r中如何将表格转换为数据框？

Question

假设，我有一个数据集如下：

State <- c("CA", "WI", "TX", "MS", "NY", "KT", "UT", "CO", "PA", "SC")
Pov_rt <- c(25, 30, 35, 40, 45, 50, 10, 15, 25, 40)


df <- data. Frame(State, Pov_rt)

我创建了一个新专栏

df[["pov_level"]] <- cut(
  df$Pov_rt, 
  breaks = c(-Inf, 10, 20, 30, 40, Inf),
  labels = c(
    "Very Low Poverty (<10%)",
    "Low Poverty (10-20%)",
    "Medium Poverty (20-30%)",
    "High Poverty (30-40%)",
    "Very High Poverty (>40%)"
  )
)

我还想订一张桌子

table(df$pov_level, df$State)
                          
                           CA CO KT MS NY PA SC TX UT WI
  Very Low Poverty (<10%)   0  0  0  0  0  0  0  0  1  0
  Low Poverty (10-20%)      0  1  0  0  0  0  0  0  0  0
  Medium Poverty (20-30%)   1  0  0  0  0  1  0  0  0  1
  High Poverty (30-40%)     0  0  0  1  0  0  1  1  0  0
  Very High Poverty (>40%)  0  0  1  0  1  0  0  0  0  0

如果我想将此表转换为数据框，我会这样做

x <- data.frame(unclass(table(df$pov_level, df$State)))

而不是x <- as.data.frame(table(df$pov_level, df$State))因为这给了我一个未分组列表的数据框。

但是使用第一个有一个问题，有时我需要将mutate行名作为新列。

我想知道是否有更好的方法来做到这一点。

非常感谢！

Answer 1

我们可以使用as.data.frame.matrix

\n

df2 <- as.data.frame.matrix(table(df$pov_level, df$State))\n

\n

-输出

\n

> df2\n                         CA CO KT MS NY PA SC TX UT WI\nVery Low Poverty (<10%)   0  0  0  0  0  0  0  0  1  0\nLow Poverty (10-20%)      0  1  0  0  0  0  0  0  0  0\nMedium Poverty (20-30%)   1  0  0  0  0  1  0  0  0  1\nHigh Poverty (30-40%)     0  0  0  1  0  0  1  1  0  0\nVery High Poverty (>40%)  0  0  1  0  1  0  0  0  0  0\n> str(df2)\n'data.frame':   5 obs. of  10 variables:\n $ CA: int  0 0 1 0 0\n $ CO: int  0 1 0 0 0\n $ KT: int  0 0 0 0 1\n $ MS: int  0 0 0 1 0\n $ NY: int  0 0 0 0 1\n $ PA: int  0 0 1 0 0\n $ SC: int  0 0 0 1 0\n $ TX: int  0 0 0 1 0\n $ UT: int  1 0 0 0 0\n $ WI: int  0 0 1 0 0\n

\n

rownames_to_column可以使用( tibble)从行名创建列

\n

library(tibble)\nlibrary(dplyr)\ndf2 %>%\n  rownames_to_column("pov_levels")\n                pov_levels CA CO KT MS NY PA SC TX UT WI\n1  Very Low Poverty (<10%)  0  0  0  0  0  0  0  0  1  0\n2     Low Poverty (10-20%)  0  1  0  0  0  0  0  0  0  0\n3  Medium Poverty (20-30%)  1  0  0  0  0  1  0  0  0  1\n4    High Poverty (30-40%)  0  0  0  1  0  0  1  1  0  0\n5 Very High Poverty (>40%)  0  0  1  0  1  0  0  0  0  0\n

\n\n

或者如果我们想使用tidyverse

\n

library(tidyr)\npivot_wider(df, names_from = State, values_from = Pov_rt,\n     values_fn = length, values_fill = 0)\n# A tibble: 5 \xc3\x97 11\n  pov_level                   CA    WI    TX    MS    NY    KT    UT    CO    PA    SC\n  <fct>                    <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>\n1 Medium Poverty (20-30%)      1     1     0     0     0     0     0     0     1     0\n2 High Poverty (30-40%)        0     0     1     1     0     0     0     0     0     1\n3 Very High Poverty (>40%)     0     0     0     0     1     1     0     0     0     0\n4 Very Low Poverty (<10%)      0     0     0     0     0     0     1     0     0     0\n5 Low Poverty (10-20%)         0     0     0     0     0     0     0     1     0     0\n

\n\n

或者更直接地使用tabyl

\n

library(janitor)\ndf %>%\n   tabyl(pov_level, State)\n                pov_level CA CO KT MS NY PA SC TX UT WI\n  Very Low Poverty (<10%)  0  0  0  0  0  0  0  0  1  0\n     Low Poverty (10-20%)  0  1  0  0  0  0  0  0  0  0\n  Medium Poverty (20-30%)  1  0  0  0  0  1  0  0  0  1\n    High Poverty (30-40%)  0  0  0  1  0  0  1  1  0  0\n Very High Poverty (>40%)  0  0  1  0  1  0  0  0  0  0\n

\n