为什么在数组的打印语句中出现句号？

Question

我目前正在学习如何使用 python 和 jupyter notebook。我想创建自己的数据集。代码如下（取自本网站：How to create my own datasets using in scikit-learn?）：

import numpy as np
import csv
from sklearn.datasets.base import Bunch

def load_movies_dataset():
    with open('Documents/movies_dataset.csv') as csv_file:
        data_file = csv.reader(csv_file)
        temp = next(data_file)
        n_samples = int(temp[0])
        n_features = int(temp[1])
        data = np.empty((n_samples, n_features))
        target = np.empty((n_samples,), dtype=np.int)

    for i, sample in enumerate(data_file):
        data[i] = np.asarray(sample[:-1], dtype=np.int)
        target[i] = np.asarray(sample[-1], dtype=np.int)

return Bunch(data=data, target=target)

这是我正在使用的 csv 文件：

"6","2","numKicks","numKisses"
"3","104","0"
"2","100","0"
"1","81","0"
"101","10","1"
"99","5","1"
"98","2","1"

此示例根据踢球次数和亲吻次数确定电影是爱情片 (0) 还是动作片 (1)。

这是我用来测试数据集创建的代码：

md = load_movies_dataset()
X = md.data
y = md.target
X

这是输出：

array([[  3., 104.],
   [  2., 100.],
   [  1.,  81.],
   [101.,  10.],
   [ 99.,   5.],
   [ 98.,   2.]])

我的问题是，为什么数组显示中有句号？

Answer 1

它们是小数点。它是一个浮点数组：

>>> x
array([[  3., 104.],
       [  2., 100.],
       [  1.,  81.],
       [101.,  10.],
       [ 99.,   5.],
       [ 98.,   2.]])
>>> y
array([0, 0, 0, 1, 1, 1])
>>> x.dtype
dtype('float64')
>>> 

---

numpy.empty 的默认数据类型是 numpy.float64。