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# PyAutoPlot Package Documentation

## 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:

```bash
pip install pyautoplot
```

{% hint style="warning" %}
**PyAutoPlot** might not work well with certain datasets. Please let us know if you encounter any issues or have an edge use case.
{% endhint %}

***

## Example Usage

### AutoPlot

```python
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

```python
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'])
```