append_rows
Add rows from one dataset to another.
I.e., vertically concatenates two datasets, appending the rows of the second to the end of the first.
When the two datasets contain different columns, the join parameter controls whether only the
common columns are kept (inner), or all columns (outer). In the latter case, rows will have missing
values (NaNs), where a column only existed in one of the two datasets.
Usage
The following example shows how the step can be used in a recipe.
To append the rows of dataset ds_right to the dataset ds_left, keeping all columns from both datasets:
Inputs & Outputs
The following are the inputs expected by the step and the outputs it produces. These are generally
columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced
by name e.g. "churn-clf").
Configuration
The following parameters can be used to configure the behaviour of the step by including them in
a json object as the last “input” to the step, i.e. step(..., {"param": "value", ...}) -> (output).
Whether to do concatenate using an “inner” or “outer” join of columns.
When "inner", only common columns will be kept. When "outer", all columns will be kept.
Values must be one of the following:
innerouter
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