def test_applymap(dtype):
size = 500
lhs_arr = np.random.random(size).astype(dtype)
lhs_col = Series(lhs_arr)._column
def generic_function(a):
return a**3
out_col = lhs_col.applymap(generic_function)
result = lhs_arr**3
np.testing.assert_almost_equal(result, out_col)
def test_applymap_python_lambda(dtype):
size = 500
lhs_arr = np.random.random(size).astype(dtype)
lhs_ser = Series(lhs_arr)
# Note that the lambda has to be written this way.
# In other words, the following code does NOT compile with numba:
# test_list = [1, 2, 3, 4]
# out_ser = lhs_ser.applymap(lambda x: x in test_list)
out_ser = lhs_ser.applymap(lambda x: x in [1, 2, 3, 4])
result = np.isin(lhs_arr, [1, 2, 3, 4])
np.testing.assert_almost_equal(result, out_ser.to_array())
