History

0.2.0 (2019-01-06)

First usable version of the package. We decided on the api:

• pipeasy_spark.build_pipeline(column_transformers={'column': []}) is the core function where you can define a list of transormers for each columns.
• pipeasy_spark.build_pipeline_by_dtypes(df, string_transformers=[]) allows you to define a list of transormers for two types of columns: string_ and numeric_.
• pipeasy_spark.build_default_pipeline(df, exclude_columns=['target']) builds a default transformer for the df dataframe.

0.1.2 (2018-10-12)

• I am still learning how all these tools interact with each other

0.1.1 (2018-10-12)

• First release on PyPI.