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The GRAPH Courses
Добавлен 14 май 2022
A data science training platform for the modern data analyst.
Developed by the GRAPH Network.
Access quizzes, notes, and more at our website: thegraphcourses.org
Developed by the GRAPH Network.
Access quizzes, notes, and more at our website: thegraphcourses.org
Git & GitHub for R Users
👋 LESSON MATERIALS 🛑
You can access free accompanying materials for this lesson at our website:
thegraphcourses.org/courses/websites-and-dashboards-with-r/
Chapters
00:00 Learning objectives
02:40 Introduction
04:33 Set up Github.com account
06:13 Windows: Install GitHub Desktop
08:01 Mac: Install GitHub Desktop
10:13 Action 1: Create repo, commit, publish
22:27 Action 2: Edit repo, commit, push
25:49 Git vocabulary & theory
34:46 Action 3: pull from remote
39:20 Action 4: add a new collaborator
41:35 Action 5: resolve a merge conflict
51:44 Action 6: access old versions of file(s)
54:29 Action 7: fork and clone a repo
57:58 Summary
Learning objectives
- Learn how to set up GitHub and GitHub Desktop.
- Unde...
You can access free accompanying materials for this lesson at our website:
thegraphcourses.org/courses/websites-and-dashboards-with-r/
Chapters
00:00 Learning objectives
02:40 Introduction
04:33 Set up Github.com account
06:13 Windows: Install GitHub Desktop
08:01 Mac: Install GitHub Desktop
10:13 Action 1: Create repo, commit, publish
22:27 Action 2: Edit repo, commit, push
25:49 Git vocabulary & theory
34:46 Action 3: pull from remote
39:20 Action 4: add a new collaborator
41:35 Action 5: resolve a merge conflict
51:44 Action 6: access old versions of file(s)
54:29 Action 7: fork and clone a repo
57:58 Summary
Learning objectives
- Learn how to set up GitHub and GitHub Desktop.
- Unde...
Просмотров: 139
Видео
Data Cleaning 2: Fixing Inconsistencies | Further Data Analysis with R (Lesson 10)
Просмотров 154Месяц назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/data-cleaning-2-fixing-inconsistencies/ Chapters 0:00 - Intro 0:58 - Cleaning Column Names 10:04 - Removing Duplicate Rows 12:19 - Homogenize strings 21:02 - Converting Data Types 23:36 - Wrap Up Learning objectives - Understand how to clean column nam...
Data Cleaning 1: Data Diagnostics | Further Data Analysis with R (Lesson 9)
Просмотров 153Месяц назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/data-cleaning-1-data-diagnostics/ Chapters 0:00 Introduction 2:40 Comments 4:45 Sections 5:32 R as a calculator 7:21 Code formatting 10:34 Creating objects 18:09 Renaming objects 20:06 Working with objects 23:25 Errors with objects 27:28 Naming objects...
R Functions and Conditionals | Further Data Analysis with R (Lesson 8)
Просмотров 152Месяц назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/functions-and-conditionals/ Chapters 0:00 - Introduction 1:09 - Basics of a Function 10:14 - When to Write a Function 13:22 - Functions with Multiple Arguments 17:36 - Understanding Function Scope 19:46 - Intro to Conditionals 29:36 - Argument Checking...
For Loops in R | Further Data Analysis with R (Lesson 7)
Просмотров 163Месяц назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/for-loops/ Chapters 0:00 - Intro 3:50 - Nested Loops 5:21 - Are for loops useful in R? 7:26 - Looping with an Index 11:47 - Looping on Multiple Vectors 13:47 - Storing Loop Results 22:04 - If Statements in Loops 30:22 - Real Loops Application: Generati...
Advanced Joins: Mismatches, One-to-Many & Multi-Key Joins | Further Data Analysis with R (Lesson 6)
Просмотров 134Месяц назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/joining-2-mismatched-values-one-to-many-multi-key-joins/ Chapters 0:00 - Introduction 0:54 - Pre-Join Data Cleaning 5:30 - Practice Question 6:04 - Real Data Example 1: Key Typos 11:31 - Identify Key Typos with setdiff() 15:49 - Identify Key Typos with...
Joining/merging data with dplyr | Further Data Analysis with R (Lesson 5)
Просмотров 132Месяц назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/joining-1-intro-to-joining-datasets/ Chapters 0:00 - Intro 1:00 - Why joins are useful 5:30 - Intro to left join 7:26 - Joining syntax 13:12 - Types of joins 13:51 - Left join details 25:02 - Right join details 29:53 - Inner join details 34:10 - Full j...
Date Intervals, Components and Rounding | Further Data Analysis with R (Lesson 4)
Просмотров 89Месяц назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/dates-2-intervals-components-and-rounding/ Chapters 0:00 - Intro 3:02 - Calculating Date Intervals 6:50 - Comparing interval methods 12:12 - Extracting Date Components 16:57 - Rounding 28:54 - Wrap up Learning objectives • You know how to calculate int...
Recognizing and Formatting Dates with lubridate | Further Data Analysis with R (Lesson 3)
Просмотров 113Месяц назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/dates-1-recognizing-and-formatting-dates/ Chapters 0:00 - Intro 5:32 - Coercing strings to dates 10:45 - Using lubridate's dmy functions 15:28 - parse_date_time 26:08 - Change how dates are displayed 31:45 - Wrap-up Learning objectives • You understand...
Factors and the forcats package | Further Data Analysis with R (Lesson 2)
Просмотров 1502 месяца назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/factors-in-r/ Chapters 0:00 - Intro 0:51 - Dataset 1:31 - What are Factors? 2:45 - Factors in Action 6:11 - Practice Question 7:01 - fct_relevel() 11:48 - Practice Question 12:03 - fct_reorder() 13:52 - Practice Question 14:05 - .fun 17:01 - fct_recode...
String Manipulation with stringr | Further Data Analysis with R (Lesson 1)
Просмотров 3052 месяца назад
👋 LESSON MATERIALS 🛑 You can access the quizzes, PDF notes, and datasets for this lesson at our website: thegraphcourses.org/courses/fdar/topics/string-manipulation/ Chapters 0:00 Introduction 0:47 Defining Strings 1:13 Practice Question 5:25 String Formatting in R with {stringr} 5:40 Changing Case 6:00 Handling Whitespace 7:38 Text Padding 9:43 Text Wrapping 13:10 Practice Question 15:44 Apply...
Boxplots | Data on display: visualizing data with ggplot2 in R (lesson 5)
Просмотров 812 месяца назад
👋 LESSON RESOURCES 🛑 Get the data, scripts, PDF notes and quizzes for this lesson from our website: thegraphcourses.org/courses/data-on-display-beta/topics/boxplots/ If this is your first time coding along with us, watch this quick video to see how it works: ruclips.net/video/xTsdNpeY2ak/видео.html Learning Objectives By the end of this lesson, you will be able to: 1. Plot a boxplot to visualiz...
Histograms | Data on display: visualizing data with ggplot2 in R (lesson 4)
Просмотров 652 месяца назад
👋 LESSON MATERIALS 🛑 Get the data, scripts, PDF notes and quizzes for this lesson from our website: thegraphcourses.org/courses/data-on-display-beta/topics/histograms/ If this is your first time coding along with us, watch this quick video to see how it works: ruclips.net/video/xTsdNpeY2ak/видео.html Learning Objectives By the end of this lesson, you will be able to: 1. Plot a histogram to visu...
Formation de Base sur R | Introduction à l'analyse des données de santé
Просмотров 328 месяцев назад
Formation de Base sur R | Introduction à l'analyse des données de santé
The Current and Future LLM Landscape: A Non-technical Intro to Large Language Models (part 2 of 3)
Просмотров 144Год назад
The Current and Future LLM Landscape: A Non-technical Intro to Large Language Models (part 2 of 3)
How was ChatGPT Created? A Non-technical Introduction to Large Language Models (part 1 of 3)
Просмотров 123Год назад
How was ChatGPT Created? A Non-technical Introduction to Large Language Models (part 1 of 3)
Nine ways to use ChatGPT as a data analyst (and 4 ways you shouldn't)
Просмотров 302Год назад
Nine ways to use ChatGPT as a data analyst (and 4 ways you shouldn't)
LLMs and the Future of Programming: A Non-technical Intro to Large Language Models (part 3 of 3)
Просмотров 72Год назад
LLMs and the Future of Programming: A Non-technical Intro to Large Language Models (part 3 of 3)
Two Types of Code: Humans vs Computer coding script
Просмотров 50Год назад
Two Types of Code: Humans vs Computer coding script
Data structures | Foundations of data analysis with R (lesson 7)
Просмотров 598Год назад
Data structures | Foundations of data analysis with R (lesson 7)
How to Install R & RStudio on a Windows Laptop
Просмотров 98Год назад
How to Install R & RStudio on a Windows Laptop
R Basics & Beyond: Introduction to Health Data Analysis
Просмотров 829Год назад
R Basics & Beyond: Introduction to Health Data Analysis
Getting R Help from Stack Overflow and ChatGPT
Просмотров 495Год назад
Getting R Help from Stack Overflow and ChatGPT
Data Dive with R: Free Course (Trailer)
Просмотров 2,7 тыс.Год назад
Data Dive with R: Free Course (Trailer)
Data Dive with R | Beginner's analysis course for health & other fields | 3-course compilation
Просмотров 4 тыс.Год назад
Data Dive with R | Beginner's analysis course for health & other fields | 3-course compilation
good
Great video for beginners
Wow, nice presentation & teaching!
After watching some videos, I must say this is a criminally underrated channel. I am so glad youtube put this in my recommendations!
Thank you such very nice presentation and very clear
Saw many tutorial videos and this is one of the best!
An excellent teacher, clear, and not confusing.
This is a wonderful tutorial. I never knew R studio was this robust. Thank you very much
At 4 min and I jyst paused to subscribe, like and appreciate this video. Very useful!
This guy is Phd and give content for free, what a humble soul
Overall these presentations are very nice. The separate function is now separate_wider_*(). Here separate_wider_delim(date, delim = "-", names = c("year", "month", "day"), remove = FALSE).
thank you
wawoo
This is highly useful.
I believe there is a mistake in the code with the here() function. here eleminates slashes (which are not the same for Mac and Windows) by using quotation marks so here("data", "file"). No slashes. Here makes the code the same for both Mac and Windows.
Hello! Actually, the here function will convert slashes to the correct version for Windows or Mac, so this code should work regardless of the system.
@@thegraphcourses Interesting, I did not know that. Thanks.
This is the best tutorial about writing functions in R. Millions thanks❤❤❤!
Very nice - I will recommend this channel to beginners.
Crystal clear. Thank you.
Waiting for new lesson.❤
Very comprehensive lesson. Thanks🙏🏿
I made this comment under another one of your videos, but it bears repeating: Excellent! This was my second GRAPH RUclips tutorial. 1. Speaker was very articulate with a soothing instructional tone. 2. Text was easy to read (good font size, and not 'dark screen' like many others) 3. Included appropriate exercises to reinforce concepts. 4. Well paced and satisfying video length. Looking forward to watching more of your tutorials.
Excellent! This was my first GRAPH RUclips tutorial. 1. Speaker was very articulate with a soothing instructional tone. 2. Text was easy to read (good font size, and not 'dark screen' like many others) 3. Included appropriate exercises to reinforce concepts. 4. Well paced and satisfying video length. Looking forward to watching more of your tutorials.
❤ How to Open Markdown output in Other than a Default Browser Window ❓️❓️
Hi, first of all I want to thank you for these super useful videos, actually I have started learning R with your youtube page, but in this video i have a problem. My viewer part does not show anything (after ggplotly and ….). Indeed i searched on google to solve it but as a very beginner it was very confusing for me, i really appreciate if you can help me.
great video, very clear, can't understand why it hasn't much more views and likes!
How can I get Yaounde_data.csv? in the description, I cannot see any link.
So helpful and lovely explanation. Thank you
Really one of the best tutorials out here..mainly bcoz of the style and effectiveness of the teaching method..Thank you!!!
Thank you so much! You are the best! I super appreciate it!
Hey . You the first professor teaching a subject so professionally. Appreciate .
From somalia this was helpful and thank you
Happy we could be of help!
Very clear and simple way of presenting information ❤
Keep on doing what you are doing ❤❤❤
Thank you for the inspiring comment!
❤This is excellent
Are you from Sierra Leone
Very nicely presented. Thanks.
God bless you guys for great work
Great and much clearer
Great lecturing techniques and helpful👏
I found this channel's demonstration procedure is stand alone. A real classroom experience. Keep up good work.❤
The style of lecturing is stand-alone. Because its not like others showing in inset view rather it is like true classroom experience!
a lovely teaching on R coding basis! I want to do on different types of design like RCBD(one way, two way.... Anova)
Great help and solving confusion 🙏
Glad to hear it was helpful!
Thank you for the video! Just one (very silly) question: In your examples, I noticed that dataframes are not assigned back to themselves (or to new dataframes). I see this same style reflected in the ?case_when() examples. However, when you run your code, the results are printed below. When I copy this code, I either get a convoluted message about the tibble being used as the dataframe or nothing happens at all. Is this style just convention when presenting examples? Should we be assigning the data frame back to itself before beginning the pipe (i.e., df <- df |> …)? Thank you!
Yes! This is just to quickly show you how to use the function with an example. We usually don’t recommend assigning back to the same named data frame though. Better to pipe chain most of your manipulation steps together and then assign to a new object like: df_clean <- df …. Or df_2 <- df We recommend downloading the project folder linked in the video description . In the attached code along file, some of the above will be clearer. Best of luck!
Thank you so mch! Will do!
Hey! How i can load imported datasets in R Markdown..and use them,😢 i can't, plz, help!!!
Hello! Our coding basics video (earlier in the playlist), discusses this topic! ruclips.net/p/PLkkleDPMR2sU2Y6H4fDBi9msOarZWOcBB
see example in 37:55
Great series!!!
Thank you so much for the feedback!
Best introduction to R markdown 🎉
not bad
This is amaizing and super easy to understand, i had been looking for an introductory course for R and i am so glad i have finally come across this one! am enjoying!. Thankyou so much for sharing
What I really love about this series of lectures are the tips on how to code in R. It's very practical and make coding efficient.
Thank you for the positive feedback! Do help us share with others who may find the resources useful.