- Matplotlib Basics
- Matplotlib - Home
- Matplotlib - Introduction
- Matplotlib - Vs Seaborn
- Matplotlib - Environment Setup
- Matplotlib - Anaconda distribution
- Matplotlib - Jupyter Notebook
- Matplotlib - Pyplot API
- Matplotlib - Simple Plot
- Matplotlib - Saving Figures
- Matplotlib - Markers
- Matplotlib - Figures
- Matplotlib - Styles
- Matplotlib - Legends
- Matplotlib - Colors
- Matplotlib - Colormaps
- Matplotlib - Colormap Normalization
- Matplotlib - Choosing Colormaps
- Matplotlib - Colorbars
- Matplotlib - Working With Text
- Matplotlib - Text properties
- Matplotlib - Subplot Titles
- Matplotlib - Images
- Matplotlib - Image Masking
- Matplotlib - Annotations
- Matplotlib - Arrows
- Matplotlib - Fonts
- Matplotlib - Font Indexing
- Matplotlib - Font Properties
- Matplotlib - Scales
- Matplotlib - LaTeX
- Matplotlib - LaTeX Text Formatting in Annotations
- Matplotlib - PostScript
- Matplotlib - Mathematical Expressions
- Matplotlib - Animations
- Matplotlib - Celluloid Library
- Matplotlib - Blitting
- Matplotlib - Toolkits
- Matplotlib - Artists
- Matplotlib - Styling with Cycler
- Matplotlib - Paths
- Matplotlib - Path Effects
- Matplotlib - Transforms
- Matplotlib - Ticks and Tick Labels
- Matplotlib - Radian Ticks
- Matplotlib - Dateticks
- Matplotlib - Tick Formatters
- Matplotlib - Tick Locators
- Matplotlib - Basic Units
- Matplotlib - Autoscaling
- Matplotlib - Reverse Axes
- Matplotlib - Logarithmic Axes
- Matplotlib - Symlog
- Matplotlib - Unit Handling
- Matplotlib - Ellipse with Units
- Matplotlib - Spines
- Matplotlib - Axis Ranges
- Matplotlib - Axis Scales
- Matplotlib - Axis Ticks
- Matplotlib - Formatting Axes
- Matplotlib - Axes Class
- Matplotlib - Twin Axes
- Matplotlib - Figure Class
- Matplotlib - Multiplots
- Matplotlib - Grids
- Matplotlib - Object-oriented Interface
- Matplotlib - PyLab module
- Matplotlib - Subplots() Function
- Matplotlib - Subplot2grid() Function
- Matplotlib - Anchored Artists
- Matplotlib - Manual Contour
- Matplotlib - Coords Report
- Matplotlib - AGG filter
- Matplotlib - Ribbon Box
- Matplotlib - Fill Spiral
- Matplotlib - Findobj Demo
- Matplotlib - Hyperlinks
- Matplotlib - Image Thumbnail
- Matplotlib - Plotting with Keywords
- Matplotlib - Create Logo
- Matplotlib - Multipage PDF
- Matplotlib - Multiprocessing
- Matplotlib - Print Stdout
- Matplotlib - Compound Path
- Matplotlib - Sankey Class
- Matplotlib - MRI with EEG
- Matplotlib - Stylesheets
- Matplotlib - Background Colors
- Matplotlib - Basemap
- Matplotlib Event Handling
- Matplotlib - Event Handling
- Matplotlib - Close Event
- Matplotlib - Mouse Move
- Matplotlib - Click Events
- Matplotlib - Scroll Event
- Matplotlib - Keypress Event
- Matplotlib - Pick Event
- Matplotlib - Looking Glass
- Matplotlib - Path Editor
- Matplotlib - Poly Editor
- Matplotlib - Timers
- Matplotlib - Viewlims
- Matplotlib - Zoom Window
- Matplotlib Widgets
- Matplotlib - Cursor Widget
- Matplotlib - Annotated Cursor
- Matplotlib - Buttons Widget
- Matplotlib - Check Buttons
- Matplotlib - Lasso Selector
- Matplotlib - Menu Widget
- Matplotlib - Mouse Cursor
- Matplotlib - Multicursor
- Matplotlib - Polygon Selector
- Matplotlib - Radio Buttons
- Matplotlib - RangeSlider
- Matplotlib - Rectangle Selector
- Matplotlib - Ellipse Selector
- Matplotlib - Slider Widget
- Matplotlib - Span Selector
- Matplotlib - Textbox
- Matplotlib Plotting
- Matplotlib - Line Plots
- Matplotlib - Area Plots
- Matplotlib - Bar Graphs
- Matplotlib - Histogram
- Matplotlib - Pie Chart
- Matplotlib - Scatter Plot
- Matplotlib - Box Plot
- Matplotlib - Arrow Demo
- Matplotlib - Fancy Boxes
- Matplotlib - Zorder Demo
- Matplotlib - Hatch Demo
- Matplotlib - Mmh Donuts
- Matplotlib - Ellipse Demo
- Matplotlib - Bezier Curve
- Matplotlib - Bubble Plots
- Matplotlib - Stacked Plots
- Matplotlib - Table Charts
- Matplotlib - Polar Charts
- Matplotlib - Hexagonal bin Plots
- Matplotlib - Violin Plot
- Matplotlib - Event Plot
- Matplotlib - Heatmap
- Matplotlib - Stairs Plots
- Matplotlib - Errorbar
- Matplotlib - Hinton Diagram
- Matplotlib - Contour Plot
- Matplotlib - Wireframe Plots
- Matplotlib - Surface Plots
- Matplotlib - Triangulations
- Matplotlib - Stream plot
- Matplotlib - Ishikawa Diagram
- Matplotlib - 3D Plotting
- Matplotlib - 3D Lines
- Matplotlib - 3D Scatter Plots
- Matplotlib - 3D Contour Plot
- Matplotlib - 3D Bar Plots
- Matplotlib - 3D Wireframe Plot
- Matplotlib - 3D Surface Plot
- Matplotlib - 3D Vignettes
- Matplotlib - 3D Volumes
- Matplotlib - 3D Voxels
- Matplotlib - Time Plots and Signals
- Matplotlib - Filled Plots
- Matplotlib - Step Plots
- Matplotlib - XKCD Style
- Matplotlib - Quiver Plot
- Matplotlib - Stem Plots
- Matplotlib - Visualizing Vectors
- Matplotlib - Audio Visualization
- Matplotlib - Audio Processing
- Matplotlib Useful Resources
- Matplotlib - Quick Guide
- Matplotlib - Useful Resources
- Matplotlib - Discussion
Matplotlib - Anaconda Distribution
Matplotlib library is a widely-used plotting library in Python and it is commonly included in the Anaconda distribution.
What is Anaconda Distribution?
Anaconda is a distribution of Python and other open-source packages that aims to simplify the process of setting up a Python environment for data science, machine learning and scientific computing.
Anaconda distribution is available for installation at https://www.anaconda.com/download/. For installation on Windows, 32 and 64 bit binaries are available −
Anaconda3-5.1.0-Windows-x86.exe
Anaconda3-5.1.0-Windows-x86_64.exe
Installation is a fairly straightforward wizard based process. You can choose between adding Anaconda in PATH variable and registering Anaconda as your default Python.
For installation on Linux, download installers for 32 bit and 64 bit installers from the downloads page −
Anaconda3-5.1.0-Linux-x86_64.sh
Now, run the following command from the Linux terminal −
Syntax
$ bash Anaconda3-5.0.1-Linux-x86_64.sh
Canopy and ActiveState are the most sought after choices for Windows, macOS and common Linux platforms. The Windows users can find an option in WinPython.
Here is how Matplotlib is typically associated with the Anaconda distribution:
Matplotlib in Anaconda
Pre-Installed
Matplotlib library is often included in the default installation of the Anaconda distribution. When we install Anaconda Matplotlib is available along with many other essential libraries for data visualization.
Integration with Jupyter
Anaconda comes with Jupyter Notebook which is a popular interactive computing environment. Matplotlib seamlessly integrates with Jupyter and makes our work easy to create and visualize plots within Jupyter Notebooks.
Anaconda Navigator
Anaconda Navigator is a graphical user interface that comes with the Anaconda distribution. This allows users to manage environments, install packages and launch applications. It provides an easy way to access and launch Jupyter Notebooks for Matplotlib plotting.
Conda Package Manager
Anaconda uses the 'conda' package manager which simplifies the installation, updating and managing of Python packages. We can use 'conda' to install or update Matplotlib within our Anaconda environment.
Verifying Matplotlib Installation
To verify whether Matplotlib is installed in our Anaconda environment we can use the following steps.
Open the Anaconda Navigator.
Navigate to the "Envinornments" tab.
Look for "Matplotlib" in the list of installed packages. If it's there Matplotlib is installed.
Alternatively we can open Anaconda Prompt or a terminal and run the below mentioned code
Syntax
conda list matplotlib
This command will list the installed version of Matplotlib in our current Anaconda environment.
Output
Installing or Updating Matplotlib in Anaconda
If Matplotlib is not installed or we want to update it then we can use the following commands in the Anaconda Prompt or terminal.
To install Matplotlib
Syntax
conda install matplotlib
As the matplotlib is already installed in the system it’s shown the message the All requested packages already installed.
To update Matplotlib
Syntax
conda update matplotlib
The above mentioned commands will manage the installation or update of Matplotlib and its dependencies in our Anaconda environment.
Finally we can say Matplotlib is a fundamental part of the Anaconda distribution making it convenient for users to create high-quality visualizations in their Python environments for data analysis and scientific computing.