Matplotlib Tutorials

If you want to visualize data, Python offers a very well-known library known as Matplotlib created by John D. Hunter, which enables both easy things easy and hard things possible. It is a robust library for producing static, animated, and interactive visualizations in Python.

So, if you are looking for a place where you can get started with the Matplotlib library. This is the place where you can get complete Python Matplotlib tutorials beginner or advanced.

This website will provide you with a brief introduction to fundamental to advanced Matplotlib topics.

Python matplotlib logo

Getting Started with Matplotlib

This Python Matplotlib tutorials section will illustrate the steps of how to get started with the Matplotlib library. It will cover some fundamental concepts, a quick introduction to Matplotlib, and instructions for installing Matplotlib.

NameDescription
Matplotlib and its usesLearn what is Matplotlib, why, and how it is used in Python.
Install Matplotlib PythonLearn how to install Matplotlib in Python.
Matplotlib inline in PythonLearn what is Matplotlib inline in Python, and how it is used.
Matplotlib default figure sizeLearn how to find the default figure size using Matplotlib in Python.
Vertical line MatplotlibLearn how to draw a vertical line in Matplotlib Python.
Horizontal line matplotlibLearn how to draw a horizontal line in Python Matplotlib.
Matplotlib increase plot sizeLearn how to increase a plot size using Matplotlib in Python.
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Different Types of Plots in Matplotlib Tutorials

After learning how to get started with Matplotlib, let’s go on to the next stage, where we learn how to create various plot types in Matplotlib.

NameDescription
Matplotlib plot a lineLearn how to plot a line using Matplotlib in Python.
Python plot multiple lines using MatplotlibLearn how to plot multiple lines using Matplotlib in Python.
Matplotlib plot bar chartLearn how to plot a bar chart using Matplotlib in Python.
Matplotlib dashed lineLearn how to create, and plot a dashed line in Python using Matplotlib with different parameters.
Matplotlib scatter markerLearn how to scatter plots with a marker using Matplotlib Python.
Stacked Bar Chart MatplotlibLearn how to stack a bar chart using Python Matplotlib.
Matplotlib multiple bar chartLearn how to create multiple bar charts in Python using Matplotlib.
Matplotlib Pie Chart TutorialLearn how to create a Matplotlib pie chart in Python.
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Matplotlib Subplots

Sometimes it is useful to contrast various data views side by side. To do this, Matplotlib has the concept of subplots and multiple plots.

Therefore, in this Matplotlib section, we will explore subplots, multiple plots, and how to plot them.

NameDescription
Matplotlib subplotLearn how to create multiple subplots from a single call in Python Matplotlib.
Matplotlib subplots_adjustLearn how to work with refining multiple plots within a single call i.e., adjusting multiple subplots in Matplotlib in Python.
Matplotlib multiple plotsLearn how to create multiple plots in Matplotlib in Python using different methods.
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Advance Plots

The fundamental capabilities of the Matplotlib library, including the ability to visualize bar graphs, line charts, pie charts, and other common data are well known.

However, I will highlight some of the advanced graphs in Matplotlib in this tutorial section, which can progress our understanding.

NameDescription
Matplotlib best-fit lineLearn how to plot the best-fit line using Matplotlib in Python.
Matplotlib loglog plotLearn how to create a Matplotlib loglog plot in Python with different log scales.
Matplotlib plot_dateLearn how to plot the data consisting of dates in Matplotlib Python.
Matplotlib plot error barsLearn how to plot error bars using Matplotlib in Python.
Matplotlib invert y axisLearn how to invert the y-axis of a graph using different methods in Python Matplotlib.
Matplotlib two y axesLearn how to plot a graph with two y-axes in Matplotlib in Python.
Matplotlib Plot NumPy ArrayLearn how to plot a graph using the NumPy array in Python Matplotlib.
Matplotlib update the plot in a loopLearn how to update a plot with different loops like for and while, using Matplotlib in Python.
Matplotlib time series plotLearn how to create, what is a time series plot and why we need it in Python Matplotlib.
Matplotlib secondary y-axisLearn how to set the axes limits of the secondary y-axis using Matplotlib in Python with different functions for setting up the axes limits.
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Matplotlib 3-D Plots

The Matplotlib library is used to create both 2D and 3D graphs from data. So, in this Matplotlib tutorials section, we will explore three-dimensional plots and how to plot them.

NameDescription
Matplotlib 3D scatterLearn how to plot a 3D scatter plot in the Python Matplotlib library.
Matplotlib 2D surface plotLearn what is a Python Matplotlib 2D surface plot, color plot, and color surface plot.
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Customizing Plots in Matplotlib

One of the merits that contribute towards the success of Matplotlib is Customizable. It allows us to customize the features and configurations of the graphs. 

So, in this Matplotlib tutorial section, we will explore how to customize the Matplotlib plots.

NameDescription
Matplotlib rotate tick labelsLearn what is meant by tick labels and the syntax for rotation of tick labels in Python Matplotlib.
Matplotlib remove tick labelsLearn how to remove tick labels using Matplotlib in Python.
Add text to plot Matplotlib in PythonLearn how to add text to a plot using Matplotlib in Python.
Matplotlib bar chart labelsLearn how to add labels to the bar chart using Matplotlib library methods in Python.
Matplotlib title font sizeLearn how to change or edit the font size of the title with Matplotlib in Python.
Put legend outside plot matplotlibLearn how to put a legend outside the plot area with Matplotlib in Python.
Matplotlib scatter plot legendLearn how to add a legend to the Scatter Plot in Mathplotlib in Python.
Matplotlib x-axis labelLearn how to set labels to the x-axis in Matplotlib with different methods in Python.
Matplotlib set y axis rangeLearn how to set a range to the y-axis with different modules in the Matplotlib library Python.
Matplotlib set axis rangeLearn how to set axis range with different modules with Matplotlib in Python.
Matplotlib legend font sizeLearn how to set the font size of the legend with different Matplotlib methods in Python.
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Matplotlib Special Functions

Matplotlib offers us several functions to make the graphs more attractive and simple to comprehend. Therefore, in this Matplotlib section, we will explore these functions.

NameDescription
Python Matplotlib tick_paramsLearn how to change the appearance of ticks, tick labels, and gridlines using tick_params in Matplotlib in Python.
Matplotlib tight_layoutLearn how to adjust the spacing between subplots using tight_layout in Python Matplotlib.
Matplotlib set_yticklabelsLearn how to set the y-ticks labels with the list of string labels using set_yticklabels with Matplotlib in Python.
Matplotlib set_xticklabelsLearn how to set the x-ticks labels with the list of string labels using set_xticklables with Matplotlib in Python.
Matplotlib set_xticksLearn how to set the x ticks location using set_xticks methods in the Python Matplotlib library.
Matplotlib xlim() functionLearn how to set or get the x-axis limits using the xlim() function in the Pyplot module in the Matplotlib library in Python.
add_axes matplotlibLearn how to add axes to the figure in Matplotlib in Python.
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Working with Colors and Images

Matplotlib gives us the ability to plot graphs in various colors and save them in a variety of formats, such as PNG, PDF, etc. Therefore, we will learn how to work with color and images in this Matplotlib section.

NameDescription
Matplotlib save as pngLearn how to save a plot or graph as an image file i.e., png by using the Matplotlib library in Python.
Matplotlib savefig blank imageLearn how to fix the matplotlib savefig blank image using different functions in Matplotlib Python.
Matplotlib scatter plot colorLearn how to color scatter plot depending on different conditions with Matplotlib functions in Python.
Matplotlib fill_betweenLearn what the fill_between function is in the pyplot module of Matplotlib in Python.
Matplotlib save as pdfLearn how to save a plot, chart, or graph as a pdf file by using the Matplotlib library in Python.
Matplotlib change the background colorLearn how to change the background color of the plot with Matplotlib in Python.
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Matplotlib Errors and Warnings

Whether you are a beginner or a Matplotlib expert, you may run into errors or problems while using the library. So, that you don’t have to struggle to find solutions, I have outlined the approaches for fixing a variety of Matplotlib issues in this section.

NameDescription
ModuleNotFoundError: no module named ‘matplotlib’Learn how to handle ModuleNotFoundError: No module named ‘matplotlib’ in Python with a different OS and editor.
module ‘matplotlib’ has no attribute ‘plot’Learn how to handle the module ‘matplotlib’ has no attribute ‘plot’, two different errors using Matplotlib in Python.
module ‘matplotlib’ has no attribute ‘artist’Learn how to handle the module ‘matplotlib, has no attribute ‘artist’, three different errors using Matplotlib in Python.
Matplotlib is currently using agg a non-gui backendLearn how to handle the Warning: Matplotlib is currently using agg a non-GUI backend using Matplotlib in Python.
Matplotlib unknown projection ‘3D’Learn the reason and solutions to handle the Matplotlib unknown projection ‘3D’ in Python.
Matplotlib 1.3.1 requires nose which is not installedLearn how to handle Matplotlib 1.3.1 requires nose which is not installed error in Python.
Matplotlib not showing the plotLearn how to handle Matplotlib not showing the plot error in different editors in Python.
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Conclusion

In this comprehensive Python Matplotlib tutorials, we journeyed from the basics to the advanced, covering the myriad ways in which this powerful library can be utilized.

We started with an introduction, delving into the initial steps to get acquainted with Matplotlib. From there, we explored the various types of plots, understood how to create and manipulate subplots, and ventured into advanced 3D plots.

Customizing these plots to suit our visual preferences was a key highlight, complemented by an in-depth look at special functions and techniques to work with colors and images. Lastly, we addressed potential errors and warnings to ensure smooth charting experiences.

Whether you’re a beginner or a seasoned professional, Matplotlib offers an extensive array of functionalities to visualize data effectively.