- html - 出于某种原因,IE8 对我的 Sass 文件中继承的 html5 CSS 不友好?
- JMeter 在响应断言中使用 span 标签的问题
- html - 在 :hover and :active? 上具有不同效果的 CSS 动画
- html - 相对于居中的 html 内容固定的 CSS 重复背景?
我有一个嵌套列表,名为 mylist
长度为 4。
这个列表的每个元素都是一个实验:exp1.1
, exp1.2
, exp2.1
和 exp2.2
.
每个实验包含四个植物生长阶段的长度(以天为单位)的观察:EM-V6
V6-R0
R0-R4
和 R4-R9
.
每个成长阶段都组织为一个数据框,带有 year
和 mean
.
这是完整的数据:
mylist=structure(list(exp1.1 = structure(list(`EM-V6` = structure(list(
year = 2011:2100, mean = c(34, 34, 32, 28, 25, 32, 32, 28,
27, 30, 32, 31, 33, 28, 26, 31, 33, 27, 34, 26, 28, 27, 27,
30, 29, 31, 34, 30, 26, 31, 33, 33, 27, 30, 28, 32, 31, 29,
32, 31, 25, 28, 28, 26, 32, 29, 26, 31, 28, 29, 30, 25, 27,
32, 27, 28, 28, 30, 24, 30, 29, 29, 29, 28, 26, 28, 26, 26,
28, 31, 30, 27, 26, 28, 25, 24, 24, 30, 27, 26, 26, 27, 26,
26, 24, 26, 28, 25, 30, 26)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `V6-R0` = structure(list(year = 2011:2100,
mean = c(30, 33, 33, 32, 29, 30, 32, 31, 32, 30, 33, 30,
32, 33, 33, 32, 29, 31, 32, 28, 31, 29, 36, 29, 30, 30, 33,
31, 33, 30, 34, 32, 29, 31, 28, 30, 30, 29, 34, 31, 32, 31,
30, 28, 32, 29, 29, 32, 29, 28, 29, 29, 32, 31, 27, 32, 29,
31, 29, 29, 30, 29, 29, 29, 28, 28, 30, 30, 30, 32, 29, 29,
30, 29, 29, 29, 28, 28, 29, 30, 29, 29, 29, 30, 28, 30, 30,
29, 29, 29)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R0-R4` = structure(list(year = 2011:2100,
mean = c(31, 32, 32, 33, 32, 32, 33, 31, 34, 32, 33, 33,
32, 31, 33, 31, 32, 32, 32, 30, 32, 31, 34, 30, 31, 32, 34,
33, 34, 32, 36, 33, 32, 32, 31, 30, 32, 32, 32, 32, 32, 32,
31, 30, 30, 31, 32, 32, 30, 30, 32, 31, 31, 32, 30, 32, 29,
32, 31, 30, 32, 30, 30, 31, 32, 30, 31, 30, 31, 32, 31, 31,
30, 30, 30, 31, 30, 30, 31, 30, 31, 30, 30, 30, 31, 32, 30,
31, 30, 30)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R4-R9` = structure(list(year = 2011:2100,
mean = c(27, 29, 28, 28, 27, 30, 29, 27, 30, 26, 30, 28,
29, 28, 29, 27, 29, 28, 25, 26, 26, 25, 27, 27, 27, 28, 30,
28, 29, 27, 29, 28, 29, 28, 26, 26, 28, 28, 30, 28, 27, 25,
26, 25, 25, 26, 26, 27, 25, 25, 26, 25, 27, 28, 24, 27, 25,
28, 26, 24, 27, 26, 27, 25, 26, 26, 24, 26, 25, 26, 24, 25,
25, 26, 26, 25, 25, 25, 25, 25, 26, 25, 25, 25, 25, 26, 26,
26, 25, 24)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame")), .Names = c("EM-V6", "V6-R0", "R0-R4",
"R4-R9")), exp1.2 = structure(list(`EM-V6` = structure(list(year = 2011:2100,
mean = c(34, 34, 32, 28, 25, 32, 32, 28, 27, 30, 32, 31,
33, 28, 26, 31, 33, 27, 34, 26, 28, 27, 27, 30, 29, 31, 34,
30, 26, 31, 33, 33, 27, 30, 28, 32, 31, 29, 32, 31, 25, 28,
28, 26, 32, 29, 26, 31, 28, 29, 30, 25, 27, 32, 27, 28, 28,
30, 24, 30, 29, 29, 29, 28, 26, 28, 26, 26, 28, 31, 30, 27,
26, 28, 25, 24, 24, 30, 27, 26, 26, 27, 26, 26, 24, 26, 28,
25, 30, 26)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `V6-R0` = structure(list(year = 2011:2100,
mean = c(30, 33, 33, 32, 29, 30, 32, 31, 32, 30, 33, 30,
32, 33, 33, 32, 29, 31, 32, 28, 31, 29, 36, 29, 30, 30, 33,
31, 33, 30, 34, 32, 29, 31, 28, 30, 30, 29, 34, 31, 32, 31,
30, 28, 32, 29, 29, 32, 29, 28, 29, 29, 32, 31, 27, 32, 29,
31, 29, 29, 30, 29, 29, 29, 28, 28, 30, 30, 30, 32, 29, 29,
30, 29, 29, 29, 28, 28, 29, 30, 29, 29, 29, 30, 28, 30, 30,
29, 29, 29)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R0-R4` = structure(list(year = 2011:2100,
mean = c(31, 32, 32, 33, 32, 32, 33, 31, 34, 32, 33, 33,
32, 31, 33, 31, 32, 32, 32, 30, 32, 31, 34, 30, 31, 32, 34,
33, 34, 32, 36, 33, 32, 32, 31, 30, 32, 32, 32, 32, 32, 32,
31, 30, 30, 31, 32, 32, 30, 30, 32, 31, 31, 32, 30, 32, 29,
32, 31, 30, 32, 30, 30, 31, 32, 30, 31, 30, 31, 32, 31, 31,
30, 30, 30, 31, 30, 30, 31, 30, 31, 30, 30, 30, 31, 32, 30,
31, 30, 30)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R4-R9` = structure(list(year = 2011:2100,
mean = c(27, 29, 28, 28, 27, 30, 29, 27, 30, 26, 30, 28,
29, 28, 29, 27, 29, 28, 25, 26, 26, 25, 27, 27, 27, 28, 30,
28, 29, 27, 29, 28, 29, 28, 26, 26, 28, 28, 30, 28, 27, 25,
26, 25, 25, 26, 26, 27, 25, 25, 26, 25, 27, 28, 24, 27, 25,
28, 26, 24, 27, 26, 27, 25, 26, 26, 24, 26, 25, 26, 24, 25,
25, 26, 26, 25, 25, 25, 25, 25, 26, 25, 25, 25, 25, 26, 26,
26, 25, 24)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame")), .Names = c("EM-V6", "V6-R0", "R0-R4",
"R4-R9")), exp2.1 = structure(list(`EM-V6` = structure(list(year = 2011:2100,
mean = c(34, 34, 32, 28, 25, 32, 32, 28, 27, 30, 32, 31,
33, 28, 26, 31, 33, 27, 34, 26, 28, 27, 27, 30, 29, 31, 34,
30, 26, 31, 33, 33, 27, 30, 28, 32, 31, 29, 32, 31, 25, 28,
28, 26, 32, 29, 26, 31, 28, 29, 30, 25, 27, 32, 27, 28, 28,
30, 24, 30, 29, 29, 29, 28, 26, 28, 26, 26, 28, 31, 30, 27,
26, 28, 25, 24, 24, 30, 27, 26, 26, 27, 26, 26, 24, 26, 28,
25, 30, 26)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `V6-R0` = structure(list(year = 2011:2100,
mean = c(30, 33, 33, 32, 29, 30, 32, 31, 32, 30, 33, 30,
32, 33, 33, 32, 29, 31, 32, 28, 31, 29, 36, 29, 30, 30, 33,
31, 33, 30, 34, 32, 29, 31, 28, 30, 30, 29, 34, 31, 32, 31,
30, 28, 32, 29, 29, 32, 29, 28, 29, 29, 32, 31, 27, 32, 29,
31, 29, 29, 30, 29, 29, 29, 28, 28, 30, 30, 30, 32, 29, 29,
30, 29, 29, 29, 28, 28, 29, 30, 29, 29, 29, 30, 28, 30, 30,
29, 29, 29)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R0-R4` = structure(list(year = 2011:2100,
mean = c(31, 32, 32, 33, 32, 32, 33, 31, 34, 32, 33, 33,
32, 31, 33, 31, 32, 32, 32, 30, 32, 31, 34, 30, 31, 32, 34,
33, 34, 32, 36, 33, 32, 32, 31, 30, 32, 32, 32, 32, 32, 32,
31, 30, 30, 31, 32, 32, 30, 30, 32, 31, 31, 32, 30, 32, 29,
32, 31, 30, 32, 30, 30, 31, 32, 30, 31, 30, 31, 32, 31, 31,
30, 30, 30, 31, 30, 30, 31, 30, 31, 30, 30, 30, 31, 32, 30,
31, 30, 30)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R4-R9` = structure(list(year = 2011:2100,
mean = c(27, 29, 28, 28, 27, 30, 29, 27, 30, 26, 30, 28,
29, 28, 29, 27, 29, 28, 25, 26, 26, 25, 27, 27, 27, 28, 30,
28, 29, 27, 29, 28, 29, 28, 26, 26, 28, 28, 30, 28, 27, 25,
26, 25, 25, 26, 26, 27, 25, 25, 26, 25, 27, 28, 24, 27, 25,
28, 26, 24, 27, 26, 27, 25, 26, 26, 24, 26, 25, 26, 24, 25,
25, 26, 26, 25, 25, 25, 25, 25, 26, 25, 25, 25, 25, 26, 26,
26, 25, 24)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame")), .Names = c("EM-V6", "V6-R0", "R0-R4",
"R4-R9")), exp2.2 = structure(list(`EM-V6` = structure(list(year = 2011:2100,
mean = c(34, 34, 32, 28, 25, 32, 32, 28, 27, 30, 32, 31,
33, 28, 26, 31, 33, 27, 34, 26, 28, 27, 27, 30, 29, 31, 34,
30, 26, 31, 33, 33, 27, 30, 28, 32, 31, 29, 32, 31, 25, 28,
28, 26, 32, 29, 26, 31, 28, 29, 30, 25, 27, 32, 27, 28, 28,
30, 24, 30, 29, 29, 29, 28, 26, 28, 26, 26, 28, 31, 30, 27,
26, 28, 25, 24, 24, 30, 27, 26, 26, 27, 26, 26, 24, 26, 28,
25, 30, 26)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `V6-R0` = structure(list(year = 2011:2100,
mean = c(30, 33, 33, 32, 29, 30, 32, 31, 32, 30, 33, 30,
32, 33, 33, 32, 29, 31, 32, 28, 31, 29, 36, 29, 30, 30, 33,
31, 33, 30, 34, 32, 29, 31, 28, 30, 30, 29, 34, 31, 32, 31,
30, 28, 32, 29, 29, 32, 29, 28, 29, 29, 32, 31, 27, 32, 29,
31, 29, 29, 30, 29, 29, 29, 28, 28, 30, 30, 30, 32, 29, 29,
30, 29, 29, 29, 28, 28, 29, 30, 29, 29, 29, 30, 28, 30, 30,
29, 29, 29)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R0-R4` = structure(list(year = 2011:2100,
mean = c(31, 32, 32, 33, 32, 32, 33, 31, 34, 32, 33, 33,
32, 31, 33, 31, 32, 32, 32, 30, 32, 31, 34, 30, 31, 32, 34,
33, 34, 32, 36, 33, 32, 32, 31, 30, 32, 32, 32, 32, 32, 32,
31, 30, 30, 31, 32, 32, 30, 30, 32, 31, 31, 32, 30, 32, 29,
32, 31, 30, 32, 30, 30, 31, 32, 30, 31, 30, 31, 32, 31, 31,
30, 30, 30, 31, 30, 30, 31, 30, 31, 30, 30, 30, 31, 32, 30,
31, 30, 30)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R4-R9` = structure(list(year = 2011:2100,
mean = c(27, 29, 28, 28, 27, 30, 29, 27, 30, 26, 30, 28,
29, 28, 29, 27, 29, 28, 25, 26, 26, 25, 27, 27, 27, 28, 30,
28, 29, 27, 29, 28, 29, 28, 26, 26, 28, 28, 30, 28, 27, 25,
26, 25, 25, 26, 26, 27, 25, 25, 26, 25, 27, 28, 24, 27, 25,
28, 26, 24, 27, 26, 27, 25, 26, 26, 24, 26, 25, 26, 24, 25,
25, 26, 26, 25, 25, 25, 25, 25, 26, 25, 25, 25, 25, 26, 26,
26, 25, 24)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame")), .Names = c("EM-V6", "V6-R0", "R0-R4",
"R4-R9"))), .Names = c("exp1.1", "exp1.2", "exp2.1", "exp2.2"
))
YEAR EXP EM-V6 V6-R0 R0-R4 R4-R9
2011 exp1.1 34 30 31 27
2011 exp1.2 34 30 31 27
2011 exp2.1 34 30 31 27
2011 exp1.1 34 30 31 27
- first year, first experiment, and growth stages.
- first year, second experiment and growth stages.
- first year, third experiment and growth stages
- first year, fourth experiment and growth stages
- second year, first experiment and growth stages
最佳答案
使用 rbindlist
的替代方法来自 data.table
-打包两次:
library(data.table)
# bind the dataframes in the 'listed lists' together and include the year with the 'id'-parameter
# the resulting 'data.table's are returned as a list
step1 <- lapply(mylist, rbindlist, id = 'stages')
# bind the resulting list together and include the experiment id
step2 <- rbindlist(step1, id = 'experiment')
# reshape to wide format
dcast(step2, year + experiment ~ stages, value.var = 'mean')
dcast(rbindlist(lapply(mylist, rbindlist, id = 'stages'), id = 'experiment'),
year + experiment ~ stages, value.var = 'mean')
year experiment EM-V6 R0-R4 R4-R9 V6-R0
1: 2011 exp1.1 34 31 27 30
2: 2011 exp1.2 34 31 27 30
3: 2011 exp2.1 34 31 27 30
4: 2011 exp2.2 34 31 27 30
5: 2012 exp1.1 34 32 29 33
---
356: 2099 exp2.2 30 30 25 29
357: 2100 exp1.1 26 30 24 29
358: 2100 exp1.2 26 30 24 29
359: 2100 exp2.1 26 30 24 29
360: 2100 exp2.2 26 30 24 29
关于r - 将列表列表转换为数据框,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/41804560/
我正在从 Stata 迁移到 R(plm 包),以便进行面板模型计量经济学。在 Stata 中,面板模型(例如随机效应)通常报告组内、组间和整体 R 平方。 I have found plm 随机效应
关闭。这个问题不符合Stack Overflow guidelines .它目前不接受答案。 想改进这个问题?将问题更新为 on-topic对于堆栈溢出。 6年前关闭。 Improve this qu
我想要求用户输入整数值列表。用户可以输入单个值或一组多个值,如 1 2 3(spcae 或逗号分隔)然后使用输入的数据进行进一步计算。 我正在使用下面的代码 EXP <- as.integer(rea
当 R 使用分类变量执行回归时,它实际上是虚拟编码。也就是说,省略了一个级别作为基础或引用,并且回归公式包括所有其他级别的虚拟变量。但是,R 选择了哪一个作为引用,以及我如何影响这个选择? 具有四个级
这个问题基本上是我之前问过的问题的延伸:How to only print (adjusted) R-squared of regression model? 我想建立一个线性回归模型来预测具有 15
我在一台安装了多个软件包的 Linux 计算机上安装了 R。现在我正在另一台 Linux 计算机上设置 R。从他们的存储库安装 R 很容易,但我将不得不使用 安装许多包 install.package
我正在阅读 Hadley 的高级 R 编程,当它讨论字符的内存大小时,它说: R has a global string pool. This means that each unique strin
我们可以将 Shiny 代码写在两个单独的文件中,"ui.R"和 "server.R" , 或者我们可以将两个模块写入一个文件 "app.R"并调用函数shinyApp() 这两种方法中的任何一种在性
我正在使用 R 通过 RGP 包进行遗传编程。环境创造了解决问题的功能。我想将这些函数保存在它们自己的 .R 源文件中。我这辈子都想不通怎么办。我尝试过的一种方法是: bf_str = print(b
假设我创建了一个函数“function.r”,在编辑该函数后我必须通过 source('function.r') 重新加载到我的全局环境中。无论如何,每次我进行编辑时,我是否可以避免将其重新加载到我的
例如,test.R 是一个单行文件: $ cat test.R # print('Hello, world!') 我们可以通过Rscript test.R 或R CMD BATCH test.R 来
我知道我可以使用 Rmd 来构建包插图,但想知道是否可以更具体地使用 R Notebooks 来制作包插图。如果是这样,我需要将 R Notebooks 编写为包小插图有什么不同吗?我正在使用最新版本
我正在考虑使用 R 包的共享库进行 R 的站点安装。 多台计算机将访问该库,以便每个人共享相同的设置。 问题是我注意到有时您无法更新包,因为另一个 R 实例正在锁定库。我不能要求每个人都关闭它的 R
我知道如何从命令行启动 R 并执行表达式(例如, R -e 'print("hello")' )或从文件中获取输入(例如, R -f filename.r )。但是,在这两种情况下,R 都会运行文件中
我正在尝试使我当前的项目可重现,因此我正在创建一个主文档(最终是一个 .rmd 文件),用于调用和执行其他几个文档。这样我自己和其他调查员只需要打开和运行一个文件。 当前设置分为三层:主文件、2 个读
关闭。这个问题不符合Stack Overflow guidelines .它目前不接受答案。 想改进这个问题?将问题更新为 on-topic对于堆栈溢出。 5年前关闭。 Improve this qu
我的 R 包中有以下描述文件 Package: blah Title: What the Package Does (one line, title case) Version: 0.0.0.9000
有没有办法更有效地编写以下语句?accel 是一个数据框。 accel[[2]]<- accel[[2]]-weighted.mean(accel[[2]]) accel[[3]]<- accel[[
例如,在尝试安装 R 包时 curl作为 usethis 的依赖项: * installing *source* package ‘curl’ ... ** package ‘curl’ succes
我想将一些软件作为一个包共享,但我的一些脚本似乎并不能很自然地作为函数运行。例如,考虑以下代码块,其中“raw.df”是一个包含离散和连续类型变量的数据框。函数“count.unique”和“squa
我是一名优秀的程序员,十分优秀!