Add: configuration file for storing settings
Add: plot locations of geocoded tweets

Use matplotlib to produce a scatter plot of the longitude and latitude
data from a collection of tweets.

We use a configuration file to store the path and filename of the
archive containing the geocoded tweets.
Reduce size and alpha of points in scatter plot
Color each point based on latitude
Generalize data extraction from tweets function
Color each point based on created time of day
Add: color bar to describe value related to color
Make points a little less transparent
Decrease point size and surrounding line width
Add: axis title and labels
Add: grid lines for scatter plot
Use tight-layout for figure
Add: rectangle to plot showing Denton County
Enlarge figure size and DPI
Make x-axis and y-axis have an equal aspect ratio

We also set the axes boundaries to around Denton County, with some
slight padding.
Have color bar vertically align with the scatter

See:
<http://matplotlib.org/mpl_toolkits/axes_grid/users/overview.html#colorbar-whose-height-or-width-in-sync-with-the-master-axes>
Adjust the tight-layout to work well with zooming

If we try to use the tight-layout function without the extra padding,
when we zoom to a plot that is extra wide or tall then the text labels
sometimes get clipped. Therefore, the advantage to using the
tight-layout is diminished, however there is still some size gain.

See:
http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.tight_layout
Generalize making plots from extracted data

We might want to make more than a single plot from the extracted data.
Therefore, by separating the data extraction from the plot making we can
make additional plots without having to re-extract the data.
Add: time of day histogram for created-at times
Add: heat map for locations of geocoded tweets