Extracting day of week and hour in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to extract the day of the week from the 'date' column.

Pandas

df['day_of_week'] = df['date'].dt.[1]

Drag options to blanks, or click blank then click option'

Asecond

Bdayofweek

Cminute

Dhour

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'hour' instead of 'dayofweek' will extract the hour, not the day.

Trying to call a method like 'dayofweek()' instead of using the attribute.

The dayofweek attribute extracts the day of the week as an integer (Monday=0, Sunday=6) from a datetime column.

2fill in blank

medium

Complete the code to extract the hour from the 'timestamp' column.

Pandas

df['hour'] = df['timestamp'].dt.[1]

Drag options to blanks, or click blank then click option'

Aday

Bmonth

Chour

Dyear

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'day' or 'month' will extract wrong parts of the datetime.

Trying to call hour() as a method instead of using the attribute.

The hour attribute extracts the hour (0-23) from a datetime column.

3fill in blank

hard

Complete the code to correctly extract the day of week from 'date_time'.

Pandas

df['day_of_week'] = df['date_time'].dt.[1]

Drag options to blanks, or click blank then click option'

Aminute

Bhour

Csecond

Ddayofweek

Attempts:

3 left

💡 Hint

Common Mistakes

Using parentheses after dayofweek causes an error.

Confusing attributes with methods.

The dayofweek is an attribute, not a method.

4fill in blank

hard

Fill both blanks to create a dictionary with day_of_week (0-6) as keys and record counts as values if count is greater than 3. Assume 'day_of_week' column exists.

Pandas

day_counts = {day: [1] for day in range(7) if [2]

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A(df['day_of_week'] == day).sum()

B(df['day_of_week'] == day).sum() > 3

Cday

Dday > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the day itself as the condition instead of its count.

Using parentheses incorrectly in the comprehension.

The dictionary comprehension maps each day to its count only if the count is greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase day names as keys, their record counts as values, only if count is greater than 4. Assume 'day_name' column exists.

Pandas

result = { [1]: [2] for day_name in df['day_name'].unique() if [3] }

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Aday_name.upper()

B(df['day_name'] == day_name).sum()

C(df['day_name'] == day_name).sum() > 4

Dday_name.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase instead of uppercase for keys.

Not filtering by count correctly.

The dictionary comprehension uses uppercase day names as keys, their counts as values, and filters those with more than 4 records.