Dropping missing values with dropna() in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to drop rows with any missing values from the DataFrame.

Pandas

cleaned_df = df.[1]()

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Afillna

Bisnull

Cdropna

Dreplace

Attempts:

3 left

💡 Hint

Common Mistakes

Using fillna() instead of dropna()

Using isnull() which only checks for missing values

Using replace() which replaces values but does not drop rows

The dropna() method removes rows with missing values.

2fill in blank

medium

Complete the code to drop columns with any missing values from the DataFrame.

Pandas

cleaned_df = df.dropna(axis=[1])

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A-1

B2

C0

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=0 which drops rows instead of columns

Using axis=2 or -1 which are invalid for dropna()

Setting axis=1 drops columns with missing values.

3fill in blank

hard

Fix the error in the code to drop rows only if all values are missing.

Pandas

cleaned_df = df.dropna(how='[1]')

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Aany

Ball

Cnone

Dsome

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'any' which drops rows with any missing value

Using invalid strings like 'none' or 'some'

Using how='all' drops rows only if all values are missing.

4fill in blank

hard

Fill both blanks to drop rows with less than 3 non-missing values.

Pandas

cleaned_df = df.dropna(thresh=[1], axis=[2])

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A3

B2

C1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using thresh less than 3 which drops too few rows

Using axis=1 which drops columns instead of rows

The thresh=3 keeps rows with at least 3 non-missing values, and axis=0 means rows.

5fill in blank

hard

Fill all three blanks to drop columns with less than 2 non-missing values and reset the index.

Pandas

cleaned_df = df.dropna(thresh=[1], axis=[2]).[3](drop=True)

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A1

B2

Dreset_index

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=0 which drops rows instead of columns

Not resetting the index after dropping rows or columns

Using incorrect thresh value

Use thresh=2 to keep columns with at least 2 non-missing values, axis=1 to drop columns, and reset_index(drop=True) to reset the index without adding the old index as a column.