data analyst | Tags | Luca Liu Blog

Why You Should Try a Local LLM Model—and How to Get Started

This article discusses the benefits of using local Large Language Models (LLMs) like LLaMA, emphasizing advantages such as enhanced privacy, speed, cost-effectiveness, and customization. It provides a step-by-step guide for Mac users on downloading and installing LM Studio, selecting and running the LLaMA model, and exploring various use cases, including integration with Obsidian and Python. The conclusion encourages developers and life hackers to embrace local LLMs as a more innovative alternative to traditional AI interactions, highlighting their potential for the future.

productivity

data analyst

Practical Tutorials

A Quick Review of SQL Window Functions with Examples

📸

Data 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 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.

Jupyter Notebook is a popular tool among data scientists and programmers for interactive data analysis, visualization, and machine learning. In this guide, we will walk you through the process of setting up Jupyer Notebook on a Windows server to enable remote access.

Combining data from multiple tables is a common requirement in Power BI. There are two primary methods to achieve this task. Using the DAX UNION function and using the Append Queries feature in Power Query are the best ways to do it. By following these two methods, you can effectively union two tables in power BI.

Python provides built-in support for working with JSON files through the json module. You can read, write, and manipulate JSON data using Python's built- in functions. To read a JSON file in Python, you can follow these steps: Import the json module, open the file, and load the contents as a Python dictionary.

In Python, you can use the pandas library to work with tabular data. The core data type in pandas is the DataFrame. Sometimes, when working with DataFrame data, you may need to convert rows to columns or columns to rows. Here is a simple example demonstrating how to achieve this.

Dynamic Show Hide Slicer Panel is a way to show or hide slicer panels in Power BI. This technique allows users to switch the visibility of slicer panel as needed, optimizing space and improving usability.

In this article, we'll explore efficient methods for updating Pandas DataFrames. We'll look at updating specific columns or rows using dictionary, updating specific values on conditions, and appending new rows. With these techniques, we can streamlined our workflows.

DAX Studio is an incredibly powerful tool that allows Power BI users to view and analyze their data model in great detail. One of the key features of DAX. Studio is its ability to extract all measures from a Power BI file. In this blog post, we will guide you through the simple steps to achieve this using DAX Studio.

The Logger class is a Python package that can be used to create and configure loggers in Python. The class uses two objects, one for general logging and one for error messages. The logger is set up to use the rotating file handler for logging messages.

When 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.