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We’re super excited to share that Aporia is now the first ML observability offering integration to the Databricks Lakehouse Platform. This partnership means that you can now effortlessly automate your data pipelines, monitor, visualize, and explain your ML models in production. Aporia and Databricks: A Match Made in Data Heaven One key benefit of this […]
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We’re excited 😁 to share that Forbes has named Aporia a Next Billion-Dollar Company. This recognition comes on the heels of our recent $25 million Series A funding and is a huge testament that Aporia’s mission and the need for trust in AI are more relevant than ever. We are very proud to be listed […]
In this short how-to article, we will learn how to select multiple columns in Pandas and PySpark DataFrames.
We can select multiple columns by writing them in a list.
cols = ["f2", "f4"] df[cols]
The iloc method can be used for selecting columns based on their indices. Consider you have a DataFrame with 30 columns and you want to select the first 10. You can perform this task as follows:
# Select the first 10 columns df.iloc[:,:10] # Select from the second to fifth df.iloc[:,2:5]
The select function can be used for selecting multiple columns from a PySpark DataFrame.
# first method df.select("f1", "f2") # second method df.select(df.f1, df.f2)
