{"id":2407,"date":"2023-07-22T10:02:37","date_gmt":"2023-07-22T10:02:37","guid":{"rendered":"https:\/\/statorials.org\/my\/%e1%80%95%e1%80%94%e1%80%ba%e1%80%92%e1%80%ab%e1%80%a5%e1%80%9a%e1%80%bb%e1%80%ac%e1%80%89%e1%80%ba%e1%80%80%e1%80%b1%e1%80%ac%e1%80%ba%e1%80%9c%e1%80%b6\/"},"modified":"2023-07-22T10:02:37","modified_gmt":"2023-07-22T10:02:37","slug":"%e1%80%95%e1%80%94%e1%80%ba%e1%80%92%e1%80%ab%e1%80%a5%e1%80%9a%e1%80%bb%e1%80%ac%e1%80%89%e1%80%ba%e1%80%80%e1%80%b1%e1%80%ac%e1%80%ba%e1%80%9c%e1%80%b6","status":"publish","type":"post","link":"https:\/\/statorials.org\/my\/%e1%80%95%e1%80%94%e1%80%ba%e1%80%92%e1%80%ab%e1%80%a5%e1%80%9a%e1%80%bb%e1%80%ac%e1%80%89%e1%80%ba%e1%80%80%e1%80%b1%e1%80%ac%e1%80%ba%e1%80%9c%e1%80%b6\/","title":{"rendered":"Pandas \u1010\u103d\u1004\u103a \u1021\u1001\u103b\u102d\u102f\u1037\u101e\u1031\u102c\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1011\u102d\u1014\u103a\u1038\u101e\u102d\u1019\u103a\u1038\u1014\u100a\u103a\u1038 (\u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u1016\u103c\u1004\u1037\u103a)"},"content":{"rendered":"

<\/p>\n

\n

Pandas DataFrame \u1010\u103d\u1004\u103a \u1021\u1001\u103b\u102d\u102f\u1037\u101e\u1031\u102c\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101e\u102c \u1006\u1000\u103a\u101c\u1000\u103a\u1011\u102c\u1038\u101b\u103e\u102d\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101e\u1004\u103a\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span><\/p>\n

\u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 1- \u1019\u100a\u103a\u101e\u100a\u1037\u103a\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101e\u102d\u1019\u103a\u1038\u1006\u100a\u103a\u1038\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1015\u102b\u104b<\/strong><\/span><\/p>\n

 #only keep columns 'col1' and 'col2'<\/span>\ndf[[' col1<\/span> ', ' col2<\/span> ']]\n<\/strong><\/pre>\n
 \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 2- \u1016\u103b\u1000\u103a\u101b\u1014\u103a \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1015\u102b\u104b<\/strong><\/span><\/p>\n
 #drop columns 'col3' and 'col4'<\/span>\ndf[df. columns<\/span> [~df. columns<\/span> . isin<\/span> ([' col3<\/span> ',' col4<\/span> '])]]\n<\/strong><\/pre>\n
 \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1014\u1019\u1030\u1014\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b pandas DataFrame \u1016\u103c\u1004\u1037\u103a \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u1005\u102e\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a-<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'B', 'B', 'B'],\n                   ' points<\/span> ': [11, 7, 8, 10, 13, 13],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5]})\n\n<\/span>#view DataFrame\n<\/span><\/span>df\n\n\tteam points assists rebounds\n0 A 11 5 11\n1 To 7 7 8\n2 to 8 7 10\n3 B 10 9 6\n4 B 13 12 6\n5 B 13 9 5\n<\/span><\/span><\/strong><\/pre>\n
 \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 1- \u1019\u100a\u103a\u101e\u100a\u1037\u103a\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101e\u102d\u1019\u103a\u1038\u1006\u100a\u103a\u1038\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1015\u102b\u104b<\/strong><\/span><\/h3>\n
 \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u101e\u100a\u103a \u201c\u1021\u1016\u103d\u1032\u1037\u201d \u1014\u103e\u1004\u1037\u103a \u201c\u1021\u1019\u103e\u1010\u103a\u1019\u103b\u102c\u1038\u201d \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101e\u102c \u1011\u102d\u1014\u103a\u1038\u101e\u102d\u1019\u103a\u1038\u1011\u102c\u1038\u101e\u100a\u1037\u103a DataFrame \u1021\u101e\u1005\u103a\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u101e\u1010\u103a\u1019\u103e\u1010\u103a\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a-<\/span><\/p>\n
 #create new DataFrame and only keep 'team' and 'points' columns\n<\/span>df2 = df[[' team<\/span> ', ' points<\/span> ']]\n\n#view new DataFrame\n<\/span>df2\n\n        team points\n0 to 11\n1 to 7\n2 to 8\n3 B 10\n4 B 13\n5 B 13<\/span><\/span><\/strong><\/pre>\n
 \u101b\u101c\u1012\u103a DataFrame \u101e\u100a\u103a \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1011\u102c\u1038\u101e\u1031\u102c \u1000\u1031\u102c\u103a\u101c\u1036\u1014\u103e\u1005\u103a\u1001\u102f\u1000\u102d\u102f\u101e\u102c \u101e\u102d\u1019\u103a\u1038\u1006\u100a\u103a\u1038\u1011\u102c\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u101e\u1010\u102d\u1015\u103c\u102f\u1015\u102b\u104b<\/span><\/p>\n
 \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 2- \u1016\u103b\u1000\u103a\u101b\u1014\u103a \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1015\u102b\u104b<\/strong><\/span><\/h3>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b\u1000\u102f\u1012\u103a\u101e\u100a\u103a \u1019\u1030\u101b\u1004\u103a\u1038 DataFrame \u1019\u103e “ \u1010\u1000\u103a\u101b\u1031\u102c\u1000\u103a\u101e\u100a\u103a”  \u1014\u103e\u1004\u1037\u103a “ \u1018\u1031\u102c\u1004\u103a\u101d\u1004\u103a\u101e\u100a\u103a”  \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1016\u101a\u103a\u101b\u103e\u102c\u1038\u101e\u100a\u1037\u103a DataFrame \u1021\u101e\u1005\u103a\u1000\u102d\u102f \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a-<\/span><\/p>\n
 #create new DataFrame and that drops 'assists' and 'rebounds'\n<\/span>df2 = df[df. columns<\/span> [~df. columns<\/span> . isin<\/span> ([' assists<\/span> ', ' rebounds<\/span> '])]]\n\n#view new DataFrame\n<\/span>df2\n\n        team points\n0 to 11\n1 to 7\n2 to 8\n3 B 10\n4 B 13\n5 B 13<\/span><\/span><\/strong><\/pre>\n
 \u101b\u101c\u1012\u103a DataFrame \u101e\u100a\u103a \u1019\u1030\u101b\u1004\u103a\u1038 DataFrame \u1019\u103e “ assists”  \u1014\u103e\u1004\u1037\u103a “ bounces”  \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1016\u101a\u103a\u101b\u103e\u102c\u1038\u1015\u103c\u102e\u1038 \u1000\u103b\u1014\u103a\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1011\u102d\u1014\u103a\u1038\u101e\u102d\u1019\u103a\u1038\u1011\u102c\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u101e\u1010\u102d\u1015\u103c\u102f\u1015\u102b\u104b<\/span><\/p>\n
 \u1011\u1015\u103a\u101c\u1031\u102c\u1004\u103a\u1038\u1021\u101b\u1004\u103a\u1038\u1021\u1019\u103c\u1005\u103a\u1019\u103b\u102c\u1038<\/strong><\/span><\/h3>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1015\u1014\u103a\u1012\u102b\u1019\u103b\u102c\u1038\u1010\u103d\u1004\u103a \u1021\u1001\u103c\u102c\u1038\u1018\u102f\u1036\u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u101e\u100a\u103a-<\/span><\/p>\n
 Pandas DataFrame \u101b\u103e\u102d \u1015\u1011\u1019\u1000\u1031\u102c\u103a\u101c\u1036\u1000\u102d\u102f \u1018\u101a\u103a\u101c\u102d\u102f\u1016\u101a\u103a\u101b\u103e\u102c\u1038\u1019\u101c\u1032\u104b<\/a>
 Pandas \u101b\u103e\u102d \u1011\u1015\u103a\u1014\u1031\u101e\u1031\u102c\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1016\u101a\u103a\u101b\u103e\u102c\u1038\u1014\u100a\u103a\u1038<\/a>
 Pandas \u101b\u103e\u102d \u1021\u100a\u103d\u103e\u1014\u103a\u1038\u1021\u102c\u1038\u1016\u103c\u1004\u1037\u103a \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1016\u103b\u1000\u103a\u1014\u100a\u103a\u1038<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Pandas DataFrame \u1010\u103d\u1004\u103a \u1021\u1001\u103b\u102d\u102f\u1037\u101e\u1031\u102c\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101e\u102c \u1006\u1000\u103a\u101c\u1000\u103a\u1011\u102c\u1038\u101b\u103e\u102d\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101e\u1004\u103a\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a- \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 1- \u1019\u100a\u103a\u101e\u100a\u1037\u103a\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101e\u102d\u1019\u103a\u1038\u1006\u100a\u103a\u1038\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1015\u102b\u104b #only keep columns ‘col1’ and ‘col2’ df[[‘ col1 ‘, ‘ col2 ‘]] \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 2- \u1016\u103b\u1000\u103a\u101b\u1014\u103a \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1015\u102b\u104b #drop columns ‘col3’ and ‘col4’ df[df. columns [~df. columns . isin ([‘ col3 ‘,’ col4 ‘])]] \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1014\u1019\u1030\u1014\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b pandas DataFrame \u1016\u103c\u1004\u1037\u103a \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u1005\u102e\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a- import pandas […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"\nPandas \u1010\u103d\u1004\u103a \u1021\u1001\u103b\u102d\u102f\u1037\u101e\u1031\u102c\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1011\u102d\u1014\u103a\u1038\u101e\u102d\u1019\u103a\u1038\u1014\u100a\u103a\u1038 (\u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u1014\u103e\u1004\u1037\u103a\u1021\u1010\u1030) \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a \u1014\u1019\u1030\u1014\u102c\u1019\u103b\u102c\u1038\u1005\u103d\u102c\u1016\u103c\u1004\u1037\u103a \u1015\u1014\u103a\u1012\u102b DataFrame \u1010\u103d\u1004\u103a \u1021\u1001\u103b\u102d\u102f\u1037\u101e\u1031\u102c\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1006\u1000\u103a\u101c\u1000\u103a\u1011\u102c\u1038\u101b\u103e\u102d\u101b\u1019\u100a\u103a\u1000\u102d\u102f 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content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a \u1014\u1019\u1030\u1014\u102c\u1019\u103b\u102c\u1038\u1005\u103d\u102c\u1016\u103c\u1004\u1037\u103a \u1015\u1014\u103a\u1012\u102b DataFrame \u1010\u103d\u1004\u103a \u1021\u1001\u103b\u102d\u102f\u1037\u101e\u1031\u102c\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1006\u1000\u103a\u101c\u1000\u103a\u1011\u102c\u1038\u101b\u103e\u102d\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/my\/\u1015\u1014\u103a\u1012\u102b\u1025\u101a\u103b\u102c\u1009\u103a\u1000\u1031\u102c\u103a\u101c\u1036\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-22T10:02:37+00:00\" \/>\n<meta name=\"author\" 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