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Orange.statistics.basic.rst

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.. py:currentmodule:: Orange.statistics.basic

.. index:: Basic Statistics for Continuous Features

Basic Statistics for Continuous Features (basic)

The are two simple classes for computing basic statistics for continuous features, such as their minimal and maximal value or average: :class:`Orange.statistics.basic.Variable` holds the statistics for a single variable and :class:`Orange.statistics.basic.Domain` behaves like a list of instances of the above class for all variables in the domain.

Computes and stores minimal, maximal, average and standard deviation of a variable. It does not include the median or any other statistics that can be computed on the fly, without remembering the data; such statistics can be obtained classes from module :obj:`Orange.statistics.distribution`.

Instances of this class are seldom constructed manually; they are more often returned by :obj:`Domain` described below.

.. attribute:: variable

    The variable to which the data applies.

.. attribute:: min

    Minimal value encountered

.. attribute:: max

    Maximal value encountered

.. attribute:: avg

    Average value

.. attribute:: dev

    Standard deviation

.. attribute:: n

    Number of instances for which the value was defined.
    If instances were weighted, :obj:`n` holds the sum of weights

.. attribute:: sum

    Weighted sum of values

.. attribute:: sum2

    Weighted sum of squared values

.. method:: add(value[, weight=1])

    Add a value to the statistics: adjust :obj:`min` and :obj:`max` if
    necessary, increase :obj:`n` and recompute :obj:`sum`, :obj:`sum2`,
    :obj:`avg` and :obj:`dev`.

    :param value: Value to be added to the statistics
    :type value: float
    :param weight: Weight assigned to the value
    :type weight: float

statistics.basic.Domain behaves like an ordinary list, except that its elements can also be indexed by variable names or descriptors.

.. method:: __init__(data[, weight=None])

    Compute the statistics for all continuous variables in the data, and put
    :obj:`None` to the places corresponding to variables of other types.

    :param data: A table of instances
    :type data: Orange.data.Table
    :param weight: The id of the meta-attribute with weights
    :type weight: `int` or none

.. method:: purge()

    Remove the :obj:`None`'s corresponding to non-continuous features; this
    truncates the list, so the indices do not respond to indices of
    variables in the domain.

part of :download:`distributions-basic-stat.py <code/distributions-basic-stat.py>`

.. literalinclude:: code/distributions-basic-stat.py
    :lines: 1-10

Output:

     feature   min   max   avg
sepal length 4.300 7.900 5.843
 sepal width 2.000 4.400 3.054
petal length 1.000 6.900 3.759
 petal width 0.100 2.500 1.199

part of :download:`distributions-basic-stat.py <code/distributions-basic-stat.py>`

.. literalinclude:: code/distributions-basic-stat.py
    :lines: 11-

Output:

5.84333467484