{"id":3723,"date":"2023-07-15T22:29:34","date_gmt":"2023-07-15T22:29:34","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%92%e1%80%b1%e1%80%90%e1%80%ac%e1%80%98%e1%80%b1%e1%80%ac%e1%80%84%e1%80%ba-7\/"},"modified":"2023-07-15T22:29:34","modified_gmt":"2023-07-15T22:29:34","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%92%e1%80%b1%e1%80%90%e1%80%ac%e1%80%98%e1%80%b1%e1%80%ac%e1%80%84%e1%80%ba-7","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%92%e1%80%b1%e1%80%90%e1%80%ac%e1%80%98%e1%80%b1%e1%80%ac%e1%80%84%e1%80%ba-7\/","title":{"rendered":"Pandas- dataframes \u1014\u103e\u1005\u103a\u1001\u102f \u1010\u1030\u100a\u102e\u1019\u103e\u102f\u101b\u103e\u102d\u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u1014\u100a\u103a\u1038"},"content":{"rendered":"

<\/p>\n

\n

Pandas DataFrames \u1014\u103e\u1005\u103a\u1001\u102f\u101e\u100a\u103a \u1010\u1030\u100a\u102e\u1001\u103c\u1004\u103a\u1038\u101b\u103e\u102d\u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b \u1021\u1001\u103c\u1031\u1001\u1036 syntax \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

 df1. equals<\/span> (df2)\n<\/strong><\/pre>\n
 \u104e\u1004\u103a\u1038\u101e\u100a\u103a True<\/strong> \u101e\u102d\u102f\u1037\u1019\u101f\u102f\u1010\u103a False<\/strong> \u104f\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1000\u102d\u102f \u1015\u103c\u1014\u103a\u1015\u1031\u1038\u101c\u102d\u1019\u1037\u103a\u1019\u100a\u103a\u104b<\/span><\/p>\n
 DataFrame \u1014\u103e\u1005\u103a\u1001\u102f \u1019\u100a\u102e\u1015\u102b\u1000\u104a \u1015\u1011\u1019 DataFrame \u1010\u103d\u1004\u103a \u1019\u101b\u103e\u102d\u101e\u1031\u102c \u1012\u102f\u1010\u102d\u101a DataFrame \u1010\u103d\u1004\u103a \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101b\u103e\u102c\u1016\u103d\u1031\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b syntax \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
 #perform outer join on two DataFrames\n<\/span>all_df = df1. merge<\/span> (df2, indicator= True<\/span> , how=' outer<\/span> ')\n\n#find which rows only exist in second DataFrame\n<\/span>only_df2 = all_df[all_df[' _merge<\/span> '] == ' right_only<\/span> ']\nonly_df2 = only_df2. drop<\/span> (' _merge<\/span> ', axis= 1<\/span> )<\/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- \u1015\u1014\u103a\u1012\u102b\u1014\u103e\u1005\u103a\u1000\u1031\u102c\u1004\u103a DataFrames \u1010\u1030\u100a\u102e\u1019\u103e\u102f\u101b\u103e\u102d\u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u1015\u102b\u104b<\/strong><\/h2>\n
 \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u1010\u103d\u1004\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b Panda DataFrames \u1014\u103e\u1005\u103a\u1001\u102f\u101b\u103e\u102d\u101e\u100a\u103a\u101f\u102f \u101a\u1030\u1006\u1000\u103c\u1015\u102b\u1005\u102d\u102f\u1037\u104b<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create first DataFrame\ndf1 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E'], \n                    ' points<\/span> ': [12, 15, 22, 29, 24]}) \n\nprint<\/span> (df1)\n\n  team points\n0 to 12\n1 B 15\n2 C 22\n3 D 29\n4 E 24\n\n#create second DataFrame\n<\/span>df2 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'D', 'F', 'G', 'H'],\n                    ' points<\/span> ': [12, 29, 15, 19, 10]})\n\nprint<\/span> (df2)\n\n  team points\n0 to 12\n1 D 29\n2 F 15\n3 G 19\n4:10 a.m.\n<\/span><\/span><\/strong><\/pre>\n
 DataFrames \u1014\u103e\u1005\u103a\u1001\u102f\u101e\u100a\u103a \u1010\u1030\u100a\u102e\u1001\u103c\u1004\u103a\u1038\u101b\u103e\u102d\u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b syntax \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
 #check if two DataFrames are equal<\/strong><\/span>\ndf1. equals<\/span> (df2)\n\nFalse<\/strong><\/span><\/pre>\n
 output \u101e\u100a\u103a False \u1000\u102d\u102f<\/strong> \u1015\u103c\u1014\u103a\u1015\u1031\u1038\u101e\u100a\u103a\u104a \u1006\u102d\u102f\u101c\u102d\u102f\u101e\u100a\u103a\u1019\u103e\u102c DataFrames \u1014\u103e\u1005\u103a\u1001\u102f\u101e\u100a\u103a \u1019\u100a\u102e\u1015\u1031\u104b<\/span><\/p>\n
 \u1011\u102d\u102f\u1037\u1014\u1031\u102c\u1000\u103a \u1012\u102f\u1010\u102d\u101a DataFrame \u1010\u103d\u1004\u103a \u1019\u100a\u103a\u101e\u100a\u1037\u103a\u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038 \u101b\u103e\u102d\u101e\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u102c\u1016\u103d\u1031\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b syntax \u1000\u102d\u102f \u101e\u102f\u1036\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u1031\u102c\u103a\u101c\u100a\u103a\u1038 \u1015\u1011\u1019 \u1019\u101f\u102f\u1010\u103a\u1015\u102b\u104b<\/span><\/p>\n
 #perform outer join on two DataFrames\n<\/span>all_df = df1. merge<\/span> (df2, indicator= True<\/span> , how=' outer<\/span> ')\n\n#find which rows only exist in second DataFrame\n<\/span>only_df2 = all_df[all_df[' _merge<\/span> '] == ' right_only<\/span> ']\nonly_df2 = only_df2. drop<\/span> (' _merge<\/span> ', axis= 1<\/span> )\n\n#view results\n<\/span>print<\/span> (only_df2)\n\n  team points\n5 F 15\n6 G 19\n7:10 a.m.<\/strong><\/pre>\n
 \u101b\u101c\u1012\u103a\u1019\u103e\u104a \u1015\u1011\u1019 DataFrame \u1010\u103d\u1004\u103a\u1019\u101b\u103e\u102d\u101e\u1031\u102c\u1012\u102f\u1010\u102d\u101a DataFrame \u1010\u103d\u1004\u103a\u1021\u1010\u1014\u103a\u1038\u101e\u102f\u1036\u1038\u1010\u1014\u103a\u1038\u101b\u103e\u102d\u101e\u100a\u103a\u1000\u102d\u102f\u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u1010\u103d\u1031\u1037\u1019\u103c\u1004\u103a\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b<\/span><\/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\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- DataFrame \u1010\u1005\u103a\u1001\u102f\u1019\u103e \u1014\u1031\u102c\u1000\u103a\u1010\u1005\u103a\u1001\u102f\u101e\u102d\u102f\u1037 \u1000\u1031\u102c\u103a\u101c\u1036\u1010\u1005\u103a\u1001\u102f\u1000\u102d\u102f \u1011\u100a\u1037\u103a\u1015\u102b\u104b<\/a>
 Pandas- \u1021\u1001\u103c\u102c\u1038 DataFrame \u1010\u103d\u1004\u103a \u1019\u101b\u103e\u102d\u101e\u1031\u102c \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101b\u101a\u1030\u1015\u102b\u104b<\/a>
 Pandas- \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1005\u103d\u102c\u101e\u100a\u103a \u1010\u1030\u100a\u102e\u1019\u103e\u102f\u101b\u103e\u102d\u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u1014\u100a\u103a\u1038<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Pandas DataFrames \u1014\u103e\u1005\u103a\u1001\u102f\u101e\u100a\u103a \u1010\u1030\u100a\u102e\u1001\u103c\u1004\u103a\u1038\u101b\u103e\u102d\u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b \u1021\u1001\u103c\u1031\u1001\u1036 syntax \u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u1015\u102b\u101e\u100a\u103a\u104b df1. equals (df2) \u104e\u1004\u103a\u1038\u101e\u100a\u103a True \u101e\u102d\u102f\u1037\u1019\u101f\u102f\u1010\u103a False \u104f\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1000\u102d\u102f \u1015\u103c\u1014\u103a\u1015\u1031\u1038\u101c\u102d\u1019\u1037\u103a\u1019\u100a\u103a\u104b DataFrame \u1014\u103e\u1005\u103a\u1001\u102f \u1019\u100a\u102e\u1015\u102b\u1000\u104a \u1015\u1011\u1019 DataFrame \u1010\u103d\u1004\u103a \u1019\u101b\u103e\u102d\u101e\u1031\u102c \u1012\u102f\u1010\u102d\u101a DataFrame \u1010\u103d\u1004\u103a \u1021\u1010\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101b\u103e\u102c\u1016\u103d\u1031\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b syntax \u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u1015\u102b\u101e\u100a\u103a\u104b #perform outer join on two DataFrames all_df = df1. merge (df2, indicator= True , how=’ outer ‘) #find which rows […]<\/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- DataFrames \u1014\u103e\u1005\u103a\u1001\u102f \u1010\u1030\u100a\u102e\u1019\u103e\u102f\u101b\u103e\u102d\u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\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 \u1015\u1014\u103a\u1012\u102b\u1014\u103e\u1005\u103a\u1000\u1031\u102c\u1004\u103a DataFrames \u1010\u1030\u100a\u102e\u1001\u103c\u1004\u103a\u1038\u101b\u103e\u102d\u104a \u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u1016\u103c\u1004\u1037\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\" href=\"https:\/\/statorials.org\/my\/\u1015\u1014\u103a\u1012\u102b\u1019\u103b\u102c\u1038\u101e\u100a\u103a-\u1012\u1031\u1010\u102c\u1018\u1031\u102c\u1004\u103a-7\/\" \/>\n<meta property=\"og:locale\" content=\"my_MM\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas- DataFrames \u1014\u103e\u1005\u103a\u1001\u102f \u1010\u1030\u100a\u102e\u1019\u103e\u102f\u101b\u103e\u102d\u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u1014\u100a\u103a\u1038 - Statorials\" \/>\n<meta property=\"og:description\" content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a \u1015\u1014\u103a\u1012\u102b\u1014\u103e\u1005\u103a\u1000\u1031\u102c\u1004\u103a DataFrames \u1010\u1030\u100a\u102e\u1001\u103c\u1004\u103a\u1038\u101b\u103e\u102d\u104a \u1019\u101b\u103e\u102d \u1005\u1005\u103a\u1006\u1031\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u1016\u103c\u1004\u1037\u103a \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\u1019\u103b\u102c\u1038\u101e\u100a\u103a-\u1012\u1031\u1010\u102c\u1018\u1031\u102c\u1004\u103a-7\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-15T22:29:34+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin Anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin Anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" 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