Jupyter Notebooks use the .ipynb format, a JSON structure containing code, Markdown, and outputs. Converting to a Python script is useful for repository storage or creating standalone packages; three methods for export are explained.
Explore the pyTZ Python package, a implementation of the tz database, to list 594 available timezones. Learn how to access and utilize timezones beyond the tz database.
Explore building an automated reporting system in Python using Jupyter Notebook and the Mercury framework. Fetch stock market data, display news, price chart, and analysis. Schedule daily execution, convert the notebook to PDF, and send it via email.
Learn to detect data drift in Machine Learning models using Python. Utilize the Evidently package for drift detection and build a dashboard in Jupyter Notebook, published as a web app with the Mercury framework.
Build a data dashboard in Python with just 9 lines of code using Jupyter Notebook. Display stock information for a selected ticker with a data table and chart. Publish it as a web app with the open-source Mercury framework.
Easily send emails from Python using the send_email() function, simplifying the process with built-in packages smtplib and email. Ideal for automation and notification applications.
Jupyter Notebook, a powerful tool for code and Markdown mixing, offers fast feedback for data analysis. This article explores various ways to install Jupyter Notebook on your local machine.
Learn how Python virtual environments work to manage dependencies, avoid conflicts, and ensure smooth execution of scripts. Avoid broken dependencies and enhance your Python development experience.