Reputation: 3392
How can I replace empty values in a column Field1
of DataFrame df
?
Field1 Field2
AA
12 BB
This command does not provide an expected result:
df.na.fill("Field1",Seq("Anonymous"))
The expected result:
Field1 Field2
Anonymous AA
12 BB
Upvotes: 2
Views: 4146
Reputation: 11
You can try using below code when you have n number of columns in dataframe.
Note: When you are trying to write data into formats like parquet, null data types are not supported. we have to type cast it.
val df = Seq(
(1, ""),
(2, "Ram"),
(3, "Sam"),
(4,"")
).toDF("ID", "Name")
// null type column
val inputDf = df.withColumn("NulType", lit(null).cast(StringType))
//Output
+---+----+-------+
| ID|Name|NulType|
+---+----+-------+
| 1| | null|
| 2| Ram| null|
| 3| Sam| null|
| 4| | null|
+---+----+-------+
//Replace all blank space in the dataframe with null
val colName = inputDf.columns //*This will give you array of string*
val data = inputDf.na.replace(colName,Map(""->"null"))
data.show()
+---+----+-------+
| ID|Name|NulType|
+---+----+-------+
| 1|null| null|
| 2| Ram| null|
| 3| Sam| null|
| 4|null| null|
+---+----+-------+
Upvotes: 1
Reputation: 39354
Fill: Returns a new DataFrame that replaces null or NaN values in numeric columns with value.
Two things:
Failing Null Replace with Fill / Text:
scala> a.show
+----+---+
| f1| f2|
+----+---+
|null| AA|
| 12| BB|
+----+---+
scala> a.na.fill("Anonymous", Seq("f1")).show
+----+---+
| f1| f2|
+----+---+
|null| AA|
| 12| BB|
+----+---+
Working Example - Using Null With All Numbers:
scala> a.show
+----+---+
| f1| f2|
+----+---+
|null| AA|
| 12| BB|
+----+---+
scala> a.na.fill(1, Seq("f1")).show
+---+---+
| f1| f2|
+---+---+
| 1| AA|
| 12| BB|
+---+---+
Failing Example (Empty String instead of Null):
scala> b.show
+---+---+
| f1| f2|
+---+---+
| | AA|
| 12| BB|
+---+---+
scala> b.na.fill(1, Seq("f1")).show
+---+---+
| f1| f2|
+---+---+
| | AA|
| 12| BB|
+---+---+
Case Statement Fix Example:
scala> b.show
+---+---+
| f1| f2|
+---+---+
| | AA|
| 12| BB|
+---+---+
scala> b.select(when(col("f1") === "", "Anonymous").otherwise(col("f1")).as("f1"), col("f2")).show
+---------+---+
| f1| f2|
+---------+---+
|Anonymous| AA|
| 12| BB|
+---------+---+
Upvotes: 2
Reputation: 1528
You can also try this. This might handle both blank/empty/null
df.show()
+------+------+
|Field1|Field2|
+------+------+
| | AA|
| 12| BB|
| 12| null|
+------+------+
df.na.replace(Seq("Field1","Field2"),Map(""-> null)).na.fill("Anonymous", Seq("Field2","Field1")).show(false)
+---------+---------+
|Field1 |Field2 |
+---------+---------+
|Anonymous|AA |
|12 |BB |
|12 |Anonymous|
+---------+---------+
Upvotes: 3