calculate diff of value and median in a group

[Craig Ching]

Hi,

When using pyspark, I'd like to be able to calculate the difference between
grouped values and their median for the group.  Is this possible?  Here is
some code I hacked up that does what I want except that it calculates the
grouped diff from mean.  Also, please feel free to comment on how I could
make this better if you feel like being helpful :)

from pyspark import SparkContext
from pyspark.sql import SparkSession
from pyspark.sql.types import (
    StringType,
    LongType,
    DoubleType,
    StructField,
    StructType
)
from pyspark.sql import functions as F


sc = SparkContext(appName='myapp')
spark = SparkSession(sc)

file_name = 'data.csv'

fields = [
    StructField(
        'group2',
        LongType(),
        True),
    StructField(
        'name',
        StringType(),
        True),
    StructField(
        'value',
        DoubleType(),
        True),
    StructField(
        'group1',
        LongType(),
        True)
]
schema = StructType(fields)

df = spark.read.csv(
    file_name, header=False, mode="DROPMALFORMED", schema=schema
)
df.show()
means = df.select([
    'group1',
    'group2',
    'name',
    'value']).groupBy([
        'group1',
        'group2'
    ]).agg(
        F.mean('value').alias('mean_value')
    ).orderBy('group1', 'group2')

cond = [df.group1 == means.group1, df.group2 == means.group2]

means.show()
df = df.select([
    'group1',
    'group2',
    'name',
    'value']).join(
        means,
        cond
    ).drop(
        df.group1
    ).drop(
        df.group2
    ).select('group1',
             'group2',
             'name',
             'value',
             'mean_value')

final = df.withColumn(
    'diff',
    F.abs(df.value - df.mean_value))
final.show()

sc.stop()

And here is an example dataset I'm playing with:

100,name1,0.43,0
100,name2,0.33,0
100,name3,0.73,0
101,name1,0.29,0
101,name2,0.96,0
101,name3,0.42,0
102,name1,0.01,0
102,name2,0.42,0
102,name3,0.51,0
103,name1,0.55,0
103,name2,0.45,0
103,name3,0.02,0
104,name1,0.93,0
104,name2,0.16,0
104,name3,0.74,0
105,name1,0.41,0
105,name2,0.65,0
105,name3,0.29,0
100,name1,0.51,1
100,name2,0.51,1
100,name3,0.43,1
101,name1,0.59,1
101,name2,0.55,1
101,name3,0.84,1
102,name1,0.01,1
102,name2,0.98,1
102,name3,0.44,1
103,name1,0.47,1
103,name2,0.16,1
103,name3,0.02,1
104,name1,0.83,1
104,name2,0.89,1
104,name3,0.31,1
105,name1,0.59,1
105,name2,0.77,1
105,name3,0.45,1

and here is what I'm trying to produce:

group1,group2,name,value,median,diff
0,100,name1,0.43,0.43,0.0
0,100,name2,0.33,0.43,0.10
0,100,name3,0.73,0.43,0.30
0,101,name1,0.29,0.42,0.13
0,101,name2,0.96,0.42,0.54
0,101,name3,0.42,0.42,0.0
0,102,name1,0.01,0.42,0.41
0,102,name2,0.42,0.42,0.0
0,102,name3,0.51,0.42,0.09
0,103,name1,0.55,0.45,0.10
0,103,name2,0.45,0.45,0.0
0,103,name3,0.02,0.45,0.43
0,104,name1,0.93,0.74,0.19
0,104,name2,0.16,0.74,0.58
0,104,name3,0.74,0.74,0.0
0,105,name1,0.41,0.41,0.0
0,105,name2,0.65,0.41,0.24
0,105,name3,0.29,0.41,0.24
1,100,name1,0.51,0.51,0.0
1,100,name2,0.51,0.51,0.0
1,100,name3,0.43,0.51,0.08
1,101,name1,0.59,0.59,0.0
1,101,name2,0.55,0.59,0.04
1,101,name3,0.84,0.59,0.25
1,102,name1,0.01,0.44,0.43
1,102,name2,0.98,0.44,0.54
1,102,name3,0.44,0.44,0.0
1,103,name1,0.47,0.16,0.31
1,103,name2,0.16,0.16,0.0
1,103,name3,0.02,0.16,0.14
1,104,name1,0.83,0.83,0.0
1,104,name2,0.89,0.83,0.06
1,104,name3,0.31,0.83,0.52
1,105,name1,0.59,0.59,0.0
1,105,name2,0.77,0.59,0.18
1,105,name3,0.45,0.59,0.14

Thanks for any help!

Cheers,
Craig