apply

问题 I have two data frames/ lists of datas 'humanSplit and ratSplit` and they are of the form > ratSplit$Kidney_F_GSM1328570 ratGene ratReplicate alignment RNAtype 1 Crot Kidney_F_GSM1328570 7 REV 2 Crot Kidney_F_GSM1328570 12 REV 3 Crot Kidney_F_GSM1328570 4 REV and > humanSplit$Fetal_Brain_408_AGTCAA_L009_R1_report.txt humanGene humanReplicate alignment RNAtype 53 ZFP28 Fetal_Brain_408_AGTCAA_L009_R1_report.txt 5 reg 55 RC3H1 Fetal_Brain_408_AGTCAA_L009_R1_report.txt 9 reg 56 IFI27 Fetal_Brain

问题 I have the following dataframe: set.seed(1) y <- data.frame(a1 = rnorm(5) , b1 = rnorm(5), c1 = rnorm(5), a2 = rnorm(5), b2 = rnorm(5), c2 = rnorm(5)) I would like to obtain the correlations of the pairs of columns: cor(a1,a2), cor(b1,b2), cor(c1,c2) I tried the following but NA's appear as output: apply(y,2,function(x) cor(x[1],x[3])) I would like to get the result equivalent to cor(y[,1],y[,4]) cor(y[,2],y[,5]) cor(y[,3],y[,6]) In my actual data frame, I have many more pairs of columns. Any

问题 I have a very large data frame containing 2 levels of a factor, levels "No" and "Yes". I would like to replace the levels to numeric values, so that "No" turns into 0, and "Yes" turns into 1. I would like to apply a function that works on the data frame. A simple example to work on: > df a b c d 1 1 No Yes 1 2 2 No No 3 3 3 Yes No 123 4 4 Yes Yes 12 5 5 No Yes 231 6 6 No No 21 7 7 Yes No 21 8 8 Yes No 21 > str(df) 'data.frame': 8 obs. of 4 variables: $ a: int 1 2 3 4 5 6 7 8 $ b: Factor w/ 2

问题 I have a very large data frame containing 2 levels of a factor, levels "No" and "Yes". I would like to replace the levels to numeric values, so that "No" turns into 0, and "Yes" turns into 1. I would like to apply a function that works on the data frame. A simple example to work on: > df a b c d 1 1 No Yes 1 2 2 No No 3 3 3 Yes No 123 4 4 Yes Yes 12 5 5 No Yes 231 6 6 No No 21 7 7 Yes No 21 8 8 Yes No 21 > str(df) 'data.frame': 8 obs. of 4 variables: $ a: int 1 2 3 4 5 6 7 8 $ b: Factor w/ 2

问题 I have a survey where users have filled in answers to questions on a likert scale. The software we are using has put text into the answers when all i want is numbers so an example is NEITHER AGREE NOR DISAGREE4 . I want to convert it to 4 I have R code that does this where it looks for a number in the cell of the dataframe for column 18 and extracts the number from it if it exists as.numeric(ifelse(grepl("[0-9]",df[,18]),as.numeric(gsub(x = df[,18],"[A-z]","")), df[,18])) I would like to be

问题 I have a data frame, such as the following: name day wages 1 Ann 1 100 2 Ann 1 150 3 Ann 2 200 4 Ann 3 150 5 Bob 1 100 6 Bob 1 200 7 Bob 1 150 8 Bob 2 100 For every unique name/day pair, I would like to calculate a range of totals, such as 'number of times wages was greater than 175 on current or next day for this person'. There are many more columns than wages and there are four time-slices to be applied to each total for each row. I can currently accomplish by unique'ing my data frame: df

问题 Why I can not use a stored procedure in OUTER APPLY block? I need to get int value from the stored procedure dbo.GetTeacherId and use this in WHERE clause. Here my code: USE [StudentsDb] DECLARE @teacherIdOut int; SELECT StudentLastName, StudentFirstName, StudentMiddleName, LessonName, Score, TLastName, TFirstName, TMiddleName FROM Scores JOIN Students ON Scores.StudentId=Students.StudentId JOIN Lessons ON Scores.LessonId=Lessons.LessonId OUTER APPLY ( EXECUTE dbo.GetTeacherId 0, 0,

问题 Consider a function foo as follows. foo <- function(a, b, c) { out <- (sum(a) + sqrt(prod(c))) / sqrt(pi * b) return(out) } I would like to apply the function to a data.table DT with the data in columns as arguments, row-wise according to a unique key column ID . DT <- structure(list(ID = c("K1L1", "K1L2", "K1L3", "K2L1", "K2L2", "K2L3", "K3L1", "K3L2", "K3L3", "K4L1", "K4L2", "K4L3", "K5L1", "K5L2", "K5L3"), K1 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), K2 = c(0L, 0L,

问题 I noticed already a couple of times that working with dates doesn't allow for using the usual tricks in R. Say I have a dataframe Data with Dates (see below), and I want to convert the complete dataframe to a date class. The only solution I could come up with until now is : for (i in 1:ncol(Data)){ Data[,i] <- as.Date(Data[,i],format="%d %B %Y") } This gives a dataframe with the correct structure : > str(Data) 'data.frame': 6 obs. of 4 variables: $ Rep1:Class 'Date' num [1:6] 12898 12898

问题 Sample of df: df <- tibble(name = LETTERS[1:10], x = rnorm(10, mean = 10), y = rnorm(10, 10), z = rnorm(10, 10)) I would like to mutate ranked columns for x , then the sums of cols x and y , then x and y and z , where the bigger numbers are ranked 1, then the smallest numbers 10. Starting with x , I could do something like: df %<>% mutate(rank_01 = min_rank(-x)) Which computes the ranked column for x , but then I'm not sure what the best process would be to compute the latter columns. I'm