Use tolist():
import numpy as np
>>> np.array([[1,2,3],[4,5,6]]).tolist()
[[1, 2, 3], [4, 5, 6]]
Note that this converts the values from whatever numpy type they may have (e.g. np.int32 or np.float32) to the "nearest compatible Python type" (in a list). If you want to preserve the numpy data types, you could call list() on your array instead, and you'll end up with a list of numpy scalars. (Thanks to Mr_and_Mrs_D for pointing that out in a comment.)
The numpy .tolist method produces nested lists if the numpy array shape is 2D.
if flat lists are desired, the method below works.
import numpy as np
from itertools import chain
a = [1,2,3,4,5,6,7,8,9]
print type(a), len(a), a
npa = np.asarray(a)
print type(npa), npa.shape, "\n", npa
npa = npa.reshape((3, 3))
print type(npa), npa.shape, "\n", npa
a = list(chain.from_iterable(npa))
print type(a), len(a), a`
a.flatten().tolist() (or list(a.flatten()) cf discussion above)
np.array(arr.tolist()) == arr; in other words .tolist is sort of a serialization of arr
c = np.array([[1,2,3],[4,5,6]])
list(c.flatten())
tolist() works fine even if encountered a nested array, say a pandas DataFrame;
my_list = [0,1,2,3,4,5,4,3,2,1,0]
my_dt = pd.DataFrame(my_list)
new_list = [i[0] for i in my_dt.values.tolist()]
print(type(my_list),type(my_dt),type(new_list))
Another option
c.ravel()
# or
c.ravel().tolist()
also works.
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tolistwill convert it tofloatss - that's not desired probably. Usinglist(myarray)doesn't suffer from this - why should we prefertolist?myarray.astype(np.int32).tolist()would be an option, and explicit about what you're trying to accomplish. (And lastly,list(array_of_type_float32)doesn't give integers here when I tried it... so I don't know what you're asking.)float32_array = np.array([0.51764709], np.float32); print(float32_array.tolist()); print(list(float32_array))np.array([[0, 'one'], ['two', 3]]).tolist() -> [['0', 'one'], ['two', '3']]