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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 […]
DataFrame is a two-dimensional data structure, which consists of labeled rows and columns. The number of rows and columns give us the shape of the DataFrame, and therefore is an indication of the data size. In this short how-to article, we will learn how to find the row count of Pandas and PySpark DataFrames.
There are two ways of getting the row count. The first one is the built-in len function of Python, which can be applied to different data structuctures. For instance, we can use the len function to find the number of items in a list. When applied to a DataFrame, it gives us the row count.
The other one is the shape method, which returns a tuple that contains both the number of rows and columns. We can get the row count by selecting the first item of the tuple returned by the shape method.
The count function gives us the row count.