R如何绘制多个图形(时间序列)

时间:2019-10-28 00:16:01

标签: r plot time-series smoothing

我有一个数据框df

ID      Final_score appScore pred_conf pred_chall obs1_conf obs1_chall obs2_conf obs2_chall exp1_conf exp1_chall
3079341 4           low      6         1          4         3           4        4          6         2 
3108080 8           high     6         1          6         1           6        1          6         2 
3130832 9           high     2         6          3         4           5        4          6         2 
3148118 10          high     4         4          4         4           5        4          6         2 
3148914 10          high     2         2          2         5           2        5          6         2 
3149040 2           low      5         4          6         4           6        4          6         4 

Q1:我想为highlow功能的appScore _conf_chall有两个覆盖图。我想用不同的颜色显示这些图。我该如何实现?

Q2:是否可以绘制两个平滑图,一个用于所有_conf变量/特征,另一个用于所有_chall特征。 请注意,我的列没有时间变量,而是按以下顺序排序:

pred_conf  --> obs1_conf  --> obs2_conf  --> exp1_conf
pred_chall --> obs1_chall --> obs2_chall --> exp1_chall

这只是一个玩具示例,实际数据有多行多列。作为参考,我在下面共享了dput():

dput(df)
structure(list(ID = c(3079341L, 3108080L, 3130832L, 3148118L, 3148914L, 3149040L), 
Final_score = c(4L, 8L, 9L, 10L, 10L, 2L), 
appScore = structure(c(2L, 1L, 1L, 1L, 1L, 2L), .Label = c("high", "low"), class = "factor"), 
pred_conf = c(6L, 6L, 2L, 4L, 2L, 5L), 
pred_chall = c(1L, 1L, 6L, 4L, 2L, 4L), 
obs1_conf = c(4L, 6L, 3L, 4L, 2L, 6L), 
obs1_chall = c(3L, 1L, 4L, 4L, 5L, 4L), 
obs2_conf = c(4L, 6L, 5L, 5L, 2L, 6L), 
obs2_chall = c(4L, 1L, 4L, 4L, 5L, 4L), 
exp1_conf = c(6L, 6L, 6L, 6L, 6L, 6L), 
exp1_chall = c(2L, 2L, 2L, 2L, 2L, 4L)), 
class = "data.frame", row.names = c(NA, -6L))

以下帖子很有帮助,但考虑了时间变量。我应该如何使用某种时间变量来更改任务名称?

Plotting multiple time-series in ggplot

Multiple time series in one plot

更新1:

_confhigh appScore组的low绘制时,我的图形当前看起来像这样。我想对这些图形进行平滑和叠加,以查看是否存在任何差异或模式。

这是我使用的代码

library(ggplot2)
df_long %>% 
  filter(part == "conf") %>% 
  ggplot(aes(feature, val, group = appScore)) +
  geom_line() +
  geom_point() +
  facet_wrap(~appScore, ncol = 1) +
  ggtitle("conf")

_conf graphs for high and low achievers

更新2:

使用脚本:

test_long %>% 
  ggplot(aes(feature, val, color = appScore, group = appScore)) + #, size = Final_score)) +
  geom_smooth() +
  facet_wrap(~part, nrow = 1) +
  ggtitle("conf and chall")

我已经能够生成所需的图形:

High and low achievers, conf and chall overlay smoothed graph

1 个答案:

答案 0 :(得分:1)

首先,我将数据转换为长格式。

library(tidyr)
library(dplyr)

df_long <- 
  df %>% 
  pivot_longer(
    cols = matches("(conf|chall)$"),
    names_to = "var",
    values_to = "val"
  )

df_long

#> # A tibble: 48 x 5
#>         ID Final_score appScore var          val
#>      <int>       <int> <fct>    <chr>      <int>
#>  1 3079341           4 low      pred_conf      6
#>  2 3079341           4 low      pred_chall     1
#>  3 3079341           4 low      obs1_conf      4
#>  4 3079341           4 low      obs1_chall     3
#>  5 3079341           4 low      obs2_conf      4
#>  6 3079341           4 low      obs2_chall     4
#>  7 3079341           4 low      exp1_conf      6
#>  8 3079341           4 low      exp1_chall     2
#>  9 3108080           8 high     pred_conf      6
#> 10 3108080           8 high     pred_chall     1
#> # … with 38 more rows

df_long <-
  df_long %>% 
  separate(var, into = c("feature", "part"), sep = "_") %>% 
  # to ensure the right order
  mutate(feature = factor(feature, levels = c("pred", "obs1", "obs2", "exp1"))) %>% 
  mutate(ID = factor(ID))

df_long
#> # A tibble: 48 x 6
#>    ID      Final_score appScore feature part    val
#>    <fct>         <int> <fct>    <fct>   <chr> <int>
#>  1 3079341           4 low      pred    conf      6
#>  2 3079341           4 low      pred    chall     1
#>  3 3079341           4 low      obs1    conf      4
#>  4 3079341           4 low      obs1    chall     3
#>  5 3079341           4 low      obs2    conf      4
#>  6 3079341           4 low      obs2    chall     4
#>  7 3079341           4 low      exp1    conf      6
#>  8 3079341           4 low      exp1    chall     2
#>  9 3108080           8 high     pred    conf      6
#> 10 3108080           8 high     pred    chall     1
#> # … with 38 more rows

现在绘制很容易。要绘制"conf"功能,例如:

library(ggplot2)
df_long %>% 
  filter(part == "conf") %>% 
  ggplot(aes(feature, val, group = ID, color = ID)) +
  geom_line() +
  geom_point() +
  facet_wrap(~appScore, ncol = 1) +
  ggtitle("conf")

enter image description here