Learning from data

I implemented the features to find "anytime" tokens, as well as days of the week, and stored them into variables of the JSON. I wanted to handle the case of "except" seen before a day of the week, for example "... except Sunday". I noticed that almost all instances of this type were for exactly Sunday. I got the count of these words. Note, this is before normalizing abbreviations:

• sunday - 34,504
• sun - 4492
• trucks - 3931
• authorized - 2871
• school - 630
• su - 286
• commercial - 266
• vehicles - 164
• farmers - 129
• saturday - 85
• taxis - 64
• comm - 61
• miu - 29
• city - 26
• buses - 21
• pick - 20
• tlc - 18
• taxis/fhv's - 17
• loading - 16
• license - 6
• tour - 6
• m - 6
• horse - 5
• nycta - 3
• sunda - 3
• flea - 3
• greenmarket - 3
• friday - 2
• 8am-11am - 2
• n - 2
• state - 2
• mon - 2
• us - 1
• deliveries - 1
• sunady - 1

Clearly Sunday is the major day. Notice even the variations of Sunday; the multiple types of abbreviations, and the one misspelling. 

After this, I should be able to create the separate HTMLs for every time slot. Let's actually calculate how many there will be.

24 hours in a day

4 15-minute blocks per hour

24 * 4 = 96

That's not so bad.