Validate my interpretation of an SQL query - sql

Question

my question is definitely going to be a little different, so I hope I'm still adhering to the stack overflow question etiquette. With that in mind, I'll get straight to the point.
Essentially, since I am still learning SQL I was looking at examples of scheduled queries in GCP and came across something and I wanted to see if I understand what's going on. So I took the query and wrote some comments explaining what I think the lines in the query are doing. The context in the code itself is irrelevant, I'm more curious if I'm correctly understanding what each of the clauses is doing.
Would anyone be able to tell me if I am interpreting it correctly or if I misunderstood some stuff, based on my comments? The code and comments are below. Note that the comments come first and the queries I'm commenting on follow directly after.
-- Create temporary table with the subquery below via the WITH () clause
-- Table contains session date, which webpage, total sessions, total sessions with a logout, and total clicks
-- The data in this temporary table is coming from the `gcp-project-223467.web.top_level` table in BigQuery
-- The columns correspond to dates 01/01/2022 & onwards, and exclude the 'Home'and 'Team' pages
-- The resulting data in the temp table is grouped by date & page type (first and second columns of the resulting temp table)
WITH logins AS (
SELECT
session_date as date,
website_page as page,
SUM(sessions) AS sessions,
SUM(sessions_with_logout) AS logouts,
SUM(clicks) AS clicks
FROM `gcp-project-223467.web.top_level`
WHERE DATE_session >= "2022-01-01"
AND website_page NOT IN ('Home','Team')
AND clicks > 0
GROUP BY 1, 2
)
-- Select the data from the above subquery (via SELECT logins.*)
-- Left join another temp table with data coming from `ingka-web-analytics-prod.web_data.transactions` in BigQuery
-- Left join is being done according to the logins & login_days date_hit AND logins & login_days ´logins_web´ columns.
-- The specific data taken from the aforementioned BQ table is aggregated and filtered via CASE WHEN - THEN statements
-- Further conditions are specified via the WHERE statements
-- The resulting temporary table in the subquery under LEFT JOIN is named login_days.
-- The columns in the select statement before the left join (web logins, mobile logins etc)
-- are from the temporary table in the select statement under the left join statement
SELECT
logins.*,
logins_web,
mobile_logins,
logins_ios,
logins_android,
logins_final
FROM logins
LEFT JOIN (
SELECT
date_hit as date,
website_page as page,
SUM(CASE WHEN login_type = 'web' THEN SAFE_CAST(count_logins_final AS INT64) END ) AS logins_web,
COUNT(DISTINCT CASE WHEN login_type = 'mobile' THEN login_id END ) AS mobile_logins,
SUM(CASE WHEN login_type = 'ipad' THEN SAFE_CAST(count_logins_final AS INT64) END ) AS logins_ios,
COUNT(DISTINCT CASE WHEN login_type = 'android' THEN login_id END ) AS logins_android,
COUNT(DISTINCT login_id) AS logins_final,
FROM `gcp-project-223467.web.login_data`
WHERE date_hit >= "2022-01-01" AND website_page NOT IN ('Home','Team')
AND count_logins_final != 'NaN'
AND count_logins_final NOT LIKE '%,%'
AND count_logins_final > '0'
AND website_platform != 'ibes'
AND login_type = 'Successful'
GROUP BY 1, 2
)login_days
ON logins.date = login_days.date AND logins.page = login_days.page
WHERE sessions_with_logout > 0