Seamless Conversion of Pandas DataFrame to Excel Files

Creating a Sample DataFrame

First, let’s create a DataFrame with some sample data:

import pandas as pd
# Sample data for freshers.in Learning
data = {
    'Name': ['Sachin', 'Manju', 'Ram', 'Raju', 'David', 'Freshers_in', 'Wilson'],
    'Age': [32, 29, 35, 40, 28, 22, 33],
    'City': ['Mumbai', 'Bangalore', 'Chennai', 'Delhi', 'New York', 'Los Angeles', 'San Francisco']
}
df = pd.DataFrame(data)

Converting DataFrame to Excel

Using to_excel() Method

The to_excel() method in Pandas allows you to write DataFrame objects to Excel files. Here’s how you can use it:

Basic Conversion

# Converting DataFrame to Excel
df.to_excel('output.xlsx', index=False)

In this example, the DataFrame df is converted to an Excel file named output.xlsx. The index=False parameter is used to prevent writing row indices into the Excel file.

Customizing the Excel Output

You can customize the output by specifying sheet names, starting row/column, and even the Excel engine to be used.

Example with Customization:

# Writing to a specific sheet and excluding the header
df.to_excel('output.xlsx', sheet_name='Sample Data', startrow=1, startcol=1, header=False, engine='xlsxwriter')

This will create an Excel file with the DataFrame data starting from the second row and second column in a sheet named ‘Sample Data’.

Reading the Excel File (Verification)

To verify that the DataFrame has been correctly written to the Excel file, you can read it back:

# Reading the Excel file
read_df = pd.read_excel('output.xlsx')
print(read_df)

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