How to find the size or shape of a DataFrame in PySpark?

You can get its shape with:

print((df.count(), len(df.columns)))

Use df.count() to get the number of rows.

Add this to the your code:

import pyspark
def spark_shape(self):
    return (self.count(), len(self.columns))
pyspark.sql.dataframe.DataFrame.shape = spark_shape

Then you can do

>>> df.shape()
(10000, 10)

But just remind you that .count() can be very slow for very large table that has not been persisted.

print((df.count(), len(df.columns)))

is easier for smaller datasets.

However if the dataset is huge, an alternative approach would be to use pandas and arrows to convert the dataframe to pandas df and call shape

spark.conf.set("spark.sql.execution.arrow.enabled", "true")
spark.conf.set("spark.sql.crossJoin.enabled", "true")
print(df.toPandas().shape)

I think there is not similar function like data.shape in Spark. But I will use len(data.columns) rather than len(data.dtypes)

I have solved this problem using this code block. Please try it, it works.

import pyspark
def sparkShape(dataFrame):
    return (dataFrame.count(), len(dataFrame.columns))
pyspark.sql.dataframe.DataFrame.shape = sparkShape

print(<Input the Dataframe name which you want the output of>.shape())