如何在python中将数组转换为数组

Question

我有一个问题，我有这行：

s=codecs.open('file.csv', encoding="utf-8").read()
array1=np.asarray(s.splitlines())

print(array1)

我变成了这个数组的结果：

['39, State-gov, 77516, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K'
 '50, Self-emp-not-inc, 83311, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 13, United-States, <=50K'
 '38, Private, 215646, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K'
 ...
 '36, Private, 146311, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K'
 '47, Self-emp-not-inc, 159869, Doctorate, 16, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K'
 '21, Private, 204641, Some-college, 10, Never-married,']

我想要的是把它变成：

[['39', 'State-gov', '77516', 'Bachelors', '13',....,'<=50K]['50'...]]

现在也是一个包含一行和多列的数组，每列是一个字符串，我想将每一列更改为一行，其中包含具有字符数的列数..

我没有任何想法，我想拆分它但我不能

有人可以帮我吗？

谢谢！

Answer 1

方法一：从文件中生成想要的数组

如果您是从 csv 开始，您不妨使用np.genfromtxt：

如果filename.csv 看起来像：

39, State-gov, 77516, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K
50, Self-emp-not-inc, 83311, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 13, United-States, <=50K

然后：

new_arr = np.genfromtxt('filename.csv', dtype='str')

>>> new_arr
array([['39,', 'State-gov,', '77516,', 'Bachelors,', '13,',
        'Never-married,', 'Adm-clerical,', 'Not-in-family,', 'White,',
        'Male,', '2174,', '0,', '40,', 'United-States,', '<=50K'],
       ['50,', 'Self-emp-not-inc,', '83311,', 'Bachelors,', '13,',
        'Married-civ-spouse,', 'Exec-managerial,', 'Husband,', 'White,',
        'Male,', '0,', '0,', '13,', 'United-States,', '<=50K']],
      dtype='<U19')

方法 2：修复数组：

否则，如果你已经有数组：

>>> arr
array(['39, State-gov, 77516, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K',
       '50, Self-emp-not-inc, 83311, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 13, United-States, <=50K'],
      dtype='<U133')

您可以遍历它并拆分每个字符串以获得您想要的输出：

new_arr = np.array([i.split() for i in arr])

>>> new_arr
array([['39,', 'State-gov,', '77516,', 'Bachelors,', '13,',
        'Never-married,', 'Adm-clerical,', 'Not-in-family,', 'White,',
        'Male,', '2174,', '0,', '40,', 'United-States,', '<=50K'],
       ['50,', 'Self-emp-not-inc,', '83311,', 'Bachelors,', '13,',
        'Married-civ-spouse,', 'Exec-managerial,', 'Husband,', 'White,',
        'Male,', '0,', '0,', '13,', 'United-States,', '<=50K']],
      dtype='<U19')