从data.frame中设置特定的列和行 - 错误消息" ...中的意外符号"

时间:2017-09-26 01:58:30

标签: r dataframe dplyr subset tibble

我是初学者,学习如何从R中的数据集中对特定的行和列进行子集化。我在R Studio中使用state.x77数据集作为练习。当我尝试选择指定的列时,我收到以下错误消息:

library(dplyr)
library(tibble)

select(state.x77, Income, HS Grad)
Error: unexpected symbol in "select(state.x77, Income, HS Grad"

我不明白该行代码中的符号是不正确的。

另外,如果我除了选择某些列(变量)之外还尝试过滤某个状态,当状态列表是行名时,如何使用过滤器功能?当我尝试:

rownames_to_column(state.x77, var = "State")

它为州名创建一个名为State的列,但是当我去查看state.x77时它似乎不是永久的(因此我不能使用过滤器函数)。

对不起,我是初学者。任何帮助将不胜感激。

谢谢。

2 个答案:

答案 0 :(得分:1)

有两个问题。首先,state.x77是一个矩阵,因此您需要将其转换为数据帧,因为select包中的dplyr函数仅将数据帧作为第一个参数。其次,如果列名中有空格,则必须使用“或”来包含列名。

# Load package
library(dplyr)

# Show the class of state.x77
class(state.x77)
# [1] "matrix"

# Convert state.x77 to a data frame
state.x77_df <- as.data.frame(state.x77)

# Show the class of state.x77_df
class(state.x77_df)
[1] "data.frame"

# Select Income and `HS Grad` columns
# All the following will work
select(state.x77_df, Income, `HS Grad`)
select(state.x77_df, "Income", "HS Grad")
select(state.x77_df, c("Income", "HS Grad"))

对于第二个问题,您必须按如下方式将输出保存回对象。

library(tibble)

state.x77_df <- rownames_to_column(state.x77_df,  var = "State")
head(state.x77_df) 
       State Population Income Illiteracy Life Exp Murder HS Grad Frost   Area
1    Alabama       3615   3624        2.1    69.05   15.1    41.3    20  50708
2     Alaska        365   6315        1.5    69.31   11.3    66.7   152 566432
3    Arizona       2212   4530        1.8    70.55    7.8    58.1    15 113417
4   Arkansas       2110   3378        1.9    70.66   10.1    39.9    65  51945
5 California      21198   5114        1.1    71.71   10.3    62.6    20 156361
6   Colorado       2541   4884        0.7    72.06    6.8    63.9   166 103766

答案 1 :(得分:0)

# Convert state.x77 into a dataframe and renaming rowname into State column
df <- tibble::rownames_to_column(data.frame(state.x77), var = "State")

## You can select any columns by their column names or by index
# by column names
 col_names <- c("Income", "HS.Grad")
 df[,col_names]

# by column index
 col_index <- c(3,7)
 df[, col_index]

# Filtering(subsetting) data by state
subset(df, df$State == "Arizona")

 State   Population Income  Illiteracy  Life.Exp Murder HS.Grad  Frost  Area
Arizona       2212   4530        1.8    70.55     7.8    58.1     15   113417