diff --git a/quacc/evaluation/report.py b/quacc/evaluation/report.py
index 19bac3f..ef57345 100644
--- a/quacc/evaluation/report.py
+++ b/quacc/evaluation/report.py
@@ -437,6 +437,8 @@ class DatasetReport:
         if mode == "delta_train":
             _data = self.data(metric, estimators) if data is None else data
             avg_on_train = _data.groupby(level=1).mean()
+            if avg_on_train.empty:
+                return None
             prevs_on_train = np.sort(avg_on_train.index.unique(0))
             return plot.plot_delta(
                 base_prevs=np.around(
@@ -455,6 +457,8 @@ class DatasetReport:
         elif mode == "stdev_train":
             _data = self.data(metric, estimators) if data is None else data
             avg_on_train = _data.groupby(level=1).mean()
+            if avg_on_train.empty:
+                return None
             prevs_on_train = np.sort(avg_on_train.index.unique(0))
             stdev_on_train = _data.groupby(level=1).std()
             return plot.plot_delta(
@@ -475,6 +479,8 @@ class DatasetReport:
         elif mode == "delta_test":
             _data = self.data(metric, estimators) if data is None else data
             avg_on_test = _data.groupby(level=0).mean()
+            if avg_on_test.empty:
+                return None
             prevs_on_test = np.sort(avg_on_test.index.unique(0))
             return plot.plot_delta(
                 base_prevs=np.around([(1.0 - p, p) for p in prevs_on_test], decimals=2),
@@ -491,6 +497,8 @@ class DatasetReport:
         elif mode == "stdev_test":
             _data = self.data(metric, estimators) if data is None else data
             avg_on_test = _data.groupby(level=0).mean()
+            if avg_on_test.empty:
+                return None
             prevs_on_test = np.sort(avg_on_test.index.unique(0))
             stdev_on_test = _data.groupby(level=0).std()
             return plot.plot_delta(
@@ -509,6 +517,8 @@ class DatasetReport:
         elif mode == "shift":
             _shift_data = self.shift_data(metric, estimators) if data is None else data
             avg_shift = _shift_data.groupby(level=0).mean()
+            if avg_shift.empty:
+                return None
             count_shift = _shift_data.groupby(level=0).count()
             prevs_shift = np.sort(avg_shift.index.unique(0))
             return plot.plot_shift(