我目前有一个 dataframe由置信区间的下限和上限以及点估计组成。我想创建一个新的数据框，以便可以绘制点估计不等于零的变量。对于n的每个值，是否可以将上限和下限的值更改为na如果点估计值为0？例如，在n = 205时提供的数据框中，y_pe = 0所以我想更改相应的y_lo和y_up 到 NA。
X1_lo <- c(0 ,0 ,0 ,0 ,0 ,0 ,0 ,0, 0 ,0)
X1_up <-c(0 ,0 ,0 ,0 ,0 ,0 ,0 ,0, 0 ,0)
X1_pe <-c(0 ,0 ,0 ,0 ,0 ,0 ,0 ,0, 0 ,0)
x_lo <- c(0 ,0 ,0 ,0 ,0 ,0 ,0 ,0, 0 ,0)
x_up <- c(0 ,0 ,0 ,0 ,0 ,0 ,0 ,0, 0 ,0)
x_pe <- c(0 ,0 ,0 ,0 ,0 ,0 ,0 ,0, 0 ,0)
y_lo <- c(-24.71177, -25.13779, -16.19142, -15.63819 ,-15.42051 ,-16.11342, -17.10603 ,-18.00848 ,-19.59877, -12.91438)
y_up <- c(14.074116, 14.051209, 13.417954, 12.187319 ,13.602022, 12.943939, 1.317839 ,11.891103, 15.165398, 1.365459)
y_pe <- c(-2.984101, -2.867680, -2.695838 ,-2.583140, -2.416878 , 0.000000, 0.000000 , 0.000000 , 0.000000, 0.000000)
test.df <- cbind(n, X1_lo, X1_up, x_lo, x_up, y_lo, y_up, X1_pe, x_pe, y_pe)
提前致谢。
最佳答案
使用列名称在 i 和 j 中指定逻辑向量，然后将 'y_pe' 为 0 的列分配给 NA
test.df[test.df[, "y_pe"] == 0, c("y_lo", "y_up")] <- NA
如果数据是 data.frame 并且希望应用于除第一列 ('n') 之外的所有列集，那么我们可以拆分 为一组 data.frames 并进行替换
nm1 <- sub("_.*", "", colnames(test.df)[-1])
out <- do.call(cbind, unname(lapply(split.default(test.df[-1], nm1),
function(x) {
i1 <- endsWith(names(x), "pe")
x[!x[,i1], !i1] <- NA
x})))
out
# x_lo x_up x_pe X1_lo X1_up X1_pe y_lo y_up y_pe
#1 NA NA 0 NA NA 0 -24.71177 14.07412 -2.984101
#2 NA NA 0 NA NA 0 -25.13779 14.05121 -2.867680
#3 NA NA 0 NA NA 0 -16.19142 13.41795 -2.695838
#4 NA NA 0 NA NA 0 -15.63819 12.18732 -2.583140
#5 NA NA 0 NA NA 0 -15.42051 13.60202 -2.416878
#6 NA NA 0 NA NA 0 NA NA 0.000000
#7 NA NA 0 NA NA 0 NA NA 0.000000
#8 NA NA 0 NA NA 0 NA NA 0.000000
#9 NA NA 0 NA NA 0 NA NA 0.000000
#10 NA NA 0 NA NA 0 NA NA 0.000000
test.df[names(out)] <- out
test.df
# n X1_lo X1_up x_lo x_up y_lo y_up X1_pe x_pe y_pe
#1 205 NA NA NA NA -24.71177 14.07412 0 0 -2.984101
#2 205 NA NA NA NA -25.13779 14.05121 0 0 -2.867680
#3 205 NA NA NA NA -16.19142 13.41795 0 0 -2.695838
#4 205 NA NA NA NA -15.63819 12.18732 0 0 -2.583140
#5 205 NA NA NA NA -15.42051 13.60202 0 0 -2.416878
#6 205 NA NA NA NA NA NA 0 0 0.000000
#7 205 NA NA NA NA NA NA 0 0 0.000000
#8 205 NA NA NA NA NA NA 0 0 0.000000
#9 205 NA NA NA NA NA NA 0 0 0.000000
#10 205 NA NA NA NA NA NA 0 0 0.000000
或者使用tidyverse
library(dplyr)
library(tidyr)
library(stringr)
test.df %>%
mutate(rn = row_number()) %>%
pivot_longer(cols = -c(n, rn), names_sep="_",
names_to = c("group", ".value")) %>%
mutate_at(vars(lo, up), ~ replace(., pe == 0, NA)) %>%
pivot_wider(names_from = "group", values_from = c('lo', 'up', 'pe'),
names_repair = ~ str_replace(., "(.*)_(.*)", "\\2_\\1")) %>%
select(-rn)
# A tibble: 10 x 10
# n X1_lo x_lo y_lo X1_pe x_pe y_pe X1_up x_up y_up
# <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 205 NA NA -24.7 0 0 -2.98 NA NA 14.1
# 2 205 NA NA -25.1 0 0 -2.87 NA NA 14.1
# 3 205 NA NA -16.2 0 0 -2.70 NA NA 13.4
# 4 205 NA NA -15.6 0 0 -2.58 NA NA 12.2
# 5 205 NA NA -15.4 0 0 -2.42 NA NA 13.6
# 6 205 NA NA NA 0 0 0 NA NA NA
# 7 205 NA NA NA 0 0 0 NA NA NA
# 8 205 NA NA NA 0 0 0 NA NA NA
# 9 205 NA NA NA 0 0 0 NA NA NA
#10 205 NA NA NA 0 0 0 NA NA NA
数据
test.df <- data.frame(n, X1_lo, X1_up, x_lo, x_up, y_lo, y_up, X1_pe, x_pe, y_pe)
关于r - 根据特定列更改数据框中的值，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/61069569/