Rename index column to __index__ to reduce likelyhood of collision

holoviews/operation/datashader.py

@@ -388,9 +388,9 @@ def _process(self, element, key=None):
         if sel_fn:
             if isinstance(params["vdims"], (Dimension, str)):
                 params["vdims"] = [params["vdims"]]
-            sum_agg = ds.summary(**{str(params["vdims"][0]): agg_fn, "index": ds.where(sel_fn)})
+            sum_agg = ds.summary(**{str(params["vdims"][0]): agg_fn, "__index__": ds.where(sel_fn)})
             agg = self._apply_datashader(dfdata, cvs_fn, sum_agg, agg_kwargs, x, y)
-            _ignore = [*params["vdims"], "index"]
+            _ignore = [*params["vdims"], "__index__"]
             sel_vdims = [s for s in agg if s not in _ignore]
             params["vdims"] = [*params["vdims"], *sel_vdims]
         else:
@@ -422,13 +422,13 @@ def _apply_datashader(self, dfdata, cvs_fn, agg_fn, agg_kwargs, x, y):
             agg = cvs_fn(dfdata, x.name, y.name, agg_fn, **agg_kwargs)
 
         is_where_index = ds15 and isinstance(agg_fn, ds.where) and isinstance(agg_fn.column, rd.SpecialColumn)
-        is_summary_index = isinstance(agg_fn, ds.summary) and "index" in agg
+        is_summary_index = isinstance(agg_fn, ds.summary) and "__index__" in agg
         if is_where_index or is_summary_index:
             if is_where_index:
                 data = agg.data
-                agg = agg.to_dataset(name="index")
+                agg = agg.to_dataset(name="__index__")
             else:  # summary index
-                data = agg.index.data
+                data = agg["__index__"].data
             neg1 = data == -1
             for col in dfdata.columns:
                 if col in agg.coords:

holoviews/tests/operation/test_datashader.py

@@ -1314,12 +1314,12 @@ def test_rasterize_where_agg_no_column(point_plot, agg_input_fn, index_col):
     rast_input = dict(dynamic=False,  x_range=(-1, 1), y_range=(-1, 1), width=2, height=2)
     img = rasterize(point_plot, aggregator=agg_fn, **rast_input)
 
-    assert list(img.data) == ["index", "s", "val", "cat"]
+    assert list(img.data) == ["__index__", "s", "val", "cat"]
     assert list(img.vdims) == ["val", "s", "cat"]  # val first and no index
 
     # N=100 in point_data is chosen to have a big enough sample size
     # so that the index are not the same for the different agg_input_fn
-    np.testing.assert_array_equal(img.data["index"].data.flatten(), index_col)
+    np.testing.assert_array_equal(img.data["__index__"].data.flatten(), index_col)
 
     img_simple = rasterize(point_plot, aggregator=agg_input_fn("val"), **rast_input)
     np.testing.assert_array_equal(img_simple["val"], img["val"])
@@ -1357,7 +1357,7 @@ def test_rasterize_selector(point_plot, sel_fn):
     img = rasterize(point_plot, selector=sel_fn("val"), **rast_input)
 
     # Count is from the aggregator
-    assert list(img.data) == ["Count", "index", "s", "val", "cat"]
+    assert list(img.data) == ["Count", "__index__", "s", "val", "cat"]
     assert list(img.vdims) == ["Count", "s", "val", "cat"]  # no index
 
     # The output for the selector should be equal to the output for the aggregator using