genfromtxt和numpy [英] genfromtxt and numpy

问题描述

我在"file.csv"之类的文件中有数据.我想用np.genfromtxt读取它们，并对某些列(X, Y, Z)进行一些统计，例如平均值，方差等.但是我想对X > 1, Y > 3 Z > 2等进行统计.这是一个简单的示例.

I have data in files such as "file.csv". I would like to read them with np.genfromtxt and do some statistics like average, variance etc. on some columns (X, Y, Z). However I want to make the statistics on for X > 1, Y > 3 Z > 2 etc. This is a simple example here.

这段代码几乎可以产生正确的结果，但是它包含所有X，Y和Z，我想这样做，但要符合上面指定的X，Y，Z条件.

This code produces almost correct results but it includes ALL Xs, Ys and Zs, I want to do the same but with the X,Y,Z conditions i specified above.

#file.csv
X,Y,Z
1,2,3
4,2,5
15,9,1
#

data = np.genfromtxt(file.csv, delimiter=',', dtype=float, unpack=True, skiprows = 0) 
X=data[0];Y=data[1];Z=data[2]
Mean = np.average(X)

->努力取得平均值.但是，我希望只有在X> 1的情况下才能获得平均水平.例如，如何做到这一点?

--> Doing a great job getting the average. However, I want i to get average ONLY IF X > 1 (for example)... How do I make it do so?

推荐答案

您可以使用所谓的"fancy-indexing"(X[X>1])来选择所需的数组部分:

You could use so-called "fancy-indexing", X[X>1], to select the part of the array you want:

import numpy as np
X,Y,Z = np.genfromtxt('file.csv', delimiter=',', dtype=float, unpack=True, skiprows = 0)
print(X)
# [ nan   1.   4.  15.]
print(X[X>1])
# [  4.  15.]
print(np.average(X[X>1]))
# 9.5

要将两个掩码(布尔数组)与按位逻辑和相结合，请使用&运算符:

To combine two masks (boolean arrays) with bit-wise logical-and, use the & operator:

print(np.average(X[(X>1)&(X<10)]))
# 4.0

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