[Numpy] How to store different data type in one numpy array?

[snippsat]

Example like this.

>>> import numpy as np
>>>
>>> dtype = [('date', 'datetime64[D]'), ('value', 'float64'), ('code', 'U3')]
>>> n = np.array([('2024-03-22', 71.0, 'ceh'), ('2024-03-23', 63.0, 'abc')], dtype=dtype)
>>> n
array([('2024-03-22', 71., 'ceh'), ('2024-03-23', 63., 'abc')],
      dtype=[('date', '<M8[D]'), ('value', '<f8'), ('code', '<U3')])

String of up to 3 characters <U3.

>>> n = np.array([('2024-03-22', 71.0, 'cehar'), ('2024-03-23', 63.0, 'abchhhhhhhhhh')], dtype=dtype)
>>> n
array([('2024-03-22', 71., 'ceh'), ('2024-03-23', 63., 'abc')],
      dtype=[('date', '<M8[D]'), ('value', '<f8'), ('code', '<U3')])

To Pandas dataFrame,as Panda i build on NumPy in bottom it seamlessly transfer over.

>>> import pandas as pd
>>> 
>>> df = pd.DataFrame(n)
>>> df
        date  value code
0 2024-03-22   71.0  ceh
1 2024-03-23   63.0  abc