从Python中的数组中提取特定值

Question

I want to calculate means and averages in a data set, but for many reasons that I can't go into here, my array contains my values and some "filler" values (which are currently set to -1000).

How can I calculate the mean (for example) on the non -1000 values?

res=[-1000 for x in range(0,10)]
res[1]=2
res[5]=3
res[7]=4
#something like this?
np.mean(res>-1000)

#the result should be the mean value of 2,3 and 4 (3)

MVCE

res=[1.0, 1.0, 1.0, 1.0, 1.0, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000, -1000]
#for instance
print(np.mean(res[res > -1000]))

Answer 1

Since you tagged numpy , you should use it for indexing / slicing. Here's an example:

res = np.array([-1000 for x in range(0,10)])
res[1]=2
res[5]=3
res[7]=4

output = np.mean(res[res > -1000])  # 3.0

Read the numpy docs for more details on indexing logic.

Answer 2

Why use another library when you have your friend filter method

import statistics
number_list = [2, -1000, 3, 4, -1000, -1000]
not_1000 = list(filter(lambda x: x != -1000, number_list))
not_1000_mean = statistics.mean(not_1000)