diff --git a/numpy_groupies/aggregate_numpy.py b/numpy_groupies/aggregate_numpy.py
index 0bfc9a0..9dd82a8 100644
--- a/numpy_groupies/aggregate_numpy.py
+++ b/numpy_groupies/aggregate_numpy.py
@@ -88,20 +88,24 @@ def _any(group_idx, a, size, fill_value, dtype=None):
 def _min(group_idx, a, size, fill_value, dtype=None):
     dtype = minimum_dtype(fill_value, dtype or a.dtype)
     dmax = maxval(fill_value, dtype)
-    ret = np.full(size, fill_value, dtype=dtype)
+    with np.errstate(invalid="ignore"):
+        ret = np.full(size, fill_value, dtype=dtype)
     if fill_value != dmax:
         ret[group_idx] = dmax  # min starts from maximum
-    np.minimum.at(ret, group_idx, a)
+    with np.errstate(invalid="ignore"):
+        np.minimum.at(ret, group_idx, a)
     return ret
 
 
 def _max(group_idx, a, size, fill_value, dtype=None):
     dtype = minimum_dtype(fill_value, dtype or a.dtype)
     dmin = minval(fill_value, dtype)
-    ret = np.full(size, fill_value, dtype=dtype)
+    with np.errstate(invalid="ignore"):
+        ret = np.full(size, fill_value, dtype=dtype)
     if fill_value != dmin:
         ret[group_idx] = dmin  # max starts from minimum
-    np.maximum.at(ret, group_idx, a)
+    with np.errstate(invalid="ignore"):
+        np.maximum.at(ret, group_idx, a)
     return ret
 
 
diff --git a/numpy_groupies/aggregate_pandas.py b/numpy_groupies/aggregate_pandas.py
index 02cb625..54a0202 100644
--- a/numpy_groupies/aggregate_pandas.py
+++ b/numpy_groupies/aggregate_pandas.py
@@ -29,7 +29,8 @@ def _wrapper(group_idx, a, size, fill_value, func="sum", dtype=None, ddof=0, **k
         ret = grouped.values[:, 0]
     else:
         ret = np.full(size, fill_value, dtype=dtype)
-        ret[grouped.index] = grouped.values[:, 0]
+        with np.errstate(invalid="ignore"):
+            ret[grouped.index] = grouped.values[:, 0]
     return ret
 
 
diff --git a/numpy_groupies/utils.py b/numpy_groupies/utils.py
index 6d1b96f..e2af7a3 100644
--- a/numpy_groupies/utils.py
+++ b/numpy_groupies/utils.py
@@ -208,7 +208,8 @@ def minimum_dtype(x, dtype=np.bool_):
 
     def check_type(x, dtype):
         try:
-            converted = np.array(x).astype(dtype)
+            with np.errstate(invalid="ignore"):
+                converted = np.array(x).astype(dtype)
         except (ValueError, OverflowError, RuntimeWarning):
             return False
         # False if some overflow has happened