How to convert column with string type to int form in pyspark data frame?

Question

I have dataframe in pyspark. Some of its numerical columns contain 'nan' so when I am reading the data and checking for the schema of dataframe, those columns will have 'string' type. How I can change them to int type.I replaced the 'nan' values with 0 and again checked the schema, but then also it's showing the string type for those columns.I am following the below code:

data_df = sqlContext.read.format("csv").load('data.csv',header=True, inferSchema="true")
data_df.printSchema()
data_df = data_df.fillna(0)
data_df.printSchema()

my data looks like this:

here columns 'Plays' and 'drafts' containing integer values but because of nan present in these columns,they are treated as string type.

Answer 1

from pyspark.sql.types import IntegerType
data_df = data_df.withColumn("Plays", data_df["Plays"].cast(IntegerType()))
data_df = data_df.withColumn("drafts", data_df["drafts"].cast(IntegerType()))

You can run loop for each column but this is the simplest way to convert string column into integer.