During the analysis of a dataset, oftentimes it happens that the dates are not represented in proper type and are rather present as simple strings which makes it difficult to process them and perform standard date-time operations on them.
pandas.to_datetime() Function helps in converting a date string to a python date object. So, it can be utilized for converting a series of date strings to a time series.
Let’s see some examples:
Example 1:
Python3
# import pandas library import pandas as pd # create a series of date strings dt_series = pd.Series(['28 July 2020', '16 January 2013', '29 February 2016 18:14']) # display the series initially print("Series of date strings:") print(dt_series) # display the series after being # converted to a time series print("\nSeries of date strings after" + " being converted to a timeseries:") print(pd.to_datetime(dt_series)) |
Output:
Example 2:
Python3
# import pandas library import pandas as pd # create a series of date strings dt_series = pd.Series(['2020/07/28', '2013/01/16', '2016/02/29 18:14']) # display the series initially print("Series of date strings:") print(dt_series) # display the series after being # converted to a time series print("\nSeries of date strings after " + "being converted to a timeseries:") print(pd.to_datetime(dt_series)) |
Output:
Example 3:
Python3
# import pandas library import pandas as pd # create a series of date strings dt_series = pd.Series(['2020-07-28', '2013-01-16', '2016-02-29 18:14']) # display the series initially print("Series of date strings:") print(dt_series) # display the series after # being converted to a time series print("\nSeries of date strings after " + "being converted to a timeseries:") print(pd.to_datetime(dt_series)) |
Output:
Example 4:
Python3
# import pandas library import pandas as pd # create a series of date strings dt_series = pd.Series(['28/07/2020', '01/16/2013', '29/02/2016 18:14']) # display the series initially print("Series of date strings:") print(dt_series) # display the series after being # converted to a time series print("\nSeries of date strings after " + "being converted to a timeseries:") print(pd.to_datetime(dt_series)) |
Output:
Example 5:
Python3
# import pandas library import pandas as pd # create a series of date strings dt_series = pd.Series(['20200728', '20130116', '20160229 181431']) # display the series initially print("Series of date strings:") print(dt_series) # display the series after # being converted to a time series print("\nSeries of date strings after " + "being converted to a timeseries:") print(pd.to_datetime(dt_series)) |
Output:
Example 6:
Python3
# import pandas library import pandas as pd # create a series of date strings dt_series = pd.Series(['28 July 2020', '2013-01-16', '20160229 18:14', '5/03/2019 2215', '20151204 09:23']) # display the series initially print("Series of date strings:") print(dt_series) # display the series after # being converted to a time series print("\nSeries of date strings after " + "being converted to a timeseries:") print(pd.to_datetime(dt_series)) |
Output:
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