Aggregation Functions
Compute sum, mean, min, max, and standard deviation across an entire array or along a specific axis.
What Is Aggregation?
Aggregation boils an array down to a few summary values, like a total or an average. NumPy's built-in functions do this in fast C, no loops needed.
import numpy as np
a = np.array([3, 7, 2, 9, 1, 6])
print('sum:', a.sum()) # 28
print('mean:', a.mean()) # 4.666...
print('max:', a.max()) # 9sum() and cumsum()
Use a.sum() for the total of every element, and np.cumsum for a running total — each spot holds the sum of everything up to it.
import numpy as np
a = np.array([1, 2, 3, 4, 5])
print(a.sum()) # 15
print(np.cumsum(a)) # [ 1 3 6 10 15]All lessons in this course
- Universal Functions (ufuncs)
- Aggregation Functions
- Broadcasting Rules
- Boolean Masking and Fancy Indexing