Wide to long format conversion in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to convert the DataFrame from wide to long format using pandas.

Pandas

long_df = pd.melt(df, id_vars=['id'], value_vars=[1])

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

A['id']

B['age']

C['score3']

D['score1', 'score2']

Attempts:

3 left

💡 Hint

Common Mistakes

Including 'id' in value_vars causes incorrect reshaping.

Not specifying value_vars leads to all columns being unpivoted.

The value_vars parameter should list the columns to unpivot. Here, 'score1' and 'score2' are the columns to convert from wide to long format.

2fill in blank

medium

Complete the code to rename the variable and value columns after melting.

Pandas

long_df = pd.melt(df, id_vars=['id'], value_vars=['score1', 'score2'], var_name=[1], value_name='score')

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

A'test'

B'subject'

C'score'

D'variable'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the same name for var_name and value_name causes confusion.

Leaving var_name as default may be unclear in the output.

The var_name parameter sets the name of the new column that holds the original column names. Here, we rename it to 'test'.

3fill in blank

hard

Fix the error in the code to correctly convert wide to long format with multiple id_vars.

Pandas

long_df = pd.melt(df, id_vars=[1], value_vars=['score1', 'score2'])

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

A['age']

B['id', 'age']

C['id']

D['score1', 'score2']

Attempts:

3 left

💡 Hint

Common Mistakes

Only including one id_var when multiple are needed.

Putting value columns in id_vars causes errors.

When multiple columns identify each row, list them all in id_vars. Here, both 'id' and 'age' are identifiers.

4fill in blank

hard

Fill both blanks to create a long DataFrame with custom variable and value column names.

Pandas

long_df = pd.melt(df, id_vars=['id'], value_vars=['score1', 'score2'], var_name=[1], value_name=[2])

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

A'test'

B'score'

C'value'

D'variable'

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping var_name and value_name values.

Using default names that are unclear.

Set var_name to 'test' to name the variable column, and value_name to 'score' to name the values column.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each word to its length if length is greater than 3.

Pandas

lengths = { [1] : [2] for [3] in words if len([3]) > 3 }

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

Aword

Blen(word)

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names inconsistently.

Using length comparison incorrectly.

The dictionary comprehension uses word as the key, len(word) as the value, and iterates over word in words.