Why reshaping data matters in Pandas - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to reshape the DataFrame from wide to long format using pandas.

Pandas

long_df = df.melt(id_vars=[1])

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

A'variable'

B'id_vars'

C'value'

D['Name', 'Date']

Attempts:

3 left

💡 Hint

Common Mistakes

Using a single string instead of a list for id_vars

Confusing id_vars with value_vars

Passing column names that should be reshaped instead of kept fixed

To reshape data from wide to long format, you specify the columns to keep fixed using id_vars. Here, ['Name', 'Date'] are the identifier columns.

2fill in blank

medium

Complete the code to pivot the DataFrame to wide format using pandas.

Pandas

wide_df = df.pivot(index=[1], columns='Month', values='Sales')

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

A'Month'

B'Store'

C'Sales'

D'Date'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the column for columns or values as the index

Confusing index and columns parameters

Passing a list instead of a single column name for index

The index parameter specifies the column to use as new row labels. Here, 'Store' is used as the index.

3fill in blank

hard

Fix the error in the code to correctly stack the DataFrame columns into a Series.

Pandas

stacked = df.[1]()

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

Astack

Bmelt

Cunstack

Dpivot

Attempts:

3 left

💡 Hint

Common Mistakes

Using unstack instead of stack

Using melt which reshapes differently

Using pivot which requires different parameters

The stack() method compresses columns into a single Series with a MultiIndex, which is the correct way to stack columns.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if length is greater than 3.

Pandas

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

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Alen(word)

Blen(word) > 3

Cword

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length

Using the wrong condition syntax

Confusing the order of key and value in the comprehension

The dictionary comprehension maps each word to its length using len(word). The condition keeps only words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their counts if count is greater than 0.

Pandas

result = [1]: [2] for [3] in data.items() if [2] > 0}

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

Ak.upper()

Bv

Ck, v

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong variable name in the loop

Not converting the key to uppercase

Using the value as the loop variable

The comprehension maps each key converted to uppercase (k.upper()) to its value v, iterating over keys k and values v from data.items(). It includes only items where the value is greater than 0.