MySqlの月次データから移動平均を計算する

Question

MySqlの月次データから移動平均を計算したいと考えています。

team_idの前回の12か月間のデータを使用して、 の平均販売数を計算します。

特定の月にteam_idが見つからない場合は、その月をとしてください。

もう一つの注意点： 我々はOctober 2016である場合、私は September 2016からSeptember 2015になるように移動平均ウィンドウをしたいと思います。ここで

動作しません。私の試みです：

SELECT t1.monthyear 
    , t2.team_id 
    , t1.itemssold 
    , AVG(t2.itemssold) AS avgTransactions 
    FROM t1 
    JOIN t1 AS t2 
    ON PERIOD_DIFF(t2.monthyear,t1.monthyear) = 12 
    AND (t2.team_id = t1.team_id) 
GROUP 
    BY t1.team_id 
    , monthyear; 

一部のデータ：

monthyear tmonth tyear team_id ItemsSold 
201405 5 2014 23 1 
201406 6 2014 23 3 
201407 7 2014 23 5 
201408 8 2014 23 3 
201409 9 2014 23 7 
201410 10 2014 23 1 
201411 11 2014 23 4 
201501 1 2015 23 6 
201502 2 2015 23 2 
201503 3 2015 23 2 
201504 4 2015 23 5 
201505 5 2015 23 5 
201506 6 2015 23 6 
201507 7 2015 23 11 
201508 8 2015 23 13 
201509 9 2015 23 5 
201601 1 2016 23 14 
201602 2 2016 23 4 
201603 3 2016 23 3 
201604 4 2016 23 10 
201605 5 2016 23 9 
201606 6 2016 23 7 
201409 9 2014 83 1 
201511 11 2015 83 1 
201604 4 2016 83 4 
201605 5 2016 83 1 
201606 6 2016 83 3 
201405 5 2014 88 1 
201406 6 2014 88 3 
201407 7 2014 88 4 
201408 8 2014 88 3 
201409 9 2014 88 6 
201410 10 2014 88 7 
201411 11 2014 88 5 
201412 12 2014 88 11 
201501 1 2015 88 8 
201502 2 2015 88 5 
201503 3 2015 88 6 
201504 4 2015 88 3 
201505 5 2015 88 11 
201506 6 2015 88 6 
201507 7 2015 88 12 
201508 8 2015 88 14 
201509 9 2015 88 11 
201510 10 2015 88 12 
201511 11 2015 88 14 
201512 12 2015 88 13 
201601 1 2016 88 7 
201602 2 2016 88 10 
201603 3 2016 88 15 
201604 4 2016 88 11 
201605 5 2016 88 14 
201606 6 2016 88 10 
201410 10 2014 131 2 
201501 1 2015 131 1 
201505 5 2015 131 1 
201509 9 2015 131 2 
201407 7 2014 135 2 
201503 3 2015 135 1 
201509 9 2015 135 1 
201603 3 2016 135 1 
201605 5 2016 135 1 
201405 5 2014 140 15 
201406 6 2014 140 18 
201407 7 2014 140 14 
201408 8 2014 140 21 
201409 9 2014 140 22 
201410 10 2014 140 19 
201411 11 2014 140 18 
201412 12 2014 140 13 
201501 1 2015 140 25 
201502 2 2015 140 17 
201503 3 2015 140 26 
201504 4 2015 140 17 
201505 5 2015 140 14 
201506 6 2015 140 16 
201507 7 2015 140 20 
201508 8 2015 140 17 
201509 9 2015 140 23 
201510 10 2015 140 19 
201511 11 2015 140 12 
201512 12 2015 140 4 

Answer 1

あなたは日付テーブルにこの

+------+------------+----------+------------------+-------------------+--------+ 
| id | dte  | CalMonth | CalMonthDescLong | CalMonthDescShort | calQtr | 
+------+------------+----------+------------------+-------------------+--------+ 
| 1 | 2000-01-01 |  1 | January   | Jan    |  1 | 
| 2 | 2000-01-02 |  1 | January   | Jan    |  1 | 
| 3 | 2000-01-03 |  1 | January   | Jan    |  1 | 
| 4 | 2000-01-04 |  1 | January   | Jan    |  1 | 
| 5 | 2000-01-05 |  1 | January   | Jan    |  1 | 
+------+------------+----------+------------------+-------------------+--------+ 

のようなものを持っている場合は、ダミーを生成することがありました欠けている日付のエントリ

select distinct year(dte) * 100 + month(dte) monthyear, month(dte) as tmonth, year(dte) as tyear, t1.team_id,0 as itemssold 
from dates 
cross join (select distinct t.team_id from t) t1 
where year(dte) * 100 + month(dte) >= (select min(monthyear) from t) and year(dte) * 100 + month(dte) <= (select max(monthyear) from t) 
     and t1.team_id = 23 

そしてこの

select s.team_id,s.monthyear,s.tmonth,s.tyear, 
     sum(case when s.itemssold is null then 0 else s.itemssold end) itemsold 
from 
(
select distinct year(dte) * 100 + month(dte) monthyear, month(dte) as tmonth, year(dte) as tyear, t1.team_id,0 as itemssold 
from dates 
cross join (select distinct t.team_id from t) t1 
where year(dte) * 100 + month(dte) >= (select min(monthyear) from t) and year(dte) * 100 + month(dte) <= (select max(monthyear) from t) 
     and t1.team_id = 23 
union 
select t.monthyear,t.tmonth,t.tyear,t.team_id,t.ItemsSold from t 
) s 
group by s.team_id,s.monthyear,s.tmonth,s.tyear 

などの実際のデータとダミーエントリをマージし、別のバージョンに参加し、移動平均

select t2.team_id,t2.monthyear,t2.itemsold 
     ,sum(t3.itemsold) sold,count(*) obs 
     ,AVG(t3.itemsold * 1.00) AS avgTransactions 

from 
(
select s.team_id,s.monthyear,s.tmonth,s.tyear, 
     sum(case when s.itemssold is null then 0 else s.itemssold end) itemsold 
from 
(
select distinct year(dte) * 100 + month(dte) monthyear, month(dte) as tmonth, year(dte) as tyear, t1.team_id,0 as itemssold 
from dates 
cross join (select distinct t.team_id from t) t1 
where year(dte) * 100 + month(dte) >= (select min(monthyear) from t) and year(dte) * 100 + month(dte) <= (select max(monthyear) from t) 
     #and t1.team_id = 23 
union 
select t.monthyear,t.tmonth,t.tyear,t.team_id,t.ItemsSold from t 
) s 
group by s.team_id,s.monthyear,s.tmonth,s.tyear 
) t2 
join 
(
select s.team_id,s.monthyear,s.tmonth,s.tyear, 
     sum(case when s.itemssold is null then 0 else s.itemssold end) itemsold 
from 
(
select distinct year(dte) * 100 + month(dte) monthyear, month(dte) as tmonth, year(dte) as tyear, t1.team_id,0 as itemssold 
from dates 
cross join (select distinct t.team_id from t) t1 
where year(dte) * 100 + month(dte) >= (select min(monthyear) from t) and year(dte) * 100 + month(dte) <= (select max(monthyear) from t) 
     #and t1.team_id = 23 
union 
select t.monthyear,t.tmonth,t.tyear,t.team_id,t.ItemsSold from t 
) s 
group by s.team_id,s.monthyear,s.tmonth,s.tyear 
) t3 
on t2.team_id = t3.team_id and (t3.tyear * 12 + t3.tmonth between (t2.tyear * 12 + t2.tmonth) - 11 and (t2.tyear * 12 + t2.tmonth)) 
group by t2.team_id,t2.monthyear desc 

（一部を）うまく

を引き起こします

+---------+-----------+----------+------+-----+-----------------+ 
| team_id | monthyear | itemsold | sold | obs | avgTransactions | 
+---------+-----------+----------+------+-----+-----------------+ 
|  23 | 201606 |  7 | 76 | 12 |  6.333333 | 
|  23 | 201605 |  9 | 75 | 12 |  6.250000 | 
|  23 | 201604 |  10 | 71 | 12 |  5.916667 | 
|  23 | 201603 |  3 | 66 | 12 |  5.500000 | 
|  23 | 201602 |  4 | 65 | 12 |  5.416667 | 
|  23 | 201601 |  14 | 63 | 12 |  5.250000 | 
|  23 | 201512 |  0 | 55 | 12 |  4.583333 | 
|  23 | 201511 |  0 | 55 | 12 |  4.583333 | 
|  23 | 201510 |  0 | 59 | 12 |  4.916667 | 
|  23 | 201509 |  5 | 60 | 12 |  5.000000 | 
|  23 | 201508 |  13 | 62 | 12 |  5.166667 | 
|  23 | 201507 |  11 | 52 | 12 |  4.333333 | 
|  23 | 201506 |  6 | 46 | 12 |  3.833333 | 
|  23 | 201505 |  5 | 43 | 12 |  3.583333 | 
|  23 | 201504 |  5 | 39 | 12 |  3.250000 | 
|  23 | 201503 |  2 | 34 | 11 |  3.090909 | 
|  23 | 201502 |  2 | 32 | 10 |  3.200000 | 
|  23 | 201501 |  6 | 30 | 9 |  3.333333 | 
|  23 | 201412 |  0 | 24 | 8 |  3.000000 | 
|  23 | 201411 |  4 | 24 | 7 |  3.428571 | 
|  23 | 201410 |  1 | 20 | 6 |  3.333333 | 
|  23 | 201409 |  7 | 19 | 5 |  3.800000 | 
|  23 | 201408 |  3 | 12 | 4 |  3.000000 | 
|  23 | 201407 |  5 | 9 | 3 |  3.000000 | 
|  23 | 201406 |  3 | 4 | 2 |  2.000000 | 
|  23 | 201405 |  1 | 1 | 1 |  1.000000 | 
|  83 | 201606 |  3 | 9 | 12 |  0.750000 | 
|  83 | 201605 |  1 | 6 | 12 |  0.500000 |