{"id":2920,"date":"2023-07-20T02:05:59","date_gmt":"2023-07-20T02:05:59","guid":{"rendered":"https:\/\/statorials.org\/ko\/pandas-groupby-nlargeest\/"},"modified":"2023-07-20T02:05:59","modified_gmt":"2023-07-20T02:05:59","slug":"pandas-groupby-nlargeest","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/pandas-groupby-nlargeest\/","title":{"rendered":"Pandas: nlargest()\uc640 \ud568\uaed8 groupby\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

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\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec pandas DataFrame\uc5d0\uc11c \uadf8\ub8f9\ubcc4\ub85c n\uac1c\uc758 \uac00\uc7a5 \ud070 \uac12\uc744 \ud45c\uc2dc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 #display two largest values by group<\/span>\ndf. groupby<\/span> (' group_var<\/span> ')[' values_var<\/span> ']. nlargest<\/span> ( 2<\/span> )\n<\/strong><\/pre>\n
 \uadf8\ub9ac\uace0 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc758 \uadf8\ub8f9\ub2f9 n\uac1c\uc758 \uac00\uc7a5 \ud070 \uac12\uc5d0 \ub300\ud574 \ud2b9\uc815 \uc791\uc5c5(\ud569\uacc4 \uacc4\uc0b0 \ub4f1)\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #find sum of two largest values by group<\/span>\ndf. groupby<\/span> (' group_var<\/span> ')[' values_var<\/span> ']. apply<\/span> ( lambda<\/span> grp: grp.nlargest<\/span> ( 2<\/span> ) .sum<\/span> ())\n<\/strong><\/pre>\n
 \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
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B'],\n                   ' points<\/span> ': [12, 29, 34, 14, 10, 11, 7, 36, 34, 22]})<\/span>\n\n#view DataFrame\nprint<\/span> (df)\n\n  team points\n0 to 12\n1 to 29\n2 to 34\n3 to 14\n4 to 10\n5 B 11\n6 B 7\n7 B 36\n8 B 34\n9 B 22\n<\/span><\/span><\/strong><\/span><\/pre>\n
 \uc608\uc2dc 1: \uadf8\ub8f9\ubcc4\ub85c N\uac1c\uc758 \uac00\uc7a5 \ud070 \uac12 \ud45c\uc2dc<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud300\ubcc4<\/strong> \ub85c \uadf8\ub8f9\ud654\ub41c \ub450 \uac1c\uc758 \uac00\uc7a5 \ud070 \uc810\uc218<\/strong> \uac12\uc744 \ud45c\uc2dc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #display two largest points values grouped by team\ndf. groupby<\/span> (' team<\/span> ')[' points<\/span> ']. nlargest<\/span> ( 2<\/span> )\n\nteam   \nAt 2 34\n      1 29\nB 7 36\n      8 34\nName: points, dtype: int64\n<\/span><\/span><\/strong><\/pre>\n
 \uacb0\uacfc\uc5d0\ub294 \uc6d0\ubcf8 DataFrame\uc758 \uc778\ub371\uc2a4 \uc704\uce58\uc640 \ud568\uaed8 \uac01 \ud300<\/strong> \uc758 \uac00\uc7a5 \ud070 \ub450 \ud3ec\uc778\ud2b8<\/strong> \uac12\uc774 \ud45c\uc2dc\ub429\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc2dc 2: \uadf8\ub8f9\ub2f9 N\uac1c\uc758 \uac00\uc7a5 \ud070 \uac12\uc5d0 \ub300\ud574 \uc791\uc5c5 \uc218\ud589<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud300\ubcc4<\/strong> \ub85c \uadf8\ub8f9\ud654\ub41c \ub450 \uac1c\uc758 \uac00\uc7a5 \ud070 \ud3ec\uc778\ud2b8<\/strong> \uac12\uc758 \ud569\uc744 \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n
 #calculate sum of two largest points values for each team\ndf. groupby<\/span> (' team<\/span> ')[' points<\/span> ']. apply<\/span> ( lambda<\/span> grp: grp.nlargest<\/span> ( 2<\/span> ) .sum<\/span> ())\n\nteam\nAt 63\nB70\nName: points, dtype: int64<\/span>\n<\/span><\/strong><\/pre>\n
 \uacb0\uacfc\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n