Extracting day of week and hour in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of extracting day of week and hour?

Given the following pandas DataFrame with a datetime column, what will be the output after extracting the day of week and hour into new columns?

Pandas

import pandas as pd

df = pd.DataFrame({
    'timestamp': pd.to_datetime(['2024-06-01 08:30', '2024-06-02 15:45', '2024-06-03 23:00'])
})
df['day_of_week'] = df['timestamp'].dt.dayofweek
df['hour'] = df['timestamp'].dt.hour
print(df[['day_of_week', 'hour']])

A

   day_of_week  hour
0            0     8
1            1    15
2            2    23

B

   day_of_week  hour
0            6     8
1            0    15
2            1    23

C

   day_of_week  hour
0            4     8
1            5    15
2            6    23

D

   day_of_week  hour
0            5     8
1            6    15
2            0    23

💡 Hint

Remember that pandas uses Monday=0 for dayofweek and Sunday=6.

The dayofweek attribute returns an integer where Monday=0 and Sunday=6. June 1, 2024 is a Saturday (5), June 2 is Sunday (6), and June 3 is Monday (0). The hour attribute extracts the hour part of the timestamp.

❓ data_output

intermediate

How many unique days of week are in the DataFrame?

Using the DataFrame below, how many unique day_of_week values are present after extraction?

Pandas

import pandas as pd

df = pd.DataFrame({
    'timestamp': pd.to_datetime([
        '2024-06-01 08:30', '2024-06-02 15:45', '2024-06-03 23:00',
        '2024-06-08 10:00', '2024-06-09 12:00'
    ])
})
df['day_of_week'] = df['timestamp'].dt.dayofweek
unique_days = df['day_of_week'].nunique()
print(unique_days)

A 3

B 5

C 7

D 2

💡 Hint

Check the dates and their corresponding weekdays carefully.

The dates correspond to Saturday (5), Sunday (6), Monday (0), Saturday (5), and Sunday (6). So unique days are 0, 5, and 6, which is 3 unique days.

🔧 Debug

advanced

Identify the error in extracting hour from a string column

What error will this code raise when trying to extract the hour from a string column without conversion?

Pandas

import pandas as pd

df = pd.DataFrame({
    'timestamp': ['2024-06-01 08:30', '2024-06-02 15:45']
})
df['hour'] = df['timestamp'].dt.hour
print(df['hour'])

A TypeError: unsupported operand type(s) for -: 'str' and 'int'

B KeyError: 'hour'

C AttributeError: Can only use .dt accessor with datetimelike values

D ValueError: invalid literal for int() with base 10

💡 Hint

The .dt accessor only works on datetime columns, not strings.

The .dt accessor requires the column to be datetime type. Here, the column is string, so pandas raises an AttributeError.

🚀 Application

advanced

Filter DataFrame rows for weekend hours between 18 and 23

Given a DataFrame with a datetime column, which code snippet correctly filters rows where the day is Saturday or Sunday and the hour is between 18 and 23 inclusive?

Pandas

import pandas as pd

df = pd.DataFrame({
    'timestamp': pd.to_datetime([
        '2024-06-01 17:00', '2024-06-01 19:00', '2024-06-02 20:00', '2024-06-03 21:00'
    ])
})
df['day_of_week'] = df['timestamp'].dt.dayofweek
df['hour'] = df['timestamp'].dt.hour

A df[(df['day_of_week'] in [5,6]) & (df['hour'] >= 18) & (df['hour'] <= 23)]

B df[(df['day_of_week'].isin([5,6])) & (df['hour'] >= 18) & (df['hour'] <= 23)]

C df[(df['day_of_week'] == 5 & df['day_of_week'] == 6) & (df['hour'] >= 18) & (df['hour'] <= 23)]

D df[(df['day_of_week'] == 5 or df['day_of_week'] == 6) & (df['hour'] >= 18) & (df['hour'] <= 23)]

💡 Hint

Use pandas methods for filtering multiple values in a column.

Option B uses isin() correctly to check if day_of_week is Saturday (5) or Sunday (6). Options B and C use Python boolean operators incorrectly on pandas Series, and D uses in which is invalid for Series.

🧠 Conceptual

expert

Understanding dayofweek vs weekday_name in pandas

Which statement correctly explains the difference between dt.dayofweek and dt.weekday_name in pandas?

A <code>dt.dayofweek</code> returns an integer (Monday=0), while <code>dt.weekday_name</code> returns the day name as a string (e.g., 'Monday').

B <code>dt.dayofweek</code> returns the day name as a string, while <code>dt.weekday_name</code> returns an integer (Monday=0).

C <code>dt.dayofweek</code> and <code>dt.weekday_name</code> both return integers but with different starting days.

D <code>dt.dayofweek</code> returns the week number, while <code>dt.weekday_name</code> returns the day name.

💡 Hint

One returns numbers, the other returns names.

dt.dayofweek returns an integer from 0 (Monday) to 6 (Sunday). dt.weekday_name (deprecated in newer pandas versions) returns the day name as a string like 'Monday'.