PySpark Online Compiler : Version 3.5.2

In this PySpark Playground, you have access to several sample datasets stored in the /samples/ folder. These datasets can be used to test your PySpark code and understand how to work with real-world data.

Example: `customers.csv`

The customers.csv file is a sample dataset that contains customer information. You can load this file into a DataFrame using PySpark and apply various transformations and actions on it. Below is a code snippet to help you get started:

# Initialize Spark session
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('Spark Playground').getOrCreate()

# Load the customers.csv dataset
df = spark.read.format('csv').option('header', 'true').load('/samples/customers.csv')

# Show the first few rows of the DataFrame
df.show(5)

# Assign the resulting df to df_result variable to display table.
df_result = df

Available Sample Datasets:

customers.csv: Contains customer data with fields like customer ID, name, and purchase history.
sales.csv: Records of sales transactions with fields like transaction ID, date, and amount.
products.csv: Information about products, including product ID, name, and price.

Try it out!

Use the provided datasets to explore various PySpark functions such as select(), filter(), groupBy(), and more. This will help you get hands-on practice with data processing in PySpark.

TABLE STDOUT STDERR

Assign the resulting DataFrame to the df_result variable to display it in this section.