Writing to Excel with to_excel in Pandas - Mini Project: Build & Apply

Writing to Excel with to_excel

📖 Scenario: You work in a small business that tracks monthly sales data. You want to save this data into an Excel file so you can share it with your team easily.

🎯 Goal: Build a simple program that creates a sales data table and writes it to an Excel file named sales_data.xlsx.

📋 What You'll Learn

Create a pandas DataFrame with specific sales data

Set a variable for the Excel file name

Use the to_excel method to write the DataFrame to the Excel file

Print a confirmation message with the file name

💡 Why This Matters

🌍 Real World

Saving data to Excel files is common in business for sharing reports and summaries with colleagues who use spreadsheet software.

💼 Career

Data analysts and scientists often export data to Excel to communicate results to non-technical team members or managers.

1

Create the sales data DataFrame

Create a pandas DataFrame called sales_df with these exact columns and values:
'Month': ['January', 'February', 'March'],
'Sales': [2500, 3000, 2800]

Pandas

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

Hint

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

2

Set the Excel file name

Create a variable called excel_file and set it to the string 'sales_data.xlsx'.

Pandas

import pandas as pd
sales_df = pd.DataFrame({
    'Month': ['January', 'February', 'March'],
    'Sales': [2500, 3000, 2800]
})
# Set the excel_file variable to 'sales_data.xlsx'
# Your code here

Hint

Just assign the string 'sales_data.xlsx' to the variable excel_file.

3

Write the DataFrame to the Excel file

Use the to_excel method on sales_df to write the data to the file named in excel_file. Do not write the DataFrame index to the file (use index=False).

Pandas

import pandas as pd
sales_df = pd.DataFrame({
    'Month': ['January', 'February', 'March'],
    'Sales': [2500, 3000, 2800]
})
excel_file = 'sales_data.xlsx'
# Write sales_df to the Excel file without the index
# Your code here

Hint

Call sales_df.to_excel(excel_file, index=False) to save the file without the index column.

4

Print confirmation message

Print the message "Data saved to sales_data.xlsx" using the excel_file variable inside the message with an f-string.

Pandas

import pandas as pd
sales_df = pd.DataFrame({
    'Month': ['January', 'February', 'March'],
    'Sales': [2500, 3000, 2800]
})
excel_file = 'sales_data.xlsx'
sales_df.to_excel(excel_file, index=False)
# Print confirmation message with the excel_file name
# Your code here

Hint

Use print(f"Data saved to {excel_file}") to show the message.

Practice

1. What does the to_excel function in pandas do?

easy

A. Saves a DataFrame to an Excel file

B. Reads data from an Excel file into a DataFrame

C. Deletes an Excel file from disk

D. Converts Excel formulas into Python code

Solution

1. Step 1: Understand the purpose of to_excel

   The to_excel function is used to save or export a pandas DataFrame into an Excel file format.

2. Step 2: Differentiate from other Excel functions

   Functions like read_excel are for reading Excel files, not saving. Deleting files or converting formulas are unrelated.

3. Final Answer:

   Saves a DataFrame to an Excel file -> Option A

4. Quick Check:

   to_excel = Save DataFrame [OK]

Hint: Remember: 'to' means saving out, 'read' means loading in [OK]

Common Mistakes:

• Confusing to_excel with read_excel
• Thinking it deletes files
• Assuming it converts formulas

2. Which of the following is the correct syntax to save a DataFrame df to an Excel file named data.xlsx?

easy

A. df.to_excel('data.xlsx')

B. df.save_excel('data.xlsx')

C. to_excel(df, 'data.xlsx')

D. df.write_excel('data.xlsx')

Solution

1. Step 1: Recall the method call format

   In pandas, saving a DataFrame uses the method to_excel called on the DataFrame object.

2. Step 2: Check the syntax correctness

   The correct syntax is df.to_excel('filename.xlsx'). Other options use incorrect method names or function calls.

3. Final Answer:

   df.to_excel('data.xlsx') -> Option A

4. Quick Check:

   Method on DataFrame = to_excel [OK]

Hint: Use df.to_excel('filename.xlsx') to save [OK]

Common Mistakes:

• Using non-existent methods like save_excel
• Calling to_excel as a standalone function
• Using wrong method names like write_excel

3. Given the code below, what will be the content of the Excel file output.xlsx?

import pandas as pd
df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df.to_excel('output.xlsx', index=False, sheet_name='Sheet1')

medium

A. Excel file with columns A and B, including row numbers, default sheet name

B. Excel file with columns A and B, no row numbers, sheet named 'Sheet1'

C. Excel file with only column A saved

D. Excel file with columns A and B, but sheet name is 'Sheet2'

Solution

1. Step 1: Analyze parameters in to_excel

   The argument index=False means row numbers are not saved. sheet_name='Sheet1' sets the sheet name explicitly.

2. Step 2: Understand DataFrame content saved

   All columns 'A' and 'B' are saved because no column filtering is done.

3. Final Answer:

   Excel file with columns A and B, no row numbers, sheet named 'Sheet1' -> Option B

4. Quick Check:

   index=False removes row numbers [OK]

Hint: index=False means no row numbers saved [OK]

Common Mistakes:

• Assuming row numbers are saved by default
• Ignoring the sheet_name parameter
• Thinking only one column is saved

4. What is wrong with this code snippet?

import pandas as pd
df = pd.DataFrame({'X': [10, 20]})
df.to_excel('file.xlsx', sheet='Data')

medium

A. File extension should be '.xls' not '.xlsx'

B. DataFrame is empty and cannot be saved

C. Missing import for Excel writer

D. The parameter name 'sheet' is incorrect; it should be 'sheet_name'

Solution

1. Step 1: Check parameter names for to_excel

   The correct parameter to name the sheet is sheet_name, not sheet.

2. Step 2: Validate other parts of the code

   The DataFrame is valid and not empty. The file extension '.xlsx' is correct. No extra import is needed for basic usage.

3. Final Answer:

   The parameter name 'sheet' is incorrect; it should be 'sheet_name' -> Option D

4. Quick Check:

   Use sheet_name to name sheets [OK]

Hint: Use exact parameter names like sheet_name [OK]

Common Mistakes:

• Using wrong parameter names like 'sheet'
• Thinking file extension must be '.xls'
• Assuming extra imports are needed

5. You want to save two DataFrames df1 and df2 into the same Excel file report.xlsx, each on a different sheet named 'Sales' and 'Expenses'. Which code correctly does this?

hard

A. df1.to_excel('report.xlsx')
df2.to_excel('report.xlsx')

B. df1.to_excel('report.xlsx', sheet_name='Sales')
df2.to_excel('report.xlsx', sheet_name='Expenses')

C. with pd.ExcelWriter('report.xlsx') as writer:
df1.to_excel(writer, sheet_name='Sales')
df2.to_excel(writer, sheet_name='Expenses')

D. pd.to_excel([df1, df2], 'report.xlsx', sheets=['Sales', 'Expenses'])

Solution

1. Step 1: Understand saving multiple sheets

   To save multiple DataFrames in one Excel file with different sheets, use pd.ExcelWriter as a context manager.

2. Step 2: Check code correctness

   with pd.ExcelWriter('report.xlsx') as writer: df1.to_excel(writer, sheet_name='Sales') df2.to_excel(writer, sheet_name='Expenses') uses ExcelWriter and calls to_excel with the writer and sheet names correctly. Directly calling to_excel on the same filename multiple times overwrites the file, and pd.to_excel([df1, df2], ...) is not a valid function.

3. Final Answer:

   with pd.ExcelWriter('report.xlsx') as writer: df1.to_excel(writer, sheet_name='Sales') df2.to_excel(writer, sheet_name='Expenses') -> Option C

4. Quick Check:

   Use ExcelWriter for multiple sheets [OK]

Hint: Use ExcelWriter to save multiple sheets [OK]

Common Mistakes:

• Saving multiple DataFrames separately overwrites the file
• Trying to pass multiple DataFrames directly to to_excel
• Using non-existent functions like pd.to_excel with lists