Learn how to efficiently convert a PySpark DataFrame to a Pandas DataFrame in Databricks, enabling data scientists to leverage the familiar Pandas API for advanced feature engineering tasks.
Table of Contents
Question
A data scientist has been given an incomplete notebook from the data engineering team. The notebook uses a Spark DataFrame spark_df on which the data scientist needs to perform further feature engineering. Unfortunately, the data scientist has not yet learned the PySpark DataFrame API.
Which of the following blocks of code can the data scientist run to be able to use the pandas API on Spark?
A. import pyspark.pandas as ps
df = ps.DataFrame(spark_df)
B. import pyspark.pandas as ps
df = ps.to_pandas(spark_df)
C. spark_df.to_sql()
D. import pandas as pd
df = pd.DataFrame(spark_df)
E. spark_df.to_pandas()
Answer
E. spark_df.to_pandas()
Explanation
When a data scientist receives a PySpark DataFrame (spark_df) from the data engineering team but is more comfortable using the Pandas API for feature engineering, they can easily convert the PySpark DataFrame to a Pandas DataFrame using the to_pandas() method directly on the PySpark DataFrame object.
Here’s how it works:
df = spark_df.to_pandas()
This single line of code converts the PySpark DataFrame spark_df into a Pandas DataFrame df, allowing the data scientist to use the familiar Pandas API for further data manipulation and feature engineering.
Let’s go through the other options and explain why they are incorrect:
A. import pyspark.pandas as ps; df = ps.DataFrame(spark_df)
This code attempts to create a Pandas DataFrame using the pyspark.pandas library, but it is not the correct way to convert a PySpark DataFrame to a Pandas DataFrame.
B. import pyspark.pandas as ps; df = ps.to_pandas(spark_df)
The pyspark.pandas library does not have a to_pandas() function. This code will raise an AttributeError.
C. spark_df.to_sql()
The to_sql() method is used to write a PySpark DataFrame to a SQL database. It does not convert the DataFrame to a Pandas DataFrame.
D. import pandas as pd; df = pd.DataFrame(spark_df)
This code attempts to create a Pandas DataFrame directly from the PySpark DataFrame, but it will not work because the PySpark DataFrame is not compatible with the Pandas DataFrame constructor.
In summary, the most straightforward and correct way to convert a PySpark DataFrame to a Pandas DataFrame in Databricks is by using the to_pandas() method directly on the PySpark DataFrame object (Option E).
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