融化并铸造一个笨拙的数据框

Melt and dcast an awkward dataframe

我正在使用如下所示的数据框。我想看起来像:

省份:选区:甲党票数:甲党百分比:乙党票数:乙党百分比:丙党票数:丙党百分比

目前,候选人姓名作为唯一标识符运行良好,避免了对聚合功能的需要,但我最终会放弃它。

candidate<-c('bob jones', 'bobby jones', 'sara jones', 'sara norah', 'nora jones', 'other name', 'name other', 'thomas name', 'name judge', 'my mayor', 'peter peter', 'paul paul')
party<-rep(c('A', 'B', 'C'), 4)
district<-c(rep('District 1', 3), rep('District 2', 3), rep('District 3', 3), rep('Disctrict 4', 3))
province<-c(rep('Province 1', 3), rep('Province 2', 3), rep('Province 3', 3), rep('Province 4', 3))
votes<-round(rnorm(12, mean=5000, sd=1000),0)
percent<-round(rnorm(12, mean=37, sd=10),2)
df<-data.frame(party, district,province, votes, percent, candidate)

我正在使用这些命令

df.test<-melt(df, id.vars=c('candidate', 'province', 'district', 'party'))
dcast(df.test, candidate+province+district~variable+party, value.var=c('value'))

很接近,不是每个区创建一行,而是每个区创建四行。问题是:在我的样本数据集中,当我从我的转换调用中删除 'candidate' 时,这个样本数据集工作得很好,例如

dcast(df.test, district~variable+party, value.var=c('value'))

但是当我在我的数据集中使用相同的调用时,我不再拥有唯一标识符,并且这会在长度上聚合。

希望对您有所帮助。谢谢。

data.table v1.9.5 中,dcast 可以在多个 value.var 列上进行转换。有了它你可以做:

require(data.table) #v1.9.5+
ans = dcast(setDT(df), province + district ~ party, value.var = c("votes", "percent"))
#      province    district votes_A votes_B votes_C percent_A percent_B percent_C
# 1: Province 1  District 1    3072    3149    4262     34.29     18.45     19.20
# 2: Province 2  District 2    5918    3970    4201     36.56     46.22     43.16
# 3: Province 3  District 3    5593    5208    5260     26.58     31.20     39.00
# 4: Province 4 Disctrict 4    6138    4537    6293     43.97     43.62     32.48

如果您想要 data.frame 回来,那么您可以 setDF(ans)ans 转换为 data.frame

您可以按照these instructions安装v1.9.5

这是一个基本解决方案:

set.seed(1)
candidate<-c('bob jones', 'bobby jones', 'sara jones', 'sara norah', 'nora jones', 'other name', 'name other', 'thomas name', 'name judge', 'my mayor', 'peter peter', 'paul paul')
party<-rep(c('A', 'B', 'C'), 4)
district<-c(rep('District 1', 3), rep('District 2', 3), rep('District 3', 3), rep('Disctrict 4', 3))
province<-c(rep('Province 1', 3), rep('Province 2', 3), rep('Province 3', 3), rep('Province 4', 3))
votes<-round(rnorm(12, mean=5000, sd=1000),0)
percent<-round(rnorm(12, mean=37, sd=10),2)
df<-data.frame(party, district,province, votes, percent, candidate)


reshape(df, direction = 'wide', times = c('votes','percent'),
        idvar = c('province', 'district'), 
        timevar = 'party', drop = 'candidate')

#       district   province votes.A percent.A votes.B percent.B votes.C percent.C
# 1   District 1 Province 1    4374     30.79    5184     14.85    4164     48.25
# 4   District 2 Province 2    6595     36.55    5330     36.84    4180     46.44
# 7   District 3 Province 3    5487     45.21    5738     42.94    5576     46.19
# 10 Disctrict 4 Province 4    4695     44.82    6512     37.75    5390     17.11