Question

我得到一个TypeError：

Traceback (most recent call last):
  File "...Transients_tP100us.py", line 20, in <module>
    temp[key] = data[key]["Temperature"].reshape((num_temp, num_dp)).T
TypeError: 'numpy.int32' object does not support item assignment

运行此脚本：

import numpy as np

transient_files = {"50ms": "Transients_50ms.TXT",
                   "500ms": "Transients_500ms.TXT",
                   "5000ms": "Transients_5000ms.TXT"}

num_dp = 513
num_temp = 37

data = {}
time = {}
temp = {}
cap = {}

for key, value in transient_files.items():
    data[key] = np.genfromtxt(value, delimiter=";", names=[
                              "Time", "Temperature", "Capacitance"])

    time[key] = data[key]["Time"].reshape((num_temp, num_dp)).T    
    temp[key] = data[key]["Temperature"].reshape((num_temp, num_dp)).T
    cap[key] = data[key]["Capacitance"].reshape((num_temp, num_dp)).T * 1e-12

如果我仅运行Transient_50ms.TXT文件，则该文件运行无错误，仅抛出了另外两个文件。文件之间的唯一区别是，50ms文件在第三列中没有负值，其他列中没有。因此，在数据文件中有无负值的两行如下所示：

 5.065E-01; 3.270E+02;-1.182E-01
 6.832E-03; 3.391E+02; 7.501E-01

我通过以下方式进行了支票

for i in np.arange(0, len(data[key]["Time"])):
    if type(data[key]["Time"][i]) is not np.float64:
        print(i)

for i in np.arange(0, len(data[key]["Temperature"])):
    if type(data[key]["Temperature"][i]) is not np.float64:
        print(i)

for i in np.arange(0, len(data[key]["Capacitance"])):
    if type(data[key]["Capacitance"][i]) is not np.float64:
        print(i)

查看所有条目是否真的被识别为np.float64（是这种情况）。我想解析数据文件是一个问题，尤其是负值，但是我不知道问题出在哪里以及如何解决。

Answer 1

@SpghttCd的评论改写为

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自从@SpghttCd在评论中回答了该问题以来，我制作了这个答案社区Wiki。

使用numpy解析csv会引发TypeError

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