Why combining DataFrames matters in Pandas - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to combine two DataFrames vertically using pandas.

Pandas

import pandas as pd

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

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Ajoin

Bmerge

Cappend

Dconcat

Attempts:

3 left

💡 Hint

Common Mistakes

Using merge instead of concat for vertical stacking.

Using join which is for columns.

Using append which is deprecated in recent pandas versions.

The concat function stacks DataFrames vertically by default, combining rows.

2fill in blank

medium

Complete the code to merge two DataFrames on column 'key'.

Pandas

import pandas as pd

df1 = pd.DataFrame({'key': ['K0', 'K1'], 'A': [1, 2]})
df2 = pd.DataFrame({'key': ['K0', 'K1'], 'B': [3, 4]})
merged = pd.merge(df1, df2, on=[1])
print(merged)

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A'key'

B'A'

C'B'

D'index'

Attempts:

3 left

💡 Hint

Common Mistakes

Using a column name that does not exist in both DataFrames.

Using 'index' which is not a column name here.

The on parameter specifies the column to join on, here it is 'key'.

3fill in blank

hard

Fix the error in the code to join two DataFrames on their indexes.

Pandas

import pandas as pd

df1 = pd.DataFrame({'A': [1, 2]}, index=['a', 'b'])
df2 = pd.DataFrame({'B': [3, 4]}, index=['a', 'b'])
joined = df1.[1](df2, how='inner')
print(joined)

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

Amerge

Bconcat

Cjoin

Dappend

Attempts:

3 left

💡 Hint

Common Mistakes

Using merge which requires specifying columns.

Using concat which stacks DataFrames.

Using append which adds rows.

The join method joins DataFrames on their indexes by default.

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

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

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Alen(word)

Blen(word) > 3

Cword

Dlen(word) < 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as value instead of its length.

Using wrong condition like less than 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.

Pandas

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 lowercase instead of uppercase for keys.

Using wrong condition or value.

The dictionary keys are uppercase words using word.upper(). Values are lengths with len(word). The condition filters words longer than 3.