**Output files can be found in E:\McNair\Users\GunnyLiu, with E:\ being McNair's shared bulk drive.
***Main datasheet that maps each row of @shortname to its count of followers and past month tweets is named <code>Hub_Tweet_Main_DataSheet.csv</code>
***Individual datasheets for each @shortname that maps each tweet to tweet details can be found at <code>Hub_Tweet_Main_DataSheetTwitter_Data_Where_@shortname_Tweets.csv</code>
**Code will be LIVE on <code>mcnair git</code> soon
*Output/Process Shortcoming:
**Unable to correct for timezone in calculating tweets over the past month. Needs to install <code>python 3.5.3</code>
**Unable to process data for a single @shortname i.e. @FORGEPortland becuz they don't tweet and that's annoying
===7/21: Application to Todd's Hub Project Pt. IV===
*Fix for time signatures in output
**Instead of discrete strings, we want the "Creation Time" value of tweets in the output to be in the format of MM/DD/YYYY, which supports performance on MS Excel and other GUI-based analysis environments
**Wrote new function time_signature_simplifier() and time_signature_mass_simplification()
**Functions iterate through all existing .csv tweetlogs of listed hubs @shortnames and process them in a python environment as pd.DataFrame objects
**For each date string that exists under the "Creation Time" column, function converts them to datetime.datetime objects, and overwrite using <code>.date().month</code>, <code>.date().day</code>, <code>.date().year</code> attributes of each object.
***Met problems with date strings such as "29 Feb"; datetime has compatibility issues with leap years esp. when year is defaulted to 1900. Do take note.
**test passed; new data is available, for every input @shortname <code>Twitter_Data_Where_@shortname_Tweets_v2.csv</code>