{"id":973,"date":"2023-07-28T03:15:43","date_gmt":"2023-07-28T03:15:43","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%8b%e1%85%a7%e1%84%85%e1%85%a5-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%87%e1%85%a7%e1%86%bc\/"},"modified":"2023-07-28T03:15:43","modified_gmt":"2023-07-28T03:15:43","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%8b%e1%85%a7%e1%84%85%e1%85%a5-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%87%e1%85%a7%e1%86%bc","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%8b%e1%85%a7%e1%84%85%e1%85%a5-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%87%e1%85%a7%e1%86%bc\/","title":{"rendered":"\uc5ec\ub7ec \uc5f4\uc5d0 \uac78\uccd0 pandas dataframe\uc744 \ubcd1\ud569\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

<\/p>\n

\n

\uc5ec\ub7ec \uc5f4\uc5d0 \uac78\uccd0 \ub450 \uac1c\uc758 Pandas DataFrame\uc744 \ubcd1\ud569\ud558\ub824\ub294 \uacbd\uc6b0\uac00 \uc885\uc885 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\ud589\ud788\ub3c4 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 pandas merge()<\/a> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uba74 \uc774 \uc791\uc5c5\uc744 \uc27d\uac8c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 p.d. merge<\/span> (df1, df2, left_on=['col1','col2'], right_on = ['col1','col2'])<\/strong><\/pre>\n
 \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc2dc 1: \uc774\ub984\uc774 \ub2e4\ub978 \uc5ec\ub7ec \uc5f4 \ubcd1\ud569<\/span><\/strong><\/h3>\n
 \ub2e4\uc74c \ub450 \uac1c\uc758 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create and view first DataFrame<\/span>\ndf1 = pd.DataFrame({'a1': [0, 0, 1, 1, 2],\n                   'b': [0, 0, 1, 1, 1],\n                   'c': [11, 8, 10, 6, 6]})\n\nprint<\/span> (df1)\n\n   a1 bc\n0 0 0 11\n1 0 0 8\n2 1 1 10\n3 1 1 6\n4 2 1 6\n\n#create and view second DataFrame<\/span> \ndf2 = pd.DataFrame({'a2': [0, 1, 1, 1, 3],\n                   'b': [0, 0, 0, 1, 1],\n                   'd': [22, 24, 25, 33, 37]})\n\nprint<\/span> (df2)\n\n   a2 comic\n0 0 0 22\n1 1 0 24\n2 1 0 25\n3 1 1 33\n4 3 1 37\n<\/strong><\/pre>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \ub450 DataFrame\uc758 \uc5ec\ub7ec \uc5f4\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc67c\ucabd \uc870\uc778\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 p.d. merge<\/span> (df1, df2, how=' left<\/span> ', left_on=[' a1<\/span> ', ' b<\/span> '], right_on = [' a2<\/span> ', ' b<\/span> '])\n\n\n        a1 b c a2 d\n0 0 0 11 0.0 22.0\n1 0 0 8 0.0 22.0\n2 1 1 10 1.0 33.0\n3 1 1 6 1.0 33.0\n4 2 1 6 NaN NaN\n<\/strong><\/pre>\n
 \uc608\uc2dc 2: \uc774\ub984\uc774 \uac19\uc740 \uc5ec\ub7ec \uc5f4 \ubcd1\ud569<\/span><\/strong><\/h3>\n
 \ub3d9\uc77c\ud55c \uc5f4 \uc774\ub984\uc744 \uac00\uc9c4 \ub2e4\uc74c \ub450 \uac1c\uc758 pandas DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrames<\/span>\ndf1 = pd.DataFrame({'a': [0, 0, 1, 1, 2],\n                   'b': [0, 0, 1, 1, 1],\n                   'c': [11, 8, 10, 6, 6]})\n\ndf2 = pd.DataFrame({'a': [0, 1, 1, 1, 3],\n                   'b': [0, 0, 0, 1, 1],\n                   'd': [22, 24, 25, 33, 37]})\n<\/strong><\/pre>\n
 \uc774 \uacbd\uc6b0 \ub450 DataFrame\uc758 \uc5f4 \uc774\ub984\uc774 \ub3d9\uc77c\ud558\ubbc0\ub85c on = [‘a’, ‘b’]<\/strong> \uc0ac\uc6a9\uc744 \ub2e8\uc21c\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 p.d. merge<\/span> (df1, df2, how=' left<\/span> ', on=[' a<\/span> ', ' b<\/span> '])\n\n\ta b c d\n0 0 0 11 22.0\n1 0 0 8 22.0\n2 1 1 10 33.0\n3 1 1 6 33.0\n4 2 1 6 NaN\n<\/strong><\/pre>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 \uc778\ub371\uc2a4\uc5d0 \ub450 \uac1c\uc758 Pandas DataFrame\uc744 \ubcd1\ud569\ud558\ub294 \ubc29\ubc95
 \uc5ec\ub7ec Pandas DataFrame\uc744 \uc2a4\ud0dd\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\uc5ec\ub7ec \uc5f4\uc5d0 \uac78\uccd0 \ub450 \uac1c\uc758 Pandas DataFrame\uc744 \ubcd1\ud569\ud558\ub824\ub294 \uacbd\uc6b0\uac00 \uc885\uc885 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\ud589\ud788\ub3c4 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 pandas merge() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uba74 \uc774 \uc791\uc5c5\uc744 \uc27d\uac8c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. p.d. merge (df1, df2, left_on=[‘col1′,’col2’], right_on = [‘col1′,’col2’]) \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4. \uc608\uc2dc 1: \uc774\ub984\uc774 \ub2e4\ub978 \uc5ec\ub7ec \uc5f4 \ubcd1\ud569 \ub2e4\uc74c \ub450 \uac1c\uc758 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud574 […]<\/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-973","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\n\uc5ec\ub7ec \uc5f4\uc5d0 \uac78\uccd0 Pandas DataFrame\uc744 \ubcd1\ud569\ud558\ub294 \ubc29\ubc95 - 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