replace() for value substitution in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of replace() on a pandas DataFrame column

What is the output of the following code snippet?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({'Fruit': ['apple', 'banana', 'cherry', 'banana', 'apple']})
df['Fruit'] = df['Fruit'].replace('banana', 'orange')
print(df)

A

     Fruit
0    apple
1   orange
2   cherry
3   orange
4    apple

B

     Fruit
0    apple
1   banana
2   cherry
3   banana
4    apple

C

     Fruit
0    apple
1   orange
2   cherry
3   banana
4    apple

D

     Fruit
0    apple
1   orange
2   orange
3   orange
4    apple

💡 Hint

replace() changes all exact matches of the old value with the new value in the column.

The replace() method substitutes all occurrences of 'banana' with 'orange' in the 'Fruit' column. Other values remain unchanged.

❓ data_output

intermediate

Number of replacements made by replace()

Given this DataFrame and code, how many values are replaced?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({'Color': ['red', 'blue', 'green', 'blue', 'yellow']})
replaced_df = df.replace({'blue': 'cyan'})
count_replaced = (df['Color'] != replaced_df['Color']).sum()
print(count_replaced)

A 3

B 1

C 2

D 0

💡 Hint

Count how many 'blue' values are in the original column.

There are two 'blue' entries in the 'Color' column, both replaced by 'cyan', so the count is 2.

🔧 Debug

advanced

Identify the error in replace() usage

What error does this code raise?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({'Animal': ['cat', 'dog', 'bird']})
df['Animal'] = df['Animal'].replace(['cat', 'dog'], 'fish', inplace=True)
print(df)

A AttributeError: 'NoneType' object has no attribute 'replace'

B TypeError: replace() got an unexpected keyword argument 'inplace'

C ValueError: Length of replacement does not match length of values

D No error, prints DataFrame with 'cat' and 'dog' replaced by 'fish'

💡 Hint

Check what replace() returns when inplace=True is used.

When inplace=True, replace() returns None. Assigning this None back to the column causes the column to become NoneType, leading to AttributeError on print.

🚀 Application

advanced

Replacing multiple values with a dictionary

Which option correctly replaces 'NY' with 'New York' and 'CA' with 'California' in the 'State' column?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({'State': ['NY', 'CA', 'TX', 'NY', 'FL']})

# Replace code here
print(df)

A df['State'] = df['State'].replace({'NY': 'California', 'CA': 'New York'})

B df['State'].replace(['NY', 'CA'], ['New York', 'California'])

C df['State'] = df['State'].replace(['NY', 'CA'], ['New York', 'California'])

D df['State'] = df['State'].replace({'NY': 'New York', 'CA': 'California'})

💡 Hint

Use a dictionary to map old values to new values correctly.

Option D correctly uses a dictionary to replace 'NY' and 'CA' with their full names and assigns the result back to the column.

🧠 Conceptual

expert

Understanding replace() behavior with regex

What is the output of this code?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({'Code': ['A1', 'B2', 'C3', 'A4']})
df['Code'] = df['Code'].replace(to_replace='A.', value='Z', regex=True)
print(df)

A

  Code
0   Z1
1   B2
2   C3
3   Z4

B

  Code
0    Z
1   B2
2   C3
3    Z

C

  Code
0   A1
1   B2
2   C3
3   A4

D

  Code
0   Z
1   Z
2   Z
3   Z

💡 Hint

The regex 'A.' matches any string starting with 'A' followed by any character.

The regex replaces any string starting with 'A' and one character with 'Z'. So 'A1' and 'A4' become 'Z'. Others remain unchanged.