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())