NumPy — Statistics

Basic statistics

import numpy as np

arr = np.array([1, 2, 3, 4, 5])

print(f"Mean: {np.mean(arr)}")
print(f"Median: {np.median(arr)}")
print(f"Std: {np.std(arr)}")
print(f"Var: {np.var(arr)}")

Min/Max

arr = np.array([3, 1, 4, 1, 5, 9, 2, 6])
print(f"Min: {np.min(arr)}")
print(f"Max: {np.max(arr)}")
print(f"Argmin: {np.argmin(arr)}")
print(f"Argmax: {np.argmax(arr)}")

Percentiles

arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
print(f"25th: {np.percentile(arr, 25)}")
print(f"50th: {np.percentile(arr, 50)}")
print(f"75th: {np.percentile(arr, 75)}")

Correlation

x = np.array([1, 2, 3, 4, 5])
y = np.array([2, 4, 5, 4, 5])
print(np.corrcoef(x, y))

Axis

arr = np.array([[1, 2], [3, 4]])
print(np.mean(arr, axis=0))  # Column mean
print(np.mean(arr, axis=1))  # Row mean

Mini Practice

1. Calculate basic stats
2. Find min/max
3. Compute percentiles
4. Use axis parameter

Up Next

Continue with Linear Algebra - Matrix operations.