使用Pandas导入多个SQL表 [英] Importing multiple SQL tables using pandas

问题描述

我有一个包含多个表的数据库，并且我试图将每个表作为pandas数据框导入.我可以对单个表执行以下操作:

I have a database that contains multiple tables, and I am trying to import each table as a pandas dataframe. I can do this for a single table as follows:

import pandas as pd
import pandas.io.sql as psql
import pypyodbc

conn = pypyodbc.connect("DRIVER={SQL Server};\
                        SERVER=serveraddress;\
                        UID=uid;\
                        PWD=pwd;\
                        DATABASE=db")

df1 = psql.read_frame('SELECT * FROM dbo.table1', conn)

数据库中的表数将改变，并且我希望能够随时将每个表导入其自己的数据框中.如何将所有这些桌子放入大熊猫中?

The number of tables in the database will change, and at any time I would like to be able to import each table into its own dataframe. How can I get all of these tables into pandas?

推荐答案

根据您的SQL Server，您可以检查数据库中的表.

Depending on your SQL server, you can inspect the tables in a database.

例如:

tables_df = pd.read_sql('SELECT table_name FROM database_name', conn)

现在您的表名可以作为pandas数据框访问，您只需解析一下即可:

Now your table names are accessible as a pandas data frame, you just need to parse it out:

table_name_list = tables_df.table_name

select_template = 'SELECT * FROM {table_name}'
frames_dict = {}
for tname in table_name_list:
    query = select_template.format(table_name = tname)
    frames_dict[tname] = pd.read_sql(query, conn)

您的词典frames_dict包含所有以table_name为键的数据框

Your dictionary frames_dict contains all the dataframes with the table_name as the key

这篇关于使用Pandas导入多个SQL表的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！