The most advanced ML Observability platform
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 […]
Start integrating our products and tools.
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 […]
We sometimes want to have particular columns next to each other. In this short how-to article, we will learn how to change the order of columns in Pandas and PySpark DataFrames.
We can change the order of columns by reassigning the DataFrame with columns in the desired order.
df = df[["f1","f2","f3","f4"]]
In order to view the entire column list, we can create a list of column names by using the list constructor of Python and the columns method of Pandas.
col_list = list(df.columns)
The same approach is valid on PySpark DataFrames. We can use the select method to reassign the DataFrame with columns in the desired order.
df = df.select(["f1","f2","f3","f4"])
The columns method in PySpark returns a list of columns so we do not need to use the list constructor.
col_list = df.columns