Exporting results to multiple formats in Pandas - Mini Project: Build & Apply

Exporting results to multiple formats

📖 Scenario: You have collected sales data for a small store. You want to save this data in different file formats so you can share it easily with others who may use different software.

🎯 Goal: Create a small sales data table using pandas, then export it to CSV and Excel files.

📋 What You'll Learn

Create a pandas DataFrame with specific sales data

Set a filename variable for saving files

Export the DataFrame to a CSV file

Export the DataFrame to an Excel file

Print confirmation messages after each export

💡 Why This Matters

🌍 Real World

Saving data in multiple formats helps share information with different tools and users easily.

💼 Career

Data scientists often export data to CSV and Excel to communicate results with teams and clients.

1

Create the sales data DataFrame

Import pandas as pd and create a DataFrame called sales_data with these exact columns and values:
'Product': ['Apples', 'Bananas', 'Cherries'],
'Quantity': [10, 20, 15],
'Price': [0.5, 0.3, 0.8]

Pandas

# Import pandas and create the sales_data DataFrame
# Your code here

Need a hint?

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

2

Set the filename prefix

Create a variable called filename and set it to the string 'store_sales'.

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apples', 'Bananas', 'Cherries'],
    'Quantity': [10, 20, 15],
    'Price': [0.5, 0.3, 0.8]
})
# Create the filename variable
# Your code here

Need a hint?

Just assign the string 'store_sales' to filename.

3

Export the DataFrame to CSV and Excel

Use sales_data.to_csv() to save the data to a CSV file named filename + '.csv' without the index. Then use sales_data.to_excel() to save the data to an Excel file named filename + '.xlsx' without the index.

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apples', 'Bananas', 'Cherries'],
    'Quantity': [10, 20, 15],
    'Price': [0.5, 0.3, 0.8]
})
filename = 'store_sales'
# Export sales_data to CSV and Excel files
# Your code here

Need a hint?

Use the to_csv and to_excel methods with index=False.

4

Print confirmation messages

Print the exact messages:
"CSV file saved as store_sales.csv"
and
"Excel file saved as store_sales.xlsx".

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apples', 'Bananas', 'Cherries'],
    'Quantity': [10, 20, 15],
    'Price': [0.5, 0.3, 0.8]
})
filename = 'store_sales'
sales_data.to_csv(filename + '.csv', index=False)
sales_data.to_excel(filename + '.xlsx', index=False)
# Print confirmation messages
# Your code here

Need a hint?

Use two print() statements with the exact text.