Watch Python for Data Analytics - Full Course for Beginners Video Tutorial


Tutorial Details & Info

Tutorial Title: Python for Data Analytics - Full Course for Beginners
Instructor / Channel: Luke Barousse
Lesson Runtime: 09:41 Minutes
Publish Date: June 07, 2024
Total Students / Views: 1,465,025 views

Follow step-by-step with Python for Data Analytics - Full Course for Beginners presented by Luke Barousse. This full video course has a total duration of 09:41 minutes with detailed practical demonstrations. Follow along to build your skills on any desktop PC, Mac, tablet, or smartphone.

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Course Description & Lesson Notes

Official Video Description:

๐Ÿ“ FREE Course Files & Project ๐Ÿ‘‰ https://lukeb.co/python_repo ๐Ÿ† Supporter Access: Problems, Certificate, & More ๐Ÿ‘‰ https://lukeb.co/python My FREE Course to be a Data Analyst ๐Ÿ‘‰ https://lukebarousse.com/5daycourse ๐Ÿ“Œ๐Ÿ’ฌ See pinned comment for troubleshooting tips. ๐—–๐—ต 0๏ธโƒฃ - ๐—œ๐—ป๐˜๐—ฟ๐—ผ โ–”โ–”โ–”โ–”โ–” 0:00:00 - Welcome 0:03:12 - What is Python? 0:04:51 - Intro to Course ๐—–๐—ต 1๏ธโƒฃ - ๐—•๐—ฎ๐˜€๐—ถ๐—ฐ๐˜€ โ–”โ–”โ–”โ–”โ–”โ–” 0:08:42 - Getting Started 0:18:52 - Variables 0:24:25 - Python Terms 0:38:06 - Data Types 0:48:41 - Strings 1:02:04 - ChatBot Help 1:05:06 - String Formatting 1:15:10 - Operators Part 1 1:26:20 - Conditional Statements 1:34:24 - Lists 1:49:42 - Dictionaries 1:59:54 - Sets 2:05:15 - Tuples 2:12:26 - Operators Part 2 2:21:06 - Loops 2:36:31 - List Comprehensions 2:44:16 - Exercise: Basics 2:52:12 - Functions 3:02:03 - Lambda 3:12:46 - Modules 3:28:16 - Exercise: Python Library 3:40:05 - Library 3:52:33 - Classes 4:10:44 - NumPy: Intro 4:22:56 - Pandas: Intro 4:33:09 - Pandas: Inspection 4:47:20 - Pandas: Cleaning 4:58:46 - Pandas: Analysis 5:08:26 - Exercise: Pandas Basics 5:17:19 - Matplotlib: Intro 5:21:23 - Matplotlib: Plotting 5:34:41 - Matplotlib: Labeling 5:40:34 - Matplotlib: Pandas Plotting 5:46:00 - Exercise: Matplotlib Basics ๐—–๐—ต 2๏ธโƒฃ - ๐—”๐—ฑ๐˜ƒ๐—ฎ๐—ป๐—ฐ๐—ฒ๐—ฑ โ–”โ–”โ–”โ–”โ–”โ–”โ–”โ–” 5:50:56 - Python Install (Anaconda) 6:00:34 - VS Code Install 6:10:49 - Virtual Environments (See Pinned Comment) 6:27:15 - Pandas: Accessing Data 6:35:38 - Pandas: Data Cleaning 6:42:54 - Pandas: Data Management 6:49:35 - Pandas: Pivot Tables 6:57:00 - Pandas: Index Management 7:04:50 - Exercise: Job Demand 7:15:37 - Pandas: Merge DataFrames 7:25:53 - Pandas: Concat DataFrames 7:34:31 - Pandas: Exporting Data 7:40:56 - Pandas: Applying Functions 7:56:39 - Pandas: Explode 8:08:27 - Exercise: Trending Skills 8:17:21 - Matplotlib: Format Charts 8:30:06 - Matplotlib: Pie Plots 8:40:04 - Matplotlib: Scatter Plots 8:50:35 - Matplotlib: Advanced Customization 9:06:00 - Matplotlib: Histograms 9:10:36 - Matplotlib: Box Plots 9:22:01 - Exercise: Skill Pay Analysis 9:31:39 - Seaborn: Intro ๐—–๐—ต 3๏ธโƒฃ - ๐—ฃ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜ โ–”โ–”โ–”โ–”โ–”โ–” 9:45:40 - Project: Intro 9:56:23 - Git & GitHub Setup 10:09:50 - Skill Demand 10:29:33 - Skills Trend 10:42:30 - Salary Analysis 10:50:57 - Optimal Skills 11:03:22 - Share on GitHub 11:06:04 - Share on LinkedIn ๐Ÿ”— ๐—Ÿ๐—ถ๐—ป๐—ธ๐˜€ ๐— ๐—ฒ๐—ป๐˜๐—ถ๐—ผ๐—ป๐—ฒ๐—ฑ โ–”โ–”โ–”โ–”โ–”โ–”โ–”โ–”โ–” 1๏ธโƒฃ ๐—•๐—ฎ๐˜€๐—ถ๐—ฐ๐˜€ ๐—Ÿ๐—ถ๐—ป๐—ธ๐˜€ - Dataset (Hugging Face) - https://huggingface.co/datasets/lukebarousse/data_jobs - Functions Python Docs - https://docs.python.org/3/library/functions.html - Python Standard Library - https://docs.python.org/3/library/index.html - DateTime Docs - https://docs.python.org/3/library/datetime.html - AST Docs - https://docs.python.org/3/library/ast.html - Format String Literals - https://docs.python.org/3/reference/lexical_analysis.html#formatted-string-literals - Pandas Docs - https://pandas.pydata.org/pandas-docs/stable/reference/index.html - Matplotlib Docs - http://matplotlib.org/ - Matplotlib CheatSheet - https://matplotlib.org/cheatsheets/ 2๏ธโƒฃ ๐—”๐—ฑ๐˜ƒ๐—ฎ๐—ป๐—ฐ๐—ฒ๐—ฑ ๐—Ÿ๐—ถ๐—ป๐—ธ๐˜€ - VS Code Install - https://code.visualstudio.com/download - Anaconda Install - https://anaconda.com/download/success - Anaconda Docs - https://docs.conda.io - Software Jobs CSV - https://lukeb.co/software_csv - Joins Explained (SQL for Data Analytics) - https://lukeb.co/sql_joins - Pandas Cheat Sheet - https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf - Seaborn Docs - https://seaborn.pydata.org/ 3๏ธโƒฃ ๐—ฃ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜ ๐—Ÿ๐—ถ๐—ป๐—ธ๐˜€ - Git Download - https://git-scm.com/downloads - GitHub Signup - http://github.com/signup - Markdown CheatSheet - https://www.markdownguide.org/cheat-sheet/ ๐—ฆ๐—ผ๐—ฐ๐—ถ๐—ฎ๐—น ๐— ๐—ฒ๐—ฑ๐—ถ๐—ฎ โ–”โ–”โ–”โ–”โ–”โ–” ๐Ÿ“ซNewsletter: https://www.lukebarousse.com/ ๐Ÿ‘จ๐Ÿผ‍๐Ÿ’ผ Linkedin: https://www.linkedin.com/in/luke-b/ ๐Ÿ…ง X/Twitter: https://twitter.com/LukeBarousse ๐ŸŒ„ Instagram: https://www.instagram.com/lukebarousse/ โฐ TikTok: https://www.tiktok.com/@lukebarousse Connect with Kelly Adams, the course producer: ๐Ÿ‘ฉ๐Ÿป‍๐Ÿ’ผ Kelly’s LinkedIn: https://www.linkedin.com/in/kellyjianadams ๐ŸŒ Kelly’s Website: https://www.kellyjadams.com As an Amazon, Coursera, and Parallels Affiliate Programs member, I earn a commission from qualifying purchases on the links above. It costs you nothing but helps me with content creation. #datanerd #dataanalyst #datascience

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๐ŸŽ“ Lesson Overview & Learning Outcomes:

Welcome to the step-by-step video guide for Python for Data Analytics - Full Course for Beginners taught by Luke Barousse. This tutorial provides a comprehensive walkthrough designed to take you from foundational principles to practical implementation.

๐Ÿ’ก Key Topics Covered in This Course:

  • Core Fundamentals & Setup: Understanding the workspace, essential tools, and initial setup for Python for Data Analytics - Full Course for Beginners.
  • Step-by-Step Practical Demonstration: Hands-on implementation guided by Luke Barousse 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.

๐Ÿ“‹ 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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