Python for Data Analytics - Full Course for Beginners

🧮 Course Problems & Certificate 👉 lukeb.co/python
📝 Course Code & Notes 👉 lukeb.co/python_repo
Connect with Kelly Adams, the course producer:
👩🏻‍💼 Kelly’s LinkedIn: www.linkedin.com/in/kellyjianadams
🌐 Kelly’s Website: 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) - huggingface.co/datasets/lukebarousse/data_jobs
- Functions Python Docs - docs.python.org/3/library/functions.html
- Python Standard Library - docs.python.org/3/library/index.html
- DateTime Docs - docs.python.org/3/library/datetime.html
- AST Docs - docs.python.org/3/library/ast.html
- Format String Literals - docs.python.org/3/reference/lexical_analysis.html#formatted-string-literals
- Pandas Docs - pandas.pydata.org/pandas-docs/stable/reference/index.html
- Matplotlib Docs - matplotlib.org/
- Matplotlib CheatSheet - matplotlib.org/cheatsheets/
2️⃣ Advanced Links
- VS Code Install - code.visualstudio.com/download
- Anaconda Install - anaconda.com/download/success
- Anaconda Docs - docs.conda.io
- Software Jobs CSV - lukeb.co/software_csv
- Joins Explained (SQL for Data Analytics) - lukeb.co/sql_joins
- Pandas Cheat Sheet - pandas.pydata.org/Pandas_Cheat_Sheet.pdf
- Seaborn Docs - seaborn.pydata.org/
3️⃣ Project Links
- Git Download - git-scm.com/downloads
- GitHub Signup - github.com/signup
- Markdown CheatSheet - www.markdownguide.org/cheat-sheet/
Social Media / Contact Me
======================
📫Newsletter: www.lukebarousse.com/
👨🏼‍💼 Linkedin: www.linkedin.com/in/luke-b/
🅧 X/Twitter: LukeBarousse
🌄 Instagram: lukebarousse
⏰ TikTok: 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

[@LukeBarousse]

Pro Tips for this 11 Hour Video: ⏪Use the "J" key to rewind 10 secs ⏩Use the "L" key to fast-forward 10 secs 🪡Precise Seeking: - Tap the screen to see the progress bar - Slide up from the scrubber (red dot) to see a row of thumbnails - Swipe on the thumbnails to find a specific moment in the video ------------------------------------------------------------------------- 👇Below are some troubleshooting steps for a common issue students have encountered: Windows Users - Conda Virtual Environment Issues (Required Steps for Windows Users): Background: By default, the terminal in VS Code on Windows, PowerShell, has a restricted execution policy. This is fancy talk for saying that certain scripts and programs are blocked from running for security concerns, with "conda" commands being one of them. There are two workarounds for this: 1. Switch from using PowerShell to Command Prompt (Easy) 2. Update PowerShell settings to allow 'conda' commands (Hard) Option 1: Switch from Powershell to Command Prompt 1. Open the Command Palette: Press Ctrl + Shift + P to open it. 2. In the Command Palette, type `Terminal: Select Default Profile` and press Enter. 3. A list of available terminal profiles will appear. Select `Command Prompt` from the list. Option 2: Update PowerShell Settings: 1. Open PowerShell as Administrator (Go to Search Bar, Type "PowerShell," Select option "Run as Administrator") 2. Check your current execution policy by running the following in the PowerShell terminal: Get-ExecutionPolicy 3. If set to "Restricted," run the following to change to a good balance of security and functionality: Set-ExecutionPolicy RemoteSigned 4. Run the following to fully setup conda to be run within PowerShell: conda init powershell -------------------------------------------------------------------------

[@aryanverma9736]

while importing matplot lib pyplot using command promt it is showing us import error.

[@LukeBarousse]

@@aryanverma9736 just tried importing these libraries in command prompt and had no issues on my ened. You may have configured something wrong or are not typing in the correct command. The best (and quite honestly fastest) approach is to go to something like ChatGPT and paste in your error; it'll be able to guide you on what's going wrong here

[@aryanverma9736]

@@LukeBarousse Thank you sir for guiding and building such an amazing course. Waiting for your next course on Excel for data analytics.😄🙏

[@jasiljazz4575]

1. **Introduction** - 00:01 2. **Python Basics** - 02:01 3. **Variables and Data Types** - 18:49 4. **Functions** - 30:05 5. **Data Types** - 39:39 6. **String Operations** - 57:28 7. **Conditional Statements** - 1:26:25 8. **Lists** - 1:34:17 9. **Dictionaries** - 1:50:04 10. **Sets and Tuples** - 2:01:58 11. **Loops** - 2:21:28 12. **List Comprehension** - 2:36:26 13. **Lambda Functions** - 3:01:33 14. **Modules** - 3:13:12 15. **Data Cleaning** - 3:28:30 16. **NumPy Basics** - 4:14:27 17. **Pandas Introduction** - 4:22:15 18. **Data Visualization with Matplotlib** - 5:17:07 19. **Setting Up Local Environment** - 6:00:26 20. **DataFrame Manipulation** - 7:01:44 21. **Advanced Pandas Operations** - 7:59:09 22. **Data Distribution Visualization** - 9:04:15 23. **Seaborn for Visualization** - 9:32:17 24. **GitHub Integration** - 9:58:43 25. **Finalizing the Project** - 11:03:37

[@ballinspalding11]

God bless you Luke, making this available for free really says a lot about the man you are.

[@humansizedaperture]

Oh eleven minutes only! …wait that’s not the minutes section of the time stamp….bookmarking, getting back to work, will return. Thank you so much for this!

[@LukeBarousse]

😂🙌

[@anonymouswizard9396]

So, did you complete it?

[@yashbharambe-n6y]

**Day 1: Course Introduction and Basics 0⃣ Course Intro 00:00 - Welcome 03:12 - What is Python? 04:51 - Intro to Course 1⃣ Basics Chapter 08:42 - Getting Started 18:51 - Variables 24:24 - Python Terms 38:04 - Data Types 48:39 - Strings 1:02:01 - ChatBot Help 1:05:03 - String Formatting 1:15:06 - Operators Part 1 1:26:15 - Conditional Statements **Day 2: Lists, Dictionaries, and Basic Data Structures 1⃣ Basics Chapter (Continued) 1:34:19 - Lists 1:49:36 - Dictionaries 1:59:47 - Sets 2:05:08 - Tuples 2:12:19 - Operators Part 2 2:20:58 - Loops 2:36:22 - List Comprehensions 2:44:07 - Exercise: Basics Day 3: Functions, Lambda, and Modules 1⃣ Basics Chapter (Continued) 2:52:02 - Functions 3:01:53 - Lambda 3:12:35 - Modules 3:28:04 - Exercise: Python Library 3:39:52 - Library 3:52:20 - Classes Day 4: Intro to Data Libraries 1⃣ Basics Chapter (Continued) 4:10:29 - NumPy: Intro 4:22:41 - Pandas: Intro 4:32:53 - Pandas: Inspection 4:47:03 - Pandas: Cleaning 4:58:29 - Pandas: Analysis 5:08:08 - Exercise: Pandas Basics 5:17:00 - Matplotlib: Intro 5:21:04 - Matplotlib: Plotting Day 5: Matplotlib Continued and Basic Exercises 1⃣ Basics Chapter (Continued) 5:34:21 - Matplotlib: Labeling 5:40:14 - Matplotlib: Pandas Plotting 5:45:40 - Exercise: Matplotlib Basics 2⃣ Advanced Chapter 5:50:35 - Python Install (Anaconda) 6:00:13 - VS Code Install 6:10:27 - Virtual Environments Day 6: Advanced Pandas 2⃣ Advanced Chapter (Continued) 6:26:52 - Pandas: Accessing Data 6:35:15 - Pandas: Data Cleaning 6:42:30 - Pandas: Data Management 6:49:11 - Pandas: Pivot Tables 6:56:35 - Pandas: Index Management 7:04:25 - Exercise: Job Demand 7:15:11 - Pandas: Merge DataFrames Day 7: More Pandas and Advanced Matplotlib 2⃣ Advanced Chapter (Continued) 7:25:27 - Pandas: Concat DataFrames 7:34:04 - Pandas: Exporting Data 7:40:29 - Pandas: Applying Functions 7:56:11 - Pandas: Explode 8:07:58 - Exercise: Trending Skills 8:16:52 - Matplotlib: Format Charts 8:29:36 - Matplotlib: Pie Plots 8:39:33 - Matplotlib: Scatter Plots Day 8: Advanced Matplotlib and Seaborn 2⃣ Advanced Chapter (Continued) 8:50:04 - Matplotlib: Advanced Customization 9:05:28 - Matplotlib: Histograms 9:10:03 - Matplotlib: Box Plots 9:21:28 - Exercise: Skill Pay Analysis 9:31:05 - Seaborn: Intro Day 9: Project Work Part 1 3⃣ Project Chapter 9:45:05 - Project: Intro 9:55:48 - Git & GitHub Setup 10:09:14 - Skill Demand 10:28:56 - Skills Trend 10:41:52 - Salary Analysis Day 10: Project Work Part 2 and Conclusion 3⃣ Project Chapter (Continued) 10:50:18 - Optimal Skills 11:02:43 - Share on GitHub 11:05:24 - Share on LinkedIn

[@humichael7228]

I almost finished the course! And I almost finished my first python project along with the course. This is hands down the best tutorial on python out there!

[@saadmayo8822]

How to access the dataset ?

[@devadharshinis525]

@@saadmayo8822 You'll find it on the Hugging Face Website.

[@ayatirfan5269]

@@saadmayo8822 same question did you find it?

[@NafishaNower]

I am halfway through this course and couldn't resist taking a moment to appreciate how clearly you have delivered all the Python concepts. You have just taught my whole four-year degree within 11 hours, and that's free of cost. You are such an amazing teacher.

[@pratikthorat3480]

You woke up and chose to upload my entire education in a 12 hour video! Thank You so much! Weekend will be fun 🎉

[@Seftehandle]

Will you do it? Please report back

[@pratikthorat3480]

@@Seftehandle I hope I can finish this in 3 days!

[@Seftehandle]

@@pratikthorat3480 the important thing is to start, right? I am also thinking of doing it.

[@pratikthorat3480]

@@Seftehandle yes it is! Just start. Does not matter how long it takes to finish the course. Just start!

[@Seftehandle]

​@@pratikthorat3480the thing is i already have basic phthon knowledge, i dont know whether to start to projects part directly

[@MOAhmed-l5t]

very wonderful, enjoyable and useful , I finished SQL course with you and now about finishing PYTHON , thank so much from my heart my best teacher online, it is Mohammed from Sudan

[@nhimallansupramaniam2626]

My god, the pivot table function is a game changer. Thank you Luke, im 81% done with the course

[@chibuezembah39]

God bless you, Luke. You announced this video during your SQL course and you fulfilled it. Thanks

[@BlackSouL24]

4:09:20 inthe function calculate bonus_rate the return statement has formatted to 0.f that's why you getting 0 instead of 0.1 bonus rate.

[@armandogutierrez2880]

Well I just finished my Data Analytics on coursera and Google, but I dont want to loose this chance. So I will start right now my corse. Thanks a lot.

[@doraskaguara37]

how was it?

[@Naeem-b4z]

this function can be written without `return` such as: 31:11 def display_job_info(job_title, location, salary): print(f"JOB: {job_title} LOCATION: {location} SALARY: {salary}")

[@maminoivan8955]

Luke Barousse, Alex the Analyst, DataWithBaraa, Mosh, Amit_Thinks and Bro Code are the BEST!!!

[@aty1532]

at 28:06 - The identity (or id) of the variables job_1, job_2, and job_3 will be the same because they all reference the same string object "Data Analyst". In the video the id for job_1 and job_2 is different which is incorrect, and it will be same as both have the same object reference "Data Analyst".

[@S1nthe0]

I also think that you are correct. ChatGPT: In Python, whether two variables have the same "ID" depends on whether they reference the same object in memory. The `id()` function in Python returns a unique identifier for an object, which is essentially its memory address. Let's explore this with your example: ```python job_1 = "data 1" job_2 = "data 1" ``` In this case, since strings in Python are immutable and the same string literals are often interned (stored in a single location to save memory), `job_1` and `job_2` might indeed reference the same object. You can check this by comparing their IDs using the `id()` function: ```python job_1 = "data 1" job_2 = "data 1" print(id(job_1)) # ID of job_1 print(id(job_2)) # ID of job_2 print(job_1 is job_2) # Check if they reference the same object ``` If you run this code, you are likely to see that both `job_1` and `job_2` have the same ID and the `job_1 is job_2` expression evaluates to `True`. This indicates that both variables reference the same string object in memory. However, if the strings were created dynamically or modified in such a way that they are no longer identical, they would have different IDs. Here's an example where two strings have the same value but are not necessarily the same object: ```python job_1 = "data " + "1" job_2 = "data 1" print(id(job_1)) # ID of job_1 print(id(job_2)) # ID of job_2 print(job_1 is job_2) # Check if they reference the same object ``` In this case, the string concatenation might result in a different object, and `job_1` and `job_2` could have different IDs, even though they contain the same string value. To summarize, in Python, two variables have the same ID if they reference the same object in memory. For string literals, this is often the case due to string interning, but it can vary depending on how the strings are created or modified.

[@mosesnyper]

Man casually dropped a whole Intro to CS course for free 😂

[@ricklove8358]

i dont normally comment on videos but to be honest you are a genius. you know exactly what you are doing. This video is so helpful. God bless you

[@faacam]

just for my ref, conda removes env 6:18:03 month extraction jan-1 feb-2 7:08:38 readme project 10:24:07 AND THANKSS A LOT FOR A GREAT COURSE! halfway through it ngl my brain is on fire but im so gonna finish this course

[@Gulhayo-v7k]

Having been watching the video for 2 hours and just saw that forgot to like it. I felt so bad for that and felt like a thankless person. Luke, your all videos are just perfect! Thank you for your hard work and dedication🥺

[@howarddantes]

a bit too fast, and some difficulty spikes --- but it's free, well organized, and it's up to me to look up stuff i don't know. 10/10. thanks man

[@Hasan-vu9ex]

Luke, thank you so much for this tutorial. I was just about to start learning Python and my favorite Data Analyst KZbinr just uploaded this gem. Can't afford to buy the certificate right now, but I definitely will pay for it in the near future just to appreciate your efforts

[@atNguyen-iw9gl]

Hi Luke, I think the Exercise Basic start at 2:44:07 have some problem, because in your example, it just return the role that have exactly skill match with my_skills list If the my_skills list have more skill than role_skill require, it will not work. I think the correct should be compare role skills to our skill, then it will more precise.

[@FranklyItsMe]

Oh my word Luke. It’s been a while…. I took Python last semester and even though I got an A, I felt like I didn’t absorb much because I was so slammed with so much hw. This is amazing!! I am SO STOKED!!! And I really love Google Collab. So I’m retaking Python with you and this is going to be fun and I’ll actually absorb it! - because it’s you! Thank you so much!!!

[@cleverhype]

Woah! Can't believe you put this up fully for free! Thank you!

[@mikelrueda6573]

Wow incredible content Luke and Kelly!! So grateful for offering the course for free, I'm sure it has been really hard work. I will definitely buy the certificate. This is hands down the best and most complete Phyton course available in KZbin. Wish you the best!!

[@amitkr_209]

Hello luke, Love your courses and videos since January 2022. Thanks for delivering such content.

[@keancabigao1461]

Just right in time! I will be transitioning my workflow from R to Python and have been looking for solid course on beginner python. Thank you!

[@Dojo.FinancialData]

Thanks for the tutorial Luke. It's always great seeing how other people use Python, learnt a couple of new tricks!

[@donnelly5757]

Thank you Luke and Kelly for putting this course together! I look forward to applying what I learn in this course to my current portfolio project! I remember writing my first Python code back in 2019 and have been on the fence as to whether it is a necessary skill to help land my first role as many will say to strictly focus on Excel, SQL, and Tableau/Power BI. Fast forward to the present and I may be finally getting a seven month contract as a Tax Analyst, which would technically be my first role as an Analyst. Looks like my knowledge in coding thanks to practicing Python is what will finally get my foot in the door on what has now been a 5+ year journey to acquire my first role!

[@albedoguardian875]

Unbelievable you put down the entire course. Bookmarked and gonna sit with Pop Corn. Thanks 😊

[@LukeBarousse]

Hope you enjoy it!

[@nutthaponrathie7145]

You haven't uploaded a new video for a while, which surprised me, and this is the answer. Thank you!

[@justinasal8886]

I completed the course and I am very impressed with its content! Luke is an engaging teacher and the course keeps your attention. It get's more complicated towards the end, but it is expected. What a great work you have done!

[@Ritz360]

This is perfect! Been looking for something like this for weeks.

[@thenicosystem8606]

Amazing. I'm half way through the Google Data Analytics Professional cert. I'm gonna learn this with SQL next

[@ahmedgalaa]

Luke, you're my hero, that's all I can tell. I just wanted to say that I trust this 11 hours video just because I finished the 4 hours PostgreSQL video and it was just fantastic. Today was a technical training day at the data analysis track provided by the Ministry of Telecommunication in Egypt and I recommended your channel to my peers and instructor especially these 2 videos of SQL and Python. Thanks a lot you're doing a fantastic job.

[@LukeBarousse]

I appreciate you recommending the channel!!

[@ninnellovrik]

The best and palatability explained course that I could find, thank you

[@johorakulsum7340]

I just finished 37 mins but I will definately complete this vdo. Your presentation , way of describing of the topis are mindblowing!! My best wishes to you!!

[@michaaelmayne3931]

Thank you for this very informative video! I have a interview this week and needed an insight. I will pay and to follow along with the practice questions

[@XPMORPHINE]

Hands down the best step by step course out there.Thnx Luke,greatly appreciated!And i hope we get more Python courses in the future.🙏

[@RakshitDwivedi-pq8qc]

Amazing course! I have a little bit knowledge on Python. It's just Day 1 of me browsing through the course and i have already finished conditional statements. It's so so good. Can't wait to reach to more advanced Python Libraries such as Pandas and Numpy.

[@ferozali6391]

will watch it all and update myself thanks a lot LUKE

[@trashboat5649]

Thanks for this tutorial!! currently watching it right now after feeling stuck in what I want to do in life, until I took interest in this course. Bless you for real for being a G by just casually uploading an 11 hour video on this!! You are a true teacher

[@letrunghieu3690]

Respect your effort Luke

[@michelcusson2673]

This is the best tutorial on Python. Thank you Luke

[@rajimajeed6563]

Just finished the course. This course revealed a lot and it really added to my prior knowledge. Now I know the secrets behind good visualization using Python. Such a good course, ran a lot of "bad boys" in this one. Thank you Luke.

[@LukeBarousse]

Congrats on finishing the course!! 🎉

[@shadafsanadi3247]

how did u acess dataset bruhhh

[@rajimajeed6563]

​@@shadafsanadi3247 Follow his instructions by either downloading the dataset from the Hugging Face website or loading it directly from the site.

[@blushandrush9584]

Great timing. I was thinking of refreshing my python skills lately. Thanks to this video there is no excuse to wait any longer😅

[@franciscogalan8017]

I'm soooo excited for this course! I'm going to go through every single minute of it. I loved the SQL course, so I'm coming in with high expectations!

[@LukeBarousse]

Hope you enjoy it!

[@abhimanyusingh3512]

9:20:29 Just in case: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11

[@LukeBarousse]

Thansk for sharing this; this is good to know

[@abhimanyusingh3512]

@@LukeBarousse You're welcome, and thank you for creating such an amazing course

[@johndomingo4165]

Amazing that you are willing to do this for free! I love the different hair styles throughout the course!

[@salahmanai2110]

Thanks Luke from a young man striving to be a good data analyst your video is helping a lot and getting me to know tricks i never seen before thanks a lot for what your doing keep it up and god bless you from tunisia🙏🙏🇹🇳

[@eldruzz]

This is just a gold masterclass. A immense thank you Luke !!

[@vaibhavpundir2998]

Thank you much Luke!! your videos are just perfect, your hardwork in creating such long video are a boon for us.

[@sinaukode]

you have share this for free, what a savior you are

[@mierky9699]

I usually don't comment on videos, but I really felt the need to thank you for this course. It helped me out more than I had ever hoped for. It has truly been a journey and I want to thank you again for the hard work you've put into making this video, especially for free. God bless you!

[@AavishSidana]

is it good for a begineer?

[@mierky9699]

@@AavishSidana yes, I highly recommend it. It's very well explained and even if let's say you don't understant the first time, you can always look back on the video or look up further information on Chat GPT

[@randallevans150]

Saved this and shared with colleagues. We are analysts but looking to grow our python skills. I am working on this over the weekend. Thank you, Luke

[@LukeBarousse]

Awesome, thank you!

[@zainsiddiqi7633]

Bro, i'm so happy that you dropped this. I just finished your SQl course and was hoping you'd have something on Python

[@thew5611]

im not skipping any of the ads in exchange for this amazing effort.

[@saumyaari3442]

after your SQL video, I was really waiting for this. so thrilled. Thanks Luke 😊

[@OnkarKasture]

Done with your SQL tutorial, now halfway there in this one. Absolutely high-quality work Luke, you got yourself a sub!

[@LukeBarousse]

Thanks for the sub!

[@yagndabhi2178]

1:13:30 1:47:18 2:03:08 2:08:01 2:27:04 2:33:02 2:36:34full 3:33:10 4:05:19 4:11:57 4:43:06

[@shreyaslahoti7542]

This stuff is amazing! Thank you for explaining all the concepts in detail. Truly appreciate the efforts.

[@erikcarantino8466]

Bro - I can’t say how impressive it is to put this for free. Insane! Least I can do is subscribe.

[@LukeBarousse]

I appreciate the sub!

[@alexandershnaidman8188]

Excellent course, clear and simple explanations! Thanks a lot! This course is Super advised

[@jopadjr]

7.4k+...Thanks. This is going to be a great adventure. Will start this weekend.

[@Qongrat]

Thank you for this I have been following you for a few years now, you are awesome!

[@shamsularifeen7245]

thank you for your hard work. you surely is giving back to the community

[@ish2222]

Bro is on a full course tutorial sprint. Just completed your SQL Data Analytics tutorial. Amazing course. Now am jumping on this. Excited!!!

[@LukeBarousse]

Hopefully Excel next!

[@ish2222]

@@LukeBarousse Let's go....

[@AbdulsanedHamid]

Data analytics should be charged for animal trafficking,couse they import pandas and feed them to python

[@abigailbotma9301]

😂don't eat the cats

[@thenaturalist7835]

😂😂😂

[@amaoppong4490]

😂😂😂😂😂

[@glenwilson]

GOD DAM...THIS IS THE BEST!!!! This will be all my spare time for the next week. Great Stuff @luke

[@EstherEmmanuel-ih3cw]

You are the best Luke. Thank you so much for making these life changing videos. God bless you

[@NotThatEnigma]

A beast of a video, so indepth...thanks so much, Luke.

[@powerplaybg007]

Love learning from you, Luke 🙂 More courses about Data Analytics, please!

[@Kishan.07824]

Hey Luke, can you please explain to me Is this entire Python for Data Analytics course covers each and every concept that is required for Data Analytics, I am on a mission to learn Basic to Advanced Python specifically for a Data Analytics Role, so before devoting my 11 hr of this course + practice hours, I want to know just confirmation from you.

[@mozo199]

Hey @luke Thanks for the course, i'm still on my way through it, I miss the sample problems you used to display after each section in SQL, appreciate the work, God bless.

[@oscaruns9200]

Hi, thank you for the course! please, in minute 27:52: I got the same id for the same example, is there any update in the python code?

[@qaiserali993]

Hats off to you Man they way to teach is very easy

[@fizzcrafts9004]

man I was waiting for this, I really like your hard work I really appreciate Luke!!! And Thank You

[@Rice0987]

1:54 how do you really speak with us.😄 Great thank you, Luke, for you videos and for this marathon in particular.🤗

[@HI-bw8fe]

I was like what the hell 11min?! 😂 and then realised almost 12h! Thanks SO much! 🥳

[@hasanalam5808]

How much time did it took?

[@MW-cs8zd]

Dang. Luke just keeps one upping himself with great content. Thank you for your efforts

[@VernHowChan]

huge kudos to you Luke. what a generous big gift this is.

[@freedommentor1]

Really loved it, Massive & fully packed one video course. Thanks Luke. 🥰

[@kashifusman5953]

Just finished the course, thank you so much Luke!

[@LukeBarousse]

Hope you enjoy it!

[@MBurnsy]

You're amazing Luke. Thanks a ton for this.

[@devgupta8657]

Love your content luke..❤ Plz create a video onhow to apply or approach for remote job in USA.

[@nimrahenna]

You nailed it Luke ❤❤ You deserve much more subscribers

[@LukeBarousse]

Thank you 🙌

[@RickTol]

A long ass video, but incredibly concise and detailed with clear communication. Very well done indeed.

[@LukeBarousse]

Long ass indeed 😂

[@vprasanna3534]

Thank you so much @LukeBarousse for the amazing content on Python, SQL, and Excel! Your tutorials have been incredibly helpful in my journey to becoming a data analyst. The step-by-step explanations and clear examples make complex topics much easier to understand. I truly appreciate all the effort you put into creating these resources. Keep up the great work - you're making a huge difference for so many of us learning these skills! 🙏

[@mrsengeel]

Luke please what are the specs of your work laptop. Thanks for the tutorial is very nice

[@solo.somewhere]

Waiting for this soooo long time. God bless you. Greetings from Algeria

[@aggu08]

Thank you for sharing Luke 🙏 👍

[@Cake-wh4pm]

I'm endlessly grateful for this!!! I love your teaching style and I feel VERY confident about the quality of your content, so basically a python course for data analytics from you is a gift to anyone in this field!! again, thank you so much for doing this!!🌟🎆

[@LukeBarousse]

🙌🙌

[@francisfuwaku-lf9tn]

i must say your sql course is fire,, i learnt a lot , and i know im going to lean a lot today.

[@Elyineify]

I just saw the repository of this on github, im so hyped that its actually out! Gj Kelly and Luke, really looking forward to dive into it

[@kahinaabbas9792]

What an opportunity for us Thank you luck for your generosity

[@harunrhimu]

Hi Luke, I just complete this course with practice for every piece of code.❤❤🔰🔰

[@LukeBarousse]

Heck yeah!!

[@mylab7064]

Amazing. You deserve a huge respect & thanks.

[@Oussamabe144]

Man, the virtual environment part felt like going through a liminal space Thank you so much

[@davidjukebox]

Hi, this is amazing!! How do you recommend splitting this up in the week?