{"id":4250,"date":"2023-07-12T12:45:03","date_gmt":"2023-07-12T12:45:03","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-iterrows-%e1%84%8b%e1%85%a5%e1%86%b8%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%b3-%e1%84%80%e1%85%a1%e1%86%b9\/"},"modified":"2023-07-12T12:45:03","modified_gmt":"2023-07-12T12:45:03","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-iterrows-%e1%84%8b%e1%85%a5%e1%86%b8%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%b3-%e1%84%80%e1%85%a1%e1%86%b9","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-iterrows-%e1%84%8b%e1%85%a5%e1%86%b8%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%b3-%e1%84%80%e1%85%a1%e1%86%b9\/","title":{"rendered":"Pandas: \ud589\uc758 \uac12\uc744 \uc5c5\ub370\uc774\ud2b8\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

<\/p>\n

\n

iterrows\ub97c<\/strong> \uc0ac\uc6a9\ud558\ub294 \ub3d9\uc548 \ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec pandas DataFrame\uc758 \uac12\uc744 \uc5c5\ub370\uc774\ud2b8\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 for<\/span> i, row in<\/span> df. iterrows<\/span> ():\n    points_add = 10\n    if<\/span> row[' points<\/span> '] > 15:\n        points_add = 50\n    df. at<\/span> [i,' points<\/span> '] = points_add\n<\/strong><\/span><\/pre>\n
 \uc774 \ud2b9\uc815 \uc608\ub294 DataFrame\uc758 \uac01 \ud589\uc744 \ubc18\ubcf5\ud558\uace0 \uac12\uc774 \ud604\uc7ac 15\ubcf4\ub2e4 \ud070 \uacbd\uc6b0 \uc810 \uc5f4\uc758 \uac12\uc744 50<\/strong> \uc73c\ub85c \uc5c5\ub370\uc774\ud2b8\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ud604\uc7ac \uac12\uc774 15\ubcf4\ub2e4 \uc791\uac70\ub098 \uac19\uc73c\uba74 \uac12\uc774 10<\/strong> \uc73c\ub85c \uc5c5\ub370\uc774\ud2b8\ub429\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 DataFrame\uc758 \uac12\uc744 \ud589\uc73c\ub85c \uc5c5\ub370\uc774\ud2b8\ud569\ub2c8\ub2e4.<\/strong><\/span><\/h2>\n
 \ub2e4\uc591\ud55c \ub18d\uad6c \uc120\uc218\uac00 \ub4dd\uc810\ud55c \uc810\uc218\ub97c \ubcf4\uc5ec\uc8fc\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' player<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'],\n                   ' points<\/span> ': [10, 12, 14, 15, 15, 15, 16, 17, 20]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  player points\n0 to 10\n1 B 12\n2 C 14\n3 D 15\n4 E 15\n5 F 15\n6 G 16\n7:17 a.m.\n8 I 20<\/strong><\/pre>\n
 \ub2e4\uc74c \ub17c\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud3ec\uc778\ud2b8 \uc5f4\uc758 \uac12\uc744 \uc5c5\ub370\uc774\ud2b8\ud55c\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n