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Query Data from a Private DataBase and save it in a Pandas DataFrame

Project description

MicrosoftSQLServerToPandasDataFrame

Description

This package query data from any SQL Server Database and parse it into a Pandas Dataframe it can be useful for pipelines process and speed up your development process.

Usage

from SQLServerToPandasDataFrame import createConnection, runQuery

Base_Query = "select * from [DataBase].dbo.Table"

server = "HOST_DIRECTION"
user = "USER_NAME"
password = "PASSWORD"

conn = createConnection("MyDataBase", server, user, password)
print(runQuery(query1, conn))

Settings

This package performs by default all the connections to a SQL Server using ODBC Driver 17 for SQL Server driver. if you wanna use a different driver, please replace add the driver parameter in create Connection method.

conn = createConnection("MyDataBase", server, user, password, driver = "DRIVER OF YOUR PREFERENCE")
conn = createConnection("MyDataBase", server, user, password, driver = "ODBC Driver 17 for SQL Server")

We use Pyodbc as ODBC access library, for more driver options please ckeck the documentation PyODBC Documentation.

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