Understanding Overlaying Histograms using Seaborn
Plotting multiple Histograms On Same Plot is built by splitting the data into periods, or “bins,” and then showing the number or density of readings within each bin as bars. Unlike different histograms, where each group has its own plot, multiple histograms show multiple distributions within the same plot, making it easier to compare them clearly.
Why Use Seaborn for Overlapping Histograms?
Seaborn offers a streamlined approach to creating aesthetically pleasing and informative histograms with simplified lines of code:
- Simplified Syntax: Concise code for generating complex plots.
- Statistical Integration: Built-in functions for density estimation (KDE).
- Customization: Extensive options for tailoring the appearance.
Plot Multiple Histograms On Same Plot With Seaborn
Histograms are a powerful tool for visualizing the distribution of data in a dataset. When working with multiple datasets or variables, it can be insightful to compare their distributions side by side. Seaborn, a python data visualization package offers powerful tools for making visually appealing maps and efficient way to plot multiple histograms on the same plot.
In this article, we will explore and implement multiple histograms on same plot.
Table of Content
- Understanding Overlaying Histograms using Seaborn
- Comparing Two Distributions : A Practical Example
- Overlaying Histograms with Kernel Density Estimation (KDE)
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