how to comparison LAG function in mysql

I got complicated problem in mysql.

I have some table on mydatabase.

sample docs(this is only simple sample, actual data are so many table that I have to join)

table “merchant”

id       name
1        arief
2        john
3        chena

table “transaction”

id       product_id        price       merchant_id        date
1        1                 20000       2                  2020-02-01
2        5                 25000       1                  2020-02-01
3        2                 10000       3                  2020-02-02
4        2                 10000       2                  2020-02-02
5        3                 5000        2                  2020-02-02
5        2                 10000       2                  2020-02-03
6        3                 5000        3                  2020-02-04

I want to know the information of merchants transaction daily “before” and “after” to comparison

like this below

name_merchant    sumtrx_20-02-01     sumtrx_20-02-02      sumtrx_20-02-03      sumtrx_20-02-04
arief            1                   0                    0                    0
john             1                   2                    1                    0
chena            0                   1                    0                    1

I tried with this query

select m.name, count(trx.id, trx.date = '2020-02-01') as sumtrx_20-02-01, count(trx.id, trx.date = '2020-02-02') as sumtrx_20-02-02, count(trx.id, trx.date = '2020-02-03') as sumtrx_20-02-03, count(trx.id, trx.date = '2020-02-04') as sumtrx_20-02-04 from merchant as m join transaction as trx on m.id = trx.merchant_id
group by m.name

but that query didn’t work

Answer

You can use sum() instead of count().

SELECT m.name,
       sum(trx.date = '2020-02-01') `sumtrx_20-02-01`,
       ...
       sum(trx.date = '2020-02-04') `sumtrx_20-02-04`
       FROM merchant m
            INNER JOIN transaction trx
                       ON m.id = trx.merchant_id
       GROUP BY m.name;

And you also need to enclose identifiers, here the column aliases, in backticks if you use special characters like - in them. Or avoid using special characters in them all together.