Hi, With interpolate_na, the following behavior looks like it is non-ideal : import xarray as xr import numpy as np # Example of data showing interpolate_na bug x = np.arange(5) y = np.arange(5) data = np.array([[np.nan, np.nan, np.nan, ...
When performing interpolate_na on a DataArray the attributes are removed. Unless I am doing something incorrect. MCVE Code Sample print(dhi_da) dhi_ds = dhi_ds.interpolate_na(dim='time') print(dhi_da) Output first print statement <xarray...
Interpolate missing valuesDaniel KofflerGregor Laaha
need at least two non-NA values to interpolate 什么是nomogram,R代码就不写了～ 直接来到这个报错点: 在删除数据框中所有含缺失值的情况下,主要问题在于:“ function(x)surv(1*12,lp=x)”这段代码中的1*12出现了问题。假如你的数据都没有达到1*12或者都超过了1*12,那就会出错,也就没有预测价值。。。