2 | Page | Luca Liu Blog

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.

python

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.

You 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.

Pyinstaller is an incredibly useful tool for packaging your Python code into a standalone executable file. This makes it simple to distribute and run your code on various systems.

Python 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.

In this article, we explore how to preserve formatting when saving Excel files using Python, specifically with the xlsxwriter library. Data analysts often face the challenge of converting Excel files into plain text, losing important visual cues. This guide covers essential steps such as importing the xlsxwriter package, creating worksheets for multiple pandas DataFrames, and applying various styles and formats to ensure data types like dates, integers, and decimals are displayed correctly. By setting up header formats, using different cell formats for specific data types, and adjusting column widths, readers will learn how to create well-formatted Excel files effortlessly. Follow these straightforward steps to enhance your data presentation!

This 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.