SheetBuddy is a Python library for performing exploratory data analysis (EDA), data summary, and generating comprehensive reports in Excel format. It supports reading data from CSV files, JSON files, and APIs.

• Data Cleaning and Preprocessing
• Load data from CSV, JSON, and APIs
• Generate EDA reports in Excel format
• Summary statistics, null values, standard deviation, and more
• Column information including descriptions ('May not be available for all columns')
• Conditional formatting and styling for Excel sheets
• Summary Statistics
• Visualization (Correlation Matrix, Basic Mathematics)
• Data Export (Excel)

1. 📊 Correlation Matrix Sheet:

   • Automatically generate and save a correlation matrix for numerical columns in your Excel report. Easily spot relationships and dependencies between variables.

2. 🧮 Basic Mathematics Sheet:

   • Get essential statistics like mean, median, mode, and range for your numerical data. Now included in a separate sheet for quick insights into data distribution and central tendencies.

• This version of SheetBuddy requires Python 3.7 or higher.

Upgrade now to leverage these powerful new features and make your data analysis even more insightful! 📈✨

You can install SheetBuddy using pip:

pip install sheetbuddy

pip install sheetbuddy==2.0.0

pip install sheetbuddy --upgrade

Example 1: Generating an EDA and Datasummary Report from a CSV File.

from sheetbuddy import SheetBuddy 

file_path_or_url = 'https://people.sc.fsu.edu/~jburkardt/data/csv/airtravel.csv'
output_file_name = 'datasummary_report.xlsx'

sb = SheetBuddy(file_path_or_url)
sb.generate_eda_report(output_file_name)

Example 2: Generating an Datasummary & EDA Report from a Local JSON File.

from sheetbuddy import SheetBuddy

file_path = 'path/to/your/data.json'
output_file_name = 'enter_your_desired_name.xlsx'

sb = SheetBuddy(file_path)
sb.generate_eda_report(output_file_name)

Example 3: Generating an Datasummary & EDA Report from a Local CSV File.

from sheetbuddy import SheetBuddy

filename = 'your_local_path.csv'
outputfile = 'enter_your_desired_name.xlsx'

sb = SheetBuddy(filename)
sb.generate_eda_report(outputfile)

1.Data Loading: SheetBuddy loads data from the specified source (CSV, JSON, or API).

2.Data Analysis: It performs various data analyses, including summary statistics, null values analysis, and column descriptions.

3.Report Generation: The results are compiled into an Excel file with conditional formatting and styling for easy interpretation.

Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request on GitHub.

SheetBuddy is licensed under the MIT License. See the LICENSE file for more details.

We hope you enjoy these new features and improvements in SheetBuddy v2.0.0 ! 🚀

Back to Top ↑