Pandas to_excel()

import pandas as pd

data = {
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35],
    'City': ['New York', 'San Francisco', 'Los Angeles']
}

df = pd.DataFrame(data)

# write df to an excel file
df.to_excel('output.xlsx')

to_excel() Syntax

The syntax of the to_excel() method in Pandas is:

df.to_excel(excel_writer, sheet_name='Sheet1', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, startrow=0, startcol=0, merge_cells=True, encoding=None, freeze_panes=None)

to_excel() Arguments

The to_excel() method has the following arguments:

• excel_writer: the file path or existing ExcelWriter object to target, or a file-like object
• sheet_name (optional): name of the sheet which will contain the DataFrame
• na_rep (optional): string representation of NaN to use
• float_format (optional): format string for floating point numbers
• columns (optional): columns to write
• header (optional): whether to write out the column names
• index (optional): whether to write out the row names (index)
• index_label (optional): column label for index column(s) if desired
• startrow (optional): upper left cell row to dump data frame
• startcol (optional): upper left cell column to dump data frame
• merge_cells (optional): write MultiIndex and hierarchical rows as merged cells
• encoding (optional): encoding for the output file
• freeze_panes (optional): top-left cell where to freeze the frame

to_excel() Return Value

The return value of to_excel() is None. The method writes the DataFrame to an Excel file without returning any value.

Example 1: Specifying Sheet Name and Starting Row

import pandas as pd

# create DataFrame
data = {'Name': ['Tom', 'Nick', 'John'],
        'Age': [20, 21, 19],
        'City': ['New York', 'London', 'Paris']}
df = pd.DataFrame(data)

# write DataFrame to Excel file with a specific sheet name and starting row
df.to_excel('output.xlsx', sheet_name='People', startrow=2)

output.xlsx

In the example above, we wrote the DataFrame to an Excel file with a specific sheet name People and started the data from the third row of the sheet.

Example 2: Writing Only Specific Columns to Excel

import pandas as pd

# create DataFrame
data = {'Name': ['Tom', 'Nick', 'John'],
        'Age': [20, 21, 19],
        'City': ['New York', 'London', 'Paris'],
        'Salary': [50000, 60000, 55000]}
df = pd.DataFrame(data)

# save only specific columns to Excel
df.to_excel('output.xlsx', columns=['Name', 'Age'])

output.xlsx

In the example above, we selectively exported only the Name and Age columns of our DataFrame to the output.xlsx Excel file.

Example 3: Using Index Label and Freeze Panes

import pandas as pd

# create DataFrame
data = {'Name': ['Tom', 'Nick', 'John'],
        'Age': [20, 21, 19]}
df = pd.DataFrame(data)

# write to Excel with index label and freeze the top row
df.to_excel('output.xlsx', index_label='ID', freeze_panes=(1,0))

output.xlsx

In the example above, we wrote the DataFrame to an Excel file and labeled the index column as ID. We also froze the top row by using the freeze_panes option.

Here,

• index_label ='ID': This argument adds a column label ID to the index column in the Excel file. If the DataFrame has an index, this will be the heading of the first column in the Excel spreadsheet.

• freeze_panes = (1,0): This argument freezes the top row of the Excel worksheet. In Excel, freezing panes keeps a set of rows or columns visible while scrolling through the rest of the worksheet.