NaN and None in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a pandas DataFrame with a None value.

Pandas

import pandas as pd

data = {'A': [1, 2, [1], 4]}
df = pd.DataFrame(data)
print(df)

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

A0

BNaN

CNone

D''

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'NaN' as a string instead of the actual NaN value.

Using 0 which is a valid number, not missing data.

None is used to represent missing data in Python and works in pandas DataFrames.

2fill in blank

medium

Complete the code to import the correct function to create a NaN value.

Pandas

import pandas as pd
from numpy import [1]

data = {'B': [1, 2, [1], 4]}
df = pd.DataFrame(data)
print(df)

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

Anan

BNaN

CNaT

DNone

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'NaN' with uppercase N which is not the correct import.

Using None which is different from NaN.

numpy.nan is the standard way to represent NaN (Not a Number) in pandas.

3fill in blank

hard

Fix the error in the code to check for NaN values in the DataFrame.

Pandas

import pandas as pd
import numpy as np

df = pd.DataFrame({'C': [1, np.nan, 3]})
print(df.[1]())

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

Aisnulls

Bisna

Cisnan

Disnull

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'isnan' which is a numpy function, not a DataFrame method.

Using 'isnulls' which is not a valid method.

DataFrame has the method isna() to check for NaN values.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if length is greater than 3.

Pandas

words = ['apple', 'bat', 'car', 'door']
lengths = {word: [1] for word in words if [2]

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as value instead of its length.

Using the word in the condition instead of its length.

The dictionary comprehension uses len(word) as value and filters words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths only if length is greater than 3.

Pandas

words = ['apple', 'bat', 'car', 'door']
result = { [1]: [2] for word in words if [3] }

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

Aword.upper()

Blen(word)

Clen(word) > 3

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase instead of uppercase for keys.

Using the word itself instead of its length for values.

Incorrect condition for filtering.

The dictionary comprehension maps uppercase words to their lengths, filtering words longer than 3 characters.