Complete Python & Matplotlib Data Visualization

Install Python 3 on Windows by downloading the installer from the Python website, running the setup, and enabling add to PATH with admin privileges, then verify installation.

Verify Python 3 environment on Windows by checking the environment variable and locating the Python executable from the command prompt.

Explore Raspberry Pi, the bestselling credit-card size single board computer embedded on a PCB, with non-upgradable design and GPIO, USB, HDMI ports.

Install Raspberry Pi OS on a Raspberry Pi 4 using the Raspberry Pi Imager, configure a headless wifi setup, and enable remote desktop access (RDP) via xrdp.

Enable and use VNC on Raspberry Pi to access its graphical desktop remotely from Windows, installing the VNC server and connecting via VNC viewer with adjustable resolution.

Open the command prompt on Raspberry Pi running Raspbian, run sudo apt-get update, then sudo apt-get install idle3. Verify by launching Python 3 from the programming section.

Discover how to run Python 3 on Raspberry Pi, invoke the Python 3 interpreter, explore IDEs and shells, and write and execute a hello world program.

Explore additional software for remote connection to Raspberry Pi, including putty and mobile system, highlighting remote command line access, remote file transfer, and X11 forwarding with an all-in-one solution.

Turn a Raspberry Pi 4 into a low-cost portable tablet by assembling the kit, connecting the display, microSD, power, cooling fan, and GPIO ribbon, then boot.

Write and run a hello world program on a Raspberry Pi using Python 3 from the terminal or an editor, and set executable permissions with a shebang.

Explore PyPI, the Python package index, and the pip tool, and see how batteries included libraries are hosted and installed automatically via pip.

Learn how to use pip on Windows in admin mode to manage Python packages. Check version, upgrade pip, list installed packages, search PyPI, and install or uninstall libraries.

Learn to manage Python packages on a Raspberry Pi using pip, upgrading to the latest version, listing packages, searching the package index, and installing or uninstalling with sudo when needed.

Install numpy and matplotlib on Windows with pip in an elevated command prompt. Verify by opening Python and importing numpy as np and matplotlib as plt to confirm successful installation.

Install NumPy and Matplotlib on Raspberry Pi by using apt-get or pip, verify by importing NumPy as np and matplotlib.pyplot, and ensure the latest versions are installed.

Explore IPython and Jupyter as interactive notebooks that run in the browser and render Markdown and rich outputs. See how language-agnostic kernels extend Python to many languages for data visualization.

Install Jupyter on Windows via an admin command prompt, install with pip, configure antivirus exceptions, launch the notebook, create and run a hello world notebook, then save and shut down.

Install Jupiter on Raspberry Pi and resolve dependencies, including the prompt toolkit 2.0. Then launch the Jupiter notebook server and verify the installation in a browser.

Install PuTTY on Windows PC by downloading the 64-bit installer and running the setup with admin privileges; then add the executable to the path and verify in cmd.

Connect to a remote Jupiter notebook on a Raspberry Pi from a Windows machine using SSH port forwarding and access it in a browser with the login token.

Learn how to start and connect to a Jupiter notebook, set a project root, write and run Python cells, and save, rename, and share ipynb notebooks from a Raspberry Pi.

NumPy provides the foundation for scientific computing in Python with a powerful multidimensional array object and fast numerical operations used by image and signal processing libraries.

Explore ndarrays in numpy from 1d to 3d and master colon-based slicing to access rows, columns, and elements with concise, loop-free indexing.

Explore ndarray properties, including shape, ndim, dtype, size, and bytes, and learn to compute the transpose of a three-dimensional data structure.

Explore NumPy constants such as inf, -inf, nan, and zero, and review key mathematical constants like e and gamma using a simple notebook demonstration.

Demonstrates creating and resizing matrices of ones and zeros, including identity and shifted-diagonal matrices in 3x3, 5x5, and higher dimensions, using unsigned 8-bit data.

Explore routines to create lower and upper triangular matrices filled with ones, shift diagonals, and visualize 5x5 examples to understand how diagonal position affects matrix structure.

Explore numerical ranges in Python and visualize them with matplotlib, using range, linspace, logspace, and geometric space to generate x and y data, apply transformations, and customize plots.