From a75a8dce463c54329b1f50de6c2eac7fbda4525f Mon Sep 17 00:00:00 2001
From: Charis <26616127+charislam@users.noreply.github.com>
Date: Fri, 4 Feb 2022 11:47:41 -0500
Subject: [PATCH] Fix linting fail (#774)

---
 timescaledb/getting-started/query-data.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/timescaledb/getting-started/query-data.md b/timescaledb/getting-started/query-data.md
index f9934d2c184c..7f2b6e48bf6a 100644
--- a/timescaledb/getting-started/query-data.md
+++ b/timescaledb/getting-started/query-data.md
@@ -93,7 +93,7 @@ powerful function for time-series analysis is `time_bucket_gapfill`.
 Another common problem in time-series analysis is dealing with imperfect datasets.
 Some time-series analyses or visualizations want to display records for each
 selected time period, even if no data was recorded during that period. This is
-commonly termed "gap filling", and may involve performing such operations as
+commonly termed "gap filling," and may involve performing such operations as
 recording a "0" for any missing data, interpolating missing values, or carrying
 the last observed value forward until new data is recorded.