python use case sql

Interactive Data Analysis with HANA using Jupyter Notebook/Jupyter Lab

We have discussed that how we can use Jupyter Lab/Jupyter Notebook to do Interactive Data Analysis with SQL Server using Jupyter Notebooks. Jupyter Notebook is a very powerful and useful tool for any Data Analyst/Data Scientist. The Jupyter Lab is the next generation tool for the Jupyter Notebooks. It provides an interface where we can […]

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Convert Jupyter notebooks to PDF

Jupyter lab is the next-generation web-based UI experience for Jupyter notebook users. It facilitates a tab-based programming interface that is highly extensible and interactive. It supports 40+ programming languages. We have already discussed how we can use Jupyter notebooks for interactive data analysis with SQL Server. With the help of Jupyter notebooks, we can keep

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Interactive Data Analysis with SQL Server using Jupyter Notebooks

In this post “Interactive Data Analysis with SQL Server using Jupyter Notebooks“, we will demonstrate how we can use Jupyter Notebooks for interactive data analysis with SQL Server. Jupyter notebooks are one of the most useful tools for any Data Scientist/Data Analyst. It supports 40+ programming languages and facilitates web-based interactive programming IDE. We can

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Python use case – Export SQL table data to excel and CSV files – SQL Server 2017

In this post, we are going to discuss how we can export SQL Server table data to an Excel file or to a CSV file using Python’s pandas library. Prior to SQL Server 2017, we could use one of the below methods to export data from SQL Server to Excel or CSV file: Create an

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Python use case – Resampling time series data (Upsampling and downsampling) – SQL Server 2017

Resampling time series data in SQL Server using Python’s pandas library In this post, we are going to learn how we can use the power of Python in SQL Server 2017 to resample time series data using Python’s pandas library. Sometimes, we get the sample data (observations) at a different frequency (higher or lower) than

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Python use case – Import data from excel to sql server table – SQL Server 2017

If we need to import data from an excel file into SQL Server, we can use these methods: SQL Server Import Export Wizard Create an SSIS package to read excel file and load data into a SQL Server table Use T-SQL OPENROWSET query Use the read_excel method of Python’s pandas library (Only available in SQL Server 2017

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Python use case – Import zipped file without unzipping it in SSIS and SQL Server – SQL Server 2017

Import zipped CSV file without unzipping it in SSIS using SQL Server 2017 SQL Server Integration Services (SSIS) is one of the most popular ETL tools. It has many built-in components which can be used in order to automate the enterprise ETL(Extract, Transform, and Load). Also, if we need a customized component which is not

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Python use case – Convert rows into comma separated values in a column – SQL Server 2017

In this post, we are going to learn how we can leverage python in SQL server to generate comma separated values. If we want to combine all values of a single column it is fairly easy as we can use COALESCE function to do that. Here is a reference to the already existing post. But have

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Python use case – Dynamic UNPIVOT using pandas – SQL Server 2017

In this post, we are going to learn how we can leverage the power of Python’s pandas module in SQL Server 2017. pandas is an open source Python library providing data frame as data structure similar to the SQL table with the vectorized operation support for high performance. To know more about pandas, you can click

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Python use case – Get employees for given skill set – SQL Server 2017

In the previous blog post “Python use case – Map unequal comma separated values from two columns – SQL Server 2017“, we demonstrated a use case example of Python in SQL Server 2017. Now, in this post, “Python use case – Get employees for given skill set – SQL Server 2017”, we are going to

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