concat() for stacking DataFrames in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to stack two DataFrames vertically using concat.

Data Analysis Python

import pandas as pd

df1 = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df2 = pd.DataFrame({'A': [5, 6], 'B': [7, 8]})

result = pd.concat([df1, df2], axis=[1])
print(result)

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A-1

B0

C2

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=1 stacks DataFrames side by side (horizontally).

For vertical stacking, axis must be 0.

To stack DataFrames vertically (one on top of the other), use axis=0 in pd.concat().

2fill in blank

medium

Complete the code to reset the index after stacking DataFrames vertically.

Data Analysis Python

import pandas as pd

df1 = pd.DataFrame({'X': [10, 20]})
df2 = pd.DataFrame({'X': [30, 40]})

stacked = pd.concat([df1, df2], axis=0)
stacked_reset = stacked.[1](drop=True)
print(stacked_reset)

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Areset_index

Breindex

Cset_index

Dsort_index

Attempts:

3 left

💡 Hint

Common Mistakes

Using reindex does not reset the index numbering.

For resetting index, use reset_index.

After stacking, the index may be duplicated. Use reset_index(drop=True) to reset it to a clean sequence.

3fill in blank

hard

Fix the error in the code to stack DataFrames horizontally.

Data Analysis Python

import pandas as pd

df1 = pd.DataFrame({'A': [1, 2]})
df2 = pd.DataFrame({'B': [3, 4]})

result = pd.concat([df1, df2], axis=[1])
print(result)

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A-1

B2

C0

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=0 stacks vertically, not horizontally.

Axis must be 1 for horizontal stacking.

To stack DataFrames side by side (horizontally), use axis=1 in pd.concat().

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.

Data Analysis Python

words = ['apple', 'bat', 'car', 'door']
lengths = {word: [1] for word in words if [2]
print(lengths)

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as value instead of its length.

Incorrect condition like comparing word to 3.

The dictionary maps each word to its length using len(word). The condition keeps 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 lengths only if length is greater than 3.

Data Analysis Python

words = ['apple', 'bat', 'car', 'door']
result = { [1]: [2] for word in words if [3] }
print(result)

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Aword.upper()

Blen(word)

Clen(word) > 3

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using the original word as key instead of uppercase.

Not filtering words by length.

Using incorrect functions for keys or values.

The dictionary keys are uppercase words using word.upper(), values are lengths with len(word), and the condition filters words longer than 3 characters.