refactor: Remove direct pandas import

holoviews/core/__init__.py

@@ -1,7 +1,5 @@
 from datetime import date, datetime
 
-import pandas as pd
-
 from .boundingregion import *
 from .data import *
 from .dimension import *
@@ -31,7 +29,7 @@
 Dimension.type_formatters[np.datetime64] = '%Y-%m-%d %H:%M:%S'
 Dimension.type_formatters[datetime] = '%Y-%m-%d %H:%M:%S'
 Dimension.type_formatters[date] = '%Y-%m-%d'
-Dimension.type_formatters[pd.Timestamp] = "%Y-%m-%d %H:%M:%S"
+# Dimension.type_formatters['pandas.Timestamp'] = "%Y-%m-%d %H:%M:%S"  # TODO: Implement this
 
 
 def public(obj):

holoviews/core/data/cudf.py

@@ -3,8 +3,6 @@
 from itertools import product
 
 import numpy as np
-import pandas as pd
-from pandas.api.types import is_numeric_dtype
 
 from .. import util
 from ..dimension import dimension_name
@@ -49,6 +47,7 @@ def applies(cls, obj):
     @classmethod
     def init(cls, eltype, data, kdims, vdims):
         import cudf
+        import pandas as pd
 
         element_params = eltype.param.objects()
         kdim_param = element_params['kdims']
@@ -276,6 +275,9 @@ def add_dimension(cls, dataset, dimension, dim_pos, values, vdim):
 
     @classmethod
     def aggregate(cls, dataset, dimensions, function, **kwargs):
+        import pandas as pd
+        from pandas.api.types import is_numeric_dtype
+
         data = dataset.data
         cols = [d.name for d in dataset.kdims if d in dimensions]
         vdims = dataset.dimensions('value', label='name')

holoviews/core/data/dask.py

@@ -1,7 +1,6 @@
 import sys
 
 import numpy as np
-import pandas as pd
 
 from .. import util
 from ..dimension import Dimension
@@ -252,6 +251,7 @@ def aggregate(cls, dataset, dimensions, function, **kwargs):
                 agg = getattr(reindexed, inbuilts[function.__name__])()
             else:
                 raise NotImplementedError
+            import pandas as pd
             df = pd.DataFrame(agg.compute()).T
 
         dropped = []

holoviews/core/data/ibis.py

@@ -9,7 +9,7 @@
 from .interface import DataError, Interface
 from .util import cached
 
-IBIS_VERSION = util._no_import_version("ibis-framework")
+IBIS_VERSION = util.versions._no_import_version("ibis-framework")
 IBIS_GE_4_0_0 = IBIS_VERSION >= (4, 0, 0)
 IBIS_GE_5_0_0 = IBIS_VERSION >= (5, 0, 0)
 IBIS_GE_9_5_0 = IBIS_VERSION >= (9, 5, 0)

holoviews/core/data/pandas.py

@@ -1,6 +1,6 @@
+import sys
+
 import numpy as np
-import pandas as pd
-from pandas.api.types import is_numeric_dtype
 
 from .. import util
 from ..dimension import Dimension, dimension_name
@@ -23,13 +23,26 @@ class PandasAPI:
             ...
     """
 
+pd = None  # Set when PandasInterface.applies is successful
 
 class PandasInterface(Interface, PandasAPI):
 
-    types = (pd.DataFrame,)
+    types = ()
 
     datatype = 'dataframe'
 
+    @classmethod
+    def loaded(cls):
+        return 'pandas' in sys.modules
+
+    @classmethod
+    def applies(cls, obj):
+        if not cls.loaded():
+            return False
+        global pd  # noqa: PLW0603
+        import pandas as pd
+        return isinstance(obj, (pd.DataFrame, pd.Series))
+
     @classmethod
     def dimension_type(cls, dataset, dim):
         return cls.dtype(dataset, dim).type
@@ -289,6 +302,7 @@ def aggregate(cls, dataset, dimensions, function, **kwargs):
                     c for c in reindexed.columns if c not in cols
                 ]
             else:
+                from pandas.api.types import is_numeric_dtype
                 numeric_cols = [
                     c for c, d in zip(reindexed.columns, reindexed.dtypes)
                     if is_numeric_dtype(d) and c not in cols

holoviews/core/data/spatialpandas.py

@@ -2,7 +2,6 @@
 from collections import defaultdict
 
 import numpy as np
-import pandas as pd
 
 from ..dimension import dimension_name
 from ..util import isscalar, unique_array, unique_iterator
@@ -98,6 +97,8 @@ def init(cls, eltype, data, kdims, vdims):
         elif 'geometry' not in data:
             cls.geo_column(data)
 
+        import pandas as pd
+
         index_names = data.index.names if isinstance(data, pd.DataFrame) else [data.index.name]
         if index_names == [None]:
             index_names = ['index']
@@ -865,6 +866,7 @@ def from_multi(eltype, data, kdims, vdims):
     Returns:
         A GeoDataFrame containing in the list based format.
     """
+    import pandas as pd
     from spatialpandas import GeoDataFrame
 
     xname, yname = (kd.name for kd in kdims[:2])

holoviews/core/data/xarray.py

@@ -2,7 +2,6 @@
 import types
 
 import numpy as np
-import pandas as pd
 
 from .. import util
 from ..dimension import Dimension, asdim, dimension_name
@@ -654,6 +653,8 @@ def dframe(cls, dataset, dimensions):
 
     @classmethod
     def sample(cls, dataset, samples=None):
+        import pandas as pd
+
         if samples is None:
             samples = []
         names = [kd.name for kd in dataset.kdims]

holoviews/core/element.py

@@ -1,7 +1,6 @@
 from itertools import groupby
 
 import numpy as np
-import pandas as pd
 import param
 
 from .dimension import Dimensioned, ViewableElement, asdim
@@ -210,6 +209,8 @@ def dframe(self, dimensions=None, multi_index=False):
         Returns:
             DataFrame of columns corresponding to each dimension
         """
+        import pandas as pd
+
         if dimensions is None:
             dimensions = [d.name for d in self.dimensions()]
         else:

holoviews/core/ndmapping.py

@@ -8,7 +8,6 @@
 from operator import itemgetter
 
 import numpy as np
-import pandas as pd
 import param
 
 from . import util
@@ -891,6 +890,8 @@ def dframe(self, dimensions=None, multi_index=False):
         Returns:
             DataFrame of columns corresponding to each dimension
         """
+        import pandas as pd
+
         if dimensions is None:
             outer_dimensions = self.kdims
             inner_dimensions = None