Outer join in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform a left outer join of DataFrame df1 with df2 on the 'id' column.

Data Analysis Python

result = df1.merge(df2, how=[1], on='id')

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

A'left'

B'inner'

C'right'

D'cross'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'inner' join which only keeps matching rows.

Using 'right' join which keeps all rows from df2 instead of df1.

The left join keeps all rows from the left DataFrame (df1) and adds matching rows from df2.

2fill in blank

medium

Complete the code to perform a full outer join of DataFrame df1 with df2 on the 'key' column.

Data Analysis Python

result = df1.merge(df2, how=[1], on='key')

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

A'right'

B'inner'

C'left'

D'outer'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'inner' join which excludes unmatched rows.

Using 'left' or 'right' which keep only one side's rows.

The outer join keeps all rows from both DataFrames, filling missing matches with NaN.

3fill in blank

hard

Fix the error in the code to perform a right outer join on 'user_id'.

Data Analysis Python

joined = df1.merge(df2, how=[1], on='user_id')

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

A'left'

B'right'

C'inner'

D'outer'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'left' join which keeps rows from the first DataFrame.

Using 'inner' join which excludes unmatched rows.

The right join keeps all rows from the right DataFrame (df2) and matches from df1.

4fill in blank

hard

Fill both blanks to create a left outer join on 'order_id' and include suffixes '_left' and '_right' for overlapping columns.

Data Analysis Python

result = df_orders.merge(df_payments, how=[1], on=[2], suffixes=('_left', '_right'))

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

A'left'

B'right'

C'order_id'

D'payment_id'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong join type like 'right'.

Joining on the wrong column like 'payment_id'.

Use how='left' to keep all orders and on='order_id' to join on the order ID column.

5fill in blank

hard

Fill all three blanks to perform a full outer join on 'emp_id' with suffixes '_emp' and '_dept'.

Data Analysis Python

final = employees.merge(departments, how=[1], on=[2], suffixes=[3])

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

A'outer'

B'emp_id'

C('_emp', '_dept')

D'emp_id', 'dept_id'

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong join type like 'inner'.

Joining on multiple columns incorrectly.

Not using suffixes or using wrong format.

Use how='outer' for full outer join, join on 'emp_id', and set suffixes to ('_emp', '_dept') to distinguish columns.