Tooltips with Python’s Matplotlib, we’ll get a look at how to use event handlers and add tooltips to Matplotlib charts.
Allowing the user to hover the mouse or click a part of our visualization to get more context is excellent. And tooltips are a perfect way to save space in our chart.
For example, for most scatter plots labelling every point can get tricky. You can color-code them and use a legend, but even that can get messy when there’s too much data.
In this article, we’ll get a look at how to use event handlers and add tooltips to Matplotlib charts.
Data visualization is the graphical representation of data in a graph, chart or other visual formats. It shows relationships of the data with images.
So here is my first blog regarding the data visualization with matplotlib in python. In this article we will cover the basic of the visualization with matplotlib.
Learning the basics of Exploratory Data Analysis (EDA) using Python with Numpy, Matplotlib, and Pandas. EDA in Python uses data visualization to draw meaningful patterns and insights. EDA is an approach of analyzing datasets to summarize their main characteristics, often with visual methods.
Google Data Studio helps us understand the meaning behind data, enabling us to build beautiful visualizations and dashboards that transform data into stories.
I work on strategic questions and provide actionable, data-driven insights to inform product and engineering decisions. In this article, I’ll use Python to explore and visualize the classic titanic data.