Let's say some of my users cannot alter their R environments, but I need them to be able to open up RData files. These environment files require a package to be loaded (httpuv to be exact). We don't care about the package, we don't need its capabilities, we just need to get at the data. Is there a way to either force R to bypass loading namespaces when loading the RData file, or fo
假设我的一些用户不能改变他们的R环境，但我需要他们能够打开RData文件。 这些环境文件需要加载一个包（确切地说httpuv）。 我们不关心软件包，我们不需要它的功能，我们只需要获取数据。 有没有办法强制R在加载RData文件时绕过加载名称空间，或者强制R在原始端没有名称空间相关性的情况下保存它？ 谢谢。 要重现，请安装Shiny。 从Shiny applet中创建一些R对象并将其保存到服务器的文件系统中作为RData文件。 将文件复
I needed to read several Excel files and used the gdata package. Unfortunately the files were formated lazily, some with "," decimal/thousand separators some with "." and some with none. To get you an idea, the numbers can look like this: #Five Times 1000.1 and four times 1000.0 x <- c("1,000.1","1.000.1","1000.1","1000,1","1.000,1","1000","1,000","1.000","1000.0") x
我需要阅读几个Excel文件并使用gdata包。 不幸的是，这些文件是懒洋洋地编写的，有些用“，”十进制/千分隔符，一些用“。”。 有的没有。 为了给你一个想法，数字可以像这样： #Five Times 1000.1 and four times 1000.0 x <- c("1,000.1","1.000.1","1000.1","1000,1","1.000,1","1000","1,000","1.000","1000.0") x 有没有一种通用的方法分别将它们转换为1000.1和1000.0？ 我想过使用gsub（）和一个正则表达式。 第一
I am trying to make a RData file from a raw numeric space deliminated text file, ie 11 33 55 22 33 45 25 78 00 44 87 99 .... I have another R script which needs to load this new RData file and perform linear regression with the data using mapreduce (rhipe). Thus when i save this RObject I need to read it back this way: data <- strsplit(unlist(map.values)," ") #so that I can run regressio
我正在尝试从原始数字空间删除文本文件，即，使RData文件 11 33 55 22 33 45 25 78 00 44 87 99 .... 我有另一个R脚本需要加载这个新的RData文件，并使用mapreduce（rhipe）对数据进行线性回归。 因此，当我保存这个RObject时，我需要以这种方式读取它： data <- strsplit(unlist(map.values)," ") #so that I can run regression like: y<- unlist(lapply(data,"[[",1)) x1<-unlist(lapply(data,"[[",2)) x2<-
I have found myself in the position of needing to update one or two data objects in an Rdata file previously created using save . If I'm not careful to load the file I can forget to re-save some objects in the file. As an example, I'm working on a package with some objects stored in sysdata.rda (look-up tables for internal use which I do not want to export) and only want to worry about
我发现自己需要更新先前使用save创建的Rdata文件中的一个或两个数据对象。 如果我不小心加载文件，我可以忘记重新保存文件中的一些对象。 作为一个例子，我正在处理一些存储在sysdata.rda对象（我不想导出用于内部使用的查找表），只想更新单个对象。 我还没有设法确定是否有一个标准的方法来做到这一点，所以创建了我自己的功能。 resave <- function (..., list = character(), file = stop("'file' must be specified"
Whenever I want to do something "map"py in R, I usually try to use a function in the apply family. However, I've never quite understood the differences between them -- how { sapply , lapply , etc.} apply the function to the input/grouped input, what the output will look like, or even what the input can be -- so I often just go through them all until I get what I want. Can someon
每当我想在R中做一些“映射”py时，我通常会尝试在apply系列中使用函数。 但是，我从来没有完全理解它们之间的差异 - 如何将输入/分组输入应用到函数，输出将会是什么样子，甚至输入什么样的东西，所以{ sapply ， lapply等}我经常只是经历他们，直到我得到我想要的。 有人可以解释如何使用哪一个？ 我目前（可能不正确/不完整）的理解是...... sapply(vec, f) ：输入是一个向量。 输出是一个向量/矩阵，其中元素i是f(vec
Let's say we have the following function: foo <- function(x) { line1 <- x line2 <- 0 line3 <- line1 + line2 return(line3) } And that we want to change the second line to be: line2 <- 2 How would you do that? One way is to use fix(foo) And change the function. Another way is to just write the function again. Is there another way? (Remember, the t
假设我们有以下功能： foo <- function(x) { line1 <- x line2 <- 0 line3 <- line1 + line2 return(line3) } 而且我们希望将第二行更改为： line2 <- 2 你会怎么做？ 一种方法是使用 fix(foo) 并改变功能。 另一种方法是再次写入函数。 有另一种方法吗？ （记住，任务是改变第二行） 我想以某种方式将函数表示为字符串的向量（以及字符），然后更改其中一个值，然后再次将其
I had a problem using function Sweave . It seemed to be an encoding problem because I did not specify any encoding like: usepackage[latin1]{inputenc}. Now using button "Compile PDF" works -> PDF is generated and everythink is OK. But I'm getting 30 warnings and 18 badboxes. Using function Sweave to generate first the tex file fails with this message: Error: chunk 4 (label
使用Sweave函数时出现问题。 这似乎是一个编码问题，因为我没有指定任何编码，如： usepackage [latin1] {inputenc}。 现在使用按钮“Compile PDF”工作 - >生成PDF并且每个方面都可以。 但我得到30个警告和18个坏箱。 使用函数Sweave首先生成tex文件失败，并显示以下消息： Error: chunk 4 (label = t4) Error in file(con, "w") : cannot open the connection In addition: There were 31 warnings (use warnings() to
I was wondering if it is possible to change the rows and columns annotation of a balloon plot generated by the gplots package. Assuming my data are a subset of the mtcars dataset data(mtcars) dt <- as.table(as.matrix(mtcars[1:10,])) I can make the balloon plot as follows library("gplots") balloonplot(t(dt), xlab ="", ylab="", label = FALSE, show.margins = FALSE) Can I change the color of
我想知道是否可以更改由gplots包生成的气球图的行和列注释。 假设我的数据是mtcars数据集的一个子集 data(mtcars) dt <- as.table(as.matrix(mtcars[1:10,])) 我可以如下制作气球图 library("gplots") balloonplot(t(dt), xlab ="", ylab="", label = FALSE, show.margins = FALSE) 我可以用任意颜色更改灰色条的颜色（对于x和y）吗？ 例如，我想要红，蓝，绿，蓝，蓝，绿，蓝，蓝，绿，蓝，蓝三种颜色。 这可能吗？
Take the example of mtcars in R: I want to make a non linear regression for the relationship between mpg and disp with: nls(data=mtcars, mpg ~ A * disp^2 + B * disp + C, start=list(A=1,B=1,C=1)) But, I need to analyse the relationship for every combination of cyl, gear and carb. I tried to do this : nlsList(data=mtcars, mpg ~ A * disp^2 + B * disp + C | cyl * gear * carb,
以R中的mtcars为例：我想对mpg和disp之间的关系进行非线性回归： nls(data=mtcars, mpg ~ A * disp^2 + B * disp + C, start=list(A=1,B=1,C=1)) 但是，我需要分析cyl，gear和carb的每种组合的关系。 我试图做到这一点： nlsList(data=mtcars, mpg ~ A * disp^2 + B * disp + C | cyl * gear * carb, start=list(A=1,B=1,C=1)) 但我总是有错误。 最后的目标是用cyl，ge
Given a fresh session, executing a small ggparcoord(.) example provided in the documentation of the function library(GGally) data(diamonds, package="ggplot2") diamonds.samp <- diamonds[sample(1:dim(diamonds)[1], 100), ] ggparcoord(data = diamonds.samp, columns = c(1, 5:10)) results into the following plot: Again, starting in a fresh session and executing the same script with the loaded dp
给定一个新的会话，执行函数文档中提供的一个小ggparcoord（。）示例 library(GGally) data(diamonds, package="ggplot2") diamonds.samp <- diamonds[sample(1:dim(diamonds)[1], 100), ] ggparcoord(data = diamonds.samp, columns = c(1, 5:10)) 结果如下图所示： 再次，从新鲜的会话开始，并使用加载的dplyr执行相同的脚本 library(GGally) library(dplyr) data(diamonds, package="ggplot2") diamonds.samp <-