StopWordsRemover¶

class pyspark.ml.feature.StopWordsRemover(*, inputCol: Optional[str] = None, outputCol: Optional[str] = None, stopWords: Optional[List[str]] = None, caseSensitive: bool = False, locale: Optional[str] = None, inputCols: Optional[List[str]] = None, outputCols: Optional[List[str]] = None)¶

A feature transformer that filters out stop words from input. Since 3.0.0, StopWordsRemover can filter out multiple columns at once by setting the inputCols parameter. Note that when both the inputCol and inputCols parameters are set, an Exception will be thrown.

Notes

null values from input array are preserved unless adding null to stopWords explicitly.

Examples

>>> df = spark.createDataFrame([(["a", "b", "c"],)], ["text"])
>>> remover = StopWordsRemover(stopWords=["b"])
>>> remover.setInputCol("text")
StopWordsRemover...
>>> remover.setOutputCol("words")
StopWordsRemover...
>>> remover.transform(df).head().words == ['a', 'c']
True
>>> stopWordsRemoverPath = temp_path + "/stopwords-remover"
>>> remover.save(stopWordsRemoverPath)
>>> loadedRemover = StopWordsRemover.load(stopWordsRemoverPath)
>>> loadedRemover.getStopWords() == remover.getStopWords()
True
>>> loadedRemover.getCaseSensitive() == remover.getCaseSensitive()
True
>>> loadedRemover.transform(df).take(1) == remover.transform(df).take(1)
True
>>> df2 = spark.createDataFrame([(["a", "b", "c"], ["a", "b"])], ["text1", "text2"])
>>> remover2 = StopWordsRemover(stopWords=["b"])
>>> remover2.setInputCols(["text1", "text2"]).setOutputCols(["words1", "words2"])
StopWordsRemover...
>>> remover2.transform(df2).show()
+---------+------+------+------+
|    text1| text2|words1|words2|
+---------+------+------+------+
|[a, b, c]|[a, b]|[a, c]|   [a]|
+---------+------+------+------+
...

Methods

`clear`(param)	Clears a param from the param map if it has been explicitly set.
`copy`([extra])	Creates a copy of this instance with the same uid and some extra params.
`explainParam`(param)	Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.
`explainParams`()	Returns the documentation of all params with their optionally default values and user-supplied values.
`extractParamMap`([extra])	Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.
`getCaseSensitive`()	Gets the value of `caseSensitive` or its default value.
`getInputCol`()	Gets the value of inputCol or its default value.
`getInputCols`()	Gets the value of inputCols or its default value.
`getLocale`()	Gets the value of `locale`.
`getOrDefault`(param)	Gets the value of a param in the user-supplied param map or its default value.
`getOutputCol`()	Gets the value of outputCol or its default value.
`getOutputCols`()	Gets the value of outputCols or its default value.
`getParam`(paramName)	Gets a param by its name.
`getStopWords`()	Gets the value of `stopWords` or its default value.
`hasDefault`(param)	Checks whether a param has a default value.
`hasParam`(paramName)	Tests whether this instance contains a param with a given (string) name.
`isDefined`(param)	Checks whether a param is explicitly set by user or has a default value.
`isSet`(param)	Checks whether a param is explicitly set by user.
`load`(path)	Reads an ML instance from the input path, a shortcut of read().load(path).
`loadDefaultStopWords`(language)	Loads the default stop words for the given language.
`read`()	Returns an MLReader instance for this class.
`save`(path)	Save this ML instance to the given path, a shortcut of ‘write().save(path)’.
`set`(param, value)	Sets a parameter in the embedded param map.
`setCaseSensitive`(value)	Sets the value of `caseSensitive`.
`setInputCol`(value)	Sets the value of `inputCol`.
`setInputCols`(value)	Sets the value of `inputCols`.
`setLocale`(value)	Sets the value of `locale`.
`setOutputCol`(value)	Sets the value of `outputCol`.
`setOutputCols`(value)	Sets the value of `outputCols`.
`setParams`(self, \*[, inputCol, outputCol, …])	Sets params for this StopWordRemover.
`setStopWords`(value)	Sets the value of `stopWords`.
`transform`(dataset[, params])	Transforms the input dataset with optional parameters.
`write`()	Returns an MLWriter instance for this ML instance.

Attributes

`caseSensitive`
`inputCol`
`inputCols`
`locale`
`outputCol`
`outputCols`
`params`	Returns all params ordered by name.
`stopWords`

Methods Documentation

clear(param: pyspark.ml.param.Param) → None¶: Clears a param from the param map if it has been explicitly set.

copy(extra: Optional[ParamMap] = None) → JP¶

Creates a copy of this instance with the same uid and some extra params. This implementation first calls Params.copy and then make a copy of the companion Java pipeline component with extra params. So both the Python wrapper and the Java pipeline component get copied.

Parameters

extradict, optional: Extra parameters to copy to the new instance

Returns

JavaParams: Copy of this instance

explainParam(param: Union[str, pyspark.ml.param.Param]) → str¶: Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.

explainParams() → str¶: Returns the documentation of all params with their optionally default values and user-supplied values.

extractParamMap(extra: Optional[ParamMap] = None) → ParamMap¶

Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.

Parameters

extradict, optional: extra param values

Returns

dict: merged param map

getCaseSensitive() → bool¶: Gets the value of caseSensitive or its default value.

getInputCol() → str¶: Gets the value of inputCol or its default value.

getInputCols() → List[str]¶: Gets the value of inputCols or its default value.

getLocale() → str¶: Gets the value of locale.

getOrDefault(param: Union[str, pyspark.ml.param.Param[T]]) → Union[Any, T]¶: Gets the value of a param in the user-supplied param map or its default value. Raises an error if neither is set.

getOutputCol() → str¶: Gets the value of outputCol or its default value.

getOutputCols() → List[str]¶: Gets the value of outputCols or its default value.

getParam(paramName: str) → pyspark.ml.param.Param ¶: Gets a param by its name.

getStopWords() → List[str]¶: Gets the value of stopWords or its default value.

hasDefault(param: Union[str, pyspark.ml.param.Param[Any]]) → bool¶: Checks whether a param has a default value.

hasParam(paramName: str) → bool¶: Tests whether this instance contains a param with a given (string) name.

isDefined(param: Union[str, pyspark.ml.param.Param[Any]]) → bool¶: Checks whether a param is explicitly set by user or has a default value.

isSet(param: Union[str, pyspark.ml.param.Param[Any]]) → bool¶: Checks whether a param is explicitly set by user.

classmethod load(path: str) → RL¶: Reads an ML instance from the input path, a shortcut of read().load(path).

static loadDefaultStopWords(language: str) → List[str]¶: Loads the default stop words for the given language. Supported languages: danish, dutch, english, finnish, french, german, hungarian, italian, norwegian, portuguese, russian, spanish, swedish, turkish

classmethod read() → pyspark.ml.util.JavaMLReader[RL]¶: Returns an MLReader instance for this class.

save(path: str) → None¶: Save this ML instance to the given path, a shortcut of ‘write().save(path)’.

set(param: pyspark.ml.param.Param, value: Any) → None¶: Sets a parameter in the embedded param map.

setCaseSensitive(value: bool) → pyspark.ml.feature.StopWordsRemover ¶: Sets the value of caseSensitive.

setInputCol(value: str) → pyspark.ml.feature.StopWordsRemover ¶: Sets the value of inputCol.

setInputCols(value: List[str]) → pyspark.ml.feature.StopWordsRemover ¶: Sets the value of inputCols.

setLocale(value: str) → pyspark.ml.feature.StopWordsRemover ¶: Sets the value of locale.

setOutputCol(value: str) → pyspark.ml.feature.StopWordsRemover ¶: Sets the value of outputCol.

setOutputCols(value: List[str]) → pyspark.ml.feature.StopWordsRemover ¶: Sets the value of outputCols.

setParams(self, \*, inputCol=None, outputCol=None, stopWords=None, caseSensitive=false, locale=None, inputCols=None, outputCols=None)¶: Sets params for this StopWordRemover.

setStopWords(value: List[str]) → pyspark.ml.feature.StopWordsRemover ¶: Sets the value of stopWords.

transform(dataset: pyspark.sql.dataframe.DataFrame, params: Optional[ParamMap] = None) → pyspark.sql.dataframe.DataFrame¶

Transforms the input dataset with optional parameters.

Parameters

datasetpyspark.sql.DataFrame: input dataset
paramsdict, optional: an optional param map that overrides embedded params.

Returns

pyspark.sql.DataFrame: transformed dataset

write() → pyspark.ml.util.JavaMLWriter¶: Returns an MLWriter instance for this ML instance.

Attributes Documentation

caseSensitive: pyspark.ml.param.Param[bool] = Param(parent='undefined', name='caseSensitive', doc='whether to do a case sensitive comparison over the stop words')¶

inputCol = Param(parent='undefined', name='inputCol', doc='input column name.')¶

inputCols = Param(parent='undefined', name='inputCols', doc='input column names.')¶

locale: pyspark.ml.param.Param[str] = Param(parent='undefined', name='locale', doc='locale of the input. ignored when case sensitive is true')¶

outputCol = Param(parent='undefined', name='outputCol', doc='output column name.')¶

outputCols = Param(parent='undefined', name='outputCols', doc='output column names.')¶

params¶: Returns all params ordered by name. The default implementation uses dir() to get all attributes of type Param.

stopWords: pyspark.ml.param.Param[List[str]] = Param(parent='undefined', name='stopWords', doc='The words to be filtered out')¶

StandardScalerModel

StringIndexer