Python for Data Analytics - Full Course for Beginners

🧮 Course Problems & Certificate 👉 https://lukeb.co/python 📝 Course Code & Notes 👉 https://lukeb.co/python_repo My FREE Course to be a Data Analyst 👉 https://lukebarousse.com/5daycourse Connect with Kelly Adams, the course producer: 👩🏻‍💼 Kelly’s LinkedIn: https://www.linkedin.com/in/kellyjianadams 🌐 Kelly’s Website: https://www.kellyjadams.com 0️⃣ Course Intro ============== 0:00:00 - Welcome 0:03:12 - What is Python? 0:04:51 - Intro to Course 1️⃣ Basics Chapter ============== 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 2️⃣ Advanced Chapter ================ 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 3️⃣ Project Chapter =============== 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 🔗 Links Mentioned =============== 1️⃣ Basics Links - 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/ 2️⃣ Advanced Links - 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/ 3️⃣ Project Links - Git Download - https://git-scm.com/downloads - GitHub Signup - http://github.com/signup - Markdown CheatSheet - https://www.markdownguide.org/cheat-sheet/ Social Media / Contact Me ====================== 📫Newsletter: https://www.lukebarousse.com/ 👨🏼‍💼 Linkedin: https://www.linkedin.com/in/luke-b/ 🅧 X/Twitter: https://twitter.com/LukeBarousse 🌄 Instagram: https://www.instagram.com/lukebarousse/ ⏰ TikTok: https://www.tiktok.com/@lukebarousse 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