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
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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