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\u00c8 possibile utilizzare la seguente sintassi per calcolare la differenza tra due tempi in un DataFrame panda:<\/span><\/p>\n Questo particolare esempio calcola la differenza tra i tempi nelle colonne end_time<\/strong> e start_time<\/strong> di alcuni Pandas DataFrame.<\/span><\/p>\n L’esempio seguente mostra come utilizzare questa sintassi nella pratica.<\/span><\/p>\n Supponiamo di avere i seguenti panda DataFrame:<\/span><\/p>\n Possiamo utilizzare la seguente sintassi per calcolare la differenza temporale tra le colonne start_time<\/strong> e end_time<\/strong> in termini di ore, minuti e secondi:<\/span><\/span><\/p>\n Le nuove colonne contengono le differenze orarie tra le colonne start_time<\/strong> e end_time<\/strong> in unit\u00e0 diverse.<\/span><\/p>\n Consideriamo ad esempio la prima riga:<\/span><\/p>\n Tieni presente che in questo esempio le colonne start_time<\/strong> e end_time<\/strong> sono gi\u00e0 formattate come datetime.<\/span><\/p>\n Se le colonne dell’ora sono attualmente formattate come stringhe, puoi utilizzare pd.to_datetime<\/strong> per convertire ciascuna colonna nel formato datetime prima di calcolare la differenza tra le ore:<\/span><\/p>\n \u00c8 quindi possibile procedere al calcolo delle differenze orarie tra le colonne poich\u00e9 ora sono entrambe in un formato data\/ora che i panda possono riconoscere.<\/span><\/p>\n I seguenti tutorial spiegano come eseguire altre operazioni comuni nei panda:<\/span><\/p>\n Come creare un intervallo di date in Pandas<\/a> \u00c8 possibile utilizzare la seguente sintassi per calcolare la differenza tra due tempi in un DataFrame panda: #calculate time difference in hours df[‘ hours_diff ‘] = (df. end_time – df. start_time ) \/ pd. Timedelta (hours= 1 ) #calculate time difference in minutes df[‘ min_diff ‘] = (df. end_time – df. start_time ) \/ pd. […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"yoast_head":"\n #calculate time difference in hours\n<\/span>df[' hours_diff<\/span> '] = (df. end_time<\/span> - df. start_time<\/span> ) \/ pd. Timedelta<\/span> (hours= 1<\/span> )\n\n#calculate time difference in minutes\n<\/span>df[' min_diff<\/span> '] = (df. end_time<\/span> - df. start_time<\/span> ) \/ pd. Timedelta<\/span> (minutes= 1<\/span> )\n\n#calculate time difference in seconds\n<\/span>df[' sec_diff<\/span> '] = (df. end_time<\/span> - df. start_time<\/span> ) \/ pd. Timedelta<\/span> (seconds= 1<\/span> )\n<\/strong><\/pre>\n Esempio: calcolare la differenza tra due tempi nei panda<\/strong><\/span><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf=pd. DataFrame<\/span> ({' start_time<\/span> ':pd. date_range<\/span> (start=' 5\/25\/2020<\/span> ', periods= 6<\/span> , freq=' 15min<\/span> '),\n ' end_time<\/span> ':pd. date_range<\/span> (start=' 5\/26\/2020<\/span> ', periods= 6<\/span> , freq=' 30min<\/span> ')})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n start_time end_time\n0 2020-05-25 00:00:00 2020-05-26 00:00:00\n1 2020-05-25 00:15:00 2020-05-26 00:30:00\n2 2020-05-25 00:30:00 2020-05-26 01:00:00\n3 2020-05-25 00:45:00 2020-05-26 01:30:00\n4 2020-05-25 01:00:00 2020-05-26 02:00:00\n5 2020-05-25 01:15:00 2020-05-26 02:30:00\n<\/span><\/span><\/strong><\/pre>\n #calculate time difference in hours\n<\/span>df[' hours_diff<\/span> '] = (df. end_time<\/span> - df. start_time<\/span> ) \/ pd. Timedelta<\/span> (hours= 1<\/span> )\n\n#calculate time difference in minutes\n<\/span>df[' min_diff<\/span> '] = (df. end_time<\/span> - df. start_time<\/span> ) \/ pd. Timedelta<\/span> (minutes= 1<\/span> )\n\n#calculate time difference in seconds\n<\/span>df[' sec_diff<\/span> '] = (df. end_time<\/span> - df. start_time<\/span> ) \/ pd. Timedelta<\/span> (seconds= 1<\/span> )\n\n#view updated DataFrame<\/span>\nprint<\/span> (df)\n\n start_time end_time hours_diff min_diff sec_diff\n0 2020-05-25 00:00:00 2020-05-26 00:00:00 24.00 1440.0 86400.0\n1 2020-05-25 00:15:00 2020-05-26 00:30:00 24.25 1455.0 87300.0\n2 2020-05-25 00:30:00 2020-05-26 01:00:00 24.50 1470.0 88200.0\n3 2020-05-25 00:45:00 2020-05-26 01:30:00 24.75 1485.0 89100.0\n4 2020-05-25 01:00:00 2020-05-26 02:00:00 25.00 1500.0 90000.0\n5 2020-05-25 01:15:00 2020-05-26 02:30:00 25.25 1515.0 90900.0\n<\/strong><\/pre>\n\n
#convert columns to datetime format\n<\/span>df[[' start_time<\/span> ', ' end_time<\/span> ']] = df[[' start_time<\/span> ', ' end_time<\/span> ]]. apply<\/span> (pd. to_datetime<\/span> )\n<\/span><\/span><\/strong><\/pre>\n Risorse addizionali<\/strong><\/span><\/h2>\n
Come estrarre il mese dalla data in Pandas<\/a>
Come convertire il timestamp in data\/ora in Pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"