如何将 200 列 numpy 数组转换为 dataframe？

Question

I have a numpy with 200 columns. Now, I want to store this with the column names in a datagram. How do I do this?

array([[0.47692407, 0.29395011, 0.54361545, ..., 0.        , 0.69314718,
        0.        ],
       [0.        , 0.41974993, 0.40546511, ..., 0.        , 0.69314718,
        0.        ],
       [0.47692407, 0.53776803, 0.54361545, ..., 0.        , 0.69314718,...]

#column names
df.columns=['a','b',.......'200th column name']

I have something like: 
pd.DataFrame(arr, columns=df.columns) but i get an error: "AttributeError: 'numpy.ndarray' object has no attribute 'columns'"

When I searched, I mostly find examples with are concerned with a few column names which makes it easier if manually coded. In my situation, it needs to be more programmatic due to the high number of columns. Please advise.

Answer 1

You can generate dynamically columns with a list comprehension iterating on the number of columns.

import numpy as np
import pandas as pd
dd = np.reshape(np.arange(20), (5,4))
pd.DataFrame(dd, columns=['col{0:03d}'.format(k) for k in range(dd.shape[1])])

That gives:

   col000  col001  col002  col003
0       0       1       2       3
1       4       5       6       7
2       8       9      10      11
3      12      13      14      15
4      16      17      18      19