python-datetime

问题 I've got an array of dates that can contain multiple date ranges in it. dates = [ '2020-01-01', '2020-01-02', '2020-01-03', '2020-01-06', '2020-01-07', '2020-01-08' ] In this example, the list contains 2 separate consecutive date ranges (2020-01-01 to 2020-01-03 & 2020-01-06 to 2020-01-08) I'm attempting to figure out how I would loop through this list and find all the consecutive date ranges. One of the articles I'm looking at (How to detect if dates are consecutive in Python?) seems to have

问题 Currently we are working on an application which is trying to calculate the travel time of a route from a to b, using the 2.db.transport.rest API. Unfortunatly we are receiving timestamps with a timezone offset from that API, such as +01:00 . What we need is a timezone offset without the : , so +0100 . The following example gives an error on Linux, using Python 3.6.7: from datetime import datetime datetimestring = "2019-01-19T15:13:00.000+01:00" datetime.strptime(datetimestring, '%Y-%m-%dT%H:

问题 Currently we are working on an application which is trying to calculate the travel time of a route from a to b, using the 2.db.transport.rest API. Unfortunatly we are receiving timestamps with a timezone offset from that API, such as +01:00 . What we need is a timezone offset without the : , so +0100 . The following example gives an error on Linux, using Python 3.6.7: from datetime import datetime datetimestring = "2019-01-19T15:13:00.000+01:00" datetime.strptime(datetimestring, '%Y-%m-%dT%H:

问题 I have a dataframe like as shown below df = pd.DataFrame({'person_id': [11,11,11,21,21], 'offset' :['-131 days','29 days','142 days','20 days','-200 days'], 'date_1': ['05/29/2017', '01/21/1997', '7/27/1989','01/01/2013','12/31/2016'], 'dis_date': ['05/29/2017', '01/24/1999', '7/22/1999','01/01/2015','12/31/1991'], 'vis_date':['05/29/2018', '01/27/1994', '7/29/2011','01/01/2018','12/31/2014']}) df['date_1'] = pd.to_datetime(df['date_1']) df['dis_date'] = pd.to_datetime(df['dis_date']) df['vis

问题 I have a data frame like as shown below df1 = pd.DataFrame({'person_id': [11, 21, 31, 41, 51], 'date_1': ['12/30/1961', '05/29/1967', '02/03/1957', '7/27/1959', '01/13/1971'], 'date_2': ['07/23/2017','05/29/2017','02/03/2015',np.nan,np.nan]}) df1 = df1.melt('person_id', value_name='dates') I would like to get the number of days to the previous and next year . I am able to get the previous and next year using the below code df1['cur_year'] = pd.DatetimeIndex(df1['dates']).year df1['prev_year']

问题 This question already has answers here : How to print a date in a regular format? (22 answers) Closed last year . I have a list of Dates returning Mondays between two dates mondays = [datetime.date(2019, 2, 14), datetime.date(2019, 2, 21)] How do I format this list to %Y%m%d format? Expecting output list to be in the below format: ['20190214','20190221'] is there a way? 回答1: the following will work [date_obj.strftime('%Y%m%d') for date_obj in mondays] Output ['20190214', '20190221'] 来源： https

问题 This question already has answers here : Why can't I subclass datetime.date? (6 answers) Closed 5 years ago . I'm looking into creating a python datetime-subclass which provides a default timezone when created. For the sake of keeping this question simple, let's assume I always want to hard-code my datetimes to be in UTC. I can't figure out why the following works: import datetime, dateutil.tz def foo(*args, **kwargs): kwargs['tzinfo'] = dateutil.tz.tzutc() return datetime.datetime(*args, *

问题 I have a date column which after using pandas read_csv is represented as the object type. I'm trying to convert it to pandas datetime object but when using pd.to_datetime() it returns incorrect datetime object. for example, I have dates in this format 01-06-68 , where 01 is the day, 06 is the month and 68 is the year. Applying pandas to_datetime() to this string returns 2068-06-01 but should return 1968-06-01 , where 06 is a month and 01 is the day. I tried every possible solution using

问题 Trying to answer another question I stumbled over the following problem: dateparser.search.search_dates() returns a list of tuples, each tuple consisting of a text segment recognized as carrying date and/or time information, and the corresponding datetime (plus an optional language code, if requested). If the segment was of date type, only the date fields of the datetime are set. The others are taken from the current time, or from a base datetime that can be supplied via the settings

问题 I'm collecting some data from sensors and I get the timestamp from it like this: "time": { "seconds": 40, "year": 115, "month": 5, "hours": 7, "time": 1434549820776, "date": 17, "minutes": 3, "day": 3, "timezoneOffset": 420 }, I have a python script that processes the data coming from the sensors (incoming data is json format), I take the value of time and converts into readable time format. I used datetime.fromtimestamp(1434549820776/1000).strftime('%Y-%m-%d %H:%M:%S') and that returned