Function r conditional-statements dataframe

如何根据每行的3个观察结果返回真或错误？

发布于 2025-02-13 16:30:04 字数 1153 浏览 0 评论 0原文

看起来像这样

ID	抗原	浓度
C001	A1	0.291259335
C001	A2	0.580050639
C001	A3	0.002235505
C001	A4	0.848792002
C002	C002	我
数据	C002	的
有一个	A1	C002
：	集	0.194151877
C003	A1	0.0142237
C003	A2 A2	0.027409926
C003	A3 A3 A3	0.000117995
C003	A4	0.042202259

每个参与者具有4个与IT相关的抗原，并且每个抗原的平均浓度在每个抗原中都在每个特定的范围内，这是不同的，这是每个抗原的范围都在每个范围内，这是属于每个抗原的量。

我正在尝试创建一个函数，其中每个参与者 - 抗原浓度组合都会检查，并在新列中返回一个真/错误。例如，如果参与者= C001，抗原= A1，浓度在0.77至1.43之间，则返回true。如果对于参与者和抗原的任何组合，浓度不超出范围，请返回错误。

我尝试使用循环，如果其他功能和其他效率低下的方式，但效果不足。我认为我不会尽我所能地接近这一点，因此，如果有人可以将我指向任何有用的功能或文档的方向，我将非常感激。

先感谢您！

原文

I have a dataset that looks like this:

ID	antigen	concentration
C001	a1	0.291259335
C001	a2	0.580050639
C001	a3	0.002235505
C001	a4	0.848792002
C002	a1	0.066808174
C002	a2	0.130661773
C002	a3	0.000530089
C002	a4	0.194151877
C003	a1	0.0142237
C003	a2	0.027409926
C003	a3	0.000117995
C003	a4	0.042202259

Each participant has 4 antigens associated with it, and the mean concentration for each antigen has to fall within a specific range, which is different for each antigen.

I'm trying to create a function where each participant-antigen-concentration combination is checked and a TRUE/FALSE is returned in a new column. For example if Participant = C001, antigen = a1, and Concentration is between 0.77 and 1.43, return TRUE. If for any combination of participant and antigen the concentration is out of range, return FALSE.

I've tried using for loops, if else functions and other inefficient ways but have come up short. I don't think I'm approaching this in as logical way as I should so if anyone could point me in the direction of any useful functions or documentation for this kind of problem I'd be very grateful.

Thank you in advance!

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恰似旧人归 2025-02-20 16:30:04

您可以使用case_when：

df <- tibble(ID = c("C001", "C001", "C002", "C002"),
             antigen = c("a1", "a2", "a1", "a2"),
             concentration = c(0.291259335, 0.580050639, 0.066808174, 0.130661773))
      
library(tidyverse)
       
df |>
  mutate(within_range = case_when(antigen == "a1" & between(concentration, 0.77, 1.43) ~ TRUE,
                                  antigen == "a2" & between(concentration, 0.1, 0.5) ~ TRUE,
                                  TRUE ~ FALSE)
         )

输出：

# A tibble: 4 × 4
  ID    antigen concentration within_range
  <chr> <chr>           <dbl> <lgl>       
1 C001  a1             0.291  FALSE       
2 C001  a2             0.580  FALSE       
3 C002  a1             0.0668 FALSE       
4 C002  a2             0.131  TRUE

You could use case_when:

df <- tibble(ID = c("C001", "C001", "C002", "C002"),
             antigen = c("a1", "a2", "a1", "a2"),
             concentration = c(0.291259335, 0.580050639, 0.066808174, 0.130661773))
      
library(tidyverse)
       
df |>
  mutate(within_range = case_when(antigen == "a1" & between(concentration, 0.77, 1.43) ~ TRUE,
                                  antigen == "a2" & between(concentration, 0.1, 0.5) ~ TRUE,
                                  TRUE ~ FALSE)
         )

Output:

# A tibble: 4 × 4
  ID    antigen concentration within_range
  <chr> <chr>           <dbl> <lgl>       
1 C001  a1             0.291  FALSE       
2 C001  a2             0.580  FALSE       
3 C002  a1             0.0668 FALSE       
4 C002  a2             0.131  TRUE

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