Pandas dt.day attribute returns a NumPy array containing the day value of the DateTime in the underlying data of the given series object.
Example
import pandas as pd
sr = pd.Series(['2012-10-21 09:30', '2019-7-18 12:30', '2008-02-2 10:30',
'2010-4-22 09:25', '2019-11-8 02:22'])
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']
# set the index sr.index = idx
sr = pd.to_datetime(sr)
print(sr)
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Output
Syntax
Syntax: Series.dt.day
Parameter : None
Returns: NumPy array containing day values
How to Extract Day From DateTime Series
To extract the day value from the DateTime Series we use the dt.day attribute of the Pandas library in Python.
Let us understand it better with an example:
Example:
Use the Series.dt.day attribute to return the day 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)
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Output :
Now we will use the Series.dt.day attribute to return the day of the datetime in the underlying data of the given Series object.
# return the day result = sr.dt.day
# print the result print(result)
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Output :
As we can see in the output, the Series.dt.day attribute has successfully accessed and returned the day of the DateTime in the underlying data of the given series object.