{"id":3409,"date":"2023-07-17T15:39:31","date_gmt":"2023-07-17T15:39:31","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%81%e1%80%af%e1%80%94%e1%80%ba%e1%80%90%e1%80%80%e1%80%ba%e1%80%80%e1%80%bc%e1%80%9e%e1%80%8a%e1%80%ba%e1%81%8b\/"},"modified":"2023-07-17T15:39:31","modified_gmt":"2023-07-17T15:39:31","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%81%e1%80%af%e1%80%94%e1%80%ba%e1%80%90%e1%80%80%e1%80%ba%e1%80%80%e1%80%bc%e1%80%9e%e1%80%8a%e1%80%ba%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%99%e1%80%bb%e1%80%ac%e1%80%b8-%e1%80%81%e1%80%af%e1%80%94%e1%80%ba%e1%80%90%e1%80%80%e1%80%ba%e1%80%80%e1%80%bc%e1%80%9e%e1%80%8a%e1%80%ba%e1%81%8b\/","title":{"rendered":"\u1015\u1014\u103a\u1012\u102b\u1019\u103b\u102c\u1038- csv \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f\u1016\u1010\u103a\u101e\u100a\u1037\u103a\u1021\u1001\u102b \u101c\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\u101e\u103d\u102c\u1038\u1014\u100a\u103a\u1038"},"content":{"rendered":"

<\/p>\n

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Pandas DataFrame \u1011\u1032\u101e\u102d\u102f\u1037 CSV \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f\u1016\u1010\u103a\u101e\u100a\u1037\u103a\u1021\u1001\u102b \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\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- \u101e\u102e\u1038\u1001\u103c\u102c\u1038\u1021\u1010\u1014\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\u1015\u102b\u104b<\/strong><\/span><\/p>\n

 #import DataFrame and skip 2nd row\n<\/span>df = pd. read_csv<\/span> ('my_data.csv', skiprows=[ 2<\/span> ])\n<\/strong><\/pre>\n
 \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 2- \u1019\u103b\u102c\u1038\u1005\u103d\u102c\u101e\u1031\u102c \u101e\u102e\u1038\u1001\u103c\u102c\u1038\u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\u1001\u103c\u1004\u103a\u1038\u104b<\/strong><\/span><\/p>\n
 #import DataFrame and skip 2nd and 4th row\n<\/span>df = pd. read_csv<\/span> (' my_data.csv', skiprows=[2,4<\/span> ]<\/span> )<\/strong><\/pre>\n
 \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 3- \u1015\u1011\u1019 N \u101c\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\u1015\u102b\u104b<\/strong><\/span><\/p>\n
 #import DataFrame and skip first 2 rows\n<\/span>df = pd. read_csv<\/span> ('my_data.csv', skiprows= 2<\/span> )<\/strong><\/pre>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a basketball_data.csv<\/strong> \u101f\u102f\u1001\u1031\u102b\u103a\u101e\u1031\u102c \u1021\u1031\u102c\u1000\u103a\u1015\u102b CSV \u1016\u102d\u102f\u1004\u103a\u1016\u103c\u1004\u1037\u103a \u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\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
\"\"<\/p>\n
 \u1025\u1015\u1019\u102c 1- \u101e\u102e\u1038\u1001\u103c\u102c\u1038\u1021\u1010\u1014\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u1000\u102d\u102f \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\u1015\u102b\u104b<\/strong><\/span><\/h2>\n
 CSV \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f \u1010\u1004\u103a\u101e\u103d\u1004\u103a\u1038\u101b\u1014\u103a\u1014\u103e\u1004\u1037\u103a \u1012\u102f\u1010\u102d\u101a\u1005\u102c\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1000\u102d\u102f \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\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\u102b\u101e\u100a\u103a\u104b<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#import DataFrame and skip 2nd row\n<\/span>df = pd. read_csv<\/span> ('basketball_data.csv', skiprows=[ 2<\/span> ])\n\n#view DataFrame\n<\/span>df\n\n        team points rebounds\n0 to 22 10\n1 C 29 6\n2 D 30 2\n<\/b><\/pre>\n
 Pandas DataFrame \u101e\u102d\u102f\u1037 CSV \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f \u1011\u100a\u1037\u103a\u101e\u103d\u1004\u103a\u1038\u101e\u100a\u1037\u103a\u1021\u1001\u102b \u1012\u102f\u1010\u102d\u101a\u1005\u102c\u1000\u103c\u1031\u102c\u1004\u103a\u1038 (\u1021\u1016\u103d\u1032\u1037 “ B”  \u1014\u103e\u1004\u1037\u103a) \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\u1011\u102c\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u101e\u1010\u102d\u1015\u103c\u102f\u1015\u102b\u104b<\/span><\/p>\n
 \u1019\u103e\u1010\u103a\u1001\u103b\u1000\u103a<\/strong> – CSV \u1016\u102d\u102f\u1004\u103a\u104f \u1015\u1011\u1019\u1005\u102c\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1000\u102d\u102f \u101c\u102d\u102f\u1004\u103a\u1038 0 \u101f\u102f \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1025\u1015\u1019\u102c 2- \u101e\u102e\u1038\u1001\u103c\u102c\u1038\u1019\u103b\u1009\u103a\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1005\u103d\u102c\u1000\u102d\u102f \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\u1001\u103c\u1004\u103a\u1038\u104b<\/strong><\/span><\/h2>\n
 CSV \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f \u1010\u1004\u103a\u101e\u103d\u1004\u103a\u1038\u1015\u103c\u102e\u1038 \u1012\u102f\u1010\u102d\u101a\u1014\u103e\u1004\u1037\u103a \u1005\u1010\u102f\u1010\u1039\u1011\u101c\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\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\u102b\u101e\u100a\u103a\u104b<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#import DataFrame and skip 2nd and 4th rows\n<\/span>df = pd. read_csv<\/span> ('basketball_data.csv', skiprows=[ 2<\/span> , 4<\/span> ])\n\n#view DataFrame\n<\/span>df\n\n        team points rebounds\n0 to 22 10\n1 C 29 6\n<\/b><\/pre>\n
 Pandas DataFrame \u1011\u1032\u101e\u102d\u102f\u1037 CSV \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f \u1011\u100a\u1037\u103a\u101e\u103d\u1004\u103a\u1038\u101e\u100a\u1037\u103a\u1021\u1001\u102b \u1012\u102f\u1010\u102d\u101a\u1014\u103e\u1004\u1037\u103a \u1005\u1010\u102f\u1010\u1039\u1011\u101c\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038 (\u1021\u1016\u103d\u1032\u1037 “ B”  \u1014\u103e\u1004\u1037\u103a “ D”  \u1010\u102d\u102f\u1037\u1015\u102b\u101b\u103e\u102d\u101e\u1031\u102c) \u1000\u102d\u102f \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\u1011\u102c\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u101e\u1010\u102d\u1015\u103c\u102f\u1015\u102b\u104b<\/span><\/p>\n
 \u1025\u1015\u1019\u102c 3- \u1015\u1011\u1019 N \u101c\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\u1015\u102b\u104b<\/strong><\/span><\/h2>\n
 CSV \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f \u1010\u1004\u103a\u101e\u103d\u1004\u103a\u1038\u1015\u103c\u102e\u1038 \u1015\u1011\u1019\u1005\u102c\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1014\u103e\u1005\u103a\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\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\u102b\u101e\u100a\u103a\u104b<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#import DataFrame and skip first 2 rows\n<\/span>df = pd. read_csv<\/span> ('basketball_data.csv', skiprows= 2<\/span> )\n\n#view DataFrame\n<\/span>df\n\n        B 14 9\n0 C 29 6\n1 D 30 2\n<\/b><\/pre>\n
 CSV \u1016\u102d\u102f\u1004\u103a\u104f \u1015\u1011\u1019\u1019\u103b\u1009\u103a\u1038\u1014\u103e\u1005\u103a\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\u101e\u103d\u102c\u1038\u1001\u1032\u1037\u1015\u103c\u102e\u1038 \u1014\u1031\u102c\u1000\u103a\u101b\u1014\u102d\u102f\u1004\u103a\u101e\u1031\u102c\u101c\u102d\u102f\u1004\u103a\u1038 (\u1021\u1016\u103d\u1032\u1037 “ B”  \u1014\u103e\u1004\u1037\u103a\u1021\u1010\u1030) \u101e\u100a\u103a DataFrame \u104f \u1001\u1031\u102b\u1004\u103a\u1038\u1005\u102e\u1038\u101c\u102d\u102f\u1004\u103a\u1038\u1016\u103c\u1005\u103a\u101c\u102c\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><\/h2>\n
 \u1021\u1031\u102c\u1000\u103a\u1015\u102b \u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a Python \u1010\u103d\u1004\u103a \u1021\u1001\u103c\u102c\u1038\u101e\u1031\u102c \u1021\u101e\u102f\u1036\u1038\u1019\u103b\u102c\u1038\u101e\u1031\u102c \u1021\u101c\u102f\u1015\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 \u1016\u103c\u1004\u1037\u103a Excel \u1016\u102d\u102f\u1004\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f\u1016\u1010\u103a\u1014\u100a\u103a\u1038<\/a>
 Pandas DataFrame \u1000\u102d\u102f Excel \u101e\u102d\u102f\u1037\u1018\u101a\u103a\u101c\u102d\u102f\u1011\u102f\u1010\u103a\u1019\u101c\u1032\u104b<\/a>
 NumPy \u1021\u1001\u1004\u103a\u1038\u1021\u1000\u103b\u1004\u103a\u1038\u1000\u102d\u102f CSV \u1016\u102d\u102f\u1004\u103a\u1010\u1005\u103a\u1001\u102f\u101e\u102d\u102f\u1037 \u1010\u1004\u103a\u1015\u102d\u102f\u1037\u1014\u100a\u103a\u1038<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Pandas DataFrame \u1011\u1032\u101e\u102d\u102f\u1037 CSV \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f\u1016\u1010\u103a\u101e\u100a\u1037\u103a\u1021\u1001\u102b \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\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- \u101e\u102e\u1038\u1001\u103c\u102c\u1038\u1021\u1010\u1014\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\u1015\u102b\u104b #import DataFrame and skip 2nd row df = pd. read_csv (‘my_data.csv’, skiprows=[ 2 ]) \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 2- \u1019\u103b\u102c\u1038\u1005\u103d\u102c\u101e\u1031\u102c \u101e\u102e\u1038\u1001\u103c\u102c\u1038\u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\u1001\u103c\u1004\u103a\u1038\u104b #import DataFrame and skip 2nd and 4th row df = pd. read_csv (‘ my_data.csv’, skiprows=[2,4 ] ) \u1014\u100a\u103a\u1038\u101c\u1019\u103a\u1038 3- \u1015\u1011\u1019 N \u101c\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101c\u103b\u1005\u103a\u101c\u103b\u1030\u101b\u103e\u102f\u1015\u102b\u104b […]<\/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- CSV \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f\u1016\u1010\u103a\u101e\u100a\u1037\u103a\u1021\u1001\u102b \u101c\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\u101e\u103d\u102c\u1038\u1014\u100a\u103a\u1038 - Statorials<\/title>\n<meta name=\"description\" content=\"\u1025\u1015\u1019\u102c\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1004\u1037\u103a \u1015\u1014\u103a\u1012\u102b\u101b\u103e\u102d CSV \u1016\u102d\u102f\u1004\u103a\u1000\u102d\u102f \u1016\u1010\u103a\u101e\u100a\u1037\u103a\u1021\u1001\u102b \u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a \u101c\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1000\u103b\u1031\u102c\u103a\u101b\u1014\u103a \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\" 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