如何使用pymysql将mySQL查询结果存储到pandas DataFrame中？

Question

我正在尝试使用pymysql将 mySQL 查询结果存储在 Pandas pymysql并且在构建数据帧时pymysql错误。 在此处和此处找到了一个类似的问题，但似乎抛出了pymysql特定的错误：

import pandas as pd
import datetime
import pymysql

# dummy values 
connection = pymysql.connect(user='username', password='password', databse='database_name', host='host')

start_date = datetime.datetime(2017,11,15)
end_date = datetime.datetime(2017,11,16)

try:
    with connection.cursor() as cursor:
    query = "SELECT * FROM orders WHERE date_time BETWEEN %s AND %s"

    cursor.execute(query, (start_date, end_date)) 

    df = pd.DataFrame(data=cursor.fetchall(), index = None, columns = cursor.keys())
finally:
    connection.close()

返回： AttributeError: 'Cursor' object has no attribute 'keys'

如果我删除index和columns参数：

try:
    with connection.cursor() as cursor:
    query = "SELECT * FROM orders WHERE date_time BETWEEN %s AND %s"

    cursor.execute(query, (start_date, end_date)) 

    df = pd.DataFrame(cursor.fetchall())
finally:
    connection.close()

返回ValueError: DataFrame constructor not properly called!

提前致谢！

Answer 1

为此使用Pandas.read_sql() ：

query = "SELECT * FROM orders WHERE date_time BETWEEN ? AND ?"
df = pd.read_sql(query, connection,  params=(start_date, end_date))

Answer 2

感谢您建议使用 pandas.read_sql()。 它也适用于执行存储过程！ 我在 MSSQL 2017 环境中对其进行了测试。

下面是一个例子（我希望它可以帮助其他人）：

def database_query_to_df(connection, stored_proc, start_date, end_date):
    # Define a query
    query ="SET NOCOUNT ON; EXEC " + stored_proc + " ?, ? " + "; SET NOCOUNT OFF"

    # Pass the parameters to the query, execute it, and store the results in a data frame
    df = pd.read_sql(query, connection, params=(start_date, end_date))
    return df

Answer 3

试试这个：

import pandas as pd
import pymysql

mysql_connection = pymysql.connect(host='localhost', user='root', password='', db='test', charset='utf8')
                    
sql = "SELECT * FROM `brands`"
df = pd.read_sql(sql, mysql_connection, index_col='brand_id')
print(df)