Resetting MultiIndex to columns in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to reset the MultiIndex of the DataFrame df to columns.

Pandas

df_reset = df.[1]()

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

Areset_index

Bset_index

Cdrop

Dsort_index

Attempts:

3 left

💡 Hint

Common Mistakes

Using set_index() instead of reset_index().

Trying to use drop() which is unrelated here.

The reset_index() method moves the MultiIndex levels back to columns in the DataFrame.

2fill in blank

medium

Complete the code to reset the MultiIndex and drop the old index from the DataFrame df.

Pandas

df_reset = df.reset_index([1]=True)

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

Adrop

Binplace

Clevel

Dcolumns

Attempts:

3 left

💡 Hint

Common Mistakes

Using inplace=True which modifies the DataFrame but does not drop the index.

Confusing level parameter with dropping the index.

Setting drop=True in reset_index() removes the old index instead of adding it as columns.

3fill in blank

hard

Fix the error in the code to reset only the first level of the MultiIndex in df.

Pandas

df_reset = df.reset_index(level=[1])

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A['level_0']

B1

C0

D'first'

Attempts:

3 left

💡 Hint

Common Mistakes

Using a string like 'first' which is not valid for the level parameter.

Passing a list instead of a single level.

The level parameter accepts an integer index of the level to reset. Using 0 resets the first level.

4fill in blank

hard

Fill both blanks to reset the MultiIndex and keep the changes in the original DataFrame df.

Pandas

df.[1](inplace=[2])

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

Areset_index

BTrue

CFalse

Dset_index

Attempts:

3 left

💡 Hint

Common Mistakes

Using set_index which does the opposite.

Setting inplace=False which returns a new DataFrame instead of modifying df.

Using reset_index with inplace=True resets the MultiIndex and updates df directly.

5fill in blank

hard

Fill all three blanks to reset the MultiIndex of df, drop the old index, and reset only the second level.

Pandas

df_reset = df.reset_index(level=[1], [2]=[3])

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

A1

Bdrop

CTrue

Dinplace

Attempts:

3 left

💡 Hint

Common Mistakes

Using inplace=True which modifies the original DataFrame instead of returning a new one.

Resetting the wrong level index.

Resetting level 1 with drop=True removes the old index from the result. inplace is not used here.