<\/p>\n
Mo\u017cesz u\u017cy\u0107 poni\u017cszej funkcji, aby obliczy\u0107 r\u00f3\u017cnic\u0119 czasu w miesi\u0105cach mi\u0119dzy dwiema kolumnami ramki DataFrame pandy:<\/span><\/p>\n Poni\u017cszy przyk\u0142ad pokazuje, jak w praktyce wykorzysta\u0107 t\u0119 funkcj\u0119.<\/span><\/p>\n Za\u0142\u00f3\u017cmy, \u017ce mamy nast\u0119puj\u0105c\u0105 ramk\u0119 DataFrame pand:<\/span><\/p>\n Za\u0142\u00f3\u017cmy teraz, \u017ce chcemy obliczy\u0107 r\u00f3\u017cnic\u0119 czasu (w miesi\u0105cach) mi\u0119dzy kolumnami data_pocz\u0105tkowa<\/strong> i data_ko\u0144cowa<\/strong> .<\/span><\/p>\n W tym celu zdefiniujemy najpierw nast\u0119puj\u0105c\u0105 funkcj\u0119:<\/span><\/p>\n Nast\u0119pnie u\u017cyjemy tej funkcji do obliczenia r\u00f3\u017cnicy czasu w miesi\u0105cach mi\u0119dzy kolumnami data_pocz\u0105tkowa<\/strong> i data_ko\u0144cowa<\/strong> :<\/span><\/p>\n Kolumna R\u00f3\u017cnica_miesi\u0105ca<\/strong> wy\u015bwietla r\u00f3\u017cnic\u0119 czasu (w miesi\u0105cach) mi\u0119dzy kolumnami data_pocz\u0105tkowa<\/strong> i data_ko\u0144cowa<\/strong> .<\/span><\/p>\n Poni\u017csze samouczki wyja\u015bniaj\u0105, jak wykonywa\u0107 inne typowe operacje na pandach:<\/span><\/p>\n Jak przekonwertowa\u0107 kolumny na DateTime w Pandach<\/a> Mo\u017cesz u\u017cy\u0107 poni\u017cszej funkcji, aby obliczy\u0107 r\u00f3\u017cnic\u0119 czasu w miesi\u0105cach mi\u0119dzy dwiema kolumnami ramki DataFrame pandy: def month_diff(x, y): end = x. dt . to_period (’ M ’). view (dtype=’ int64 ’) start = y. dt . to_period (’ M ’). view (dtype=’ int64 ’) return end-start Poni\u017cszy przyk\u0142ad pokazuje, jak w praktyce wykorzysta\u0107 t\u0119 […]<\/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":[],"class_list":["post-2576","post","type-post","status-publish","format-standard","hentry","category-przewodnik"],"yoast_head":"\n def<\/span> month_diff(x, y):\n end = x. dt<\/span> . to_period<\/span> (' M<\/span> '). view<\/span> (dtype=' int64<\/span> ')\n start = y. dt<\/span> . to_period<\/span> (' M<\/span> '). view<\/span> (dtype=' int64<\/span> ')\n return<\/span> end-start\n<\/strong><\/pre>\n Przyk\u0142ad: Oblicz Timedelt\u0119 w miesi\u0105cach w Pandach<\/strong><\/span><\/h3>\n
import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' event<\/span> ': ['A', 'B', 'C'],\n ' start_date<\/span> ': ['20210101', '20210201', '20210401'],\n ' end_date<\/span> ': ['20210608', '20210209', '20210801'] })\n\n#convert start date and end date columns to datetime\n<\/span>df[' start_date<\/span> '] = pd. to_datetime<\/span> (df[' start_date<\/span> '])\ndf[' end_date<\/span> '] = pd. to_datetime<\/span> (df[' end_date<\/span> '])\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n event start_date end_date\n0 A 2021-01-01 2021-06-08\n1 B 2021-02-01 2021-02-09\n2 C 2021-04-01 2021-08-01\n<\/span><\/span><\/strong><\/pre>\n #define function to calculate time delta in months between two columns<\/span>\ndef<\/span> month_diff(x, y):\n end = x. dt<\/span> . to_period<\/span> (' M<\/span> '). view<\/span> (dtype=' int64<\/span> ')\n start = y. dt<\/span> . to_period<\/span> (' M<\/span> '). view<\/span> (dtype=' int64<\/span> ')\n return<\/span> end-start<\/strong><\/pre>\n #calculate month difference between start date and end date columns\n<\/span>df[' month_difference<\/span> '] = month_diff(df. end_date<\/span> , df. start_date<\/span> )\n\n#view updated DataFrame\n<\/span>df\n\n event start_date end_date month_difference\n0 A 2021-01-01 2021-06-08 5\n1 B 2021-02-01 2021-02-09 0\n2 C 2021-04-01 2021-08-01 4<\/span><\/span><\/strong><\/pre>\n Dodatkowe zasoby<\/strong><\/span><\/h3>\n
Jak przekonwertowa\u0107 DateTime na dat\u0119 w Pandach<\/a>
Jak wyodr\u0119bni\u0107 miesi\u0105c z daty w Pandach<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"