RunStats API Reference

class runstats.Statistics

Compute statistics in a single pass.

Computes the minimum, maximum, mean, variance, standard deviation, skewness, and kurtosis. Statistics objects may also be added together and copied.

Based entirely on the C++ code by John D Cook at http://www.johndcook.com/skewness_kurtosis.html

__add__

Add two Statistics objects together.

__copy__()

Copy Statistics object.

__deepcopy__()

Copy Statistics object.

__eq__

x.__eq__(y) <==> x==y

__ge__

x.__ge__(y) <==> x>=y

__gt__

x.__gt__(y) <==> x>y

__iadd__

Add another Statistics object to this one.

__imul__

Multiply by a scalar to change Statistics weighting in-place.

__init__

Initialize Statistics object.

Iterates optional parameter iterable and pushes each value into the statistics summary.

__le__

x.__le__(y) <==> x<=y

__len__

Number of values that have been pushed.

__lt__

x.__lt__(y) <==> x<y

__mul__

Multiply by a scalar to change Statistics weighting.

__ne__

x.__ne__(y) <==> x!=y

__new__(S, ...) → a new object with type S, a subtype of T
__radd__

x.__radd__(y) <==> y+x

__rmul__

x.__rmul__(y) <==> y*x

clear()

Clear Statistics object.

copy()

Copy Statistics object.

fromstate()

Return Statistics object from state.

get_state()

Get internal state.

kurtosis()

Kurtosis of values.

maximum()

Maximum of values.

mean()

Mean of values.

minimum()

Minimum of values.

push()

Add value to the Statistics summary.

set_state()

Set internal state.

skewness()

Skewness of values.

stddev()

Standard deviation of values (with ddof degrees of freedom).

variance()

Variance of values (with ddof degrees of freedom).

class runstats.Regression

Compute simple linear regression in a single pass.

Computes the slope, intercept, and correlation. Regression objects may also be added together and copied.

Based entirely on the C++ code by John D Cook at http://www.johndcook.com/running_regression.html

__add__

Add two Regression objects together.

__copy__()

Copy Regression object.

__deepcopy__()

Copy Regression object.

__eq__

x.__eq__(y) <==> x==y

__ge__

x.__ge__(y) <==> x>=y

__gt__

x.__gt__(y) <==> x>y

__iadd__

Add another Regression object to this one.

__init__

Initialize Regression object.

Iterates optional parameter iterable and pushes each pair into the regression summary.

__le__

x.__le__(y) <==> x<=y

__len__

Number of values that have been pushed.

__lt__

x.__lt__(y) <==> x<y

__ne__

x.__ne__(y) <==> x!=y

__new__(S, ...) → a new object with type S, a subtype of T
__radd__

x.__radd__(y) <==> y+x

clear()

Clear Regression object.

copy()

Copy Regression object.

correlation()

Correlation of values (with ddof degrees of freedom).

fromstate()

Return Regression object from state.

get_state()

Get internal state.

intercept()

Intercept of values (with ddof degrees of freedom).

push()

Add a pair (x, y) to the Regression summary.

set_state()

Set internal state.

slope()

Slope of values (with ddof degrees of freedom).