How to Convert CSV to Excel using Pandas in Python?

In this article, we will show you how to convert a CSV file (Comma Separated Values) to an Excel file using the pandas module in Python. This is useful when you need to transform data into Excel format for reporting or sharing purposes.

We'll use a sample CSV file called ExampleCsvFile.csv containing cricket player data to demonstrate the conversion process.

Sample Data

Our example CSV file contains the following player statistics ?

Method 1: Converting CSV to Excel Without Index

This method creates an Excel file without displaying row index numbers ?

import pandas as pd

# Create sample CSV data for demonstration
data = {
    'Player Name': ['Virat Kohli', 'Bhuvneshwar Kumar', 'MS Dhoni', 'Rashid Khan'],
    'Age': [33, 34, 39, 28],
    'Type': ['Batsman', 'Bowler', 'Wicket Keeper', 'Bowler'],
    'Country': ['India', 'India', 'India', 'Afghanistan'],
    'Team': ['RCB', 'SRH', 'CSK', 'GT'],
    'Runs': [6300, 333, 4500, 500],
    'Wickets': [20, 140, 0, 130]
}

# Create DataFrame and save as CSV
df = pd.DataFrame(data)
df.to_csv('sample_players.csv', index=False)

# Read the CSV file
csv_data = pd.read_csv('sample_players.csv')

# Convert to Excel without index
with pd.ExcelWriter('output_no_index.xlsx') as writer:
    csv_data.to_excel(writer, index=False)

print("CSV converted to Excel successfully (without index)")
print("First 3 rows of the data:")
print(csv_data.head(3))

CSV converted to Excel successfully (without index)
First 3 rows of the data:
    Player Name  Age          Type Country Team  Runs  Wickets
0   Virat Kohli   33       Batsman   India  RCB  6300       20
1  Bhuvneshwar Kumar   34        Bowler   India  SRH   333      140
2      MS Dhoni   39  Wicket Keeper   India  CSK  4500        0

Method 2: Converting CSV to Excel With Index

This method includes row index numbers in the Excel file ?

import pandas as pd

# Read CSV data
csv_data = pd.read_csv('sample_players.csv')

# Convert to Excel with index
with pd.ExcelWriter('output_with_index.xlsx') as writer:
    csv_data.to_excel(writer, index=True)

# Read the Excel file back to verify
excel_data = pd.read_excel('output_with_index.xlsx')
print("CSV converted to Excel successfully (with index)")
print("Excel file contents:")
print(excel_data)

CSV converted to Excel successfully (with index)
Excel file contents:
   Unnamed: 0    Player Name  Age          Type     Country Team  Runs  Wickets
0           0    Virat Kohli   33       Batsman       India  RCB  6300       20
1           1  Bhuvneshwar Kumar   34        Bowler       India  SRH   333      140
2           2       MS Dhoni   39  Wicket Keeper       India  CSK  4500        0
3           3    Rashid Khan   28        Bowler  Afghanistan   GT   500      130

Using to_excel() Directly

You can also convert CSV to Excel directly using the to_excel() method ?

import pandas as pd

# Read CSV and convert directly to Excel
df = pd.read_csv('sample_players.csv')
df.to_excel('direct_output.xlsx', index=False, sheet_name='Players')

print("Direct conversion completed")
print(f"DataFrame shape: {df.shape}")
print(f"Columns: {list(df.columns)}")

Direct conversion completed
DataFrame shape: (4, 7)
Columns: ['Player Name', 'Age', 'Type', 'Country', 'Team', 'Runs', 'Wickets']

Key Parameters

Conclusion

Converting CSV to Excel with pandas is straightforward using to_excel(). Use index=False to exclude row numbers or index=True to include them. The ExcelWriter class provides more control for complex operations.