I'm targeting an experience level somewhere between novice and intermediate. Hopefully you're familiar with the IPython notebook, and have heard of pandas. If not, don't worry. The first two notebooks (~20 minutes) are for people who may be entirely new to NumPy and pandas.
If you're more experienced, the first 30-40 minutes of the talk will likely be a review for you. After that we'll get into some more advanced topics.
First clone this repository
git clone https://github.com/tomaugspurger/pydataseattle
cd pydataseattle
- git for windows
brew install git
on mac with homebrew
If that fails, try the zip.
It will probably be best to do a git pull
just before the tutorial starts.
Make sure that you're in the pydataseattle
folder.
With conda:
conda update --all
conda env create -f environment.yml
source activate sea # or activate sea on Windows
pip install beautifulsoup4
pip install simplejson
pip install vincent
With pip / virtualenv:
$ [sudo] pip install virtualenv # try without sudo first
$ virtualenv --python=`which python3` sea
$ source sea/bin/activate
$ pip install -U pip
$ pip install -r requirements.txt
Verify your installation with
python check_environment.py
I have no idea if this is useful, but we have a chat room for the tutorial. If you have them, you can log in with your GitHub credentials.
Speak up in there with installation problems / questions / random gifs if you find that more convenient.
- [Basics](notebooks/1. Basics.ipynb)
- [Operations](notebooks/2. Operations.ipynb)
- [Indexing](notebooks/3. Indexing.ipynb)
- [Groupby](notebooks/4. Groupby.ipynb)
- [Tidy Data](5. Tidy Data.ipynb)
- [For Stats & ML](6. For Stats & ML.ipynb)