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PurePy 0. Woffle and Getting Started
PurePy 1. Numbers and Variables
PurePy 10. Object-Oriented Programming
PurePy 10.5. Object-Oriented Programming./ipynb_checkpoints
PurePy 11. Exceptions
PurePy 12. Parallel Computing
PurePy 2. Logic and Flow
PurePy 3. Importing modules
PurePy 4. Defining Our Own Functions
PurePy 5. Data Structures
PurePy 5.5 Command-line interlude
PurePy 6. Strings and Text
PurePy 7. Importing Data
PurePy 8. Advanced Flow Control
PurePy 9. Advanced Functions
[BASICS] Getting Started With Python 1 - The Basics
[BASICS] Getting Started With Python 2 - The Basics
[BASICS] Numpy and Pandas
[BASICS] Setting Up Python
[ML] Decision Trees
[ML] Introduction to Machine Learning
[ML] K Means Clustering
[ML] K Nearest Neighbours
[ML] Support Vector Machines
[SOURCING] Importing Data From Files
[SOURCING] Importing Data From The Web
[STATISTICS] ANOVA (Analysis Of Variance)
[STATISTICS] Hypothesis Testing In Python
[STATISTICS] Introduction to Statistcal Analysis
[STATISTICS] Statistical Regression
[VISUALISATION] A Deeper Look Into Matplotlib
[VISUALISATION] Interactive Plots With Bokeh
[VISUALISATION] Panda's Built In Vis
[VISUALISATION] Statistical Plotting With Seaborn
__pycache__
docs
my-folder
web
CNAME
Machine Learning Helper Notebook.ipynb
README.md
Using Python, and your environment.ipynb
data-structures.py
data-structures1.py
fizzbuzz.aux
fizzbuzz.log
fizzbuzz.pdf
fizzbuzz.py
fizzbuzz.synctex.gz
fizzbuzz.tex
fizzcopy
header.png
polynomial.py
pwd.py
strings.py
table.py
test.py

README.md

HiPy learning resources

Created by Sam Ball and Sam Cassidy

Two collections

We have two series of resources here: Python, Data, and You; and PurePy. Absolute beginners should start with either the [BASICS] section of PD&Y if you want to fast-track to data-driven applications, or from the beginning of PurePy if you're more interested in general programming concepts. Both series combine written resources, worked example videos, and a sprinkling of exercises and challenges.

Although github has a Jupyter notebook viewer, it's not great. They are not interactive. Moreover, the YouTube videos don't display, similarly some of the text formatting doesn't quite work. We recommend downloading this github repo using the button at the top right and viewing them in Juypter Notebook (installed with Anaconda) locally.

Python, Data and You

Python is one of the strongest and simplest tools for data processing around today, used by thousands of people to build models and perform statistical analysis. In these guides, we will start by looking at the basic tools for data manipulation in Python, then move on to statistical analysis and building more complex models using machine learning algorithms. By the end of reading these guides, you should be comfortable learning about neural networks, natural language processing, or artificial intelligence.

PurePy

This series exposes the basic concepts of Python programming, including functions, data structures, and eventually classes, giving you the tools you need to structure larger projects, improve your coding skills, and better understand how Python works. The approach is informal, prefering intuition over technicalities. Chapter 0 includes a crash course on command-line computing, a skill that is often taken for granted in other introductory guides.

TODO

  • Video for PurePy 6 (coming this weekend)
  • Video for PurePy 11
  • Some PurePy on network and internet
  • Extend PurePy 6 to include Regular expressions
  • PurePy on utility scripting