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Adriano rsvp.github.com edited this page Dec 31, 2015 · 8 revisions

Welcome to our wiki for financial economics!

The main repository at GitHub is called fecon235 (short address https://git.io/fecon235) where you will find README.md for setting up the computational data tools.

The best way to first learn about our project is to pick a IPython/Jupyter notebook for a topic which interests you, and then to work interactively with it. Please checkout the nb directory.

The lib directory contains Python modules with the high-level commands used in the notebooks. If customization is required, these functions provide good templates to access the core packages such as pandas, numpy, and matplotlib.

The essential modules are unified by the top-level module called fecon235.py. Please see https://git.io/fecon-intro where details are given regarding its import. The most current user documentation can be found in the docs directory, however, the source code is thoroughly documented with comments.

Q: Are there online discussions?

Chat with fellow users at Gitter: https://gitter.im/rsvp/fecon235

Q: How do I report a bug, or suggest enhancements?

For issues, please visit https://github.com/rsvp/fecon235/issues -- but better yet please consider fixing module bugs by making a pull request https://git.io/fecon-pr

Q: How do I retrieve economic data series not listed in fecon235?

We have defined procedures to access data from the St. Louis Federal Reserve Bank. Now each economic time series and its frequency has its own "fredcode" which is freely available at their site: http://research.stlouisfed.org/fred2/ so check there first.

                   df = getfred( fredcode )
                   #             ^Favorites are named d4*, m4*, q4*.
                   #             fredcode is entered as a string.
 
                   plotfred( dataframe or fredcode )
 
                   holtfred( dataframe or fredcode )
                   #  Holt-Winters forecast.

See the yi_fred.py module for further details. Constructing your own data file is easy, see for example m4eurusd as to how a synthetic series can be created.

Revision date : 2015-12-30

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