在列上过滤numpy矩阵 [英] filtering numpy matrix on a column

问题描述

我有一个如下的numpy矩阵:

I have a numpy matrix as follows:

data = np.matrix(
      "5 3 1;"
      "4 4 1;"
      "6 4 1;"
      "8 2 1;"
      "3 5 1;"
      "1 7 1;"
      "5 4 1;"
      "0 1 0;"
      "2 0 0")
# Output:
matrix([[5, 3, 1],
    [4, 4, 1],
    [6, 4, 1],
    [8, 2, 1],
    [3, 5, 1],
    [1, 7, 1],
    [5, 4, 1],
    [0, 1, 0],
    [2, 0, 0]])

我想要的是在值为1的第三列上过滤矩阵；也就是说，我不想获取第三个值为0的行.总之，我想提取下面的矩阵:

what I want is to filter the matrix on the third column whose value is 1; that is, I do not want to get the rows whose 3rd value is 0. In short, I want to extract the matrix below:

matrix([[5, 3, 1],
    [4, 4, 1],
    [6, 4, 1],
    [8, 2, 1],
    [3, 5, 1],
    [1, 7, 1],
    [5, 4, 1]])

我尝试了几种组合来过滤它；但他们都没有为我工作.例如，以下代码将零行排除在外，但仅返回第一列.

I tried a few combinations to filter it; but none of them worked for me. For instance, the following code rules out the rows with zero, but it returns only the first column.

data[data[:,2]>0]
#Output: 
matrix([[5, 4, 6, 8, 3, 1, 5]])

是否可以在不显式编写循环语句的情况下过滤此矩阵?

Is there a way to filter this matrix without explicitly writing loop statements?

推荐答案

使用np.array代替np.matrix，您可以进行简单的掩码索引编制，例如:

Using np.array instead of np.matrix allows you to do a simple mask indexing like:

a = a[a[:, 2] != 0]

要将np.matrix转换为np.array，您可以执行以下操作:

to convert from np.matrix to np.array you can do:

a = np.asarray(a)    

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