Aggregating and grouping

Is a common use case to want to calculate the minimum, maximum, or any other aggregation in a dataset while considering a common set of values in another column. Here, we can use a practice called grouping. Let's try to explain this concept using the following diagram:

Figure 4.6 – Sum values applying grouping

In the previous example, we are summing the sepal_lenght values that are from the same species. Now, let's learn how to use grouping and aggregation in Optimus.

For example, we have the following dataframe:

df = op.load.file("foo.csv")
df.print()

The dataframe contains the following data:

name        job                id
(object)    (object)      (int64)
----------  ----------  ---------
optimus ...