{"id":3255,"date":"2023-07-18T10:46:40","date_gmt":"2023-07-18T10:46:40","guid":{"rendered":"https:\/\/statorials.org\/pl\/grupa-pand-na-kwartal\/"},"modified":"2023-07-18T10:46:40","modified_gmt":"2023-07-18T10:46:40","slug":"grupa-pand-na-kwartal","status":"publish","type":"post","link":"https:\/\/statorials.org\/pl\/grupa-pand-na-kwartal\/","title":{"rendered":"Jak grupowa\u0107 wed\u0142ug kwarta\u0142\u00f3w w pandas dataframe (z przyk\u0142adem)"},"content":{"rendered":"

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Aby grupowa\u0107 wiersze wed\u0142ug \u0107wiartek w ramce DataFrame pandy, mo\u017cesz u\u017cy\u0107 nast\u0119puj\u0105cej podstawowej sk\u0142adni:<\/span><\/p>\n

 #convert date column to datetime<\/span>\ndf[' date<\/span> '] = pd. to_datetime<\/span> (df[' date<\/span> '])\n\n#calculate sum of values, grouped by quarter\n<\/span>df. groupby<\/span> (df[' date<\/span> ']. dt<\/span> . to_period<\/span> (' Q<\/span> '))[' values<\/span> ']. sum<\/span> ()\n<\/strong><\/pre>\n
 Ta konkretna formu\u0142a grupuje wiersze wed\u0142ug kwarta\u0142\u00f3w w kolumnie daty<\/strong> i oblicza sum\u0119 kolumny warto\u015bci<\/strong> w DataFrame.<\/span><\/p>\n
 Poni\u017cszy przyk\u0142ad pokazuje, jak zastosowa\u0107 t\u0119 sk\u0142adni\u0119 w praktyce.<\/span><\/p>\n
 Przyk\u0142ad: Jak grupowa\u0107 wed\u0142ug kwarta\u0142\u00f3w w Pandach<\/strong><\/span><\/h2>\n
 Za\u0142\u00f3\u017cmy, \u017ce mamy nast\u0119puj\u0105c\u0105 ramk\u0119 danych pandy, kt\u00f3ra pokazuje sprzeda\u017c dokonan\u0105 przez firm\u0119 w r\u00f3\u017cnych datach:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' date<\/span> ': pd. date_range<\/span> (start='1\/1\/2022', freq='M', periods= 12<\/span> ),\n                   ' sales<\/span> ': [6, 8, 10, 5, 4, 8, 8, 3, 5, 14, 8, 3]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n         dirty date\n0 2022-01-31 6\n1 2022-02-28 8\n2 2022-03-31 10\n3 2022-04-30 5\n4 2022-05-31 4\n5 2022-06-30 8\n6 2022-07-31 8\n7 2022-08-31 3\n8 2022-09-30 5\n9 2022-10-31 14\n10 2022-11-30 8\n11 2022-12-31 3<\/strong><\/span><\/pre>\n
 Powi\u0105zane:<\/strong> Jak utworzy\u0107 zakres dat w Pandach<\/a><\/span><\/p>\n
 Do obliczenia sumy sprzeda\u017cy pogrupowanej wed\u0142ug kwarta\u0142\u00f3w mo\u017cna zastosowa\u0107 nast\u0119puj\u0105c\u0105 sk\u0142adni\u0119:<\/span><\/p>\n
 #convert date column to datetime and subtract one week<\/span>\ndf[' date<\/span> '] = pd. to_datetime<\/span> (df[' date<\/span> '])\n\n#calculate sum of sales, grouped by quarter\n<\/span>df. groupby<\/span> (df[' date<\/span> ']. dt<\/span> . to_period<\/span> (' Q<\/span> '))[' sales<\/span> ']. sum<\/span> ()\n\ndate\n2022Q1 24\n2022Q2 17\n2022Q3 16\n2022Q4 25\nFreq: Q-DEC, Name: sales, dtype: int64\n<\/strong><\/pre>\n
 Oto jak zinterpretowa\u0107 wynik:<\/span><\/p>\n