Object

org.apache.spark.sql.DataFrameNaFunctions

public abstract class DataFrameNaFunctions extends Object

Functionality for working with missing data in DataFrames.

Since:
1.3.1

  • Constructor Summary

    Constructors

  • Method Summary

    drop()

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

    drop(int minNonNulls)

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

    drop(int minNonNulls, String[] cols)

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

    drop(int minNonNulls, scala.collection.immutable.Seq<String> cols)

    (Scala-specific) 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 null or NaN values.

    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 null or NaN values in the specified columns.

    drop(String how, scala.collection.immutable.Seq<String> cols)

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

    drop(scala.collection.immutable.Seq<String> cols)

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

    fill(boolean value)

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

    fill(boolean value, String[] cols)

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

    fill(boolean value, scala.collection.immutable.Seq<String> cols)

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

    fill(double value)

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

    fill(double value, String[] cols)

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

    fill(double value, scala.collection.immutable.Seq<String> cols)

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

    fill(long value)

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

    fill(long value, String[] cols)

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

    fill(long value, scala.collection.immutable.Seq<String> cols)

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

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

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

    fill(String value, scala.collection.immutable.Seq<String> cols)

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

    Returns a new DataFrame that replaces null values.

    fill(scala.collection.immutable.Map<String,Object> valueMap)

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

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

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

    replace(String col, scala.collection.immutable.Map<T,T> replacement)

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

    replace(scala.collection.immutable.Seq<String> cols, scala.collection.immutable.Map<T,T> replacement)

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

  • Constructor Details

    • DataFrameNaFunctions

      public DataFrameNaFunctions()

  • Method Details

    • drop

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

      Returns:
      (undocumented)
      Since:
      1.3.1

    • drop

      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.

      Parameters:
      how - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • drop

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

      Parameters:
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • drop

      public Dataset<Row> drop(scala.collection.immutable.Seq<String> cols)

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

      Parameters:
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • drop

      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.

      Parameters:
      how - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • drop

      (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.

      Parameters:
      how - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • drop

      public Dataset<Row> drop(int minNonNulls)

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

      Parameters:
      minNonNulls - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • drop

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

      Parameters:
      minNonNulls - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • drop

      public Dataset<Row> drop(int minNonNulls, scala.collection.immutable.Seq<String> cols)

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

      Parameters:
      minNonNulls - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • fill

      public abstract Dataset<Row> fill(long value)

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

      Parameters:
      value - (undocumented)
      Returns:
      (undocumented)
      Since:
      2.2.0

    • fill

      public abstract Dataset<Row> fill(double value)

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

      Parameters:
      value - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • fill

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

      Parameters:
      value - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • fill

      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.

      Parameters:
      value - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      2.2.0

    • fill

      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.

      Parameters:
      value - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • fill

      public abstract Dataset<Row> fill(long value, scala.collection.immutable.Seq<String> cols)

      (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.

      Parameters:
      value - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      2.2.0

    • fill

      public abstract Dataset<Row> fill(double value, scala.collection.immutable.Seq<String> cols)

      (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.

      Parameters:
      value - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • fill

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

      Parameters:
      value - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • fill

      public abstract Dataset<Row> fill(String value, scala.collection.immutable.Seq<String> cols)

      (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.

      Parameters:
      value - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • fill

      public abstract Dataset<Row> fill(boolean value)

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

      Parameters:
      value - (undocumented)
      Returns:
      (undocumented)
      Since:
      2.3.0

    • fill

      public abstract Dataset<Row> fill(boolean value, scala.collection.immutable.Seq<String> cols)

      (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.

      Parameters:
      value - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      2.3.0

    • fill

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

      Parameters:
      value - (undocumented)
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      2.3.0

    • fill

      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));
      Parameters:
      valueMap - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • fill

      (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
   ))
      Parameters:
      valueMap - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.3.1

    • replace

      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"));
      Parameters:
      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.
      Returns:
      (undocumented)
      Since:
      1.3.1

    • replace

      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"));
      Parameters:
      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.
      Returns:
      (undocumented)
      Since:
      1.3.1

    • replace

      public abstract <T> Dataset<Row> replace(String col, scala.collection.immutable.Map<T,T> replacement)

      (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"));
      Parameters:
      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.
      Returns:
      (undocumented)
      Since:
      1.3.1

    • replace

      public abstract <T> Dataset<Row> replace(scala.collection.immutable.Seq<String> cols, scala.collection.immutable.Map<T,T> replacement)

      (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"));
      Parameters:
      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.
      Returns:
      (undocumented)
      Since:
      1.3.1