I'm trying to write a function to find the mean of an attribute for values that only fall within a specific class.
Below is my code:
`mean=0
total=0
count=0
for i in range(len(training_data)):
if (training_data[i,334])==0:
if training_data[i,2]<>None:
total+=training_data[i,2]
count+=1
mean=total/count`
However, my attribute has some null values in it. I am working with numpy, and the null values are being coded as "NaN". In my function above, even though I am specifically specifying that the value cannot be equal to "None", which is Python's equivalent to null, my "total" attribute continues to show up as 'nan'. I have tried many different equivalents to "None" and have not been able to get a value for the total variable other than 'nan'. Is there something obvious I'm missing? Thank you in advance!
With the power of numpy your code can be trimmed to 2 lines:
idx = training_data[:,334] == 0
mean = np.nanmean(training_data[idx, 2])
idx here is the boolean array which is True for the indices of rows falling into specific class, and np.nanmean calculates the mean value ignoring NaNs.
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