I am using pandas in Python.
I have a dataframe:
col1 col2 col3 col4 col5 col6 col7 Variance Mean
chr1 1002 NA NA 2 3 4 ......... .........
chr2 1005 2 3 NA NA 6 ........ ..........
I want to take row mean and row variance of every row from column no.3 to 7 and also want to ignore NA while calculating mean and variance.The code I m using for mean is
df['means']=df[[3:7]].mean(axis=1)
But it is giving me weird values of mean at some records and NaN for most values.
How to do this?
Am I using the code for selection of columns correctly or not and how to ignore NA during calculation.
Hi from my experience the statistical library of python is not accurate. Anyway if you are using panda try to omit the column with values like NA. This is the main reason that you are getting weird result.
You may want to try Python numpy
import numpy
prank = []
for(int i =3; i
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