Advanced dplyr practice in R

preview_player
Показать описание

  1. Quant Psych
  2. Statistics
  3. Psychology
  4. NHST
  5. Null Hypothesis Significance Testing
  6. Philosophy of Science
Рекомендации по теме
Advanced dplyr practice 0:18:04

Advanced dplyr practice in R

Practice with dplyr 0:19:38

Practice with dplyr in R

Creating sum scales 0:12:29

Creating sum scales in R - Using mutate and across in dplyr

R PROGRAMMING dplyr 0:04:50

R PROGRAMMING dplyr ADVANCED

ReshapingAndManipulatingData.5.Advanced Functions in 0:04:13

ReshapingAndManipulatingData.5.Advanced Functions in Dplyr

Recoding and reverse 0:17:45

Recoding and reverse coding variables in dplyr

RStudio Dplyr comprehensive 0:59:53

RStudio Dplyr comprehensive tutorial

Group by and 0:05:37

Group by and Summarise functions in R programming - use the tidyverse package to wrangle your data

Data Wrangling with 0:20:45

Data Wrangling with dplyr in R

Using dplyr's group_by 0:10:56

Using dplyr's group_by for grouping data in R (CC163)

Using dplyr's filter 0:18:02

Using dplyr's filter function to pick rows from a data frame in R (CC161)

Stat 412 6: 1:13:55

Stat 412 6: Advanced Data Wrangling with dplyr

Advanced R-studio: the 0:06:42

Advanced R-studio: the wonderful SNIPPETS

Renaming variables with 0:15:50

Renaming variables with dplyr in R

DPLYR with Data 0:15:22

DPLYR with Data Camp

Learning R is 0:17:24

Learning R is Fun! - dplyr part -1 (24/40)

Daniel Chen - 0:21:57

Daniel Chen - Learning Tidy Evaluation by Reimplementing dplyr

Using dplyr's group_by 0:25:54

Using dplyr's group_by function with and without summarize (CC233)

Advanced R with 0:00:52

Advanced R with Hadley Wickham

Programming with dplyr 0:18:44

Programming with dplyr and the tidyverse

Data Manipulation in 0:51:46

Data Manipulation in R with dplyr

R's for loops 0:36:47

R's for loops are horrible. Really? Getting better performance than dplyr with for loops! (CC05...

dplyr::arrange( ) function 0:08:20

dplyr::arrange( ) function in R

Today I learned 0:08:09

Today I learned in R: magic wand & advanced piping

Комментарии
Автор

The reason you needed the tilda is because you want to feed across a function as the second argument. The tilda and dot notation is a way to write an anonymous function but it's not the recommended way as of when I'm writing this. Now you specify the arguments of the anonymous function like \(x) . I'll be excited to see what your code at present day looks like <3

eeeeeeeeeeeee
Автор

Why recode and not ifelse? x <- sample(5, 20, T)
x
ifelse(x==1, 5, ifelse(x==2, 4, x)) is a lot more flexible and allows you to only change your desired values (or leave at x)

djangoworldwide
Автор

I have seen phds in MIT who can not even explain half of these as half-good as he is. How come this dude is not already in one of the IVYs? Thanks to make this accessible! Well appreciate it!

icefunkdark
Автор

Dear sir, i have been following your videos for sometime it changed my thinking perspective on statistics. thank you for making such resourceful content and by the way, when can we expect a video on kaplan meier curves with cox regex model

gsaiteja
Автор

pls, continue to give such quality and crisp content

seriousperson