primo_dataflow_topshot_missing_play_type
Updated 2022-07-22
99
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
›
⌄
--Create an analysis on NBA Top Shots moments and attempt to uncover any correlations between a specific category and sales volume.
--This week, focus specifically on the play_type column in the flow.core.dim_topshot_metadata table.
--What play_types do users hold most, and how much volume in sales do these play_types generate? Include any other transactional metrics you can think of.
select
case when d.PLAY_TYPE is null then 'Missing Play Type' else 'Have Play Type' end dim_table
, count(distinct s.tx_id) sales_ct
, count(distinct s.nft_id) nft_ct
from flow.core.fact_nft_sales s
left join flow.core.dim_topshot_metadata d
on s.nft_id = d.nft_id
where s.tx_succeeded = TRUE
and s.nft_collection = 'A.0b2a3299cc857e29.TopShot'
group by 1
Run a query to Download Data