A histogram contour plot is a two-dimensional representation of a histogram that looks like a contour plot. It is used to analyze anomalies and manage overplotting in a large dataset. If you don’t know how to visualize a histogram contour plot, this article is for you. In this article, I will take you through a tutorial on visualizing a histogram contour plot using Python.

## Histogram Contour Plot using Python

A histogram contour plot is also known as a density contour plot. It looks like a standard contour plot, but it represents data by computing the grouping set of data points into bins and applying an aggregation function. You can use a histogram contour plot instead of a scatter plot when the **scatter plot** results in overlapping data points.

To visualize a histogram contour graph using Python, I will first import the necessary Python libraries and a dataset:

import pandas as pd import plotly.graph_objects as go data = pd.read_csv("https://raw.githubusercontent.com/amankharwal/Website-data/master/tips.csv") print(data.head())

total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner 3 2 21.01 3.50 Male No Sun Dinner 3 3 23.68 3.31 Male No Sun Dinner 2 4 24.59 3.61 Female No Sun Dinner 4

Now here’s how to visualize a histogram contour plot using Python:

figure = go.Figure(go.Histogram2dcontour(x = data["total_bill"], y = data["tip"], colorscale = "Blues")) figure.show()

So this is how you can easily visualize a histogram contour graph or a density contour graph by using the plotly library in **Python**.

### Summary

A histogram contour plot is a two-dimensional representation of a histogram that looks like a contour plot. It is also known as a density contour plot. You can use a histogram contour plot instead of a scatter plot when the scatter plot results in overlapping data points. I hope you liked this article on how to visualize a histogram contour plot. Feel free to ask valuable questions in the comments section below.