In this post, we are going to learn how we can apply a conditional GROUP BY clause on a column, based on the values of another column. Assume that we have a table named tbl_EmpSaleDetail which contains the sales records for each employee. Let’s have a look at the table data. In the above table, […]
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
Python use case – Import data from excel to sql server table – SQL Server 2017 Read More »
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
In this post “Find and Delete all duplicate rows but keep one”, we are going to discuss that how we can find and delete all the duplicate rows of a table except one row. Assume that we have a table named tbl_sample which has four columns – EmpId, EmpName, Age, and City. This table has
Sometimes, we need to read an external CSV file using T-SQL query in SQL Server. Due to some functional limitations, we cannot use the import-export wizard functionality in such kinds of scenarios as we need the result set in the middle of the execution of the other queries. There, we can use the BULK INSERT
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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
Python use case – Convert rows into comma separated values in a column – SQL Server 2017 Read More »
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
Python use case – Dynamic UNPIVOT using pandas – SQL Server 2017 Read More »
In this post “Connecting Python 3 to SQL Server 2017 using pyodbc”, we are going to learn that how we can connect Python 3 to SQL Server 2017 to execute SQL queries. We can change the settings accordingly to connect to other versions of SQL Server also. If you are interested to know more about
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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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We know that Microsoft has integrated Python in SQL Server 2017 to enable rich data analytics capabilities within the database itself. Python is one of the most powerful languages which provides lots of built-in libraries for advanced data analytics and transformations. We can use Python for almost everything from website development to robotics and Data
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