Data is becoming the backbone of our current society. Companies can use data to predict their customer reactions, the success of their products and services, and the areas they need to work on. Data can also be used to understand many social and natural phenomena in the world such as social media trends, mass migration, global warming, etc. However, while data scientists can understand all these using various analytical procedures and statistical modeling on the data, it’s a very different thing to convey these findings to other people. That’s where data visualization is extremely important!

Data visualization allows data scientists to understand the layout and patterns in the data in visual form. It also allows them to demonstrate the findings from their data in simple terms to other people that are not experienced in data science. Therefore, data visualization is the language that is used to convey the data to regular people. There are many data visualization libraries across programming languages that can be used for this task. This article deals with the most popular data visualization libraries in Python, R, and Javascript. You can use these libraries to create basic charts like bar charts, pie charts, histograms, scatterplots, sparklines, dendrograms, contour plots, choropleth maps, etc. If you want to be more creative, you can even add animations to your charts and create data stories. So what are you waiting for? Check out these libraries and begin your data visualization journey by creating your first chart!

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