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 <[email protected]>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.
[email protected]
1-512-536-1057
http://www.enthought.com
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