Merging on different column names in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to merge two DataFrames on columns with different names.

Pandas

merged_df = df1.merge(df2, left_on=[1], right_on='id')

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

A'key'

B'id'

C'value'

D'index'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'id' for left_on which is the column name in the second DataFrame.

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

We use left_on='key' because the first DataFrame's column to join on is named 'key'.

2fill in blank

medium

Complete the code to merge on columns with different names using suffixes to distinguish overlapping columns.

Pandas

merged_df = df1.merge(df2, left_on='key', right_on=[1], suffixes=('_left', '_right'))

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

A'key'

B'value'

C'id'

D'index'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'key' for right_on which is the column name in the first DataFrame.

Using 'value' which is unrelated.

We use right_on='id' because the second DataFrame's join column is named 'id'.

3fill in blank

hard

Fix the error in the merge code by choosing the correct parameter for merging on different column names.

Pandas

merged_df = df1.merge(df2, on=[1])

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

ANone

B'id'

C'key'

D['key', 'id']

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to merge on a list of different column names with 'on' parameter.

Using a single column name that exists only in one DataFrame.

When merging on columns with different names, on cannot be used. Instead, use left_on and right_on. So on=None disables this parameter.

4fill in blank

hard

Fill both blanks to create a merge that joins df1 and df2 on different column names and keeps all rows from df1.

Pandas

merged_df = df1.merge(df2, left_on=[1], right_on=[2], how='left')

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

A'key'

B'value'

C'id'

D'index'

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping the left_on and right_on values.

Using 'value' or 'index' which are not join columns.

Use left_on='key' for df1 and right_on='id' for df2 to merge on different column names. The how='left' keeps all rows from df1.

5fill in blank

hard

Fill all three blanks to merge df1 and df2 on different column names, keep all rows from df2, and add suffixes to overlapping columns.

Pandas

merged_df = df1.merge(df2, left_on=[1], right_on=[2], how=[3], suffixes=('_df1', '_df2'))

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

A'key'

B'id'

C'right'

D'outer'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'left' or 'outer' instead of 'right' for the how parameter.

Mixing up left_on and right_on values.

Use left_on='key' and right_on='id' to merge on different column names. The how='right' keeps all rows from df2. Suffixes distinguish overlapping columns.