帝王谷资源网 Design By www.wdxyy.com

背景

统计某个指标,指标按照月进行累加,注意需要按省份和年份进行分组。

PostgreSQL完成按月累加的操作

方法一、使用自关联

-- with 按月统计得到中间结果
WITH yms AS (SELECT regionid,SUM(getnum) AS getnum,SUM(dealnum) AS dealnum,to_char(qndate,'yyyy-MM') AS yearmonth
FROM t_queuenumber
GROUP BY regionid,to_char(qndate,'yyyy-MM')
ORDER BY regionid,yearmonth)-- 查用子查询解决。
SELECT s1.regionid,s1.yearmonth, getnum,dealnum,
(SELECT SUM(getnum) FROM yms s2 WHERE s2.regionid = s1.regionid AND s2.yearmonth <= s1.yearmonth AND SUBSTRING(s1.yearmonth,0,5) = SUBSTRING(s2.yearmonth,0,5) ) AS getaccumulatednum,
(SELECT SUM(dealnum) FROM yms s2 WHERE s2.regionid = s1.regionid AND s2.yearmonth <= s1.yearmonth AND SUBSTRING(s1.yearmonth,0,5) = SUBSTRING(s2.yearmonth,0,5) ) AS accumulatednum
FROM yms s1;

查询的结果如下:

PostgreSQL完成按月累加的操作

方法二、使用窗口函数

更多关于窗口函数的用法,可以参考以前的文章。窗口函数十分适合这样的场景:

 WITH yms AS (SELECT regionid,SUM(getnum) AS getnum,SUM(dealnum) AS dealnum,to_char(qndate,'yyyy-MM') AS yearmonth
 FROM t_queuenumber
 GROUP BY regionid,to_char(qndate,'yyyy-MM')
 ORDER BY regionid,yearmonth)
 -- 窗口函数的使用
 SELECT regionid,yearmonth,
 SUM(getnum) OVER(PARTITION BY regionid,SUBSTRING(yearmonth,0,5) ORDER BY yearmonth) AS getaccumulatednum,
 SUM(dealnum) OVER(PARTITION BY regionid ,SUBSTRING(yearmonth,0,5) ORDER BY yearmonth) AS dealaccumulatednum
 FROM yms; 

PostgreSQL完成按月累加的操作

后记

可以使用子查询、可以使用窗口函数完成上面业务场景。

补充:PostgreSQL实现按秒按分按时按日按周按月按年统计数据

提取时间(年月日时分秒):

import datetime
from dateutil.relativedelta import relativedelta
today = str(datetime.datetime.now())
print(today)
print(today[:4], today[:7], today[:10],today[:13])
 
print("************分隔符***************")
 
yesterday = (datetime.datetime.now() + datetime.timedelta(days=-1)).strftime("%Y-%m-%d %H:%M:%S")
yesterday2 = (datetime.datetime.now() + datetime.timedelta(days=-2)).strftime("%Y-%m-%d %H:%M:%S")
nextmonths = str(datetime.date.today() - relativedelta(months=-1))[:7]
lastmonths = str(datetime.date.today() - relativedelta(months=+1))[:7]
lastyears = str(datetime.date.today() - relativedelta(years=+1))[:4]
nextyears = str(datetime.date.today() - relativedelta(years=-1))[:4]
 
print(yesterday)
print(yesterday2)
print(nextmonths)
print(lastmonths)
print(lastyears)
print(nextyears)

结果:

2020-03-05 13:49:59.982555
2020 2020-03 2020-03-05 2020-03-05 13
************分隔符***************
2020-03-04 13:49:59
2020-03-03 13:49:59
2020-04
2020-02
2019
2021

昨日每时:

select s.acceptDate, s.data_num
 from (select to_char(acceptDate, 'yyyy-mm-dd hh24') || '点' as acceptDate,
        count(1) as data_num
     from table_name t
     where t.acceptDate >= to_date('20190506', 'yyyymmdd')
      and t.acceptDate < to_date('20190507', 'yyyymmdd') and organization_ = 'abcdefghijklmnopqrstuvwxyz' 
     group by to_char(acceptDate, 'yyyy-mm-dd hh24') || '点') s

PostgreSQL完成按月累加的操作

本月每天:

select s.acceptDate, s.data_num
 from (select to_char(acceptDate, 'yyyy-mm-dd') as acceptDate,
        count(1) as data_num
     from table_name t
     where t.acceptDate >= to_date('201905', 'yyyymm')
      and t.acceptDate < to_date('201906', 'yyyymm') and organization_ = 'abcdefghijklmnopqrstuvwxyz' 
     group by to_char(acceptDate, 'yyyy-mm-dd') ) s

PostgreSQL完成按月累加的操作

本年每月:

select s.acceptDate, s.data_num
 from (select to_char(acceptDate, 'yyyy-mm') as acceptDate,
        count(1) as data_num
     from table_name t
     where t.acceptDate >= to_date('2019', 'yyyy')
      and t.acceptDate < to_date('2020', 'yyyy') and organization_ = 'abcdefghijklmnopqrstuvwxyz' 
     group by to_char(acceptDate, 'yyyy-mm') ) s

PostgreSQL完成按月累加的操作

2月-7月中每月的人数统计:

sql = """SELECT to_char(rujiaoriqi, 'yyyy-mm') as month,count(1) num 
           FROM jibenxx where rujiaoriqi is not null and zhongzhiriqi is null 
           AND to_char(rujiaoriqi,'yyyy-mm-dd')>='2020-02-01'
           GROUP BY to_char(rujiaoriqi, 'yyyy-mm') order by to_char(rujiaoriqi, 'yyyy-mm') """

统计每年:

select s.acceptDate, s.data_num
 from (select to_char(acceptDate, 'yyyy') as acceptDate,
        count(1) as data_num
     from table_name t
     where t.acceptDate >= to_date('2015', 'yyyy')
      and t.acceptDate < to_date('2021', 'yyyy') and organization_ = 'abcdefghijklmnopqrstuvwxyz' 
     group by to_char(acceptDate, 'yyyy') ) s

PostgreSQL完成按月累加的操作

里面时间参数进行传参即可。

补充:

统计今天(查询当天或者指定某天数量)

select count(1) FROM "shequjz_jibenxx" where to_char(zhongzhiriqi,'yyyy-mm-dd')='2019-11-11' 

PostgreSQL完成按月累加的操作

最近七天每天的数量:

select s.acceptDate, s.data_num
 from (select to_char(jiaozheng_jieshushijian, 'yyyy-mm-dd') as acceptDate,
        count(1) as data_num
     from shequjz_jibenxx t
     where t.jiaozheng_jieshushijian >= to_date('2020-11-06', 'yyyy-mm-dd')
      and t.jiaozheng_jieshushijian < to_date('2020-11-13', 'yyyy-mm-dd') 
     group by to_char(jiaozheng_jieshushijian, 'yyyy-mm-dd') ) s ORDER BY acceptDate ASC

最近七天(1天、3天、7天、一个月、一年、1h、1min、60s)的数量(总量):

# 包括今天向前推6天的总量
select count(1) from shequjz_jibenxx where jiaozheng_jieshushijian 
between (SELECT current_timestamp - interval '7 day') 
and current_timestamp
# 最近一天(昨天)
SELECT current_timestamp - interval '1 day'
# 最近三天
SELECT current_timestamp - interval '3 day'
# 最近一周
SELECT current_timestamp - interval '7 day'
# 最近一个月(当前时间向前推进一个月)
SELECT current_timestamp - interval '1 month'
# 最近一年(当前时间向前推进一年)
SELECT current_timestamp - interval '1 year'
# 最近一小时(当前时间向前推一小时)
SELECT current_timestamp - interval '1 hour'
# 最近一分钟(当前时间向前推一分钟)
SELECT current_timestamp - interval '1 min'
# 最近60秒(当前时间向前推60秒)
SELECT current_timestamp - interval '60 second'

最近七天中每天的累计历史总量:

步骤:

1)先统计出近7天每天的数量

2)后统计出7天前的累计历史总量

3)再对第(1)步中获取的结果进行累计求和,使用cumsum()函数

4)最后在第(3)步结果的基础上,加上7天前的累计历史总量(也就是第2步的结果)

# 趋势
def getWeekTrends(self):
  try:
    database = DataBase()
    sql = """select s.zhongzhi_Date, s.data_num
        from (select to_char(jiaozheng_jieshushijian, 'yyyy-mm-dd') as zhongzhi_Date,
        count(1) as data_num
        from shequjz_jibenxx t
        where t.jiaozheng_jieshushijian >= to_date('{}', 'yyyy-mm-dd')
        and t.jiaozheng_jieshushijian < to_date('{}', 'yyyy-mm-dd') 
        group by to_char(jiaozheng_jieshushijian, 'yyyy-mm-dd') ) s""".format(lastweek, today[:10])
    res_df = database.queryData(sql, flag=True)
 
    sql_total = """select count(1) FROM "shequjz_jibenxx" where rujiaoriqi is not null 
           and zhongzhiriqi is null and to_char(rujiaoriqi,'yyyy-mm-dd')<'{}'""".format(lastweek)
    res_total = database.queryData(sql_total, count=1, flag=False)  #7131
 
    res_df['cumsum'] = res_df['data_num'].cumsum() # 累计求和
    res_df['cumsum'] = res_df['cumsum'] + res_total[0]
    res_df = res_df[['zhongzhi_date', 'cumsum']].to_dict(orient='records')
    res = {'code': 1, 'message': '数据获取成功', 'data': res_df}
    print(res)
    return res
  except Exception as e:
    error_info = '数据获取错误:{}'.format(e)
    logger.error(error_info)
    res = {'code': 0, 'message': error_info}
    return res
{'code': 1, 'message': '数据获取成功', 'data': [
{'zhongzhi_date': '2020-11-13', 'cumsum': 7148}, 
{'zhongzhi_date': '2020-11-10', 'cumsum': 7161}, 
{'zhongzhi_date': '2020-11-11', 'cumsum': 7195}, 
{'zhongzhi_date': '2020-11-12', 'cumsum': 7210}, 
{'zhongzhi_date': '2020-11-09', 'cumsum': 7222}, 
{'zhongzhi_date': '2020-11-14', 'cumsum': 7229}, 
{'zhongzhi_date': '2020-11-15', 'cumsum': 7238}]}

postgresql按周统计数据

(实际统计的是 上周日到周六 7天的数据):

因为外国人的习惯是一周从周日开始,二我们中国人的习惯一周的开始是星期一,这里 -1 即将显示日期从周日变成了周一,但是内部统计的数量还是从 上周日到周六进行 统计的,改变的仅仅是显示星期一的时间。

提取当前星期几: 1

SELECT EXTRACT(DOW FROM CURRENT_DATE)

提取当前日期: 2020-11-16 00:00:00

SELECT CURRENT_DATE-(EXTRACT(DOW FROM CURRENT_DATE)-1||'day')::interval diffday;

按周统计数据一:

select to_char(jiaozheng_jieshushijian::DATE-(extract(dow from "jiaozheng_jieshushijian"::TIMESTAMP)-1||'day')::interval, 'YYYY-mm-dd') date_,
count(1) from shequjz_jibenxx where jiaozheng_jieshushijian BETWEEN '2020-01-01' and '2020-11-16' 
 GROUP BY date_ order by date_

其中date_为一周中的第一天即星期一

PostgreSQL完成按月累加的操作

按周统计数据二:

SELECT
to_char ( cda.jiaozheng_jieshushijian, 'yyyy ' ) || EXTRACT ( WEEK FROM cda.jiaozheng_jieshushijian ) :: INTEGER AS date_,
count( cda.id ) AS count,
cda.jiaozheng_jieshushijian AS times 
FROM
shequjz_jibenxx AS cda
 
WHERE
1 = 1 
AND to_char ( cda.jiaozheng_jieshushijian, 'YYYY-MM-DD HH24:MI:SS' ) BETWEEN '2020-10-01 00:00:00' AND '2020-11-12 00:00:00' 
GROUP BY
date_,
times 
ORDER BY
date_,
times DESC

PostgreSQL完成按月累加的操作

postgresql中比较日期的四种方法

select * from user_info where create_date >= '2020-11-01' and create_date <= '2020-11-16' 
select * from user_info where create_date between '2020-11-01' and '2020-11-16' 
select * from user_info where create_date >= '2020-11-01'::timestamp and create_date < '2020-11-16'::timestamp 
select * from user_info where create_date between to_date('2020-11-01','YYYY-MM-DD') and to_date('2020-11-16','YYYY-MM-DD')

以上为个人经验,希望能给大家一个参考,也希望大家多多支持。如有错误或未考虑完全的地方,望不吝赐教。

标签:
PostgreSQL,按月累加

帝王谷资源网 Design By www.wdxyy.com
广告合作:本站广告合作请联系QQ:858582 申请时备注:广告合作(否则不回)
免责声明:本站文章均来自网站采集或用户投稿,网站不提供任何软件下载或自行开发的软件! 如有用户或公司发现本站内容信息存在侵权行为,请邮件告知! 858582#qq.com
帝王谷资源网 Design By www.wdxyy.com

《魔兽世界》大逃杀!60人新游玩模式《强袭风暴》3月21日上线

暴雪近日发布了《魔兽世界》10.2.6 更新内容,新游玩模式《强袭风暴》即将于3月21 日在亚服上线,届时玩家将前往阿拉希高地展开一场 60 人大逃杀对战。

艾泽拉斯的冒险者已经征服了艾泽拉斯的大地及遥远的彼岸。他们在对抗世界上最致命的敌人时展现出过人的手腕,并且成功阻止终结宇宙等级的威胁。当他们在为即将于《魔兽世界》资料片《地心之战》中来袭的萨拉塔斯势力做战斗准备时,他们还需要在熟悉的阿拉希高地面对一个全新的敌人──那就是彼此。在《巨龙崛起》10.2.6 更新的《强袭风暴》中,玩家将会进入一个全新的海盗主题大逃杀式限时活动,其中包含极高的风险和史诗级的奖励。

《强袭风暴》不是普通的战场,作为一个独立于主游戏之外的活动,玩家可以用大逃杀的风格来体验《魔兽世界》,不分职业、不分装备(除了你在赛局中捡到的),光是技巧和战略的强弱之分就能决定出谁才是能坚持到最后的赢家。本次活动将会开放单人和双人模式,玩家在加入海盗主题的预赛大厅区域前,可以从强袭风暴角色画面新增好友。游玩游戏将可以累计名望轨迹,《巨龙崛起》和《魔兽世界:巫妖王之怒 经典版》的玩家都可以获得奖励。