numpy数组:按一列分组，对另一列求和 [英] Numpy array: group by one column, sum another

问题描述

我有一个看起来像这样的数组:

I have an array that looks like this:

 array([[ 0,  1,  2],
        [ 1,  1,  6],
        [ 2,  2, 10],
        [ 3,  2, 14]])

我想对第三列中第二列中具有相同值的值求和，所以结果是:

I want to sum the values of the third column that have the same value in the second column, so the result is something is:

 array([[ 0,  1,  8],
        [ 1,  2, 24]])

我开始对此进行编码，但是我坚持了这一金额:

I started coding this but I'm stuck with this sum:

import numpy as np
import sys

inFile = sys.argv[1]

with open(inFile, 'r') as t:
    f = np.genfromtxt(t, delimiter=None, names =["1","2","3"])

f.sort(order=["1","2"])
if value == previous.value:
   sum(f["3"])

推荐答案

您可以使用pandas将算法矢量化:

You can use pandas to vectorize your algorithm:

import pandas as pd, numpy as np

A = np.array([[ 0,  1,  2],
              [ 1,  1,  6],
              [ 2,  2, 10],
              [ 3,  2, 14]])

df = pd.DataFrame(A)\
       .groupby(1, as_index=False)\
       .sum()\
       .reset_index()

res = df[['index', 1, 2]].values

结果

array([[ 0,  1,  8],
       [ 2,  2, 24]], dtype=int64)

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