diff --git a/pynapple/core/interval_set.py b/pynapple/core/interval_set.py
index 96663323..44103d80 100644
--- a/pynapple/core/interval_set.py
+++ b/pynapple/core/interval_set.py
@@ -112,10 +112,10 @@ class IntervalSet(NDArrayOperatorsMixin, _MetadataMixin):
     >>> end = [5, 12, 33]
     >>> metadata = {"label": ["a", "b", "c"]}
     >>> ep = nap.IntervalSet(start=start, end=end, metadata=metadata)
-      index    start    end      label
-          0        0      5  |   a
-          1       10     12  |   b
-          2       20     33  |   c
+      index    start    end     label
+          0        0      5     a
+          1       10     12     b
+          2       20     33     c
     shape: (3, 2), time unit: sec.
 
     Initialize an IntervalSet with a pandas DataFrame:
@@ -124,10 +124,10 @@ class IntervalSet(NDArrayOperatorsMixin, _MetadataMixin):
     >>> df = pd.DataFrame(data={"start": [0, 10, 20], "end": [5, 12, 33], "label": ["a", "b", "c"]})
     >>> ep = nap.IntervalSet(df)
     >>> ep
-      index    start    end      label
-          0        0      5  |   a
-          1       10     12  |   b
-          2       20     33  |   c
+      index    start    end     label
+          0        0      5     a
+          1       10     12     b
+          2       20     33     c
     shape: (3, 2), time unit: sec.
 
     Apply numpy functions to an IntervalSet:
@@ -1054,10 +1054,10 @@ def set_info(self, metadata=None, **kwargs):
         >>> metadata = pd.DataFrame(data=['left','right','left'], columns=['choice'])
         >>> ep.set_info(metadata)
         >>> ep
-          index    start    end      choice
-              0        0      5  |   left
-              1       10     12  |   right
-              2       20     33  |   left
+          index    start    end     choice
+              0        0      5     left
+              1       10     12     right
+              2       20     33     left
         shape: (3, 2), time unit: sec.
 
         To add metadata with a dictionary:
@@ -1065,10 +1065,10 @@ def set_info(self, metadata=None, **kwargs):
         >>> metadata = {"reward": [1, 0, 1]}
         >>> ep.set_info(metadata)
         >>> ep
-          index    start    end      choice      reward
-              0        0      5  |   left             1
-              1       10     12  |   right            0
-              2       20     33  |   left             1
+          index    start    end     choice      reward
+              0        0      5     left             1
+              1       10     12     right            0
+              2       20     33     left             1
         shape: (3, 2), time unit: sec.
 
         To add metadata with a keyword argument (pd.Series, numpy.ndarray, list or tuple):
@@ -1076,40 +1076,40 @@ def set_info(self, metadata=None, **kwargs):
         >>> stim = pd.Series(data = [10, -23, 12])
         >>> ep.set_info(stim=stim)
         >>> ep
-          index    start    end      choice      reward    stim
-              0        0      5  |   left             1      10
-              1       10     12  |   right            0     -23
-              2       20     33  |   left             1      12
+          index    start    end     choice      reward    stim
+              0        0      5     left             1      10
+              1       10     12     right            0     -23
+              2       20     33     left             1      12
         shape: (3, 2), time unit: sec.
 
         To add metadata as an attribute:
 
         >>> ep.label = ["a", "b", "c"]
         >>> ep
-          index    start    end      choice      reward  label
-              0        0      5  |   left             1  a
-              1       10     12  |   right            0  b
-              2       20     33  |   left             1  c
+          index    start    end     choice      reward  label
+              0        0      5     left             1  a
+              1       10     12     right            0  b
+              2       20     33     left             1  c
         shape: (3, 2), time unit: sec.
 
         To add metadata as a key:
 
         >>> ep["error"] = [0, 0, 0]
         >>> ep
-          index    start    end      choice      reward  label      error
-              0        0      5  |   left             1  a             0
-              1       10     12  |   right            0  b             0
-              2       20     33  |   left             1  c             0
+          index    start    end     choice      reward  label      error
+              0        0      5     left             1  a             0
+              1       10     12     right            0  b             0
+              2       20     33     left             1  c             0
         shape: (3, 2), time unit: sec.
 
         Metadata can be overwritten:
 
         >>> ep.set_info(label=["x", "y", "z"])
         >>> ep
-          index    start    end      choice      reward  label      error
-              0        0      5  |   left             1  x             0
-              1       10     12  |   right            0  y             0
-              2       20     33  |   left             1  z             0
+          index    start    end     choice      reward  label      error
+              0        0      5     left             1  x             0
+              1       10     12     right            0  y             0
+              2       20     33     left             1  z             0
         shape: (3, 2), time unit: sec.
         """
         _MetadataMixin.set_info(self, metadata, **kwargs)
diff --git a/tests/test_ts_group.py b/tests/test_ts_group.py
index bd5b3cc4..04cab0ff 100644
--- a/tests/test_ts_group.py
+++ b/tests/test_ts_group.py
@@ -424,6 +424,10 @@ def test_repr_(self, group):
             )
         assert tabulate(lines, headers=headers) == tsgroup.__repr__()
 
+        # Empty TsGroup
+        empty_tsg = nap.TsGroup({}, time_support=nap.IntervalSet(0, 10))
+        assert tabulate([], headers=["Index", "rate"]) == empty_tsg.__repr__()
+
     def test_str_(self, group):
         tsgroup = nap.TsGroup(group)
         assert tsgroup.__str__() == tsgroup.__repr__()