scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
References
[R26]
count_tied_groups(x, use_missing=False)
Counts the number of tied values in x, and returns a dictionary
(nb of ties: nb of groups).
Examples
Parameters
x : sequence
Sequence of data on which to counts the ties
use_missing : boolean
Whether to consider missing values as tied.
>>> z = [0, 0, 0, 2, 2, 2, 3, 3, 4, 5, 6]
>>> count_tied_groups(z)
>>> {2:1, 3:2}
>>> # The ties were 0 (3x), 2 (3x) and 3 (2x)
>>> z = ma.array([0, 0, 1, 2, 2, 2, 3, 3, 4, 5, 6])
>>> count_tied_groups(z)
>>> {2:2, 3:1}
>>> # The ties were 0 (2x), 2 (3x) and 3 (2x)
>>> z[[1,-1]] = masked
>>> count_tied_groups(z, use_missing=True)
>>> {2:2, 3:1}
>>> # The ties were 2 (3x), 3 (2x) and masked (2x)
describe(a, axis=0)
Computes several descriptive statistics of the passed array.
Parameters
a : array
axis : int or None
Returns
(size of the data (discarding missing values), :
(min, max), arithmetic mean, unbiased variance, biased skewness, biased kurtosis)
f_oneway(*args)
Performs a 1-way ANOVA, returning an F-value and probability given any number of groups. From Heiman,
pp.394-7.
Usage: f_oneway (*args) where *args is 2 or more arrays, one per
treatment group
Returns: f-value, probability
f_value_wilks_lambda(ER, EF, dfnum, dfden, a, b)
Calculation of Wilks lambda F-statistic for multivarite data, per Maxwell & Delaney p.657.
find_repeats(arr)
672 Chapter 3. Reference