My data looks like the following:
+----------+-------------+-------+--------------------+--------------+---+
|purch_date| purch_class|tot_amt| serv-provider|purch_location| id|
+----------+-------------+-------+--------------------+--------------+---+
|03/11/2017|Uncategorized| -17.53| HOVER | | 0|
|02/11/2017| Groceries| -70.05|1774 MAC'S CONVEN...| BRAMPTON | 1|
|31/10/2017|Gasoline/Fuel| -20| ESSO | | 2|
|31/10/2017| Travel| -9|TORONTO PARKING A...| TORONTO | 3|
|30/10/2017| Groceries| -1.84| LONGO'S # 2| | 4|
I am attempting to create a binary column which will be defined by the value of the tot_amt column. I would like to add this column to the above data. If tot_amt <(-50) I would like it to return 0 and if tot_amt > (-50) I would like it to return 1 in a new column.
My attempt so far:
from pyspark.sql.types import IntegerType
from pyspark.sql.functions import udf
def y(row):
if row['tot_amt'] < (-50):
val = 1
else:
val = 0
return val
y_udf = udf(y, IntegerType())
df_7 = df_4.withColumn('Y',y_udf(df_4['tot_amt'], (df_4['purch_class'],
(df_4['purch_date'], (df_4['serv-provider'], (df_4['purch_location'])))
display(df_7)
Error message I'm receiving:
SparkException: Job aborted due to stage failure: Task 0 in stage 67.0 failed
1 times, most recent failure: Lost task 0.0 in stage 67.0 (TID 85, localhost,
executor driver): org.apache.spark.api.python.PythonException: Traceback (most
recent call last):
File "/databricks/spark/python/pyspark/worker.py", line 177, in main
process()
File "/databricks/spark/python/pyspark/worker.py", line 172, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/databricks/spark/python/pyspark/worker.py", line 104, in <lambda>
func = lambda _, it: map(mapper, it)
File "<string>", line 1, in <lambda>
File "/databricks/spark/python/pyspark/worker.py", line 71, in <lambda>
return lambda *a: f(*a)
TypeError: y() takes exactly 1 argument (2 given)
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