A lightweight EDA tool inspired by the curious nature of suricates. Built just for fun 🔬.
Project description
pysuricata
pysuricata is a lightweight Python library for exploratory data analysis (EDA) that supports multiple data formats—Pandas, Dask, and Polars DataFrames. It generates self-contained HTML reports featuring summary statistics, missing values, and correlation matrices with a clean, modern design.
Installation
Install pysuricata directly from PyPI:
pip install pysuricata
Quick Example
The following example demonstrates how to generate an EDA report using the Iris dataset with Pandas:
import pandas as pd
from pysuricata import generate_report
from IPython.display import HTML
# Load the Iris dataset directly using Pandas
iris_url = "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv"
iris_df = pd.read_csv(iris_url)
# Generate the HTML EDA report and save it to a file
html_report = generate_report(iris_df, output_file="iris_report.html")
# Display the report in a Jupyter Notebook
HTML(html_report)
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