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A library for data summary and analysis from various formats such as CSV, API, URL, etc.
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.
detect_outliers
and add_outliers_plot
to identify and visualize outliers with boxplots in the EDA sheet.add_text_heading
method to add custom text headings to each visualization.add_dataset_info
method to create a structured summary of the dataset.To use SheetBuddy, ensure you have the following dependencies:
pandas==1.3.3
requests==2.26.0
openpyxl==3.0.9
tqdm==4.62.3
matplotlib==3.4.3
seaborn==0.11.2
scipy==1.7.1
This library is designed specifically for numerical data analysis. Ensure your datasets are primarily numerical to make the most of SheetBuddy's capabilities.
Enjoy the new features and improvements! 🎉
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==3.1.0
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 v3.1.0 ! 🚀
FAQs
A library for data summary and analysis from various formats such as CSV, API, URL, etc.
We found that sheetbuddy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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