<\/p>\n
Voc\u00ea pode usar a seguinte sintaxe para calcular a diferen\u00e7a entre dois tempos em um DataFrame do pandas:<\/span><\/p>\n Este exemplo espec\u00edfico calcula a diferen\u00e7a entre os hor\u00e1rios nas colunas end_time<\/strong> e start_time<\/strong> de alguns Pandas DataFrame.<\/span><\/p>\n O exemplo a seguir mostra como usar essa sintaxe na pr\u00e1tica.<\/span><\/p>\n Suponha que temos o seguinte DataFrame do pandas:<\/span><\/p>\n Podemos usar a seguinte sintaxe para calcular a diferen\u00e7a de tempo entre as colunas start_time<\/strong> e end_time<\/strong> em termos de horas, minutos e segundos:<\/span><\/span><\/p>\n As novas colunas cont\u00eam as diferen\u00e7as de tempo entre as colunas start_time<\/strong> e end_time<\/strong> em unidades diferentes.<\/span><\/p>\n Por exemplo, considere a primeira linha:<\/span><\/p>\n Observe que neste exemplo, as colunas start_time<\/strong> e end_time<\/strong> j\u00e1 est\u00e3o formatadas como datetime.<\/span><\/p>\n Se suas colunas de hora estiverem formatadas como strings, voc\u00ea poder\u00e1 usar pd.to_datetime<\/strong> para primeiro converter cada coluna para o formato de data e hora antes de calcular a diferen\u00e7a entre as horas:<\/span><\/p>\n Voc\u00ea pode ent\u00e3o calcular as diferen\u00e7as de tempo entre as colunas, j\u00e1 que agora ambas est\u00e3o em um formato de data e hora que os pandas podem reconhecer.<\/span><\/p>\n Os tutoriais a seguir explicam como realizar outras opera\u00e7\u00f5es comuns em pandas:<\/span><\/p>\n Como criar um intervalo de datas no Pandas<\/a> Voc\u00ea pode usar a seguinte sintaxe para calcular a diferen\u00e7a entre dois tempos em um DataFrame do pandas: #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 ) \/ […]<\/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":[],"class_list":["post-3752","post","type-post","status-publish","format-standard","hentry","category-guia"],"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 Exemplo: calculando a diferen\u00e7a entre dois tempos em pandas<\/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 Recursos adicionais<\/strong><\/span><\/h2>\n
Como extrair o m\u00eas da data no Pandas<\/a>
Como converter carimbo de data\/hora em data\/hora no Pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"