u3002\r\n
\r\n
x_name_list=iris.columns\r\ny_name='petal_width'\r\n\r\nimport math\r\n\r\n#\u30ec\u30a4\u30a2\u30a6\u30c8\u6307\u5b9a\r\n#2\u00d73\u3067\u8868\u793a\r\nnrows=2\r\nncol=3\r\n\r\n# 1\u3064\u306e\u30b0\u30e9\u30d5\u306e\u30b5\u30a4\u30ba\u3092\u8a2d\u5b9a\u3059\u308b\r\nfig, axes = plt.subplots(nrows=nrows, ncols=ncol, figsize=(20, 10))\r\n\r\n# \u5217\u306e\u540d\u524d\u3092\u8a2d\u5b9a\u3059\u308b\r\ncols = list(iris.columns)\r\n\r\n# \u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3059\u308b\r\nfor i in range(nrows):\r\n  for j in range(ncol):\r\n  # \u30b0\u30e9\u30d5\u304c\u3059\u3079\u3066\u8868\u793a\u3055\u308c\u305f\u5834\u5408\u306b\u306f\u3001\u30eb\u30fc\u30d7\u3092\u7d42\u4e86\u3059\u308b\r\n    if (i*ncol+j) >= len(cols):\r\n    break\r\n\r\n  # \u6563\u5e03\u56f3\u3092\u63cf\u753b\u3059\u308b\r\n  axes[i][j].scatter(iris[cols[i*ncol+j]], iris[y_name], label=cols[i*ncol+j])\r\n\r\n  # \u8ef8\u30e9\u30d9\u30eb\u3092\u8a2d\u5b9a\u3059\u308b\r\n  axes[i][j].set_xlabel(cols[i*ncol+j])\r\n  axes[i][j].set_ylabel(y_name)\r\n\r\n  # \u51e1\u4f8b\u3092\u8868\u793a\u3059\u308b\r\n  axes[i][j].legend()\r\n\r\n# \u30b0\u30e9\u30d5\u3092\u8868\u793a\u3059\u308b\r\nplt.show()<\/code><\/pre>\r\n\u3053\u308c\u3092\u5b9f\u884c\u3059\u308c\u3070Y\u8ef8\u306e\u5024\u306f\u56fa\u5b9a\u3057\u305f\u307e\u307e\u3001\u30ec\u30a4\u30a2\u30a6\u30c8\u306e\u5909\u66f4\u3082\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\u3002\r\n\r\n\u6563\u5e03\u56f3\u4ee5\u5916\u306b\u3082\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3084\u7bb1\u3072\u3052\u56f3\u3067\u3082\u9069\u5fdc\u53ef\u80fd\u306a\u306e\u3067\u4fbf\u5229\u3067\u3059\u3002\r\n\r\n\"\u30ec\u30a4\u30a2\u30a6\u30c8\u6307\u5b9a\u3057\u305f\u6563\u5e03\u56f3\"\r\n\r\n\u3053\u3061\u3089\u304c\u5b9f\u884c\u7d50\u679c\u306b\u306a\u308a\u307e\u3059\u3002\r\n\r\n\u56f3\u306e\u30ec\u30a4\u30a2\u30a6\u30c8\u304c\u5909\u66f4\u3055\u308c\u3066\u3044\u307e\u3059\u3002\r\n\r\n\u3061\u3083\u3093\u3068\uff12\u00d7\uff13\u3067\u56f3\u304c\u8868\u793a\u3055\u308c\u3066\u3044\u307e\u3059\u306d\u3002\r\n\r\n<\/div>\n\n
[\u304a\u307e\u3051]\u8fd1\u4f3c\u7dda\u306e\u8868\u793a<\/h2>\n\u57fa\u672c\u7684\u306b\u306f\u3053\u308c\u3067\u826f\u3044\u3067\u3059\u304c\u3001\u5473\u6c17\u306a\u3044\u306e\u3067\u8fd1\u4f3c\u7dda\u3082seaborn\u3092\u4f7f\u3063\u3066\u8868\u793a\u3055\u305b\u307e\u3057\u3087\u3046\u3002\r\n
\r\n
x_name_list=iris.columns\r\ny_name='petal_width'\r\n\r\nimport math\r\n\r\n#\u30ec\u30a4\u30a2\u30a6\u30c8\u6307\u5b9a\r\n#3\u00d72\u3067\u8868\u793a\r\nnrows=2\r\nncol=3\r\n\r\n# 1\u3064\u306e\u30b0\u30e9\u30d5\u306e\u30b5\u30a4\u30ba\u3092\u8a2d\u5b9a\u3059\u308b\r\nfig, axes = plt.subplots(nrows=nrows, ncols=ncol, figsize=(20, 10))\r\n\r\n# \u5217\u306e\u540d\u524d\u3092\u8a2d\u5b9a\u3059\u308b\r\ncols = list(iris.columns)\r\n\r\n# \u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3059\u308b\r\nfor i in range(nrows):\r\n  for j in range(ncol):\r\n  # \u30b0\u30e9\u30d5\u304c\u3059\u3079\u3066\u8868\u793a\u3055\u308c\u305f\u5834\u5408\u306b\u306f\u3001\u30eb\u30fc\u30d7\u3092\u7d42\u4e86\u3059\u308b\r\n    if (i*ncol+j) >= len(cols):\r\n    break\r\n\r\n  # \u6563\u5e03\u56f3\u3092\u63cf\u753b\u3059\u308b\r\n  #axes[i][j].scatter(iris[cols[i*ncol+j]], iris[y_name], label=cols[i*ncol+j])\r\n  # \u6563\u5e03\u56f3\u3092\u63cf\u753b\u3059\u308b(seaborn\u3092\u4f7f\u3046\uff06\u8fd1\u4f3c\u7dda\u8868\u793a)\r\n  sns.regplot(data=iris, x=cols[i*ncol+j], y=y_name, ax=axes[i][j], label=cols[i*ncol+j])\r\n\r\n\r\n  # \u8ef8\u30e9\u30d9\u30eb\u3092\u8a2d\u5b9a\u3059\u308b\r\n  axes[i][j].set_xlabel(cols[i*ncol+j])\r\n  axes[i][j].set_ylabel(y_name)\r\n\r\n  # \u51e1\u4f8b\u3092\u8868\u793a\u3059\u308b\r\n  axes[i][j].legend()\r\n\r\n# \u30b0\u30e9\u30d5\u3092\u8868\u793a\u3059\u308b\r\nplt.show()<\/code><\/pre>\r\nsna.regplot()\u3068\u3044\u3046\u95a2\u6570\u3092\u7528\u3044\u308b\u3053\u3068\u3067\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u8fd1\u4f3c\u7dda\u304c\u8868\u793a\u3055\u308c\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3059\u3002\r\n\r\n\u3053\u308c\u3060\u3051\u3067\u8fd1\u4f3c\u7dda\u304c\u8868\u793a\u3055\u308c\u308b\u306a\u3093\u3066\u4fbf\u5229\u3067\u3059\u306d\u3002\r\n\r\n\u5b9f\u884c\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002\r\n\r\n\"\u30ec\u30a4\u30a2\u30a6\u30c8\u6307\u5b9a\u3057\u3001\u8fd1\u4f3c\u7dda\u3092\u5165\u308c\u305f\u6563\u5e03\u56f3\"\r\n\r\n\u8fd1\u4f3c\u7dda\u304c\u8868\u793a\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u304c\u5206\u304b\u308b\u3068\u601d\u3044\u307e\u3059\u3002\r\n\r\n\u3053\u308c\u3067\u5c11\u3057\u83ef\u3084\u304b\u306b\u898b\u3048\u307e\u3059\u306d\u3002\r\n\r\n<\/div>\n\n
\u304a\u308f\u308a\u306b<\/h2>\n\u4eca\u56de\u306f\u305f\u3060pairplot\u3067\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3059\u308b\u306e\u3067\u306f\u306a\u304f\u3001Y\u8ef8\u3082\u56fa\u5b9a\u3057\u3001\u30ec\u30a4\u30a2\u30a6\u30c8\u3082\u5909\u66f4\u3059\u308b\u65b9\u6cd5\u3092\u5b66\u3073\u307e\u3057\u305f\u3002\r\n\r\n\u30c7\u30fc\u30bf\u306e\u5217\u304c\u591a\u3059\u304e\u308b\u3068\u304d\u306b\u306f\u3059\u3079\u3066\u306e\u7d44\u307f\u5408\u308f\u305b\u306e\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3059\u308b\u3068\u5927\u5909\u306a\u306e\u3067Y\u8ef8\u3092\u56fa\u5b9a\u3057\u3066\u3042\u3052\u308b\u3068\u3088\u3044\u3067\u3057\u3087\u3046\u3002\r\n\r\n\u6b21\u56de\u306f\u6563\u5e03\u56f3\u3060\u3051\u3067\u306a\u304f\u76f8\u95a2\u4fc2\u6570\u3082\u4e00\u6c17\u306b\u8868\u793a\u3057\u3001\u304b\u3064\u53ef\u8996\u5316\u3055\u305b\u308b\u65b9\u6cd5\u3092\u8a18\u4e8b\u5316\u3057\u305f\u3044\u3068\u601d\u3044\u307e\u3059\u3002","protected":false},"excerpt":{"rendered":"
\u3010Python\u3011Y\u8ef8\u3092\u56fa\u5b9a\u3057\u3001\u30b0\u30e9\u30d5\u4f4d\u7f6e\u3082\u6307\u5b9a\u3057\u3066\u6563\u5e03\u56f3\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5 \u306f\u3058\u3081\u306b Python\u3067\u306f\u6563\u5e03\u56f3\u3092\u63cf\u753b\u3059\u308b\u969b\u306b\u3001seaborn\u306epairplot\u95a2\u6570\u306a\u3069\u3092\u4f7f\u7528\u3057\u3066\u4e00\u6c17\u306b\u63cf\u753b\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002 \u4ee5\u4e0b\u306f\u3001seabo […]<\/p>\n","protected":false},"author":83,"featured_media":3123,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","swell_btn_cv_data":"","footnotes":"","_wp_rev_ctl_limit":""},"categories":[1246],"tags":[258,331,430,431,294,432],"class_list":["post-3326","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-infrastructure","tag-bi","tag-python","tag-seaborn","tag-431","tag-294","tag-432"],"_links":{"self":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/posts\/3326","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/users\/83"}],"replies":[{"embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/comments?post=3326"}],"version-history":[{"count":0,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/posts\/3326\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/media\/3123"}],"wp:attachment":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/media?parent=3326"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/categories?post=3326"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/tags?post=3326"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}