PyAutoPlot Package Documentation

Package documentation for PyAutoPlot. PyAutoPlot is an open-source Python library designed to simplify dataset analysis by generating helpful detailed plots using matplotlib.

Changelog

• 1.1.0 (Latest):

  1. New Visualizations: Added Correlation Heatmaps and Violin Plots.

  2. Data Cleanup: New cleanup() method allows filling or dropping missing values with multiple strategies.

  3. Advanced Reporting:

     • export_json(): Saves all stats and metadata to JSON.

     • export_report(): Generates professional HTML (self-contained) or PDF reports.

  4. Improved Intelligence: Automatically detects and parses date strings into datetime objects.

  5. Optimizations: Better memory management and resource warnings for large datasets.

• 1.0.2 (Latest): Performance and other improvements, along with better error handling.

• 1.0.1: Added package dependencies to PyAutoPlot.

• 1.0.0: Initial release.

Installation

You can install PyAutoPlot using PyPi. Please make sure that you are using Python 3.6 or later before installing PyAutoPlot:

pip install pyautoplot

PyAutoPlot might not work well with certain datasets. Please let us know if you encounter any issues or have an edge use case.

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Example Usage

AutoPlot

from pyautoplot import AutoPlot

# Initialize with a CSV file
plotter = AutoPlot("path/to/dataset.csv")

# Automatically analyze and plot
plotter.auto_plot(output_file='test', theme="dark", color='orange', excludes=['detailed_analysis'])

Customization

from pyautoplot import AutoPlot

# Define your custom theme
custom_theme = {
    "axes.facecolor": "#ffffff",
    "axes.edgecolor": "#000000",
    "axes.labelcolor": "#000000",
    "figure.facecolor": "#ffffff",
    "grid.color": "#dddddd",
    "text.color": "#000000",
    "xtick.color": "#000000",
    "ytick.color": "#000000",
    "legend.frameon": True,
}

# Initialize with a CSV file
plotter = AutoPlot("path/to/dataset.csv")

# Automatically analyze and plot using the custom theme
plotter.auto_plot(output_file='test', theme=custom_theme, color='orange', excludes=['detailed_analysis'])