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Using Python Pandas dataframe to read and insert data to Microsoft SQL Server
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...
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Real-time data visualization using R and data extracting from SQL Server
In the previous post, I have showed how to visualize near real-time data using Python and Dash module. And it is time to see one of the many ways, how to do it in R. This time, I will not use any...
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Using Python with Microsoft Reporting Services (SSRS)
Using Python with SQL Server 2017 SSRS should not be an obstacle, since the framework and the technology is the same as with R language. With SQL Server 2017, Python got a full and functional support...
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Creating data frame using structure() function in R
Structure() function is a simple, yet powerful function that describes a given object with given attributes. It is part of base R language library, so there is no need to load any additional library....
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Data engineering functions on large datasets in Microsoft Fabric
Data engineering and even simple data wrangling functions in Fabric can make several tasks faster, when you know know, which package (language) to choose. By comparing Python Pandas with PySpark...
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Some of the more useful Tidyverse functions
R functions for every data engineer using Tidyverse Tidyverse has long been an amazing collection of R packages, primarily for data engineering and data science. Common among these packages is the...
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