Otherwise we could create multiple instances of the twitter scraper and put each binned key-term into it's own database. Then join all the databases together into one at the end, creating a binned column name for each database to keep track of which tweet belongs to which bin.
I'll work on using the list comprehension method and see if it's feasible this afternoon.
This is the best solution I've found so far, a list comprehension: http://stackoverflow.com/questions/28658729/how-to-check-the-text-of-a-tweet-for-a-specific-keyword-from-an-array-in-python
Otherwise we could create multiple instances of the twitter scraper and put each binned key-term into it's own database. Then join all the databases together into one at the end, creating a binned column name for each database to keep track of which tweet belongs to which bin.
I'll work on using the list comprehension method and see if it's feasible this afternoon.