Changes

*Eventbrite event objects in json are well-organized and consistent. There are many interesting fields such as the longitude/latitude decimals, apart from name/location/organizer/start-time/end-time data which are data we want to amass initially.

**For instance, the upcoming startup weekend event in Seville looks like the following.

**In the events object, organizer and venue are represented as ID's and have to be queried separately since they contain a multitude of string-value pairs such as "description", "logo", and "url" in the case of organizer data. Huge opportunity here for more data extraction. Kudos to eventbrite for documenting their stuff meticulously. Can you tell I'm impressed?

**To produce a local database, I'm using the <code>import pandas as pd</code> library, the <code>pandas.DataFrame</code> object and the <code>pandas.DataFrame.to_csv()</code> method. Currently, I initialize a dataframe with columns of variables that I seek to extract, and iterate through event objects and venue/organizer objects within to populate the dataframe with rows of event data.

**'''Still debugging/writing at the moment'''.

**RDP went down, major sadness.