Python | Pandas Series.dt.month

Опубликовано: 27 Марта, 2022

Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.month attribute return a numpy array containing the month of the datetime in the underlying data of the given series object.

Syntax: Series.dt.month
Parameter : None
Returns : numpy array

Example #1: Use Series.dt.month attribute to return the month of the datetime in the underlying data of the given Series object.

Выход :

Now we will use Series.dt.month attribute to return the month of the datetime in the underlying data of the given Series object.

# return the month
result = sr.dt.month
  
# print the result
print(result)

Output :

As we can see in the output, the Series.dt.month attribute has successfully accessed and returned the month of the datetime in the underlying data of the given series object.

Example #2 : Use Series.dt.month attribute to return the month of the datetime in the underlying data of the given Series object.

# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(pd.date_range("2012-12-12 12:12",
                       periods = 5, freq = "H"))
  
# Creating the index
idx = ["Day 1", "Day 2", "Day 3", "Day 4", "Day 5"]
  
# set the index
sr.index = idx
  
# Print the series
print(sr)

Выход :

Now we will use Series.dt.month attribute to return the month of the datetime in the underlying data of the given Series object.

# return the month
result = sr.dt.month
  
# print the result
print(result)

Output :

As we can see in the output, the Series.dt.month attribute has successfully accessed and returned the month of the datetime in the underlying data of the given series object.

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Python | Pandas Series.dt.month

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