我有一个如下数据框:
year income group
1 2008 27907 Under25
2 2009 25522 Under25
3 2010 26777 Under25
4 2008 58809 Age25_34
5 2009 57239 Age25_34
6 2010 58558 Age25_34
7 2008 75677 Age35_44
8 2009 74900 Age35_44
9 2010 74136 Age35_44
10 2008 78537 Age45_54
11 2009 77460 Age45_54
12 2010 76266 Age45_54
13 2008 69009 Age55_64
14 2009 67586 Age55_64
15 2008 44402 Age65_74
16 2009 46147 Age65_74
17 2010 48595 Age65_74
18 2008 32747 Over75
19 2009 31272 Over75
20 2010 31638 Over75
> str(df)
'data.frame': 20 obs. of 3 variables:
$ year : int 2008 2009 2010 2008 2009 2010 2008 2009 2010 2008 ...
$ income: int 27907 25522 26777 58809 57239 58558 75677 74900 74136 78537 ...
$ group : Factor w/ 7 levels "Age25_34","Age35_44",..: 7 7 7 1 1 1 2 2 2 3 ...
我想使用强制转换来按组找到均值。另外,我想从这个df创建一个宽的data.frame,第一列是年,下面的列是不同组的收入。例如
year under25 Age25_34 Age35_44 Age45_54 ...
2008 27907 58809 75677 78537 ...
2009 25522 57239 74900 77460 ...
...
当我尝试演员时,我收到以下错误:
施放(df,收入〜组,意思) 使用组作为值列。使用值参数进行强制转换以覆盖此选项
[.data.frame
中的错误(数据,变量,drop = FALSE): 选择了未定义的列
我对cast命令做错了什么?
如何将其转换为宽格式,如示例所示?
我的R版本信息如下所示。
> unlist(R.Version())
platform arch os
"x86_64-pc-mingw32" "x86_64" "mingw32"
system status major
"x86_64, mingw32" "" "2"
minor year month
"13.1" "2011" "07"
day svn rev language
"08" "56322" "R"
version.string
"R version 2.13.1 (2011-07-08)"
答案 0 :(得分:35)
使用cast
cast(df, year ~ group, mean, value = 'income')
year Age25_34 Age35_44 Age45_54 Age55_64 Age65_74 Over75 Under25
1 2008 58809 75677 78537 69009 44402 32747 27907
2 2009 57239 74900 77460 67586 46147 31272 25522
3 2010 58558 74136 76266 NaN 48595 31638 26777
答案 1 :(得分:5)
aggregate(cbind(year, income)~group, data=df, FUN=mean)
group year income
1 Age25_34 2009.0 58202.00
2 Age35_44 2009.0 74904.33
3 Age45_54 2009.0 77421.00
4 Age55_64 2008.5 68297.50
5 Age65_74 2009.0 46381.33
6 Over75 2009.0 31885.67
7 Under25 2009.0 26735.33
答案 2 :(得分:2)
为什么不使用tapply?
with(df, tapply(income, list(year, group), mean))
(感谢Ramnath的好评)
答案 3 :(得分:-1)
创建数据框:
year<-c(2008,2009, 2010,2008,2009, 2010, 2008,2009, 2010,2008, 2009, 2010, 2008, 2009, 2008, 2009, 2010, 2008,2009,2010)
income<-c(27907,25522, 26777,58809, 57239, 58558, 75677,74900, 74136, 78537,77460,76266, 69009,67586, 44402, 46147,48595,32747, 31272,31638)
group<-c("Under25","Under25","Under25","Age25_34","Age25_34","Age25_34","Age35_44","Age35_44","Age35_44","Age45_54","Age45_54","Age45_54","Age55_64","Age55_64","Age65_74","Age65_74","Age65_74","Over75","Over75","Over75")
demographic_data<-data.frame(year, income,group)
demographic_data
str(demographic_data)
按年度将人口统计数据融化:
library(reshape)
melted_demographic_data<-melt(demographic_data,id=c("group","year"))
melted_demographic_data
groupmeans<-cast(melted_demographic_data,group~variable, mean)
groupmeans
yearmeans<-cast(melted_demographic_data,year~variable, mean)
yearmeans