SheetBuddy 2.1.1

A library for data summary and analysis from various formats such as CSV, API, URL, etc.

SheetBuddy

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.

Features

• 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)

New Features in SheetBuddy v2.1.1 🎉

We are excited to announce the release of SheetBuddy v2.1.1, which brings several new features and enhancements to improve your data analysis experience:

1. Expanded Column Descriptions 📝:

   • Added a comprehensive dictionary for column descriptions.

2. Enhanced Data Ingestion 🚀:

   • Improved methods for reading CSV, JSON, and API data.
   • Better error handling for smoother data ingestion.

3. Advanced Data Summarization 📊:

   • New get_column_info method for detailed column information.
   • Enhanced summary statistics for all data types.
   • Methods to calculate null values, percentages, standard deviation, unique values, and most frequent values.
   • get_basic_math method for basic calculations (mean, median, mode, range).

4. Improved Excel Formatting and Styling ✨:

   • Consistent formatting and styling for all Excel sheets.
   • New methods for conditional formatting and adding text headings.

5. Visualization Enhancements 📈:

   • New methods for histograms, correlation heatmaps, and bar charts in Excel sheets.

6. Comprehensive Dataset Info Sheet 🗂️:

   • Summary sheet with dataset name, format, rows, columns, description, and data link.

7. Robust Report Generation 📝:

   • Comprehensive EDA report with multiple detailed sheets.
   • Improved progress indicators and logging.

Installation

You can install SheetBuddy using pip:

pip install sheetbuddy

or

pip install sheetbuddy==2.1.1

Check for the lastest version

pip install sheetbuddy --upgrade

Usage

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)

How It Works:

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.

Contributing:

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

License:

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 v2.1.1! 🚀

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