在 ggplot2 的同一列中绘制 x 和 y 值

Question

我希望为每个患者创建一个包含一系列的散点/线图，其中 x/y 对源自该患者列的数据。数据的小样本如下所示：

Patient ID             1        2
Controll_Percent_1     0.000    0.000
Controll_Percent_2     0.035    0.000
Controll_Percent_3     0.035    0.039
Controll_Percent_4     0.053    0.053
Controll_Percent_5     0.088    0.066
Controll_Percent_6     0.088    0.066
Controll_Percent_7     0.105    0.092
Controll_Percent_8     0.123    0.171
Controll_Percent_9     0.158    0.263
Controll_Percent_10    0.158    0.224
Controll_Percent_11    0.197
Controll_Percent_12    0.211
Controll_Percent_13    0.276
Controll_Percent_14     
Controll_Percent_15     
Controll_Percent_16     
Controll_Percent_17     
Controll_Days_1        33        32
Controll_Days_2        378       128
Controll_Days_3        575       502
Controll_Days_4        951       633
Controll_Days_5        1127      800
Controll_Days_6        1324      853
Controll_Days_7        1512      999
Controll_Days_8        1887      1122
Controll_Days_9        2141      1312
Controll_Days_10       2331      1467
Controll_Days_11       1657
Controll_Days_12       2022
Controll_Days_13       2393
Controll_Days_14        
Controll_Days_15        
Controll_Days_16        

每个“Controll_Percent”与“Controll_days”配对，描述操作后x天后y的结果。通过在散点图中手动定义每个 x 和 y 系列，可以在 Excel 中轻松实现这一点。

如何在 R 或 ggplot2 中实现这一点？

Answer 1

我了解您希望在 x 轴上显示天数，在 y 轴上显示百分比，并为每个患者单独绘制一条线。这是一种方法。我存储了中间结果，以便更容易理解数据整理过程。

library(tidyverse)
DF <- read_csv("~/R/Play/Dummy.csv")
#> Warning: One or more parsing issues, call `problems()` on your data frame for details,
#> e.g.:
#>   dat <- vroom(...)
#>   problems(dat)
#> Rows: 32 Columns: 3
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (1): Patient_ID
#> dbl (2): 1, 2
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

DF2 <- DF |>  rename("P1" = `1`, "P2" = `2`) |> filter(!is.na(P1) | !is.na(P2)) 
DF3 <- DF2 |> pivot_longer(cols = c("P1","P2"),names_to = "Patient")
DF4 <- DF3 |> separate("Patient_ID", into = c("Control", "Measure", "Index"))
DF5 <- DF4 |> pivot_wider(names_from = "Measure", values_from = "value" )
DF5
#> # A tibble: 26 × 5
#>    Control  Index Patient Percent  Days
#>    <chr>    <chr> <chr>     <dbl> <dbl>
#>  1 Controll 1     P1        0        33
#>  2 Controll 1     P2        0        32
#>  3 Controll 2     P1        0.035   378
#>  4 Controll 2     P2        0       128
#>  5 Controll 3     P1        0.035   575
#>  6 Controll 3     P2        0.039   502
#>  7 Controll 4     P1        0.053   951
#>  8 Controll 4     P2        0.053   633
#>  9 Controll 5     P1        0.088  1127
#> 10 Controll 5     P2        0.066   800
#> # ℹ 16 more rows
ggplot(DF5, aes(x = Days, y = Percent, color = Patient, group = Patient)) + 
  geom_line() +geom_point()
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_line()`).
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_point()`).

^{创建于 2024 年 10 月 26 日，使用 reprex v2.1.1}