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Extending Excel with Python and R

You're reading from  Extending Excel with Python and R

Product type Book
Published in Apr 2024
Publisher Packt
ISBN-13 9781804610695
Pages 344 pages
Edition 1st Edition
Languages
Authors (2):
Steven Sanderson Steven Sanderson
Profile icon Steven Sanderson
David Kun David Kun
Profile icon David Kun
View More author details

Table of Contents (20) Chapters

Preface Part 1:The Basics – Reading and Writing Excel Files from R and Python
Chapter 1: Reading Excel Spreadsheets Chapter 2: Writing Excel Spreadsheets Chapter 3: Executing VBA Code from R and Python Chapter 4: Automating Further – Task Scheduling and Email Part 2: Making It Pretty – Formatting, Graphs, and More
Chapter 5: Formatting Your Excel Sheet Chapter 6: Inserting ggplot2/matplotlib Graphs Chapter 7: Pivot Tables and Summary Tables Part 3: EDA, Statistical Analysis, and Time Series Analysis
Chapter 8: Exploratory Data Analysis with R and Python Chapter 9: Statistical Analysis: Linear and Logistic Regression Chapter 10: Time Series Analysis: Statistics, Plots, and Forecasting Part 4: The Other Way Around – Calling R and Python from Excel
Chapter 11: Calling R/Python Locally from Excel Directly or via an API Part 5: Data Analysis and Visualization with R and Python for Excel Data – A Case Study
Chapter 12: Data Analysis and Visualization with R and Python in Excel – A Case Study Index Other Books You May Enjoy

Keeping it simple – exporting data to Excel with pandas

pandas is a popular data manipulation library in Python that provides powerful tools for data analysis. It also offers excellent functionality for exporting data to Excel. Using pandas, you can effortlessly transform your data into Excel sheets or workbooks.

pandas provides the DataFrame.to_excel() method, allowing you to export data to an Excel file with just a few lines of code. Here’s an example:

import pandas as pd
# Create a DataFrame with sample data
data = {
    'Name': ['John', 'Jane', 'Mike'],
    'Age': [25, 30, 35],
    'City': ['New York', 'London', 'Sydney']
}
df = pd.DataFrame(data)
# Export the DataFrame to an Excel file
df.to_excel('data.xlsx', index=False)

The code doesn’t return anything, but it does have a side effect –...

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