R按組之一重新排序ggplot

以下資料有兩組診斷和預期。我正在創建一個克利夫蘭點圖來比較診斷值與預期值。我想重新排序繪圖以根據診斷率降序顯示概念名稱，這就是我設定資料集的方式。

                                      concept_name rate       grp
1                                 Disorder of bone 0.28 Diagnosed
2                                          Fatigue 0.28 Diagnosed
3                                    Low back pain 0.28 Diagnosed
4  Abnormal findings on diagnostic imaging of lung 0.29 Diagnosed
5                                           Anemia 0.34 Diagnosed
6                 Raised prostate specific antigen 0.53 Diagnosed
7             Secondary malignant neoplasm of bone 0.58 Diagnosed
8                                   Hyperlipidemia 0.59 Diagnosed
9                           Essential hypertension 0.76 Diagnosed
10          Primary malignant neoplasm of prostate 0.97 Diagnosed
11            Secondary malignant neoplasm of bone 0.01  Expected
12                                Disorder of bone 0.06  Expected
13          Primary malignant neoplasm of prostate 0.11  Expected
14                Raised prostate specific antigen 0.13  Expected
15 Abnormal findings on diagnostic imaging of lung 0.15  Expected
16                                         Fatigue 0.19  Expected
17                                          Anemia 0.20  Expected
18                                   Low back pain 0.25  Expected
19                                  Hyperlipidemia 0.60  Expected
20                          Essential hypertension 0.74  Expected



 p <-  ggplot(df, aes(rate, concept_name))  
  geom_line(aes(group = concept_name))  
  geom_point(aes(color = grp) )  
  theme_bw()   theme (legend.title=element_blank())

該圖不遵循資料集的順序。我希望看到概念名稱 - 骨骼疾病，疲勞，腰痛..

資料

    structure(list(concept_name = structure(c(3L, 5L, 7L, 1L, 2L, 
9L, 10L, 6L, 4L, 8L, 10L, 3L, 8L, 9L, 1L, 5L, 2L, 7L, 6L, 4L), .Label = c("Abnormal findings on diagnostic imaging of lung", 
"Anemia", "Disorder of bone", "Essential hypertension", "Fatigue", 
"Hyperlipidemia", "Low back pain", "Primary malignant neoplasm of prostate", 
"Raised prostate specific antigen", "Secondary malignant neoplasm of bone"
), class = "factor", scores = structure(c(`Abnormal findings on diagnostic imaging of lung` = NA_real_, 
Anemia = NA_real_, `Disorder of bone` = NA_real_, `Essential hypertension` = NA_real_, 
Fatigue = NA_real_, Hyperlipidemia = NA_real_, `Low back pain` = NA_real_, 
`Primary malignant neoplasm of prostate` = NA_real_, `Raised prostate specific antigen` = NA_real_, 
`Secondary malignant neoplasm of bone` = NA_real_), .Dim = 10L, .Dimnames = list(
    c("Abnormal findings on diagnostic imaging of lung", "Anemia", 
    "Disorder of bone", "Essential hypertension", "Fatigue", 
    "Hyperlipidemia", "Low back pain", "Primary malignant neoplasm of prostate", 
    "Raised prostate specific antigen", "Secondary malignant neoplasm of bone"
    )))), rate = c(0.28, 0.28, 0.28, 0.29, 0.34, 0.53, 0.58, 
0.59, 0.76, 0.97, 0.01, 0.06, 0.11, 0.13, 0.15, 0.19, 0.2, 0.25, 
0.6, 0.74), grp = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Diagnosed", 
"Expected"), class = "factor")), class = "data.frame", row.names = c(NA, 
-20L))

uj5u.com熱心網友回復：

您可以使用fct_inorder來自forcats：

library(tidyverse)

ggplot(df, aes(rate, fct_inorder(concept_name)))  
  geom_line(aes(group = concept_name))  
  geom_point(aes(color = grp))  
  theme_bw()  
  theme (legend.title = element_blank())

或者，如果您想要從 y 軸頂部開始排序，那么我們可以先arrange獲取資料，然后使用fct_inorder：

df %>%
  arrange(grp, desc(rate), desc(concept_name)) %>%
  ggplot(aes(rate, fct_inorder(concept_name)))  
  geom_line(aes(group = concept_name))  
  geom_point(aes(color = grp))  
  theme_bw()  
  theme (legend.title = element_blank())

標籤：r 排序 ggplot2 团体

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