def test_fillna(self): s = SparseArray([1, np.nan, np.nan, 3, np.nan]) res = s.fillna(-1) exp = SparseArray([1, -1, -1, 3, -1], fill_value=-1, dtype=np.float64) tm.assert_sp_array_equal(res, exp) s = SparseArray([1, np.nan, np.nan, 3, np.nan], fill_value=0) res = s.fillna(-1) exp = SparseArray([1, -1, -1, 3, -1], fill_value=0, dtype=np.float64) tm.assert_sp_array_equal(res, exp) s = SparseArray([1, np.nan, 0, 3, 0]) res = s.fillna(-1) exp = SparseArray([1, -1, 0, 3, 0], fill_value=-1, dtype=np.float64) tm.assert_sp_array_equal(res, exp) s = SparseArray([1, np.nan, 0, 3, 0], fill_value=0) res = s.fillna(-1) exp = SparseArray([1, -1, 0, 3, 0], fill_value=0, dtype=np.float64) tm.assert_sp_array_equal(res, exp) s = SparseArray([np.nan, np.nan, np.nan, np.nan]) res = s.fillna(-1) exp = SparseArray([-1, -1, -1, -1], fill_value=-1, dtype=np.float64) tm.assert_sp_array_equal(res, exp) s = SparseArray([np.nan, np.nan, np.nan, np.nan], fill_value=0) res = s.fillna(-1) exp = SparseArray([-1, -1, -1, -1], fill_value=0, dtype=np.float64) tm.assert_sp_array_equal(res, exp) # float dtype's fill_value is np.nan, replaced by -1 s = SparseArray([0., 0., 0., 0.]) res = s.fillna(-1) exp = SparseArray([0., 0., 0., 0.], fill_value=-1) tm.assert_sp_array_equal(res, exp) # int dtype shouldn't have missing. No changes. s = SparseArray([0, 0, 0, 0]) self.assertEqual(s.dtype, np.int64) self.assertEqual(s.fill_value, 0) res = s.fillna(-1) tm.assert_sp_array_equal(res, s) s = SparseArray([0, 0, 0, 0], fill_value=0) self.assertEqual(s.dtype, np.int64) self.assertEqual(s.fill_value, 0) res = s.fillna(-1) exp = SparseArray([0, 0, 0, 0], fill_value=0) tm.assert_sp_array_equal(res, exp) # fill_value can be nan if there is no missing hole. # only fill_value will be changed s = SparseArray([0, 0, 0, 0], fill_value=np.nan) self.assertEqual(s.dtype, np.int64) self.assertTrue(np.isnan(s.fill_value)) res = s.fillna(-1) exp = SparseArray([0, 0, 0, 0], fill_value=-1) tm.assert_sp_array_equal(res, exp)
def test_fillna_overlap(self): s = SparseArray([1, np.nan, np.nan, 3, np.nan]) # filling with existing value doesn't replace existing value with # fill_value, i.e. existing 3 remains in sp_values res = s.fillna(3) exp = np.array([1, 3, 3, 3, 3]) tm.assert_numpy_array_equal(res.to_dense(), exp) s = SparseArray([1, np.nan, np.nan, 3, np.nan], fill_value=0) res = s.fillna(3) exp = SparseArray([1, 3, 3, 3, 3], fill_value=0) tm.assert_sp_array_equal(res, exp)
def test_fillna_overlap(self): s = SparseArray([1, np.nan, np.nan, 3, np.nan]) # filling with existing value doesn't replace existing value with # fill_value, i.e. existing 3 remains in sp_values res = s.fillna(3) exp = np.array([1, 3, 3, 3, 3], dtype=np.float64) tm.assert_numpy_array_equal(res.to_dense(), exp) s = SparseArray([1, np.nan, np.nan, 3, np.nan], fill_value=0) res = s.fillna(3) exp = SparseArray([1, 3, 3, 3, 3], fill_value=0) tm.assert_sp_array_equal(res, exp)
def test_fillna(self): s = SparseArray([1, np.nan, np.nan, 3, np.nan]) res = s.fillna(-1) exp = SparseArray([1, -1, -1, 3, -1], fill_value=-1) tm.assert_sp_array_equal(res, exp) s = SparseArray([1, np.nan, np.nan, 3, np.nan], fill_value=0) res = s.fillna(-1) exp = SparseArray([1, -1, -1, 3, -1], fill_value=0) tm.assert_sp_array_equal(res, exp) s = SparseArray([1, np.nan, 0, 3, 0]) res = s.fillna(-1) exp = SparseArray([1, -1, 0, 3, 0], fill_value=-1) tm.assert_sp_array_equal(res, exp) s = SparseArray([1, np.nan, 0, 3, 0], fill_value=0) res = s.fillna(-1) exp = SparseArray([1, -1, 0, 3, 0], fill_value=0) tm.assert_sp_array_equal(res, exp) s = SparseArray([np.nan, np.nan, np.nan, np.nan]) res = s.fillna(-1) exp = SparseArray([-1, -1, -1, -1], fill_value=-1) tm.assert_sp_array_equal(res, exp) s = SparseArray([np.nan, np.nan, np.nan, np.nan], fill_value=0) res = s.fillna(-1) exp = SparseArray([-1, -1, -1, -1], fill_value=0) tm.assert_sp_array_equal(res, exp) s = SparseArray([0, 0, 0, 0]) res = s.fillna(-1) exp = SparseArray([0, 0, 0, 0], fill_value=-1) tm.assert_sp_array_equal(res, exp) s = SparseArray([0, 0, 0, 0], fill_value=0) res = s.fillna(-1) exp = SparseArray([0, 0, 0, 0], fill_value=0) tm.assert_sp_array_equal(res, exp)