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How to Convert Integer to Datetime in Pandas DataFrame?

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Let’s discuss how to convert an Integer to Datetime in it. Now to convert Integers to Datetime in Pandas DataFrame.

Syntax of  pd.to_datetime

df['DataFrame Column'] = pd.to_datetime(df['DataFrame Column'], format=specify your format)

Create the DataFrame to Convert Integer to Datetime in Pandas

Check data type for the ‘Dates’ column is Integer.

Python

# importing pandas package
import pandas as pd
 
# creating a dataframe
values = {'Dates':  [20190902, 20190913, 20190921],
          'Attendance': ['Attended', 'Not Attended', 'Attended']
          }
 
df = pd.DataFrame(values, columns=['Dates', 'Attendance'])
 
# display
print(df)
print(df.dtypes)

                    

Output:

 

Example 1:

Now to convert it into Datetime we use the previously mentioned syntax. Since in this example the date format is yyyymmdd, the date format can be represented as follows:

format= '%Y%m%d'

Python3

# importing pandas package
import pandas as pd
 
# creating the dataframe
values = {'Dates':  [20190902, 20190913, 20190921],
          'Attendance': ['Attended', 'Not Attended', 'Attended']
          }
 
df = pd.DataFrame(values, columns=['Dates', 'Attendance'])
 
# converting the integers to datetime format
df['Dates'] = pd.to_datetime(df['Dates'], format='%Y%m%d')
 
# display
print(df)
print(df.dtypes)

                    

Output:

 

Example 2: 

Now, suppose the Pandas DataFrame has a date in the format yymmdd. In this case, the date format would now contain ‘y’ in lowercase:

format='%y%m%d'

Python3

# importing pandas package
import pandas as pd
 
# creating dataframe
values = {'Dates':  [190902, 190913, 190921],
          'Attendance': ['Attended', 'Not Attended', 'Attended']
          }
 
df = pd.DataFrame(values, columns=['Dates', 'Attendance'])
 
# changing the integer dates to datetime format
df['Dates'] = pd.to_datetime(df['Dates'], format='%y%m%d')
 
# display
print(df)
print(df.dtypes)

                    

Output:

 

Example 3: 

Now, let’s suppose that your integers contain both date and time. In that case, the format that you should specify is:

format='%Y%m%d%H%M%S'

Python3

# importing pandas package
import pandas as pd
 
# creating dataframe
values = {'Dates': [20190902093000, 20190913093000, 20190921200000],
          'Attendance': ['Attended', 'Not Attended', 'Attended']
          }
 
df = pd.DataFrame(values, columns=['Dates', 'Attendance'])
 
# changing integer values to datetime format
df['Dates'] = pd.to_datetime(df['Dates'], format='%Y%m%d%H%M%S')
 
# display
print(df)
print(df.dtypes)

                    

Output:

 

Example 4: 

Consider this DataFrame with microseconds in our DateTime values. In this case, the format should be specified as:

format='%Y%m%d%H%M%S%F'

Python3

# importing pandas package
import pandas as pd
 
# creating dataframe
values = {'Dates':  [20190902093000912, 20190913093000444,
                     20190921200000009],
          'Attendance': ['Attended', 'Not Attended', 'Attended']
          }
 
df = pd.DataFrame(values, columns=['Dates', 'Attendance'])
 
# changing the integer dates to datetime format
df['Dates'] = pd.to_datetime(df['Dates'], format='%Y%m%d%H%M%S%F')
 
# display
print(df)
print(df.dtypes)

                    

Output:

 



Last Updated : 03 Oct, 2022
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