[英]Count number of times a value occurs within a group R
我的數據樣本如下:
id = c(1, 2, 3, 4, 5, 1, 4, 7, 8, 3)
date = c("2020-12-31", "2020-12-31", "2020-12-31", "2020-12-31",
"2020-12-31", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
"01-01-2021")
total = c(1, 4, 4, 15, 0, 12, 1, 1, 1, 0)
data = data.frame(id, date, total)
我試圖計算每個日期出現“總”值的次數。 因此,例如,對於日期"2020-12-31"
,值4
出現兩次,但值1
只出現一次,因為它在該日期出現15
和0
。 然后對於日期"01-01-2021"
,值1
出現 3 次,依此類推。 本質上,我希望 out 導致:
day = c("2020-12-31", "01-01-2021")
one = c(1, 3)
two = c(0, 0)
three = c(0, 0)
four = c(2, 0)
five = c( 0, 0)
six = c(0, 0)
seven = c(0,0)
eight = c(0, 0)
nine = c(0,0)
ten = c(0,0)
eleven = c(0,0)
twelve = c(0,1)
thirteen = c(0,0)
fourteen = c(0,0)
fifteen = c(1,0)
df = data.frame(day, one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen,
fourteen, fifteen)
所以一列代表日期,接下來的 15 列代表我正在計算的數字。 (我的數據還有更多日期,我只是沒有把它們都放在我的例子中)
我首先按以下方式對原始列進行分組:
data %>%
group_by(date, total)
但我不確定如何計算每組的值並將其放入生成的 dataframe 中。 謝謝!
library(tidyr)
library(dplyr)
data %>%
count(date, total) %>%
complete(date, total = 0:15, fill = list(n = 0)) %>%
pivot_wider(id_cols = date, names_from = total, values_from = n, names_prefix = "total")
# # A tibble: 2 × 17
# date total0 total1 total2 total3 total4 total5 total6 total7 total8 total9 total10 total11 total12
# <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 01-01… 1 3 0 0 0 0 0 0 0 0 0 0 1
# 2 2020-… 1 1 0 0 2 0 0 0 0 0 0 0 0
# # … with 3 more variables: total13 <dbl>, total14 <dbl>, total15 <dbl>
`as.data.frame.table 是歷史悠久的方法:
as.data.frame( with(data, table(date, total)))
#------------------------
date total Freq
1 01-01-2021 0 1
2 2020-12-31 0 1
3 01-01-2021 1 3
4 2020-12-31 1 1
5 01-01-2021 4 0
6 2020-12-31 4 2
7 01-01-2021 12 1
8 2020-12-31 12 0
9 01-01-2021 15 0
10 2020-12-31 15 1
如果您希望它采用“寬”格式,這確實是 ab*tch 可以使用,然后將其保留為 tble:
with(data, table(date, total))
total
date 0 1 4 12 15
01-01-2021 1 3 0 1 0
2020-12-31 1 1 2 0 1
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