As we know it, data has evolved over the years in complexity. Many organizations and business owners have had a significant role in data collection and analysis.

According to Shift Disruptive Learning, our brain cannot take in much text data. This is because it processes 60,000 times more visualizations than texts.

One interesting fact is that 90% of the information we transmit in our brain is visual.

In our daily lives, we find ourselves entering data into our spreadsheets. Analyzing and visualizing data is usually the best part of the work.

Entering too many complex texts into our personal computers can be a tiresome task. That is why knowing data visualization is essential.

Visualizing data is an essential role in statistics because you allow others to recognize the crucial points in your data.

In this blog, we will learn in detail about visualizations in Python. The objective is to cover how we can make appealing charts in Python programming.

Let us briefly learn about data visualization in the next step.




In brief, data visualization is changing data into visual form. The objective is to make your data simple to read and interpret.

Data visualization is essential as it helps you depict various data forms into simple graphs.

Let us look at some other reasons why data visualization is essential:


You can use it to present information to others. 

Your objective is to make others understand your data. You can communicate to your audience the reasons behind particular logical reasoning.



Summarize large data sets

When you present your extensive data in the graphical form it makes it easy to summarize essential insights.

Visualizing data can help decision-makers make conclusions from big data sets.



Allows you to find solutions

One of the advantages of data visualization is that it helps you seek solutions. You can investigate information to find existing outliers and relationships in your data.

Let us examine one of the programming languages in our computers we can use for data visualization.




Python is one of the programming languages – you can use it to create websites and perform data visualization and analysis.

When you use Python, you will learn that you can use it for general purposes. You cannot use the programming language for any particular commands.

Why Use Python in Data Visualization?

When you use Python in visualizing your data, it will offer you numerous graphing libraries.

If you are interested in creating high-quality plots, Python will support you with customizations. You can make many types of charts with Python.

Python is one of those programming languages with many in-built modules. A large community also supports the program.

Visualizations in Python can seem complicated, but they are easy. It does not matter if you are a beginner, you can easily create visualizations in Python even if you are not a computer guru.

The question is, how do we create data visualization in Python?

As we have briefly explained, Python has numerous visualization tools. You can make impressive charts with Python using its libraries. Each python library has its unique visualization styles depending on the visualization form.




Let us start with the most popular:



Matplotlib is among the first data visualization tools in Python.

This data visualization tool in Python is used widely by most people. If you are lucky to be a data scientist, you may have used it once in your visualizations.

The remarkable aspect of Matplotlib is that you can use it with other libraries. Such libraries include Pandas and NumPy.

Matplotlib allows you to design charts in Python that are dynamic and interactive. When you use it to create charts in Python, you will realize that it is a flexible tool.

If you have used MATLAB before, it has similar features to Matplotlib.

The advantage of using Matplotlib is that the library has many aspects of color and size. This aspect helps you make remarkable charts with Python.

Let us see how we can create a Bar Chart with Python’s Matplotlib.


Creating a Bar Chart with Python

In this section, let us use a practical example of how we can create a chart in Python using Matplotlib.

A bar chart represents values in vertical or horizontal bars. When you use Matplotlib in making bar charts in Python, it becomes easy and efficient.

Source: Python Spot



This type of python data visualization library is also popular among many users. You can use it to make appealing visualizations in Python for studying data.

With Seaborn, you can make chart visualization in Python a crucial component of your data analysis.

Seaborn library contains visual diagrams such as scatter plots and histograms. You can use these charts for the visualization of data.

Seaborn also has its internal procedures for statistical analysis. This feature can aid you in making the charts of your choice.

One significant advantage of using Seaborn is that it allows straightforward data representation on plots.


Making a Scatter Plot Using Seaborn

You can use a scatter plot chart to plot points on a horizontal or vertical axis. It shows the relationship between two variables.


Source: PyData


Learn more on how to make a scatter plot chart in Python.

Last but not least, let us examine more visualizations in Python.





You can use this visual library to create charts in Python, such as error charts and histograms.

The visualization package allows you to use various data visualization components. You can use such elements in a precise visualization.

When you indicate on Ggplot what to include in your chart, the visual tool will do the rest.

The advantage of using Ggplot is that it gives you more time to analyze the data. Ggplot will do much of the designing than studying.

The plotting technique of Ggplot is usually straightforward. This is because it avoids data visualization complexities.

Learn how to make a pie chart using Ggplot in this section.




As we have seen, you can design data visualizations outside of spreadsheet tools – Python comes with many libraries that can help you visualize your charts.

As a business professional, you can use such knowledge to create appealing visuals in your data stories.

We have shown you how to do visualizations in Python without coding. Although we have not covered all of them, the ones above are widely used by most people.


Do not miss out on making visualization charts in Python – install the programming language on your PC and embark on this fantastic adventure.

Have a question for us or wish to share an idea?

We’re keen to hear more and happy to share our knowledge.