calculate mean of 'n' number of rows

[Ranjan Kumar Sahu]

hii all,

I am trying to calculate the average of n number of rows, for every subsequent rows, in such a way that,

avg1 = avg of 0 to n rows

avg2 = avg of n+1 to 2n rows

and so on.

In pandas, there is groupby function, wherein conditional statement can be incorporated, unlike the groupby function of xarray. (or maybe there is and I dont know yet)

Any ideas how I can achieve this.

any help is appreciated.

ranjan

[Thomas Elliot Gruffydd Nicholas]

Hi Ranjan,

Have you seen the coarsen method? I think you should be able to use something like  .coarsen(dim_name=n).mean() to achieve what you want.

Let us know if that works for you!

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[Ranjan Kumar Sahu]

hii ten,

Thanks for the response.

I have implemented the code. It works!! Without any errors!! But the thing is I expected the length of the dimension (in my case the depth dimension) to be halved compared to original length of the dimension.

        print(np.shape(ds2["Depth"]))

        >>> (58,)

        ds2.coarsen(Depth=2).mean()
        print(np.shape(ds2["Depth"]))

        >>> (58,)

regards

ranjan

[Ranjan Kumar Sahu]

I apologize. it works.

       ds2_m =  ds2.coarsen(Depth=2).mean()

storing it in a new variable solves the issue.

thanks for the help.

[Thomas Elliot Gruffydd Nicholas]

Isn't that just because you haven't assigned your result to a new variable? i.e.

>>> result = ds2.coarsen(Depth=2).mean()
>>> print(result["Depth"].shape)

(You also can use the .shape attribute instead of calling np.shape as I did here)

To view this discussion on the web visit https://groups.google.com/d/msgid/xarray/5139b520-85a2-459d-97ea-fda59f06b5e6n%40googlegroups.com.