Reputation: 24478
The test data:
df = spark.createDataFrame([(1, 1), (2, 3), (3, 3)], ['c1', 'c2'])
df.show()
#+---+---+
#| c1| c2|
#+---+---+
#| 1| 1|
#| 2| 3|
#| 3| 3|
#+---+---+
I intend to count distinct values in every row, creating a separate column with the count. How to do it?
The desired result:
#+---+---+---+
#| c1| c2| c3|
#+---+---+---+
#| 1| 1| 1|
#| 2| 3| 2|
#| 3| 3| 1|
#+---+---+---+
Upvotes: 1
Views: 103
Reputation: 42402
Check the size of array_distinct
:
import pyspark.sql.functions as F
df.withColumn('c3', F.size(F.array_distinct(F.array(*df.columns)))).show()
+---+---+---+
| c1| c2| c3|
+---+---+---+
| 1| 1| 1|
| 2| 3| 2|
| 3| 3| 1|
+---+---+---+
Upvotes: 2