From 45f27c81a408ada692ef51e2ce73408aee4d6c53 Mon Sep 17 00:00:00 2001
From: Tuhin Sharma <tuhinsharma121@gmail.com>
Date: Tue, 3 Dec 2024 00:40:49 +0530
Subject: [PATCH] DOC: fix SA01,ES01 for pandas.infer_freq (#60441)
---
ci/code_checks.sh | 1 -
pandas/tseries/frequencies.py | 12 ++++++++++++
2 files changed, 12 insertions(+), 1 deletion(-)
diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 5db76fba3a..dde98a01cc 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -109,7 +109,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.errors.PerformanceWarning SA01" \
-i "pandas.errors.UndefinedVariableError PR01,SA01" \
-i "pandas.errors.ValueLabelTypeMismatch SA01" \
- -i "pandas.infer_freq SA01" \
-i "pandas.io.json.build_table_schema PR07,RT03,SA01" \
-i "pandas.plotting.andrews_curves RT03,SA01" \
-i "pandas.plotting.scatter_matrix PR07,SA01" \
diff --git a/pandas/tseries/frequencies.py b/pandas/tseries/frequencies.py
index 534bee5fed..9a01568971 100644
--- a/pandas/tseries/frequencies.py
+++ b/pandas/tseries/frequencies.py
@@ -89,6 +89,11 @@ def infer_freq(
"""
Infer the most likely frequency given the input index.
+ This method attempts to deduce the most probable frequency (e.g., 'D' for daily,
+ 'H' for hourly) from a sequence of datetime-like objects. It is particularly useful
+ when the frequency of a time series is not explicitly set or known but can be
+ inferred from its values.
+
Parameters
----------
index : DatetimeIndex, TimedeltaIndex, Series or array-like
@@ -106,6 +111,13 @@ def infer_freq(
ValueError
If there are fewer than three values.
+ See Also
+ --------
+ date_range : Return a fixed frequency DatetimeIndex.
+ timedelta_range : Return a fixed frequency TimedeltaIndex with day as the default.
+ period_range : Return a fixed frequency PeriodIndex.
+ DatetimeIndex.freq : Return the frequency object if it is set, otherwise None.
+
Examples
--------
>>> idx = pd.date_range(start="2020/12/01", end="2020/12/30", periods=30)
--
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