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1 change: 0 additions & 1 deletion ci/code_checks.sh
Original file line number Diff line number Diff line change
Expand Up @@ -97,7 +97,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.Series.dt.unit GL08" \
-i "pandas.Series.pad PR01,SA01" \
-i "pandas.Series.sparse.from_coo PR07,SA01" \
-i "pandas.Series.sparse.npoints SA01" \
-i "pandas.Timedelta.max PR02" \
-i "pandas.Timedelta.min PR02" \
-i "pandas.Timedelta.resolution PR02" \
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12 changes: 12 additions & 0 deletions pandas/core/arrays/sparse/array.py
Original file line number Diff line number Diff line change
Expand Up @@ -708,6 +708,18 @@ def npoints(self) -> int:
"""
The number of non- ``fill_value`` points.

This property returns the number of elements in the sparse series that are
not equal to the ``fill_value``. Sparse data structures store only the
non-``fill_value`` elements, reducing memory usage when the majority of
values are the same.

See Also
--------
Series.sparse.to_dense : Convert a Series from sparse values to dense.
Series.sparse.fill_value : Elements in `data` that are `fill_value` are
not stored.
Series.sparse.density : The percent of non- ``fill_value`` points, as decimal.

Examples
--------
>>> from pandas.arrays import SparseArray
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