Allow user to filter which features to encode for OneHotEncoder

[angela97lin]

Closes #1237.

I chose to raise a ValueError if any column in features_to_encode does not exist in the input DataFrame.

[codecov]

Codecov Report

Merging #1249 into main will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##             main    #1249   +/-   ##
=======================================
  Coverage   99.93%   99.93%           
=======================================
  Files         207      207           
  Lines       12997    13031   +34     
=======================================
+ Hits        12988    13022   +34     
  Misses          9        9           

Impacted Files	Coverage Δ
evalml/tests/component_tests/test_components.py	100.00% <ø> (ø)
evalml/tests/pipeline_tests/test_pipelines.py	100.00% <ø> (ø)
...components/transformers/encoders/onehot_encoder.py	100.00% <100.00%> (ø)
...alml/tests/component_tests/test_one_hot_encoder.py	100.00% <100.00%> (ø)

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[freddyaboulton]

@angela97lin I think this is great! Right now, we fit and transform on different columns which can cause bugs. I'm a fan of letting users fit/transform on the columns they pass in as features_to_encode to get around this but open to other solutions.

[freddyaboulton]

@angela97lin Thanks this looks great!