{"id":3947,"date":"2023-07-14T13:59:17","date_gmt":"2023-07-14T13:59:17","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-value_counts-%e1%84%87%e1%85%a2%e1%86%a8%e1%84%87%e1%85%ae%e1%86%ab%e1%84%8b%e1%85%b2%e1%86%af\/"},"modified":"2023-07-14T13:59:17","modified_gmt":"2023-07-14T13:59:17","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-value_counts-%e1%84%87%e1%85%a2%e1%86%a8%e1%84%87%e1%85%ae%e1%86%ab%e1%84%8b%e1%85%b2%e1%86%af","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-value_counts-%e1%84%87%e1%85%a2%e1%86%a8%e1%84%87%e1%85%ae%e1%86%ab%e1%84%8b%e1%85%b2%e1%86%af\/","title":{"rendered":"Pandas: value_counts\ub97c \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\ud32c\ub354\uc758 <strong>value_counts()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \ud2b9\uc815 \uc5f4\uc5d0\uc11c \uac12\uc758 \ubc1c\uc0dd \ud69f\uc218\ub97c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uac12\uc744 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc\ud558\ub824\uba74 \ub2e4\uc74c \ubc29\ubc95 \uc911 \ud558\ub098\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 1: \uac12\uc744 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc(\uc18c\uc218\uc810 \ud615\uc2dd)<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">my_col<\/span> . <span style=\"color: #3366ff;\">value_counts<\/span> (normalize= <span style=\"color: #008000;\">True<\/span> )\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 2: \uac12\uc744 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc(\ubc31\ubd84\uc728 \uae30\ud638\ub85c \ud615\uc2dd \uc9c0\uc815)<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">my_col<\/span> . <span style=\"color: #3366ff;\">value_counts<\/span> (normalize= <span style=\"color: #008000;\">True<\/span> ). <span style=\"color: #3366ff;\">mul<\/span> ( <span style=\"color: #008000;\">100<\/span> ). <span style=\"color: #3366ff;\">round<\/span> ( <span style=\"color: #008000;\">1<\/span> ). <span style=\"color: #3366ff;\">astype<\/span> (str) + ' <span style=\"color: #ff0000;\">%<\/span> '<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 3: \uac12 \uac1c\uc218\ub97c \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc(\uac1c\uc218 \ud3ec\ud568)<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>counts = df. <span style=\"color: #3366ff;\">my_col<\/span> . <span style=\"color: #3366ff;\">value_counts<\/span> ()<\/strong>\n<strong>percs = df. <span style=\"color: #3366ff;\">my_col<\/span> . <span style=\"color: #3366ff;\">value_counts<\/span> (normalize= <span style=\"color: #008000;\">True<\/span> )<\/strong>\n<strong>p.d. <span style=\"color: #3366ff;\">concat<\/span> ([counts, percs], axis= <span style=\"color: #008000;\">1<\/span> , keys=[' <span style=\"color: #ff0000;\">count<\/span> ', ' <span style=\"color: #ff0000;\">percentage<\/span> '])<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \ub2e4\uc74c pandas DataFrame\uc5d0\uc11c \uc2e4\uc81c\ub85c \uac01 \uba54\uc11c\ub4dc\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: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<span style=\"color: #000000;\">\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'A', 'B', 'B', 'B', 'B', 'B', 'C'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [15, 12, 18, 20, 22, 28, 35, 40]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team points\n0 to 15\n1 to 12\n2 B 18\n3 B 20\n4 B 22\n5 B 28\n6 B 35\n7 C 40\n<\/span><\/span><\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 1: \uac12\uc744 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc(\uc18c\uc218\uc810 \ud615\uc2dd)<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 <strong>\ud300<\/strong> \uc5f4\uc5d0\uc11c \uac01 \uac12\uc758 \ubc1c\uc0dd \ud69f\uc218\ub97c \uacc4\uc0b0\ud558\uace0 \ubc1c\uc0dd \ud69f\uc218\ub97c \uc804\uccb4\uc758 \ubc31\ubd84\uc728(\uc2ed\uc9c4\uc218 \ud615\uc2dd)\ub85c \ud45c\uc2dc\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: #008080;\">#count occurrence of each value in 'team' column as percentage of total\n<\/span>df. <span style=\"color: #3366ff;\">team<\/span> . <span style=\"color: #3366ff;\">value_counts<\/span> (normalize= <span style=\"color: #008000;\">True<\/span> )\n\nB 0.625\nAt 0.250\nC 0.125\nName: team, dtype: float64\n<\/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;\"><strong>B<\/strong> \uac12\uc740 \ud300 \uc5f4 \ubc1c\uc0dd\uc758 62.5%\ub97c \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>A<\/strong> \uac12\uc740 \ud300 \uc5f4\uc758 \ubc1c\uc0dd \ud69f\uc218 \uc911 25%\ub97c \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>C<\/strong> \uac12\uc740 \ud300 \uc5f4\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 \ud69f\uc218\uc758 12.5%\ub97c \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ubc31\ubd84\uc728\uc740 \uc18c\uc218\uc810 \ud615\uc2dd\uc73c\ub85c \ud45c\uc2dc\ub429\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 2: \uac12\uc744 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc(\ubc31\ubd84\uc728 \uae30\ud638\ub85c \ud615\uc2dd \uc9c0\uc815)<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 <strong>\ud300<\/strong> \uc5f4\uc5d0\uc11c \uac01 \uac12\uc758 \ubc1c\uc0dd \ud69f\uc218\ub97c \uacc4\uc0b0\ud558\uace0 \ubc1c\uc0dd \ud69f\uc218\ub97c \ubc31\ubd84\uc728 \uae30\ud638 \ud615\uc2dd\uc73c\ub85c \uc804\uccb4 \ub300\ube44 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc\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: #008080;\">#count occurrence of each value in 'team' column as percentage of total\n<\/span>df. <span style=\"color: #3366ff;\">team<\/span> . <span style=\"color: #3366ff;\">value_counts<\/span> (normalize= <span style=\"color: #008000;\">True<\/span> ). <span style=\"color: #3366ff;\">mul<\/span> ( <span style=\"color: #008000;\">100<\/span> ). <span style=\"color: #3366ff;\">round<\/span> ( <span style=\"color: #008000;\">1<\/span> ). <span style=\"color: #3366ff;\">astype<\/span> (str) + ' <span style=\"color: #ff0000;\">%<\/span> '\n\nB 62.5%\nAt 25.0%\nC 12.5%\nName: team, dtype: object\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ubc31\ubd84\uc728\uc740 \ubc31\ubd84\uc728 \uae30\ud638\uac00 \ud3ec\ud568\ub41c \ubb38\uc790\uc5f4\ub85c \ud615\uc2dd\ud654\ub429\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 3: \uac12\uc758 \uac1c\uc218\ub97c \ubc31\ubd84\uc728\ub85c \ud45c\ud604\ud558\uae30(\uc22b\uc790 \ud3ec\ud568)<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 <strong>\ud300<\/strong> \uc5f4\uc5d0\uc11c \uac01 \uac12\uc758 \ubc1c\uc0dd \ud69f\uc218\ub97c \uacc4\uc0b0\ud558\uace0 \ubc1c\uc0dd \ud69f\uc218\ub97c \uc22b\uc790\uc640 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc\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: #008080;\">#count occurrence of each value in 'team' column\n<\/span>counts = df. <span style=\"color: #3366ff;\">team<\/span> . <span style=\"color: #3366ff;\">value_counts<\/span> ()\n\n<span style=\"color: #008080;\">#count occurrence of each value in 'team' column as percentage of total<\/span>\npercs = df. <span style=\"color: #3366ff;\">team<\/span> . <span style=\"color: #3366ff;\">value_counts<\/span> (normalize= <span style=\"color: #008000;\">True<\/span> )\n\n<span style=\"color: #008080;\">#concatenate results into one DataFrame\n<\/span>p.d. <span style=\"color: #3366ff;\">concat<\/span> ([counts, percs], axis= <span style=\"color: #008000;\">1<\/span> , keys=[' <span style=\"color: #ff0000;\">count<\/span> ', ' <span style=\"color: #ff0000;\">percentage<\/span> '])\n\n        count percentage\nB 5 0.625\nAt 2 0.250\nC 1 0.125<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\uac1c\uc218<\/strong> \uc5f4\uc5d0\ub294 \ud300 \uc5f4\uc758 \uac01 \uace0\uc720 \uac12 \uac1c\uc218\uac00 \ud45c\uc2dc\ub418\uace0, <strong>\ubc31\ubd84\uc728<\/strong> \uc5f4\uc5d0\ub294 \uac01 \uace0\uc720 \uac12\uc774 \ucd1d \ubc1c\uc0dd \ud69f\uc218\uc5d0 \ub300\ud55c \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc\ub429\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\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\u1162\u11ab\u1103\u1165-\u1111\u1173\u11af\u1105\u1169\u11ba-\u1100\u1161\u11b9-\u1100\u1162\u1109\u116e\/\" target=\"_blank\" rel=\"noopener\">Pandas: \uac00\uce58 \uacc4\uc815\uc744 \uadf8\ub9ac\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165-\u1100\u1173\u1105\u116e\u11b8-\u1107\u1167\u11af-\u1100\u1161\u11b9-\u1100\u1162\u1109\u116e\/\" target=\"_blank\" rel=\"noopener\">Pandas: GroupBy \ubc0f \uac12 \uac1c\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1100\u1173\u1105\u116e\u11b8\u1107\u1167\u11af-\u1111\u1162\u11ab\u1103\u1165-\u1112\u1175\u1109\u1173\u1110\u1169\u1100\u1173\u1105\u1162\u11b7\/\" target=\"_blank\" rel=\"noopener\">Pandas: \uadf8\ub8f9\ubcc4\ub85c \ud788\uc2a4\ud1a0\uadf8\ub7a8\uc744 \uadf8\ub9ac\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ud32c\ub354\uc758 value_counts() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \ud2b9\uc815 \uc5f4\uc5d0\uc11c \uac12\uc758 \ubc1c\uc0dd \ud69f\uc218\ub97c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uac12\uc744 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc\ud558\ub824\uba74 \ub2e4\uc74c \ubc29\ubc95 \uc911 \ud558\ub098\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubc29\ubc95 1: \uac12\uc744 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc(\uc18c\uc218\uc810 \ud615\uc2dd) df. my_col . value_counts (normalize= True ) \ubc29\ubc95 2: \uac12\uc744 \ubc31\ubd84\uc728\ub85c \ud45c\uc2dc(\ubc31\ubd84\uc728 \uae30\ud638\ub85c \ud615\uc2dd \uc9c0\uc815) df. my_col . value_counts (normalize= True ). mul ( 100 ). 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