{"id":850,"date":"2023-07-28T13:14:00","date_gmt":"2023-07-28T13:14:00","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%ae%e1%84%91%e1%85%a1%e1%84%89%e1%85%ae-%e1%84%90%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%87%e1%85%b3%e1%86%af\/"},"modified":"2023-07-28T13:14:00","modified_gmt":"2023-07-28T13:14:00","slug":"%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%ae%e1%84%91%e1%85%a1%e1%84%89%e1%85%ae-%e1%84%90%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%87%e1%85%b3%e1%86%af","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%ae%e1%84%91%e1%85%a1%e1%84%89%e1%85%ae-%e1%84%90%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%87%e1%85%b3%e1%86%af\/","title":{"rendered":"Python\uc5d0\uc11c \ube48\ub3c4\ud45c\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\ube48\ub3c4\ud45c\ub294<\/strong> \ub2e4\uc591\ud55c \ubc94\uc8fc\uc758 \ube48\ub3c4\ub97c \ud45c\uc2dc\ud558\ub294 \ud45c\uc785\ub2c8\ub2e4. \uc774 \uc720\ud615\uc758 \ud14c\uc774\ube14\uc740 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uac12 \ubd84\ud3ec\ub97c \uc774\ud574\ud558\ub294 \ub370 \ud2b9\ud788 \uc720\uc6a9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ube48\ub3c4\ud45c\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uacc4\uc5f4\uc5d0 \ub300\ud55c \ub2e8\ubc29\ud5a5 \ube48\ub3c4\ud45c<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ud32c\ub354 \uc2dc\ub9ac\uc988\uc5d0\uc11c \uac1c\ubcc4 \uac12\uc758 \ube48\ub3c4\ub97c \ucc3e\uc73c\ub824\uba74 <strong>value_counts()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#defineSeries<\/span>\ndata = pd.Series([1, 1, 1, 2, 3, 3, 3, 3, 4, 4, 5])\n\n<span style=\"color: #008080;\">#find frequencies of each value\n<\/span>data.value_counts()\n\n3 4\n1 3\n4 2\n5 1\n2 1\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub370\uc774\ud130 \uac12\uc744 \ube48\ub3c4\ubcc4\ub85c \uc815\ub82c\ud558\uc9c0 \uc54a\uc73c\ub824\uba74 <strong>sort=False<\/strong> \uc778\uc218\ub97c \ucd94\uac00\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>data.value_counts(sort= <span style=\"color: #008000;\">False<\/span> )\n\n1 3\n2 1\n3 4\n4 2\n5 1<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\uac12 &#8220;1&#8221;\uc774 \uc2dc\ub9ac\uc988\uc5d0 <strong>3<\/strong> \ubc88 \ub098\ud0c0\ub0a9\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uac12 &#8220;2&#8221;\ub294 \uc2dc\ub9ac\uc988\uc5d0\uc11c <strong>1<\/strong> \ubc88 \ub098\ud0c0\ub0a9\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\uac12 &#8220;3&#8221;\uc740 \uc2dc\ub9ac\uc988\uc5d0\uc11c <strong>4<\/strong> \ubc88 \ub098\ud0c0\ub0a9\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub4f1\ub4f1.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>DataFrame<\/strong><\/span> <span style=\"color: #000000;\"><strong>\uc758 \ub2e8\ubc29\ud5a5 \ube48\ub3c4 \ud14c\uc774\ube14<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Pandas DataFrame\uc758 \ube48\ub3c4\ub97c \ucc3e\uc73c\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 <strong>crosstab<\/strong> <strong>()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ud06c\ub85c\uc2a4\ud0ed(\uc0c9\uc778, \uc5f4)<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uae08:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>index:<\/strong> \uadf8\ub8f9\ud654 \uae30\uc900\uc774 \ub418\ub294 \uc5f4 \uc774\ub984<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\uc5f4:<\/strong> \ube48\ub3c4 \uc5f4\uc5d0 \ubd80\uc5ec\ud560 \uc774\ub984<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\uc608\ub97c \ub4e4\uc5b4, \ud55c \ud559\uae09\uc5d0 \uc18d\ud55c 10\uba85\uc758 \ud559\uc0dd\uc758 \ud559\ub144, \ub098\uc774, \uc131\ubcc4\uc5d0 \ub300\ud55c \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uac01 \ubb38\uc790 \ub4f1\uae09\uc758 \ube48\ub3c4\ub97c \ucc3e\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create data<\/span>\ndf = pd.DataFrame({'Grade': ['A','A','A','B','B', 'B', 'B', 'C', 'D', 'D '],\n                   'Age': [18, 18, 18, 19, 19, 20, 18, 18, 19, 19],\n                   'Gender': ['M','M', 'F', 'F', 'F', 'M', 'M', 'F', 'M', 'F']})\n<span style=\"color: #008080;\">\n#view data<\/span>\ndf\n\n\tGrade Age Gender\n0 to 18 m\n1 to 18 m\n2 A 18 F\n3 B 19 F\n4 B 19 F\n5 B 20 M\n6 B 18 M\n7 C 18 F\n8 D 19 M\n9 D 19 F \t  \n\n<span style=\"color: #008080;\">#find frequency of each letter grade\n<\/span>pd.crosstab(index=df[' <span style=\"color: #008000;\">Grade<\/span> '], columns=' <span style=\"color: #008000;\">count<\/span> ')\n\ncol_0 count\nGrade\t\nAt 3\nB4\nC 1\nD 2<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>3\uba85\uc758<\/strong> \ud559\uc0dd\uc774 \ud574\ub2f9 \uc218\uc5c5\uc5d0\uc11c &#8220;A&#8221;\ub97c \ubc1b\uc558\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>4\uba85\uc758<\/strong> \ud559\uc0dd\uc774 \uc218\uc5c5\uc5d0\uc11c &#8220;B&#8221;\ub97c \ubc1b\uc558\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1\uba85\uc758<\/strong> \ud559\uc0dd\uc774 \uc218\uc5c5\uc5d0\uc11c &#8220;C&#8221;\ub97c \ubc1b\uc558\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>2\uba85\uc758<\/strong> \ud559\uc0dd\uc774 \ud574\ub2f9 \uc218\uc5c5\uc5d0\uc11c &#8220;D&#8221;\ub97c \ubc1b\uc558\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\uc720\uc0ac\ud55c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub2e4\ub978 \uc5f4\uc758 \ube48\ub3c4 \uc218\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \uc5f0\ub839\ubcc4 \ube48\ub3c4\ub97c \ucc3e\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>pd.crosstab(index=df[' <span style=\"color: #008000;\">Age<\/span> '], columns=' <span style=\"color: #008000;\">count<\/span> ') \n\ncol_0 count\nAge\t\n18 5\n19 4\n20 1\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>5\uba85\uc758<\/strong> \ud559\uc0dd\uc740 18\uc138\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>4\uba85\uc758<\/strong> \ud559\uc0dd\uc740 19\uc138\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ud559\uc0dd <strong>1<\/strong> \uba85\uc740 20\uc138\uc785\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ud569\uacc4\ub85c \ub098\ub204\uc5b4 \ube48\ub3c4\ub97c \ub370\uc774\ud130 \uc138\ud2b8\uc758 \ube44\uc728\ub85c \uc27d\uac8c \ud45c\uc2dc\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define crosstab<\/span>\ntab = pd.crosstab(index=df['Age'], columns='count')\n\n<span style=\"color: #008080;\">#find proportions<\/span> \ntab\/tab.sum()\n\ncol_0 count\nAge\t\n18 0.5\n19 0.4\n20 0.1\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\ud559\uc0dd\uc758 <strong>50%<\/strong> \uac00 18\uc138\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ud559\uc0dd\uc758 <strong>40%<\/strong> \uac00 19\uc138\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ud559\uc0dd\uc758 <strong>10%<\/strong> \ub294 20\uc138\uc785\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<h3> <span style=\"color: #000000;\"><strong>DataFrame\uc758 \uc591\ubc29\ud5a5 \ube48\ub3c4 \ud14c\uc774\ube14<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub610\ud55c \uc591\ubc29\ud5a5 \ube48\ub3c4\ud45c\ub97c \uc0dd\uc131\ud558\uc5ec \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \uc788\ub294 \uc11c\ub85c \ub2e4\ub978 \ub450 \ubcc0\uc218\uc758 \ube48\ub3c4\ub97c \ud45c\uc2dc\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc5f0\ub839 \ubc0f \ub4f1\uae09 \ubcc0\uc218\uc5d0 \ub300\ud55c \uc591\ubc29\ud5a5 \ube48\ub3c4\ud45c\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>pd.crosstab(index=df[' <span style=\"color: #008000;\">Age<\/span> '], columns=df[' <span style=\"color: #008000;\">Grade<\/span> '])\n\n\nGrade A B C D\nAge\t\t\t\t\n18 3 1 1 0\n19 0 2 0 2\n20 0 1 0 0\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\ud574\ub2f9 \ud559\uae09\uc5d0\ub294 &#8220;A&#8221; \ud559\uc810\uc744 \ubc1b\uc740 18\uc138 \ud559\uc0dd <strong>3<\/strong> \uba85\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">18\uc138\uc758 \ud559\uc0dd\uc774 <strong>1\uba85<\/strong> \uc788\ub294\ub370, \uadf8 \uc218\uc5c5\uc5d0\uc11c \u201cB\u201d\ub97c \ubc1b\uc558\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">18\uc138\uc758 \ud559\uc0dd\uc774 <strong>1\uba85<\/strong> \uc788\ub294\ub370, \uadf8 \uc218\uc5c5\uc5d0\uc11c \u201cC\u201d\ub97c \ubc1b\uc558\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ud574\ub2f9 \ud559\uae09\uc5d0\uc11c &#8220;D&#8221; \ud559\uc810\uc744 \ubc1b\uc740 18\uc138 \ud559\uc0dd\uc774 <strong>0<\/strong> \uba85 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub4f1\ub4f1.<\/span><\/p>\n<p> <em><span style=\"color: #000000;\"><a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.crosstab.html\" target=\"_blank\" rel=\"noopener\">\uc5ec\uae30\uc5d0\uc11c<\/a> <strong>crosstab()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ube48\ub3c4\ud45c\ub294 \ub2e4\uc591\ud55c \ubc94\uc8fc\uc758 \ube48\ub3c4\ub97c \ud45c\uc2dc\ud558\ub294 \ud45c\uc785\ub2c8\ub2e4. \uc774 \uc720\ud615\uc758 \ud14c\uc774\ube14\uc740 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uac12 \ubd84\ud3ec\ub97c \uc774\ud574\ud558\ub294 \ub370 \ud2b9\ud788 \uc720\uc6a9\ud569\ub2c8\ub2e4. \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ube48\ub3c4\ud45c\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4. \uacc4\uc5f4\uc5d0 \ub300\ud55c \ub2e8\ubc29\ud5a5 \ube48\ub3c4\ud45c \ud32c\ub354 \uc2dc\ub9ac\uc988\uc5d0\uc11c \uac1c\ubcc4 \uac12\uc758 \ube48\ub3c4\ub97c \ucc3e\uc73c\ub824\uba74 value_counts() \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. import pandas as pd #defineSeries data = pd.Series([1, 1, 1, 2, 3, 3, 3, 3, 4, [&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-850","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>Python\uc5d0\uc11c \ube48\ub3c4\ud45c\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95 - 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