TypeError in pySpark UDF functions

I've got this function:

def ead(lista):
    ind_mmff, isdebala, isfubala, k1, k2, ead = lista
    try:
        isdebala = float(isdebala)
        isfubala = float(isfubala)
        k1 = float(k1)
        k2 = float(k2)
        ead = float(ead)
    except ValueError:
        return 'Error: invalid input'        
    min_deb = min(0, isdebala)
    min_fub = min(0, isfubala)
    
    if ind_mmff == '0':
        ead_dai = abs(min_deb * k1 / 100 + min_fub * k2 / 100)
    else:
        ead_dai = ead
    return ead_dai

Afterwards, I define a UDF such as:

ead_udf = udf(lambda z: ead(z), FloatType())

The aim is to create a ead_calc column in my df dataframe such as:

df = df.withColumn('ead_calc', ead_udf (array(df.ind_mmff, df.isdebala, df.isfubala, df.k1, df.k2, df.ead_final_motor)))

After executing df.select('ead_calc').show() the following error raises:

Py4JJavaError: An error occurred while calling o3026.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 813.0 failed 4 times, most recent failure: Lost task 3.3 in stage 813.0 (TID 12054, csslncclowp0006.unix.aacc.corp, executor 2): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main
    process()
  File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/serializers.py", line 345, in dump_stream
    self.serializer.dump_stream(self._batched(iterator), stream)
  File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/serializers.py", line 141, in dump_stream
    for obj in iterator:
  File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/serializers.py", line 334, in _batched
    for item in iterator:
  File "<string>", line 1, in <lambda>
  File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/worker.py", line 85, in <lambda>
    return lambda *a: f(*a)
  File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper
    return f(*args, **kwargs)
  File "<ipython-input-93-25e605cffdae>", line 1, in <lambda>
  File "<ipython-input-92-a1937fe32209>", line 12, in ead
TypeError: _() takes 1 positional argument but 2 were given

The error is located at min_deb = min(0, isdebala). Don't know how to solve this issue since min function obviously requires 2 arguments.

The aim is to create a ead_calc column in my df dataframe such as:

df = df.withColumn('ead_calc', ead_udf (array(df.ind_mmff, df.isdebala, df.isfubala, df.k1, df.k2, df.ead_final_motor)))

I think you have imported the wrong min function, I guess you have imported the one from pyspark by using from pyspark.sql.functions import *, the pyspark min function takes only one argument (column) but the python one takes two arguments

Trying to import only the needed functions and it seems working (Just added some random input)

from pyspark.sql.functions import udf, array

from pyspark.sql.types import StructField, StructType, FloatType

def ead(lista):
    ind_mmff, isdebala, isfubala, k1, k2, ead = lista
    try:
        isdebala = float(isdebala)
        isfubala = float(isfubala)
        k1 = float(k1)
        k2 = float(k2)
        ead = float(ead)
    except ValueError:
        return 'Error: invalid input'        
    min_deb = min(0, isdebala)
    min_fub = min(0, isfubala)
    
    if ind_mmff == '0':
        ead_dai = abs(min_deb * k1 / 100 + min_fub * k2 / 100)
    else:
        ead_dai = ead
    return ead_dai


ead_udf = udf(lambda z: ead(z), FloatType())


schema = StructType([
  StructField('ind_mmff', FloatType(), True),
  StructField('isdebala', FloatType(), True),
  StructField('isfubala', FloatType(), True),
  StructField('k1', FloatType(), True),
  StructField('k2', FloatType(), True),
  StructField('ead_final_motor', FloatType(), True)
  ])

df = spark.createDataFrame(data=[(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)],schema=schema)

df = df.withColumn('ead_calc', ead_udf (array(df.ind_mmff, df.isdebala, df.isfubala, df.k1, df.k2, df.ead_final_motor)))

df.show()

+--------+--------+--------+---+---+---------------+--------+                   
|ind_mmff|isdebala|isfubala| k1| k2|ead_final_motor|ead_calc|
+--------+--------+--------+---+---+---------------+--------+
|     1.0|     2.0|     3.0|4.0|5.0|            6.0|     6.0|
+--------+--------+--------+---+---+---------------+--------+