Remove a pd

holoviews/core/util.py

@@ -1150,22 +1150,18 @@ def unique_array(arr):
     """
     if not len(arr):
         return np.asarray(arr)
-    elif pd:
-        if isinstance(arr, np.ndarray) and arr.dtype.kind not in 'MO':
-            # Avoid expensive unpacking if not potentially datetime
-            return pd.unique(arr)
-
-        values = []
-        for v in arr:
-            if (isinstance(v, datetime_types) and
-                not isinstance(v, cftime_types)):
-                v = pd.Timestamp(v).to_datetime64()
-            values.append(v)
-        return pd.unique(values)
-    else:
-        arr = np.asarray(arr)
-        _, uniq_inds = np.unique(arr, return_index=True)
-        return arr[np.sort(uniq_inds)]
+
+    if isinstance(arr, np.ndarray) and arr.dtype.kind not in 'MO':
+        # Avoid expensive unpacking if not potentially datetime
+        return pd.unique(arr)
+
+    values = []
+    for v in arr:
+        if (isinstance(v, datetime_types) and
+            not isinstance(v, cftime_types)):
+            v = pd.Timestamp(v).to_datetime64()
+        values.append(v)
+    return pd.unique(values)
 
 
 def match_spec(element, specification):
@@ -2095,15 +2091,14 @@ def dt_to_int(value, time_unit='us'):
     """
     Converts a datetime type to an integer with the supplied time unit.
     """
-    if pd:
-        if isinstance(value, pd.Period):
-            value = value.to_timestamp()
-        if isinstance(value, pd.Timestamp):
-            try:
-                value = value.to_datetime64()
-            except Exception:
-                value = np.datetime64(value.to_pydatetime())
-    elif isinstance(value, cftime_types):
+    if isinstance(value, pd.Period):
+        value = value.to_timestamp()
+    if isinstance(value, pd.Timestamp):
+        try:
+            value = value.to_datetime64()
+        except Exception:
+            value = np.datetime64(value.to_pydatetime())
+    if isinstance(value, cftime_types):
         return cftime_to_timestamp(value, time_unit)
 
     # date class is a parent for datetime class

holoviews/element/comparison.py

@@ -19,6 +19,7 @@
 """
 from functools import partial
 import numpy as np
+import pandas as pd
 from unittest.util import safe_repr
 from unittest import TestCase
 from numpy.testing import assert_array_equal, assert_array_almost_equal
@@ -28,7 +29,7 @@
                     HoloMap, Dimensioned, Layout, NdLayout, NdOverlay,
                     GridSpace, DynamicMap, GridMatrix, OrderedDict)
 from ..core.options import Options, Cycle
-from ..core.util import (pd, cast_array_to_int64, datetime_types, dt_to_int,
+from ..core.util import (cast_array_to_int64, datetime_types, dt_to_int,
                          is_float)
 
 
@@ -115,8 +116,7 @@ def register(cls):
         cls.equality_type_funcs[np.ma.masked_array]  = cls.compare_arrays
 
         # Pandas dataframe comparison
-        if pd:
-            cls.equality_type_funcs[pd.DataFrame] = cls.compare_dataframe
+        cls.equality_type_funcs[pd.DataFrame] = cls.compare_dataframe
 
         # Dimension objects
         cls.equality_type_funcs[Dimension] =    cls.compare_dimensions

holoviews/element/util.py

@@ -185,12 +185,9 @@ def _aggregate_dataset(self, obj):
         reindexed = concat_data.reindex([xdim, ydim], vdims)
         if not reindexed:
             agg = reindexed
-        elif pd:
-            df = PandasInterface.as_dframe(reindexed)
-            df = df.groupby([xdim, ydim], sort=False).first().reset_index()
-            agg = reindexed.clone(df)
-        else:
-            agg = reindexed.aggregate([xdim, ydim], reduce_fn)
+        df = PandasInterface.as_dframe(reindexed)
+        df = df.groupby([xdim, ydim], sort=False).first().reset_index()
+        agg = reindexed.clone(df)
 
         # Convert data to a gridded dataset
         for vdim in vdims:
@@ -225,12 +222,8 @@ def _process(self, obj, key=None):
             raise ValueError("Must have at two dimensions to aggregate over"
                              "and one value dimension to aggregate on.")
 
-        if pd:
-            obj = Dataset(obj, datatype=['dataframe'])
-            return self._aggregate_dataset_pandas(obj)
-        else:
-            obj = Dataset(obj, datatype=['dictionary'])
-            return self._aggregate_dataset(obj)
+        obj = Dataset(obj, datatype=['dataframe'])
+        return self._aggregate_dataset_pandas(obj)
 
 
 def circular_layout(nodes):

holoviews/operation/element.py

@@ -12,10 +12,10 @@
 
 from ..core import (Operation, NdOverlay, Overlay, GridMatrix,
                     HoloMap, Dataset, Element, Collator, Dimension)
-from ..core.data import ArrayInterface, DictInterface, default_datatype
+from ..core.data import ArrayInterface, DictInterface, PandasInterface, default_datatype
 from ..core.data.util import dask_array_module
 from ..core.util import (
-    group_sanitizer, label_sanitizer, pd, datetime_types, isfinite,
+    group_sanitizer, label_sanitizer, datetime_types, isfinite,
     dt_to_int, isdatetime, is_dask_array, is_cupy_array, is_ibis_expr
 )
 from ..element.chart import Histogram, Scatter
@@ -24,10 +24,7 @@
 from ..element.util import categorical_aggregate2d # noqa (API import)
 from ..streams import RangeXY
 
-column_interfaces = [ArrayInterface, DictInterface]
-if pd:
-    from ..core.data import PandasInterface
-    column_interfaces.append(PandasInterface)
+column_interfaces = [ArrayInterface, DictInterface, PandasInterface]
 
 
 def identity(x,k): return x