连续活跃天数统计

需求说明

什么是连续出现？

假设有如下日期信息： 20230401,20230402,20230403,20230405,20230406,20230407,20230410,20230411
则：
20230401-20230403 为一次连续出现，连续出现天数为 3
20230405-20230407 为一次连续出现，连续出现天数为 3
20230410-20230411 为一次连续出现，连续出现天数为 2

---

在一些业务场景下，我们需要找符合类似规则的的对象。这里基于Python和SQL尝试进行解决。

python版本解决方案

import pandas as pd# 计算连续出现天数
def calculate_consecutive_days(df):results = []df['日期'] = pd.to_datetime(df['日期'], format='%Y%m%d')df = df.sort_values(by=['对象ID', '日期'])# 遍历每个号码for number, group in df.groupby('对象ID''):consecutive_days = 1start_date = group['日期'].iloc[0]prev_date = group['日期'].iloc[0]details = []# 遍历每个日期for date in group['日期'].iloc[1:]:if date == prev_date + pd.Timedelta(days=1):consecutive_days += 1else:if consecutive_days > 1:details.append((start_date, prev_date, consecutive_days))consecutive_days = 1start_date = dateprev_date = date# 添加最后一个连续天数if consecutive_days > 1:details.append((start_date, prev_date, consecutive_days))# 添加结果for start, end, days in details:results.append({'对象ID': number,'连续出现天数': days,'首次发现日期': start.strftime('%Y%m%d'),'末次发现日期': end.strftime('%Y%m%d'),'连续天数详情': f"{start.strftime('%Y%m%d')}-{end.strftime('%Y%m%d')}"})return results

模拟数据这里就不提供了，下面是运行结果。

SQL版本解决方案

【基于mysql8+版本，用到了一些mysql5版本不支持的语法~】

创建模拟数据

CREATE TABLE OccurrenceDays (uid VARCHAR(100),dt DATE );INSERT INTO OccurrenceDays (uid, dt) VALUES  
('1234567890', '2023-04-01'),  
('1234567890', '2023-04-02'),  
('1234567890', '2023-04-03'),  
('1234567890', '2023-04-05'),  
('1234567890', '2023-04-06'),  
('1234567890', '2023-04-07'),  
('1234567890', '2023-04-10'),  
('1234567890', '2023-04-11'),  
('9876543210', '2023-04-02'),  
('9876543210', '2023-04-03'),  
('9876543210', '2023-04-04');

查询脚本：

WITH RankedDays AS (  SELECT   uid,  dt,  DATE_SUB(dt, INTERVAL ROW_NUMBER() OVER (PARTITION BY uid ORDER BY dt) DAY) AS grp  FROM   OccurrenceDays  
),  
GroupedDays AS (  SELECT   uid,  MIN(dt) AS start_dt,  MAX(dt) AS end_dt,  COUNT(*) AS consecutive_days  FROM   RankedDays  GROUP BY   uid, grp  HAVING   COUNT(*) > 1  
),  
ConsecutiveDetails AS (  SELECT   g.uid,  g.consecutive_days,  g.start_dt,  g.end_dt,  GROUP_CONCAT(od.dt ORDER BY od.dt SEPARATOR ',') AS consecutive_details  FROM   GroupedDays g  JOIN   OccurrenceDays od ON g.uid = od.uid AND od.dt BETWEEN g.start_dt AND g.end_dt  GROUP BY   g.uid, g.consecutive_days, g.start_dt, g.end_dt  
)  
SELECT   uid,  consecutive_days,  DATE_FORMAT(start_dt, '%Y%m%d') AS first_discovery_date,  DATE_FORMAT(end_dt, '%Y%m%d') AS last_discovery_date,  consecutive_details  
FROM   ConsecutiveDetails  
ORDER BY   uid, start_dt;

查询结果：

uid	consecutive_days	first_discovery_date	last_discovery_date	consecutive_details
1234567890	3	20230401	20230403	2023-04-01,2023-04-02,2023-04-03
1234567890	3	20230405	20230407	2023-04-05,2023-04-06,2023-04-07
1234567890	2	20230410	20230411	2023-04-10,2023-04-11
9876543210	3	20230402	20230404	2023-04-02,2023-04-03,2023-04-04

不使用CTE语法

drop  table OccurrenceDays;   
CREATE TABLE OccurrenceDays (uid VARCHAR(100),dt VARCHAR(100)
);
-- 模拟数据
INSERT INTO OccurrenceDays (uid, dt) VALUES ('1234567890', '20230401');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('1234567890', '20230402');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('1234567890', '20230403');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('1234567890', '20230405');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('1234567890', '20230406');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('1234567890', '20230407');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('1234567890', '20230410');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('1234567890', '20230411');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('9876543210', '20230402');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('9876543210', '20230403');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('9876543210', '20230404');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('9876543210', '20230405');
INSERT INTO OccurrenceDays (uid, dt) VALUES ('9876543210', '20230406');-- 查询脚本   
SELECT  uid,  COUNT(*) AS consecutive_days,  MIN(dt) AS first_occurrence_date,  MAX(dt) AS last_occurrence_date,  GROUP_CONCAT(dt ORDER BY dt) AS consecutive_days_detail  
FROM (  SELECT  uid,  dt,  dt - ROW_NUMBER() OVER (PARTITION BY uid ORDER BY STR_TO_DATE(dt, '%Y%m%d')) AS grp  FROM  OccurrenceDays  
) AS ranked_dates  
GROUP BY  uid, grp  
HAVING  COUNT(*) > 1  
ORDER BY  uid, MIN(dt);

输出结果：

uid	consecutive_days	first_occurrence_date	last_occurrence_date	consecutive_days_detail
1234567890	3	20230401	20230403	20230401,20230402,20230403
1234567890	3	20230405	20230407	20230405,20230406,20230407
1234567890	2	20230410	20230411	20230410,20230411
9876543210	5	20230402	20230406	20230402,20230403,20230404,20230405,20230406

补充:模拟数据生成脚本

import random  
import datetime  def generate_sql_inserts(uid):  # 获取当前日期  today = datetime.date.today()  # 设定近3个月的开始日期  start_date = today - datetime.timedelta(days=90)  # 初始化SQL语句列表  sql_inserts = []  # 设定要插入的数据条数，这里可以调整  num_inserts = 30  # 用于追踪连续日期的计数器  consecutive_counter = 0  last_date = None  for _ in range(num_inserts):  # 生成随机日期，在最近三个月内  random_date = start_date + datetime.timedelta(days=random.randint(0, (today - start_date).days))  random_date_str = random_date.strftime('%Y%m%d')  # 以一定概率生成连续日期  if last_date and random.random() < 0.5:  # 假设有50%的概率生成连续日期  random_date_str = (last_date + datetime.timedelta(days=1)).strftime('%Y%m%d')  consecutive_counter += 1  else:  consecutive_counter = 0  last_date = datetime.datetime.strptime(random_date_str, '%Y%m%d').date()  # 生成SQL INSERT语句  sql_insert = f"INSERT INTO OccurrenceDays (uid, dt) VALUES ('{uid}', '{random_date_str}');"  sql_inserts.append(sql_insert)  return "\n".join(sql_inserts)  # 示例使用  
uid = "a"  
sql_script = generate_sql_inserts(uid)  
print(sql_script)