统计某一类别最受欢迎的商品WITH Produce AS (SELECT 'kale' as item, 23 as purchases, 'vegetable' as category UNION ALL SELECT 'orange', 2, 'fruit' UNION ALL SELECT 'cabbage', 9, 'vegetable' UNION ALL SELECT 'app
SELECT ARRAY (SELECT 1 UNION ALL SELECT 2 UNION ALL SELECT 3) AS new_array;+-----------+| new_array |+-----------+| [1, 2, 3] |+-----------+SELECT ARRAY (SELECT AS STRUCT 1, 2, 3 UNION AL
WITH Produce AS (SELECT 'kale' as item, 23 as purchases, 'vegetable' as category UNION ALL SELECT 'orange', 2, 'fruit' UNION ALL SELECT 'cabbage', 9, 'vegetable' UNION ALL SELECT 'apple', 8, 'fruit
安装postgresssudo apt-get updatesudo apt-get install postgresql-9.5进入postgresssudo -u postgres psql会有很多人问，有了mysql 为甚么还用什么postgres,这里我的回答是：mysql 中查询语法不全，在hive 和oracle,bigquery中用很多用法，mysql中没有,如简单的with as
求和WITH Produce AS (SELECT 'kale' as item, 23 as purchases, 'vegetable' as category UNION ALL SELECT 'orange', 2, 'fruit' UNION ALL SELECT 'cabbage', 9, 'vegetable' UNION ALL SELECT 'apple', 8, 'fru
编号函数概念 编号函数会根据每一行在指定窗口中的位置向该行分配整数值。RANK()、DENSE_RANK() 和 ROW_NUMBER() 示例：WITH Numbers AS (SELECT 1 as x UNION ALL SELECT 2 UNION ALL SELECT 2 UNION ALL SELECT 5 UNION ALL SELECT 8 UNION ALL SELEC
标准 SQL 中的编号函数 以下部分介绍了 BigQuery 支持的编号函数。编号函数是分析函数的一部分。 如需了解分析函数的工作原理，请参阅分析函数概念。如需了解编号函数的工作原理，请参阅编号函数概念。OVER 子句要求：PARTITION BY：可选。 ORDER BY：必需（ROW_NUMBER() 除外）。 window_frame_clause：禁止。 RANK 说明返回排序分区中各行的
分析函数针对一组行计算值，并为每行返回一个结果。这与聚合函数不同；聚合函数会为整组行返回一个结果。分析函数包含一个 OVER 子句，该子句定义了涵盖所要计算行的行窗口。对于每一行，系统会使用 - 选定的行窗口作为输入来计算分析函数结果，并可能进行聚合。借助分析函数，您可以计算移动平均值、对各项进行排名、计算累计总和，以及执行其他分析。分析函数包括以下几类：导航函数、编号函数和聚合分析函数。
WITH finishers AS (SELECT 'Sophia Liu' as name, TIMESTAMP '2016-10-18 2:51:45' as finish_time, 'F30-34' as division UNION ALL SELECT 'Lisa Stelzner', TIMESTAMP '2016-10-18 2:54:11', 'F35-39' UNION
SELECT 1 as x UNION ALL SELECT 2 UNION ALL SELECT 2 UNION ALL SELECT 5 UNION ALL SELECT 8 UNION ALL SELECT 10 UNION ALL SELECT 10;
SELECT (CAST('123' AS INT64) ) as pp 123
import pandas as pdimport pymysqlfrom sqlalchemy import create_engine#engine = create_engine(&am
新建数据库create database learn;显示数据库show databases;+--------------------+| Database |+--------------------+| information_schema || learn || mysql || perform...
import pandas as pdimport pymysqlfrom sqlalchemy import create_engineengine = create_engine("mysql+pymysql://root:root@127.0.0.1:3306/stock?charset=utf8") import tushare as ts ts.set_token('46fc...
在读取数据时候，需要输入你自己的tokenimport pandas as pdimport pymysq
改变字段类型，将表 dailykt的 ts_code字段类型改为 varchar(60)alter table dailykt modify column ts_code varchar(60);
#!/usr/bin/env python3# -*- coding: utf-8 -*-"""Created on Thu Apr 18 18:55:47 2019@author: lg"""import pandas as pdimport pymysqlfrom sqlalchemy import create_engineengine = create_engine(...
读取表dailykt 里字段ts_code='300167.SZ’的 按照 trade_date 倒序最后10条数据，select * from dailykt where ts_code='300167.SZ' order by trade_date desc limit 10 ;
#!/usr/bin/env python3# -*- coding: utf-8 -*-"""Created on Thu Apr 18 18:55:47 2019@author: lg"""import pandas as pdimport pymysqlfrom sqlalchemy import create_engine#engine = create_engi...
import psycopg2import pandas as pd#本函数用于读取某只股票的历史数据，输入的code不是股票代码而是公司内部代码def data(code): #连接数据库 conn = psycopg2.connect(dbname="db_dev_django", user="db_user", password="密...
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