The most advanced ML Observability product in the market
Building an ML platform is nothing like putting together Ikea furniture; obviously, Ikea is way more difficult. However, they both, similarly, include many different parts that help create value when put together. As every organization sets out on a unique path to building its own machine learning platform, taking on the project of building a […]
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 […]
Shuffling rows in a DataFrame means changing the order of rows. In this short how-to article, we will learn how to do this operation in Pandas DataFrames.
We can use the sample method, which returns a randomly selected sample from a DataFrame. If we make the size of the sample the same as the original DataFrame, the resulting sample will be the shuffled version of the original one.
# with n parameter df = df.sample(n=len(df)) # with frac parameter df = df.sample(frac=1)
The frac and n parameters define the size of the sample.