Watch Python Data Analysis and Visualization Course – Astronomical Data Video Tutorial


Tutorial Details & Info

Tutorial Title: Python Data Analysis and Visualization Course – Astronomical Data
Instructor / Channel: freeCodeCamp.org
Lesson Runtime: 31:58 Minutes
Publish Date: January 20, 2024
Total Students / Views: 136,981 views

Follow step-by-step with Python Data Analysis and Visualization Course – Astronomical Data presented by freeCodeCamp.org. The total lesson runtime is 31:58 minutes with crystal clear HD video and audio quality. Watch this video tutorial for free without any subscription or sign-up required.

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Course Description & Lesson Notes

Official Video Description:

Learn data analysis, data visualizations, and image processing techniques using real-world astronomical data. The course offers a practical, hands-on approach to simplifying complex concepts in data analysis, making it great for beginners. Code: https://drive.google.com/drive/folders/1KufkfHYGUyQmqexkKjgGJZgWgeh69ENf?usp=sharing ✏️ Course developed by @Spartificial Spartificial Website: https://spartificial.com/ ❤️ Try interactive Python courses we love, right in your browser: https://scrimba.com/freeCodeCamp-Python (Made possible by a grant from our friends at Scrimba) ⭐️ Contents ⭐️ ⌨️ (0:00:34) Introduction to Course ⌨️ (0:03:54) Introduction to Google Colab ⌨️ (0:09:13) Python Comments ⌨️ (0:14:39) Variables and Constants ⌨️ (0:21:26) Basic Data Types ⌨️ (0:33:06) f-string ⌨️ (0:42:14) User inputs ⌨️ (0:47:43) Data Type Conversions ⌨️ (0:59:34) Control Flow ⌨️ (1:19:34) Functions ⌨️ (1:46:05) Intro to Tabular Dataset ⌨️ (1:48:14) Importing the libraries for tabular dataset ⌨️ (1:51:44) Exploring the tabular dataset ⌨️ (2:08:55) Creating First Visualization with barplot matplotlib ⌨️ (2:12:48) Adding customization to barplot ⌨️ (2:31:26) Creating bargraph using Seaborn ⌨️ (2:39:54) Visusalizing outliers using boxplot ⌨️ (2:46:13) Introducing subplots using matplotlib ⌨️ (2:53:57) Line plots ⌨️ (3:05:04) Pair plot and scatter plot ⌨️ (3:16:25) Creating HR Diagram ⌨️ (3:49:18) Downloading visualizations ⌨️ (3:54:44) Understanding Images, pixels, grayscale and colors ⌨️ (4:07:44) What are FITS file? ⌨️ (4:11:24) Installing Astroquery ⌨️ (4:13:44) SkyView Form - Virtual Telescope ⌨️ (4:19:12) Visualize Andromeda galaxy ⌨️ (4:41:14) Creating FITS file and testing ⌨️ (4:52:19) Pixel Distribution ⌨️ (5:01:39) MinMax Pixel Scaling ⌨️ (5:12:30) Standard Scaling, Log Normalization, Square root normalization ⌨️ (5:22:34) ZScaleInterval ⌨️ (5:43:39) Convolution Operation - Why? Why? and Demonstration ⌨️ (5:50:13) Gaussian Denoising ⌨️ (6:02:21) Enhancing features with Meijering and Sato filter ⌨️ (6:11:12) Corner Foerstner - What and How to use it in Python ⌨️ (6:19:21) Multiscale Basic Features using skimage ⌨️ (6:30:02) Conclusion 🎉 Thanks to our Champion and Sponsor supporters: 👾 davthecoder 👾 jedi-or-sith 👾 南宮千影 👾 Agustín Kussrow 👾 Nattira Maneerat 👾 Heather Wcislo 👾 Serhiy Kalinets 👾 Justin Hual 👾 Otis Morgan 👾 Oscar Rahnama -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

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🎓 Lesson Overview & Learning Outcomes:

Welcome to the step-by-step video guide for Python Data Analysis and Visualization Course – Astronomical Data taught by freeCodeCamp.org. This tutorial provides a comprehensive walkthrough designed to take you from foundational principles to practical implementation.

💡 Key Topics Covered in This Course:

  • Core Fundamentals & Setup: Understanding the workspace, essential tools, and initial setup for Python Data Analysis and Visualization Course – Astronomical Data.
  • Step-by-Step Practical Demonstration: Hands-on implementation guided by freeCodeCamp.org with real-world examples.
  • Best Practices & Key Shortcuts: Time-saving workflows, keyboard shortcuts, and industry-standard recommendations.
  • Troubleshooting & Common Pitfalls: How to avoid common beginner errors and optimize your workflow for peak efficiency.

📋 Recommended Prerequisites & Study Notes:

No prior advanced experience is required. Follow along with the video player above on any desktop computer, tablet, or mobile device. Pause and rewind at key steps to practice along with the instructor.

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