pyautoplot 1.0.1

PyAutoPlot is an open-source Python library designed to make dataset analysis much easier by generating helpful detailed plots using matplotlib based on your dataset.

PyAutoPlot

PyAutoPlot is an open-source Python library designed to make dataset analysis much easier by generating helpful detailed plots using matplotlib. It automatically generates appropriate plots based on the dataset you feed it.

Changes in version 1.0.1:

• Added package dependencies to PyAutoPlot: matplotlib>=3.0.0, pandas>=1.0.0, and numpy>=1.18.0.

Changes in version 1.0.0:

• AutoPlot class, along with auto_plot and plot functions. auto_plot automatically generates suitable plots based on values in your dataset.

[!IMPORTANT] The AutoPlot object needs to be initialized with a CSV dataset before any plots can be generated using either plot or auto_plot.

Installation

You can install PyAutoPlot using pip:

pip install pyautoplot

Supported Python Versions

PyAutoPlot supports the following Python versions:

• Python 3.6
• Python 3.7
• Python 3.8
• Python 3.9
• Python 3.10
• Python 3.11/Later (Preferred)

Please ensure that you have one of these Python versions installed before using PyAutoPlot. PyAutoPlot may not work as expected on lower versions of Python than the supported.

Features

• Automatic Plotting: PyAutoPlot automatically generates appropriate plots based on values present in your dataset. Currently, PyAutoPlot supports the following types of data: numeric, categorical, and time-series.
• Customization: Due to matplotlib's high customizability, you can create and use custom themes for PyAutoPlot, just pass in your theme as a dictionary of RCParams (See plot.rcParams.keys() for a list of valid parameters) or choose from our predefined themes. You can also pass in additional parameters to the function that matplotlib can recognize (e.g. color='#5d17eb').

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'])

[!NOTE] PyAutoPlot may not work well with certain datasets. If you find any issues please open an issue.

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'])

Contributing

Contributions are welcome! If you encounter any issues, have suggestions, or want to contribute to PyAutoPlot, please open an issue or submit a pull request on GitHub.

License

PyAutoPlot is released under the terms of the MIT License (Modified). Please see the LICENSE file for the full text.

Modified License Clause

The modified license clause grants users the permission to make derivative works based on the PyAutoPlot software. However, it requires any substantial changes to the software to be clearly distinguished from the original work and distributed under a different name.