Simplify your Quarto, Shiny, & Streamlit Deployments with Posit Connect Cloud! Get started using this link: https://pos.it/keith_pcc This comprehensive crash course introduces you to Quarto - an open-source publishing system that combines the simplicity of Markdown with the power of Python. Learn how to create professional reports, slideshows, websites, and dashboards that bridge the gap between your code and your audience. What You'll Learn: * Quarto Basics: Installation, markdown fundamentals, and embedding Python code in your documents * Multiple Output Formats: Transform your Quarto files into HTML, PDF, presentations, and more * Custom Styling: Master fenced divs, page layouts, and design options to create visually appealing documents * Parameterized Reports: Generate multiple custom reports from a single template file * Real-World Applications: Build analytics reports, presentations, and websites with practical examples * Deployment Options: Share your work with teammates using Posit Connect Cloud Perfect for data scientists, analysts, and developers who want to communicate their work more effectively. This crash course provides all the tools you need to start creating polished, professional documents that showcase your Python analyses. #python #quarto #datascience Links! PDF Analytics Reports Video: https://youtu.be/Q3phTByW138?si=W4Z1b6I3pgY3iJuW Check out the website built! https://quartoisfun.com Book a consultation with me (Upwork): https://www.upwork.com/services/product/marketing-keith-1514312208968638464?ref=project_share Source Code — Quarto Crash Course: https://github.com/KeithGalli/quarto-crash-course Quarto Projects: https://github.com/KeithGalli/quarto-projects/tree/master Data Portfolio Website: https://github.com/KeithGalli/quarto-portfolio Miscellaneous Resources — Bootstrap Icons: https://icons.getbootstrap.com/ Airbnb Data: https://insideairbnb.com/get-the-data/ Video Timeline! 0:00:00 - Video Overview Part 1: Quarto Crash Course 0:03:02 - Introduction & Quarto Overview 0:04:26 - Installation, Setup & Markdown Basics 0:11:00 - Styling & Formatting (CSS, fenced divs) 0:21:51 - Parameters & CLI Options 0:43:00 - HTML, Publishing & Static Docs 0:57:07 - Dashboards & Slideshows 1:18:25 - Websites & Automated Report Generation Part 2: Generate 100s of Reports in Minutes! (Parameterized Reporting) 1:38:38 - Overview & Starter Code 1:41:58 - Passing Parameters (Python & R) 1:45:14 - Dynamically Generating Markdown (asis) 1:50:34 - Adding Images, Graphs & Pagebreaks 1:56:32 - Tying Everything Together & Styling Part 3: Convert Jupyter Notebooks into Analytics Reports 2:04:29 - Overview & Accessing Code/Data 2:06:15 - Rendering Notebook as HTML 2:07:59 - Quick Report Improvements (YAML, hiding code) 2:12:44 - Business Context & Insights 2:18:59 - Aesthetic Refinements & Publishing Part 4: Real-World Dashboard Project (Airbnb Review Analysis) 2:38:27 - Overview & Data Setup 2:40:05 - Dashboard Layout & Value Boxes 2:55:27 - Matplotlib Visualizations & Folium Map 3:11:45 - Interactive Tables (itables) 3:20:50 - Shiny Integration & Hosting Part 5: Create Slideshows with Python & Markdown Code 3:30:54 - Overview & Slideshow Basics 3:37:09 - PPTX & RevealJS Outputs 3:45:34 - Data Visualizations & Dataframes 3:49:09 - Presentation Features & Shortcuts 4:00:08 - _brand.yml Styling & Notebook to RevealJS Part 6: Build a Data Science Portfolio Website 4:11:04 - Overview & Getting Started (Quarto, Python) 4:23:50 - Sidebar, Navigation & Custom Themes 4:39:42 - Adding Social Media Links 4:40:54 - Extra Sections & Navbar 4:51:29 - Deployment & Custom Domains ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

In this video we walk through a few simple tips to improve the cleanliness of your Python code. To do this we make use of the pyjanitor library. This video was inspired by a recent live stream we did where we analyzed internet usage data. Here’s a link to the Internet Usage Analysis Live Stream: https://www.youtube.com/live/m6v7a3sZlL8?si=l2RaS5GDhjWS9CXK Documentation on Pyjanitor: https://pyjanitor-devs.github.io/pyjanitor/ Hope you all enjoy! Let me know if you have ideas for future videos :) ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

In this live stream we will walk through some real-world data analysis skills with Python while raising money for charity! Github repo: https://github.com/KeithGalli/internet-usage-analysis I've partnered with Give Internet to help provide laptops & internet access to students in need from around the world. Learn more at giveinternet.org/keithgalli. ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

Check out the Kaggle Notebook I created! https://www.kaggle.com/code/keithgalli/gemini-for-u-s-legislation-understanding In this video we try out the Google Gemini API with 1,000,000+ Token Context windows as part of a Kaggle competition. If you have any questions about the project, let me know in the comments! ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

In this video, we're speed-running the creation of an animated line graph visualization comparing AMD, Intel, and Nvidia stock prices over time using Python and matplotlib! We'll go from raw data to a polished animation in minutes, utilizing AI assistance from Claude to help accelerate our development. You'll see how to load and process stock data, create dynamic visualizations with moving price labels, and export the final result as both MP4 and GIF formats. Whether you're interested in data visualization, financial analysis, or just want to see how AI can help speed up coding workflows, this tutorial has something for you! All the code is available in the description below. Let's dive in! Link to Code: https://github.com/KeithGalli/time-series-animations Check out the other video on bar chart races! https://youtu.be/mafzIn8TneQ?si=E3TLplnVhMdAY0aL #python #matplotlib #datavisualization Music by Dyce: https://www.instagram.com/agodnameddyce/?igsh=aGxtMHJ3bGY1Z3Y%3D ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

Learn how to create fun animated bar chart races in Python using matplotlib! This tutorial walks through building population trend visualizations from scratch, covering data processing, basic plotting, animation techniques, and styling improvements. Perfect for anyone interested in data visualization who wants to recreate those engaging animated charts you've seen online. We'll turn static data into dynamic visualizations using just Python and matplotlib. Link to Code: https://github.com/KeithGalli/time-series-animations Link to Dataset: https://population.un.org/wpp/Download/Standard/MostUsed/ Video Timeline! 0:00 - Video Overview 1:01 - Step 0.) Find a Dataset to Use (link in description) 1:43 - Step 1.) Initial Data Processing/Cleaning 5:17 - Step 2.) Plot Static Bar Chart using Matplotlib 8:27 - Step 3.) Create animation using Matplotlib FuncAnimation & Save it as mp4 video 15:39 - Step 4.) Improve Formatting & Styles #python #matplotlib #datavisualization ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

In this video we discuss 5 Python libraries that you may not know about now, but you'll be happy to learn about. From progress bars with tqdm to code formatting with ruff, these tools will improve your Python development workflows! Here are some code samples: https://github.com/KeithGalli/good-to-know-python-libraries Here's the Reddit thread I mentioned: https://www.reddit.com/r/Python/comments/1dsyi19/what_are_your_glad_to_have_met_you_packages/ Video Timeline! 0:00 - Introduction 0:40 - 1.) tqdm 3:39 - 2.) rich 8:49 - 3.) pathlib 12:40 - 4.) pydantic 19:12 - 5.) ruff While prepping this video, here are some YouTube videos that I found helpful tqdm video (by @robmulla): https://youtu.be/n4E7of9BINo?si=1k08sSs6r5TSc8sR rich video (by @patloeber): https://youtu.be/4zbehnz-8QU?si=4v5SZBaUUiMwjgCX pathlib video (by @coreyms): https://youtu.be/yxa-DJuuTBI?si=i8IFn6TvxdcgC-D3 pydantic video (by @pixegami): https://youtu.be/XIdQ6gO3Anc?si=CLa1FS71EdaRZsRa ruff video (@PyConUS presentation): https://youtu.be/r1EZ3GXuwBA?si=iBppFwvVI6z9oniL #python #python3 Intro Song by Dyce (https://www.instagram.com/agodnameddyce/) ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

In this stream we cover beginner to advanced concepts of Quarto. Quarto is an open-source technical publication system that allows you to use a combination of Markdown & Python (or R, Julia, or Observable) code to easily produce websites, analytics dashboards, slideshows, and more. We start with getting set up with Quarto and the basics and then dive into the various output formats that you can create. Feel free to ask questions as we go through the presentation! Link to code: https://github.com/KeithGalli/quarto-crash-course Get started with Connect Cloud: https://pos.it/connect-keith Check out my video on PDF reports in Python: https://youtu.be/Q3phTByW138?si=ElidBjACwUpiKpd6 Thank you to Posit Connect Cloud for sponsoring this live stream! Video Timeline! 0:00 - Waiting to get started 2:11 - Quarto Introduction (Why use Quarto? What can you build?) 9:36 - Installation of Quarto & VSCode Setup 15:56 - Markdown Text-Formatting Basics 23:01 - Quarto-Specific Features (YAML Settings, Embedding Code, Visual Editor, Passing in Parameters, Converting to/from Jupyter Notebooks) 48:48 - Creating Interactive HTML Reports & Publishing Publicly with Posit Connect Cloud 1:05:19 - Interactive Tables and Advanced Display Options 1:10:08 - Quarto Dashboards 1:26:20 - Slideshows with Quarto #python #quarto #analytics ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

NumPy is a foundational library for computation in Python. In this video we walk through exercises to learn the library in a hands-on manner. We learn skills such as array creation and manipulation, working with random numbers, performing mathematical operations, handling dates, dealing with various data types, and more. Should be a lot of fun! Link to GitHub repo: https://github.com/rougier/numpy-100 My solutions: https://github.com/KeithGalli/numpy-100 If you enjoy this video, make sure to throw it a like & subscribe if you haven't already 🫡 Here is a link to the similar video I did with the Python Pandas library! https://youtu.be/i7v2m-ebXB4?si=G3U8SRK2k2mgoQ7e Video timeline! 0:00 - Video Overview & Code Setup 4:18 - 1.) Import the numpy package under the name np 5:15 - 2.) Print the numpy version and the configuration 6:21 - 3.) Create a null vector of size 10 9:29 - 4.) How to get the memory size of any array 15:19 - 5.) How to get documentation of the numpy add function from the command line 18:51 - 6.) Create a null vector of size 10 but the fifth value which is 1 20:03 - 7.) Create a vector with values ranging from 10 to 49 21:48 - 8.) Reverse a vector (first number becomes last) 23:20 - 9.) Create a 3x3 Matrix with values ranging from 0 to 8 24:41 - 10.) Find indices of non-zero elements from array 26:24 - 11.) Create a 3x3 identity matrix 29:35 - 12.) Create a 3x3x3 array with random values. 30:48 - 13.) Create a 10x10 array with random values and find min/max values 33:17 - 14.) Create a random vector of size 30 and find the mean value 34:57 - 15.) Create a 2d array with 1 on the border and 0 inside 40:19 - 16.) How to add a border (filled with 0’s around an existing array? (np.pad) 43:41 - 17.) Evaluate some np.nan expressions 48:32 - 18.) Create a 5x5 matrix with values 1,2,3,4 just below the diagonal 56:01 - 19.) Create an 8x8 matrix and fill it with a checkerboard pattern 1:02:35 - 20.) Get the 100th element from a (6,7,8) shape array 1:07:09 - 21.) Create a checkerboard pattern 8x8 matrix using np.tile function 1:16:22 - 22.) Normalize a random 5x5 matrix 1:24:20 - 23.) Create a custom dtype that describes a color as four unsigned bytes (RGBA) 1:29:27 - 24.) Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) 1:32:54 - 25.) Given a 1D array, negate all elements which are between 3 and 8, in place 1:37:16 - 26.) Default “range” function vs numpy “range” function 1:40:25 - 27.) Evaluate whether expressions are legal or not 1:55:41 - 28.) Evaluate divide by zero expressions / np.nan type casting 1:57:48 - 29.) How to round away from zero a float array? 1:59:22 - 30.) How to find common values between two arrays? 2:00:19 - 31.) How to ignore all numpy warnings? 2:03:24 - 32.) Is np.sqrt(-1) == np.emath.sqrt(-1) ?? 2:05:22 - 33.) Get the dates of yesterday, today, and tomorrow with numpy 2:19:39 - 34.) How to get all the dates corresponding to the month of July 2016? 2:27:27 - 35.) How to compute ((A+B)*(-A/2)) in place (without copy)? 2:35:00 - 36.) Extract the integer part of a random array of positive numbers using 4 different methods 2:40:47 - 37.) Create a 5x5 matrix with row values ranging from 0 to 4 2:43:07 - 38.) Use generator function that generates 10 integers and use it to build an array 2:43:58 - 39.) Create a vector of size 10 with values ranging from 0 to 1, both excluded. 2:48:49 - 40.) Create a random vector of size 10 and sort it. 2:51:07 - 41.) How to sum a small array faster than np.sum? 2:54:37 - 42.) Check if two random arrays A & B are equal 2:58:48 - 43.) Make an array immutable (read-only) 3:02:14 - Puppies are great 3:03:06 - 44.) Convert cartesian coordinates to polar coordinates 3:20:37 - 45.) Create a random vector of size 10 and replace the maximum value by 0 3:23:58 - 46.) Create a structured array with x and y coordinates covering the [0,1]x[0,1] area 3:26:25 - 47.) Given two arrays, X and Y, construct the Cauchy matrix C (Cij = 1/(xi-yj)) 3:34:31 - 48.) Print the min/max values for each numpy scalar type 3:36:50 - 49.) How to print all the values of an array? 3:39:23 - 50.) How to find the closest value (to a given scalar) in a vector? I got a little tired at the end, so not doing all 100 problems in this video. Will release the next 50 problems soon! #python #numpy -------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli -------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

The programming landscape is always changing, in this video we walk through three tips to keep up with the new tools & technologies. These tips are relevant whether you're in data science, front or back-end engineering, devops, cybersecurity, you name it. If you have other recommendations, I would love to hear them in the comments! Video Timeline 0:00 - Video Overview 0:54 - Tip #1: Leverage your Network! 4:13 - Tip #2: Watch Conference Talks 7:30 - Tip #3: Use Social Media (Strategically) 11:23 - Some additional thoughts on the topic ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

Try out the Datacamp platform - Assess your skills, learn Python, SQL, R and more... and get certified as a data professional! (Get 25% off annual subscription with my link) https://datacamp.pxf.io/75RPRg This video teaches how to predict health insurance costs using Python and machine learning. It covers the full process from cleaning data to building and testing a regression model. Viewers will learn to use pandas for data handling, create visualizations, and apply scikit-learn for linear regression. The tutorial provides hands-on experience with real-world data analysis and predictive modeling. Github repo: https://github.com/KeithGalli/Regression-Example Datacamp Project link: https://datacamp.pxf.io/75REKg Video timeline! 0:00 - Video overview 0:47 - What is regression? 2:29 - Getting started with the code 4:30 - Initial regression modeling strategy 6:41 - Task #1: Clean our health insurance data 25:47 - Task #2: Create scatterplots of our variables mapped to charges 31:34 - Task #3: Prepare the data for regression model fitting 41:32 - Task #4: Fit a linear regression model to our dataframe with sklearn 52:11 - Task #5: Test our model on validation data & submit project #datascience #regression ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

Show off your data skills! Deploy Shiny, Streamlit, Quarto, and more—all in one place with Posit Connect Cloud. Get started for free: https://pos.it/connect-keith In this video we learn how to generate analytic report PDFs in Python using the Quarto library. Quarto allows you to write markdown with embedded code and many customization options to easily generate PDF reports, slideshow presentations, and HTML dashboards. Link to code: https://github.com/KeithGalli/country-analytics Check out David Keyes & the R for the Rest of Us presentation at Posit Conference (there is a free option to sign up to see conference presentations -- the video will be on YouTube soon): https://reg.conf.posit.co/flow/posit/positconf24/publiccatalog/page/publiccatalog/session/1712004041983001s1h4 Thank you to DYce for music: https://www.instagram.com/agodnameddyce?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw== ---------- Video timeline! 0:00 - What we're building in this video 1:16 - Quarto Installation & setup 6:35- Adding Python code & code output to our reports 11:03 - Specifying the project output directory where reports are rendered to (_quarto.yml) 13:02 - Render output files from the command line (quarto render) 13:53 - Generating more fancy and stylized reports (county-analytics-report.qmd) 16:00 - Modifying parameters/variables/metadata when you render different reports (from command line) 21:45- Generate hundreds of analytics reports from a single script! 23:09 - Deep dive into how the code works & formatting 28:17 - Project Extension Ideas ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

Let's do some leetcode coding problems live! Join Saturday at 11am EST for about 2-3 hours of Python problems. Will plan to give some advice on how to strengthen your coding interview skills more generally as well. Hope to see you there! https://leetcode.com/explore/featured/card/top-interview-questions-easy/ Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 ------------------------- Video Timeline! 0:00 - Fixing Live Stream Settings 2:38 - Introduction & what we're doing today 4:10 - [Leetcode 412] Fizz Buzz string manipulation problem 22:04 - [Leetcode 189] Rotate Array 46:39 - [Leetcode 217] Contains Duplicate list problem 1:01:44 - [Leetcode 125] Valid Palindrome string problem 1:17:37 - [Leetcode 237] Delete Node in a Linked List (watch my brain not function properly!!!) 2:06:19 - [Leetcode 136] Single Number (trickier problem than it might first seem!) 2:28:52 - [Leetcode 104] Maximum Depth of a Binary Tree 2:47:35 - [Leetcode 36] Valid Sudoku (good function design problem) ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

Try out the Datacamp platform - Assess your skills, learn Python, SQL, R and more... and get certified as a data professional! https://datacamp.pxf.io/WqjMVn Explore data science and Python skills through a Datacamp assessment walkthrough. This video covers challenges in data manipulation, importing and cleaning data, and using pandas functions like melt and pivot tables. Learn approaches for coding problems, effective use of documentation, and tips for consistent practice. Suitable for beginners and those looking to refine their skills, the video provides insights into data analysis tasks and showcases learning resources for aspiring data scientists. Special shoutout to David Yusuf for making intro & outro music! https://www.instagram.com/agodnameddyce?igsh=aGxtMHJ3bGY1Z3Y= ------------------------- Video timeline! 0:00 - Introduction and Getting Started 1:38 - Data Importing and Cleaning Assessment Walkthrough 19:30 - Reviewing our Results 22:45 - Four Elements of Expertise in Data Science 26:53 - Exploring DataCamp's Additional Features ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

Learn data skills with hands-on exercises & tutorials at Datacamp! https://datacamp.pxf.io/c/3588040/1012793/13294 Even though it's been out for a bit now, I haven't really touched the Polars library, but that's about to change! I figure it might be a cool opportunity to showcase how I go about learning something new so I plan to livestream for 2-3 hours as I start to get more comfortable with the library. Learn some strategies and techniques that you can employ to learn new skills efficiently. Pick up some dataframe manipulation skills in the process. Hope to see you there. Github: https://github.com/KeithGalli/polars-livestream Migrating from Pandas to Polars Resource: https://docs.pola.rs/user-guide/migration/pandas/ Data referenced Original Pokemon Dataset: https://www.kaggle.com/datasets/abcsds/pokemon Trending YouTube Videos: https://www.kaggle.com/datasets/asaniczka/trending-youtube-videos-113-countries Video timeline! 0:00 - Random Banter 2:10 - Livestream Overview & General Learning Strategy 12:46 - Getting started with Polars 15:00 - I temporarily don't know how to share my screen 16:23 - Getting started with Polars (in code) 21:36 - Expressions in Polars (Select, Filter) 29:10 - Learning Polars vs Pandas Strategy 31:10 - Main Polars Concepts (Exploring the Documentation) 38:35 - Performance Benefits of Polars vs Pandas 42:23 - More complex Polars select context 46:34 - Exploring Polars Documentation (with_columns, filters, group_by) 48:20 - Groupby Example (see comments for small correction) 56:57 - Q&A: How long did it take you to learn Python for Data Science? 58:35 - Q&A: What laptop are you using? 1:01:01 - Q&A: Have you ever gotten stuck at work? What did you do? 1:04:29 - Q&A: Any advice on leetcoding? 1:06:06 - Performance Benefits of Polars (Loading in 2gb file) 1:14:24 - Q&A: How to get started with freelance projects?? (& Upwork Strategy) 1:22:45 - More Polars Exploration & Continued Learning Strategy 1:39:22 - Question & Answer Session ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.