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

How to store mySQL query result into pandas DataFrame with pymysql?

我正在尝试使用 pymysql 将 mySQL 查询结果存储在 pandas DataFrame 中,并且 运行 在构建 DataFrame 时出错。发现了一个类似的问题 and here,但似乎有 pymysql 特定的错误被抛出:

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()

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

如果我删除 indexcolumns 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()

returns ValueError: DataFrame constructor not properly called!

提前致谢!

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))

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环境下测试过。

下面是一个例子(希望对大家有帮助):

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

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)