{"id":30781,"date":"2024-10-28T06:03:50","date_gmt":"2024-10-28T06:03:50","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=30781"},"modified":"2024-11-26T06:47:27","modified_gmt":"2024-11-26T06:47:27","slug":"%ed%8c%8c%ec%9d%b4%ec%8d%ac-%ec%9e%90%eb%8f%99%eb%a7%a4%eb%a7%a4-%ea%b0%9c%eb%b0%9c-dataframe-%ec%b9%bc%eb%9f%bc-%eb%a1%9c%ec%9a%b0-%ec%84%a0%ed%83%9d","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/30781\/","title":{"rendered":"\ud30c\uc774\uc36c \uc790\ub3d9\ub9e4\ub9e4 \uac1c\ubc1c, DataFrame \uce7c\ub7fc, \ub85c\uc6b0 \uc120\ud0dd"},"content":{"rendered":"<p><body><\/p>\n<p>\n        \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c \ub9e4\ub9e4\ub97c \uc790\ub3d9\uc73c\ub85c \uc218\ud589\ud558\ub294 \uc2dc\uc2a4\ud15c\uc785\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc2dc\uc2a4\ud15c\uc744 \uac1c\ubc1c\ud558\uae30 \uc704\ud574\uc11c\ub294<br \/>\n        \ub370\uc774\ud130 \ucc98\ub9ac \ubc0f \ubd84\uc11d\uc774 \ud544\uc218\uc801\uc785\ub2c8\ub2e4. \ud30c\uc774\uc36c\uc740 \ud2b9\ud788 \ub370\uc774\ud130 \ubd84\uc11d\uc744 \uc704\ud55c \uac15\ub825\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac,<br \/>\n        <code>pandas<\/code>\ub97c \uc81c\uacf5\ud558\uc5ec \ub370\uc774\ud130\ud504\ub808\uc784(DataFrame)\uc744 \ub2e4\ub8e8\ub294 \ub370 \ub9e4\uc6b0 \uc720\uc6a9\ud569\ub2c8\ub2e4.\n    <\/p>\n<h2>1. pandas\ub780?<\/h2>\n<p>\n<code>pandas<\/code>\ub294 \ud30c\uc774\uc36c\uc5d0\uc11c \ub370\uc774\ud130 \uc870\uc791 \ubc0f \ubd84\uc11d\uc744 \uc704\ud574 \ub110\ub9ac \uc0ac\uc6a9\ub418\ub294 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4.<br \/>\n        \uc774 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ub370\uc774\ud130\ud504\ub808\uc784\uc774\ub77c\ub294 2\ucc28\uc6d0 \ub370\uc774\ud130 \uad6c\uc870\ub97c \uc774\uc6a9\ud558\uc5ec \ub370\uc774\ud130\ub97c \uc27d\uac8c \ucc98\ub9ac\ud560 \uc218 \uc788\uac8c \ud574\uc90d\ub2c8\ub2e4.<br \/>\n        \ub370\uc774\ud130\ud504\ub808\uc784\uc740 \uc5d1\uc140\uc758 \uc2a4\ud504\ub808\ub4dc\uc2dc\ud2b8\uc640 \uc720\uc0ac\ud55c \ud615\ud0dc\ub85c, \ud589(row)\uacfc \uc5f4(column)\ub85c \uad6c\uc131\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<br \/>\n        \ub370\uc774\ud130\ud504\ub808\uc784\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \ub370\uc774\ud130 \ubd84\uc11d \uc791\uc5c5\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<h3>1.1 pandas \uc124\uce58\ud558\uae30<\/h3>\n<p>\n        pandas \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud558\uae30 \uc704\ud574\uc11c\ub294 pip\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \ub2e4\uc74c \uba85\ub839\uc5b4\ub97c \ud130\ubbf8\ub110\uc5d0 \uc785\ub825\ud558\uba74 \ub429\ub2c8\ub2e4:\n    <\/p>\n<pre><code>pip install pandas<\/code><\/pre>\n<h3>1.2 pandas \uae30\ubcf8 \uc0ac\uc6a9\ubc95<\/h3>\n<p>\n        pandas\ub97c \uc0ac\uc6a9\ud558\uae30 \uc704\ud574 \uba3c\uc800 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc784\ud3ec\ud2b8\ud569\ub2c8\ub2e4. \uc784\ud3ec\ud2b8\ud55c \ud6c4\uc5d0\ub294 \uc0d8\ud50c \ub370\uc774\ud130\ub97c \uc0dd\uc131\ud558\uc5ec<br \/>\n        \ub370\uc774\ud130\ud504\ub808\uc784\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<pre><code>import pandas as pd\n\n# \uc0d8\ud50c \ub370\uc774\ud130 \uc0dd\uc131\ndata = {\n    '\ub0a0\uc9dc': ['2023-01-01', '2023-01-02', '2023-01-03'],\n    '\uac00\uaca9': [100, 102, 105],\n    '\uac70\ub798\ub7c9': [200, 220, 210]\n}\n\n# \ub370\uc774\ud130\ud504\ub808\uc784 \uc0dd\uc131\ndf = pd.DataFrame(data)\nprint(df)<\/code><\/pre>\n<h2>2. DataFrame \uce7c\ub7fc \uc120\ud0dd<\/h2>\n<p>\n        \ub370\uc774\ud130\ud504\ub808\uc784\uc5d0\uc11c \ud2b9\uc815 \uce7c\ub7fc\uc744 \uc120\ud0dd\ud558\uba74 \ud574\ub2f9 \uce7c\ub7fc\uc5d0 \ub300\ud55c \ub370\uc774\ud130\ub97c \uac04\ud3b8\ud558\uac8c \uc870\uc791\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<br \/>\n        \uce7c\ub7fc\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:\n    <\/p>\n<h3>2.1 \ub2e8\uc77c \uce7c\ub7fc \uc120\ud0dd<\/h3>\n<pre><code>\uac00\uaca9 \uce7c\ub7fc \uc120\ud0dd \uc608\uc81c\n\uac00\uaca9_col = df['\uac00\uaca9']\nprint(\uac00\uaca9_col)<\/code><\/pre>\n<h3>2.2 \uc5ec\ub7ec \uce7c\ub7fc \uc120\ud0dd<\/h3>\n<pre><code>\uc5ec\ub7ec \uce7c\ub7fc \uc120\ud0dd \uc608\uc81c\nselected_columns = df[['\uac00\uaca9', '\uac70\ub798\ub7c9']]\nprint(selected_columns)<\/code><\/pre>\n<h3>2.3 \uce7c\ub7fc \ucd94\uac00 \ubc0f \uc218\uc815<\/h3>\n<p>\n        \uc0c8\ub85c\uc6b4 \uce7c\ub7fc\uc744 \ucd94\uac00\ud558\uac70\ub098 \uae30\uc874 \uce7c\ub7fc\uc758 \uac12\uc744 \uc218\uc815\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<pre><code>df['\ubcc0\ub3d9\uc131'] = df['\uac00\uaca9'].pct_change() * 100  # \ubcc0\ub3d9\uc131 \uce7c\ub7fc \ucd94\uac00\nprint(df)<\/code><\/pre>\n<h2>3. DataFrame \ub85c\uc6b0 \uc120\ud0dd<\/h2>\n<p>\n        \ud589(row)\uc744 \uc120\ud0dd\ud558\uba74 \ud2b9\uc815 \uae30\uac04 \ub3d9\uc548\uc758 \ub370\uc774\ud130\ub098 \ud2b9\uc815 \uc870\uac74\uc744 \ub9cc\uc871\ud558\ub294 \ub370\uc774\ud130\ub9cc \ucd94\ucd9c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<br \/>\n        \uc5ec\uae30\uc11c\ub294 \ub85c\uc6b0\ub97c \uc120\ud0dd\ud558\ub294 \ub2e4\uc591\ud55c \ubc29\ubc95\uc744 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<h3>3.1 \uc778\ub371\uc2a4\ub97c \uc0ac\uc6a9\ud55c \ub85c\uc6b0 \uc120\ud0dd<\/h3>\n<pre><code>\uccab \ubc88\uc9f8 \ub85c\uc6b0 \uc120\ud0dd \uc608\uc81c\nfirst_row = df.iloc[0]  # \uc778\ub371\uc2a4\uac00 0\uc778 \ub85c\uc6b0 \uc120\ud0dd\nprint(first_row)<\/code><\/pre>\n<h3>3.2 \uc870\uac74\uc5d0 \ub530\ub978 \ub85c\uc6b0 \uc120\ud0dd<\/h3>\n<p>\n        \ub85c\uc6b0 \uc120\ud0dd \uc2dc \uc870\uac74\uc744 \uc124\uc815\ud558\uc5ec \ud2b9\uc815 \uc870\uac74\uc744 \ub9cc\uc871\ud558\ub294 \ub370\uc774\ud130\ub9cc \uc120\ud0dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<pre><code>price_above_101 = df[df['\uac00\uaca9'] &gt; 101]\nprint(price_above_101)<\/code><\/pre>\n<h3>3.3 \uc5ec\ub7ec \uc870\uac74\uc744 \uc0ac\uc6a9\ud55c \ub85c\uc6b0 \uc120\ud0dd<\/h3>\n<p>\n        \uc5ec\ub7ec \uc870\uac74\uc744 \uacb0\ud569\ud558\uc5ec \ubcf5\uc7a1\ud55c \ud544\ud130\ub9c1\uc744 \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<pre><code>\ub2e4\uc591\ud55c \uc870\uac74\uc744 \uc774\uc6a9\ud55c \ub85c\uc6b0 \uc120\ud0dd \uc608\uc81c\nfiltered_df = df[(df['\uac00\uaca9'] &gt; 100) &amp; (df['\uac70\ub798\ub7c9'] &gt; 200)]\nprint(filtered_df)<\/code><\/pre>\n<h2>4. DataFrame \ud65c\uc6a9: \uc790\ub3d9\ub9e4\ub9e4 \uc2e0\ud638 \uc0dd\uc131<\/h2>\n<p>\n        \uc774\uc81c\uae4c\uc9c0 \uc0b4\ud3b4\ubcf8 \ub370\uc774\ud130\ub97c \uac00\uc9c0\uace0 \uac04\ub2e8\ud55c \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc758 \uc2e0\ud638\ub97c \uc0dd\uc131\ud574\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<br \/>\n        \uc5ec\uae30\uc11c\ub294 \uc774\ub3d9\ud3c9\uade0 \uad50\ucc28 \uc804\ub7b5\uc744 \uc774\uc6a9\ud55c \uc2e0\ud638 \uc0dd\uc131 \uc608\uc81c\ub97c \ubcf4\uc5ec\uc8fc\uaca0\uc2b5\ub2c8\ub2e4.\n    <\/p>\n<h3>4.1 \ub370\uc774\ud130 \uc900\ube44<\/h3>\n<pre><code>import numpy as np\n\n# \uc774\ub3d9\ud3c9\uade0 \uacc4\uc0b0\uc744 \uc704\ud55c \ub370\uc774\ud130\ud504\ub808\uc784 \uc0dd\uc131\ndf['\ub2e8\uae30\uc774\ud3c9'] = df['\uac00\uaca9'].rolling(window=2).mean()\ndf['\uc7a5\uae30\uc774\ud3c9'] = df['\uac00\uaca9'].rolling(window=3).mean()\nprint(df)<\/code><\/pre>\n<h3>4.2 \ub9e4\ub9e4 \uc2e0\ud638 \uc0dd\uc131<\/h3>\n<pre><code>\ub9e4\ub9e4 \uc2e0\ud638 \uc0dd\uc131 \uc608\uc81c\ndf['\uc2e0\ud638'] = np.where(df['\ub2e8\uae30\uc774\ud3c9'] &gt; df['\uc7a5\uae30\uc774\ud3c9'], 1, 0)  # 1: \ub9e4\uc218 \uc2e0\ud638, 0: \ub9e4\ub3c4 \uc2e0\ud638\nprint(df)<\/code><\/pre>\n<h2>5. \uacb0\ub860<\/h2>\n<p>\n        \uc774\ubc88 \uac15\uc88c\uc5d0\uc11c\ub294 \ud30c\uc774\uc36c\uc758 pandas \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc774\uc6a9\ud558\uc5ec \ub370\uc774\ud130\ud504\ub808\uc784\uc758 \uce7c\ub7fc\uacfc \ub85c\uc6b0\ub97c \uc120\ud0dd\ud558\ub294<br \/>\n        \ubc29\ubc95\uc744 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \ub610\ud55c, \uc774\ub97c \ud65c\uc6a9\ud558\uc5ec \uac04\ub2e8\ud55c \uc790\ub3d9\ub9e4\ub9e4 \uc2e0\ud638\ub97c \uc0dd\uc131\ud558\ub294 \ubc29\ubc95\uc744 \ud559\uc2b5\ud558\uc600\uc2b5\ub2c8\ub2e4.<br \/>\n        \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uac1c\ubc1c\ud558\ub294 \ub370 \ub370\uc774\ud130 \ucc98\ub9ac \ub2a5\ub825\uc740 \ub9e4\uc6b0 \uc911\uc694\ud558\uba70, pandas\ub294 \uc774 \uc791\uc5c5\uc744 \uc218\uc6d4\ud558\uac8c \ub9cc\ub4e4\uc5b4\uc90d\ub2c8\ub2e4.<br \/>\n        \uc5ec\ub7ec\ubd84\ub3c4 \ub2e4\uc591\ud55c \ub370\uc774\ud130 \ubd84\uc11d \uae30\ubc95\uc744 \uc751\uc6a9\ud558\uc5ec \uc790\uc2e0\ub9cc\uc758 \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \ub9cc\ub4e4\uc5b4\ubcf4\uc138\uc694!\n    <\/p>\n<h2>\ucc38\uace0 \uc790\ub8cc<\/h2>\n<ul>\n<li><a href=\"https:\/\/pandas.pydata.org\/\">pandas \uacf5\uc2dd \ubb38\uc11c<\/a><\/li>\n<li><a href=\"https:\/\/numpy.org\/\">NumPy \uacf5\uc2dd \ubb38\uc11c<\/a><\/li>\n<li><a href=\"https:\/\/matplotlib.org\/\">Matplotlib \uacf5\uc2dd \ubb38\uc11c<\/a><\/li>\n<\/ul>\n<p><\/body><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c \ub9e4\ub9e4\ub97c \uc790\ub3d9\uc73c\ub85c \uc218\ud589\ud558\ub294 \uc2dc\uc2a4\ud15c\uc785\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc2dc\uc2a4\ud15c\uc744 \uac1c\ubc1c\ud558\uae30 \uc704\ud574\uc11c\ub294 \ub370\uc774\ud130 \ucc98\ub9ac \ubc0f \ubd84\uc11d\uc774 \ud544\uc218\uc801\uc785\ub2c8\ub2e4. \ud30c\uc774\uc36c\uc740 \ud2b9\ud788 \ub370\uc774\ud130 \ubd84\uc11d\uc744 \uc704\ud55c \uac15\ub825\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac, pandas\ub97c \uc81c\uacf5\ud558\uc5ec \ub370\uc774\ud130\ud504\ub808\uc784(DataFrame)\uc744 \ub2e4\ub8e8\ub294 \ub370 \ub9e4\uc6b0 \uc720\uc6a9\ud569\ub2c8\ub2e4. 1. pandas\ub780? pandas\ub294 \ud30c\uc774\uc36c\uc5d0\uc11c \ub370\uc774\ud130 \uc870\uc791 \ubc0f \ubd84\uc11d\uc744 \uc704\ud574 \ub110\ub9ac \uc0ac\uc6a9\ub418\ub294 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. \uc774 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ub370\uc774\ud130\ud504\ub808\uc784\uc774\ub77c\ub294 2\ucc28\uc6d0 \ub370\uc774\ud130 \uad6c\uc870\ub97c \uc774\uc6a9\ud558\uc5ec \ub370\uc774\ud130\ub97c \uc27d\uac8c \ucc98\ub9ac\ud560 \uc218 \uc788\uac8c &hellip; <a href=\"https:\/\/atmokpo.com\/w\/30781\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;\ud30c\uc774\uc36c \uc790\ub3d9\ub9e4\ub9e4 \uac1c\ubc1c, DataFrame \uce7c\ub7fc, \ub85c\uc6b0 \uc120\ud0dd&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[37],"tags":[],"class_list":["post-30781","post","type-post","status-publish","format-standard","hentry","category-37"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - 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