Python data useful references

The IPython Notebook

IPython notebook home [1], [2] and examples [3]. Video tutorial at PyCon 2014 by Fernando Perez: [4], Video tutorial at PyCon 2015 (skip to 5:44 for the beginning of the talk): [5].

The easiest way to install IPython (with all dependencies) is to install Anaconda Python distribution (no registration) [6]. Python 3 is recommended.

Beyond Python: Open source, interactive data science and scientific computing across over 40 programming languages [7], [8].

Pandas

Minimal set of essential tutorials on Pandas [9], [10], [11], [12].

Python data

PyData repositories [13].

• pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
• pydata-book - Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
• pandas-datareader
• conf_site - conf.pydata.org
• patsy - Describing statistical models in Python using symbolic formulas
• numexpr - Fast numerical array expression evaluator for Python, NumPy, PyTables, pandas, bcolz and more
• pandas-website - Front page website for the pandas project
• vbench: A tool for benchmarking your code through time, for showing performance improvement or regressions
• symposion - forked from pinax/symposion - a Django project for conference websites
• pyrallel - Experimental parallel data analysis toolkit.
• PyDataNYC2013 - wiki for the PyData NYC 2013 conference
• compilers-webpage - Webpage source for compilers-webpage
• pandasjson
• pydatanyc2012 - Code, Examples, Wiki for PyData NYC 2012 conference
• notebooks - Place to contribute PyData-related IPython HTML notebooks
• pydata2012 - Materials related to the PyData workshop / PyCon 2012 tutorials
• scikits.timeseries-sandbox: forked from pierregm/scikits.timeseries-sandbox - A library to handle time series in NumPy/SciPy

 

References

1. The IPython Notebook
2. The IPython Notebook Documentation
3. A gallery of interesting IPython Notebooks
4. Fernando Perez, IPython in depth: high productivity interactive and parallel python - PyCon 2014
5. Thomas Kluyver, Kyle Kelley, IPython & Jupyter in depth: high productivity interactive and parallel python - PyCon 2015
6. Anaconda Python distribution
7. Jupyter Notebook
8. Try Jupyter
9. Alfred Essa, pandas cookbook
10. Brandon Rhodes, Pandas From The Ground Up - PyCon 2015 (Video)
11. Brandon Rhodes, Pandas From The Ground Up - PyCon 2015 (Code - GitHub)
12. Wes McKinney, Data analysis in Python with pandas - PyCon 2012 (Video)
13. Python for Data