merge() for SQL-style joins in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

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

Data Analysis Python

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

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

A'id'

B'name'

C'age'

D'score'

Attempts:

3 left

💡 Hint

Common Mistakes

Using a column that does not exist in both DataFrames.

Forgetting to put quotes around the column name.

The on parameter specifies the column to join on. Here, 'id' is the common key.

2fill in blank

medium

Complete the code to perform a left join using merge().

Data Analysis Python

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

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

A'left'

B'inner'

C'right'

D'outer'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'inner' instead of 'left' when you want to keep all left rows.

Misspelling the join type string.

The how='left' parameter keeps all rows from the left DataFrame and matches rows from the right.

3fill in blank

hard

Fix the error in the merge code to join on columns 'id' and 'date'.

Data Analysis Python

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

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

A('id', 'date')

B'id, date'

C['id', 'date']

D'id date'

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a single string with commas instead of a list.

Using parentheses instead of square brackets.

To join on multiple columns, pass a list of column names to on.

4fill in blank

hard

Fill both blanks to merge df1 and df2 on 'user_id' with an outer join.

Data Analysis Python

merged_df = df1.merge(df2, on=[1], how=[2])

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

A'user_id'

B'left'

C'outer'

D'right'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'left' or 'right' instead of 'outer' for full join.

Forgetting quotes around column names.

Use on='user_id' to join on that column and how='outer' to keep all rows from both DataFrames.

5fill in blank

hard

Fill all three blanks to merge on 'key', keep only matching rows, and suffix overlapping columns with '_left' and '_right'.

Data Analysis Python

merged = df1.merge(df2, on=[1], how=[2], suffixes=([3], '_right'))

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

A'key'

B'inner'

C'_left'

D'_common'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'outer' or 'left' instead of 'inner' when only matching rows are needed.

Not providing suffixes or using incorrect suffix strings.

Use on='key' to join on the key column, how='inner' to keep only matching rows, and suffixes=('_left', '_right') to rename overlapping columns.