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How to add List[String] values to a single column in Dataframe
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I have a dataframe, I have a list of values (possibly list string) and I want to create a new column in my dataframe and add those list values as column values to this new column. I tried
val x = List("def", "cook", "abc")
val c_df = null
x.foldLeft(c_df)((df, column) => df.withColumn("newcolumnname" , lit(column)))
but it throws StackOverflow exception, I also tried iterating over list of string values and adding to dataframe but result value is a list of dataframe but all i want is a single dataframe.
Please help!
here is the sample input and output dataframe:
scala apache-spark
asked Jan 3 at 8:36
Jimmy MaguelJimmy Maguel
117
|
show 13 more comments
0
I have a dataframe, I have a list of values (possibly list string) and I want to create a new column in my dataframe and add those list values as column values to this new column. I tried
val x = List("def", "cook", "abc")
val c_df = null
x.foldLeft(c_df)((df, column) => df.withColumn("newcolumnname" , lit(column)))
but it throws StackOverflow exception, I also tried iterating over list of string values and adding to dataframe but result value is a list of dataframe but all i want is a single dataframe.
Please help!
here is the sample input and output dataframe:
scala apache-spark
asked Jan 3 at 8:36
Jimmy MaguelJimmy Maguel
117
can you provide a sample output of how you expect your dataframe to look like? Also are you attempting to create a new dataframe or expanding on an existing one?
– Assaf Mendelson
Jan 3 at 8:44
I am trying to add new column to an existing dataframe, just need a way to add list of string to that new column i added
– Jimmy Maguel
Jan 3 at 8:48
Hi Jimmy, what I understood is you would like to add the list of values to existing DataFrame in a separate column? Is it correct?
– neeraj bhadani
Jan 3 at 8:58
@neerajbhadani, thatz exactly what I want, can u plz help
– Jimmy Maguel
Jan 3 at 9:01
do you want to have a new column per value? Or just a single column with 3 rows?
– AKSW
Jan 3 at 9:09
|
show 13 more comments
0
0
0
I have a dataframe, I have a list of values (possibly list string) and I want to create a new column in my dataframe and add those list values as column values to this new column. I tried
val x = List("def", "cook", "abc")
val c_df = null
x.foldLeft(c_df)((df, column) => df.withColumn("newcolumnname" , lit(column)))
but it throws StackOverflow exception, I also tried iterating over list of string values and adding to dataframe but result value is a list of dataframe but all i want is a single dataframe.
Please help!
here is the sample input and output dataframe:
scala apache-spark
asked Jan 3 at 8:36
Jimmy MaguelJimmy Maguel
117
I have a dataframe, I have a list of values (possibly list string) and I want to create a new column in my dataframe and add those list values as column values to this new column. I tried
val x = List("def", "cook", "abc")
val c_df = null
x.foldLeft(c_df)((df, column) => df.withColumn("newcolumnname" , lit(column)))
but it throws StackOverflow exception, I also tried iterating over list of string values and adding to dataframe but result value is a list of dataframe but all i want is a single dataframe.
Please help!
here is the sample input and output dataframe:
scala apache-spark
scala apache-spark
asked Jan 3 at 8:36
Jimmy MaguelJimmy Maguel
117
asked Jan 3 at 8:36
Jimmy MaguelJimmy Maguel
117
edited Jan 3 at 10:02
Jimmy Maguel
asked Jan 3 at 8:36
Jimmy MaguelJimmy Maguel
117
asked Jan 3 at 8:36
Jimmy MaguelJimmy Maguel
117
asked Jan 3 at 8:36
Jimmy MaguelJimmy Maguel
117
117
can you provide a sample output of how you expect your dataframe to look like? Also are you attempting to create a new dataframe or expanding on an existing one?
– Assaf Mendelson
Jan 3 at 8:44
I am trying to add new column to an existing dataframe, just need a way to add list of string to that new column i added
– Jimmy Maguel
Jan 3 at 8:48
Hi Jimmy, what I understood is you would like to add the list of values to existing DataFrame in a separate column? Is it correct?
– neeraj bhadani
Jan 3 at 8:58
@neerajbhadani, thatz exactly what I want, can u plz help
– Jimmy Maguel
Jan 3 at 9:01
do you want to have a new column per value? Or just a single column with 3 rows?
– AKSW
Jan 3 at 9:09
|
show 13 more comments
can you provide a sample output of how you expect your dataframe to look like? Also are you attempting to create a new dataframe or expanding on an existing one?
– Assaf Mendelson
Jan 3 at 8:44
I am trying to add new column to an existing dataframe, just need a way to add list of string to that new column i added
– Jimmy Maguel
Jan 3 at 8:48
Hi Jimmy, what I understood is you would like to add the list of values to existing DataFrame in a separate column? Is it correct?
– neeraj bhadani
Jan 3 at 8:58
@neerajbhadani, thatz exactly what I want, can u plz help
– Jimmy Maguel
Jan 3 at 9:01
do you want to have a new column per value? Or just a single column with 3 rows?
– AKSW
Jan 3 at 9:09
can you provide a sample output of how you expect your dataframe to look like? Also are you attempting to create a new dataframe or expanding on an existing one?
– Assaf Mendelson
Jan 3 at 8:44
can you provide a sample output of how you expect your dataframe to look like? Also are you attempting to create a new dataframe or expanding on an existing one?
– Assaf Mendelson
Jan 3 at 8:44
I am trying to add new column to an existing dataframe, just need a way to add list of string to that new column i added
– Jimmy Maguel
Jan 3 at 8:48
I am trying to add new column to an existing dataframe, just need a way to add list of string to that new column i added
– Jimmy Maguel
Jan 3 at 8:48
Hi Jimmy, what I understood is you would like to add the list of values to existing DataFrame in a separate column? Is it correct?
– neeraj bhadani
Jan 3 at 8:58
Hi Jimmy, what I understood is you would like to add the list of values to existing DataFrame in a separate column? Is it correct?
– neeraj bhadani
Jan 3 at 8:58
@neerajbhadani, thatz exactly what I want, can u plz help
– Jimmy Maguel
Jan 3 at 9:01
@neerajbhadani, thatz exactly what I want, can u plz help
– Jimmy Maguel
Jan 3 at 9:01
do you want to have a new column per value? Or just a single column with 3 rows?
– AKSW
Jan 3 at 9:09
do you want to have a new column per value? Or just a single column with 3 rows?
– AKSW
Jan 3 at 9:09
|
show 13 more comments
2 Answers
2
active
oldest
votes
0
You can try below code.
- Create First DataFrame with Index.
from pyspark.sql.functions import *
from pyspark.sql import Window
w = Window.orderBy("Col2")
df = spark.createDataFrame([("a", 10), ("b", 20), ("c", 30)], ["Col1", "Col2"])
df1 = df.withColumn("index", row_number().over(w))
df1.show()
- Create Another DataFrame from List of Values.
from pyspark.sql.types import * newdf = spark.createDataFrame(['x','y', 'z'], StringType()) newdf.show()
- Add Index column to DF created from List of values in step 2.
w = Window.orderBy("value")
df2 = newdf.withColumn("index", row_number().over(w))
df2.show()
- Join the DataFrame df1 and df2 based on index.
df1.join(df2, "index").show()
answered Jan 3 at 9:42
neeraj bhadanineeraj bhadani
935313
1
its in python, do u have scala version plz
– Jimmy Maguel
Jan 3 at 9:44
add a comment |
0
There is a function array in Spark 1.4 or later that takes an array of Columns and returns a new Column. Function lit takes a Scala value and returns a Column type.
import spark.implicits._
val df = Seq(1, 2, 3).toDF("col1")
df.withColumn("new_col", array(lit("def"), lit("cook"), lit("abc"))).show
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
In Spark 2.2.0, there is a function typedLit that takes Scala types and returns a Column type. this function can handle parameterized scala types e.g.: List, Seq and Map.
val newDF = df.withColumn("new_col", typedLit(List("def", "cook", "abc")))
newDF.show()
newDF.printSchema()
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
root
|-- col1: integer (nullable = false)
|-- new_col: array (nullable = false)
| |-- element: string (containsNull = true)
This is what you wanted to do ? You can add when to conditionally add different set of lists to each row.
answered Jan 3 at 10:18
ryandamryandam
1346
instead of duplicating array, i wanted in col 1 value as def, in col2 cook and in col3 abc only
– Jimmy Maguel
Jan 3 at 10:28
in new_col data is getting duplicated in ur answer
– Jimmy Maguel
Jan 3 at 11:17
Adding to @ryandam answer: df.withColumn("new_col", typedLit(List("def", "cook", "abc"))).withColumn("col1", new_col(0)).withColumn("col2", new_col(1)).withColumn("col3", new_col(2)).drop("new_col")
– Mohd Avais
Jan 4 at 10:59
add a comment |
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2 Answers
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2 Answers
2
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oldest
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0
You can try below code.
- Create First DataFrame with Index.
from pyspark.sql.functions import *
from pyspark.sql import Window
w = Window.orderBy("Col2")
df = spark.createDataFrame([("a", 10), ("b", 20), ("c", 30)], ["Col1", "Col2"])
df1 = df.withColumn("index", row_number().over(w))
df1.show()
- Create Another DataFrame from List of Values.
from pyspark.sql.types import * newdf = spark.createDataFrame(['x','y', 'z'], StringType()) newdf.show()
- Add Index column to DF created from List of values in step 2.
w = Window.orderBy("value")
df2 = newdf.withColumn("index", row_number().over(w))
df2.show()
- Join the DataFrame df1 and df2 based on index.
df1.join(df2, "index").show()
answered Jan 3 at 9:42
neeraj bhadanineeraj bhadani
935313
1
its in python, do u have scala version plz
– Jimmy Maguel
Jan 3 at 9:44
add a comment |
0
You can try below code.
- Create First DataFrame with Index.
from pyspark.sql.functions import *
from pyspark.sql import Window
w = Window.orderBy("Col2")
df = spark.createDataFrame([("a", 10), ("b", 20), ("c", 30)], ["Col1", "Col2"])
df1 = df.withColumn("index", row_number().over(w))
df1.show()
- Create Another DataFrame from List of Values.
from pyspark.sql.types import * newdf = spark.createDataFrame(['x','y', 'z'], StringType()) newdf.show()
- Add Index column to DF created from List of values in step 2.
w = Window.orderBy("value")
df2 = newdf.withColumn("index", row_number().over(w))
df2.show()
- Join the DataFrame df1 and df2 based on index.
df1.join(df2, "index").show()
answered Jan 3 at 9:42
neeraj bhadanineeraj bhadani
935313
1
its in python, do u have scala version plz
– Jimmy Maguel
Jan 3 at 9:44
add a comment |
0
0
0
You can try below code.
- Create First DataFrame with Index.
from pyspark.sql.functions import *
from pyspark.sql import Window
w = Window.orderBy("Col2")
df = spark.createDataFrame([("a", 10), ("b", 20), ("c", 30)], ["Col1", "Col2"])
df1 = df.withColumn("index", row_number().over(w))
df1.show()
- Create Another DataFrame from List of Values.
from pyspark.sql.types import * newdf = spark.createDataFrame(['x','y', 'z'], StringType()) newdf.show()
- Add Index column to DF created from List of values in step 2.
w = Window.orderBy("value")
df2 = newdf.withColumn("index", row_number().over(w))
df2.show()
- Join the DataFrame df1 and df2 based on index.
df1.join(df2, "index").show()
answered Jan 3 at 9:42
neeraj bhadanineeraj bhadani
935313
You can try below code.
- Create First DataFrame with Index.
from pyspark.sql.functions import *
from pyspark.sql import Window
w = Window.orderBy("Col2")
df = spark.createDataFrame([("a", 10), ("b", 20), ("c", 30)], ["Col1", "Col2"])
df1 = df.withColumn("index", row_number().over(w))
df1.show()
- Create Another DataFrame from List of Values.
from pyspark.sql.types import * newdf = spark.createDataFrame(['x','y', 'z'], StringType()) newdf.show()
- Add Index column to DF created from List of values in step 2.
w = Window.orderBy("value")
df2 = newdf.withColumn("index", row_number().over(w))
df2.show()
- Join the DataFrame df1 and df2 based on index.
df1.join(df2, "index").show()
answered Jan 3 at 9:42
neeraj bhadanineeraj bhadani
935313
answered Jan 3 at 9:42
neeraj bhadanineeraj bhadani
935313
answered Jan 3 at 9:42
neeraj bhadanineeraj bhadani
935313
answered Jan 3 at 9:42
neeraj bhadanineeraj bhadani
935313
935313
1
its in python, do u have scala version plz
– Jimmy Maguel
Jan 3 at 9:44
add a comment |
1
its in python, do u have scala version plz
– Jimmy Maguel
Jan 3 at 9:44
1
1
its in python, do u have scala version plz
– Jimmy Maguel
Jan 3 at 9:44
its in python, do u have scala version plz
– Jimmy Maguel
Jan 3 at 9:44
add a comment |
0
There is a function array in Spark 1.4 or later that takes an array of Columns and returns a new Column. Function lit takes a Scala value and returns a Column type.
import spark.implicits._
val df = Seq(1, 2, 3).toDF("col1")
df.withColumn("new_col", array(lit("def"), lit("cook"), lit("abc"))).show
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
In Spark 2.2.0, there is a function typedLit that takes Scala types and returns a Column type. this function can handle parameterized scala types e.g.: List, Seq and Map.
val newDF = df.withColumn("new_col", typedLit(List("def", "cook", "abc")))
newDF.show()
newDF.printSchema()
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
root
|-- col1: integer (nullable = false)
|-- new_col: array (nullable = false)
| |-- element: string (containsNull = true)
This is what you wanted to do ? You can add when to conditionally add different set of lists to each row.
answered Jan 3 at 10:18
ryandamryandam
1346
instead of duplicating array, i wanted in col 1 value as def, in col2 cook and in col3 abc only
– Jimmy Maguel
Jan 3 at 10:28
in new_col data is getting duplicated in ur answer
– Jimmy Maguel
Jan 3 at 11:17
Adding to @ryandam answer: df.withColumn("new_col", typedLit(List("def", "cook", "abc"))).withColumn("col1", new_col(0)).withColumn("col2", new_col(1)).withColumn("col3", new_col(2)).drop("new_col")
– Mohd Avais
Jan 4 at 10:59
add a comment |
0
There is a function array in Spark 1.4 or later that takes an array of Columns and returns a new Column. Function lit takes a Scala value and returns a Column type.
import spark.implicits._
val df = Seq(1, 2, 3).toDF("col1")
df.withColumn("new_col", array(lit("def"), lit("cook"), lit("abc"))).show
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
In Spark 2.2.0, there is a function typedLit that takes Scala types and returns a Column type. this function can handle parameterized scala types e.g.: List, Seq and Map.
val newDF = df.withColumn("new_col", typedLit(List("def", "cook", "abc")))
newDF.show()
newDF.printSchema()
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
root
|-- col1: integer (nullable = false)
|-- new_col: array (nullable = false)
| |-- element: string (containsNull = true)
This is what you wanted to do ? You can add when to conditionally add different set of lists to each row.
answered Jan 3 at 10:18
ryandamryandam
1346
instead of duplicating array, i wanted in col 1 value as def, in col2 cook and in col3 abc only
– Jimmy Maguel
Jan 3 at 10:28
in new_col data is getting duplicated in ur answer
– Jimmy Maguel
Jan 3 at 11:17
Adding to @ryandam answer: df.withColumn("new_col", typedLit(List("def", "cook", "abc"))).withColumn("col1", new_col(0)).withColumn("col2", new_col(1)).withColumn("col3", new_col(2)).drop("new_col")
– Mohd Avais
Jan 4 at 10:59
add a comment |
0
0
0
There is a function array in Spark 1.4 or later that takes an array of Columns and returns a new Column. Function lit takes a Scala value and returns a Column type.
import spark.implicits._
val df = Seq(1, 2, 3).toDF("col1")
df.withColumn("new_col", array(lit("def"), lit("cook"), lit("abc"))).show
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
In Spark 2.2.0, there is a function typedLit that takes Scala types and returns a Column type. this function can handle parameterized scala types e.g.: List, Seq and Map.
val newDF = df.withColumn("new_col", typedLit(List("def", "cook", "abc")))
newDF.show()
newDF.printSchema()
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
root
|-- col1: integer (nullable = false)
|-- new_col: array (nullable = false)
| |-- element: string (containsNull = true)
This is what you wanted to do ? You can add when to conditionally add different set of lists to each row.
answered Jan 3 at 10:18
ryandamryandam
1346
There is a function array in Spark 1.4 or later that takes an array of Columns and returns a new Column. Function lit takes a Scala value and returns a Column type.
import spark.implicits._
val df = Seq(1, 2, 3).toDF("col1")
df.withColumn("new_col", array(lit("def"), lit("cook"), lit("abc"))).show
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
In Spark 2.2.0, there is a function typedLit that takes Scala types and returns a Column type. this function can handle parameterized scala types e.g.: List, Seq and Map.
val newDF = df.withColumn("new_col", typedLit(List("def", "cook", "abc")))
newDF.show()
newDF.printSchema()
+----+----------------+
|col1| new_col|
+----+----------------+
| 1|[def, cook, abc]|
| 2|[def, cook, abc]|
| 3|[def, cook, abc]|
+----+----------------+
root
|-- col1: integer (nullable = false)
|-- new_col: array (nullable = false)
| |-- element: string (containsNull = true)
This is what you wanted to do ? You can add when to conditionally add different set of lists to each row.
answered Jan 3 at 10:18
ryandamryandam
1346
answered Jan 3 at 10:18
ryandamryandam
1346
answered Jan 3 at 10:18
ryandamryandam
1346
answered Jan 3 at 10:18
ryandamryandam
1346
1346
instead of duplicating array, i wanted in col 1 value as def, in col2 cook and in col3 abc only
– Jimmy Maguel
Jan 3 at 10:28
in new_col data is getting duplicated in ur answer
– Jimmy Maguel
Jan 3 at 11:17
Adding to @ryandam answer: df.withColumn("new_col", typedLit(List("def", "cook", "abc"))).withColumn("col1", new_col(0)).withColumn("col2", new_col(1)).withColumn("col3", new_col(2)).drop("new_col")
– Mohd Avais
Jan 4 at 10:59
add a comment |
instead of duplicating array, i wanted in col 1 value as def, in col2 cook and in col3 abc only
– Jimmy Maguel
Jan 3 at 10:28
in new_col data is getting duplicated in ur answer
– Jimmy Maguel
Jan 3 at 11:17
Adding to @ryandam answer: df.withColumn("new_col", typedLit(List("def", "cook", "abc"))).withColumn("col1", new_col(0)).withColumn("col2", new_col(1)).withColumn("col3", new_col(2)).drop("new_col")
– Mohd Avais
Jan 4 at 10:59
instead of duplicating array, i wanted in col 1 value as def, in col2 cook and in col3 abc only
– Jimmy Maguel
Jan 3 at 10:28
instead of duplicating array, i wanted in col 1 value as def, in col2 cook and in col3 abc only
– Jimmy Maguel
Jan 3 at 10:28
in new_col data is getting duplicated in ur answer
– Jimmy Maguel
Jan 3 at 11:17
in new_col data is getting duplicated in ur answer
– Jimmy Maguel
Jan 3 at 11:17
Adding to @ryandam answer: df.withColumn("new_col", typedLit(List("def", "cook", "abc"))).withColumn("col1", new_col(0)).withColumn("col2", new_col(1)).withColumn("col3", new_col(2)).drop("new_col")
– Mohd Avais
Jan 4 at 10:59
Adding to @ryandam answer: df.withColumn("new_col", typedLit(List("def", "cook", "abc"))).withColumn("col1", new_col(0)).withColumn("col2", new_col(1)).withColumn("col3", new_col(2)).drop("new_col")
– Mohd Avais
Jan 4 at 10:59
add a comment |
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can you provide a sample output of how you expect your dataframe to look like? Also are you attempting to create a new dataframe or expanding on an existing one?
– Assaf Mendelson
Jan 3 at 8:44
I am trying to add new column to an existing dataframe, just need a way to add list of string to that new column i added
– Jimmy Maguel
Jan 3 at 8:48
Hi Jimmy, what I understood is you would like to add the list of values to existing DataFrame in a separate column? Is it correct?
– neeraj bhadani
Jan 3 at 8:58
@neerajbhadani, thatz exactly what I want, can u plz help
– Jimmy Maguel
Jan 3 at 9:01
do you want to have a new column per value? Or just a single column with 3 rows?
– AKSW
Jan 3 at 9:09