🔅 Rapid Application Development with Python

🔊 Author: Malcolm Shore
🔸 Date: 2020-08-24
⏰ Duration: 2h 6m

🌀 Learn how to quickly develop Python graphical user interface (GUI) apps using the wxPython library, which brings the wxWidgets capability to Python, and the wxGlade tool.

📗 Topics: Rapid Application Development, Python

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🔸 Full denoscription 🔸

Developing graphical user interfaces (GUIs) in Python traditionally involves a lot of manual coding. wxGlade, a GUI designer written in Python for the wxPython GUI toolkit, was designed to help simplify this process. In this course, learn how to quickly develop Python GUI apps using the wxPython library—which brings the wxWidgets capability to Python—and the wxGlade tool. To lend each concept a real-world context, instructor Malcom Shore steps through how to build a cybersecurity compliance app based on the NIST Cybersecurity Framework. Malcom begins by detailing how to create a simple wxPython application. He then shows how to construct a user interface for your application using wxGlade and add functional application code to put the finishing touches on your project.

📦 Exercice Files

🔅 pandas Code Challenges

🔊 Author: Harshit Tyagi
🔸 Date: 2022-03-29
⏰ Duration: 1h 23m

🌀 Test your pandas knowledge with this edition of Code Challenges.

📗 Topics: Pandas

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🔸 Full denoscription 🔸

Want to test your pandas skills? These concise challenges let you stretch your brain and test your talents. Instructor Harshit Tyagi shares over a dozen pandas challenges, as well as his own solutions to each problem. Harshits challenges cover: Reading files and initial exploration of data using pandas attributes; data cleaning; creating subsets of data using indexing and slicing; writing queries to filter out rows based on conditional statements and Boolean indexing; and grouping and aggregation to answer categorical questions. Learn to apply statistical functions to groups. And since each challenge is self-contained, you can complete the course in any order—and at your own pace. Tune in to get the hands-on practice you need to keep your skills sharp.

🔅 Python for Data Science Tips, Tricks, and Techniques

🔊 Author: Ben Sullins
🔸 Date: 2022-12-02
⏰ Duration: 1h 1m

🌀 Explore a series of tips and tricks that you can put into practice to improve your skills in Python.

📗 Topics: Data Science, Python

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🔸 Full denoscription 🔸

Modern work in data science requires skilled professionals versed in analysis workflows and using powerful tools. Python can play an integral role in nearly every aspect of working with data—from ingest, to querying, to extracting and visualizing. In this course, instructor Ben Sullins highlights tips and tricks you can use right away to improve your skills in Python. Learn how to work with JSON data, CSV files, and Parquet files. Explore ways to read, inspect, and aggregate data using pandas. Plus, find out how to visualize data using basic charts, small multiples, and color in Plotly, as well as how to put the finishing touches on your data visualizations.

📦 Exercice Files

🔅 CircuitPython: Connecting a Robot Cat to the Internet

🔊 Author: Charlyn Gonda
🔸 Date: 2021-11-04
⏰ Duration: 1h 14m

🌀 Learn how to use CircuitPython for a practical, real-world project: Programming a robot cat that you control over the internet.

📗 Topics: Internet of Things, Python

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🔸 Full denoscription 🔸

While many Internet of Things projects send data to the cloud, sometimes you want a physical indication of an event from the internet. In this course, Charlyn Gonda shows you how to use CircuitPython—a version of Python specifically for microcontrollers—to program a robot cat that reacts to events while connected to the internet. Charlyn shows how to code for common hardware devices like LEDs and servos, and explains a common messaging protocol for IoT projects called message queue telemetry transport, or MQTT. If youre looking for an internet cat video that actually teaches you something useful, join Charlyn as she shows how to program this robot cat.

CircuitPython: Connecting a Robot Cat to the Internet

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🔅 Python vs. R for Data Science

🔊 Author: Lavanya Vijayan
🔸 Date: 2021-10-04
⏰ Duration: 39m

🌀 Learn about the pros and cons of using Python and R, two common programming languages, when working on data science projects.

📗 Topics: R, Python

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🔸 Full denoscription 🔸

Python and R are common programming languages used when working with data. Each language is powerful in its own way; however, it's important that you select the language that will best help you achieve your end result. In this course, data scientist and coding instructor Lavanya Vijayan helps you make this choice, sharing important considerations for using each language in various circumstances. Lavanya starts by going over the background of both languages, as well as the strengths and disadvantages of each in different scenarios. She then walks through the process of working on a data science project and how you'd handle the data at various stages using Python and R. Lavanya then covers how to analyze data using both languages. She rounds out the course by discussing the use cases that play to each language's strengths. By the end of this training, youll have the essential information you need to determine whether Python or R is right for you.This course was created by Madecraft. We are pleased to host this training in our library.

Python vs. R for Data Science

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