From 71076bb3bfa62e838ea1a6a089d7d10fcdc05176 Mon Sep 17 00:00:00 2001 From: Tuhin Sharma Date: Sun, 22 Sep 2024 10:37:19 +0530 Subject: [PATCH] DOC: fix SA01 for pandas.Series.sparse.fill_value --- ci/code_checks.sh | 1 - pandas/core/arrays/sparse/array.py | 6 ++++++ 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/ci/code_checks.sh b/ci/code_checks.sh index f2d9f582d8932..35e23f8d7c531 100755 --- a/ci/code_checks.sh +++ b/ci/code_checks.sh @@ -97,7 +97,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then -i "pandas.Series.dt.tz_localize PR01,PR02" \ -i "pandas.Series.dt.unit GL08" \ -i "pandas.Series.pad PR01,SA01" \ - -i "pandas.Series.sparse.fill_value SA01" \ -i "pandas.Series.sparse.from_coo PR07,SA01" \ -i "pandas.Series.sparse.npoints SA01" \ -i "pandas.Series.sparse.sp_values SA01" \ diff --git a/pandas/core/arrays/sparse/array.py b/pandas/core/arrays/sparse/array.py index a09dc20af3b36..7504a9bab8544 100644 --- a/pandas/core/arrays/sparse/array.py +++ b/pandas/core/arrays/sparse/array.py @@ -623,6 +623,12 @@ def fill_value(self): For memory savings, this should be the most common value in the array. + See Also + -------- + SparseDtype : Dtype for data stored in :class:`SparseArray`. + Series.value_counts : Return a Series containing counts of unique values. + Series.fillna : Fill NA/NaN in a Series with a specified value. + Examples -------- >>> ser = pd.Series([0, 0, 2, 2, 2], dtype="Sparse[int]")