How to display the days of the week for a particular year using Pandas?

Pandas is a powerful Python library for data manipulation and time-series analysis. When working with date data, you often need to find all occurrences of a specific weekday in a given year. Pandas provides the date_range() function to generate these dates efficiently.

Understanding date_range() Function

The pd.date_range() function creates a sequence of dates based on specified parameters. For weekly frequencies, it uses the format 'W-XXX' where XXX is the three-letter day abbreviation.

Syntax

range_of_dates = pd.date_range(start, periods, freq)
result = pd.Series(range_of_dates)

Parameters

• start ? The starting date of the range (e.g., '2023-01-01')

• periods ? Number of dates to generate (typically 52 for weekly occurrences)

• freq ? Frequency string like 'W-MON' for weekly Monday occurrences

Example 1: Finding All Mondays in 2023

This example generates all Monday dates for the year 2023 ?

import pandas as pd

day = "monday"
year = "2023"
range_of_dates = pd.date_range(year + '-01-01', periods=52, freq='W-' + day[:3].upper())
result = pd.Series(range_of_dates)
print(result)

0    2023-01-02
1    2023-01-09
2    2023-01-16
3    2023-01-23
4    2023-01-30
5    2023-02-06
6    2023-02-13
7    2023-02-20
8    2023-02-27
9    2023-03-06
10   2023-03-13
11   2023-03-20
12   2023-03-27
13   2023-04-03
14   2023-04-10
15   2023-04-17
16   2023-04-24
17   2023-05-01
18   2023-05-08
19   2023-05-15
20   2023-05-22
21   2023-05-29
22   2023-06-05
23   2023-06-12
24   2023-06-19
25   2023-06-26
26   2023-07-03
27   2023-07-10
28   2023-07-17
29   2023-07-24
30   2023-07-31
31   2023-08-07
32   2023-08-14
33   2023-08-21
34   2023-08-28
35   2023-09-04
36   2023-09-11
37   2023-09-18
38   2023-09-25
39   2023-10-02
40   2023-10-09
41   2023-10-16
42   2023-10-23
43   2023-10-30
44   2023-11-06
45   2023-11-13
46   2023-11-20
47   2023-11-27
48   2023-12-04
49   2023-12-11
50   2023-12-18
51   2023-12-25
dtype: datetime64[ns]

Example 2: Finding All Fridays in 2023

This example demonstrates how to find all Friday occurrences in 2023 ?

import pandas as pd

day = "FRIDAY"
year = "2023"
range_of_dates = pd.date_range(year + '-01-01', periods=52, freq='W-' + day[:3].upper())
result = pd.Series(range_of_dates)
print(result)

0    2023-01-06
1    2023-01-13
2    2023-01-20
3    2023-01-27
4    2023-02-03
5    2023-02-10
6    2023-02-17
7    2023-02-24
8    2023-03-03
9    2023-03-10
10   2023-03-17
11   2023-03-24
12   2023-03-31
13   2023-04-07
14   2023-04-14
15   2023-04-21
16   2023-04-28
17   2023-05-05
18   2023-05-12
19   2023-05-19
20   2023-05-26
21   2023-06-02
22   2023-06-09
23   2023-06-16
24   2023-06-23
25   2023-06-30
26   2023-07-07
27   2023-07-14
28   2023-07-21
29   2023-07-28
30   2023-08-04
31   2023-08-11
32   2023-08-18
33   2023-08-25
34   2023-09-01
35   2023-09-08
36   2023-09-15
37   2023-09-22
38   2023-09-29
39   2023-10-06
40   2023-10-13
41   2023-10-20
42   2023-10-27
43   2023-11-03
44   2023-11-10
45   2023-11-17
46   2023-11-24
47   2023-12-01
48   2023-12-08
49   2023-12-15
50   2023-12-22
51   2023-12-29
dtype: datetime64[ns]

How the Frequency Code Works

The frequency string 'W-XXX' tells Pandas to generate weekly dates ending on a specific weekday:

• W-MON ? Weekly frequency ending on Monday

• W-FRI ? Weekly frequency ending on Friday

• W-SUN ? Weekly frequency ending on Sunday

Practical Applications

This technique is useful for:

• Scheduling recurring events

• Analyzing weekly patterns in data

• Creating calendar-based reports

• Time series analysis with weekly granularity

Conclusion

Pandas date_range() function makes it easy to generate all occurrences of a specific weekday in any given year. This powerful feature is essential for time-series analysis and date-based data manipulation tasks.