ray.data.preprocessors.LabelEncoder#

class ray.data.preprocessors.LabelEncoder(label_column: str)[source]#

Bases: ray.data.preprocessor.Preprocessor

Encode labels as integer targets.

LabelEncoder encodes labels as integer targets that range from \(0\) to \(n - 1\), where \(n\) is the number of unique labels.

If you transform a label that isn’t in the fitted datset, then the label is encoded as float("nan").

Examples

>>> import pandas as pd
>>> import ray
>>> df = pd.DataFrame({
...     "sepal_width": [5.1, 7, 4.9, 6.2],
...     "sepal_height": [3.5, 3.2, 3, 3.4],
...     "species": ["setosa", "versicolor", "setosa", "virginica"]
... })
>>> ds = ray.data.from_pandas(df)  
>>>
>>> from ray.data.preprocessors import LabelEncoder
>>> encoder = LabelEncoder(label_column="species")
>>> encoder.fit_transform(ds).to_pandas()  
   sepal_width  sepal_height  species
0          5.1           3.5        0
1          7.0           3.2        1
2          4.9           3.0        0
3          6.2           3.4        2

If you transform a label not present in the original dataset, then the new label is encoded as float("nan").

>>> df = pd.DataFrame({
...     "sepal_width": [4.2],
...     "sepal_height": [2.7],
...     "species": ["bracteata"]
... })
>>> ds = ray.data.from_pandas(df)  
>>> encoder.transform(ds).to_pandas()  
   sepal_width  sepal_height  species
0          4.2           2.7      NaN

Parameters: label_column – A column containing labels that you want to encode.

Ray 2.3.0

ray.data.preprocessors.LabelEncoder

ray.data.preprocessors.LabelEncoder#