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.
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.
|Matplotlib and its uses||Learn what is Matplotlib, why, and how it is used in Python.|
|Install Matplotlib Python||Learn how to install Matplotlib in Python.|
|Matplotlib inline in Python||Learn what is Matplotlib inline in Python, and how it is used.|
|Matplotlib default figure size||Learn how to find the default figure size using Matplotlib in Python.|
|Vertical line Matplotlib||Learn how to draw a vertical line in Matplotlib Python.|
|Horizontal line matplotlib||Learn how to draw a horizontal line in Python Matplotlib.|
|Matplotlib increase plot size||Learn how to increase a plot size using Matplotlib in Python.|
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.
|Matplotlib plot a line||Learn how to plot a line using Matplotlib in Python.|
|Python plot multiple lines using Matplotlib||Learn how to plot multiple lines using Matplotlib in Python.|
|Matplotlib plot bar chart||Learn how to plot a bar chart using Matplotlib in Python.|
|Matplotlib dashed line||Learn how to create, and plot a dashed line in Python using Matplotlib with different parameters.|
|Matplotlib scatter marker||Learn how to scatter plots with a marker using Matplotlib Python.|
|Stacked Bar Chart Matplotlib||Learn how to stack a bar chart using Python Matplotlib.|
|Matplotlib multiple bar chart||Learn how to create multiple bar charts in Python using Matplotlib.|
|Matplotlib Pie Chart Tutorial||Learn how to create a Matplotlib pie chart in Python.|
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.
|Matplotlib subplot||Learn how to create multiple subplots from a single call in Python Matplotlib.|
|Matplotlib subplots_adjust||Learn how to work with refining multiple plots within a single call i.e., adjusting multiple subplots in Matplotlib in Python.|
|Matplotlib multiple plots||Learn how to create multiple plots in Matplotlib in Python using different methods.|
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.
|Matplotlib best-fit line||Learn how to plot the best-fit line using Matplotlib in Python.|
|Matplotlib loglog plot||Learn how to create a Matplotlib loglog plot in Python with different log scales.|
|Matplotlib plot_date||Learn how to plot the data consisting of dates in Matplotlib Python.|
|Matplotlib plot error bars||Learn how to plot error bars using Matplotlib in Python.|
|Matplotlib invert y axis||Learn how to invert the y-axis of a graph using different methods in Python Matplotlib.|
|Matplotlib two y axes||Learn how to plot a graph with two y-axes in Matplotlib in Python.|
|Matplotlib Plot NumPy Array||Learn how to plot a graph using the NumPy array in Python Matplotlib.|
|Matplotlib update the plot in a loop||Learn how to update a plot with different loops like for and while, using Matplotlib in Python.|
|Matplotlib time series plot||Learn how to create, what is a time series plot and why we need it in Python Matplotlib.|
|Matplotlib secondary y-axis||Learn how to set the axes limits of the secondary y-axis using Matplotlib in Python with different functions for setting up the axes limits.|
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.
|Matplotlib 3D scatter||Learn how to plot a 3D scatter plot in the Python Matplotlib library.|
|Matplotlib 2D surface plot||Learn what is a Python Matplotlib 2D surface plot, color plot, and color surface plot.|
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.
|Matplotlib rotate tick labels||Learn what is meant by tick labels and the syntax for rotation of tick labels in Python Matplotlib.|
|Matplotlib remove tick labels||Learn how to remove tick labels using Matplotlib in Python.|
|Add text to plot Matplotlib in Python||Learn how to add text to a plot using Matplotlib in Python.|
|Matplotlib bar chart labels||Learn how to add labels to the bar chart using Matplotlib library methods in Python.|
|Matplotlib title font size||Learn how to change or edit the font size of the title with Matplotlib in Python.|
|Put legend outside plot matplotlib||Learn how to put a legend outside the plot area with Matplotlib in Python.|
|Matplotlib scatter plot legend||Learn how to add a legend to the Scatter Plot in Mathplotlib in Python.|
|Matplotlib x-axis label||Learn how to set labels to the x-axis in Matplotlib with different methods in Python.|
|Matplotlib set y axis range||Learn how to set a range to the y-axis with different modules in the Matplotlib library Python.|
|Matplotlib set axis range||Learn how to set axis range with different modules with Matplotlib in Python.|
|Matplotlib legend font size||Learn how to set the font size of the legend with different Matplotlib methods in Python.|
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.
|Python Matplotlib tick_params||Learn how to change the appearance of ticks, tick labels, and gridlines using tick_params in Matplotlib in Python.|
|Matplotlib tight_layout||Learn how to adjust the spacing between subplots using tight_layout in Python Matplotlib.|
|Matplotlib set_yticklabels||Learn how to set the y-ticks labels with the list of string labels using set_yticklabels with Matplotlib in Python.|
|Matplotlib set_xticklabels||Learn how to set the x-ticks labels with the list of string labels using set_xticklables with Matplotlib in Python.|
|Matplotlib set_xticks||Learn how to set the x ticks location using set_xticks methods in the Python Matplotlib library.|
|Matplotlib xlim() function||Learn 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 matplotlib||Learn how to add axes to the figure in Matplotlib in Python.|
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.
|Matplotlib save as png||Learn how to save a plot or graph as an image file i.e., png by using the Matplotlib library in Python.|
|Matplotlib savefig blank image||Learn how to fix the matplotlib savefig blank image using different functions in Matplotlib Python.|
|Matplotlib scatter plot color||Learn how to color scatter plot depending on different conditions with Matplotlib functions in Python.|
|Matplotlib fill_between||Learn what the fill_between function is in the pyplot module of Matplotlib in Python.|
|Matplotlib save as pdf||Learn how to save a plot, chart, or graph as a pdf file by using the Matplotlib library in Python.|
|Matplotlib change the background color||Learn how to change the background color of the plot with Matplotlib in Python.|
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.
|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 backend||Learn 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 installed||Learn how to handle Matplotlib 1.3.1 requires nose which is not installed error in Python.|
|Matplotlib not showing the plot||Learn how to handle Matplotlib not showing the plot error in different editors in Python.|
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.