.py scripts for data fixes. As of 05.14.14 contents include:
(1) clean_numbers.py: script that looks at numeric data--in my case--currency, and removes characters that are not part of an integer or a float. Additionally, I round the float numbers.
(2) fillblanks.py: script that runs a for loop that fills blank fields in a row with the last row's value. in this instance, I am filling rows with last row information.
(3) skipblanks.py: script that says if value in field of spreadsheet/csv is blank, skip and only write fields with content into new file.
(4) tranpose_all.py: script that uses the iterator module to do a souped up version of zip (izip) that will transpose all rows of data into "columns" in your new file. I put "columns" in quotes b/c python doesn't natively read columns--what we're doing here is reorganizing values w/i a matrix essentially.
(5) transpose_some.py: script that parses specified x rows of data (not all) into x columns (each specification = 1 column) and in this instance, also fills additional corresponding columns with specified data.
(6) unique_keys.py: script used to identify institutions with consecutive years of data, as the goal of this script was to identify which groups could be backfilled with the more recent year of information.