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 Matplotlib tutorials.

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

## Getting Started with Matplotlib

This Matplotlib 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.

- What is Matplotlib and how to use it in Python
- How to install matplotlib python
- What is Matplotlib inline in Python
- Matplotlib default figure size
- Draw vertical line matplotlib
- Horizontal line matplotlib
- Matplotlib increase plot size

## Different Types of Plots

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 (Detailed Guide)
- Python plot multiple lines using Matplotlib
- Matplotlib plot bar chart
- Matplotlib dashed line – Complete Tutorial
- Matplotlib scatter marker
- Stacked Bar Chart Matplotlib – complete tutorial
- Matplotlib multiple bar chart
- Matplotlib Pie Chart Tutorial

## 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.

## 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.

- Matplotlib best fit line
- Matplotlib log log plot
- Matplotlib plot_date – Complete tutorial
- Matplotlib plot error bars
- Matplotlib invert y axis
- Matplotlib two y axes
- Matplotlib Plot NumPy Array
- Matplotlib update plot in loop
- Matplotlib time series plot
- Matplotlib secondary y-axis [Complete Guide]

## Matplotlib 3-D Plots

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

## 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
- Matplotlib remove tick labels
- Add text to plot matplotlib in Python
- Matplotlib bar chart labels
- Matplotlib title font size
- Put legend outside plot matplotlib
- Matplotlib scatter plot legend
- Matplotlib x-axis label
- Matplotlib set y axis range
- Matplotlib set axis range
- Matplotlib legend font size

## 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 + 29 examples
- Matplotlib tight_layout – Helpful tutorial
- Matplotlib set_yticklabels – Helpful Guide
- Matplotlib set_xticklabels
- Matplotlib set_xticks – Detailed tutorial
- Matplotlib xlim – Complete Guide
- What is add_axes matplotlib

## 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
- Matplotlib savefig blank image
- Matplotlib scatter plot color
- Matplotlib fill_between – Complete Guide
- Matplotlib save as pdf + 13 examples
- Matplotlib change background color

## 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’
- module ‘matplotlib’ has no attribute ‘plot’
- module ‘matplotlib’ has no attribute ‘artist’
- Matplotlib is currently using agg a non-gui backend
- Matplotlib unknown projection ‘3d’
- Matplotlib 1.3.1 requires nose which is not installed
- Matplotlib not showing plot