[ad_1] We could match the substring starting from _ to the end of the string (.*$) in ‘IsomiR’ column and replace with ” using sub. We use that as the grouping variable. If we are doing this with dplyr, the summarise_each can be used for summing multiple columns. library(dplyr) df1 %>% group_by(IsomiR= sub(‘_.*$’, ”, IsomiR)) … Read more
[ad_1] I’ll give you a ggplot2 answer. For this, you need to reshape your data, so there are separate x and y variables. Right now, your y values are split between two columns. Then we highlight the specific genes by only plotting points for a subset. library(ggplot2) library(dplyr) library(tidyr) gene_list <- c(‘C’, ‘F’, ‘G’, ‘I’) … Read more
[ad_1] is there a way to get the sign of a number (any kind, not just integer) Not for any number type, no. For an integer, you can test the most significant bit: if it’s 1, the number is negative. You could theoretically do the same with a floating point number, but bitwise operators don’t … Read more
[ad_1] > apply(x, 2, function(z) mean(z[order(z)][1:2]) ) [1] 1.5 6.5 Look at ?apply for row-wise or column-wise operations on matrices or all-numeric or all-character subsets of dataframes. This is actually the lowest 40% of values, since 2/5 = 0.4. If you wanted this to be “sensitive” to varying lengths (and still asking for 40% rather … Read more
[ad_1] First off, for future posts please provide sample data in a reproducible and copy&paste-able format. Screenshots are not a good idea because we can’t easily extract data from an image. For more details, please review how to provide a minimal reproducible example/attempt. That aside, here is a tidyverse solution library(tidyverse) df %>% separate_rows(Text, sep … Read more
[ad_1] There are two ways: 1) Attaching the data: attach(data1) And then this code should work: cor(V1, V2) 2) Using $ for accesing columns in a dataframe cor(data1$V1, data1$V2) [ad_2] solved Object not detected in R [closed]
[ad_1] You can try library(tidyverse) d %>% gather(key, value, -PtsAgRdTm) %>% ggplot(aes(x=PtsAgRdTm, y=value, fill=key)) + geom_col(position = “dodge”) You transform the data from wide to long using tidyr’s gather function, then plot the bars in a “dodge” or a “stack” way. 3 [ad_2] solved ggplot Grouped barplot with R
[ad_1] Promoting my comment to an answer as the OP appears to agree (and removing a spurious ) in the process): computeY <- function(x) { sqrt(1-(x-1)^2) } which at the prompt works as well: R> computeY <- function(x) { sqrt(1-(x-1)^2) } R> sapply((1:5)/10, computeY) [1] 0.435890 0.600000 0.714143 0.800000 0.866025 R> Disclaimer: No pipes were … Read more
[ad_1] d <- read.table(text=readClipboard(), header=TRUE, stringsAsFactors = T, na.strings=”U”) df <- melt(d, id.var=”date”) ggplot(aes(x=date, y=value), data = df) + geom_bar(aes(fill = variable), stat=”identity”, position = ‘dodge’) or ggplot(aes(x=factor(date), y=value), data = df) + geom_bar(stat=”identity”, position = ‘dodge’) + facet_grid(variable~., scales=”free_y”, drop = F) + theme(axis.text.x = element_text(angle = 45, vjust = 1.1, hjust = 1.05)) … Read more
[ad_1] If you really want to do this, it’s pretty trivial with lapply(), where we use it to “loop” over the other columns of df. A custom function takes each variable in turn as x and fits a model for that covariate. df <- data.frame(crim = rnorm(20), rm = rnorm(20), ad = rnorm(20), wd = … Read more
[ad_1] Try to do this library(‘stringr’) apply(data, 1, function(x) str_c(x$columnnane,collapse=”,”)) where, data is you dataframe and columnname is the column containing list. edited answer out = do.call(rbind, lapply(data, function(x) str_c(x,collapse=”, “))) where data is your list object if the list is stored inside a dataframe then pass the column in place of the data above … Read more
[ad_1] I think I understand your request. You seem to care about the order of the observations regardless if, for instance, the second observations Time is prior to the first observations Time. That doesn’t make much sense, but here is a quit efficient data.table solution in order to achieve this. This is basically does a … Read more
[ad_1] Here’s one way to add a new column by reference using data.table: require(data.table) setDT(d1); setDT(d2); setDT(data) # convert all data.frames to data.tables data[src == “one”, location := d1[.SD, location, on=”index”]] data[src == “two”, location := d2[.SD, location, on=”index”]] .SD stands for subset of data, and contains all columns in data that matches the condition … Read more
[ad_1] Not sure what is your question, but you can specify your own column prefix for columns of each merged object with named arguments of cbind: data(‘cars’) cars2=cbind(DataSet1=cars, DataSet2=cars) head(cars2) # DataSet1.speed DataSet1.dist DataSet2.speed DataSet2.dist # 1 4 2 4 2 # 2 4 10 4 10 # 3 7 4 7 4 # 4 … Read more
[ad_1] Because you are comparing character strings. Consider… max(“apple”,”banana”,”banana2″) #[1] “banana2” max( “1” , “2” , “10” ) #[1] “2” sort( c( “1” , “2” , “10” ) ) #[1] “1” “10” “2” sort( as.integer( c(“1” , “2” , “10” ) ) ) #[1] 1 2 10 max( as.integer( c(“1” , “2” , “10” ) … Read more