Resources for teaching & learning practical data visualization with python.

Overview

Practical Data Visualization with Python

Overview

All views expressed on this site are my own and do not represent the opinions of any entity with which I have been, am now, or will be affiliated.

This repository contains all materials related to a lecture / seminar I teach on practical data visualization with python. What I mean by "practical" is that the materials herein do not focus on one particular library or data visualization method; rather, my goal is to empower the consumer of this content with the tools, heuristics, and methods needed to handle a wide variety of data visualization problems.

If you have questions, comments, or suggested alterations to these materials, please open an issue here on GitHub. Also, don't hesitate to reach out via LinkedIn.

Outline of Materials

Below you'll find a brief outline of the content contained in the four sections of this seminar, along with notebook links, and an example visualization from each section. For each section there is a separate notebook of python code containing all the materials for that section. Each notebook will start with a few setup steps--package imports and data prep mostly--that are almost identical between the notebooks, directly after which comes the content for each section. For information about the data used in these materials, check out the data_prep_nb.ipynb notebook, the easy-to-view version of which is hosted here.

Section 1: Why We Visualize

Here is the link to the easy-to-view notebook for this section of material.
Here is the link to the GitHub-hosted notebook for this section of the material.

  1. The power of visual data representation and storytelling.
  2. A few principles and heuristics of visualization.
  3. The building blocks of visualization explored.

Example Visualization from this Section:

Section 2: Overview of Python Visualization Landscape

Here is the link to the easy-to-view notebook for this section of material.
Here is the link to the GitHub-hosted notebook for this section of the material.

  1. Intro to the visualization ecosystem: python's Tower of Babel.
  2. Smorgasbord of packages explored through a single example viz.
  3. Quick & dirty (and subjective) heuristics for picking a visualization package.

Example Visualization from this Section:

Section 3: Statistical Visualization in the Wild

Here is the link to the easy-to-view notebook for this section of material.
Here is the link to the GitHub-hosted notebook for this section of the material.

  1. Example business use case of data visualization:
    1. Observational:
      • mean, median, and variance
      • distributions
    2. Inferential:
      • parametric tests
      • non-parametric tests

Example Visualization from this Section:

Section 4: Library Deep-Dive (Plotly)

Here is the link to the easy-to-view notebook for this section of material.
Here is the link to the GitHub-hosted notebook for this section of the material.

  1. Quick and simple data visualizations with Plotly Express.
  2. Additional control and complexity with base Plotly.

Example Visualization from this Section:

Homework Exercises

There is a homework associated with these materials, for those interested. Given the open-ended nature of the homework, there is no answer key. That said, if you're working through it and would like some feedback, feel free to reach out to me via LinkedIn.

Here is the link to the easy-to-view homework notebook.
Here is the link to the GitHub-hosted version of the homework notebook.

Setup Instructions

  • clone this repository
  • create a virtual environment using python3 -m venv env
  • activate that virtual environment using source env/bin/activate
  • install needed packages using pip install -r requirements.txt
  • run an instance of jupyter lab out of your virutal env using env/bin/jupyter-lab
  • open and run the four main files of content for this course--one for each section:
    • part_1_main_nb.ipynb
    • part_2_main_nb.ipynb
    • part_3_main_nb.ipynb
    • part_4_main_nb.ipynb
Owner
Paul Jeffries
Trained in intl. econ; started in mortgage finance; dabbled in equities & crypto; now working in banking. I enjoy challenging questions regarding value & risk.
Paul Jeffries
Minimalistic tool to visualize how the routes to a given target domain change over time, feat. Python 3.10 & mermaid.js

Minimalistic tool to visualize how the routes to a given target domain change over time, feat. Python 3.10 & mermaid.js

Péter Ferenc Gyarmati 1 Jan 17, 2022
Altair extension for saving charts in a variety of formats.

Altair Saver This packge provides extensions to Altair for saving charts to a variety of output types. Supported output formats are: .json/.vl.json: V

Altair 85 Dec 09, 2022
Generating interfaces(CLI, Qt GUI, Dash web app) from a Python function.

oneFace is a Python library for automatically generating multiple interfaces(CLI, GUI, WebGUI) from a callable Python object. oneFace is an easy way t

NaNg 31 Oct 21, 2022
An automatic prover for tautologies in Metamath

completeness An automatic prover for tautologies in Metamath This program implements the constructive proof of the Completeness Theorem for propositio

Scott Fenton 2 Dec 15, 2021
Lightweight, extensible data validation library for Python

Cerberus Cerberus is a lightweight and extensible data validation library for Python. v = Validator({'name': {'type': 'string'}}) v.validate({

eve 2.9k Dec 27, 2022
GD-UltraHack - A Mod Menu for Geometry Dash. Specifically a MegahackV5 clone in Python. Only for Windows

GD UltraHack: The Mod Menu that Nobody asked for. This is a mod menu for the gam

zeo 1 Jan 05, 2022
Blender addon that creates a temporary window of any type from the 3D View.

CreateTempWindow2.8 Blender addon that creates a temporary window of any type from the 3D View. Features Can the following window types: 3D View Graph

3 Nov 27, 2022
I'm doing Genuary, an aritifiacilly generated month to build code that make beautiful things

Genuary 2022 I'm doing Genuary, an aritifiacilly generated month to build code that make beautiful things. Every day there is a new prompt for making

Joaquín Feltes 1 Jan 10, 2022
GUI for visualization and interactive editing of SMPL-family body models ie. SMPL, SMPL-X, MANO, FLAME.

Body Model Visualizer Introduction This is a simple Open3D-based GUI for SMPL-family body models. This GUI lets you play with the shape, expression, a

Muhammed Kocabas 207 Jan 01, 2023
This is a Boids Simulation, written in Python with Pygame.

PyNBoids A Python Boids Simulation This is a Boids simulation, written in Python3, with Pygame2 and NumPy. To use: Save the pynboids_sp.py file (and n

Nik 17 Dec 18, 2022
Time series visualizer is a flexible extension that provides filling world map by country from real data.

Time-series-visualizer Time series visualizer is a flexible extension that provides filling world map by country from csv or json file. You can know d

Long Ng 3 Jul 09, 2021
An easy to use burndown chart generator for GitHub Project Boards.

Burndown Chart for GitHub Projects An easy to use burndown chart generator for GitHub Project Boards. Table of Contents Features Installation Assumpti

Joseph Hale 15 Dec 28, 2022
These data visualizations were created as homework for my CS40 class. I hope you enjoy!

Data Visualizations These data visualizations were created as homework for my CS40 class. I hope you enjoy! Nobel Laureates by their Country of Birth

9 Sep 02, 2022
Generate graphs with NetworkX, natively visualize with D3.js and pywebview

webview_d3 This is some PoC code to render graphs created with NetworkX natively using D3.js and pywebview. The main benifit of this approac

byt3bl33d3r 68 Aug 18, 2022
The repository is my code for various types of data visualization cases based on the Matplotlib library.

ScienceGallery The repository is my code for various types of data visualization cases based on the Matplotlib library. It summarizes the code and cas

Warrick Xu 2 Apr 20, 2022
A grammar of graphics for Python

plotnine Latest Release License DOI Build Status Coverage Documentation plotnine is an implementation of a grammar of graphics in Python, it is based

Hassan Kibirige 3.3k Jan 01, 2023
Use Perspective to create the chart for the trader’s dashboard

Task Overview | Installation Instructions | Link to Module 3 Introduction Experience Technology at JP Morgan Chase Try out what real work is like in t

Abdulazeez Jimoh 1 Jan 22, 2022
Visualizations of some specific solutions of different differential equations.

Diff_sims Visualizations of some specific solutions of different differential equations. Heat Equation in 1 Dimension (A very beautiful and elegant ex

2 Jan 13, 2022
kyle's vision of how datadog's python client should look

kyle's datadog python vision/proposal not for production use See examples/comprehensive.py for a mostly working example of the proposed API. 📈 🐶 ❤️

Kyle Verhoog 2 Nov 21, 2021
A customized interface for single cell track visualisation based on pcnaDeep and napari.

pcnaDeep-napari A customized interface for single cell track visualisation based on pcnaDeep and napari. 👀 Under construction You can get test image

ChanLab 2 Nov 07, 2021