How to keep column names when converting from pandas to numpy

Question

According to this post, I should be able to access the names of columns in an ndarray as a.dtype.names

Howevever, if I convert a pandas DataFrame to an ndarray with df.a

Answer 1

Consider a DF as shown below:

X = pd.DataFrame(dict(one=['Strawberry', 'Fields', 'Forever'], two=[1,2,3]))
X

Provide a list of tuples as data input to the structured array:

arr_ip = [tuple(i) for i in X.as_matrix()]

Ordered list of field names:

dtyp = np.dtype(list(zip(X.dtypes.index, X.dtypes)))

Here, X.dtypes.index gives you the column names and X.dtypes it's corresponding dtypes which are unified again into a list of tuples and fed as input to the dtype elements to be constructed.

arr = np.array(arr_ip, dtype=dtyp)

gives:

arr
# array([('Strawberry', 1), ('Fields', 2), ('Forever', 3)], 
#       dtype=[('one', 'O'), ('two', '

and

arr.dtype.names
# ('one', 'two')