{"id":3698,"date":"2023-07-16T01:59:39","date_gmt":"2023-07-16T01:59:39","guid":{"rendered":"https:\/\/statorials.org\/my\/%e1%80%95%e1%80%94%e1%80%ba%e1%80%92%e1%80%ab%e1%80%a1%e1%80%af%e1%80%95%e1%80%ba%e1%80%85%e1%80%af%e1%80%9b%e1%80%be%e1%80%ad%e1%80%81%e1%80%bc%e1%80%84%e1%80%ba%e1%80%b8%e1%81%8b\/"},"modified":"2023-07-16T01:59:39","modified_gmt":"2023-07-16T01:59:39","slug":"%e1%80%95%e1%80%94%e1%80%ba%e1%80%92%e1%80%ab%e1%80%a1%e1%80%af%e1%80%95%e1%80%ba%e1%80%85%e1%80%af%e1%80%9b%e1%80%be%e1%80%ad%e1%80%81%e1%80%bc%e1%80%84%e1%80%ba%e1%80%b8%e1%81%8b","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%a1%e1%80%af%e1%80%95%e1%80%ba%e1%80%85%e1%80%af%e1%80%9b%e1%80%be%e1%80%ad%e1%80%81%e1%80%bc%e1%80%84%e1%80%ba%e1%80%b8%e1%81%8b\/","title":{"rendered":"Pandas – "\u1015\u102d\u102f\u1004\u103a\u1006\u102d\u102f\u1004\u103a\u1019\u103e\u102f\u1021\u101c\u102d\u102f\u1000\u103a \u1021\u102f\u1015\u103a\u1005\u102f\u1016\u103d\u1032\u1037\u1001\u103c\u1004\u103a\u1038" \u1021\u1010\u103d\u1000\u103a \u101b\u102d\u102f\u1038\u101b\u103e\u1004\u103a\u1038\u101e\u1031\u102c \u1016\u1031\u102c\u103a\u1019\u103c\u1030\u101c\u102c"},"content":{"rendered":"

<\/p>\n

\n

\u1015\u1014\u103a\u1012\u102b\u1019\u103b\u102c\u1038\u1010\u103d\u1004\u103a “ GROUP BY HAVING” SQL \u1000\u103c\u1031\u1004\u103c\u102c\u1001\u103b\u1000\u103a\u1014\u103e\u1004\u1037\u103a\u100a\u102e\u1019\u103b\u103e\u101e\u1031\u102c \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1021\u1001\u103c\u1031\u1001\u1036\u1021\u1011\u102c\u1038\u1021\u101e\u102d\u102f\u1000\u102d\u102f\u101e\u102f\u1036\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n

 df. groupby<\/span> (' some_column<\/span> '). filter<\/span> ( lambda<\/span> x: some condition)\n<\/span><\/span><\/strong><\/pre>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b\u1014\u1019\u1030\u1014\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b pandas DataFrame \u1014\u103e\u1004\u1037\u103a \u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\u103a \u1024 syntax \u1000\u102d\u102f\u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a \u104b<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C'],\n                   ' position<\/span> ': ['G', 'F', 'F', 'G', 'F', 'F', 'G', 'G'],\n                   ' points<\/span> ': [30, 22, 19, 14, 14, 11, 20, 28]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team position points\n0 AG 30\n1 AF 22\n2 FY 19\n3 BG 14\n4 BF 14\n5 BF 11\n6 GC 20\n7 GC 28\n<\/b><\/pre>\n
 \u1025\u1015\u1019\u102c 1- Count \u1015\u102b\u101e\u1031\u102c \u1015\u1014\u103a\u1012\u102b\u1021\u102f\u1015\u103a\u1005\u102f<\/strong><\/span><\/h2>\n
 \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u101e\u100a\u103a \u1021\u1016\u103d\u1032\u1037<\/strong> \u1000\u1031\u102c\u103a\u101c\u1036\u101b\u103e\u102d\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1021\u1015\u1031\u102b\u103a\u1021\u1001\u103c\u1031\u1001\u1036\u104d \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1021\u102f\u1015\u103a\u1005\u102f\u1016\u103d\u1032\u1037\u1014\u100a\u103a\u1038\u1000\u102d\u102f\u1015\u103c\u101e\u1015\u103c\u102e\u1038 2 \u1011\u1000\u103a\u1000\u103c\u102e\u1038\u101e\u1031\u102c\u1021\u101e\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101e\u102c \u1005\u1005\u103a\u1011\u102f\u1010\u103a\u1015\u102b-<\/span><\/span><\/p>\n
 #group by team and filter for teams with count > 2<\/span>\ndf. groupby<\/span> (' team<\/span> '). filter<\/span> ( lambda<\/span> x: len<\/span> (x) > 2<\/span> )\n\n\n        team position points\n0 A G 30\n1 A F 22\n2 A F 19\n3 B G 14\n4 B F 14\n5 B F 11<\/span><\/span><\/strong><\/pre>\n
 \u1024\u1021\u101e\u1004\u103a\u1038\u1014\u103e\u1005\u103a\u101e\u1004\u103a\u1038\u1005\u101c\u102f\u1036\u1038\u101e\u100a\u103a \u1014\u1036\u1015\u102b\u1010\u103a 2 \u1011\u1000\u103a\u1000\u103c\u102e\u1038\u101e\u1031\u102c\u1021\u101e\u1004\u103a\u1038\u1016\u103c\u1005\u103a\u101e\u1031\u102c\u1000\u103c\u1031\u102c\u1004\u1037\u103a “ A”  \u101e\u102d\u102f\u1037\u1019\u101f\u102f\u1010\u103a “ B”  \u104f\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u101b\u103e\u102d\u101e\u1031\u102c\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101e\u102c \u1015\u103c\u1014\u103a\u1015\u1031\u1038\u101e\u100a\u103a\u1000\u102d\u102f \u101e\u1010\u102d\u1015\u103c\u102f\u1015\u102b\u104b<\/span><\/p>\n
 \u1025\u1015\u1019\u102c 2- \u1015\u103b\u1019\u103a\u1038\u1019\u103b\u103e\u1015\u102b\u101b\u103e\u102d\u101e\u1031\u102c \u1015\u1014\u103a\u1012\u102b\u1021\u102f\u1015\u103a\u1005\u102f<\/strong><\/span><\/h2>\n
 \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u101e\u100a\u103a \u1021\u1016\u103d\u1032\u1037<\/strong> \u1000\u1031\u102c\u103a\u101c\u1036\u101b\u103e\u102d \u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1021\u1015\u1031\u102b\u103a\u1021\u1001\u103c\u1031\u1001\u1036\u104d \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1021\u102f\u1015\u103a\u1005\u102f\u1016\u103d\u1032\u1037\u1014\u100a\u103a\u1038\u1000\u102d\u102f\u1015\u103c\u101e\u1015\u103c\u102e\u1038 \u1015\u103b\u1019\u103a\u1038\u1019\u103b\u103e \u1021\u1019\u103e\u1010\u103a<\/strong> \u1010\u1014\u103a\u1016\u102d\u102f\u1038 20 \u1011\u1000\u103a\u1000\u103c\u102e\u1038\u101e\u1031\u102c\u1021\u101e\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101e\u102c \u1005\u1005\u103a\u1011\u102f\u1010\u103a\u1015\u102b-<\/span><\/p>\n
 #group by team and filter for teams with mean points > 20<\/span>\ndf. groupby<\/span> (' team<\/span> '). filter<\/span> ( lambda<\/span> x: x[' points<\/span> ']. mean<\/span> () > 20<\/span> )\n\n        team position points\n0 A G 30\n1 A F 22\n2 A F 19\n6 C G 20\n7 C G 28<\/span><\/span><\/strong><\/pre>\n
 \u1024\u1021\u101e\u1004\u103a\u1038\u1014\u103e\u1005\u103a\u101e\u1004\u103a\u1038\u101e\u100a\u103a \u1015\u103b\u1019\u103a\u1038\u1019\u103b\u103e\u1021\u1019\u103e\u1010\u103a\u1010\u1014\u103a\u1016\u102d\u102f\u1038 20 \u1011\u1000\u103a\u1000\u103c\u102e\u1038\u101e\u1031\u102c \u1021\u101e\u1004\u103a\u1038\u1014\u103e\u1005\u103a\u101e\u1004\u103a\u1038\u1016\u103c\u1005\u103a\u101e\u1031\u102c\u1000\u103c\u1031\u102c\u1004\u1037\u103a “ A”  \u101e\u102d\u102f\u1037\u1019\u101f\u102f\u1010\u103a “ C”  \u101b\u103e\u102d\u101e\u1031\u102c \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101e\u102c \u1015\u103c\u1014\u103a\u1015\u1031\u1038\u101e\u100a\u103a\u1000\u102d\u102f \u101e\u1010\u102d\u1015\u103c\u102f\u1015\u102b\u104b<\/span><\/p>\n
 \u1025\u1015\u1019\u102c 3- \u1021\u101c\u102f\u1036\u1038\u101c\u102d\u102f\u1000\u103a\u1015\u102b\u101b\u103e\u102d\u101e\u1031\u102c \u1015\u1014\u103a\u1012\u102b\u1021\u102f\u1015\u103a\u1005\u102f<\/strong><\/span><\/h2>\n
 \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u101e\u100a\u103a Team<\/strong> \u1000\u1031\u102c\u103a\u101c\u1036\u101b\u103e\u102d \u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1021\u101c\u102d\u102f\u1000\u103a \u1010\u1014\u103a\u1038\u1005\u102e\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u1015\u103c\u101e\u1015\u103c\u102e\u1038 \u1021\u1019\u103e\u1010\u103a<\/strong> \u1015\u1031\u102b\u1004\u103a\u1038 48 \u1021\u1010\u102d\u1021\u1000\u103b\u101b\u103e\u102d\u101e\u1031\u102c \u1021\u101e\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101e\u102c \u1005\u1005\u103a\u1011\u102f\u1010\u103a\u1015\u102b\u104b<\/span><\/p>\n
 #group by team and filter for teams with sum of points equal to 48<\/span>\ndf. groupby<\/span> (' team<\/span> '). filter<\/span> ( lambda<\/span> x: x[' points<\/span> ']. sum<\/span> () == 48<\/span> )\n\n        team position points\n6 C G 20\n7 C G 28<\/span><\/span><\/strong><\/pre>\n
 \u1024\u1021\u101e\u1004\u103a\u1038\u101e\u100a\u103a 48 \u1014\u103e\u1004\u1037\u103a \u100a\u102e\u1019\u103b\u103e\u101e\u1031\u102c \u1021\u1019\u103e\u1010\u103a\u1015\u1031\u102b\u1004\u103a\u1038\u1012\u103a\u101b\u103e\u102d\u101e\u1031\u102c \u1010\u1005\u103a\u1001\u102f\u1010\u100a\u103a\u1038\u101e\u1031\u102c\u1021\u101e\u1004\u103a\u1038\u1016\u103c\u1005\u103a\u101e\u1031\u102c\u1000\u103c\u1031\u102c\u1004\u1037\u103a “ C”  \u104f \u1021\u101e\u1004\u103a\u1038\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u101b\u103e\u102d\u101e\u1031\u102c \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u101e\u102c \u1015\u103c\u1014\u103a\u1015\u1031\u1038\u101e\u100a\u103a\u1000\u102d\u102f \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><\/h2>\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- \u1000\u1031\u102c\u103a\u101c\u1036\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1014\u103e\u1004\u1037\u103a \u1000\u102d\u102f\u1000\u103a\u100a\u102e\u101e\u1031\u102c \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u104f \u1021\u100a\u103d\u103e\u1014\u103a\u1038\u1000\u102d\u102f \u101b\u101a\u1030\u1015\u102b\u104b<\/a>
 Pandas- \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1011\u102c\u1038\u101e\u1031\u102c\u1005\u102c\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1015\u102b\u101b\u103e\u102d\u101e\u1031\u102c \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u101b\u103d\u1031\u1038\u1001\u103b\u101a\u103a\u101b\u1019\u100a\u103a\u1014\u100a\u103a\u1038\u104b<\/a>
 Pandas- \u1000\u1031\u102c\u103a\u101c\u1036\u1010\u103d\u1004\u103a \u1005\u102c\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u1015\u102b\u101b\u103e\u102d\u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u1014\u100a\u103a\u1038<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u1015\u1014\u103a\u1012\u102b\u1019\u103b\u102c\u1038\u1010\u103d\u1004\u103a “ GROUP BY HAVING” SQL \u1000\u103c\u1031\u1004\u103c\u102c\u1001\u103b\u1000\u103a\u1014\u103e\u1004\u1037\u103a\u100a\u102e\u1019\u103b\u103e\u101e\u1031\u102c \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1021\u1001\u103c\u1031\u1001\u1036\u1021\u1011\u102c\u1038\u1021\u101e\u102d\u102f\u1000\u102d\u102f\u101e\u102f\u1036\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b df. groupby (‘ some_column ‘). filter ( lambda x: some condition) \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b\u1014\u1019\u1030\u1014\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b pandas DataFrame \u1014\u103e\u1004\u1037\u103a \u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\u103a \u1024 syntax \u1000\u102d\u102f\u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a \u104b import pandas as pd #createDataFrame df = pd. DataFrame ({‘ team ‘: [‘A’, ‘A’, ‘A’, ‘B’, ‘B’, ‘B’, ‘C’, ‘C’], ‘ position ‘: [‘G’, ‘F’, […]<\/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":"\n\u1015\u1014\u103a\u1012\u102b\u1019\u103b\u102c\u1038- "\u101b\u103e\u102d\u1001\u103c\u1004\u103a\u1038\u1016\u103c\u1004\u1037\u103a \u1021\u102f\u1015\u103a\u1005\u102f\u1016\u103d\u1032\u1037\u1001\u103c\u1004\u103a\u1038" \u1021\u1010\u103d\u1000\u103a \u101b\u102d\u102f\u1038\u101b\u103e\u1004\u103a\u1038\u101e\u1031\u102c \u1016\u1031\u102c\u103a\u1019\u103c\u1030\u101c\u102c - Statorials<\/title>\n<meta name=\"description\" content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u101e\u100a\u103a pandas DataFrame \u1010\u103d\u1004\u103a \u1021\u102f\u1015\u103a\u1005\u102f\u1016\u103d\u1032\u1037\u1011\u102c\u1038\u101e\u1031\u102c SQL \u1014\u103e\u1004\u1037\u103a\u100a\u102e\u1019\u103b\u103e\u101e\u1031\u102c \u1016\u1031\u102c\u103a\u1019\u103c\u1030\u101c\u102c\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/my\/\u1015\u1014\u103a\u1012\u102b\u1021\u102f\u1015\u103a\u1005\u102f\u101b\u103e\u102d\u1001\u103c\u1004\u103a\u1038\u104b\/\" \/>\n<meta property=\"og:locale\" content=\"my_MM\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u1015\u1014\u103a\u1012\u102b\u1019\u103b\u102c\u1038- "\u101b\u103e\u102d\u1001\u103c\u1004\u103a\u1038\u1016\u103c\u1004\u1037\u103a 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