Why systematic cleaning matters in Pandas - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to load the CSV file into a DataFrame.

Pandas

import pandas as pd
df = pd.[1]('data.csv')

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

Aread_csv

Bread_excel

Cto_csv

DDataFrame

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'to_csv' which saves data instead of loading it.

Using 'read_excel' which is for Excel files.

Use pd.read_csv to load CSV files into a DataFrame.

2fill in blank

medium

Complete the code to remove rows with missing values.

Pandas

clean_df = df.[1]()

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Aisnull

Bfillna

Cdropna

Dreplace

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'fillna' which fills missing values instead of removing rows.

Using 'isnull' which checks for missing values but does not remove rows.

dropna() removes rows with missing values.

3fill in blank

hard

Fix the error in the code to convert a column to lowercase.

Pandas

df['Name'] = df['Name'].[1]()

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Alower

Btitle

Ccapitalize

Dupper

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'upper' which converts to uppercase.

Using 'capitalize' which only changes the first letter.

Use lower() to convert text to lowercase.

4fill in blank

hard

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

Pandas

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

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' causing wrong filtering.

Using 'word' instead of 'len(word)' as dictionary value.

The dictionary maps each word to its length if the word is longer than 3 letters.

5fill in blank

hard

Fill all three blanks to create a filtered dictionary with uppercase keys and values greater than 0.

Pandas

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

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Ak.upper()

Bv

C>

Dk.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'k.lower()' instead of 'k.upper()' for keys.

Using '<' instead of '>' in the condition.

Using 'k' instead of 'v' as dictionary values.

This dictionary comprehension creates keys as uppercase strings and includes only items with values greater than zero.