Skip to content

SimpleImputer

Replace missing values with the given strategy.

Parent type: TableTransformer

Parameters:

Name Type Description Default
strategy Strategy The strategy used to impute missing values. -
selector union<List<String>, String?> The list of columns used to fit the transformer. If None, all columns are used. null
valueToReplace union<Float, String?> The value that should be replaced. null

Examples:

pipeline example {
   val table = Table({"a": [1, null], "b": [3, 4]});
   val imputer = SimpleImputer(SimpleImputer.Strategy.Mean, selector = "a").fit(table);
   val transformedTable = imputer.transform(table);
   // Table({"a": [1, 1], "b": [3, 4]})
}

pipeline example {
   val table = Table({"a": [1, null], "b": [3, 4]});
   val imputer = SimpleImputer(SimpleImputer.Strategy.Constant(0), selector = "a").fit(table);
   val transformedTable = imputer.transform(table);
   // Table({"a": [1, 0], "b": [3, 4]})
}

Stub code in SimpleImputer.sdsstub 

 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
class SimpleImputer(
    strategy: SimpleImputer.Strategy,
    selector: union<List<String>, String, Nothing?> = null,
    @PythonName("value_to_replace") valueToReplace: union<Float, String, Nothing?> = null
) sub TableTransformer {
    /**
     * Various strategies to replace missing values.
     */
    enum Strategy {
        /**
         * Replace missing values with the given constant value.
         *
         * @param value The value to replace missing values.
         */
        @PythonName("constant")
        Constant(value: Any)

        /**
         * Replace missing values with the mean of each column.
         */
        @PythonName("mean")
        Mean

        /**
         * Replace missing values with the median of each column.
         */
        @PythonName("median")
        Median

        /**
         * Replace missing values with the mode of each column.
         */
        @PythonName("mode")
        Mode
    }

    /**
     * The strategy used to replace missing values.
     */
    attr strategy: SimpleImputer.Strategy
    /**
     * The value that should be replaced.
     */
    @PythonName("value_to_replace") attr valueToReplace: Any

    /**
     * Learn a transformation for a set of columns in a table.
     *
     * This transformer is not modified.
     *
     * @param table The table used to fit the transformer.
     *
     * @result fittedTransformer The fitted transformer.
     */
    @Pure
    fun fit(
        table: Table
    ) -> fittedTransformer: SimpleImputer

    /**
     * Learn a transformation for a set of columns in a table and apply the learned transformation to the same table.
     *
     * **Note:** Neither this transformer nor the given table are modified.
     *
     * @param table The table used to fit the transformer. The transformer is then applied to this table.
     *
     * @result fittedTransformer The fitted transformer.
     * @result transformedTable The transformed table.
     */
    @Pure
    @PythonName("fit_and_transform")
    fun fitAndTransform(
        table: Table
    ) -> (fittedTransformer: SimpleImputer, transformedTable: Table)
}

isFitted

Whether the transformer is fitted.

Type: Boolean

strategy

The strategy used to replace missing values.

Type: Strategy

valueToReplace

The value that should be replaced.

Type: Any

fit

Learn a transformation for a set of columns in a table.

This transformer is not modified.

Parameters:

Name Type Description Default
table Table The table used to fit the transformer. -

Results:

Name Type Description
fittedTransformer SimpleImputer The fitted transformer.
Stub code in SimpleImputer.sdsstub 

83
84
85
86
@Pure
fun fit(
    table: Table
) -> fittedTransformer: SimpleImputer

fitAndTransform

Learn a transformation for a set of columns in a table and apply the learned transformation to the same table.

Note: Neither this transformer nor the given table are modified.

Parameters:

Name Type Description Default
table Table The table used to fit the transformer. The transformer is then applied to this table. -

Results:

Name Type Description
fittedTransformer SimpleImputer The fitted transformer.
transformedTable Table The transformed table.
Stub code in SimpleImputer.sdsstub 

 98
 99
100
101
102
@Pure
@PythonName("fit_and_transform")
fun fitAndTransform(
    table: Table
) -> (fittedTransformer: SimpleImputer, transformedTable: Table)

transform

Apply the learned transformation to a table.

Note: The given table is not modified.

Parameters:

Name Type Description Default
table Table The table to which the learned transformation is applied. -

Results:

Name Type Description
transformedTable Table The transformed table.
Stub code in TableTransformer.sdsstub 

37
38
39
40
@Pure
fun transform(
    table: Table
) -> transformedTable: Table

Strategy

Various strategies to replace missing values.

Stub code in SimpleImputer.sdsstub 

37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
enum Strategy {
    /**
     * Replace missing values with the given constant value.
     *
     * @param value The value to replace missing values.
     */
    @PythonName("constant")
    Constant(value: Any)

    /**
     * Replace missing values with the mean of each column.
     */
    @PythonName("mean")
    Mean

    /**
     * Replace missing values with the median of each column.
     */
    @PythonName("median")
    Median

    /**
     * Replace missing values with the mode of each column.
     */
    @PythonName("mode")
    Mode
}

Constant

Replace missing values with the given constant value.

Parameters:

Name Type Description Default
value Any The value to replace missing values. -

Mean

Replace missing values with the mean of each column.

Median

Replace missing values with the median of each column.

Mode

Replace missing values with the mode of each column.