Handling missing values in Series in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a pandas Series with missing values.

Data Analysis Python

import pandas as pd
s = pd.Series([1, 2, [1], 4])

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

ANone

B5

C0

D3

Attempts:

3 left

💡 Hint

Common Mistakes

Using a number like 0 or 5 instead of a missing value placeholder.

Leaving the blank empty.

Use None to represent missing values in a pandas Series.

2fill in blank

medium

Complete the code to check for missing values in the Series.

Data Analysis Python

missing = s.[1]()

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

Anotnull

Bdropna

Cisnull

Dfillna

Attempts:

3 left

💡 Hint

Common Mistakes

Using notnull() which returns True for non-missing values.

Using fillna() or dropna() which modify the Series.

The isnull() method returns a boolean Series indicating missing values.

3fill in blank

hard

Fix the error in the code to fill missing values with zero.

Data Analysis Python

s_filled = s.[1](0)

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

Adropna

Bfillna

Creplace

Disnull

Attempts:

3 left

💡 Hint

Common Mistakes

Using dropna() which removes missing values instead of filling them.

Using replace() without specifying the missing value.

The fillna() method replaces missing values with the specified value.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 3 characters.

Data Analysis Python

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

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

Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length.

Using the wrong comparison operator.

Use len(word) to get the length and filter words with length greater than 3 using >.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase keys and values greater than zero.

Data Analysis Python

result = [1]: [2] for k, v in data.items() if v [3] 0

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

Ak.upper()

Bv

C>

Dk

Attempts:

3 left

💡 Hint

Common Mistakes

Using original keys instead of uppercase keys.

Using wrong comparison operator or filtering condition.

Use k.upper() for uppercase keys, v for values, and filter values greater than zero with >.