Packages

c

org.apache.spark.sql

DataFrameNaFunctions

final class DataFrameNaFunctions extends sql.api.DataFrameNaFunctions

Functionality for working with missing data in DataFrames.

Annotations
@Stable()
Since

1.3.1

Linear Supertypes
api.DataFrameNaFunctions, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. DataFrameNaFunctions
  2. DataFrameNaFunctions
  3. AnyRef
  4. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. Protected

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##: Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
  6. def drop(minNonNulls: Int, cols: Seq[String]): DataFrame

    (Scala-specific) Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values in the specified columns.

    (Scala-specific) Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values in the specified columns.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  7. def drop(minNonNulls: Int): DataFrame

    Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values.

    Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  8. def drop(how: String, cols: Seq[String]): DataFrame

    (Scala-specific) Returns a new DataFrame that drops rows containing null or NaN values in the specified columns.

    (Scala-specific) Returns a new DataFrame that drops rows containing null or NaN values in the specified columns.

    If how is "any", then drop rows containing any null or NaN values in the specified columns. If how is "all", then drop rows only if every specified column is null or NaN for that row.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  9. def drop(how: String): DataFrame

    Returns a new DataFrame that drops rows containing null or NaN values.

    Returns a new DataFrame that drops rows containing null or NaN values.

    If how is "any", then drop rows containing any null or NaN values. If how is "all", then drop rows only if every column is null or NaN for that row.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  10. def drop(minNonNulls: Int, cols: Array[String]): DataFrame

    Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values in the specified columns.

    Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values in the specified columns.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  11. def drop(how: String, cols: Array[String]): DataFrame

    Returns a new DataFrame that drops rows containing null or NaN values in the specified columns.

    Returns a new DataFrame that drops rows containing null or NaN values in the specified columns.

    If how is "any", then drop rows containing any null or NaN values in the specified columns. If how is "all", then drop rows only if every specified column is null or NaN for that row.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  12. def drop(cols: Seq[String]): DataFrame

    (Scala-specific) Returns a new DataFrame that drops rows containing any null or NaN values in the specified columns.

    (Scala-specific) Returns a new DataFrame that drops rows containing any null or NaN values in the specified columns.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  13. def drop(cols: Array[String]): DataFrame

    Returns a new DataFrame that drops rows containing any null or NaN values in the specified columns.

    Returns a new DataFrame that drops rows containing any null or NaN values in the specified columns.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  14. def drop(): DataFrame

    Returns a new DataFrame that drops rows containing any null or NaN values.

    Returns a new DataFrame that drops rows containing any null or NaN values.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  15. def drop(minNonNulls: Option[Int], cols: Seq[String]): Dataset[Row]
    Attributes
    protected
    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  16. def drop(minNonNulls: Option[Int]): Dataset[Row]
    Attributes
    protected
    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  17. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  19. def fill(valueMap: Map[String, Any]): DataFrame

    (Scala-specific) Returns a new DataFrame that replaces null values.

    (Scala-specific) Returns a new DataFrame that replaces null values.

    The key of the map is the column name, and the value of the map is the replacement value. The value must be of the following type: Int, Long, Float, Double, String, Boolean. Replacement values are cast to the column data type.

    For example, the following replaces null values in column "A" with string "unknown", and null values in column "B" with numeric value 1.0.

    df.na.fill(Map(
  "A" -> "unknown",
  "B" -> 1.0
))
    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  20. def fill(valueMap: Map[String, Any]): DataFrame

    Returns a new DataFrame that replaces null values.

    Returns a new DataFrame that replaces null values.

    The key of the map is the column name, and the value of the map is the replacement value. The value must be of the following type: Integer, Long, Float, Double, String, Boolean. Replacement values are cast to the column data type.

    For example, the following replaces null values in column "A" with string "unknown", and null values in column "B" with numeric value 1.0.

    import com.google.common.collect.ImmutableMap;
df.na.fill(ImmutableMap.of("A", "unknown", "B", 1.0));
    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  21. def fill(value: Boolean, cols: Array[String]): DataFrame

    Returns a new DataFrame that replaces null values in specified boolean columns.

    Returns a new DataFrame that replaces null values in specified boolean columns. If a specified column is not a boolean column, it is ignored.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  22. def fill(value: String, cols: Array[String]): DataFrame

    Returns a new DataFrame that replaces null values in specified string columns.

    Returns a new DataFrame that replaces null values in specified string columns. If a specified column is not a string column, it is ignored.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  23. def fill(value: Double, cols: Array[String]): DataFrame

    Returns a new DataFrame that replaces null or NaN values in specified numeric columns.

    Returns a new DataFrame that replaces null or NaN values in specified numeric columns. If a specified column is not a numeric column, it is ignored.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  24. def fill(value: Long, cols: Array[String]): DataFrame

    Returns a new DataFrame that replaces null or NaN values in specified numeric columns.

    Returns a new DataFrame that replaces null or NaN values in specified numeric columns. If a specified column is not a numeric column, it is ignored.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  25. def fill(value: Boolean, cols: Seq[String]): DataFrame

    (Scala-specific) Returns a new DataFrame that replaces null values in specified boolean columns.

    (Scala-specific) Returns a new DataFrame that replaces null values in specified boolean columns. If a specified column is not a boolean column, it is ignored.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  26. def fill(value: Boolean): DataFrame

    Returns a new DataFrame that replaces null values in boolean columns with value.

    Returns a new DataFrame that replaces null values in boolean columns with value.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  27. def fill(value: String, cols: Seq[String]): DataFrame

    (Scala-specific) Returns a new DataFrame that replaces null values in specified string columns.

    (Scala-specific) Returns a new DataFrame that replaces null values in specified string columns. If a specified column is not a string column, it is ignored.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  28. def fill(value: Double, cols: Seq[String]): DataFrame

    (Scala-specific) Returns a new DataFrame that replaces null or NaN values in specified numeric columns.

    (Scala-specific) Returns a new DataFrame that replaces null or NaN values in specified numeric columns. If a specified column is not a numeric column, it is ignored.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  29. def fill(value: Long, cols: Seq[String]): DataFrame

    (Scala-specific) Returns a new DataFrame that replaces null or NaN values in specified numeric columns.

    (Scala-specific) Returns a new DataFrame that replaces null or NaN values in specified numeric columns. If a specified column is not a numeric column, it is ignored.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  30. def fill(value: String): DataFrame

    Returns a new DataFrame that replaces null values in string columns with value.

    Returns a new DataFrame that replaces null values in string columns with value.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  31. def fill(value: Double): DataFrame

    Returns a new DataFrame that replaces null or NaN values in numeric columns with value.

    Returns a new DataFrame that replaces null or NaN values in numeric columns with value.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  32. def fill(value: Long): DataFrame

    Returns a new DataFrame that replaces null or NaN values in numeric columns with value.

    Returns a new DataFrame that replaces null or NaN values in numeric columns with value.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  33. def fillMap(values: Seq[(String, Any)]): DataFrame
    Attributes
    protected
    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  34. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @IntrinsicCandidate() @native()
  35. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @IntrinsicCandidate() @native()
  36. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  37. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  38. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @IntrinsicCandidate() @native()
  39. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @IntrinsicCandidate() @native()
  40. def replace[T](cols: Array[String], replacement: Map[T, T]): DataFrame

    Replaces values matching keys in replacement map with the corresponding values.

    Replaces values matching keys in replacement map with the corresponding values.

    import com.google.common.collect.ImmutableMap;

// Replaces all occurrences of 1.0 with 2.0 in column "height" and "weight".
df.na.replace(new String[] {"height", "weight"}, ImmutableMap.of(1.0, 2.0));

// Replaces all occurrences of "UNKNOWN" with "unnamed" in column "firstname" and "lastname".
df.na.replace(new String[] {"firstname", "lastname"}, ImmutableMap.of("UNKNOWN", "unnamed"));
    cols

    list of columns to apply the value replacement. If col is "*", replacement is applied on all string, numeric or boolean columns.

    replacement

    value replacement map. Key and value of replacement map must have the same type, and can only be doubles, strings or booleans. The map value can have nulls.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  41. def replace[T](col: String, replacement: Map[T, T]): DataFrame

    Replaces values matching keys in replacement map with the corresponding values.

    Replaces values matching keys in replacement map with the corresponding values.

    import com.google.common.collect.ImmutableMap;

// Replaces all occurrences of 1.0 with 2.0 in column "height".
df.na.replace("height", ImmutableMap.of(1.0, 2.0));

// Replaces all occurrences of "UNKNOWN" with "unnamed" in column "name".
df.na.replace("name", ImmutableMap.of("UNKNOWN", "unnamed"));

// Replaces all occurrences of "UNKNOWN" with "unnamed" in all string columns.
df.na.replace("*", ImmutableMap.of("UNKNOWN", "unnamed"));
    col

    name of the column to apply the value replacement. If col is "*", replacement is applied on all string, numeric or boolean columns.

    replacement

    value replacement map. Key and value of replacement map must have the same type, and can only be doubles, strings or booleans. The map value can have nulls.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  42. def replace[T](cols: Seq[String], replacement: Map[T, T]): DataFrame

    (Scala-specific) Replaces values matching keys in replacement map.

    (Scala-specific) Replaces values matching keys in replacement map.

    // Replaces all occurrences of 1.0 with 2.0 in column "height" and "weight".
df.na.replace("height" :: "weight" :: Nil, Map(1.0 -> 2.0));

// Replaces all occurrences of "UNKNOWN" with "unnamed" in column "firstname" and "lastname".
df.na.replace("firstname" :: "lastname" :: Nil, Map("UNKNOWN" -> "unnamed"));
    cols

    list of columns to apply the value replacement. If col is "*", replacement is applied on all string, numeric or boolean columns.

    replacement

    value replacement map. Key and value of replacement map must have the same type, and can only be doubles, strings or booleans. The map value can have nulls.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  43. def replace[T](col: String, replacement: Map[T, T]): DataFrame

    (Scala-specific) Replaces values matching keys in replacement map.

    (Scala-specific) Replaces values matching keys in replacement map.

    // Replaces all occurrences of 1.0 with 2.0 in column "height".
df.na.replace("height", Map(1.0 -> 2.0));

// Replaces all occurrences of "UNKNOWN" with "unnamed" in column "name".
df.na.replace("name", Map("UNKNOWN" -> "unnamed"));

// Replaces all occurrences of "UNKNOWN" with "unnamed" in all string columns.
df.na.replace("*", Map("UNKNOWN" -> "unnamed"));
    col

    name of the column to apply the value replacement. If col is "*", replacement is applied on all string, numeric or boolean columns.

    replacement

    value replacement map. Key and value of replacement map must have the same type, and can only be doubles, strings or booleans. The map value can have nulls.

    Definition Classes
    DataFrameNaFunctions → DataFrameNaFunctions
  44. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  45. def toString(): String
    Definition Classes
    AnyRef → Any
  46. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  47. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  48. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable]) @Deprecated
    Deprecated

    (Since version 9)

Inherited from api.DataFrameNaFunctions

Inherited from AnyRef

Inherited from Any

Ungrouped