{"id":3951,"date":"2023-07-14T13:27:00","date_gmt":"2023-07-14T13:27:00","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%8c%e1%85%a5%e1%86%af%e1%84%87%e1%85%a7%e1%86%af-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%80%e1%85%b3%e1%84%85%e1%85%ae%e1%86%b8-%e1%84%84%e1%85%a9%e1%84%82%e1%85%b3%e1%86%ab\/"},"modified":"2023-07-14T13:27:00","modified_gmt":"2023-07-14T13:27:00","slug":"%e1%84%8c%e1%85%a5%e1%86%af%e1%84%87%e1%85%a7%e1%86%af-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%80%e1%85%b3%e1%84%85%e1%85%ae%e1%86%b8-%e1%84%84%e1%85%a9%e1%84%82%e1%85%b3%e1%86%ab","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%8c%e1%85%a5%e1%86%af%e1%84%87%e1%85%a7%e1%86%af-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%80%e1%85%b3%e1%84%85%e1%85%ae%e1%86%b8-%e1%84%84%e1%85%a9%e1%84%82%e1%85%b3%e1%86%ab\/","title":{"rendered":"Pandas: where \uc870\uac74\uacfc \ud568\uaed8 group by\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

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Pandas\uc5d0\uc11c Where<\/strong> \uc870\uac74\uacfc \ud568\uaed8 \uadf8\ub8f9\ud654\ub97c<\/strong> \uc0ac\uc6a9\ud558\ub294 \uac00\uc7a5 \uc26c\uc6b4 \ubc29\ubc95\uc740 query()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \uac83\uc785\ub2c8\ub2e4.<\/span><\/p>\n

 df. query<\/span> (\" team == 'A'<\/span> \"). groupby<\/span> ([\" position<\/span> \"])[\" points<\/span> \"]. mean<\/span> (). reset_index<\/span> ()\n<\/strong><\/pre>\n
 \uc774 \ud2b9\uc815 \uc608\ub294 position<\/strong> \ubcc4\ub85c \uadf8\ub8f9\ud654\ub41c points<\/strong> \uc758 \ud3c9\uade0 \uac12\uc744 \uacc4\uc0b0\ud569\ub2c8\ub2e4. \uc5ec\uae30\uc11c \ud300\uc740<\/strong> \uc77c\ubd80 pandas DataFrame\uc5d0\uc11c “A”\uc640 \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uc774 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608: Pandas\uc5d0\uc11c Where \uc870\uac74\uacfc \ud568\uaed8 Group By\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95<\/strong><\/span><\/h2>\n
 \ub2e4\uc591\ud55c \ub18d\uad6c \uc120\uc218\uc5d0 \ub300\ud55c \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B'],\n                   ' position<\/span> ': ['G', 'G', 'F', 'F', 'F', 'G', 'G', 'F'],\n                   ' points<\/span> ': [22, 14, 15, 10, 8, 29, 33, 18]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team position points\n0 AG 22\n1 AG 14\n2 AF15\n3 AF 10\n4 AF 8\n5 BG 29\n6 BG 33\n7 BF 18\n<\/b><\/pre>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud300\uc774<\/strong> “A”\uc778 \uc704\uce58<\/strong> \ubcc4\ub85c \uadf8\ub8f9\ud654\ub41c \ud3c9\uade0 \ud3ec\uc778\ud2b8<\/strong> \uac12\uc744 \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #calculate mean value of points, grouped by position, where team == 'A'<\/span>\ndf. query<\/span> (\" team == 'A'<\/span> \"). groupby<\/span> ([\" position<\/span> \"])[\" points<\/span> \"]. mean<\/span> (). reset_index<\/span> ()\n\n        position points\n0 F 11.0\n1G 18.0\n<\/strong><\/pre>\n
 \uacb0\uacfc\uc5d0\uc11c \uc6b0\ub9ac\ub294 \ub2e4\uc74c\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/span><\/p>\n