标签: boxplot

我想做一些非常简单的事情:我想为一个完整的数据帧创建一个 boxplot.然而,搜索"组合箱图"和相关术语并没有提出任何建议.如果我忽略了一种显而易见的方式,请告诉我.

我有以下数据:

> theData
     X20.7    X21.7    X22.7    X23.7    X24.7    X25.7    X26.7    X27.7    X28.7    X29.7    X30.7    X31.7    X32.7    X33.7    X34.7    X35.7
1 99.64920 99.49319 99.49319 99.49319 99.49319 99.49319 99.80837 99.29348 99.29348 99.29348 99.29348 99.29348 99.29348 99.46376 99.46376 99.51554
2 98.76469 98.60867 98.60867 98.60867 98.60867 98.60867 99.41553 98.40896 98.40896 98.40896 98.40896 98.40896 98.40896 98.74975 98.74975 98.54527
3 98.37824 98.22222 98.22222 98.22222 98.22222 98.22222 98.70900 98.13767 98.13767 98.13767 98.13767 98.13767 98.13767 98.47846 98.47846 98.01791
4 98.11356 97.95754 97.95754 97.95754 97.95754 97.95754 …

我需要从具有三个数字列的data.frame创建一个箱形图，并使用split参数通过paint分隔这些框。我有一个很大的data.frame，但是我需要的是下面的示例：

paint<-c("blue", "black", "red", "blue", "black", "red", "blue", "black", "red")
car1<-c(100, 138, 123, 143, 112, 144, 343, 112, 334)
car2<-c(111, 238, 323, 541, 328, 363, 411, 238, 313)
car3<-c(432, 123, 322, 342, 323, 522, 334, 311, 452)
data<-data.frame(paint, car1, car2, car3)

>data
      paint  car1 car2 car3
   1  blue   100  111  432
   2  black  138  238  123
   3  red    123  323  322
   4  blue   143  541  342
   5  black  112  328  323
   6  red    144 …

我试图使用MATLAB从箱线图中识别异常值.该函数的默认晶须值为1.5,提供+ - 2.7*sigma或99.3覆盖率.但是,我想要99.7或3*sigma覆盖.在这种情况下,晶须的价值是什么？我不想随意猜测,所以需要你们的帮助.谢谢

我有一个pandas数据框,如下所示:

[('1975801_m', 1      0.203244
10    -0.159756
16    -0.172756
19    -0.089756
20    -0.033756
23    -0.011756
24     0.177244
32     0.138244
35    -0.104756
36     0.157244
40     0.108244
41     0.032244
42     0.063244
45     0.362244
59    -0.093756
62    -0.070756
65    -0.030756
66    -0.100756
73    -0.140756
77    -0.110756
81    -0.100756
84    -0.090756
86    -0.180756
87     0.119244
88     0.709244
102   -0.030756
105   -0.000756
107   -0.010756
109    0.039244
111    0.059244
Name: RTdiff), ('3878418_m', 1637    0.13811
1638   -0.21489
1644   -0.15989
1657   -0.11189
1662   -0.03289
1666   -0.09489
1669    0.03411
1675 …

Box和Whisker图表显示以下信息:max,min,mean,75th百分位数,第25百分位数.如果我有这些信息,我可以绘制相应的B&W图吗？

我有这个名为TP.df的数据框:

        pb1    ag1     pb2     ag2     pb3    ag3
Nb      498    498      85      85      68     68
Min       0      0       0       0       0      0
Max    1.72    461   2.641   260.8     0.3    144
Mean   0.06   19.2    0.15   35.35    0.02   9.11
75_p   0.06     20    0.08      33    0.02      8
25_p   0.01     10       0      14    0.01      4

文件:

,pb1,ag1,pb2,ag2,pb3,ag3
Nb,498,498,85,85,68,68
Min,0,0,0,0,0,0
Max,1.72,461,2.641,260.8,0.3,144
Mean,0.06,19.2,0.15,35.35,0.02,9.11
75_p,0.06,20,0.08,33,0.02,8
25_p,0.01,10,0,14,0.01,4

如何获得相应的Box和Whisker图:

• 它必须显示6盒
• x轴:pb1,ag1,pb2,ag2,pb3,ag3
• y轴:0到max(TP.df[Max,])

我可以做到这一点而没有问题：

boxplot(coef ~ habitat, data = res)
abline(h = 0, col = "green")

但是当我使用点阵时，水平线放错了位置：

bwplot(coef ~ habitat, data = res)
abline(h = 0, col = "green")

我尝试使用它panel.abline代替，但是将绿线放在图片的顶部。

我有一个如下所示的数据框:

> head(DOData)
    Date        Site1 Site2  Site3   Site4  Site5  Months
1   1/1/2012    1.07  3.32   11.35   6.26   5.39   January
2   1/2/2012    1.24  3.08   10.69   6.57   6.59   January
3   1/3/2012    1.94  2.69   11.86   6.23   6.23   January
4   1/4/2012    0.81  3.50   11.47   4.67   5.94   January
5   1/5/2012    1.41  3.11   10.38   7.44   5.40   January
6   1/6/2012    2.73  3.28   11.11   6.15   6.22   January
.
.
.
361 12/26/2012  3.54  3.86   12.67   5.44   6.03   December
362 12/27/2012  2.05  3.42   10.27   6.05   7.10   December
363 12/28/2012  3.59 …

我试图在matplotlib中计算箱形图的胡须和框坐标.我不明白我的错误以及为什么我不计算相同的值.

Q1, median, Q3 = np.percentile(becher, [25, 50, 75])
IQR = Q3 - Q1
Qs = [Q1, median, Q3, Q1 - 1.5 * IQR, Q3 + 1.5 * IQR]
Qname = ["Q1", "median", "Q3", "Q1-1.5xIQR", "Q3+1.5xIQR"]
for Q, name in zip(Qs, Qname):
    plt.axhline(Q, color="k")
    plt.text(1.52, Q, name)
plt.boxplot(becher)

如下图所示,Q1,Q3和中位数都可以.但胡须是错的.

这是我的数据:

becher = [9.1495,
 9.9479,
 9.7933,
 9.8002,
 8.47,
 9.14,
 9.06,
 9.6933,
 9.7871,
 10.5676,
 9.7441,
 10.4874,
 7.9584,
 7.9598,
 8.3483,
 7.2536,
 9.0823,
 10.8343,
 10.4104,
 7.2004,
 9.6297,
 9.96,
 9.761,
 9.684,
 8.6062,
 10.2098,
 8.9002,
 8.4511, …

我正在研究一个带有预测和观测的箱线图,这是一个非常长的数据集.我在这里提供样本格式.

> forecasts <- data.frame(f_type = c(rep("A", 9), rep("B", 9)), 
                          Date = c(rep(as.Date("2007-01-31"),3), rep(as.Date("2007-02-28"), 3), rep(as.Date("2007-03-31"), 3), rep(as.Date("2007-01-31"), 3), rep(as.Date("2007-02-28"), 3), rep(as.Date("2007-03-31"), 3)), 
                          value = c(10, 50, 60, 05, 90, 20, 30, 46, 39, 69, 82, 48, 65, 99, 75, 15 ,49, 27))
> 
> observation <- data.frame(Dt = c(as.Date("2007-01-31"), as.Date("2007-02-28"), as.Date("2007-03-31")), 
                            obs = c(30,49,57))

到目前为止,我有:

ggplot() + 
    geom_boxplot(data = forecasts,
                 aes(x = as.factor(Date), y = value, 
                     group = interaction(Date, f_type), fill = f_type)) +  
    geom_line(data = observations,
              aes(x = …

我有一个tibble名为的数据框my_data,如下所示:

> my_data
# A tibble: 60 x 4
   SPECIES       simulation_id psi_hat p_hat
   <chr>                 <int>   <dbl> <dbl>
 1 Grey squirrel            74   0.527 0.306
 2 Grey squirrel           102   0.526 0.316
 3 Grey squirrel           142   0.527 0.309
 4 Grey squirrel           121   0.527 0.309
 5 Grey squirrel            25   0.526 0.317
 6 Grey squirrel            50   0.527 0.309
 7 Grey squirrel            67   0.491 0.326
 8 Grey squirrel            19   0.527 0.306
 9 Grey squirrel           174   0.527 0.302
10 Grey squirrel            46   0.527 …