{"id":4162,"date":"2023-07-13T04:16:13","date_gmt":"2023-07-13T04:16:13","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%89%e1%85%a1%e1%86%a8\/"},"modified":"2023-07-13T04:16:13","modified_gmt":"2023-07-13T04:16:13","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%89%e1%85%a1%e1%86%a8","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%89%e1%85%a1%e1%86%a8\/","title":{"rendered":"Pandas\uc5d0\uc11c \uc5ec\ub7ec \uc5f4\uc744 \uc0ad\uc81c\ud558\ub294 \ubc29\ubc95(4\uac00\uc9c0 \ubc29\ubc95)"},"content":{"rendered":"

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\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0\uc11c \uc5ec\ub7ec \uc5f4\uc744 \uc81c\uac70\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n

\ubc29\ubc95 1: \uc774\ub984\ubcc4\ub85c \uc5ec\ub7ec \uc5f4 \uc81c\uac70<\/strong><\/span><\/p>\n

 df. drop<\/span> (columns=[' col1<\/span> ', ' col2<\/span> ', ' col4<\/span> '], inplace= True<\/span> )\n<\/strong><\/pre>\n
 \ubc29\ubc95 2: \uc774\ub984\ubcc4\ub85c \ubc94\uc704\uc758 \uc5f4 \uc81c\uac70<\/strong><\/span><\/p>\n
 df. drop<\/span> (columns= df.loc<\/span> [:, ' col1<\/span> ':' col4<\/span> '], inplace= True<\/span> )<\/strong><\/pre>\n
 \ubc29\ubc95 3: \uc778\ub371\uc2a4\ubcc4\ub85c \uc5ec\ub7ec \uc5f4 \uc0ad\uc81c<\/strong><\/span><\/p>\n
 df. drop<\/span> (columns=df. columns<\/span> [[0, 3, 4]], inplace= True<\/span> )\n<\/strong><\/pre>\n
 \ubc29\ubc95 4: \uc778\ub371\uc2a4\ubcc4\ub85c \ubc94\uc704\uc758 \uc5f4 \uc81c\uac70<\/strong><\/span><\/p>\n
 df. drop<\/span> (columns= df.columns<\/span> [1:4], inplace= True<\/span> )<\/strong><\/pre>\n
 \ucc38\uace0<\/strong> : inplace=True<\/strong> \uc778\uc218\ub294 \ud32c\ub354\uc5d0\uac8c DataFrame\uc744 \ub2e4\uc2dc \ud560\ub2f9\ud558\uc9c0 \uc54a\uace0 \ub0b4\ubd80 \uc5f4\uc744 \uc81c\uac70\ud558\ub3c4\ub85d \uc9c0\uc2dc\ud569\ub2c8\ub2e4.<\/span><\/p>\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<\/span>\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12],\n                   ' steals<\/span> ': [4, 5, 10, 12, 4, 8, 7, 2]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team points assists rebounds steals\n0 A 18 5 11 4\n1 B 22 7 8 5\n2 C 19 7 10 10\n3 D 14 9 6 12\n4 E 14 12 6 4\n5 F 11 9 5 8\n6 G 20 9 9 7\n7:28 4 12 2<\/strong><\/pre>\n
 \uc608 1: \uc774\ub984\ubcc4\ub85c \uc5ec\ub7ec \uc5f4 \uc81c\uac70<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \uc774\ub984\ubcc4\ub85c points<\/strong> , bounds<\/strong> \ubc0f steles<\/strong> \uc5f4\uc744 \uc81c\uac70\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #drop multiple columns by name\n<\/span>df. drop<\/span> (columns=[' points<\/span> ', ' rebounds<\/span> ', ' steals<\/span> '], inplace= True<\/span> )\n\n#view updated Dataframe\n<\/span>print<\/span> (df)\n\n  team assists\n0 to 5\n1 B 7\n2 C 7\n3 D 9\n4 E 12\n5 F 9\n6 G 9\n7:04 a.m.<\/strong>\n<\/pre>\n
 \uc608 2: \uc774\ub984\ubcc4\ub85c \ubc94\uc704\uc758 \uc5f4 \uc81c\uac70<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \uc774\ub984\ubcc4\ub85c \ud3ec\uc778\ud2b8<\/strong> \ubc0f \ubc14\uc6b4\uc2a4<\/strong> \uc5f4 \uc0ac\uc774\uc5d0 \uac01 \uc5f4\uc744 \uc0ad\uc81c\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #drop columns in range by name\n<\/span>df. drop<\/span> (columns= df.loc<\/span> [:, ' points<\/span> ':' rebounds<\/span> '], inplace= True<\/span> )\n\n#view updated Dataframe\n<\/span>print<\/span> (df)\n\n  team steals\n0 to 4\n1 B 5\n2 C 10\n3 D 12\n4 E 4\n5 F 8\n6 G 7\n7 A.M. 2<\/strong><\/pre>\n
 \uc608\uc2dc 3: \uc778\ub371\uc2a4\ubcc4\ub85c \uc5ec\ub7ec \uc5f4 \uc0ad\uc81c<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 DataFrame\uc5d0\uc11c \uc778\ub371\uc2a4 \uc704\uce58 0, 3, 4\uc758 \uc5f4\uc744 \uc81c\uac70\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #drop multiple columns by index\n<\/span>df. drop<\/span> (columns=df. columns<\/span> [[0, 3, 4]], inplace= True<\/span> )\n\n#view updated Dataframe\n<\/span>print<\/span> (df)\n\n   assist points\n0 18 5\n1 22 7\n2 19 7\n3 14 9\n4 14 12\n5 11 9\n6 20 9\n7 28 4<\/strong><\/pre>\n
 \uc608 4: \uc778\ub371\uc2a4\ubcc4\ub85c \ubc94\uc704 \ub0b4 \uc5f4 \uc81c\uac70<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 DataFrame\uc5d0\uc11c \uc778\ub371\uc2a4 \uc704\uce58 0, 3, 4\uc758 \uc5f4\uc744 \uc81c\uac70\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #drop columns by index range\n<\/span>df. drop<\/span> (columns= df.columns<\/span> [1:4], inplace= True<\/span> )\n\n#view updated Dataframe\n<\/span>print<\/span> (df)\n\n  team steals\n0 to 4\n1 B 5\n2 C 10\n3 D 12\n4 E 4\n5 F 8\n6 G 7\n7 A.M. 2<\/strong><\/pre>\n
 df.columns[1:4]<\/strong> \uad6c\ubb38\uc740 \uc778\ub371\uc2a4 \uc704\uce58 1 \ubd80\ud130<\/em> 4\uae4c\uc9c0\uc758 \uc5f4\uc744 \uc9c0\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ub530\ub77c\uc11c \uc774 \uad6c\ubb38\uc740 \uc778\ub371\uc2a4 \uc704\uce58 1, 2, 3\uc758 \uc5f4\uc744 \uc81c\uac70\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ucc38\uace0<\/strong> : \uc5ec\uae30\uc5d0\uc11c<\/a> pandas drop()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 Pandas: NaN \uac12\uc774 \uc788\ub294 \uc5f4\uc744 \uc81c\uac70\ud558\ub294 \ubc29\ubc95<\/a>
 Pandas: \ubaa9\ub85d\uc5d0 \uc5c6\ub294 \uc5f4\uc744 \uc81c\uac70\ud558\ub294 \ubc29\ubc95<\/a>
 Pandas:\ud2b9\uc815 \uc5f4\uc744 \uc81c\uc678\ud55c \ubaa8\ub4e0 \uc5f4\uc744 \uc81c\uac70\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0\uc11c \uc5ec\ub7ec \uc5f4\uc744 \uc81c\uac70\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubc29\ubc95 1: \uc774\ub984\ubcc4\ub85c \uc5ec\ub7ec \uc5f4 \uc81c\uac70 df. drop (columns=[‘ col1 ‘, ‘ col2 ‘, ‘ col4 ‘], inplace= True ) \ubc29\ubc95 2: \uc774\ub984\ubcc4\ub85c \ubc94\uc704\uc758 \uc5f4 \uc81c\uac70 df. drop (columns= df.loc [:, ‘ col1 ‘:’ col4 ‘], inplace= True ) \ubc29\ubc95 3: \uc778\ub371\uc2a4\ubcc4\ub85c \uc5ec\ub7ec \uc5f4 \uc0ad\uc81c […]<\/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-4162","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nPandas\uc5d0\uc11c \uc5ec\ub7ec \uc5f4\uc744 \uc0ad\uc81c\ud558\ub294 \ubc29\ubc95(4\uac00\uc9c0 \ubc29\ubc95) \u2013 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