Update pyarrow version, use pyarrow backend for pandas (#513)

* Update pyarrow version, los prediction notebook

* Small fix to unique (cast as np array)

* Update dependencies in pyproject.toml

* Fix data type check in `filter_range` function

---------

Co-authored-by: Franklin <41602287+fcogidi@users.noreply.github.com>

cyclops/data/slicer.py

@@ -8,6 +8,7 @@
 import numpy as np
 import pandas as pd
 from dateutil.parser import parse
+from pandas.api.types import is_datetime64_any_dtype, is_numeric_dtype
 
 
 @dataclass
@@ -552,11 +553,11 @@ def filter_range(
     example_values = pd.Series(
         examples[column_name],
         dtype="datetime64[ns]" if value_is_datetime else None,
-    ).to_numpy()
+    )
 
     if not (  # column does not contain number or datetime values
-        np.issubdtype(example_values.dtype, np.number)
-        or np.issubdtype(example_values.dtype, np.datetime64)
+        is_numeric_dtype(example_values.dtype)
+        or is_datetime64_any_dtype(example_values.dtype)
     ):
         raise TypeError(
             "Expected feature to be numeric or datetime, but got "

cyclops/process/feature/handle_types.py

@@ -50,7 +50,7 @@ def get_unique(
 
     """
     if unique is None:
-        return values.unique()  # type: ignore
+        return np.array(values.unique())  # type: ignore
 
     return unique