concat

getml.data.split.concat(name: str, **kwargs: DataFrame) → Tuple[DataFrame, StringColumnView]

Concatenates several data frames into and produces a split column that keeps track of their origin.

Args:

name (str):

The name of the data frame you would like to create.

kwargs:

The data frames you would like to concat with the name in which they should appear in the split column.

Example:

A common use case for this functionality are TimeSeries:

data_train = getml.DataFrame.from_pandas(
    datatraining_pandas, name='data_train')

data_validate = getml.DataFrame.from_pandas(
    datatest_pandas, name='data_validate')

data_test = getml.DataFrame.from_pandas(
    datatest2_pandas, name='data_test')

population, split = getml.data.split.concat(
    "population", train=data_train, validate=data_validate, test=data_test)

...

time_series = getml.data.TimeSeries(
    population=population, split=split)

my_pipeline.fit(time_series.train)