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Installation instructions for doing data science in a Python environment on Ubuntu. We'll install base packages like numpy, scipy, scikit-learn and pandas. We also install the IPython Notebook interactive environment. This is a best practice recommendation for doing research-type work. We make use of virtualenvwrapper, but don't show how to inst…
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mkvirtualenv datascience | |
sudo apt-get install python-scipy libblas-dev liblapack-dev gfortran | |
sudo apt-get install libffi-dev # for cryptography from scrapy | |
sudo apt-get install libxslt-dev # for libxml from scrapy | |
export BLAS=/usr/lib/libblas.so | |
export LAPACK=/usr/lib/liblapack.so | |
pip install numpy | |
pip install scipy | |
pip install scikit-learn | |
pip install pandas | |
pip install patsy | |
pip install statsmodels | |
pip install ipython tornado pyzmq | |
pip install networkx | |
pip install gensim | |
pip install scrapy | |
pip install numexpr bottleneck | |
pip install sqlalchemy | |
pip install nltk | |
pip install seaborn |
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@startakovsky, both command install
scipy
but they're somewhat different. Usingsudo apt-get python-scipy
gives you the most stable version that the OS supports butpip install scipy
installs the latest version that scipy pushed in to the pypi index.