Pandas Data Series: Get the day of month, year, week, week number

Last update on April 03 2025 13:08:24 (UTC/GMT +8 hours)

28. Extract Date Components

Write a Pandas program to get the day of month, day of year, week number and day of week from a given series of date strings.

Sample Solution :

Python Code :

import pandas as pd
from dateutil.parser import parse
date_series = pd.Series(['01 Jan 2015', '10-02-2016', '20180307', '2014/05/06', '2016-04-12', '2019-04-06T11:20'])
print("Original Series:")
print(date_series)
date_series = date_series.map(lambda x: parse(x))
print("Day of month:")
print(date_series.dt.day.tolist())
print("Day of year:")
print(date_series.dt.dayofyear.tolist())
print("Week number:")
print(date_series.dt.weekofyear.tolist())
print("Day of week:")
print(date_series.dt.weekday_name.tolist())

Sample Output:

Original Series:
0         01 Jan 2015
1          10-02-2016
2            20180307
3          2014/05/06
4          2016-04-12
5    2019-04-06T11:20
dtype: object
Day of month:
[1, 2, 7, 6, 12, 6]
Day of year:
[1, 276, 66, 126, 103, 96]
Week number:
[1, 39, 10, 19, 15, 14]
Day of week:
['Thursday', 'Sunday', 'Wednesday', 'Tuesday', 'Tuesday', 'Saturday']

Explanation:

date_series = pd.Series(['01 Jan 2015', '10-02-2016', '20180307', '2014/05/06', '2016-04-12', '2019-04-06T11:20']): This code creates a Pandas Series object 'date_series' containing six strings representing dates in different formats.

date_series = date_series.map(lambda x: parse(x)): This line applies the map() method to the Pandas Series object 'date_series' and a lambda function to parse each string into a Pandas Timestamp object using the dateutil.parser.parse() method.

The following code lines then apply various Pandas datetime-related methods to the Pandas Series object 'date_series'.

date_series.dt.day.tolist() returns a list of the day-of-the-month values of the Timestamp objects in 'date_series'.
date_series.dt.dayofyear.tolist() returns a list of the day-of-the-year values of the Timestamp objects in 'date_series'.
date_series.dt.weekofyear.tolist() returns a list of the week-of-the-year values of the Timestamp objects in 'date_series'.
date_series.dt.weekday_name.tolist() returns a list of the weekday names (i.e., Monday, Tuesday, etc.) of the Timestamp objects in 'date_series'.

For more Practice: Solve these Related Problems:

Write a Pandas program to extract the month and year from a Series of date strings and add them as new columns.
Write a Pandas program to extract the day, week, and quarter from a Series of date strings.
Write a Pandas program to convert a Series of date strings to datetime and then extract the day of the week in full text.
Write a Pandas program to extract date components (day, month, year) from a Series and then filter by specific months.

Python-Pandas Code Editor:

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