When determining the ordering of rows and columns in cohort grids, Sisense for Cloud Data Teams examines the order of your underlying data. In most cases, this produces a result in the desired order. Sometimes however, there's that one pesky column that looks like it's in the wrong spot. What's going on here?
Turns out, the underlying data doesn't have a value associated with that pivot for the first row. In other words, if I have data for January, February, April, etc but not March for the first year I am showing data, then March will appear at the end of the list of months.
How do we work around this? By creating a list of combinations via a cross join and left joining our data set onto this list of combinations! The below snippet creates a cross join to generate a comprehensive list of days and weeks from our demo database (a hypothetical gaming company).
First, we need to generate a list of weeks:
with
t1 as (
select distinct
[created_at:week] as week_of
from
purchases
)
Then, we need to generate a list of days:
, t2 as (
select distinct
extract(dow from created_at) as ordering
, case
when extract(dow from created_at) = 0
then 'Sunday'
when extract(dow from created_at) = 1
then 'Monday'
when extract(dow from created_at) = 2
then 'Tuesday'
when extract(dow from created_at) = 3
then 'Wednesday'
when extract(dow from created_at) = 4
then 'Thursday'
when extract(dow from created_at) = 5
then 'Friday'
else 'Saturday'
end as day_of_week
from
purchases
)
Putting them together in the cross join:
, combinations as (
select
t1.week_of
, t2.day_of_week
from
t1
, t2
order by
1
, t2.ordering
)
After this, we just need to make sure to "Preserve Sort Order" in the "Format Chart" tab on the right hand side of our editor. Once we have this list, we just need to left join our data set and voila! Perfectly ordered cohort grids!
