Show current row “win streak” Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern)Using Row_Number to find consecutive row countReset password for 'postgres' on v9.3 (Win Srv)Group by maximum consecutive rowMerging adjacent date intervals into a single rowTrigger function using current row and current table name as variablesTrigger function using current row and current table name as variables (final part)Selecting row grouped by an “add-on” indicatorFilter on time difference between current and next rowPostgreSQL: mark current session as “unimportant”How to count max date row if current status column is 0 or 2?

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Show current row “win streak”



Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern)Using Row_Number to find consecutive row countReset password for 'postgres' on v9.3 (Win Srv)Group by maximum consecutive rowMerging adjacent date intervals into a single rowTrigger function using current row and current table name as variablesTrigger function using current row and current table name as variables (final part)Selecting row grouped by an “add-on” indicatorFilter on time difference between current and next rowPostgreSQL: mark current session as “unimportant”How to count max date row if current status column is 0 or 2?



.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;








3















I need to show the running win/loss streak per row in a query, so given the table below, the query should return the "expected" column. I've tried some approaches with window functions, but no success.



create table matches (player text, dt date, is_winner boolean, expected integer )
insert into matches values
('A', '2019-01-01', TRUE, 0),
('A', '2019-01-03', TRUE, 1),
('A', '2019-01-04', TRUE, 2),
('A', '2019-01-09', FALSE, 0),
('A', '2019-01-10', FALSE, -1),
('A', '2019-01-15', TRUE, 0);


player dt is_winner expected
A 2019-01-01 true 0
A 2019-01-03 true 1
A 2019-01-04 true 2
A 2019-01-09 false 0
A 2019-01-10 false -1
A 2019-01-15 true 0



The logic is:



  1. Resets to 0 when winning after a loss, or losing after a win.

  2. Increments after a win, but not if it's case 1.

  3. Decrements after a loss, but not if it's case 1.

Any insights on how to tackle this are welcome. My last resort would be a function with a loop called by every row.










share|improve this question









New contributor




codigofontes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.


























    3















    I need to show the running win/loss streak per row in a query, so given the table below, the query should return the "expected" column. I've tried some approaches with window functions, but no success.



    create table matches (player text, dt date, is_winner boolean, expected integer )
    insert into matches values
    ('A', '2019-01-01', TRUE, 0),
    ('A', '2019-01-03', TRUE, 1),
    ('A', '2019-01-04', TRUE, 2),
    ('A', '2019-01-09', FALSE, 0),
    ('A', '2019-01-10', FALSE, -1),
    ('A', '2019-01-15', TRUE, 0);


    player dt is_winner expected
    A 2019-01-01 true 0
    A 2019-01-03 true 1
    A 2019-01-04 true 2
    A 2019-01-09 false 0
    A 2019-01-10 false -1
    A 2019-01-15 true 0



    The logic is:



    1. Resets to 0 when winning after a loss, or losing after a win.

    2. Increments after a win, but not if it's case 1.

    3. Decrements after a loss, but not if it's case 1.

    Any insights on how to tackle this are welcome. My last resort would be a function with a loop called by every row.










    share|improve this question









    New contributor




    codigofontes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.






















      3












      3








      3








      I need to show the running win/loss streak per row in a query, so given the table below, the query should return the "expected" column. I've tried some approaches with window functions, but no success.



      create table matches (player text, dt date, is_winner boolean, expected integer )
      insert into matches values
      ('A', '2019-01-01', TRUE, 0),
      ('A', '2019-01-03', TRUE, 1),
      ('A', '2019-01-04', TRUE, 2),
      ('A', '2019-01-09', FALSE, 0),
      ('A', '2019-01-10', FALSE, -1),
      ('A', '2019-01-15', TRUE, 0);


      player dt is_winner expected
      A 2019-01-01 true 0
      A 2019-01-03 true 1
      A 2019-01-04 true 2
      A 2019-01-09 false 0
      A 2019-01-10 false -1
      A 2019-01-15 true 0



      The logic is:



      1. Resets to 0 when winning after a loss, or losing after a win.

      2. Increments after a win, but not if it's case 1.

      3. Decrements after a loss, but not if it's case 1.

      Any insights on how to tackle this are welcome. My last resort would be a function with a loop called by every row.










      share|improve this question









      New contributor




      codigofontes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.












      I need to show the running win/loss streak per row in a query, so given the table below, the query should return the "expected" column. I've tried some approaches with window functions, but no success.



      create table matches (player text, dt date, is_winner boolean, expected integer )
      insert into matches values
      ('A', '2019-01-01', TRUE, 0),
      ('A', '2019-01-03', TRUE, 1),
      ('A', '2019-01-04', TRUE, 2),
      ('A', '2019-01-09', FALSE, 0),
      ('A', '2019-01-10', FALSE, -1),
      ('A', '2019-01-15', TRUE, 0);


      player dt is_winner expected
      A 2019-01-01 true 0
      A 2019-01-03 true 1
      A 2019-01-04 true 2
      A 2019-01-09 false 0
      A 2019-01-10 false -1
      A 2019-01-15 true 0



      The logic is:



      1. Resets to 0 when winning after a loss, or losing after a win.

      2. Increments after a win, but not if it's case 1.

      3. Decrements after a loss, but not if it's case 1.

      Any insights on how to tackle this are welcome. My last resort would be a function with a loop called by every row.







      postgresql gaps-and-islands






      share|improve this question









      New contributor




      codigofontes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      share|improve this question









      New contributor




      codigofontes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      share|improve this question




      share|improve this question








      edited 3 hours ago









      Paul White

      54.3k14288461




      54.3k14288461






      New contributor




      codigofontes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      asked 10 hours ago









      codigofontescodigofontes

      183




      183




      New contributor




      codigofontes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      New contributor





      codigofontes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






      codigofontes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.




















          1 Answer
          1






          active

          oldest

          votes


















          4














          I've done this in stages using CTEs so that you can see how it's done as the queries progress. Each CTE adds a column in the output in order to show you progress.



          It's pretty much self-documenting with the CTE names, to be honest.



          with lags as (
          select player,
          dt,
          is_winner,
          lag(is_winner) OVER (partition by player ORDER BY dt ASC) as prev_is_winner,
          expected
          from matches
          ),
          group_changes as (
          select lags.*,
          case
          when prev_is_winner <> is_winner or prev_is_winner is null
          then 1
          else 0
          end as is_new_group
          from lags
          ),
          groups_numbered as (
          select *,
          sum(is_new_group)
          over (partition by player order by dt, is_winner desc) as streak_group
          from group_changes
          ),
          expected_in_groups as (
          select groups_numbered.*,
          row_number()
          over (partition by player,streak_group
          order by dt asc, streak_group asc) - 1 as expected_unsigned
          from groups_numbered
          )
          select expected_in_groups.*, case when is_winner = 't' then expected_unsigned else expected_unsigned * -1 end as actual
          from expected_in_groups
          order by player asc, dt asc;


          DB Fiddle Link (I added an extra row just to make sure it was working at a certain point)



          Basically:




          1. lags CTE: use LAG() to get the previous result relative to the current row.


          2. group_changes CTE: Detect whether the previous streak, whether win or loss, has ended


          3. groups_numbered CTE: Give each streak a number


          4. expected_in_groups CTE: Number the rows in the group

          5. Final select: negate the loss streaks

          .



          +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
          | player | dt | is_winner | prev_is_winner | expected | is_new_group | streak_group | expected_unsigned | actual |
          +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
          | A | 2019-01-01 | t | | 0 | 1 | 1 | 0 | 0 |
          | A | 2019-01-03 | t | t | 1 | 0 | 1 | 1 | 1 |
          | A | 2019-01-04 | t | t | 2 | 0 | 1 | 2 | 2 |
          | A | 2019-01-09 | f | t | 0 | 1 | 2 | 0 | 0 |
          | A | 2019-01-10 | f | f | -1 | 0 | 2 | 1 | -1 |
          | A | 2019-01-11 | f | f | -2 | 0 | 2 | 2 | -2 |
          | A | 2019-01-15 | t | f | 0 | 1 | 3 | 0 | 0 |
          +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+





          share|improve this answer

























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            1 Answer
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            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            4














            I've done this in stages using CTEs so that you can see how it's done as the queries progress. Each CTE adds a column in the output in order to show you progress.



            It's pretty much self-documenting with the CTE names, to be honest.



            with lags as (
            select player,
            dt,
            is_winner,
            lag(is_winner) OVER (partition by player ORDER BY dt ASC) as prev_is_winner,
            expected
            from matches
            ),
            group_changes as (
            select lags.*,
            case
            when prev_is_winner <> is_winner or prev_is_winner is null
            then 1
            else 0
            end as is_new_group
            from lags
            ),
            groups_numbered as (
            select *,
            sum(is_new_group)
            over (partition by player order by dt, is_winner desc) as streak_group
            from group_changes
            ),
            expected_in_groups as (
            select groups_numbered.*,
            row_number()
            over (partition by player,streak_group
            order by dt asc, streak_group asc) - 1 as expected_unsigned
            from groups_numbered
            )
            select expected_in_groups.*, case when is_winner = 't' then expected_unsigned else expected_unsigned * -1 end as actual
            from expected_in_groups
            order by player asc, dt asc;


            DB Fiddle Link (I added an extra row just to make sure it was working at a certain point)



            Basically:




            1. lags CTE: use LAG() to get the previous result relative to the current row.


            2. group_changes CTE: Detect whether the previous streak, whether win or loss, has ended


            3. groups_numbered CTE: Give each streak a number


            4. expected_in_groups CTE: Number the rows in the group

            5. Final select: negate the loss streaks

            .



            +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
            | player | dt | is_winner | prev_is_winner | expected | is_new_group | streak_group | expected_unsigned | actual |
            +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
            | A | 2019-01-01 | t | | 0 | 1 | 1 | 0 | 0 |
            | A | 2019-01-03 | t | t | 1 | 0 | 1 | 1 | 1 |
            | A | 2019-01-04 | t | t | 2 | 0 | 1 | 2 | 2 |
            | A | 2019-01-09 | f | t | 0 | 1 | 2 | 0 | 0 |
            | A | 2019-01-10 | f | f | -1 | 0 | 2 | 1 | -1 |
            | A | 2019-01-11 | f | f | -2 | 0 | 2 | 2 | -2 |
            | A | 2019-01-15 | t | f | 0 | 1 | 3 | 0 | 0 |
            +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+





            share|improve this answer





























              4














              I've done this in stages using CTEs so that you can see how it's done as the queries progress. Each CTE adds a column in the output in order to show you progress.



              It's pretty much self-documenting with the CTE names, to be honest.



              with lags as (
              select player,
              dt,
              is_winner,
              lag(is_winner) OVER (partition by player ORDER BY dt ASC) as prev_is_winner,
              expected
              from matches
              ),
              group_changes as (
              select lags.*,
              case
              when prev_is_winner <> is_winner or prev_is_winner is null
              then 1
              else 0
              end as is_new_group
              from lags
              ),
              groups_numbered as (
              select *,
              sum(is_new_group)
              over (partition by player order by dt, is_winner desc) as streak_group
              from group_changes
              ),
              expected_in_groups as (
              select groups_numbered.*,
              row_number()
              over (partition by player,streak_group
              order by dt asc, streak_group asc) - 1 as expected_unsigned
              from groups_numbered
              )
              select expected_in_groups.*, case when is_winner = 't' then expected_unsigned else expected_unsigned * -1 end as actual
              from expected_in_groups
              order by player asc, dt asc;


              DB Fiddle Link (I added an extra row just to make sure it was working at a certain point)



              Basically:




              1. lags CTE: use LAG() to get the previous result relative to the current row.


              2. group_changes CTE: Detect whether the previous streak, whether win or loss, has ended


              3. groups_numbered CTE: Give each streak a number


              4. expected_in_groups CTE: Number the rows in the group

              5. Final select: negate the loss streaks

              .



              +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
              | player | dt | is_winner | prev_is_winner | expected | is_new_group | streak_group | expected_unsigned | actual |
              +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
              | A | 2019-01-01 | t | | 0 | 1 | 1 | 0 | 0 |
              | A | 2019-01-03 | t | t | 1 | 0 | 1 | 1 | 1 |
              | A | 2019-01-04 | t | t | 2 | 0 | 1 | 2 | 2 |
              | A | 2019-01-09 | f | t | 0 | 1 | 2 | 0 | 0 |
              | A | 2019-01-10 | f | f | -1 | 0 | 2 | 1 | -1 |
              | A | 2019-01-11 | f | f | -2 | 0 | 2 | 2 | -2 |
              | A | 2019-01-15 | t | f | 0 | 1 | 3 | 0 | 0 |
              +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+





              share|improve this answer



























                4












                4








                4







                I've done this in stages using CTEs so that you can see how it's done as the queries progress. Each CTE adds a column in the output in order to show you progress.



                It's pretty much self-documenting with the CTE names, to be honest.



                with lags as (
                select player,
                dt,
                is_winner,
                lag(is_winner) OVER (partition by player ORDER BY dt ASC) as prev_is_winner,
                expected
                from matches
                ),
                group_changes as (
                select lags.*,
                case
                when prev_is_winner <> is_winner or prev_is_winner is null
                then 1
                else 0
                end as is_new_group
                from lags
                ),
                groups_numbered as (
                select *,
                sum(is_new_group)
                over (partition by player order by dt, is_winner desc) as streak_group
                from group_changes
                ),
                expected_in_groups as (
                select groups_numbered.*,
                row_number()
                over (partition by player,streak_group
                order by dt asc, streak_group asc) - 1 as expected_unsigned
                from groups_numbered
                )
                select expected_in_groups.*, case when is_winner = 't' then expected_unsigned else expected_unsigned * -1 end as actual
                from expected_in_groups
                order by player asc, dt asc;


                DB Fiddle Link (I added an extra row just to make sure it was working at a certain point)



                Basically:




                1. lags CTE: use LAG() to get the previous result relative to the current row.


                2. group_changes CTE: Detect whether the previous streak, whether win or loss, has ended


                3. groups_numbered CTE: Give each streak a number


                4. expected_in_groups CTE: Number the rows in the group

                5. Final select: negate the loss streaks

                .



                +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
                | player | dt | is_winner | prev_is_winner | expected | is_new_group | streak_group | expected_unsigned | actual |
                +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
                | A | 2019-01-01 | t | | 0 | 1 | 1 | 0 | 0 |
                | A | 2019-01-03 | t | t | 1 | 0 | 1 | 1 | 1 |
                | A | 2019-01-04 | t | t | 2 | 0 | 1 | 2 | 2 |
                | A | 2019-01-09 | f | t | 0 | 1 | 2 | 0 | 0 |
                | A | 2019-01-10 | f | f | -1 | 0 | 2 | 1 | -1 |
                | A | 2019-01-11 | f | f | -2 | 0 | 2 | 2 | -2 |
                | A | 2019-01-15 | t | f | 0 | 1 | 3 | 0 | 0 |
                +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+





                share|improve this answer















                I've done this in stages using CTEs so that you can see how it's done as the queries progress. Each CTE adds a column in the output in order to show you progress.



                It's pretty much self-documenting with the CTE names, to be honest.



                with lags as (
                select player,
                dt,
                is_winner,
                lag(is_winner) OVER (partition by player ORDER BY dt ASC) as prev_is_winner,
                expected
                from matches
                ),
                group_changes as (
                select lags.*,
                case
                when prev_is_winner <> is_winner or prev_is_winner is null
                then 1
                else 0
                end as is_new_group
                from lags
                ),
                groups_numbered as (
                select *,
                sum(is_new_group)
                over (partition by player order by dt, is_winner desc) as streak_group
                from group_changes
                ),
                expected_in_groups as (
                select groups_numbered.*,
                row_number()
                over (partition by player,streak_group
                order by dt asc, streak_group asc) - 1 as expected_unsigned
                from groups_numbered
                )
                select expected_in_groups.*, case when is_winner = 't' then expected_unsigned else expected_unsigned * -1 end as actual
                from expected_in_groups
                order by player asc, dt asc;


                DB Fiddle Link (I added an extra row just to make sure it was working at a certain point)



                Basically:




                1. lags CTE: use LAG() to get the previous result relative to the current row.


                2. group_changes CTE: Detect whether the previous streak, whether win or loss, has ended


                3. groups_numbered CTE: Give each streak a number


                4. expected_in_groups CTE: Number the rows in the group

                5. Final select: negate the loss streaks

                .



                +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
                | player | dt | is_winner | prev_is_winner | expected | is_new_group | streak_group | expected_unsigned | actual |
                +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+
                | A | 2019-01-01 | t | | 0 | 1 | 1 | 0 | 0 |
                | A | 2019-01-03 | t | t | 1 | 0 | 1 | 1 | 1 |
                | A | 2019-01-04 | t | t | 2 | 0 | 1 | 2 | 2 |
                | A | 2019-01-09 | f | t | 0 | 1 | 2 | 0 | 0 |
                | A | 2019-01-10 | f | f | -1 | 0 | 2 | 1 | -1 |
                | A | 2019-01-11 | f | f | -2 | 0 | 2 | 2 | -2 |
                | A | 2019-01-15 | t | f | 0 | 1 | 3 | 0 | 0 |
                +--------+------------+-----------+----------------+----------+--------------+--------------+-------------------+--------+






                share|improve this answer














                share|improve this answer



                share|improve this answer








                edited 7 hours ago

























                answered 8 hours ago









                PhilᵀᴹPhilᵀᴹ

                25.9k65691




                25.9k65691




















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