Why transformation reshapes data for analysis in Data Analysis Python - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to reshape the data using pandas melt function.

Data Analysis Python

import pandas as pd

data = pd.DataFrame({
    'Name': ['Alice', 'Bob'],
    'Math': [90, 80],
    'Science': [85, 88]
})

reshaped = pd.melt(data, id_vars=['Name'], value_vars=[1])
print(reshaped)

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

A['Math', 'Science']

B['Name']

C['Math']

D['Science']

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'Name' in value_vars instead of id_vars

Not passing a list for value_vars

The value_vars parameter specifies which columns to reshape into rows. Here, we want to reshape the 'Math' and 'Science' columns.

2fill in blank

medium

Complete the code to pivot the reshaped data back to wide format.

Data Analysis Python

reshaped.pivot(index='Name', columns=[1], values='value')

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A'score'

B'Name'

C'variable'

D'value'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'Name' or 'value' as columns parameter

Confusing index and columns parameters

The pivot function uses the 'variable' column created by melt as the new columns.

3fill in blank

hard

Fix the error in the code to correctly filter rows where score is greater than 85.

Data Analysis Python

filtered = reshaped[reshaped['value'] [1] 85]
print(filtered)

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A>

B<

C==

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' or '<=' instead of '>'

Using '==' which checks for equality

To filter rows where the score is greater than 85, use the '>' operator.

4fill in blank

hard

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

Data Analysis Python

words = ['data', 'is', 'fun', 'science']
lengths = {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 word in the condition instead of its length

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

5fill in blank

hard

Fill all three blanks to create a dictionary from data items where the value is greater than 50, with keys uppercased.

Data Analysis Python

data = {'a': 40, 'b': 60, 'c': 70}
result = [1]: [2] for k, v in data.items() if v [3] 50}}

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Ak.upper()

Bv

C>

Dk

Attempts:

3 left

💡 Hint

Common Mistakes

Using original keys without uppercasing

Using wrong comparison operator

Swapping keys and values

The dictionary comprehension creates keys as uppercase versions of original keys using k.upper(), values as v, and filters items where v > 50.