Snowpark Scala API Reference 1.19.0 - com.snowflake.snowpark.DataFrameNaFunctions
Keywords: Snowpark Scala API Reference 1.19.0 com.snowflake.snowpark.DataFrameNaFunctions

Snowpark Scala API Reference1.19.0 < Back
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# Packages

-  package root
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    root
-  package com
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    root
-  package snowflake
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    com
-  package snowpark
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    snowflake
-  package types

  This package contains all Snowpark logical types.

  This package contains all Snowpark logical types.

  Definition Classes
    snowpark
  Since

    0.1.0

-  package udaf
  Definition Classes
    snowpark
-  package udtf
  Definition Classes
    snowpark
- AggregateFunction
- AsyncJob
- CaseExpr
- Column
- CopyableDataFrame
- CopyableDataFrameAsyncActor
- DataFrame
- DataFrameAsyncActor
- DataFrameNaFunctions
- DataFrameReader
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- Updatable
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- functions
- tableFunctions

c

com.snowflake.snowpark

# DataFrameNaFunctions 

###

#### final class DataFrameNaFunctions extends Logging

Provides functions for handling missing values in a DataFrame.

Since

  0.2.0

Linear Supertypes
Logging, AnyRef, Any
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Ordering

1. Alphabetic
2. By Inheritance

Inherited

1. DataFrameNaFunctions
2. Logging
3. AnyRef
4. Any

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Visibility

1. Public
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### 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( ... ) @native() @HotSpotIntrinsicCandidate()
6.  def drop(minNonNullsPerRow: Int, cols: Seq[String]): DataFrame

   Returns a new DataFrame that excludes all rows containing fewer than `minNonNullsPerRow` non-null and non-NaN values in the specified columns `cols` .

   Returns a new DataFrame that excludes all rows containing fewer than `minNonNullsPerRow` non-null and non-NaN values in the specified columns `cols` .

   - If `minNonNullsPerRow` is greater than the number of the specified columns, the method returns an empty DataFrame.
   - If `minNonNullsPerRow` is less than 1, the method returns the original DataFrame.
   - If `cols` is empty, the method returns the original DataFrame.
   minNonNullsPerRow

     The minimum number of non-null and non-NaN values that should be in the specified columns in order for the row to be included.

   cols

     A sequence of the names of columns to check for null and NaN values.

   returns

     A DataFrame

   Since

     0.2.0

   Exceptions thrown

     `SnowparkClientException` if cols contains any unrecognized column name

7.  final def eq(arg0: AnyRef): Boolean
   Definition Classes
     AnyRef
8.  def equals(arg0: Any): Boolean
   Definition Classes
     AnyRef → Any
9.  def fill(valueMap: Map[String, Any]): DataFrame

   Returns a new DataFrame that replaces all null and NaN values in the specified columns with the values provided.

   Returns a new DataFrame that replaces all null and NaN values in the specified columns with the values provided.

   `valueMap` describes which columns will be replaced and what the replacement values are.

   - It only supports Long, Int, short, byte, String, Boolean, float, and Double values.
   - If the type of the given value doesn't match the column type (e.g. a Long value for a StringType column), the replacement in this column will be skipped.
   valueMap

     A Map that associates the names of columns with the values that should be used to replace null and NaN values in those columns.

   returns

     A DataFrame

   Since

     0.2.0

   Exceptions thrown

     `SnowparkClientException` if valueMap contains unrecognized columns

10.  final def getClass(): Class[_]
    Definition Classes
      AnyRef → Any
    Annotations
      @native() @HotSpotIntrinsicCandidate()
11.  def hashCode(): Int
    Definition Classes
      AnyRef → Any
    Annotations
      @native() @HotSpotIntrinsicCandidate()
12.  final def isInstanceOf[T0]: Boolean
    Definition Classes
      Any
13.  def log(): Logger
    Attributes
      protected[internal]
    Definition Classes
      Logging
14.  def logDebug(msg: String, throwable: Throwable): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
15.  def logDebug(msg: String): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
16.  def logError(msg: String, throwable: Throwable): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
17.  def logError(msg: String): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
18.  def logInfo(msg: String, throwable: Throwable): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
19.  def logInfo(msg: String): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
20.  def logTrace(msg: String, throwable: Throwable): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
21.  def logTrace(msg: String): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
22.  def logWarning(msg: String, throwable: Throwable): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
23.  def logWarning(msg: String): Unit
    Attributes
      protected[internal]
    Definition Classes
      Logging
24.  final def ne(arg0: AnyRef): Boolean
    Definition Classes
      AnyRef
25.  final def notify(): Unit
    Definition Classes
      AnyRef
    Annotations
      @native() @HotSpotIntrinsicCandidate()
26.  final def notifyAll(): Unit
    Definition Classes
      AnyRef
    Annotations
      @native() @HotSpotIntrinsicCandidate()
27.  def replace(colName: String, replacement: Map[Any, Any]): DataFrame

    Returns a new DataFrame that replaces values in a specified column.

    Returns a new DataFrame that replaces values in a specified column.

    Use the `replacement` parameter to specify a Map that associates the values to replace with new values. To replace a null value, use None as the key in the Map.

    For example, suppose that you pass `col1` for `colName` and `Map(2 -> 3, None -> 2, 4 -> null)` for `replacement` . In `col1`, this function replaces:

    - `2` with `3`
    - null with `2`
    - `4` with null
    colName

      The name of the column in which the values should be replaced.

    replacement

      A Map that associates the original values with the replacement values.

    Since

      0.2.0

    Exceptions thrown

      `SnowparkClientException` if colName is an unrecognized column name

28.  final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
      AnyRef
29.  def toString(): String
    Definition Classes
      AnyRef → Any
30.  def transformation(funcName: String)(func: ⇒ DataFrame): DataFrame
    Attributes
      protected
    Annotations
      @inline()
31.  final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
      AnyRef
    Annotations
      @throws( ... )
32.  final def wait(arg0: Long): Unit
    Definition Classes
      AnyRef
    Annotations
      @throws( ... ) @native()
33.  final def wait(): Unit
    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

### Deprecated Value Members

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

### Inherited from Logging

### Inherited from AnyRef

### Inherited from Any

### Ungrouped