A PySpark Dataframe is a distributed group of data arranged into columns and is similar to a relational table in Spark SQL. Dataframes are the common data structures used in modern data analytics. Moreover, this dataframe is also similar to the Pandas framework.
PySpark is much faster in running various operations than Pandas in dealing large datasets. It processes data with 100x speed than Pandas.
If you are familiar with programming skills like Python, SQL, and the fundamentals of Spark, then you can learn PySpark quickly.
PySpark is Python API and an open-source framework with real-time libraries and supports processing large datasets. It is not a programming language but a Python API.
Using PySpark, we can write similar commands like SQL and Python to analyze data. Further, we can also use PySpark through separate Python scripts by developing SparkContext within the script and running it using bin/pyspark.