apply() on columns in Pandas - Mini Project: Build & Apply

Using apply() on DataFrame Columns with pandas

📖 Scenario: You work in a small store and have a table of products with their prices in dollars. You want to convert these prices to euros to see how much they cost in Europe.

🎯 Goal: You will create a pandas DataFrame with product names and prices in dollars. Then, you will use the apply() function on the price column to convert all prices to euros using a fixed exchange rate.

📋 What You'll Learn

Create a pandas DataFrame with product names and prices in dollars

Create a variable for the exchange rate from dollars to euros

Use apply() on the price column to convert prices to euros

Print the new column with prices in euros

💡 Why This Matters

🌍 Real World

Stores often need to convert prices between currencies to sell products internationally.

💼 Career

Data analysts use pandas apply() to quickly transform and clean data columns for reports and dashboards.

1

Create the products DataFrame

Create a pandas DataFrame called products with two columns: 'Product' and 'PriceUSD'. The products and prices should be exactly:
'Apple', 1.2
'Banana', 0.5
'Cherry', 2.5

Pandas

import pandas as pd
# Create the DataFrame 'products' with the exact data
# Your code here

Need a hint?

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

2

Set the exchange rate

Create a variable called usd_to_eur and set it to 0.85 to represent the exchange rate from US dollars to euros.

Pandas

import pandas as pd
products = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Cherry'],
    'PriceUSD': [1.2, 0.5, 2.5]
})
# Create the variable 'usd_to_eur' and set it to 0.85
# Your code here

Need a hint?

Just assign the number 0.85 to the variable usd_to_eur.

3

Convert prices to euros using apply()

Use the apply() function on the PriceUSD column of products to create a new column called PriceEUR. The conversion should multiply each price by usd_to_eur.

Pandas

import pandas as pd
products = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Cherry'],
    'PriceUSD': [1.2, 0.5, 2.5]
})
usd_to_eur = 0.85
# Use apply() on 'PriceUSD' to create 'PriceEUR' by multiplying by usd_to_eur
# Your code here

Need a hint?

Use products['PriceUSD'].apply(lambda x: x * usd_to_eur) to multiply each price by the exchange rate.

4

Print the new prices in euros

Print the PriceEUR column of the products DataFrame.

Pandas

import pandas as pd
products = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Cherry'],
    'PriceUSD': [1.2, 0.5, 2.5]
})
usd_to_eur = 0.85
products['PriceEUR'] = products['PriceUSD'].apply(lambda x: x * usd_to_eur)
# Print the 'PriceEUR' column
# Your code here

Need a hint?

Use print(products['PriceEUR']) to show the new prices.