[英]R how to plot multiple graphs (time-series)
我有一个 dataframe 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_conf
和low
_chall
high
叠加图。 我想让这些图表有不同的颜色。 我怎样才能做到这一点?
Q2:plot 是否可以绘制两个平滑图,一个用于所有_conf
变量/功能,一个用于所有_chall
功能。 请注意,我的列没有时间变量,而是按顺序排列为:
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,实际数据有几行多列。 作为参考,我在下面分享 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,但他们考虑了时间变量。 我应该如何使用某种时间变量更改我的任务名称?
更新1:
当为high
appScore 组和low
appScore 组的_conf
绘制时,我的图表目前看起来像这样。 我想平滑和叠加这些图表,看看是否有任何差异或模式。
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")
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表:
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
现在绘图很容易。 以 plot "conf"
功能为例:
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")
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