Data wrangling
with Python / Numpy
http://slides.com/dansandiford/deck-4
What is Python?
Python is a simple general-purpose programming language. Python is not tied to a specific task or discipline, but is widely used for processing and analysing text, numbers, images, building websites and applications, and increasingly in machine learning and data science.
http://slides.com/dansandiford/deck-4
What i Do with Python...
http://slides.com/dansandiford/deck-4
http://www.underworldcode.org/pages/Blog/
Learning objectives.
In this chapter we're going to look a Python library called Numpy (numeric Python).
A library is group of tools (code) designed to assist a common purpose, yet outside the core capabilities of the Langauge.
Numpy provides the ability to work with structured groups of numbers (arrays).
http://slides.com/dansandiford/deck-4
Learning objectives.
By the end of this chapter you will learn:
- How to import, wrangle, and query structured, numeric data, using Python/Numpy.
- The flavour of using Python/Numpy for a data science workflow.
This tutorial should be challenging, particularly if you haven't seen a programming language before.
http://slides.com/dansandiford/deck-4
Learning (non ) objectives.
This tutorial should be challenging, particularly if you haven't seen a programming language before.
There are a number of core concepts that I will rush over including:
- types
- variables
- functions
Come back at 4:00 pm Tuesday or 3:30 Wednesday for ToolHack, where we'll discuss these concepts in more detail
http://slides.com/dansandiford/deck-4
A problem
Our example looks at a real (data) science problem. In fact, we are going to try to falsify a hypothesis. We'll try to show that there are predictable patterns in day-to-day stockmarket data, a discovery which would contradict the efficient market hypothesis
...given a time series, we want to find out how often the change between any two data points is the same as the change between the previous two data points
http://slides.com/dansandiford/deck-4
Your Turn!
Now we're going to try this together. Start a Jupyter session on the Cloud by going to the website:
https://tinyurl.com/h3td8qn
Once a notebook session has started, go to the 'new' dropdown and start a new terminal. Type in or paste:
git clone https://github.com/dansand/ResChapterBinder.git
option b
Start a Jupyter session by going to the website:
https://tmp60.tmpnb.org
Download and unzip the following repository (click clone or download):
https://github.com/dansand/ResChapterBinder.git
In your tmpnb notebook, click upload and upload the following files from the repo. you just downloaded:
index.ipynb
nasdaq.txt
Come and Talk Python / Jupyter
Python tutorials:
https://dansand.gitbooks.io/resguides-research-with-jupyter/content/
https://software-carpentry.org/lessons/
a byte of Python: https://python.swaroopch.com/
https://github.com/dansand/ResChapter/blob/master/content/numpy.md
Python communities:
Unimelb facebook group: research with jupyter
www.pyladies.com/ http://jupyter.org/
https://www.scipy.org/ pydata.org/
https://djangogirls.org/