staircase.cov

staircase.cov(collection, where=(<staircase.constants.NegInf object>, <staircase.constants.Inf object>))

Calculates the covariance matrix for a collection of Stairs instances

Parameters

collection: :class:`pandas.Series`, dict, or array-like of :class:`Stairs` values

the stairs instances with which to compute the covariance matrix

lowerint, float or pandas.Timestamp

lower bound of the interval on which to perform the calculation

upperint, float or pandas.Timestamp

upper bound of the interval on which to perform the calculation

Returns

pandas.DataFrame

The covariance matrix

See also

Stairs.cov, staircase.corr

Examples

>>> import staircase as sc
>>> pd.Series([s1, s2, s1+s2])
0    <staircase.Stairs, id=2452772382088, dates=False>
1    <staircase.Stairs, id=2452772381320, dates=False>
2    <staircase.Stairs, id=2452772893512, dates=False>
dtype: object

>>> sc.cov(pd.Series([s1, s2, s1+s2], index=['s1', 's2', 's1+s2']))
              s1         s2      s1+s2
s1      0.687500   0.140496   0.652893
s2      0.140496   0.471074   0.611570
s1+ s2  0.652893   0.611570   1.264463

>>> sc.cov([s1, s2, s1+s2])
          0          1          2
0  0.687500   0.140496   0.652893
1  0.140496   0.471074   0.611570
2  0.652893   0.611570   1.264463

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