Resampling time series data in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to resample the DataFrame to daily frequency and calculate the mean.

Pandas

daily_mean = df.resample([1]).mean()

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

A'D'

B'W'

C'M'

D'H'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'W' which resamples weekly instead of daily.

Using 'M' which resamples monthly instead of daily.

Using 'H' which resamples hourly instead of daily.

To resample time series data to daily frequency, use 'D' as the rule in the resample method.

2fill in blank

medium

Complete the code to resample the DataFrame to monthly frequency and calculate the sum.

Pandas

monthly_sum = df.resample([1]).sum()

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

A'D'

B'Y'

C'Q'

D'M'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'D' which resamples daily instead of monthly.

Using 'Q' which resamples quarterly instead of monthly.

Using 'Y' which resamples yearly instead of monthly.

To resample data monthly, use 'M' as the rule in the resample method.

3fill in blank

hard

Fix the error in the code to resample the DataFrame to hourly frequency and calculate the mean.

Pandas

hourly_mean = df.resample([1]).mean()

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

A'h'

B'hour'

C'H'

D'hr'

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase 'h' which is not recognized.

Using full words like 'hour' or abbreviations like 'hr' which are invalid.

The correct frequency string for hourly resampling in pandas is 'H' (uppercase).

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length only if the length is greater than 3.

Pandas

lengths = {word: [1] for word in words if [2]

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

Alen(word)

Blen(word) > 3

Cword

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word' instead of 'len(word)' for the value.

Using 'word > 3' which compares string to number and causes error.

The dictionary comprehension maps each word to its length using len(word), and filters words with length greater than 3 using len(word) > 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase keys to values only if the value is greater than 0.

Pandas

result = {{ [1]: [2] for k, v in data.items() if v [3] 0 }}

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

Ak.upper()

Bv

C>

Dk.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using k.lower() instead of k.upper() for keys.

Using v < 0 or other operators that do not filter positive values.

Using k or v incorrectly in the comprehension.

The dictionary comprehension uses k.upper() as keys, v as values, and filters items where v > 0.