concat() for stacking DataFrames in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to stack 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]})

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

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Amerge

Bjoin

Cconcat

Dappend

Attempts:

3 left

💡 Hint

Common Mistakes

Using merge instead of concat causes errors or unexpected joins.

Using append is deprecated for stacking multiple DataFrames.

The concat() function stacks DataFrames vertically by default when given a list of DataFrames.

2fill in blank

medium

Complete the code to stack two DataFrames horizontally (side by side) using pandas concat.

Pandas

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

B0

C2

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=0 stacks vertically, not horizontally.

Using axis=2 or -1 causes errors.

Setting axis=1 stacks DataFrames side by side (columns).

3fill in blank

hard

Fix the error in the code to stack DataFrames vertically and reset the index.

Pandas

import pandas as pd

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

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

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AFalse

BTrue

CNone

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using False keeps original indexes, causing duplicate index values.

Using None or 0 causes errors or unexpected behavior.

Setting ignore_index=True resets the index after stacking.

4fill in blank

hard

Fill both blanks to stack DataFrames vertically and add keys to identify each part.

Pandas

import pandas as pd

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

result = pd.concat([df1, df2], [1]=True, [2]=['first', 'second'])
print(result)

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Akeys

Bignore_index

Caxis

Dsort

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up 'keys' and 'ignore_index' parameters.

Forgetting to reset index causes confusing output.

Use ignore_index=True to reset index and keys to label each DataFrame part.

5fill in blank

hard

Fill all three blanks to stack DataFrames horizontally, join only common columns, and reset index.

Pandas

import pandas as pd

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

result = pd.concat([df1, df2], axis=[1], join="[2]", ignore_index=[3])
print(result)

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ATrue

B1

Cinner

Douter

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=0 stacks vertically, not horizontally.

Using join='outer' keeps all columns, not just common ones.

Not resetting index causes duplicate indexes.

Set axis=1 to stack side by side, join='inner' to keep only common columns, and ignore_index=True to reset index.