I am trying to get the number of appointments for each month.
The results are grouped into each month for a rolling-12-months graph.
I have the following Query:
SELECT a.time AS appointmentdatetime,
m.text AS ref_month_text,
m.month AS ref_month_int,
YEAR(TIME) AS appointmentyear,
COUNT(a.id) AS COUNT
FROM ref_months m LEFT JOIN
appointment a
ON m.month = MONTH(a.time) AND
a.time >= DATE_ADD(NOW(), INTERVAL - 12 MONTH)
AND a.dealershipid = '1' AND a.dealerstatus != 'No-Show'
GROUP BY m.month
ORDER BY appointmentyear ASC, m.month ASC
This is the result:
+----------------+--------------------+-------+--+
| ref_month_text | appointmentyear | COUNT | |
+----------------+--------------------+-------+--+
| February | 2019 | 16 | |
| March | 2019 | 18 | |
| April | 2019 | 10 | |
| May | 2019 | 15 | |
| June | 2019 | 18 | |
| July | 2019 | 10 | |
| August | 2019 | 12 | |
| September | 2019 | 20 | |
| October | 2019 | 7 | |
| November | 2019 | 13 | |
| December | 2019 | 7 | |
| January | 2020 | 11 | |
+----------------+--------------------+-------+--+
The grouping by month, on a rolling-12-months, and showing null when no data, is what I am getting, but the issue I am having is that the count is wrong for each month.
Eg. March 2019 should be 20.
I have tried all variations of JOIN types. But still returning wrong figures.
I simplified your query
SELECT
YEAR(a.time) AS year,
ANY_VALUE(MONTHNAME(a.time)) AS month,
ANY_VALUE(COUNT(a.id)) AS counter,
MONTH(a.time) AS mo
FROM
appointment AS a
GROUP BY
year,mo
ORDER BY
year ASC,
mo ASC
Related
select * from new_joiner;
+------+--------------+
| id | date_of_join |
+------+--------------+
| 1 | 2020-01-10 |
| 2 | 2020-01-02 |
| 3 | 2020-01-05 |
| 4 | 2020-02-10 |
| 5 | 2020-02-11 |
| 6 | 2020-07-11 |
| 7 | 2020-07-11 |
| 8 | 2020-07-11 |
| 9 | 2020-07-11 |
| 10 | 2020-07-11 |
| 11 | 2020-05-01 |
| 12 | 2020-05-02 |
| 13 | 2020-05-03 |
| 14 | 2020-05-04 |
| 15 | 2020-05-05 |
| 16 | 2020-05-05 |
| 17 | 2020-05-06 |
+------+--------------+
select MONTHNAME(date_of_join) as MONTHNAME,
count(id) as JOINEE
from new_joiner
where MONTH(date_of_join)>=1
group by MONTH(date_of_join);
+-----------+--------+
| MONTHNAME | JOINEE |
+-----------+--------+
| January | 3 |
| February | 2 |
| May | 7 |
| July | 5 |
+-----------+--------+
I want a query that gives me the monthly data change compare to previous month.
For example: new joinee in Jan was 3, and in Feb it was 2, so compare to Jan in Feb month -1 joined, so the query should output me:
+-----------+-------------+
| MONTHNAME | JOINEE_DIFF |
+-----------+-------------+
| February | -1 |
| Mar | -2 |
| April | 0 |
| May | 7 |
| June | -7 |
| July | 5 |
| Aug | -5 |
| Sep | 0 |
| Oct | 0 |
| Nov | 0 |
| Dec | 0 |
+-----------+-------------+
Ignore Jan as it doesn't have a previous month and assume we have data only for a given year say 2020. Require data for all months from Feb to Dec.
Assuming you have data for every month, you can use lag():
select MONTHNAME(date_of_join) as MONTHNAME,
count(id) as JOINEE,
(count(*) - lag(count(*)) over (order by min(date_of_join)) as diff
from new_joiner
where MONTH(date_of_join) >= 1
group by MONTH(date_of_join);
Note that using months without years if fraught with peril. Also, the month() of any well-formed date should be larger than 1.
All this suggests a query more like:
select *
from (select MONTHNAME(date_of_join) as MONTHNAME,
count(id) as JOINEE,
(count(*) - lag(count(*)) over (order by min(date_of_join)) as diff,
min(date_of_join) as min_date_of_join
from new_joiner
where date_of_join >= '2020-01-01' and date_of_join < '2021-01-01'
group by MONTH(date_of_join)
) t
where diff is not null
order by min_date_of_join;
Use a correlated subquery to get the number of joinees of previous month and subtract it:
SELECT
t.monthname,
joinee - (SELECT COUNT(*) FROM new_joiner WHERE MONTH(date_of_join) = t.month - 1) JOINEE_DIFF
FROM (
SELECT MONTH(date_of_join) month, MONTHNAME(date_of_join) monthname,
COUNT(id) joinee
FROM new_joiner
GROUP BY month, monthname
) t
WHERE t.month > 1;
t_table looks like:
+-----------+---------+--------------+------------------+-----------------------+----------------------------------+
| pk_IdLoan | fk_IdCar| fk_IdCustomer| fk_Source_Agency | fk_Destination_Agency | RentalDate | DeliveryDate | Cost |
+-----------+---------+--------------+------------------+-----------------------+----------------------------------+
I wrote a query:
(SELECT fk_IdCustomer, MONTHNAME(RentalDate) AS Month, YEAR(RentalDate) As Year, COUNT(*)
FROM t_loan
GROUP BY fk_IdCustomer, Month, Year);
which results in
+---------------+-------------+------+----------+
| fk_IdCustomer | Month | Year | COUNT(*) |
+---------------+-------------+------+----------+
| 1 | July | 2016 | 3 |
| 1 | November | 2017 | 1 |
| 1 | September | 2016 | 7 |
| 5 | May | 2016 | 1 |
| 6 | January | 2016 | 1 |
| 6 | September | 2017 | 2 |
+---------------+-------------+------+----------+
Now I want to get these months and years for each customer which result in highest COUNT(*), f.e.:
+---------------+-------------+------+----------+
| fk_IdCustomer | Month | Year | COUNT(*) |
+---------------+-------------+------+----------+
| 1 | September | 2016 | 7 |
| 5 | May | 2016 | 1 |
| 6 | September | 2017 | 2 |
+---------------+-------------+------+----------+
How to achieve this?
This is a bit painful in MySQL, which doesn't support CTEs or window functions. One method is:
SELECT fk_IdCustomer, MONTHNAME(RentalDate) AS Month,
YEAR(RentalDate) As Year, COUNT(*) as cnt
FROM t_loan l
GROUP BY fk_IdCustomer, Month, Year
HAVING cnt = (SELECT COUNT(*)
FROM t_loan l2
WHERE l2.fk_IdCustomer = l.fk_IdCustomer
GROUP BY MONTHNAME(RentalDate), YEAR(RentalDate)
ORDER BY COUNT(*) DESC
LIMIT 1
);
Note: If there are duplicates, you will get all matching values.
Let's say I have a table "calendar"
+------------+
| day_date |
+------------+
| 2015-01-01 |
| 2015-01-02 |
| 2015-01-03 |
| .......... |
| 2015-07-14 |
| 2015-07-15 |
+------------+
With this query I can select the WEEK (that I need)
SELECT WEEK(day_date,1) AS NUM_WEEK,
YEAR(day_date) AS YEAR,
STR_TO_DATE(CONCAT(YEAR(day_date),WEEK(day_date,1),' Monday'), '%X%V %W') AS date_start
FROM calendar
GROUP BY NUM_WEEK
And this is the result:
+----------+------+------------+
| NUM_WEEK | YEAR | date_start |
+----------+------+------------+
| 29 | 2015 | 2015-07-20 |
| 30 | 2015 | 2015-07-27 |
| 31 | 2015 | 2015-08-03 |
| 32 | 2015 | 2015-08-10 |
| 33 | 2015 | 2015-08-17 |
| 34 | 2015 | 2015-08-24 |
| 35 | 2015 | 2015-08-31 |
| 36 | 2015 | 2015-09-07 |
| 37 | 2015 | 2015-09-14 |
| 38 | 2015 | 2015-09-21 |
| 39 | 2015 | 2015-09-28 |
| 40 | 2015 | 2015-10-05 |
| 41 | 2015 | 2015-10-12 |
| 42 | 2015 | 2015-10-19 |
| 43 | 2015 | 2015-10-26 |
+----------+------+------------+
Now I have another table:
+----+------------+--------+---------------------+
| id | id_account | amount | date_transaction |
+----+------------+--------+---------------------+
| 1 | 283 | 150 | 2015-06-21 15:50:47 |
| 2 | 283 | 47.74 | 2015-07-23 15:55:44 |
| 3 | 281 | 21.55 | 2015-08-24 12:27:11 |
| 4 | 283 | 11.22 | 2015-08-25 10:00:54 |
+----+------------+--------+---------------------+
They are gaps in date.
With a similar query:
SELECT WEEK(date_transaction,1) AS NUM_WEEK,
YEAR(date_transaction) AS YEAR,
STR_TO_DATE(CONCAT(YEAR(date_transaction),WEEK(date_transaction,1),' Monday'), '%X%V %W')
AS date_start,
transaction.id_account,
SUM(amount) as total FROM transaction
INNER JOIN account ON account.id_account = transaction.id_account
WHERE amount > 0 AND transaction.id_account
IN ( SELECT id_account FROM account WHERE id_customer = 12 )
GROUP BY id_account, WEEK(date_transaction,1)
I obtain this result (probably data are not accurate, referring to previous tables, just to explain).
+----------+------+------------+-----------+----------+
| NUM_WEEK | YEAR | date_start | idAccount | total |
+----------+------+------------+-----------+----------+
| 29 | 2015 | 2015-07-20 | 281 | 22377.00 |
| 30 | 2015 | 2015-07-27 | 281 | 11550.00 |
| 32 | 2015 | 2015-08-04 | 281 | 4500.00 |
| 30 | 2015 | 2015-07-27 | 283 | 1500 |
+----------+------+------------+-----------+----------+
What I would, RIGHT (or LEFT) JOINING the two tables?
The min (and max) WEEK, so I can... (see 2)
Fill the gaps with missing WEEKS with NULL VALUES.
E.g., in a more complicated resultset:
+----------+------+------------+-----------+----------+
| NUM_WEEK | YEAR | date_start | idAccount | total |
+----------+------+------------+-----------+----------+
| 29 | 2015 | 2015-07-20 | 281 | 22377.00 |
| 30 | 2015 | 2015-07-27 | 281 | 11550.00 |
| 31 | 2015 | 2015-07-02 | 281 | NULL |
| 32 | 2015 | 2015-08-09 | 281 | 4500.00 |
| 29 | 2015 | 2015-08-09 | 283 | NULL |
| 30 | 2015 | 2015-07-16 | 283 | 1500 |
| 31 | 2015 | 2015-07-16 | 283 | NULL |
| 32 | 2015 | 2015-07-16 | 283 | NULL |
+----------+------+------------+-----------+----------+
Note, for example, that id=283 now has NULL at WEEK 29, 31 and 32, for example, like id=281 has NULL in WEEK 31.
I prepared also SQLFiddle here: http://sqlfiddle.com/#!9/a8fdc/3
Thank you very much.
I take a look on your question and i came up with this solution. Here is how your query could look like:
SELECT t1.NUM_WEEK, t1.`YEAR`, t1.date_start, t1.id_account, t2.total
FROM (SELECT c.NUM_WEEK, c.`YEAR`, c.date_start, a.id_account
FROM (SELECT WEEK(day_date,1) AS NUM_WEEK,
YEAR(day_date) AS `YEAR`,
STR_TO_DATE(CONCAT(YEAR(day_date),WEEK(day_date,1),' Monday'), '%X%V %W') AS date_start,
(SELECT GROUP_CONCAT(id_account) FROM account WHERE id_customer=12) AS accounts_id
FROM calendar
GROUP BY NUM_WEEK) c
INNER JOIN account a
ON FIND_IN_SET(a.id_account, c.accounts_id)
ORDER BY a.id_account, c.NUM_WEEK) t1
LEFT JOIN
(SELECT WEEK(t.date_transaction,1) AS NUM_WEEK,
YEAR(t.date_transaction) AS `YEAR`,
STR_TO_DATE(CONCAT(YEAR(t.date_transaction),WEEK(t.date_transaction,1),' Monday'), '%X%V %W') AS date_start,
t.id_account, SUM(t.amount) AS total
FROM `transaction` t
INNER JOIN account a
ON a.id_account = t.id_account
WHERE t.amount > 0 AND
t.id_account IN (SELECT id_account FROM account WHERE id_customer = 12)
GROUP BY id_account, WEEK(date_transaction,1)) t2
ON t1.NUM_WEEK = t2.NUM_WEEK AND t1.YEAR = t2.YEAR AND t1.id_account = t2.id_account;
Here is SQL Fiddle for that so you can check up result. Hope that is what are you looking for.
Little explanation:
First think i done is that I little modified your first query where you extract data from table calendar and add there one new column called accounts_id. That query now look's like this:
SELECT WEEK(day_date,1) AS NUM_WEEK,
YEAR(day_date) AS `YEAR`,
STR_TO_DATE(CONCAT(YEAR(day_date),WEEK(day_date,1),' Monday'), '%X%V %W') AS date_start,
(SELECT GROUP_CONCAT(id_account) FROM account WHERE id_customer=12) AS accounts_id
FROM calendar
GROUP BY NUM_WEEK
Please pay attention on this line in SELECT statement
(SELECT GROUP_CONCAT(id_account) FROM account WHERE id_customer=12) AS accounts_id
Note that when you select for specific customer you need to change customer ID in this line too!!!
Here is Fiddle so you can check result that this query produce.
This is necessary because we need to connect each week with each account to get desired result.
Next step is to extend previous query so we could separate accounts_id column (look result of previous query) so we could get row for each value in that column. Extended query look like this:
SELECT c.NUM_WEEK, c.`YEAR`, c.date_start, a.id_account
FROM (SELECT WEEK(day_date,1) AS NUM_WEEK,
YEAR(day_date) AS `YEAR`,
STR_TO_DATE(CONCAT(YEAR(day_date),WEEK(day_date,1),' Monday'), '%X%V %W') AS date_start,
(SELECT GROUP_CONCAT(id_account) FROM account WHERE id_customer=12) AS accounts_id
FROM calendar
GROUP BY NUM_WEEK) c
INNER JOIN account a
ON FIND_IN_SET(a.id_account, c.accounts_id)
ORDER BY a.id_account, c.NUM_WEEK
and output you can see in this Fiddle
After that all we need to do is to make left join between this query and query you already wrote in your question (last query).
There might be a better solution or even this one maybe can be improved a little, but I don't have much time now to deal with that and this is the first think that cross my mind...
GL!
P. S. pay attention when you use reserved word in MySQL like YEAR, TRANSACTION etc for column name (as column_name).. that can cause you a treble if have to use them in name of column or table use backquote () to mark them (asyear`)...
I am having an issue with incorrect counts for a query which is as follows:
mysql> SELECT DATE_FORMAT(FROM_UNIXTIME(timestamp), '%M') AS month,
YEAR(FROM_UNIXTIME(timestamp)) AS year, count(*) AS count FROM table1 WHERE
result LIKE '%created%' GROUP BY YEAR(FROM_UNIXTIME(timestamp)),
MONTH(FROM_UNIXTIME(timestamp)) DESC;
+-----------+------+-------+
| month | year | count |
+-----------+------+-------+
| September | 2011 | 1 |
| December | 2013 | 393 |
| November | 2013 | 70 |
| September | 2014 | 233 |
| August | 2014 | 739 |
| July | 2014 | 691 |
| June | 2014 | 618 |
| May | 2014 | 120 |
| March | 2014 | 272 |
| February | 2014 | 528 |
| January | 2014 | 607 |
+-----------+------+-------+
11 rows in set (0.40 sec)
However, when I check my work by using another syntax I get different results:
mysql> select count(*) from table1 where result like '%created%' and
timestamp >= unix_timestamp('2014-07-01') and timestamp <= unix_timestamp('2014-07-31');
+----------+
| count(*) |
+----------+
| 662 |
+----------+
1 row in set (0.39 sec)
What is wrong with the syntax?
In the second query use < unix_timestamp('2014-08-01'). I think you filter out everything that happened after 2014-07-31 00:00:00 am. There are still 24 hours in that day that shouldn't be filtered.
I want query from sql server 2088 R2. But it's duplicate values.
I need it's not duplicate values.
Code:
Select es.EmpCode,es.Eff,es.Year,MAX(es.Month)
From SP_EffEmpAnalysis es
Where es.Year = '2012'
Group By es.EmpCode,es.Eff,es.Year
Order By es.EmpCode,MAX(es.Month) desc
Output
EmpCode | Eff | Year | Month
1410013 | 0 | 2012 | 11
1450021 | 0.952700018882751 | 2012 | 8
1460037 | 0.653999984264374 | 2012 | 9
1460037 | 0.809899985790253 | 2012 | 8
1460037 | 0.863600015640259 | 2012 | 7
1460047 | 0.796299993991852 | 2012 | 7
1480013 | 0 | 2012 | 11
1480080 | 0.91839998960495 | 2012 | 12
1480080 | 0.982299983501434 | 2012 | 11
1480080 | 1.08259999752045 | 2012 | 10
1480080 | 0.989700019359589 | 2012 | 9
I need ouput
EmpCode | Eff | Year | Month
1410013 | 0 | 2012 | 11
1450021 | 0.952700018882751 | 2012 | 8
1460037 | 0.653999984264374 | 2012 | 9
1460047 | 0.796299993991852 | 2012 | 7
1480013 | 0 | 2012 | 11
1480080 | 0.91839998960495 | 2012 | 12
I think what you are looking for is the last month's values per employee. You can get that with the row-number function:
SELECT EmpCdoe, Eff, Year, Month
FROM(
SELECT *,ROW_NUMBER()OVER(PARTITION BY EmpCode ORDER BY Year DESC, Month DESC) AS frn
WHERE Year = '2012'
)X
WHERE frn=1
ORDER BY EmpCode;
Sebastian typed faster, but I think this is more complete:
select EmpCode, Eff, Year, Month
from (
select es.EmpCode, es.Eff, es.Year, es.Month,
Row_Number() over ( partition by es.EmpCode order by es.Year desc, es.Month desc ) as RN
from SP_EffEmpAnalysis es
where es.Year = '2012' ) as Placeholder
where RN = 1
order By es.EmpCode