Roger Hilfiker rhilfi

## pivot_longer_several_columns_names_pattern_numbers #R
library(tidyverse)
# thanks for the help:
# https://community.rstudio.com/t/pivot-longer-on-multiple-column-sets-pairs/43958/9
# https://cran.r-project.org/web/packages/stringr/vignettes/regular-expressions.html

walking_speed_1<-c(0.3,0.5,0.7)
balance_four_balance_test_1<-c(1,2,1)
tug_1<-c(10,20,12)

walking_speed_2<-c(0.4,0.6,0.8)

## sum_of_some_columns_per_row #R
# Calculate sum of different columns per row

id<-1:5
food<-c(1,4,3,2,1)
drink<-c(4,3,2,4,5)
names<-c("John", "Mick", "Paul","George", "Ringo")
books<-c(3,4,5,4,2)

data<-data.frame(id, food, drink,names, books )

## round_all_number_in_dataframe #R

Name<-c("John", "Paul","George", "Ringo")
Age <-rnorm(4, 70, 2)
number_1<-c(2.34324,2.32145,5.432,5.3456)
number_2<-c(6.5432,8.32456,3.2346,9.3254245)

data<-data.frame(Name, Age, number_1, number_2)

data_rounded<-data %>%
  mutate(across(where(is.numeric), round, 1))

## mutate_across_str_replace
library(dplyr)
# see https://www.tidyverse.org/blog/2020/04/dplyr-1-0-0-colwise/
# see https://vbaliga.github.io/replace-text-in-specific-column/

ID<-1:3
Names<-c("Peter", "Paul", "Marhy")
FamilyNames<-c("Lennon", "McCartney", "Jagger")
Age<-rnorm(3, 80, 12)
data<-data.frame(Names, FamilyNames, ID, Age)

## remove_NA_in_String
# remove NA in string variables

library(dplyr)
Names = c("Peter","NA", "Gabriel", "John", "Lennon","Stuart")
Country=c("Sweden", "Switzerland", "Cumberland", "Wonderland", "Nowhereland", "Land")
Numbers=c(1,2,3,4,NA,6)
id<- 1:6

data<-data.frame(id, Names, Numbers, Country)
head(data)

## stopInstallingPackagesOnOneDrive
https://medium.com/@ValidScience/how-to-fix-rstudios-package-installation-on-windows-10-c1e602bf3a1f

## rename_column_names_with_rename_all_and_str_replace

library(tidyverse)
Dieser_Alte_Hase=rnorm(10,2,2)
Dieses_Alte_Pferd=rnorm(10,4,2)
Dieses_Alte_Haus=rnorm(10,4,2)

data<-data.frame(Dieser_Alte_Hase, Dieses_Alte_Pferd, Dieses_Alte_Haus)
names(data)

data<-data %>%

## move_delete_files_from_within_R
# see http://theautomatic.net/2018/07/11/manipulate-files-r/#:~:text=Files%20can%20be%20deleted%20with,add%20the%20parameter%20recursive%20%3D%20TRUE.

## calculate_with_mutate_at
# calculate with mutate_at

# see also here: https://suzan.rbind.io/2018/02/dplyr-tutorial-2/

# create an example data frame ####
library(tidyverse)

id<-1:10
item1<-c(2,3,2,4,3,2,1,0,2,1)
item2<-c(4,3,2,1,2,3,1,0,1,2)

## tabulate_absolute_and_relative_frequencies_R

list.of.packages <- c("summarytools")
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])] # https://stackoverflow.com/questions/4090169/elegant-way-to-check-for-missing-packages-and-install-them
if(length(new.packages)) install.packages(new.packages)


summarytools::freq(models$significant) # https://cran.r-project.org/web/packages/summarytools/vignettes/Introduction.html


gender<-c(rep("men",10), rep("women", 20), rep(NA,5))
	library(tidyverse)
	# thanks for the help:
	# https://community.rstudio.com/t/pivot-longer-on-multiple-column-sets-pairs/43958/9
	# https://cran.r-project.org/web/packages/stringr/vignettes/regular-expressions.html

	walking_speed_1<-c(0.3,0.5,0.7)
	balance_four_balance_test_1<-c(1,2,1)
	tug_1<-c(10,20,12)

	walking_speed_2<-c(0.4,0.6,0.8)
	# Calculate sum of different columns per row

	id<-1:5
	food<-c(1,4,3,2,1)
	drink<-c(4,3,2,4,5)
	names<-c("John", "Mick", "Paul","George", "Ringo")
	books<-c(3,4,5,4,2)

	data<-data.frame(id, food, drink,names, books )

	Name<-c("John", "Paul","George", "Ringo")
	Age <-rnorm(4, 70, 2)
	number_1<-c(2.34324,2.32145,5.432,5.3456)
	number_2<-c(6.5432,8.32456,3.2346,9.3254245)

	data<-data.frame(Name, Age, number_1, number_2)

	data_rounded<-data %>%
	mutate(across(where(is.numeric), round, 1))
	library(dplyr)
	# see https://www.tidyverse.org/blog/2020/04/dplyr-1-0-0-colwise/
	# see https://vbaliga.github.io/replace-text-in-specific-column/

	ID<-1:3
	Names<-c("Peter", "Paul", "Marhy")
	FamilyNames<-c("Lennon", "McCartney", "Jagger")
	Age<-rnorm(3, 80, 12)
	data<-data.frame(Names, FamilyNames, ID, Age)
	# remove NA in string variables

	library(dplyr)
	Names = c("Peter","NA", "Gabriel", "John", "Lennon","Stuart")
	Country=c("Sweden", "Switzerland", "Cumberland", "Wonderland", "Nowhereland", "Land")
	Numbers=c(1,2,3,4,NA,6)
	id<- 1:6

	data<-data.frame(id, Names, Numbers, Country)
	head(data)

	library(tidyverse)
	Dieser_Alte_Hase=rnorm(10,2,2)
	Dieses_Alte_Pferd=rnorm(10,4,2)
	Dieses_Alte_Haus=rnorm(10,4,2)

	data<-data.frame(Dieser_Alte_Hase, Dieses_Alte_Pferd, Dieses_Alte_Haus)
	names(data)

	data<-data %>%
	# calculate with mutate_at

	# see also here: https://suzan.rbind.io/2018/02/dplyr-tutorial-2/

	# create an example data frame ####
	library(tidyverse)

	id<-1:10
	item1<-c(2,3,2,4,3,2,1,0,2,1)
	item2<-c(4,3,2,1,2,3,1,0,1,2)

	list.of.packages <- c("summarytools")
	new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])] # https://stackoverflow.com/questions/4090169/elegant-way-to-check-for-missing-packages-and-install-them
	if(length(new.packages)) install.packages(new.packages)


	summarytools::freq(models$significant) # https://cran.r-project.org/web/packages/summarytools/vignettes/Introduction.html


	gender<-c(rep("men",10), rep("women", 20), rep(NA,5))