DataFrame as labeled two-dimensional table in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a DataFrame from a dictionary.

Pandas

import pandas as pd

data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}
df = pd.[1](data)
print(df)

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ASeries

BPanel

CDataFrame

Darray

Attempts:

3 left

💡 Hint

Common Mistakes

Using Series instead of DataFrame creates a one-dimensional structure.

Using Panel is deprecated and not suitable here.

The DataFrame constructor creates a labeled two-dimensional table from the dictionary.

2fill in blank

medium

Complete the code to select the 'Age' column from the DataFrame.

Pandas

import pandas as pd

data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}
df = pd.DataFrame(data)
age_column = df[1]
print(age_column)

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A[['Age']]

B['Age']

C.Age()

D.Age

Attempts:

3 left

💡 Hint

Common Mistakes

Using double brackets returns a DataFrame, not a Series.

Using dot notation with parentheses is invalid.

Using df['Age'] selects the 'Age' column as a Series.

3fill in blank

hard

Fix the error in the code to access the first row using .iloc.

Pandas

import pandas as pd

data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}
df = pd.DataFrame(data)
first_row = df.iloc[1]
print(first_row)

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A(0)

B0

C[[0]]

D[0]

Attempts:

3 left

💡 Hint

Common Mistakes

Using parentheses instead of square brackets causes a TypeError.

Using double brackets returns a DataFrame instead of a Series.

The iloc indexer requires square brackets to select rows by position. Use df.iloc[0] to get the first row.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths for words longer than 3 characters.

Pandas

words = ['apple', 'bat', 'carrot', 'dog']
lengths = {word: [1] for word in words if [2]
print(lengths)

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Alen(word)

Bword > 3

Clen(word) > 3

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself instead of its length.

Comparing the word string directly to a number.

The dictionary comprehension maps each word to its length using len(word). The condition len(word) > 3 filters words longer than 3 characters.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths for words longer than 3 characters.

Pandas

words = ['apple', 'bat', 'carrot', 'dog']
lengths = { [1]: [2] for word in words if [3] }
print(lengths)

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Aword.upper()

Blen(word)

Clen(word) > 3

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the original word instead of uppercase.

Not filtering words by length.

The dictionary comprehension uses word.upper() as keys, maps to len(word), and filters words with length greater than 3.