diff options
| -rw-r--r-- | Lib/statistics.py | 26 |
1 files changed, 14 insertions, 12 deletions
diff --git a/Lib/statistics.py b/Lib/statistics.py index db8c581..507a5b2 100644 --- a/Lib/statistics.py +++ b/Lib/statistics.py @@ -107,9 +107,12 @@ A single exception is defined: StatisticsError is a subclass of ValueError. __all__ = [ 'NormalDist', 'StatisticsError', + 'correlation', + 'covariance', 'fmean', 'geometric_mean', 'harmonic_mean', + 'linear_regression', 'mean', 'median', 'median_grouped', @@ -122,9 +125,6 @@ __all__ = [ 'quantiles', 'stdev', 'variance', - 'correlation', - 'covariance', - 'linear_regression', ] import math @@ -882,10 +882,10 @@ def covariance(x, y, /): raise StatisticsError('covariance requires that both inputs have same number of data points') if n < 2: raise StatisticsError('covariance requires at least two data points') - xbar = fmean(x) - ybar = fmean(y) - total = fsum((xi - xbar) * (yi - ybar) for xi, yi in zip(x, y)) - return total / (n - 1) + xbar = fsum(x) / n + ybar = fsum(y) / n + sxy = fsum((xi - xbar) * (yi - ybar) for xi, yi in zip(x, y)) + return sxy / (n - 1) def correlation(x, y, /): @@ -910,11 +910,13 @@ def correlation(x, y, /): raise StatisticsError('correlation requires that both inputs have same number of data points') if n < 2: raise StatisticsError('correlation requires at least two data points') - cov = covariance(x, y) - stdx = stdev(x) - stdy = stdev(y) + xbar = fsum(x) / n + ybar = fsum(y) / n + sxy = fsum((xi - xbar) * (yi - ybar) for xi, yi in zip(x, y)) + s2x = fsum((xi - xbar) ** 2.0 for xi in x) + s2y = fsum((yi - ybar) ** 2.0 for yi in y) try: - return cov / (stdx * stdy) + return sxy / sqrt(s2x * s2y) except ZeroDivisionError: raise StatisticsError('at least one of the inputs is constant') @@ -958,7 +960,7 @@ def linear_regression(regressor, dependent_variable, /): sxy = fsum((xi - xbar) * (yi - ybar) for xi, yi in zip(x, y)) s2x = fsum((xi - xbar) ** 2.0 for xi in x) try: - slope = sxy / s2x + slope = sxy / s2x # equivalent to: covariance(x, y) / variance(x) except ZeroDivisionError: raise StatisticsError('regressor is constant') intercept = ybar - slope * xbar |