Remove IntegerNullable Logical Type and have 1 Integer Logical Type

[gsheni]

• We originally had IntegerNullable and Integer because EvalML relies on estimator/classifiers that do not support the pandas Int64 dtype (which is used in IntegerNullable)
• However, a better long term solution is for Woodwork to have 1 Integer type that supports nullable values
• For this issue

1. Remove/Deprecate IntegerNullable
2. Change the Integer physical type from int64 to Int64
3. Update inference logic to account for this change
4. Verify that Featuretools and EvalML can properly handle this change

[thehomebrewnerd]

@gsheni Also Age and AgeNullable? Or maybe that should be separate since we also have AgeFractional that could/should be cleaned up?

[gsheni]

@thehomebrewnerd yep, created: #1519