Miscellaneaous
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Resources
Python
I can not recommend enough using Python for econometrics/statistics/data manipulation and data visualization. I have been a huge R fan for many years - and I still like it - but I prefer Python for most of my daily tasks.
A very easy way to use Python for scientific applications is to download the Anaconda distribution (admin rights are not necessary). Anaconda is a completely free Python distribution (including for commercial use and redistribution). It includes more than 400 of the most popular Python packages for science, math, engineering, and data analysis: link
Please find some helpful resources below. I strongly recommend the Introduction to Python for Econometrics, Statistics and Data Analysis written by Kevin Sheppard, from the University of Oxford.
Introduction to Python for Econometrics, Statistics and Data Analysis, by Kevin Sheppard, University of Oxford: link
You can find on my Github repo a list of Python tricks that I have gathered across time link
Quantitative Economics (Thomas Sargent and John Stachurski) uses Python and Julia to develop some economics applications: link. They have very nice jupyter notebooks as well ! (link)
The Harvard School of Engineering and Applied Sciences has comprehensive slides, videos and tutorials on how to use Python: link
A beginner-oriented website to learn how to use Python in a professional environment: Automate the Boring Stuff with Python: link
Python for Economists, by Alex Bell, Brown University: link
Numpy and Scipy are among the most useful packages for scientific applications with Python. A gentle introduction is provided by John Stachurski here
Pandas is probably the most important Python package for manipulating datasets and vizualise them: link I like using HDF5 for storing large datasets and manipulate them easily. It is much faster than SQL for numerical data and integrates seamlessly with Pandas: link
Emacs
Windows and Mac users can install the modified Emacs version by Vincent Goulet, which incorporates most of the packages useful for econometrics (ESS : R/Stata, etc.) and LateX (AucteX): link
My dot emacs file (.emacs) is available here.
You need to install wmctrl, aspell, flyspell, browse-killring, isend-mode and framemove using the Alt + X package-install command. Note that my dotemacs focuses on the programs I use the most, e.g. orgmode, Python, LateX and R. In particular, I emulate the matlab cell behaviour for Python using the #%% delimiter. I also emulate the darkroom mode (no distraction mode), see the file for more details