Pandas has many inbuilt methods that can be used to extract the month from a given date that are being generated randomly using the random function or by using Timestamp function or that are transformed to date format using the to_datetimefunction. Let’s see few examples for better understanding.
Example 1
import pandas as pd
dti = pd.date_range( '2020-07-01' , periods = 4 , freq = 'M' )
print (dti.month)
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Output:
Int64Index([7, 8, 9, 10], dtype='int64')
Example 2
import pandas as pd
import numpy as np
import datetime
date1 = pd.Series(pd.date_range( '2020-7-1 12:00:00' , periods = 5 ))
df = pd.DataFrame( dict (date_given = date1))
df[ 'month_of_date' ] = df[ 'date_given' ].dt.month
df |
Output:
Example 3
import pandas as pd
import datetime
import numpy as np
dates = [ '14 / 05 / 2017' , '2017' , '07 / 09 / 2017' ]
frame = pd.to_datetime(dates, dayfirst = True )
frame = pd.DataFrame([frame]).transpose()
frame[ 'date' ] = frame
frame[ 'month' ] = frame[ 'date' ].dt.month
frame.drop( 0 , axis = 1 , inplace = True )
frame |
Output: