[Numpy-discussion] Data standardizing

Jonathan Rocher jrocher at enthought.com
Wed Apr 13 09:50:13 EDT 2011


Hi,

I assume you have this data in a txt file, correct? You can load up all of
it in a numpy array using
import numpy as np
data = np.loadtxt("climat_file.txt", skiprows = 1)

Then you can compute the mean you want by taking it on a slice of the data
array. For example, if you want to compute the mean of your data in Jan for
1950-1970 (say including 1970)
mean1950_1970 = data[1950:1971,1].mean()

Then the std deviation you want could be computed using
my_std = np.sqrt(np.mean((data[:,1]-mean1950_1970)**2))

Hope this helps,
Jonathan

On Tue, Apr 12, 2011 at 1:48 PM, Climate Research <climateforu at gmail.com>wrote:

> Hi
> I am purely new to python and numpy..  I am using python for doing
> statistical calculations to Climate data..
>
> I  have  a  data set in the following format..
>
> Year  Jan      feb       Mar    Apr.................   Dec
> 1900  1000    1001       ,        ,                         ,
> 1901  1011    1012       ,        ,                         ,
> 1902  1009    1007       ,                                  ,
> ,,,,        ,           '          ,        ,                         ,
> ,,,,        ,           ,
> 2010  1008    1002       ,        ,                         ,
>
> I actually want to standardize each of these values with corresponding
> standard deviations for  each monthly data column..
> I have found out the standard deviations for each column..  but now i need
> to  find the standared deviation  only for a prescribed mean value
> ie,  when i am finding the standared deviation for the January data
> column..  the mean should be calculated only for the january data, say from
> 1950-1970. With this mean  i  want to calculate the SD  for entire column.
> Any help will be appreciated..
>
>
>
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>


-- 
Jonathan Rocher, PhD
Scientific software developer
Enthought, Inc.
jrocher at enthought.com
1-512-536-1057
http://www.enthought.com
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