org.apache.spark.sql

Class DataFrameNaFunctions

Object

org.apache.spark.sql.DataFrameNaFunctions

public final class DataFrameNaFunctions
extends Object

:: Experimental :: Functionality for working with missing data in DataFrames.

Since:

1.3.1

Method Summary

Methods

Modifier and Type	Method and Description
Dataset<Row>	drop() Returns a new DataFrame that drops rows containing any null or NaN values.
Dataset<Row>	drop(int minNonNulls) Returns a new DataFrame that drops rows containing less than minNonNulls non-null and non-NaN values.
Dataset<Row>	drop(int minNonNulls, scala.collection.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.
Dataset<Row>	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.
Dataset<Row>	drop(scala.collection.Seq<String> cols) (Scala-specific) Returns a new DataFrame that drops rows containing any null or NaN values in the specified columns.
Dataset<Row>	drop(String how) Returns a new DataFrame that drops rows containing null or NaN values.
Dataset<Row>	drop(String[] cols) Returns a new DataFrame that drops rows containing any null or NaN values in the specified columns.
Dataset<Row>	drop(String how, scala.collection.Seq<String> cols) (Scala-specific) Returns a new DataFrame that drops rows containing null or NaN values in the specified columns.
Dataset<Row>	drop(String how, String[] cols) Returns a new DataFrame that drops rows containing null or NaN values in the specified columns.
Dataset<Row>	fill(double value) Returns a new DataFrame that replaces null or NaN values in numeric columns with value.
Dataset<Row>	fill(double value, scala.collection.Seq<String> cols) (Scala-specific) Returns a new DataFrame that replaces null or NaN values in specified numeric columns.
Dataset<Row>	fill(double value, String[] cols) Returns a new DataFrame that replaces null or NaN values in specified numeric columns.
Dataset<Row>	fill(java.util.Map<String,Object> valueMap) Returns a new DataFrame that replaces null values.
Dataset<Row>	fill(scala.collection.immutable.Map<String,Object> valueMap) (Scala-specific) Returns a new DataFrame that replaces null values.
Dataset<Row>	fill(String value) Returns a new DataFrame that replaces null values in string columns with value.
Dataset<Row>	fill(String value, scala.collection.Seq<String> cols) (Scala-specific) Returns a new DataFrame that replaces null values in specified string columns.
Dataset<Row>	fill(String value, String[] cols) Returns a new DataFrame that replaces null values in specified string columns.
<T> Dataset<Row>	replace(scala.collection.Seq<String> cols, scala.collection.immutable.Map<T,T> replacement) (Scala-specific) Replaces values matching keys in replacement map.
<T> Dataset<Row>	replace(String[] cols, java.util.Map<T,T> replacement) Replaces values matching keys in replacement map with the corresponding values.
<T> Dataset<Row>	replace(String col, java.util.Map<T,T> replacement) Replaces values matching keys in replacement map with the corresponding values.
<T> Dataset<Row>	replace(String col, scala.collection.immutable.Map<T,T> replacement) (Scala-specific) Replaces values matching keys in replacement map.

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

drop

public Dataset<Row> drop()

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

Returns:

(undocumented)

Since:

1.3.1

drop

public Dataset<Row> drop(String how)

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

public Dataset<Row> drop(String[] cols)

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.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

public Dataset<Row> drop(String how,
                String[] cols)

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

(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

public Dataset<Row> 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.

Parameters:

minNonNulls - (undocumented)

cols - (undocumented)

Returns:

(undocumented)

Since:

1.3.1

drop

public Dataset<Row> drop(int minNonNulls,
                scala.collection.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 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

public Dataset<Row> fill(String value)

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

Parameters:

value - (undocumented)

Returns:

(undocumented)

Since:

1.3.1

fill

public Dataset<Row> fill(double value,
                String[] cols)

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 Dataset<Row> fill(double value,
                scala.collection.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

public Dataset<Row> fill(String value,
                String[] cols)

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 Dataset<Row> fill(String value,
                scala.collection.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 Dataset<Row> fill(java.util.Map<String,Object> valueMap)

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

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

(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

public <T> Dataset<Row> replace(String col,
                       java.util.Map<T,T> replacement)

Replaces values matching keys in replacement map with the corresponding values. Key and value of replacement map must have the same type, and can only be doubles, strings or booleans. If col is "*", then the replacement is applied on all string columns or numeric columns.

   import com.google.common.collect.ImmutableMap;

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

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

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

Parameters:

col - name of the column to apply the value replacement

replacement - value replacement map, as explained above

Returns:

(undocumented)

Since:

1.3.1

replace

public <T> Dataset<Row> replace(String[] cols,
                       java.util.Map<T,T> replacement)

Replaces values matching keys in replacement map with the corresponding values. Key and value of replacement map must have the same type, and can only be doubles, strings or booleans.

   import com.google.common.collect.ImmutableMap;

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

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

Parameters:

cols - list of columns to apply the value replacement

replacement - value replacement map, as explained above

Returns:

(undocumented)

Since:

1.3.1

replace

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

(Scala-specific) Replaces values matching keys in replacement map. Key and value of replacement map must have the same type, and can only be doubles, strings or booleans. If col is "*", then the replacement is applied on all string columns , numeric columns or boolean columns.

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

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

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

Parameters:

col - name of the column to apply the value replacement

replacement - value replacement map, as explained above

Returns:

(undocumented)

Since:

1.3.1

replace

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

(Scala-specific) Replaces values matching keys in replacement map. Key and value of replacement map must have the same type, and can only be doubles , strings or booleans.

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

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

Parameters:

cols - list of columns to apply the value replacement

replacement - value replacement map, as explained above

Returns:

(undocumented)

Since:

1.3.1