利用pandas实现从数据库读写数据

可以使用pandas的 

1、read_sql_query来执行sql语句

2、read_sql实现获取整个表的数据

3、to_sql实现向数据库中添加数据

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1. read_sql_table(table_name, con[, schema, ...])           Read SQL database table into a DataFrame. 
2. read_sql_query(sql, con[, index_col, ...])                      Read SQL query into a DataFrame. 
3. read_sql(sql, con[, index_col, ...])                                 Read SQL query or database table into a DataFrame. 
4. DataFrame.to_sql(name, con[, flavor, ...])                    Write records stored in a DataFrame to a SQL database.

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实例：

 

1. today = datetime.datetime.now()
2. daogang = today.replace(hour =8, minute=10,second=3)
3. ligang = today.replace(hour =17, minute=05,second=3)
4. logindate = daogang.strftime('%Y-%m-%d')
5. df['logindate'] = logindate

1. [m1,n1] = df.shape

1. for i in range(m1):

1. daogang_time = (daogang-datetime.timedelta(minutes = random.randint(0,15),seconds=random.randint(0,59))).strftime('%H:%M:%S')
2. ligang_time = (ligang-datetime.timedelta(minutes = random.randint(0,10),seconds=random.randint(0,59))).strftime('%H:%M:%S')
3. df.iloc[i,5] = daogang_time
4. df.iloc[i,6] = ligang_time
5. engine = create_engine('mysql+pymysql://root:123456@localhost:3306/office?charset=utf8')
6. loginList = pd.read_sql_query("select * from kaoqin_sub where logindate ='"+str(logindate)+u"'", engine)

1. [m2,n2] = loginList.shape   

1. mypd = loginList[0:m1].copy()
2. mypd = mypd.drop([u"daogang_time","ligang_time"],axis=1)

1. if m2 > 0:
2. for i in range(m1):

1. mypd.loc[i,"id"] = df.loc[i,"id"]
2. mypd.loc[i,u"name"] = df.loc[i,u"name"]
3. mypd.loc[i,u"groupid"] = df.loc[i,u"groupid"]
4. mypd.loc[i,u"dept"] = df.loc[i,u"dept"]
5. mypd.loc[i,u"logindate"] = df.loc[i,u"logindate"]
6. mypd.loc[i,u"daogang_time"] = df.loc[i,u"daogang_time"]
7. mypd.loc[i,u"ligang_time"] = df.loc[i,u"ligang_time"]
8. mypd.loc[i,u"daogang_IP"] = df.loc[i,u"daogang_IP"]
9. mypd.loc[i,u"ligang_IP"] = df.loc[i,u"ligang_IP"]
10. mypd.to_sql('kaoqin_sub',engine,if_exists='append',index=False)