Get the day from a date in Pandas

Pandas provides several methods to extract the day name from dates. Whether you're working with single dates or multiple date strings, you can use dt.dayofweek, dt.day_name(), or dt.strftime() to get day information in different formats.

Using dt.dayofweek with Manual Mapping

The dt.dayofweek property returns numeric values (0-6) for days, which you can map to day names ?

import pandas as pd

# Create a date range
dates = pd.date_range(start='2022-01-01', end='2022-01-07')

# Create a DataFrame with the dates
df = pd.DataFrame({'date': dates})

# Add a column with the day of the week as numbers
df['day_number'] = df['date'].dt.dayofweek

# Map the day number to its name
day_mapping = {
    0: 'Monday',
    1: 'Tuesday', 
    2: 'Wednesday',
    3: 'Thursday',
    4: 'Friday',
    5: 'Saturday',
    6: 'Sunday'
}

df['day_name'] = df['day_number'].map(day_mapping)
print(df)

        date  day_number   day_name
0 2022-01-01           5   Saturday
1 2022-01-02           6     Sunday
2 2022-01-03           0     Monday
3 2022-01-04           1    Tuesday
4 2022-01-05           2  Wednesday
5 2022-01-06           3   Thursday
6 2022-01-07           4     Friday

Using pd.to_datetime() and dt.day_name()

Convert date strings to datetime objects and use dt.day_name() for direct day name extraction ?

import pandas as pd

# Create DataFrame with date string
df = pd.DataFrame({'date': ['2023-04-10']})

# Convert to datetime and extract day name
df['date'] = pd.to_datetime(df['date'])
df['day'] = df['date'].dt.day_name()

print(df)

        date     day
0 2023-04-10  Monday

Working with Multiple Dates

Process multiple date strings at once using vectorized operations ?

import pandas as pd

# Create DataFrame with multiple date strings
dates_df = pd.DataFrame({
    'date': ['2019-03-07', '2020-03-07', '2021-03-07', '2022-03-07', '2023-03-07']
})

# Convert to datetime and extract day names
dates_df['date'] = pd.to_datetime(dates_df['date'])
dates_df['day'] = dates_df['date'].dt.day_name()

print(dates_df)

        date       day
0 2019-03-07  Thursday
1 2020-03-07  Saturday
2 2021-03-07    Sunday
3 2022-03-07    Monday
4 2023-03-07   Tuesday

Using dt.strftime() for Abbreviated Names

Use strftime() to get abbreviated day names or custom date formats ?

import pandas as pd

# Create DataFrame with date string
df = pd.DataFrame({'date': ['2023-04-10']})

# Convert to datetime
df['date'] = pd.to_datetime(df['date'])

# Extract day information in different formats
df['day_number'] = df['date'].dt.dayofweek
df['day_abbreviated'] = df['date'].dt.strftime('%a')
df['day_full'] = df['date'].dt.day_name()

print(df)

        date  day_number day_abbreviated   day_full
0 2023-04-10           0             Mon     Monday

Comparison of Methods

Conclusion

Use dt.day_name() for readable full day names, dt.dayofweek for numerical operations, and dt.strftime() for custom formatting. All methods work efficiently with both single dates and multiple date columns.