Python 3 Data Processing with Pandas and Plotly

Install Python 3 on Windows by downloading the official python.org installer and running it with admin privileges. Understand Python 3 and Python 2 flavors and verify the installation.

Verify Python 3 is added to Windows environment variables and accessible from the command prompt; confirm the installation path, the scripts folder, and version with python -V.

Explore what Raspberry Pi is, a credit-card-sized single-board computer, why SBCs differ from traditional PCs, and its key hardware like processor, RAM, GPIO, USB-C, micro HDMI, camera and display ports.

Learn to flash Raspberry Pi OS onto a Raspberry Pi 4 with the Raspberry Pi Imager and set up headless remote access over Wi-Fi, including IP discovery for remote connection.

Learn to access the Raspberry Pi's graphical desktop remotely by enabling the VNC server, installing the VNC viewer, and connecting from Windows.

Install idle3 on Raspberry Pi running Raspbian by updating repositories and installing idle3, verify the install with the exit status, and launch the Python 3 prompt from the programming section.

Discover how to run Python 3 on Raspberry Pi, invoke the Python 3 interpreter, and work with pre-installed development tools to write and execute hello world programs.

Learn to connect to a Raspberry Pi remotely using additional software such as Putty, VCP, and mobile system for remote command line, file transfer, and X11 forwarding.

Turn a Raspberry Pi 4 into a portable touchscreen tablet by assembling the SunFounder kit, wiring the display, microSD, power, Ethernet, USB, HDMI, cooling fan, and GPIO ribbon.

discover how to write and run a simple hello world program in Python 3 on Windows using the interpreter or the command prompt.

Learn to write and run a Python 3 hello world on a Raspberry Pi, using IDLE and the terminal, set executable permissions, and add a shebang for direct shell execution.

Compare Python 3 interpreter mode, an interactive memory-driven environment for prototyping, with script mode that runs saved files for data science and automation.

Learn to launch IDLE on Raspberry Pi, create and run Python programs, save files with .py extensions, and explore essential editor features and help resources.

Compare Raspberry Pi with a laptop and a custom PC to weigh low-cost, low-power options against high-performance machines, and learn where Raspberry Pi fits light Python projects and small databases.

Explore the Python package index and its repository of third-party libraries. Learn to search, download, and automatically install packages, and discover how to contribute your own library for public use.

Learn to manage Python packages on Windows using pip: check version, upgrade, list, search, install, and uninstall libraries.

Learn to use pip3 on a Raspberry Pi to upgrade pip3, list installed packages, search PyPI, and install or uninstall packages with sudo when needed.

Install numpy and matplotlib on Windows by running pip install numpy and pip install matplotlib in an admin command prompt; verify installations by importing numpy and matplotlib in Python.

Upgrade numpy and install matplotlib on a Raspberry Pi, then verify by launching Python 3 and importing numpy as np and matplotlib.pyplot as plt.

Explore IPython's interactive computing with a browser-based notebook, learn Jupiter's language-agnostic support for 40+ languages, markdown-rich text, inline visualizations, and sharing of notebooks.

Install jupiter on Windows using the command prompt with admin privileges, handle antivirus scans, install jupiter, launch a jupiter notebook, create and save a notebook, run hello world, and exit.

Install and verify Jupiter on a Raspberry Pi by installing the required kernel and dependencies, then launch the Jupiter notebook server and open it in the chromium browser.

Install putty on Windows by downloading the 64-bit installer from putty.org and running the setup with admin privileges. Add the executable to the path and verify by typing putty.

Connect to a remote Jupyter notebook running on a Raspberry Pi from Windows by launching a headless server, tunneling the port with SSH, and logging in with a token.

Launch a Jupyter notebook from a root directory, connect via an SSH tunnel, run Python in interactive cells, and save or rename notebooks with ipynb and other downloadable formats.

Explore NumPy, the core Python library for scientific computing, offering the ndarray data structure and operations to process multidimensional data for image, signal, and data science tasks.

Master numpy ndarrays by creating 1D, 2D, and 3D arrays, indexing elements, and slicing with colon syntax. Understand out-of-bounds errors and how to efficiently access data in Python.

Explore ndarray properties by creating a three-dimensional ndarray and inspecting its shape, number of dimensions, dtype, size, and size in bytes, then compute its transpose.

Explains numpy's mathematical and scientific constants, including representations of infinity, NaN, and zero, and shows how to access and print constants such as e and gamma.

Create and manipulate three by three matrices using ones, zeros, identity, and full functions, control diagonal position with k, and build n dimensional matrices for scientific computing.

Explore routines to create upper and lower triangular matrices in Python, with diagonals of ones and diagonal shifts controlled by k.

Explore matplotlib, an open-source Python plotting library with a MATLAB-like pyplot interface that enables 10–15 line plots, including bar charts, scatter plots, and 3D visuals in IPython or Jupyter notebooks.

Generate numerical ranges with arange and linspace and visualize data in Python. Plot x versus y, customize titles and axes, and explore linear, logarithmic, and geometric progressions.

Learn to generate random numbers with numpy, creating 1d arrays and multidimensional matrices, including 3x3 and higher dimensions, using two functions for random integers and n-dimensional arrays.