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Showing content from https://github.com/TomAugspurger/PyDataSeattle below:

TomAugspurger/PyDataSeattle: For the pandas tutorial at PyData Seattle: https://www.youtube.com/watch?v=otCriSKVV_8

Pandas .head() to .tail()

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)

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