Practice_Solutions.rmd

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# For Loop Solutions




# Vectorization Solutions

- First, use the `apply` function to find the median value across columns of the "dataset" data frame.
```{r}
apply(dataset, 1, median)
```


- Next, find the average number of breaks from yarn with wool type A and tensions L & M only. You should end up with one dataframe with 2 rows and 2 columns ("tension" and "mean_breaks") showing mean A/L breaks and A/M breaks. *Hint: Take it one function at a time (you'll use 3) and check your code as you go to see that you're on the right track.*
```{r}
yarn %>%
  filter(wool == "A" & tension != "H") %>%
  group_by(tension) %>%
  summarise(mean_breaks = mean(breaks)) %T>%
  print()
```


- Lastly, choose only the rows with supp = VC from the teeth data frame and then create 2 new columns: one with the product of len x dose (called "len_x_dose") and the other with the ranking for the len values (called "rank") in descending order (the largest value should rank at 1). *Hint: [here's how to write the ranking function.](https://dplyr.tidyverse.org/reference/ranking.html)*
```{r}
teeth %>%
  filter(supp == "VC") %>%
  mutate(len_x_dose = len*dose,
         rank = row_number(desc(len)))
```