使用 Pandas 导入多个 SQL 表
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/32912373/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Importing multiple SQL tables using pandas
提问by petercj
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:
我有一个包含多个表的数据库，我正在尝试将每个表作为 Pandas 数据框导入。我可以为单个表执行此操作，如下所示：
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)
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?
数据库中表的数量会发生变化，我希望能够随时将每个表导入到自己的数据框中。如何将所有这些表放入Pandas？
回答by elelias
Depending on your SQL server, you can inspect the tables in a database.
根据您的 SQL 服务器，您可以检查数据库中的表。
For example:
例如：
tables_df = pd.read_sql('SELECT table_name FROM database_name', conn)
Now your table names are accessible as a pandas data frame, you just need to parse it out:
现在您的表名可以作为 Pandas 数据框访问，您只需要解析它：
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)
Your dictionary frames_dictcontains all the dataframes with the table_name as the key
您的字典frames_dict包含所有以 table_name 为键的数据框
