Major Features and Improvements
* Add support for computing statistics over slices of data.
* Performance improvement due to optimizing inner loops.
* Add support for generating statistics from a pandas dataframe.
* Performance improvement due to pre-allocating tf.Example in
TFExampleDecoder.
* Performance improvement due to merging common stats generator, numeric stats
generator and string stats generator as a single basic stats generator.
* Performance improvement due to merging top-k and uniques generators.
* Add a `validate_instance` function, which checks a single example for
anomalies.
* Add a utility method `get_statistics_html`, which returns HTML that can be
used for Facets visualization outside of a notebook.
* Add support for schema inference of semantic domains.
* Performance improvement on statistics computation over a pandas dataframe.
Bug Fixes and Other Changes
* Use constant '__BYTES_VALUE__' in the statistics proto to represent a bytes
value which cannot be decoded as a utf-8 string.
* Introduced CombinerFeatureStatsGenerator, a specialized interface for
combiners that do not require cross-feature computations.
* Expand unit test coverage.
* Add optional frequency threshold that allows keeping only the most frequent
values that are present in a minimum number of examples.
* Add optional desired batch size that allows specification of the number of
examples to include in each batch.
* Depends on `numpy>=1.14.5,<2`.
* Depends on `protobuf>=3.6.1,<4`.
* Depends on `apache-beam[gcp]>=2.10,<3`.
* Depends on `tensorflow-metadata>=0.12.1,<0.13`.
* Depends on `scikit-learn>=0.18,<1`.
* Depends on `IPython>=5.0`.
* Requires pre-installed `tensorflow>=1.12,<2`.
* Revise example notebook and update it to be able to run in Colab and Jupyter.
Breaking changes
* Represent batch as a list of ndarrays instead of ndarrays of ndarrays.
* Modify decoders to return ndarrays of type numpy.float32 for FLOAT features.
Deprecations