date parser. Next, create a DataFrame to capture the above data in Python. from dateutil import parser ds '' or any date sting of differing formats. If the date string is changed to DD-MM-YY, the format has to be set to d-m-Y. If you have a list of 5-6 elements you can directly make use of np.datetime64 data type by just changing the format (yyyy-mm-dd hh:mm:ss) of date in your list. To begin, collect the data that you’d like to convert to datetime.įor example, here is a simple dataset about 3 different dates (with a format of yyyymmdd), when a store might be opened or closed: Dates 10 Answers Sorted by: 273 datetime module could help you with that : (inputdatestring, inputformat).strftime (outputformat) For the specific example you could do : > from datetime import datetime > datetime.strptime ('Mon Feb 15 2010', 'a b d Y'). np.datetime64 works with format yyyy-mm-dd hh:mm:ss. The first parameter is the string and the second is the date time format specifier. Steps to Convert Strings to Datetime in Pandas DataFrame Step 1: Collect the Data to be Converted Using strptime (), date and time in string format can be converted to datetime type. Later, you’ll see several scenarios for different formats. Note that the strings must match the format specified. The syntax for the method used to convert string to datetime object is strptime(x,y) where: x is the the date entered in the string. The datetime module supplies classes for manipulating dates and times. Sample code: import dateparser t1 '1:33PM' t2 '12:00AM' dt1 dateparser.parse (t1) dt2 dateparser. You may use this template in order to convert strings to datetime in Pandas DataFrame: df = pd.to_datetime(df, format=specify your format) The most straightforward way is to use the dateparser.parse function, that wraps around most of the functionality in the module.
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