Usage Guide

Basic Concepts

The core of exploralytics is the Visualizer class, which provides methods for creating various types of plots.

Initialization

from exploralytics import Visualizer

# Create a visualizer with default settings
viz = Visualizer()

# Or customize the appearance
viz = Visualizer(
    color="#2E75B6",      # Main color theme
    height=400,           # Default plot height
    width=800,           # Default plot width
    title_bold=True,     # Bold titles
    texts_font_style='Arial'  # Font family
)

Creating Plots

Histogram

# Single histogram
fig = viz.plot_histogram(
    df,
    x_col='values',
    title='Distribution',
    show_mean=True,
    show_median=True
)

Bar Plot

# Bar plot with highlighted values
fig = viz.plot_bar(
    df,
    x_col='category',
    y_col='values',
    highlight_top_n=(3, "green"),
    highlight_low_n=(2, "red")
)

Correlation Analysis

# Correlation with target variable
fig = viz.plot_correlation_with_target(
    df,
    target_column='target',
    title='Feature Correlations'
)

Displaying Plots

All plotting methods return a Plotly Figure object that can be:

# Displayed in a notebook
fig.show()

# Saved to a file
fig.write_html("plot.html")
fig.write_image("plot.png")