Iterate through each column and find the max length

Question

I want to get the maximum length from each column from a pyspark dataframe.

Following is the sample dataframe:

from pyspark.sql.types import StructType,StructField, StringType, IntegerType

data2 = [("James","","Smith","36636","M",3000),
    ("Michael","Rose","","40288","M",4000),
    ("Robert","","Williams","42114","M",4000),
    ("Maria","Anne","Jones","39192","F",4000),
    ("Jen","Mary","Brown","","F",-1)
  ]

schema = StructType([ 
    StructField("firstname",StringType(),True), 
    StructField("middlename",StringType(),True), 
    StructField("lastname",StringType(),True), 
    StructField("id", StringType(), True), 
    StructField("gender", StringType(), True), 
    StructField("salary", IntegerType(), True) 
  ])
 
df = spark.createDataFrame(data=data2,schema=schema)

I tried to implement the solution provided in Scala but could not convert it.

Asked By: venus

||

Source

Answer 1

This would work

from pyspark.sql.functions import col, length, max


df=df.select([max(length(col(name))) for name in df.schema.names])

Result

Edit: For reference: Converting to Rows (As asked here, updated there as well – pyspark max string length for each column in the dataframe)

df = df.select([max(length(col(name))).alias(name) for name in df.schema.names])
row=df.first().asDict()
df2 = spark.createDataFrame([Row(col=name, length=row[name]) for name in df.schema.names], ['col', 'length'])

Output:

Answered By: Ronak Jain

Iterate through each column and find the max length

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