How to convert all int dtypes to double simultanously on PySpark

Question

here's my dataset

DataFrame[column1: double, column2: double, column3: int, column4: int, column5: int, ... , column300: int]

What I want is

DataFrame[column1: double, column2: double, column3: double, column4: double, column5: double, ... , column300: double]

What I did dataset.withColumn("column3", datalabel.column3.cast(DoubleType()))

It is too manual, can you show me how to do that?

Answer 1

You can use list comprehensions to construct the converted field list.

import pyspark.sql.functions as F
...
cols = [F.col(field[0]).cast('double') if field[1] == 'int' else F.col(field[0]) for field in df.dtypes]
df = df.select(cols)
df.printSchema()