Functions, Users, and Comparative Analysis
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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 […]
Fundamentals of ML observability
Metrics, feature importance and more
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 add an empty column to Pandas and PySpark DataFrames.
We can create an empty column by assigning an empty string as follows:
df["f4"] = ""
The logic is the same as Pandas but the implementation is a bit different. We can assign an empty string to a new column as follows:
from pyspark.sql import functions as F
df = df.withColumn("f4", F.lit(""))