Interacting With SQL Server From Pandas

Tomaz Kastrun shows how to use pyodbc to interact with a SQL Server database from Pandas:

In the SQL Server Management Studio (SSMS), the ease of using external procedure sp_execute_external_script has been (and still will be) discussed many times. But the reason for this short blog post is the fact that, changing Python environments using Conda package/module management within Microsoft SQL Server (Services), is literally impossible. Scenarios, where you want to build  a larger set of modules (packages) but are impossible to be compatible with your SQL Server or Conda, then you would need to set up a new virtual environment and start using Python from there.

Communicating with database to load the data into different python environment should not be a problem. Python Pandas module is an easy way to store dataset in a table-like format, called dataframe. Pandas is very powerful python package for handling data structures and doing data analysis.

Click through for examples of reading and writing data.

Related Posts

Naive Bays in R

Zulaikha Lateef takes us through the Naive Bayes algorithm and implementations in R: Naive Bayes is a Supervised Machine Learning algorithm based on the Bayes Theorem that is used to solve classification problems by following a probabilistic approach. It is based on the idea that the predictor variables in a Machine Learning model are independent of […]

Read More

Forensic Accounting: Cohort Analysis

I continue my series on forensic accounting techniques with cohort analysis: In the last post, we focused on high-level aggregates to gain a basic understanding of our data. We saw some suspicious results but couldn’t say much more than “This looks weird” due to our level of aggregation. In this post, I want to dig […]

Read More

Categories

July 2018
MTWTFSS
« Jun Aug »
 1
2345678
9101112131415
16171819202122
23242526272829
3031