Building cleaning pipelines with pipe() in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to apply the cleaning function using pipe().

Pandas

cleaned_df = df.[1](remove_nulls)

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

Amap

Bapply

Cfilter

Dpipe

Attempts:

3 left

💡 Hint

Common Mistakes

Using apply instead of pipe, which doesn't support chaining well.

Using map, which is for Series, not DataFrames.

The pipe() method applies a function to the DataFrame, allowing chaining of cleaning steps.

2fill in blank

medium

Complete the code to chain two cleaning functions using pipe().

Pandas

cleaned_df = df.pipe(remove_nulls).[1](strip_whitespace)

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

Apipe

Bmap

Capply

Dfilter

Attempts:

3 left

💡 Hint

Common Mistakes

Using apply or map breaks the pipeline chain.

Using filter is for filtering rows, not chaining functions.

Using pipe() again allows chaining the next cleaning function.

3fill in blank

hard

Fix the error in the pipeline by completing the code correctly.

Pandas

cleaned_df = df.pipe(remove_nulls).pipe([1])

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

Astrip_whitespace(df=df)

Bstrip_whitespace

Cstrip_whitespace(df)

Dstrip_whitespace()

Attempts:

3 left

💡 Hint

Common Mistakes

Calling the function inside pipe causes errors.

Passing the DataFrame as argument manually is unnecessary.

When using pipe(), pass the function name without calling it (no parentheses).

4fill in blank

hard

Fill both blanks to create a pipeline that removes nulls and converts column names to lowercase.

Pandas

cleaned_df = df.[1](remove_nulls).[2](lowercase_columns)

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

Apipe

Bapply

Cmap

Dfilter

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing pipe with apply or map breaks the chain.

Using filter is incorrect for applying functions.

Use pipe() for both steps to chain cleaning functions smoothly.

5fill in blank

hard

Fill all three blanks to build a cleaning pipeline that removes nulls and strips whitespace.

Pandas

cleaned_df = df.[1](remove_nulls).[2]([3])

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

Apipe

Bstrip_whitespace

Clowercase_columns

Dapply

Attempts:

3 left

💡 Hint

Common Mistakes

Calling functions inside pipe with parentheses.

Using apply instead of pipe for chaining.

Use pipe() to chain functions and pass the function names without parentheses.