lazyman

baseR_functions_adv.Rmd

@@ -160,4 +160,24 @@ mystat <- function(x){
 
 ## 更多
 
+冰淇淋放大器，这个机器有很多档位，可以让冰淇淋放大指定的倍数，默认为10倍
+
+```{r}
+enlarge_icecream <- function(multi = 10) {
+  function(penis) {
+    penis * multi
+  }
+}
+```
+
+等待被放大的冰淇淋的大小
+```{r}
+x <- c(2, 3, 4.5)
+x
+```
+
+这个冰淇淋机器 `extent_penis(multi = 100)()`有很多档位，可以指定放大的倍数，比如这里设定为100倍
+```{r}
+enlarge_icecream(multi = 100)(x)
+```
 

eda_lazyman.Rmd

@@ -206,12 +206,16 @@ library(statsExpressions)
 # https://github.com/IndrajeetPatil/statsExpressions
 
 
-ggplot(mtcars, aes(x = mpg, y = wt)) +
+# dataframe with results
+results_data <- corr_test(mtcars, mpg, wt, type = "nonparametric")
+
+# create a scatter plot
+ggplot(mtcars, aes(mpg, wt)) +
   geom_point() +
-  geom_smooth(method = "lm") +
+  geom_smooth(method = "lm", formula = y ~ x) +
   labs(
     title = "Spearman's rank correlation coefficient",
-    subtitle = expr_corr_test(mtcars, mpg, wt, type = "nonparametric")
+    subtitle = parse(text = results_data$expression)
   )
 ```
 

tidyverse_beauty_of_across4.Rmd

@@ -199,6 +199,19 @@ d %>%
   mutate(100 * proportions(across(.names = "%{.col}")))
 ```
 
+### 方法6
+更好的呈现比例
+
+```{r beauty-of-across4-8-0}
+d %>%
+  rowwise() %>% 
+  mutate(
+   across(c(water, food), ~scales::label_percent(scale = 100)(.x /sum(c_across())), .names = "{.col}_%")
+  )
+```
+
+
+
 上面的方法虽然很多，但基本思路是一样的。