How to sum the values of a column in pyspark dataframe

Question

I am working in Pyspark and I have a data frame with the following columns.

Q1 = spark.read.csv("Q1final.csv",header = True, inferSchema = True)
Q1.printSchema()

root
|-- index_date: integer (nullable = true)
|-- item_id: integer (nullable = true)
|-- item_COICOP_CLASSIFICATION: integer (nullable = true)
|-- item_desc: string (nullable = true)
|-- index_algorithm: integer (nullable = true)
|-- stratum_ind: integer (nullable = true)
|-- item_index: double (nullable = true)
|-- all_gm_index: double (nullable = true)
|-- gm_ra_index: double (nullable = true)
|-- coicop_weight: double (nullable = true)
|-- item_weight: double (nullable = true)
|-- cpih_coicop_weight: double (nullable = true)

I need the sum of all the elements in the last column (cpih_coicop_weight) to use as a Double in other parts of my program. How can I do it? Thank you very much in advance!

Answer 1

If you want just a double or int as return, the following function will work:

def sum_col(df, col):
    return df.select(F.sum(col)).collect()[0][0]

Then

sum_col(Q1, 'cpih_coicop_weight')

will return the sum. I am new to pyspark so I am not sure why such a simple method of a column object is not in the library.