Question

我有以下数据框 [数据框] [1]

现在我想要做的是根据向量p中的值生成带有显着性代码的附加向量（每个估计的p值）。有没有一种方法R可以根据另一个向量的信息生成一个充满星星的矢量（作为重要性）？而且：有没有一种方法可以告诉R，它应该根据新的观察顺序重新组织数据帧（我希望有以下顺序：vol_s，vol_s_avg，vol_s_med，vol_s_end，vol_l等）？

df的结构

structure(list(id = c("vol_avg_cer", "vol_avg_cer",     "vol_avg_cer","vol_avg_cer", "vol_cer", "vol_cer"), type = c("partial", "partial", 
"full", "full", "partial", "partial"), parm = c("vol_s_avg", 
"vol_l_avg", "vol_s_avg", "vol_l_avg", "vol_s", "vol_l"), estimate =     c(-0.00419972506246416, 
-0.0199988264598171, -0.0429143892387528, 0.0367191277063419, 
-0.0180348542378266, -0.0825424096818213), stderr = c(0.00729095969265321, 
0.00950796168366169, 0.0296902477909246, 0.052772355386909,     0.0280972492739437, 
0.0458807583546288), p = c(0.564602918461653, 0.0354328407781613, 
0.148344569863659, 0.486552631437604, 0.520955910904793, 0.0720085952786877
)), .Names = c("id", "type", "parm", "estimate", "stderr", "p"
), row.names = c(1L, 2L, 20L, 21L, 1825L, 1826L), class = "data.frame")

Answer 1

您可以使用symnum将数字转换为符号：

library(dplyr)
mutate(df, signif = symnum(
  p, cutpoints = c(0, 0.01, 0.05, 0.10, 0.5, 1), 
  symbols = c("***", "**", "*", ".", " ")))

Answer 2

在@ user2802241使用dplyr和symnum的答案的基础上，为了对parm列进行排序，您可以将列的顺序定义为单独的向量，然后设置parm列作为使用向量作为其级别的因素，并使用arrange。

e.g。

library(dplyr)

## define a vector with the variables in the order you require
factor_levels <- c("vol_s", "vol_s_avg", "vol_s_med","vol_s_end", "vol_l", "vol_l_avg", "vol_l_med", "vol_l_end")


## stay within dplyr - convert 'parm' to a factor and arrange on it
df <- df %>%
  mutate(signif = symnum(p, 
                         cutpoints = c(0, 0.01, 0.05, 0.10, 0.5, 1), 
                         symbols = c("***", "**", "*", ".", " ")),
         parm = factor(parm, levels = factor_levels)) %>%
  arrange(parm)

> df
           id    type      parm     estimate      stderr          p signif
1     vol_cer partial     vol_s -0.018034854 0.028097249 0.52095591       
2 vol_avg_cer partial vol_s_avg -0.004199725 0.007290960 0.56460292       
3 vol_avg_cer    full vol_s_avg -0.042914389 0.029690248 0.14834457      .
4     vol_cer partial     vol_l -0.082542410 0.045880758 0.07200860      *
5 vol_avg_cer partial vol_l_avg -0.019998826 0.009507962 0.03543284     **
6 vol_avg_cer    full vol_l_avg  0.036719128 0.052772355 0.48655263      .

如果您希望将parm列保留为character，则可以将其转换回来

df <- df %>%
  mutate(signif = symnum(p, 
                     cutpoints = c(0, 0.01, 0.05, 0.10, 0.5, 1), 
                     symbols = c("***", "**", "*", ".", " ")),
     parm = factor(parm, levels = factor_levels)) %>%
arrange(parm) %>%
mutate(parm = as.character(parm))

根据数据框架中的向量生成数值

2 个答案: