Python – Data visualization tutorial Last Updated : 16 May, 2023 Improve Improve Like Article Like Save Share Report Data Visualization is a technique of presenting data graphically or in a pictorial format which helps to understand large quantities of data very easily. This allows decision-makers to make better decisions and also allows identifying new trends, patterns in a more efficient way. In this tutorial, we will look at different modules provided by Python for data visualization and will learn about these modules from basic to advance with the help of a huge dataset containing information from installation to different types of charts to exercises, applications, and projects. Matplotlib Matplotlib is an easy-to-use Python library for data visualization which is built on top of NumPy arrays. It is a low-level module and provides a lot of flexibility but at the cost of writing more code. Introduction Environment Setup for Matplotlib Introduction to Matplotlib Python Matplotlib – An Overview Using Matplotlib with Jupyter Notebook Pyplot in Matplotlib Matplotlib – Axes Class Multiple Plots Multiplots in Python using Matplotlib How to create multiple subplots in Matplotlib in Python? How to Add Title to Subplots in Matplotlib? How to Set a Single Main Title for All the Subplots in Matplotlib? How to Create Different Subplot Sizes in Matplotlib? How to set the spacing between subplots in Matplotlib in Python? Line Graph Line chart in Matplotlib Line plot styles in Matplotlib Plot Multiple lines in Matplotlib Plot line graph from NumPy array Bar Chart Bar Plot in Matplotlib Create a stacked bar plot in Matplotlib Stacked Percentage Bar Plot In MatPlotLib Plotting back-to-back bar charts Matplotlib Histogram Plotting Histogram in Python using Matplotlib Create a cumulative histogram in Matplotlib How to plot two histograms together in Matplotlib? Overlapping Histograms with Matplotlib in Python Bin Size in Matplotlib Histogram Compute the histogram of a set of data using NumPy in Python Plot 2-D Histogram in Python using Matplotlib Scatter Plot matplotlib.pyplot.scatter() in Python How to add a legend to a scatter plot in Matplotlib ? How to Connect Scatterplot Points With Line in Matplotlib? How to create a Scatter Plot with several colors in Matplotlib? How to increase the size of scatter points in Matplotlib ? Pie Chart Plot a pie chart in Python using Matplotlib How to set border for wedges in Matplotlib pie chart? Radially displace pie chart wedge in Matplotlib 3D Plots Three-dimensional Plotting in Python using Matplotlib 3D Scatter Plotting in Python using Matplotlib 3D Surface plotting in Python using Matplotlib 3D Wireframe plotting in Python using Matplotlib 3D Contour Plotting in Python using Matplotlib Tri-Surface Plot in Python using Matplotlib Surface plots and Contour plots in Python How to change angle of 3D plot in Python? Working with Images Working with Images in Python using Matplotlib Working with PNG Images using Matplotlib Customizing Plots Style Plots using Matplotlib Change plot size in Matplotlib – Python How to Change the Transparency of a Graph Plot in Matplotlib with Python? How to Change the Color of a Graph Plot in Matplotlib with Python? How to Change Fonts in matplotlib? How to Set Plot Background Color in Matplotlib? How to add text to Matplotlib? How to change Matplotlib color bar size in Python? More on Matplotlib Make a violin plot in Python using Matplotlib Errorbar graph in Python using Matplotlib Python | Basic Gantt chart using Matplotlib Stem and Leaf Plots in Python How to draw 2D Heatmap using Matplotlib in python? Plotting Correlation Matrix using Python Plot Candlestick Chart using mplfinance module in Python Autocorrelation plot using Matplotlib Place plots side by side in Matplotlib Difference Between cla(), clf() and close() Methods in Matplotlib Make filled polygons between two horizontal curves in Python using Matplotlib How to Save a Plot to a File Using Matplotlib? How to Plot Logarithmic Axes in Matplotlib? Using Matplotlib for Animations Recent Articles on Matplotlib !!! Seaborn Seaborn is a high-level library built on the top of Matplotlib which means that it can also use Matplotlib functions and classes. This library provides default styles and color palettes to make a plot more attractive. Introduction Introduction to Seaborn – Python Difference Between Matplotlib VS Seaborn Plotting graph using Seaborn Multiple Plots Grid Plot in Python using Seaborn FacetGrid() method PairGrid() method Multi-plot grid in Seaborn Relation Plots Relational plots in Seaborn – Part I Relational plots in Seaborn – Part II Data Visualization with Seaborn Line Plot Scatterplot using Seaborn in Python Categorical Plots Categorical Plots Barplot using seaborn in Python Count Plot using seaborn in Python Boxplot using Seaborn in Python Violin plot using Seaborn in Python Strip plot using Seaborn in Python Swarmplot using Seaborn in Python Factorplot Plotting different types of plots using Factor plot in seaborn Python Seaborn – Catplot Distribution Plots Distribution Plots How to Make Histograms with Density Plots with Seaborn histplot? Jointplot Data visualization with Pairplot Seaborn and Pandas Seaborn Kdeplot – A Comprehensive Guide Regression Plots Regression Plots Lmplot Regplot Matrix plots in Seaborn Seaborn Heatmap – A comprehensive guide Hierarchically-clustered Heatmap in Python with Seaborn Clustermap Customizing Plots Change Axis Labels, Set Title and Figure Size to Plots with Seaborn How to set the title and fonts of your Seaborn Chart? How To Place Legend Outside the Plot with Seaborn in Python? How to change Seaborn legends font size, location and color? How to add center align text in each subplot graph in seaborn? How to set a Seaborn chart figure size? Rotate axis tick labels in Seaborn and Matplotlib How to set axes labels & limits in a Seaborn plot? How to change axes limits in Seaborn? Seaborn – Color Palette Seaborn | Style And Color Recent Articles on Seaborn !!!​​​​​​​ Plotly After going through these two libraries, you all might be wondering why Plotly. Why we have to learn Plotly over the above visualization tools. Here’s why – Plotly has hover tool capabilities that allow us to detect any outliers or anomalies in a large number of data points. It is visually attractive that can be accepted by a wide range of audiences. It allows us for the endless customization of our graphs that makes our plot more meaningful and understandable for others. Introduction Getting Started with Plotly-Python Different Types of Charts Line Chart using Plotly in Python Bar Chart Bar chart using Plotly in Python How to create Stacked bar chart in Python-Plotly? How to group Bar Charts in Python-Plotly? Histograms Histogram using Plotly in Python How to create a Cumulative Histogram in Plotly? Scatter plot using Plotly in Python Bubble chart using Plotly in Python Pie plot using Plotly in Python Box Plot Box Plot using Plotly in Python How to create Grouped box plot in Plotly? Violin plot using Plotly in Python Gantt Chart in Plotly Contour Plots using Plotly in Python Create Heatmaps using graph_objects class in Plotly 3D Plots 3D Line Plots using Plotly in Python 3D scatter plot using Plotly in Python 3D Bubble chart using Plotly in Python 3D Mesh Plots using Plotly in Python Sunburst Plot using Plotly in Python Polar Charts using Plotly in Python Ternary Plots in Plotly Sankey Diagram using Plotly in Python Quiver Plots using Plotly in Python Treemap using Plotly in Python Interacting with the Plots How to make Dropdown Menus in Plotly? How to make Custom Buttons in Plotly? How to make Range Slider and Selector in Plotly? Recent Articles on Plotly !!!​​​​​​​ Like Article Suggest improvement Next Pandas Tutorial Share your thoughts in the comments Add Your Comment Please Login to comment...