---
title: "Distribution Charts"
url: https://docs.catalyst.zoho.com/en/quickml/help/data-visualization/distribution-charts/
description: "QuickML is a fully no-code ML pipeline builder service in the Catalyst development platform for creating machine-learning pipelines with end-to-end solutions."
last_updated: 2026-08-17T12:16:04Z
service: QuickML
type: general
---

# Distribution Charts

Distribution charts are graphical representations used to visualize the frequency or distribution of values within a dataset. They provide insights into the spread, variability, and patterns of data points, allowing for a better understanding of how values are distributed across different ranges. Distribution charts are particularly useful for identifying central tendencies, outliers, and the overall shape of data distributions.

1. ### Scatter Plot

    A ScatterPlot is a graphical representation used to display the relationship between two variables or attributes. It comprises individual data points placed on a Cartesian plane, where each point represents a combination of values for the two variables. Scatter plots are particularly useful for revealing patterns, correlations, or outliers within data.

    ![ScatterPlot](https://catalyst-docs-development.zohostratus.in/images/help/quickml/visualization-charts/scatter_plot_chart.webp)

    **Description:**

    - **Individual Data Points:** Each data point on the chart represents a specific combination of values for the two variables.

    - **Cartesian Plane:** The chart is based on a Cartesian coordinate system, with one variable plotted along the x-axis and the other along the y-axis.

    - **Variable Relationships:** Scatter plots help visualize how changes in one variable correspond to changes in the other, indicating potential correlations or patterns.

2. ### BoxPlot

    A BoxPlot, also known as a box-and-whisker plot, is a graphical representation used to visualize the distribution, spread, and outliers within a dataset. It provides a concise summary of key statistics, such as the median, quartiles, and potential outliers. The chart comprises a rectangular **“box”** and lines extending from it, known as **“whiskers.”**

    ![BoxPlot](https://catalyst-docs-development.zohostratus.in/images/help/quickml/visualization-charts/boxplot_chart.webp)

    **Description:**

    - **Box:** The central rectangle (box) spans the interquartile range (IQR), showing where the middle 50% of the data is concentrated. The box’s vertical line inside represents the median.

    - **Whiskers:** Lines (whiskers) extend from the edges of the box to the minimum and maximum values within a defined range, excluding outliers.

    - **Outliers:** Points outside the whiskers are marked as individual data points and can indicate potential outliers.

3. ### Histogram

    A histogram is a graphical representation used to visualize the distribution of numerical data. It divides the data into bins or intervals along the x-axis and displays the frequency or count of data points falling within each bin on the y-axis. Histograms help you understand the shape, central tendency, and spread of a dataset.

    ![Histogram](https://catalyst-docs-development.zohostratus.in/images/help/quickml/visualization-charts/histogram.webp)

    **Description:**

    - **Binning:** Data is divided into intervals (bins) along the x-axis, and the y-axis represents the frequency or count of data points within each bin.

    - **Bar Heights:** The height of each bar corresponds to the number of data points in the respective bin.

    - **Shape Interpretation:** Histograms provide insights into data distribution patterns, such as whether it’s skewed, symmetric, or bimodal.