{"id":2261,"date":"2023-07-23T00:47:34","date_gmt":"2023-07-23T00:47:34","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%8e%e1%85%ae%e1%86%a8-0-%e1%84%8e%e1%85%ae%e1%86%a8-1-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5\/"},"modified":"2023-07-23T00:47:34","modified_gmt":"2023-07-23T00:47:34","slug":"%e1%84%8e%e1%85%ae%e1%86%a8-0-%e1%84%8e%e1%85%ae%e1%86%a8-1-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%8e%e1%85%ae%e1%86%a8-0-%e1%84%8e%e1%85%ae%e1%86%a8-1-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5\/","title":{"rendered":"Pandas\uc5d0\uc11c \ucd95=0\uacfc \ucd95=1\uc758 \ucc28\uc774\uc810"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/pandas.pydata.org\/\" target=\"_blank\" rel=\"noopener\">Pandas<\/a> \uc758 \ub9ce\uc740 \ud568\uc218\uc5d0\uc11c\ub294 \ud2b9\uc815 \uacc4\uc0b0\uc744 \uc801\uc6a9\ud560 \ucd95\uc744 \uc9c0\uc815\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc77c\ubc18\uc801\uc73c\ub85c \ub2e4\uc74c\uacfc \uac19\uc740 \uacbd\ud5d8 \ubc95\uce59\uc774 \uc801\uc6a9\ub429\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>axis=0<\/strong> : &#8220;\uc5f4\ub2f9&#8221; \uacc4\uc0b0 \uc801\uc6a9<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>axis=1<\/strong> : &#8220;\ub77c\uc778\ub2f9&#8221; \uacc4\uc0b0 \uc801\uc6a9<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \ub2e4\uc74c Pandas DataFrame\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \uc2dc\ub098\ub9ac\uc624\uc5d0\uc11c <strong>\ucd95<\/strong> \uc778\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #ff0000;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'A', 'B', 'B', 'B', 'B', 'C', 'C'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n\tteam points assists rebounds\n0 to 25 5 11\n1 to 12 7 8\n2 B 15 7 10\n3 B 14 9 6\n4 B 19 12 6\n5 B 23 9 5\n6 C 25 9 9\n7 C 29 4 12<\/span><\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 1: \ub2e4\uc591\ud55c \ucd95\uc744 \ub530\ub77c \ud3c9\uade0 \ucc3e\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\"><strong>axis=0\uc744<\/strong> \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \uac01 \uc5f4\uc758 \ud3c9\uade0\uc744 \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find mean of each column\n<\/span>df. <span style=\"color: #3366ff;\">mean<\/span> (axis= <span style=\"color: #008000;\">0<\/span> )\n\npoints 20.250\nassists 7,750\nrebounds 8,375\ndtype:float64\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ucd9c\ub825\uc5d0\ub294 DataFrame\uc5d0 \uc788\ub294 \uac01 \uc22b\uc790 \uc5f4\uc758 \ud3c9\uade0 \uac12\uc774 \ud45c\uc2dc\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Pandas\ub294 \ubb38\uc790 \uc5f4\uc774\uae30 \ub54c\ubb38\uc5d0 &#8220;\ud300&#8221; \uc5f4\uc758 \ud3c9\uade0 \uacc4\uc0b0\uc744 \uc790\ub3d9\uc73c\ub85c \ubc29\uc9c0\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub610\ud55c <strong>axis=1\uc744<\/strong> \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \uac01 \ud589\uc758 \ud3c9\uade0\uc744 \ucc3e\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find mean of each row\n<\/span>df. <span style=\"color: #3366ff;\">mean<\/span> (axis= <span style=\"color: #008000;\">1<\/span> )\n\n0 13.666667\n1 9.000000\n2 10.666667\n3 9.666667\n4 12.333333\n5 12.333333\n6 14.333333\n7 15.000000\ndtype:float64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c \uc6b0\ub9ac\ub294 \ub2e4\uc74c\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\uccab \ubc88\uc9f8 \ud589\uc758 \ud3c9\uade0\uac12\uc740 <strong>13.667<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ub450 \ubc88\uc9f8 \ud589\uc758 \ud3c9\uade0\uac12\uc740 <strong>9000<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uc138 \ubc88\uc9f8 \ud589\uc758 \ud3c9\uade0\uac12\uc740 <strong>10,667<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub4f1\ub4f1.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 2: \ub2e4\uc591\ud55c \ucd95\uc744 \ub530\ub77c \ud569\uacc4 \ucc3e\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\"><strong>\ucd95=0\uc744<\/strong> \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \ud2b9\uc815 \uc5f4\uc758 \ud569\uacc4\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find sum of 'points' and 'assists' columns<\/span>\ndf[[' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">assists<\/span> ']]. <span style=\"color: #3366ff;\">sum<\/span> (axis= <span style=\"color: #008000;\">0<\/span> )\n\npoints 162\nassists 62\ndtype: int64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub610\ud55c <strong>axis=1\uc744<\/strong> \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \uac01 \ud589\uc758 \ud569\uacc4\ub97c \ucc3e\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find sum of each row\n<\/span>df. <span style=\"color: #3366ff;\">sum<\/span> (axis= <span style=\"color: #008000;\">1<\/span> )\n\n0 41\n1 27\n2 32\n3 29\n4 37\n5 37\n6 43\n7 45\ndtype: int64<\/span><\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 3: \ub2e4\uc591\ud55c \ucd95\uc744 \ub530\ub77c \ucd5c\ub300\uac12 \ucc3e\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\"><strong>\ucd95=0\uc744<\/strong> \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc5d0 \uc788\ub294 \ud2b9\uc815 \uc5f4\uc758 \ucd5c\ub300\uac12\uc744 \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find max of 'points', 'assists', and 'rebounds' columns\n<\/span>df[[' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">assists<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ']]. <span style=\"color: #3366ff;\">max<\/span> (axis= <span style=\"color: #008000;\">0<\/span> )\n\npoints 29\nassists 12\nrebounds 12\ndtype: int64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub610\ud55c <strong>axis=1\uc744<\/strong> \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \uac01 \ud589\uc758 \ucd5c\ub300\uac12\uc744 \ucc3e\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find max of each row\n<\/span>df. <span style=\"color: #3366ff;\">max<\/span> (axis= <span style=\"color: #008000;\">1<\/span> )\n\n0 25\n1 12\n2 15\n3 14\n4 19\n5 23\n6 25\n7 29\ndtype: int64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c \uc6b0\ub9ac\ub294 \ub2e4\uc74c\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\uccab \ubc88\uc9f8 \uc904\uc758 \ucd5c\ub300\uac12\uc740 <strong>25<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ub450 \ubc88\uc9f8 \uc904\uc758 \ucd5c\ub300\uac12\uc740 <strong>12<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uc138 \ubc88\uc9f8 \ud589\uc758 \ucd5c\ub300\uac12\uc740 <strong>15<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub4f1\ub4f1.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1167\u11bc\u1100\u1172\u11ab-\u1111\u1162\u11ab\u1103\u1165-\u110b\u1167\u11af\/\" target=\"_blank\" rel=\"noopener\">Pandas\uc5d0\uc11c \uc5f4\uc758 \ud3c9\uade0\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165-\u1100\u1175\u1103\u116e\u11bc\u110b\u1175\u110b\u1163\/\" target=\"_blank\" rel=\"noopener\">Pandas\uc5d0\uc11c \uc5f4\uc758 \ud569\uacc4\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><br \/> Pandas\uc5d0\uc11c \uc5f4\uc758 \ucd5c\ub300\uac12\uc744 \ucc3e\ub294 \ubc29\ubc95<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Pandas \uc758 \ub9ce\uc740 \ud568\uc218\uc5d0\uc11c\ub294 \ud2b9\uc815 \uacc4\uc0b0\uc744 \uc801\uc6a9\ud560 \ucd95\uc744 \uc9c0\uc815\ud574\uc57c \ud569\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c \ub2e4\uc74c\uacfc \uac19\uc740 \uacbd\ud5d8 \ubc95\uce59\uc774 \uc801\uc6a9\ub429\ub2c8\ub2e4. axis=0 : &#8220;\uc5f4\ub2f9&#8221; \uacc4\uc0b0 \uc801\uc6a9 axis=1 : &#8220;\ub77c\uc778\ub2f9&#8221; \uacc4\uc0b0 \uc801\uc6a9 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \ub2e4\uc74c Pandas DataFrame\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \uc2dc\ub098\ub9ac\uc624\uc5d0\uc11c \ucd95 \uc778\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. import pandas as pd #createDataFrame df = pd. DataFrame ({&#8216; team &#8216;: [&#8216;A&#8217;, &#8216;A&#8217;, &#8216;B&#8217;, &#8216;B&#8217;, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-2261","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas\uc5d0\uc11c \ucd95=0\uacfc \ucd95=1\uc758 \ucc28\uc774\uc810 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \ub2e4\uc591\ud55c \ud32c\ub354 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud560 \ub54c axis=0\uacfc axis=1\uc758 \ucc28\uc774\uc810\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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