R组加权数据组频率表

Question

我想用加权数据组来计算两种频率表。

您可以用下面的代码生成可再生的数据：

Data <- data.frame(
    country = sample(c("France", "USA", "UK"), 100, replace = TRUE), 
    migrant = sample(c("Native", "Foreign-born"), 100, replace = TRUE), 
    gender = sample (c("men", "women"), 100, replace = TRUE), 
    wgt = sample(100), 
    year = sample(2006:2007) 
    ) 

首先，我试图计算的移民身份的频率表（本机VS外国出生）的国家和年份。我写了使用包questionr和plyr下面的代码：

db2006 <- subset (Data, year == 2006) 
db2007 <- subset (Data, year == 2007) 

result2006 <- as.data.frame(cprop(wtd.table(db2006$migrant, db2006$country, weights=db2006$wgt),total=FALSE)) 
result2007 <- as.data.frame(cprop(wtd.table(db2007$migrant, db2007$country, weights=db2007$wgt),total=FALSE)) 

result2006<-rename (result2006, c(Freq = "y2006")) 
result2007<-rename (result2007, c(Freq = "y2007")) 

result <- merge(result2006, result2007, by = c("Var1","Var2")) 

在我真正的数据库，我有10个年，所以它需要时间来应用此代码对所有年。有没有人知道更快的方法来做到这一点？

我也希望计算按国家和年份计算的移民身份中男女比例。我正在寻找类似的东西：

Var1   Var2  Var3  y2006 y2007 
Foreign born France men  52  55 
Foreign born France women  48  45 
Native   France men  51  52 
Native   France women  49  48 
Foreign born UK  men  60  65 
Foreign born UK  women  40  35 
Native   UK  men  48  50 
Native   UK  women  52  50 

有没有人有我如何得到这些结果的想法？

Answer 1

您可以通过以下操作来完成此操作：使用您已写入的代码创建函数;使用lapply在数据中遍历所有年份的函数;然后使用Reduce和merge将结果列表折叠为一个数据帧。像这样：

# let's make your code into a function called 'tallyho' 
tallyho <- function(yr, data) { 

    require(dplyr) 
    require(questionr) 

    DF <- filter(data, year == yr) 

    result <- with(DF, as.data.frame(cprop(wtd.table(migrant, country, weights = wgt), total = FALSE))) 

    # rename the last column by year 
    names(result)[length(names(result))] <- sprintf("y%s", year) 

    return(result) 

} 

# now iterate that function over all years in your original data set, then 
# use Reduce and merge to collapse the resulting list into a data frame 
NewData <- lapply(unique(Data$year), function(x) tallyho(x, Data)) %>% 
    Reduce(function(...) merge(..., all=T), .)