如何将dtype('o')转换为numpy中的dtype(float) ?

I'm looking for a way to read this csv into python 2.7 and turn it into a (3,22000) array. For some reason I haven't been able to do it, no matter which way i try, I either get a groupn of strings in an array that i cant convert or an array seen below that won't convert to floats or allow computations to be done on them. Any help would be appreciated. Thanks

我正在寻找一种方法，将这个csv文件读入python 2.7，并将其转换为(3,22000)数组。由于某种原因，我无法做到这一点，不管我怎么尝试，我要么得到一个数组中的字符串，要么我不能转换，或者在下面看到的数组不会转换为浮点数，或者允许对它们进行计算。如有任何帮助，我们将不胜感激。谢谢

For the record it says the shape is (22000,), which I'm unsure about also.

据记录，它的形状是(22000，)，我也不确定。

In [126]: import csv
import numpy as np

with open("Data.csv") as sd:
ri = []
dv = []
for row in csv.reader(sd):
    if row != ["ccx","ccy","ccz","cellVolumes","Cell Type"]:
        nrow = []
        for val in row[0:3]:
            val = float(val)
            nrow.append(val)
        ri.append(nrow)

        nrow = []
        for val in row[3:4]:
            val = float(val)
            nrow.append(val)
        dv.append(nrow)

ri = np.array(ri)
ri

。

Out[126]: array([[-0.179967, -0.38936, -0.46127], [-0.0633236, -0.407683, -0.542979],
   [-0.125841, -0.494202, -0.412042], ...,
   [-0.0116821, 0.764493, 0.573541], [0.630377, 0.469657, 0.442017],
   [0.248253, 0.615365, 0.354134]], dtype=object

1 个解决方案

#1

(from the helpful comments)

(从有用的评论)

Check the length of those sublists. If they are all the same I'd expect a 2d array; but if they differ (most 3, but some 0, 2,4 etc) then the best it can do is give you a 1d array of 'objects' - the lists.

检查这些子列表的长度。如果它们都是一样的，我期望一个2d数组;但是如果它们不同(大多数是3，但是0、2、4等等)，那么它所能做的最好的事情就是给你一个1d的“对象”数组——列表。

I would just do [len(x) for x in ri] before passing it to np.array. Maybe apply a max and min. A list comprehension like that won't take long.

在将它传递给np数组之前，我只需要(len(x) for x)。也许可以使用max和min，这样的列表理解不会花太长时间。

#1