每个值每年的百分比

Question

我的数据

Chemical  date      concentration  limit
A     01-01-2016     0.2         0.01
A     01-02-2016     0.2         0.01
A     01-01-2017     0.005       0.01
A     01-02-2017     0.2         0.01
B     01-01-2016     0.3         0.1
B     01-02-2016     0.05        0.1
B     01-01-2017     0.2         0.1
B     01-02-2017     0.2         0.1
C     01-01-2016     1.2         1
C     01-02-2016     0.8         1
C     01-01-2017     0.9         1
C     01-02-2017     0.9         1

我想显示每年超过限值的每种化学品的百分比（注意每个限值都不同）。所以我想得到这样的东西

Year   A         B     C
2016   100%     50%   50%
2017   50%      100%   0

我已经有了计算每种化学物质每年超过次数的代码，但是在计算百分比时我弄错了。

这个我得算次数了

  library(tidyverse)
   counts<- data %>% 
   group_by(Chemical, grp = format(date, format = '%Y')) %>% 
   mutate(exceed = concentration >= limit) %>% # TRUE/FALSE
   summarise(tot_exceed = sum(exceed)) %>%  # count each T/F
   spread(Chemical, tot_exceed, fill = 0)

所以我明白了

   Year   A     B    C
   2016   2     1    1
   2017   1     2    0

对于百分比，我试过了。

percentage_exceed<- data %>% 
group_by(Chemical, grp = format(date, format = '%Y')) %>% 
mutate(exceed = concentration >= limit, countconc = length(concentration)) 
%>% 
summarise(percent = (sum(exceed)/countconc)*100) %>% 
spread(Chemical, percent, fill = 0)

但是我没有得到我想要的结果。你能帮帮我吗？

Answer 1

与tidyverse:

library(tidyverse)
library(lubridate)

 data  %>% 
   mutate(yr=mdy(date) %>% year) %>% 
   group_by(Chemical,yr) %>% 
   mutate(exceed  = ifelse(concentration>=limit,1,0  )) %>% 
   summarise(tot_exceed =sum(exceed)) %>% 
   group_by(Chemical) %>% 
   mutate(proc=tot_exceed/max(tot_exceed)*100) %>% 
   select(-tot_exceed) %>% 
   spread(Chemical,proc)
# A tibble: 2 x 4
     yr     A     B     C
  <dbl> <dbl> <dbl> <dbl>
1  2016   100    50   100
2  2017    50   100     0

Answer 2

dt = read.table(text = "
Chemical  date      concentration  limit
A     01-01-2016     0.2         0.01
A     01-02-2016     0.2         0.01
A     01-01-2017     0.005       0.01
A     01-02-2017     0.2         0.01
B     01-01-2016     0.3         0.1
B     01-02-2016     0.05        0.1
B     01-01-2017     0.2         0.1
B     01-02-2017     0.2         0.1
C     01-01-2016     1.2         1
C     01-02-2016     0.8         1
C     01-01-2017     0.9         1
C     01-02-2017     0.9         1
", header=T)

library(tidyverse)
library(lubridate)

dt %>%
  mutate(year = year(dmy(date))) %>%
  group_by(year, Chemical) %>%
  summarise(Total = n(),
            Num_exceed = sum(concentration >= limit)) %>%
  ungroup() %>%
  mutate(Prc = paste0(Num_exceed / Total * 100,"%")) %>%
  select(year, Chemical, Prc) %>%
  spread(Chemical, Prc)

# # A tibble: 2 x 4
#    year A     B     C    
#   <dbl> <chr> <chr> <chr>
# 1  2016 100%  50%   50%  
# 2  2017 50%   100%  0%

Answer 3

你的方法非常好，你只需要用mean替换sum并乘以100：

data %>% group_by(Chemical, grp = format(date, format = '%Y')) %>% 
  mutate(exceed = concentration >= limit) %>% 
  summarise(tot_exceed = mean(exceed) * 100) %>%
  spread(Chemical, tot_exceed, fill = 0)
# A tibble: 2 x 4
#   grp       A     B     C
#   <chr> <dbl> <dbl> <dbl>
# 1 2016    100    50    50
# 2 2017     50   100     0

您尝试的线路

summarise(percent = (sum(exceed)/countconc) * 100)

几乎做到了这一点：错误是关于 countconc 是整个列而不是单个值（汇总所需）这一事实。因此，由于无论如何它在每个组中都是 constant 列，因此您可以编写，例如，

summarise(percent = (sum(exceed)/countconc[1]) * 100)

但是考虑到之前的那一行，

mutate(exceed = concentration >= limit, countconc = length(concentration))

归根结底只是一个意思，所以我们回到我回答开头的代码。

另请注意，使用 lubridate 您可以将第一行写为

data %>% group_by(Chemical, Year = year(date)) %>%

一些非常简洁但可能不是您想要的格式

data %>% group_by(Chemical, Year = year(date)) %>% 
  summarise(Percentage = mean(concentration > limit) * 100)
# A tibble: 6 x 3
# Groups:   Chemical [?]
#   Chemical  Year Percentage
#   <fct>    <dbl>      <dbl>
# 1 A         2016        100
# 2 A         2017         50
# 3 B         2016         50
# 4 B         2017        100
# 5 C         2016         50
# 6 C         2017          0

Answer 4

使用 tidyverse 和 reshape2 你可以：

df %>%
 mutate(date = str_sub(as.character(date), 7, 10)) %>% #Taking out the year from "date"
 group_by(date, Chemical) %>% #Group by "date" and "Chemical"
 summarise(temp = length(concentration[concentration > limit])/n()*100) %>% #Applying the condition
 dcast(date~Chemical, value.var = "temp") #Reshaping the data

  date   A   B  C
1 2016 100  50 50
2 2017  50 100  0

或者仅 tidyverse 使用 spread()

df %>%
 mutate(date = str_sub(as.character(date), 7, 10)) %>% #Taking out the year from "date"
 group_by(date, Chemical) %>% #Group by "date" and "Chemical"
 summarise(temp = length(concentration[concentration > limit])/n()*100) %>% #Applying the condition
 spread(Chemical, temp, fill = 0) #Reshaping the data

每个值每年的百分比

Percentages per year per value

r

count

percentage