diff --git a/pandas/tests/resample/test_base.py b/pandas/tests/resample/test_base.py
index 02203f476af8e..97a95d107f070 100644
--- a/pandas/tests/resample/test_base.py
+++ b/pandas/tests/resample/test_base.py
@@ -7,7 +7,7 @@
 from pandas import DataFrame, Series
 from pandas.core.groupby.groupby import DataError
 from pandas.core.groupby.grouper import Grouper
-from pandas.core.indexes.datetimes import date_range
+from pandas.core.indexes.datetimes import DatetimeIndex, date_range
 from pandas.core.indexes.period import PeriodIndex, period_range
 from pandas.core.indexes.timedeltas import TimedeltaIndex, timedelta_range
 import pandas.util.testing as tm
@@ -267,3 +267,60 @@ def test_resample_quantile(series):
     result = s.resample(freq).quantile(q)
     expected = s.resample(freq).agg(lambda x: x.quantile(q)).rename(s.name)
     tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "_index_factory,_series_name,_index_start,_index_end", [DATE_RANGE, PERIOD_RANGE]
+)
+@pytest.mark.parametrize(
+    "freq, result_name, result_data, result_index, result_freq",
+    [
+        (
+            "D",
+            "dti",
+            [1.0] * 5 + [np.nan] * 5,
+            ["2005-01-{}".format(i) for i in range(1, 11)],
+            "D",
+        ),
+        (
+            "D",
+            "pi",
+            [1.0] * 5 + [np.nan] * 5,
+            ["2005-01-{}".format(i) for i in range(1, 11)],
+            "D",
+        ),
+        (
+            "W",
+            "dti",
+            [2.0, 3.0, np.nan],
+            ["2005-01-02", "2005-01-09", "2005-01-16"],
+            "W-SUN",
+        ),
+        (
+            "W",
+            "pi",
+            [2.0, 3.0, np.nan],
+            ["2004-12-27/2005-01-02", "2005-01-03/2005-01-09", "2005-01-10/2005-01-16"],
+            "W-SUN",
+        ),
+        ("M", "dti", [5.0], ["2005-01-31"], "M"),
+        ("M", "pi", [5.0], ["2005-01"], "M"),
+    ],
+)
+def test_resample_sum(
+    series, freq, result_name, result_data, result_index, result_freq
+):
+    # GH 19974
+    series[:5] = 1
+    series[5:] = np.nan
+    result = series.resample(freq).sum(min_count=1)
+
+    if isinstance(series.index, PeriodIndex) and result_name == "pi":
+        index = PeriodIndex(result_index, freq=result_freq)
+    elif isinstance(series.index, DatetimeIndex) and result_name == "dti":
+        index = DatetimeIndex(result_index, freq=result_freq)
+    else:
+        pytest.skip("unsupported configuration")
+
+    expected = Series(result_data, index, name=result_name)
+    tm.assert_series_equal(result, expected)
diff --git a/pandas/tests/resample/test_timedelta.py b/pandas/tests/resample/test_timedelta.py
index 7a6ebf826ca4d..cd95d8b7b0f61 100644
--- a/pandas/tests/resample/test_timedelta.py
+++ b/pandas/tests/resample/test_timedelta.py
@@ -4,7 +4,7 @@
 
 import pandas as pd
 from pandas import DataFrame, Series
-from pandas.core.indexes.timedeltas import timedelta_range
+from pandas.core.indexes.timedeltas import TimedeltaIndex, timedelta_range
 import pandas.util.testing as tm
 
 
@@ -125,3 +125,15 @@ def test_resample_timedelta_values():
     tm.assert_series_equal(res, exp)
     res = df["time"].resample("2D").first()
     tm.assert_series_equal(res, exp)
+
+
+def test_resample_sum():
+    # GH 19974
+    data = [1.0] * 5 + [np.nan] * 5
+    index = timedelta_range("1 day", "10 day", freq="D")
+    series = Series(data, index=index)
+    result = series.resample("D").sum(min_count=1)
+
+    index = TimedeltaIndex(["{} days".format(i) for i in range(1, 11)], freq="D")
+    expected = Series(data, index=index)
+    tm.assert_series_equal(result, expected)