Convert structured array with various numeric data types to regular array
Question: Suppose I have a NumPy structured array with various numeric datatypes. As a
basic example,

    
    
    my_data = np.array( [(17, 182.1),  (19, 175.6)],  dtype='i2,f4')
    

How can I cast this into a regular NumPy array of floats?

From [this answer](http://stackoverflow.com/a/5957455/2223706), I know I could
use

    
    
    np.array(my_data.tolist())
    

but apparently it is slow since you "convert an efficiently packed NumPy array
to a regular Python list".


Answer: You can do it easily with Pandas:

    
    
    >>> import pandas as pd
    >>> pd.DataFrame(my_data).values
    array([[  17.       ,  182.1000061],
           [  19.       ,  175.6000061]], dtype=float32)
    

