{"id":4233,"date":"2023-07-12T15:50:28","date_gmt":"2023-07-12T15:50:28","guid":{"rendered":"https:\/\/statorials.org\/pl\/grupa-pand-wedlug-sredniej-i-std\/"},"modified":"2023-07-12T15:50:28","modified_gmt":"2023-07-12T15:50:28","slug":"grupa-pand-wedlug-sredniej-i-std","status":"publish","type":"post","link":"https:\/\/statorials.org\/pl\/grupa-pand-wedlug-sredniej-i-std\/","title":{"rendered":"Pandy: oblicz \u015bredni\u0105 i standard kolumny w groupby"},"content":{"rendered":"

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Mo\u017cesz u\u017cy\u0107 nast\u0119puj\u0105cej sk\u0142adni, aby obliczy\u0107 \u015bredni\u0105 i odchylenie standardowe kolumny po u\u017cyciu operacji groupby()<\/strong> w pandach:<\/span><\/p>\n

 df. groupby<\/span> ([' team<\/span> '], as_index= False<\/span> ). agg<\/span> ({' points<\/span> ':[' mean<\/span> ', ' std<\/span> ']})\n<\/strong><\/pre>\n
 Ten konkretny przyk\u0142ad grupuje wiersze ramki DataFrame pandy wed\u0142ug warto\u015bci w kolumnie Zesp\u00f3\u0142<\/strong> , a nast\u0119pnie oblicza \u015bredni\u0105 i odchylenie standardowe warto\u015bci w kolumnie Punkty<\/strong> .<\/span><\/p>\n
 Poni\u017cszy przyk\u0142ad pokazuje, jak zastosowa\u0107 t\u0119 sk\u0142adni\u0119 w praktyce.<\/span><\/p>\n
 Przyk\u0142ad: Oblicz \u015bredni\u0105 i norm\u0119 kolumny w grupie Pandas<\/span><\/strong><\/span><\/h2>\n
 Za\u0142\u00f3\u017cmy, \u017ce mamy nast\u0119puj\u0105c\u0105 ramk\u0119 danych pand, kt\u00f3ra zawiera informacje o koszykarzach z r\u00f3\u017cnych dru\u017cyn:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'C', 'C', 'C'],\n                   ' points<\/span> ': [12, 15, 17, 17, 19, 14, 15, 20, 24, 28],\n                   ' assists<\/span> ': [5, 5, 7, 9, 10, 14, 13, 8, 2, 7]})\n                            \n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team points assists\n0 to 12 5\n1 to 15 5\n2 To 17 7\n3 To 17 9\n4 B 19 10\n5 B 14 14\n6 B 15 13\n7 C 20 8\n8 C 24 2\n9 C 28 7\n<\/b><\/pre>\n
 Do obliczenia \u015bredniej i odchylenia standardowego warto\u015bci w kolumnie punkt\u00f3w<\/strong> , pogrupowanych wed\u0142ug kolumny zespo\u0142u<\/strong> , mo\u017cemy zastosowa\u0107 nast\u0119puj\u0105c\u0105 sk\u0142adni\u0119:<\/span><\/span><\/p>\n
 #calculate mean and standard deviation of points, grouped by team<\/span>\noutput = df. groupby<\/span> ([' team<\/span> '], as_index= False<\/span> ). agg<\/span> ({' points<\/span> ':[' mean<\/span> ', ' std<\/span> ']})\n\n#view results<\/span>\nprint<\/span> (output)\n\n  team points          \n         mean std\n0 A 15.25 2.362908\n1 B 16.00 2.645751\n2 C 24.00 4.000000\n<\/strong><\/pre>\n
 Z wyniku mo\u017cemy zobaczy\u0107:<\/span><\/span><\/p>\n