Improved handling of common data types and documented supported data types

[tleonhardt]

Added special handling to generate_table() for the following data types:

• pandas DataFrame
• numpy record arrays
• dictionaries of iterables

Also:

• Added data_types.py example
• Updated README.md
• Added unit tests for supported data types

This closes #23
This closes #24

[codecov-io]

Codecov Report

Merging #25 into master will increase coverage by 0.28%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master      #25      +/-   ##
==========================================
+ Coverage   88.05%   88.33%   +0.28%     
==========================================
  Files           1        1              
  Lines         829      849      +20     
==========================================
+ Hits          730      750      +20     
  Misses         99       99

Impacted Files	Coverage Δ
tableformatter.py	88.33% <100%> (+0.28%)	⬆️

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[tleonhardt]

@anselor
I improved how tableformatter handles a couple common tabular data types, namely:

• Pandas DataFrames
• dictionaries of iterables
  These data types are now handled in a manner which should likely match the expectation of a reasonable user and is essentially identical to how tabulate handles them.

I also improved how Numpy record arrays are handled, though I believe I slightly deviated from how tabulate handles them - I did what seemed to make sense, but I have never used this data type, so I don't have a great feel for it.

The one outstanding question in my mind is should we modify how we handle iterables of dictionaries to be identical to how tabulate handles them or leave them the way we handle them now. I think this is an awkward data type regardless, but the way tabulate handles it probably makes the most sense. What do you think?

[tleonhardt]

@anselor If you don't have any feedback I'll merge this in sometime this weekend

[tleonhardt]

It may not be the perfect solution, but it is definitely an improvement and a step in the right direction, so I am going to merge it in. We can improve it further as we best see fit.