data.frame子集长格式

发布于 2024-08-04 19:25:37 字数 373 浏览 0 评论 0原文

我想这个问题会有一个非常简单的答案。但就这样吧。

长格式数据。像这样

d <- data.frame(cbind(numbers = rnorm(10), 
                         year = rep(c(2008, 2009), 5), 
                         name = c("john", "David", "Tom", "Kristin", "Lisa","Eve","David","Tom","Kristin","Lisa")))

我如何获得一个仅包含 2008 年和 2009 年出现的名称行的新数据框？（即只有大卫、克里斯汀、丽莎和汤姆）。

提前致谢

原文

I guess there will be a very simple answer to this. But here goes.

Data in long format. like this

d <- data.frame(cbind(numbers = rnorm(10), 
                         year = rep(c(2008, 2009), 5), 
                         name = c("john", "David", "Tom", "Kristin", "Lisa","Eve","David","Tom","Kristin","Lisa")))

How do I get a new dataframe only with rows for names that occur in both 2008 and 2009? (i.e. with only David, Kristin, Lisa and Tom).

Thanks in advance

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榕城若虚 2024-08-11 19:25:37

简单的方法：

subset(
    d,
    name %in% intersect(name[year==2008], name[year==2009])
)

Simple way:

subset(
    d,
    name %in% intersect(name[year==2008], name[year==2009])
)

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爱的故事 2024-08-11 19:25:37

一种方法是使用 reshape 包创建一个 data.frame，其中列中包含年份，行中包含名称：

library(reshape)
cast(d, name ~ year, value = "numbers")

然后您可以使用 complete.cases 提取感兴趣的行。

One approach is to use the reshape package to create a data.frame with years in columns and names in rows:

library(reshape)
cast(d, name ~ year, value = "numbers")

You could then use complete.cases to extract the rows of interest.

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听闻余生 2024-08-11 19:25:37

如果一年只有一条记录，只需统计每个人在数据集中出现的次数：

counts <- as.data.frame(table(name = d$name))

然后查找出现两次的每个人：

subset(counts, Freq == 2)

If there is only one record per year, just count up the number of times each person appears in the dataset:

counts <- as.data.frame(table(name = d$name))

Then look for everyone who appeared twice:

subset(counts, Freq == 2)

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仙女 2024-08-11 19:25:37

这是另一个仅使用基本 R 的解决方案，并且不对一个人每年拥有的记录数做出任何假设：

d <- data.frame(cbind(numbers = rnorm(10), 
                      year = rep(c(2008, 2009), 5),
                      name = c("john", "David", "Tom", "Kristin",
                               "Lisa","Eve","David","Tom","Kristin",
                               "Lisa")))
# split data into 2 data.frames (1 for each year)
by.year <- split(d, d$year, drop=T)

# find the names that appear in both years
keep <- intersect(by.year[['2008']]$name, by.year[['2009']]$name)
# Or, if you had several years, use Reduce as a more general solution:
keep <- Reduce(intersect, lapply(by.year, '[[', 'name'))

# show the rows of the original dataset only if their $name field
# is in our 'keep' vector
d[d$name %in% keep,]

Here's another solution that uses just base R and doesn't make any assumptions about the number of records a person has per year:

d <- data.frame(cbind(numbers = rnorm(10), 
                      year = rep(c(2008, 2009), 5),
                      name = c("john", "David", "Tom", "Kristin",
                               "Lisa","Eve","David","Tom","Kristin",
                               "Lisa")))
# split data into 2 data.frames (1 for each year)
by.year <- split(d, d$year, drop=T)

# find the names that appear in both years
keep <- intersect(by.year[['2008']]$name, by.year[['2009']]$name)
# Or, if you had several years, use Reduce as a more general solution:
keep <- Reduce(intersect, lapply(by.year, '[[', 'name'))

# show the rows of the original dataset only if their $name field
# is in our 'keep' vector
d[d$name %in% keep,]

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