SQL calculates daily new users and retention rate indicators

show databases;
--  Select a database to build a database 
use tempt2022;
--  User registry 
create table user_info(user_id varchar(10) primary key,reg_time datetime);

insert into user_info values
('u_01','2020-01-01 09:15:00'),
('u_02','2020-01-01 00:04:00'),
('u_03','2020-01-01 22:16:00'),
('u_04','2020-01-01 20:32:00'),
('u_05','2020-01-01 13:59:00'),
('u_06','2020-01-01 21:28:00'),
('u_07','2020-01-01 14:03:00'),
('u_08','2020-01-01 11:00:00'),
('u_09','2020-01-01 23:57:00'),
('u_10','2020-01-01 04:46:00'),
('u_11','2020-01-02 14:21:00'),
('u_12','2020-01-02 11:15:00'),
('u_13','2020-01-02 07:26:00'),
('u_14','2020-01-02 10:34:00'),
('u_15','2020-01-02 08:22:00'),
('u_16','2020-01-02 14:23:00'),
('u_17','2020-01-03 09:20:00'),
('u_18','2020-01-03 11:21:00'),
('u_19','2020-01-03 12:17:00'),
('u_20','2020-01-03 15:26:00');

--  Login log table 
create table login_log(user_id varchar(10),login_time datetime,primary key(user_id,login_time));

insert into login_log values
('u_02','2020-01-02 00:14:00'),
('u_10','2020-01-02 08:32:00'),
('u_03','2020-01-02 09:20:00'),
('u_08','2020-01-02 10:07:00'),
('u_04','2020-01-02 10:29:00'),
('u_09','2020-01-02 11:45:00'),
('u_05','2020-01-02 12:19:00'),
('u_01','2020-01-02 14:29:00'),
('u_15','2020-01-03 00:26:00'),
('u_14','2020-01-03 11:18:00'),
('u_11','2020-01-03 13:18:00'),
('u_16','2020-01-03 14:33:00'),
('u_06','2020-01-04 07:51:00'),
('u_18','2020-01-04 08:11:00'),
('u_07','2020-01-04 09:27:00'),
('u_10','2020-01-04 10:59:00'),
('u_20','2020-01-04 11:51:00'),
('u_03','2020-01-04 12:37:00'),
('u_17','2020-01-04 15:07:00'),
('u_08','2020-01-04 16:35:00'),
('u_01','2020-01-04 19:29:00'),
('u_14','2020-01-05 08:03:00'),
('u_12','2020-01-05 10:27:00'),
('u_15','2020-01-05 16:33:00'),
('u_19','2020-01-06 09:03:00'),
('u_20','2020-01-06 15:26:00'),
('u_04','2020-01-08 11:03:00'),
('u_05','2020-01-08 12:54:00'),
('u_06','2020-01-08 19:22:00'),
('u_13','2020-01-09 10:20:00'),
('u_15','2020-01-09 16:40:00'),
('u_18','2020-01-10 21:34:00');

show tables;
select * from  user_info limit 10; 

#  Add... Every day DNU, Next day retention rate ,3 Daily retention rate ,7 Daily retention rate 

select  *  
from user_info a 
left join login_log b on a.user_id = b.user_id;

/* *  The next day ：1 month 1 New users registered on the th , stay 1 month 2 It's the day of landing app, I.e. login date  -  Registration date  = 1 God  * 3 Daily retention ：1 month 1 New users registered on the th , stay 1 month 4 It's the day of landing app, I.e. login date  -  Registration date  = 3 God  * 7 Daily retention ：1 month 1 New users registered on the th , stay 1 month 8 It's the day of landing app, I.e. login date  -  Registration date  = 7 God  * */

select  date(reg_time) as dt
       ,count(distinct a.user_id) as  Number of new users 
       ,sum(datediff(login_time,reg_time) = 1) as  Number of users retained in the next day 
       ,sum(datediff(login_time,reg_time) = 3) as  Number of users retained in three days 
       ,sum(datediff(login_time,reg_time) = 7) as  Number of users retained in seven days 
       ,concat(round(sum(datediff(login_time,reg_time) = 1)/ count(distinct a.user_id)*100,0),'%') as  Next day retention rate 
       ,concat(round(sum(datediff(login_time,reg_time) = 3)/ count(distinct a.user_id)*100,1),'%') as  Three day retention rate 
       ,concat(round(sum(datediff(login_time,reg_time) = 7)/ count(distinct a.user_id)*100,2),'%') as  Seven day retention rate 
from user_info a 
left join login_log b on a.user_id = b.user_id
group by date(reg_time);