NOTES

This set of python and bash scripts is used to put the miso data into a database.  When I started, I was just doing one year, and it now loads all the years for which I could find data.  I was initially using this to calculate bounds on the value of energy storage, but I'm sure there are a lot of interesting uses for this data, as Prof. Paul Wilson pointed out.  I'm using his example for a way to show what can be done and how to work with the database to make use of it.  I keep it simple and just use it to pull data and put into a csv file for charting purposes.  

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To use (I'm using a recent linux mint distro)
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->Get sqlite3 if you dont have

->The miso data tarball can be found at: 
https://drive.google.com/file/d/0B218a-tmzP5VUkc1QnFtQVZvRU0/edit?usp=sharing
(if this doesn't work, let me know)

->Extract in the db directory, which will create two folders, data which contains the newer files and miso which contains pre-2012 files

->Run createdb and load scripts

Example:

sudo apt-get install sqlite3
cd db
tar -xvzf data.tar.gz ./
./createdb.py
./load-miso;./load-miso2;


The other python files just give examples of how to interact with an sqlite database through python.  I normally use the commmand line version, 

Example: 

sqlite3 power.db "select * from Market where name='MGE.MGE'"
#to get all the records for MGE.MGE

sqlite3 power.db "select date,max from Stats where name='MGE.MGE'"
#to get the max price for MGE.MGE for each day

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Contact:
For help on getting this set up or feel free to let me know how you are using this
eanderson4@wisc.edu