np.corrcoef()
Correlation says how closely two sets of numbers move together, from -1 to +1.
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Syntax
corr = np.corrcoef(x, y)np.corrcoef()
np.corrcoef returns a correlation matrix. Values near +1 mean the variables rise together, near -1 mean one rises as the other falls, and near 0 mean no linear relationship. The diagonal is always 1.
Note:
The off-diagonal entry [0, 1] is the correlation between the two inputs.
Example: np.corrcoef()
import numpy as np
hours = np.array([1, 2, 3, 4, 5])
score = np.array([52, 58, 65, 70, 78])
r = np.corrcoef(hours, score)
print(r.round(3))
print("r =", r[0, 1].round(3))
# Output:
# [[1. 0.998]
# [0.998 1. ]]
# r = 0.998Related Topics
Common Mistakes
- Reading correlation as causation
- Forgetting it only detects linear relationships
- Passing columns when NumPy expects rows
Chapter Summary
- corrcoef returns a matrix
- Range is -1 to +1
- Diagonal is 1
- Rows are treated as variables
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