Question

in excel there is a frequency function:

The Excel FREQUENCY function This
useful function can analyse a series
of values and summarise them into a
number of specified ranges. For
example the heights of some children
can be grouped in to four categories
of [Less than 150cm]; [151 – 160cm];
[161 – 170cm]; [More than 170cm].

Would you like to learn more?

Excel 2003 Formulas by John Walkenbach
(with CD)

FREQUENCY() is an unusual array
function and it works differently to
most other normal functions. It can
not simply be typed into a cell or
even entered properly using the Excel
Function Wizard.

Note that this function does not
analyse values into categories e.g.
household expenditure into groups such
as gas, electricity, water, rates etc.
To perform this kind of analysis an
Advanced Filter may be appropriate.

The frequency function has two
arguments – the first is the range of
cells containing values to be
analysed; the second is the range of
cells containing the upper values of
each group banding. e.g.
=FREQUENCY(A3:A120, B6:B10)

The second argument (the group upper
limits) will exclude any values which
exceed the highest category or
banding. The function allows you to
take account of this and extend the
range of analysis to an additional
category which contains all values
that exceed the specified upper limit.

http://www.meadinkent.co.uk/xlfreq.htm

is there such a thing in python?

Answer 1

import numpy
numpy.histogram( [ <data> ], [ <bins> ] )

Docs:

numpy.histogram(a, bins=10, range=None, normed=False, weights=None)

Compute the histogram of a set of data.
Parameters:

a : array_like
Input data. The histogram is computed over the flattened array.

bins : int or sequence of scalars, optional
If bins is an int, it defines the number of equal-width bins in the
given range (10, by default). If bins
is a sequence, it defines the bin
edges, including the rightmost edge,
allowing for non-uniform bin widths.

range : (float, float), optional
The lower and upper range of the bins. If not provided, range is
simply (a.min(), a.max()). Values
outside the range are ignored.

normed : bool, optional
If False, the result will contain the number of samples in each
bin. If True, the result is the value
of the probability density function at
the bin, normalized such that the
integral over the range is 1. Note
that the sum of the histogram values
will not be equal to 1 unless bins of
unity width are chosen; it is not a
probability mass function.

weights : array_like, optional
An array of weights, of the same shape as a. Each value in a only
contributes its associated weight
towards the bin count (instead of 1).
If normed is True, the weights are
normalized, so that the integral of
the density over the range remains 1

Returns:

hist : array
The values of the histogram. See normed and weights for a
description of the possible semantics.

bin_edges : array of dtype float
Return the bin edges (length(hist)+1).

You may have to install numpy first.