R programming for beginners. Manipulate data using the tidyverse: select, filter and mutate.

Learn to manipulate data using the tidyverse package in R. This is part of the "R programming for beginners" series of videos. In this video, I use one of R's built-in datasets and demonstrate how to use the following DPLYR commands: select, filter, mutate, group_by, and summarise. Part of the analysis includes changing a variable and creating a new variable. R is used for data science and quantitative analysis including statistics. The demonstration is done using R Studio

[rpiazza]

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[ryan_kat_x]

2023 and this is still super helpful, best intro to R programming

[rendezvous-]

Tried MatLab, Python and then found R.
I instantly subbed and chose R as my Data Analysis tool.
Please continue making more videos, best teacher I have found!

[johners]

I learnt a lot very quickly from your videos. Your emphasis on actually 'doing it', not just watching it done by others, is key. So many instructors don't seem to get this simple principle.
"I see and I understand, I do and I learn".
Thanks for your great work.

[kiantefernandez]

Best guide I have found online thus far. Excited to see where this project goes as concepts become more complex.

[kevinedw]

I've purchased several 'beginner' books on R programming, but have found your videos to be clearer and far more useful. I particularly appreciate the very 'hands on approach. Very much looking forward to further content.

[nadstab]

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[RedFeather]

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[antoniominio]

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[FluGiPi]

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[fatemehrasouli]

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[tremolo_painter]

This is a wonderful resource and such a gentle way to start learning R.
It helps reduce my about moving SPSS to R.
I will be recommending this to my colleagues and students.

[jrtoujoursj]

I have yet to do the exercise. I was just searching for how to use the "mutate" function because of a course I'm taking... And as they say in Spanish: "I came looking for copper, and found gold"! THANKS FOR THE AWESOME CHANNEL!!! I hope I can keep watching more of your videos! Cheers!

[mailchippull]

I count not have learnt R so easily without your videos. Would you please continue making more videos on R. It would be of great help if there are tutorials on how to use R for RNA sequencing analysis, to make venndiagrams, heatmaps etc using R. Thank you once again for all your help, I greatly appreciate your effort!

[jtmidzi]

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[estefanhernandez]

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[redserpent]

It worked beautifully and I learned a few things that books do not mention and are lifesavers such as dividing the lines after the pipe %>%. The approach to framing the problem and framing the solution is perfect. Thank you for the effort to make these videos, they are golden.
I had a hard time making the code work. Of course, it was a typo that caused it all

[esanau]

You're not just an expert in R, but also in teaching! You're a magician 😊

[rayk]

Thanks very much for the video - very helpful!
It took me a few attempts to get it to work (Important to pay attention to upper/lower case and spaces).
I think it would be great if you could deliberately make a coding error in future videos, and then show how to go back and correct it.

[icedsolid]

For anyone wondering... gender is currently set to "sex" in the dataset downloaded from Aug 2023
If you get the "Error: object 'gender' not found" the below code should work for you.
Also in order to view the amended dataset you need to store it as a variable.
Finally, in order to use the pipe operator you need another library dplyr to be active in the script:

require(tidyverse)
require(dplyr)
library(tidyverse)
library(dplyr)

data("starwars")
selected_data <- starwars %>%
select(sex, mass, height, species) %>%
filter(species == "Human") %>%
na.omit()


Simply click on the selected_data in the environment tab to view the filtered dataset. Hope that helps anyone with similar issues.