Pandas convert string to datetime

In this post, you will learn how to convert a string format to a datetime format using the Python Pandas. Pandas is a Python library that is basically used for data analysis.

In any programming language, datetime is a common datatype. Date and Time are often written in strings or any other format that we should convert into a single format. In data science time series projects, it is common practice to convert strings to datetime objects. Python pandas contains a feature for working with date and time. Here, we have mentioned how to convert a dataframe column of strings to a datatime format using Python Pandas inbuilt function pd.to_datetime().

Syntax of pd.to_datetime()

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 into a DateTime object.
• dayfirst: Boolean value, True if the input contains the day first
• yearfirst: Boolean value, True if the input contains the year first.
• utc: Boolean value, Returns the UTC Datetime Index if True.
• format: the position of the day, month, and year in the date.

Pandas convert date string to datetime

In the given Python program, we have converted a string to a date format.

import pandas as pd
# input in mm.dd.yyyy format
date = ['06.10.2020']
# output in yyyy-mm-dd format
print(pd.to_datetime(date))

Output of the above code-

DatetimeIndex(['2020-06-10'], dtype='datetime64[ns]', freq=None)

Pandas convert data and time string to datetime

In the given Python program, we have converted a date and time string to a datetime format.

import pandas as pd
# date (mm.dd.yyyy) and time (H:MM:SS)
date = ['11.02.2020 5:50:10 PM']
# output in yyyy-mm-dd HH:MM:SS
print(pd.to_datetime(date))

DatetimeIndex(['2020-11-02 17:50:10'], dtype='datetime64[ns]', freq=None)

Convert Strings to Datetime in Pandas DataFrame

In the given Python program, we have mentioned a step-by-step process to convert Pandas DataFrame column type from string to datetime format. Suppose we have the following data and we want to convert strings to datetime in Pandas DataFrame.

Create the dataframe

Here, we have created a DataFrame from the above data.

import pandas as pd

values = {'Name': ['Ankita', 'Somya', 'Tanya', 'Kanika'],
           'DOB':  ['20110413', '20020113', '20050713', '20100113']
           }

df = pd.DataFrame(values, columns = ['Name','DOB'])

print (df)
print (df.dtypes)

     Name   DOB
0  Ankita  20110413
1   Somya  20020113
2   Tanya  20050713
3  Kanika  20100113
Name     object
DOB    object
dtype: object

Convert the Strings to Datetime in the DataFrame

import pandas as pd

values = {'Name': ['Ankita', 'Somya', 'Tanya', 'Kanika'],
           'DOB':  ['20110413', '20020113', '20050713', '20100113']
           }

df = pd.DataFrame(values, columns = ['Name','DOB'])

df['DOB'] = pd.to_datetime(df['DOB'], format='%Y%m%d')

print (df)
print (df.dtypes)

     Name      DOB
0  Ankita 2011-04-13
1   Somya 2002-01-13
2   Tanya 2005-07-13
3  Kanika 2010-01-13
Name             object
DOB    datetime64[ns]
dtype: object

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