将大量列表转换为数据框

Question

我想做以下事情：

data = [1,2,3,4,5,6,7,8,9]

import pandas as pd
import numpy as np

df = pd.DataFrame(np.array(data).reshape(3,3), columns = list("abc"))

...

   a  b  c
0  1  2  3
1  4  5  6
2  7  8  9

针对：

data = [[[69, 2.0], [69, 2.0], [64, 3.872983346207417], [71, 1.4142135623730951], [80, 4.0]],
        [[69, 2.0], [69, 2.0], [64, 3.872983346207417], [71, 1.4142135623730951], [80, 4.0]], 
        [[69, 2.0], [69, 2.0], [64, 3.872983346207417], [71, 1.4142135623730951], [80, 4.0]]]

import pandas as pd
import numpy as np

df = pd.DataFrame(np.array(data).reshape([[[2], [2], [2], [2], [2]]]), columns = list("abcde"))

但是代码中存在问题：

Traceback (most recent call last):
  File "script.py", line 9, in <module>
    df = pd.DataFrame(np.array(data).reshape([[[2], [2], [2], [2], [2]]]), columns = list("abcde"))
TypeError: 'list' object cannot be interpreted as an integer

有没有建议？

注意：更大的数据呈指数增长

Answer 1

喜欢吗？

df = pd.DataFrame(data= data)
df.columns = list("abcde")

输出：

           a          b                        c                         d         e
0  [69, 2.0]  [69, 2.0]  [64, 3.872983346207417]  [71, 1.4142135623730951] [80, 4.0]
1  [69, 2.0]  [69, 2.0]  [64, 3.872983346207417]  [71, 1.4142135623730951] [80, 4.0]
2  [69, 2.0]  [69, 2.0]  [64, 3.872983346207417]  [71, 1.4142135623730951] [80, 4.0]

Answer 2

尝试不添加reshape

pd.DataFrame(data, columns = list("abcde"))
           a          b  ...                         d          e
0  [69, 2.0]  [69, 2.0]  ...  [71, 1.4142135623730951]  [80, 4.0]
1  [69, 2.0]  [69, 2.0]  ...  [71, 1.4142135623730951]  [80, 4.0]
2  [69, 2.0]  [69, 2.0]  ...  [71, 1.4142135623730951]  [80, 4.0]
[3 rows x 5 columns]