dplyr

问题 This question already has answers here : Split comma-separated strings in a column into separate rows (6 answers) Split delimited strings in a column and insert as new rows [duplicate] (6 answers) Closed 3 years ago . I have a dataframe that looks like the following example df which consist of a character variable VAR . df<-data.frame(ID = 1:2, VAR = c("VAL1\r\nVAL2\r\nVAL8","VAL2\r\nVAL5"), stringsAsFactors = FALSE) # ID VAR # 1 1 VAL1\r\nVAL2\r\nVAL8 # 2 2 VAL2\r\nVAL5 I would like to split

问题 This question already has an answer here : Using Reshape from wide to long in R [closed] (1 answer) Closed 6 months ago . I have a df population that looks something like this (not all columns and rows listed): Region X1975 X1976 X1977 ... X2008 National Total 942420 93717 94974 132802 Bejing 844.4 845.10 860.50 1695 Tianjin 702.86 706.50 712.87 968.87 Hebei 4913 4943 4998 6989 ... sum 91979 93275 94540 132058 difference 440 441 433 743 The columns go from X1975 to X2008 and have every year

问题 I have a data frame like this Observations: 2,190,835 Variables: 13 $ patientid <int> 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489, 4489… $ preparationid <dbl> 1000307, 1000307, 1000307, 1000307, 1000307, 1000307, 1000307, 1000307, 1000307, 1000307, 1000307, 1… $ doseday <int> 90, 90, 91, 91, 92, 92, 92, 92, 93, 93, 93, 93, 94, 94, 94, 94, 95, 95, 95, 95, 99, 99, 100, 100, 10… $ route <fct> enteral., enteral., enteral., enteral., enteral.,

问题 I have a data frame with a few variables to reverse code. I have a separate vector that has all the variables to reverse code. I'd like to use mutate_at(), or some other tidy way, to reverse code them all in one line of code. Here's the dataset and the vector of items to reverse library(tidyverse) mock_data <- tibble(id = 1:5, item_1 = c(1, 5, 3, 5, 5), item_2 = c(4, 4, 4, 1, 1), item_3 = c(5, 5, 5, 5, 1)) reverse <- c("item_2", "item_3") Here's what I want it to look like with only items 2

问题 I have a data frame with a few variables to reverse code. I have a separate vector that has all the variables to reverse code. I'd like to use mutate_at(), or some other tidy way, to reverse code them all in one line of code. Here's the dataset and the vector of items to reverse library(tidyverse) mock_data <- tibble(id = 1:5, item_1 = c(1, 5, 3, 5, 5), item_2 = c(4, 4, 4, 1, 1), item_3 = c(5, 5, 5, 5, 1)) reverse <- c("item_2", "item_3") Here's what I want it to look like with only items 2

问题 I would like to replace outliers in each column of a dataframe with NA. If for example we define outliers as being any value greater than 3 standard deviations from the mean I can achieve this per variable with the code below. Rather than specify each column individually I'd like to perform the same operation on all columns of df in one call. Any pointers on how to do this?! Thanks! library(dplyr) data("iris") df <- iris %>% select(Sepal.Length, Sepal.Width, Petal.Length)%>% head(10) # add a

问题 I am new to R and I am trying to build a frequency/severity simulation. Everything is working fine except that it takes about 10min to do 10000 simulations for each of 700 locations. For the simulation of one individual location, I got a list of vectors with varying lengths and I would like to efficiently rbind these vectors, filling in NAs for all non-existing values. I would like R to return a data.frame to me. So far, I used rbind.fill.matrix after converting the vectors in the list to

问题 I am new to R and I am trying to build a frequency/severity simulation. Everything is working fine except that it takes about 10min to do 10000 simulations for each of 700 locations. For the simulation of one individual location, I got a list of vectors with varying lengths and I would like to efficiently rbind these vectors, filling in NAs for all non-existing values. I would like R to return a data.frame to me. So far, I used rbind.fill.matrix after converting the vectors in the list to

问题 I am trying to use the case_when function for a bunch of columns y a data.frame. This case does not return the specified columns in mutate cars %>% mutate ( km = speed * dist, mt = km / 1000 ) %>% mutate ( .funs = case_when( (speed < 20 ) ~ { km = km * 2 mt = mt * 3 } ) ) Thanks 回答1: We could use mutate_at library(tidyverse) cars %>% mutate(km = speed * dist, mt = km/1000) %>% mutate_at(vars(km, mt), funs(case_when(speed < 20 ~ .*2, TRUE ~ .))) If we need to do computation with separate

问题 I am trying to use the case_when function for a bunch of columns y a data.frame. This case does not return the specified columns in mutate cars %>% mutate ( km = speed * dist, mt = km / 1000 ) %>% mutate ( .funs = case_when( (speed < 20 ) ~ { km = km * 2 mt = mt * 3 } ) ) Thanks 回答1: We could use mutate_at library(tidyverse) cars %>% mutate(km = speed * dist, mt = km/1000) %>% mutate_at(vars(km, mt), funs(case_when(speed < 20 ~ .*2, TRUE ~ .))) If we need to do computation with separate