When a csv file is imported and a Data Frame is made, the Date time objects in the file are read as a string object rather a Date Time object and Hence it’s very tough to perform operations like Time difference on a string rather a Date Time object. Pandas
to_datetime() method helps to convert string Date time into Python Date time object.
pandas.to_datetime(arg, errors=’raise’, dayfirst=False, yearfirst=False, utc=None, box=True, format=None, exact=True, unit=None, infer_datetime_format=False, origin=’unix’, cache=False)
arg: An integer, string, float, list or dict object to convert in to Date time object.
dayfirst: Boolean value, places day first if True.
yearfirst: Boolean value, places year first if True.
utc: Boolean value, Returns time in UTC if True.
format: String input to tell position of day, month and year.
Return type: Date time object series.
For link of the CSV file used, click here.
Example #1: String to Date
In the following example, a csv file is read and the date column of Data frame is converted into Date Time object from a string object.
As shown in the image, the Data Type of Date column was object but after using to_datetime(), it got converted into a date time object.
Example #2: Exception while converting Time
Time object can also be converted with this method. But since in the Time column, a date isn’t specified and hence Pandas will put Today’s date automatically in that case.
As shown in the output, a date (2018-07-07) that is Today’s date is already added with the Date time object.
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