replace() for value substitution in Pandas - Mini Project: Build & Apply

Replace Values in a DataFrame Using replace()

📖 Scenario: You work in a small company that tracks employee departments and their status. Some department names are outdated and need to be updated to new names.

🎯 Goal: You will create a pandas DataFrame with employee data, set up a dictionary for replacing old department names with new ones, use the replace() method to update the DataFrame, and finally print the updated DataFrame.

📋 What You'll Learn

Create a pandas DataFrame with specific employee data

Create a dictionary mapping old department names to new names

Use the replace() method on the DataFrame to update department names

Print the updated DataFrame

💡 Why This Matters

🌍 Real World

Companies often need to update or clean data, such as renaming departments or correcting typos in employee records.

💼 Career

Data analysts and data scientists frequently use value substitution to prepare data for analysis and reporting.

1

Create the employee DataFrame

Import pandas as pd and create a DataFrame called df with these exact data: columns 'Employee', 'Department', and 'Status'. The rows should be: 'Alice', 'HR', 'Active', 'Bob', 'Sales', 'Inactive', 'Charlie', 'HR', 'Active', 'David', 'Marketing', 'Active', 'Eva', 'Sales', 'Inactive'.

Pandas

# Import pandas and create the DataFrame df with the given data
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary where keys are column names and values are lists of column data.

2

Create the replacement dictionary

Create a dictionary called replace_dict that maps the old department names to new ones: 'HR' to 'Human Resources' and 'Sales' to 'Sales & Marketing'.

Pandas

import pandas as pd

df = pd.DataFrame({
    'Employee': ['Alice', 'Bob', 'Charlie', 'David', 'Eva'],
    'Department': ['HR', 'Sales', 'HR', 'Marketing', 'Sales'],
    'Status': ['Active', 'Inactive', 'Active', 'Active', 'Inactive']
})

# Create the replace_dict dictionary with the specified mappings
# Your code here

Need a hint?

Use curly braces {} to create a dictionary with the exact key-value pairs.

3

Replace old department names with new ones

Use the replace() method on the 'Department' column of df with replace_dict to update the department names. Assign the result back to the 'Department' column of df.

Pandas

import pandas as pd

df = pd.DataFrame({
    'Employee': ['Alice', 'Bob', 'Charlie', 'David', 'Eva'],
    'Department': ['HR', 'Sales', 'HR', 'Marketing', 'Sales'],
    'Status': ['Active', 'Inactive', 'Active', 'Active', 'Inactive']
})

replace_dict = {'HR': 'Human Resources', 'Sales': 'Sales & Marketing'}

# Replace old department names in df['Department'] using replace_dict
# Your code here

Need a hint?

Use df['Department'].replace(replace_dict) and assign it back to df['Department'].

4

Print the updated DataFrame

Print the DataFrame df to see the updated department names.

Pandas

import pandas as pd

df = pd.DataFrame({
    'Employee': ['Alice', 'Bob', 'Charlie', 'David', 'Eva'],
    'Department': ['HR', 'Sales', 'HR', 'Marketing', 'Sales'],
    'Status': ['Active', 'Inactive', 'Active', 'Active', 'Inactive']
})

replace_dict = {'HR': 'Human Resources', 'Sales': 'Sales & Marketing'}

df['Department'] = df['Department'].replace(replace_dict)

# Print the updated DataFrame df
# Your code here

Need a hint?

Use print(df) to display the DataFrame.