📸A Quick Review of SQL Window Functions with ExamplesData Manipulation Language (DML) commands enable you to add, modify, or remove rows in a database. In this article, we’ll explore these commands with practical examples. The INSERT command is used to add new rows to a table. The UPDATE command allows you to modify data in existing rows. The DELETE command removes rows from a table based on a condition.
📸Tableau Desktop Public: Try the Free Version for Data VisualizationTableau Desktop Public Edition is now free and packed with advanced features previously exclusive to Tableau Desktop Professional—excluding only enterprise database connectivity. Ideal for data enthusiasts, educators, and professionals, this powerful tool supports local file use, drag-and-drop visualizations, and cloud sharing for non-commercial purposes. Learn how to download, install, and get started with creating stunning data visualizations today.
🗃️Python: Setting data types when using to_sqlWhen dealing with databases, it's important to pay attention to data types to ensure that the table structure is preserved. The following is a basic code snippet to save a DataFrame to an Oracle database using SQLAlchemy and pandas.
🌅Saving Dataframes into Oracle Database with PythonYou can use the pandas library in combination with the sqlalchemy and cx_Oracle libraries to save a dataframe to an Oracle database in Python. The table structure should match the structure of the dataframe in terms of column names and data types.
🎯Using Python to Retrieve Data Through Tableau REST-APIPython can be a powerful tool for automating this process using Tableau's REST API. We will walk through the process of using Python to extract data from the Tableau Server. The following examples demonstrate how to retrieve information about views, projects, and workbooks.
🌦️Accessing Power BI Data with Python Using Power BI REST-APIThis article provides a comprehensive guide on accessing Power BI data using Python through the Power BI Report Server REST API. It explains the capabilities of the API, including CRUD operations, and details the authentication process using NTLM. The article includes practical Python code snippets for retrieving Power BI reports, folders, refresh plans, user policies, and row-level security settings. Readers will gain insights into effectively managing and analyzing their Power BI Report Server data. Ideal for developers and data analysts looking to automate and integrate Power BI functionalities into their applications.
📌Automate SAP Report Extraction with PyAutoGUIAutomating SAP with PyAutoGUI involves using the Python package to simulate mouse clicks and keyboard inputs. It offers the advantage of not requiring extra rights and permissions, but may be less efficient and require more maintenance. This method is best for situations where access to APIs or databases is restricted and there is a need to automate tasks.
🎣Merge multiple Excel files using PythonThis article provides a comprehensive guide on how to efficiently merge multiple Excel files using Python. It highlights the challenges faced when consolidating similarly formatted Excel files and presents a Python solution utilizing the pandas and os libraries to automate the process. The code snippet allows users to easily combine their Excel files into a single merged_excel.xlsx file. For those without Python installed, alternatives like Deepnote and Google Colab are suggested, complete with step-by-step instructions. The article emphasizes the importance of ensuring consistent file formats and provides pro tips for a smooth merging experience. Perfect for data analysts and anyone needing to handle multiple Excel files regularly.
