diff --git a/docs/EXPERIMENTAL_PUBLIC_TRANSPORT_SUPPORT.md b/docs/EXPERIMENTAL_PUBLIC_TRANSPORT_SUPPORT.md
index 1dca16b817..8e2a6c0bee 100644
--- a/docs/EXPERIMENTAL_PUBLIC_TRANSPORT_SUPPORT.md
+++ b/docs/EXPERIMENTAL_PUBLIC_TRANSPORT_SUPPORT.md
@@ -10,10 +10,10 @@ At the moment our app does not have full support for public transport. What we h
 
 :bus: But you can turn on the experimental feature of [GTFS](https://developers.google.com/transit/gtfs/reference) public transport and use it inside the Organic Maps app. It includes all [transit types definded by GTFS specification:](https://developers.google.com/transit/gtfs/reference/extended-route-types) bus, train, ferry, aerial lifts of different kinds, trolleybus and much more. Let's call this version of transit data **GTFS transit** from now on.
 
-To mixin the experimental GTFS transit into the OSM transit data you should follow 2 simple steps:
+To mix in the experimental GTFS transit into the OSM transit data you should follow these steps:
 
-- Run the pipeline for downloading and preparing GTFS data about public transport.
-- Switch to the new version of the transit routing section in maps: build maps with the GTFS transit section with the help of special options for generator_tool.
+1. Run the pipeline for downloading and preparing GTFS data about public transport.
+2. Switch to the new version of the transit routing section in maps: build maps with the GTFS transit section with the help of special options for generator_tool.
 
 After completing these steps you will have maps with:
 
diff --git a/tools/python/stylesheet/cat_stat.py b/tools/python/stylesheet/cat_stat.py
index b405d54c1d..ba693b1774 100755
--- a/tools/python/stylesheet/cat_stat.py
+++ b/tools/python/stylesheet/cat_stat.py
@@ -81,7 +81,7 @@ def find_in_taginfo(cur, kv, seen):
 
 
 def find_popular_taginfo(cur, seen):
-    """Finds popular values that have not been seen, among some popular tags."""
+    """Finds popular keys that have not been seen."""
     RE_VALID = re.compile(r'^[a-z_]+$')
     keys = ('amenity', 'shop', 'craft', 'emergency', 'office', 'highway', 'railway', 'tourism', 'historic', 'leisure', 'man_made')
     cur.execute("select key, value, count_all from tags where key in ({}) and count_all > 1000 order by count_all desc".