Question

我有一个2d-Numpy数组，基本上包含一个标签值对。我已将这些基质中的几个结合起来，但我希望将标签四舍五入到小数点后4位并对这些值求和，这样：

[[70.00103, 1],
[70.02474, 1],
[70.02474, 1],
[70.024751, 1],
[71.009100, 1],
[79.0152, 1],
[79.0152633, 1],
[79.0152634, 1]]

变为

[[70.001, 1],
[70.0247, 2],
[70.0248, 1],
[71.0091, 1],
[79.0152, 1],
[79.0153, 2]]

关于如何使用numpy或pandas快速完成此任务的任何想法？谢谢！

Answer 1

在[10]中：

var lastY = 0;

var render = function () {

    if (bgReady) 
        ctx.drawImage(bgImage, 0, 0);    

    if (carReady) 
        ctx.drawImage(carImage, car.x, car.y, (carImage.width / 100 * 50), (carImage.height / 100 * 50));    

    var deltaY = car.y - lastY;

    carImage.width = carImage.width - deltaY;
    carImage.height = carImage.height - deltaY;

    lastY = car.y;
};

输出[10]：

import numpy as np
x=np.array([[70.00103, 1],[70.02474, 1],[70.02474, 1],[70.024751, 1],[71.009100, 1],[79.0152, 1],[79.0152633, 1],[79.0152634,1]])
x[:,0]=x[:,0].round(4)
x

在[14]中：

 array([[ 70.001 ,   1.    ],
           [ 70.0247,   1.    ],
           [ 70.0247,   1.    ],
           [ 70.0248,   1.    ],
           [ 71.0091,   1.    ],
           [ 79.0152,   1.    ],
           [ 79.0153,   1.    ],
           [ 79.0153,   1.    ]])

缺货[14]：

import pandas as pd
pd.DataFrame(x).groupby(0).sum()

Answer 2

这是np.around的用途：

>>> A=np.array([[70.00103, 1],
... [70.02474, 1],
... [70.02474, 1],
... [70.024751, 1],
... [71.009100, 1],
... [79.0152, 1],
... [79.0152633, 1],
... [79.0152634, 1]])
>>> 
>>> np.around(A, decimals=4)
array([[ 70.001 ,   1.    ],
       [ 70.0247,   1.    ],
       [ 70.0247,   1.    ],
       [ 70.0248,   1.    ],
       [ 71.0091,   1.    ],
       [ 79.0152,   1.    ],
       [ 79.0153,   1.    ],
       [ 79.0153,   1.    ]])

标签值对2d-numpy数组中的圆形标签和总和值

2 个答案: