{"id":2468,"date":"2023-07-22T03:30:18","date_gmt":"2023-07-22T03:30:18","guid":{"rendered":"https:\/\/statorials.org\/my\/%e1%80%95%e1%80%94%e1%80%ba%e1%80%92%e1%80%ab%e1%80%99%e1%80%bb%e1%80%ac%e1%80%b8%e1%80%9e%e1%80%8a%e1%80%ba-%e1%80%80%e1%80%b1%e1%80%ac%e1%80%ba%e1%80%9c%e1%80%b6%e1%80%90%e1%80%94%e1%80%ba-2\/"},"modified":"2023-07-22T03:30:18","modified_gmt":"2023-07-22T03:30:18","slug":"%e1%80%95%e1%80%94%e1%80%ba%e1%80%92%e1%80%ab%e1%80%99%e1%80%bb%e1%80%ac%e1%80%b8%e1%80%9e%e1%80%8a%e1%80%ba-%e1%80%80%e1%80%b1%e1%80%ac%e1%80%ba%e1%80%9c%e1%80%b6%e1%80%90%e1%80%94%e1%80%ba-2","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%99%e1%80%bb%e1%80%ac%e1%80%b8%e1%80%9e%e1%80%8a%e1%80%ba-%e1%80%80%e1%80%b1%e1%80%ac%e1%80%ba%e1%80%9c%e1%80%b6%e1%80%90%e1%80%94%e1%80%ba-2\/","title":{"rendered":"Pandas- dataframe \u1000\u102d\u102f \u1000\u1031\u102c\u103a\u101c\u1036\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1016\u103c\u1004\u1037\u103a \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1001\u103d\u1032\u1019\u100a\u103a\u1014\u100a\u103a\u1038\u104b"},"content":{"rendered":"

<\/p>\n

\n

\u1000\u1031\u102c\u103a\u101c\u1036\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1016\u103c\u1004\u1037\u103a pandas DataFrame \u1000\u102d\u102f\u1001\u103d\u1032\u101b\u1014\u103a \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

 #define value to split on<\/span>\nx = 20\n\n#define df1 as DataFrame where 'column_name' is >= 20<\/span>\ndf1 = df[df[' column_name<\/span> '] >=<\/span> x]\n\n#define df2 as DataFrame where 'column_name' is < 20<\/span>\ndf2 = df[df[' column_name<\/span> '] <<\/span> x]\n<\/strong><\/pre>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u1025\u1015\u1019\u102c\u101e\u100a\u103a \u1024 syntax \u1000\u102d\u102f \u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\u103a \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\u1011\u102c\u1038\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1025\u1015\u1019\u102c- Pandas DataFrame \u1000\u102d\u102f Column Value \u1016\u103c\u1004\u1037\u103a \u1001\u103d\u1032\u1015\u102b\u104b<\/strong><\/span><\/h3>\n
 \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u1010\u103d\u1004\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b \u1015\u1014\u103a\u1012\u102b DataFrame \u101b\u103e\u102d\u101e\u100a\u103a \u1006\u102d\u102f\u1015\u102b\u1005\u102d\u102f\u1037\u104b<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' points<\/span> ': [22, 24, 19, 18, 14, 29, 31, 16],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n        team points rebounds\n0 to 22 11\n1 B 24 8\n2 C 19 10\n3 D 18 6\n4 E 14 6\n5 F 29 5\n6 G 31 9\n7:16:12<\/span><\/span><\/strong><\/pre>\n
 DataFrame \u1000\u102d\u102f \u1015\u1011\u1019\u1010\u1005\u103a\u1001\u102f\u1010\u103d\u1004\u103a “ \u1019\u103e\u1010\u103a\u1019\u103b\u102c\u1038”  \u1011\u1000\u103a 20 \u1014\u103e\u1004\u1037\u103a \u100a\u102e\u1019\u103b\u103e\u101e\u100a\u1037\u103a \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1015\u102b\u101b\u103e\u102d\u101e\u1031\u102c \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1015\u102b\u101b\u103e\u102d\u101e\u1031\u102c DataFrame \u1014\u103e\u1005\u103a\u1001\u102f\u101e\u102d\u102f\u1037 \u1001\u103d\u1032\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u1015\u103c\u102e\u1038 \u1012\u102f\u1010\u102d\u101a\u1010\u103d\u1004\u103a “ \u1019\u103e\u1010\u103a\u1019\u103b\u102c\u1038”  \u1011\u1000\u103a\u1014\u100a\u103a\u1038\u101e\u1031\u102c \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1015\u102b\u101b\u103e\u102d\u101e\u100a\u103a-<\/span><\/p>\n
 #define value to split on<\/span>\nx = 20\n\n#define df1 as DataFrame where 'points' is >= 20<\/span>\ndf1 = df[df[' points<\/span> '] >=<\/span> x]\n\nprint<\/span> (df1)\n\n  team points rebounds\n0 to 22 11\n1 B 24 8\n5 F 29 5\n6 G 31 9\n\n#define df2 as DataFrame where 'points' is < 20<\/span>\ndf2 = df[df[' points<\/span> '] <<\/span> x]\n\nprint<\/span> (df2)\n\n  team points rebounds\n2 C 19 10\n3 D 18 6\n4 E 14 6\n7:16:12\n<\/strong><\/pre>\n
 \u101b\u101c\u1012\u103a DataFrame \u1010\u1005\u103a\u1001\u102f\u1005\u102e\u1021\u1010\u103d\u1000\u103a \u1021\u100a\u103d\u103e\u1014\u103a\u1038\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1015\u103c\u1014\u103a\u101c\u100a\u103a\u101e\u1010\u103a\u1019\u103e\u1010\u103a\u101b\u1014\u103a reset_index()<\/strong> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f\u101c\u100a\u103a\u1038 \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u101e\u1010\u102d\u1015\u103c\u102f\u1015\u102b\u104b<\/span><\/p>\n
 #define value to split on<\/span>\nx = 20\n\n#define df1 as DataFrame where 'points' is >= 20<\/span>\ndf1 = df[df[' points<\/span> '] >=<\/span> x]. reset_index<\/span> (drop= True<\/span> )\n\nprint<\/span> (df1)\n\n  team points rebounds\n0 to 22 11\n1 B 24 8\n2 F 29 5\n3 G 31 9\n\n#define df2 as DataFrame where 'points' is < 20<\/span>\ndf2 = df[df[' points<\/span> '] <<\/span> x]. reset_index<\/span> (drop= True<\/span> )\n\nprint<\/span> (df2)\n\n  team points rebounds\n0 C 19 10\n1 D 18 6\n2 E 14 6\n3:16:12<\/strong><\/pre>\n
 \u101b\u101c\u1012\u103a DataFrame \u1010\u1005\u103a\u1001\u102f\u1005\u102e\u104f \u1021\u100a\u103d\u103e\u1014\u103a\u1038\u101e\u100a\u103a \u101a\u1001\u102f 0 \u1010\u103d\u1004\u103a \u1005\u1010\u1004\u103a\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><\/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 Python \u101b\u103e\u102d \u1021\u1001\u103c\u102c\u1038\u101e\u1031\u102c \u1018\u102f\u1036\u1021\u1019\u103e\u102c\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1015\u103c\u102f\u1015\u103c\u1004\u103a\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u101e\u100a\u103a-<\/span><\/p>\n
 Pandas \u1010\u103d\u1004\u103a KeyError \u1000\u102d\u102f\u1018\u101a\u103a\u101c\u102d\u102f\u1015\u103c\u1004\u103a\u1019\u101c\u1032\u104b<\/a>
 \u1015\u103c\u1004\u103a\u1006\u1004\u103a\u1014\u100a\u103a\u1038- ValueError- float NaN \u1000\u102d\u102f int \u101e\u102d\u102f\u1037 \u1015\u103c\u1031\u102c\u1004\u103a\u1038\u101c\u1032\u104d\u1019\u101b\u1015\u102b\u104b<\/a>
 \u1015\u103c\u102f\u1015\u103c\u1004\u103a\u1014\u100a\u103a\u1038- \u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1021\u1019\u103e\u102c\u1038- Operands \u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1015\u102f\u1036\u101e\u100f\u1039\u100d\u102c\u1014\u103a\u1019\u103b\u102c\u1038\u1016\u103c\u1004\u1037\u103a \u1011\u102f\u1010\u103a\u101c\u103d\u103e\u1004\u1037\u103a\u104d\u1019\u101b\u1015\u102b\u104b<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u1000\u1031\u102c\u103a\u101c\u1036\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1016\u103c\u1004\u1037\u103a pandas DataFrame \u1000\u102d\u102f\u1001\u103d\u1032\u101b\u1014\u103a \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 #define value to split on x = 20 #define df1 as DataFrame where ‘column_name’ is >= 20 df1 = df[df[‘ column_name ‘] >= x] #define df2 as DataFrame where ‘column_name’ is < 20 df2 = df[df[‘ column_name ‘] < x] \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u1025\u1015\u1019\u102c\u101e\u100a\u103a \u1024 syntax \u1000\u102d\u102f \u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\u103a \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\u1011\u102c\u1038\u101e\u100a\u103a\u104b \u1025\u1015\u1019\u102c- 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- DataFrame \u1000\u102d\u102f \u1000\u1031\u102c\u103a\u101c\u1036\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1016\u103c\u1004\u1037\u103a \u1001\u103d\u1032\u1014\u100a\u103a\u1038 - 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 \u1000\u1031\u102c\u103a\u101c\u1036\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1016\u103c\u1004\u1037\u103a pandas DataFrame \u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1001\u103d\u1032\u101b\u1019\u100a\u103a\u1000\u102d\u102f 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