https://github.com/asimihsan/pydata-ldn2014-writeup
One-stop write up of PyData London 2014 - tutorials, slides, code, examples
https://github.com/asimihsan/pydata-ldn2014-writeup
Last synced: 4 months ago
JSON representation
One-stop write up of PyData London 2014 - tutorials, slides, code, examples
- Host: GitHub
- URL: https://github.com/asimihsan/pydata-ldn2014-writeup
- Owner: asimihsan
- License: mit
- Created: 2014-02-23T19:22:58.000Z (over 11 years ago)
- Default Branch: master
- Last Pushed: 2014-02-24T16:22:58.000Z (over 11 years ago)
- Last Synced: 2024-04-08T16:29:04.355Z (about 1 year ago)
- Language: CSS
- Size: 6.42 MB
- Stars: 11
- Watchers: 6
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# pydata-ldn2014-writeup
One-stop write up of PyData London 2014 - tutorials, slides, code,
examples.
> http://nbviewer.ipython.org/github/asimihsan/pydata-ldn2014-writeup/tree/master/
## Contents
- Introduction
- Original content
- Following along
- TODO
## Introduction
I attended [PyData London 2014](http://pydata.org/ldn2014/schedule/),
and took some notes. These notes are my own; all mistakes are my own,
missing content is usually because I couldn't keep up, additional
content is to help give myself context as I look over the material
again.
## Original content
Some of the IPython Notebooks in this repo are original content of
their authors. They usually read "presenter notes". However in the
first instance please visit the PyData London 2014 website to
refer to original content and, even better, video recordings.
## Following along
- A static view of all IPython Notebook are viewable via the official
online nbviewer instance:
> http://nbviewer.ipython.org/github/asimihsan/pydata-ldn2014-writeup/tree/master/
- Please initialize a new virtualenv - there are a lot of dependencies,
they probably won't just work.
- Try `pip install -r requirements.txt`, but I haven't tested it. Use
your judgement overcoming errors. Try `pip install $MISSING_MODULE`
on failure. See if you're missing OS-level dependencies for given
modules.
## TODO
- Review all notes for accuracy, use audio recordings to improve
legibility and fill in gaps.
- Add examples or notes-to-self in the "00" notebook, to give myself
toy examples to understand the presentation material.
- Go through "03 - Faster Python Programs Through Optimization"
handout and turn (most of) it into an IPython Notebook.
- Complete all examples in the "04 - Visualisations Using Bokeh"
tutorial and compile everything into a single gigantic IPython
Notebook.
- Go through "05 - Databases for Scientists" and re-apply to
(small) Stackexchange dataset and make sure I understand it.
- Go through "10 - The High Performance Python Landscape" and re-apply
all of it using code examples to a new and novel toy example to make
sure I understand it.
- Go through "18 - Measuring Similarity and Clustering Data" and apply
to my own toy data to make sure I understand it.