Handling inconsistent values in Pandas - Mini Project: Build & Apply

Handling inconsistent values in pandas

📖 Scenario: You work in a company that collects customer feedback. The feedback data has inconsistent values for the rating column, such as different spellings and cases for the same rating.Cleaning this data will help the company analyze customer satisfaction accurately.

🎯 Goal: You will clean the rating column in a pandas DataFrame by replacing inconsistent values with consistent ones.

📋 What You'll Learn

Create a pandas DataFrame with given customer feedback data

Create a dictionary to map inconsistent ratings to consistent ratings

Use the replace() method with the mapping dictionary to clean the ratings

Print the cleaned DataFrame

💡 Why This Matters

🌍 Real World

Data collected from customers often has inconsistent text entries. Cleaning these values helps in accurate analysis and reporting.

💼 Career

Data scientists and analysts frequently clean and preprocess data to prepare it for analysis, making this skill essential in many data-related jobs.

1

Create the initial DataFrame

Create a pandas DataFrame called feedback with these exact columns and values:
customer_id: [101, 102, 103, 104, 105]
rating: ['Good', 'good', 'Excellent', 'excellent', 'Bad']

Pandas

import pandas as pd
# Create the DataFrame called feedback with the given data
# Your code here

Need a hint?

Use pd.DataFrame() with a dictionary of lists for columns.

2

Create a mapping dictionary for ratings

Create a dictionary called rating_map that maps these inconsistent ratings to consistent ones:
'good' to 'Good',
'excellent' to 'Excellent',
and keep 'Bad' as is (no mapping needed for 'Bad').

Pandas

import pandas as pd

feedback = pd.DataFrame({
    'customer_id': [101, 102, 103, 104, 105],
    'rating': ['Good', 'good', 'Excellent', 'excellent', 'Bad']
})
# Create the rating_map dictionary to fix inconsistent ratings
# Your code here

Need a hint?

Use a dictionary with keys as inconsistent values and values as correct ones.

3

Replace inconsistent ratings using the mapping

Use the replace() method on the rating column of feedback with the rating_map dictionary to fix inconsistent values. Assign the result back to the rating column.

Pandas

import pandas as pd

feedback = pd.DataFrame({
    'customer_id': [101, 102, 103, 104, 105],
    'rating': ['Good', 'good', 'Excellent', 'excellent', 'Bad']
})

rating_map = {
    'good': 'Good',
    'excellent': 'Excellent'
}
# Replace inconsistent ratings in feedback['rating'] using rating_map
# Your code here

Need a hint?

Use feedback['rating'].replace(rating_map) and assign it back to feedback['rating'].

4

Print the cleaned DataFrame

Print the feedback DataFrame to see the cleaned ratings.

Pandas

import pandas as pd

feedback = pd.DataFrame({
    'customer_id': [101, 102, 103, 104, 105],
    'rating': ['Good', 'good', 'Excellent', 'excellent', 'Bad']
})

rating_map = {
    'good': 'Good',
    'excellent': 'Excellent'
}

feedback['rating'] = feedback['rating'].replace(rating_map)
# Print the feedback DataFrame
# Your code here

Need a hint?

Use print(feedback) to display the DataFrame.