String Indexer Transform

StringIndexer encodes a string column of labels to a column of label indices

Input

It takes in a DataFrame and transforms it to another DataFrame

Output

It adds a new column containing the encoding of the string column of labels to a column of label indices, to the incoming DataFrame.

Type

ml-predict

Class

fire.nodes.etl.NodeStringIndexerTransform

Fields

Details

String Indexer Transform Node Details

The String Indexer Transform Node is used to encode a string column of labels to a column of label indices. It takes in an input DataFrame and transforms it to another DataFrame. It also takes in a fit model as input, which is typically the output of a previous String Indexer Estimator Node.

The transformed DataFrame contains a new column with the encoded label indices.

Input Parameters

FIT MODEL : The output of a previous String Indexer Estimator Node, which contains the information about the encoding of the labels.

Examples

String Indexer Transform Node Example

Consider the following example, where we have a DataFrame with a column ‘gender’ containing string values. We use a String Indexer Estimator Node to encode the string values to label indices, creating a fit model. Then, we use the String Indexer Transform Node to encode the ‘gender’ column using the fit model.

Input DataFrame:

id gender

1 male

2 female

3 male

4 female

Output

id gender gender_encoded

1 male 1

2 female 0

3 male 1

4 female 0

In this example, the input column is ‘gender’ and the output column is ‘gender_encoded’. The fit model is created using the String Indexer Estimator Node. The String Indexer Transform Node uses this fit model to encode the ‘gender’ column, creating a new column ‘gender_encoded’ with the encoded label indices.