make combined plot with ggarrange

codes/practice_code.Rmd

@@ -67,14 +67,28 @@ df <- read_csv('robotmod_data.csv') %>%
 ```{r}
 df.SD_Rday1 <- df %>% filter(df$robot.day == 1, df$group == "SD")
 
-p_1 <- ggplot(df.SD_Rday1, aes(x=trials, y=foraging.score, group=rat_ID))
-p_1 + geom_line(color="gray", alpha=0.2)+
+#summarize the percentage of foraging.score != 7 for each age in df.SD_Rday1
+SD_Rday1_sum<-df.SD_Rday1 %>% group_by(trials, age) %>% summarize(percentage = sum(foraging.score != 7)/n())
+
+fig1a <-ggbarplot(SD_Rday1_sum, x="trials", y="percentage",
+  color = "age", palette = c("#7fc97f", "#fdc086"),
+  size = 2, ylab = "foraging success [%]", 
+  position = position_dodge(0.8))
+
+
+
+p_1b <- ggplot(df.SD_Rday1, aes(x=trials, y=foraging.score, group=rat_ID))
+
+fig1b<-p_1b + geom_line(color="gray", alpha=0.2)+
 stat_summary(fun=mean, aes(group = age, color= age), geom="line", linewidth=2)+
 stat_summary(fun.data = mean_se, aes(group=age, color = age), geom = "errorbar", alpha=1, width=0.05)+
 scale_color_manual(values = c("#7fc97f", "#fdc086"))+
 scale_y_continuous(breaks = seq(0, 7, by = 1))+
 labs(x = "positions", y = "foraging score") + theme_classic() + facet_wrap(~age, ncol=2)
 
+ggarrange(fig1a, fig1b, ncols=2,labels=c('A','B'), common.legend=TRUE, widths=c(1,2))
+
+
 ```