REF: avoid core.missing dependency on Series (pandas-dev#29400)

Author: jbrockmendel

pandas/core/generic.py

@@ -83,6 +83,7 @@
 from pandas.core.indexes.period import Period, PeriodIndex
 import pandas.core.indexing as indexing
 from pandas.core.internals import BlockManager
+from pandas.core.missing import find_valid_index
 from pandas.core.ops import _align_method_FRAME
 
 from pandas.io.formats import format as fmt
@@ -10870,27 +10871,11 @@ def _find_valid_index(self, how: str):
         -------
         idx_first_valid : type of index
         """
-        assert how in ["first", "last"]
 
-        if len(self) == 0:  # early stop
+        idxpos = find_valid_index(self._values, how)
+        if idxpos is None:
             return None
-        is_valid = ~self.isna()
-
-        if self.ndim == 2:
-            is_valid = is_valid.any(1)  # reduce axis 1
-
-        if how == "first":
-            idxpos = is_valid.values[::].argmax()
-
-        if how == "last":
-            idxpos = len(self) - 1 - is_valid.values[::-1].argmax()
-
-        chk_notna = is_valid.iat[idxpos]
-        idx = self.index[idxpos]
-
-        if not chk_notna:
-            return None
-        return idx
+        return self.index[idxpos]
 
     @Appender(
         _shared_docs["valid_index"] % {"position": "first", "klass": "Series/DataFrame"}

pandas/core/missing.py

@@ -128,6 +128,43 @@ def clean_interp_method(method, **kwargs):
     return method
 
 
+def find_valid_index(values, how: str):
+    """
+    Retrieves the index of the first valid value.
+
+    Parameters
+    ----------
+    values : ndarray or ExtensionArray
+    how : {'first', 'last'}
+        Use this parameter to change between the first or last valid index.
+
+    Returns
+    -------
+    int or None
+    """
+    assert how in ["first", "last"]
+
+    if len(values) == 0:  # early stop
+        return None
+
+    is_valid = ~isna(values)
+
+    if values.ndim == 2:
+        is_valid = is_valid.any(1)  # reduce axis 1
+
+    if how == "first":
+        idxpos = is_valid[::].argmax()
+
+    if how == "last":
+        idxpos = len(values) - 1 - is_valid[::-1].argmax()
+
+    chk_notna = is_valid[idxpos]
+
+    if not chk_notna:
+        return None
+    return idxpos
+
+
 def interpolate_1d(
     xvalues,
     yvalues,
@@ -192,14 +229,10 @@ def interpolate_1d(
     # default limit is unlimited GH #16282
     limit = algos._validate_limit(nobs=None, limit=limit)
 
-    from pandas import Series
-
-    ys = Series(yvalues)
-
     # These are sets of index pointers to invalid values... i.e. {0, 1, etc...
     all_nans = set(np.flatnonzero(invalid))
-    start_nans = set(range(ys.first_valid_index()))
-    end_nans = set(range(1 + ys.last_valid_index(), len(valid)))
+    start_nans = set(range(find_valid_index(yvalues, "first")))
+    end_nans = set(range(1 + find_valid_index(yvalues, "last"), len(valid)))
     mid_nans = all_nans - start_nans - end_nans
 
     # Like the sets above, preserve_nans contains indices of invalid values,