select(n) will choose column n:
get_index <- function(dat, row, col) {
- dat %>%
- filter(row_number() == row) %>%
- select(all_of(col))
-}
-
-get_index(dat = ces, row = 10, col = 7)
-
-# A tibble: 1 × 1 - CES4.0Score - <dbl> -1 43.7- -
Summary
-
@@ -3775,6 +3761,8 @@
Combining with mutate() - the replace_na function
Here we will use the yearly_co2_emissions data from dasehr
replace_na({data frame}, {list of values}) or replace_na({vector}, {single value})
yearly_co2_emissions %>%
diff --git a/modules/Functions/lab/Functions_Lab.Rmd b/modules/Functions/lab/Functions_Lab.Rmd
index 551b5d9f..661f8054 100644
--- a/modules/Functions/lab/Functions_Lab.Rmd
+++ b/modules/Functions/lab/Functions_Lab.Rmd
@@ -116,18 +116,18 @@ data %>%
# Practice on Your Own!
-### P.1
+### P.2
Use `across` and `mutate` to convert all columns starting with the string "PM" into a binary variable: TRUE if the value is greater than 10 and FALSE if less than or equal to 10. **Hint**: use `starts_with()` to select the columns that start with "PM". Use a "function on the fly" to do a logical test if the value is greater than 10.
-```{r P.1response}
+```{r P.2response}
```
-### P.2
+### P.3
Take your code from question 2.4 and assign it to the variable `ces_dat`.
@@ -135,6 +135,6 @@ Take your code from question 2.4 and assign it to the variable `ces_dat`.
- Create a ggplot boxplot (`geom_boxplot()`) where (1) the x-axis is `PM2.5` and (2) the y-axis is `Asthma`.
- You change the `labs()` layer so that the x-axis is "ER Visits for Asthma: PM2.5 greater than 10"
-```{r P.2response}
+```{r P.3response}
```
diff --git a/modules/Functions/lab/Functions_Lab_Key.Rmd b/modules/Functions/lab/Functions_Lab_Key.Rmd
index c97c3d87..8591cbf1 100644
--- a/modules/Functions/lab/Functions_Lab_Key.Rmd
+++ b/modules/Functions/lab/Functions_Lab_Key.Rmd
@@ -149,13 +149,13 @@ ces %>%
# Practice on Your Own!
-### P.1
+### P.2
Use `across` and `mutate` to convert all columns starting with the string "PM" into a binary variable: TRUE if the value is greater than 10 and FALSE if less than or equal to 10. **Hint**: use `starts_with()` to select the columns that start with "PM". Use a "function on the fly" to do a logical test if the value is greater than 10.
-```{r P.1response}
+```{r P.2response}
ces %>%
mutate(across(
.cols = starts_with("PM"),
@@ -164,7 +164,7 @@ ces %>%
```
-### P.2
+### P.3
Take your code from question 2.4 and assign it to the variable `ces_dat`.
@@ -172,7 +172,7 @@ Take your code from question 2.4 and assign it to the variable `ces_dat`.
- Create a ggplot boxplot (`geom_boxplot()`) where (1) the x-axis is `PM2.5` and (2) the y-axis is `Asthma`.
- You change the `labs()` layer so that the x-axis is "ER Visits for Asthma: PM2.5 greater than 10"
-```{r P.2response}
+```{r P.3response}
ces_dat <-
ces %>%
mutate(across(
diff --git a/modules/Functions/lab/Functions_Lab_Key.html b/modules/Functions/lab/Functions_Lab_Key.html
index bc375fef..8b09e46f 100644
--- a/modules/Functions/lab/Functions_Lab_Key.html
+++ b/modules/Functions/lab/Functions_Lab_Key.html
@@ -362,9 +362,9 @@ Part 1
1.1
Create a function that takes one argument, a vector, and returns the
-sum of the vector and squares the result. Call it “sum_squared”. Test
-your function on the vector c(2,7,21,30,90) - you should
-get the answer 22500.
+sum of the vector and then squares the result. Call it “sum_squared”.
+Test your function on the vector c(2,7,21,30,90) - you
+should get the answer 22500.
# General format
NEW_FUNCTION <- function(x, y) x + y
or
@@ -411,8 +411,8 @@ 1.3
has_n(x = nums)
## [1] TRUE
-
-1.4
+
+P.1
Create a new number b_num that is not contained with
nums. Use your updated has_n function with the
default value and add b_num as the n argument
@@ -424,7 +424,7 @@
1.4
Part 2
-
+
2.1
Read in the CalEnviroScreen from https://daseh.org/data/CalEnviroScreen_data.csv. Assign
the data the name “ces”.
@@ -432,7 +432,7 @@ 2.1
# If downloaded
# ces <- read_csv("CalEnviroScreen_data.csv")
-
+
2.2
We want to get some summary statistics on water contamination. Use
across inside summarize to get the sum total
@@ -479,14 +479,21 @@
2.2
## <dbl> <dbl> <dbl>
## 1 403640. 304029. 256802.
-
+
2.3
Use across and mutate to convert all
columns containing the word “Pctl” into proportions (i.e., divide that
value by 100). Hint: use contains() to
select the right columns within across(). Use a “function
-on the fly” to divide by 100. It will also be easier to check your work
-if you select() columns that match “Pctl”.
+on the fly” to divide by 100 (function(x) x / 100). It will
+also be easier to check your work if you select() columns
+that match “Pctl”.
+# General format
+data %>%
+ mutate(across(
+ .cols = {vector or tidyselect},
+ .fns = {some function}
+ ))
ces %>%
mutate(across(
.cols = contains("Pctl"),
@@ -514,8 +521,11 @@ 2.3
## # CardiovascularDiseasePctl <dbl>, PopCharPctl <dbl>, EducationPctl <dbl>,
## # LinguisticIsolPctl <dbl>, PovertyPctl <dbl>, UnemploymentPctl <dbl>, …
-
-2.4
+
+
+Practice on Your Own!
+
+P.2
Use across and mutate to convert all
columns starting with the string “PM” into a binary variable: TRUE if
the value is greater than 10 and FALSE if less than or equal to 10.
@@ -548,11 +558,8 @@
2.4
## # PesticidesPctl <dbl>, ToxRelease <dbl>, ToxReleasePctl <dbl>,
## # Traffic <dbl>, TrafficPctl <dbl>, CleanupSites <dbl>, …
-
-
-Practice on Your Own!
-
-P.1
+
+P.3
Take your code from question 2.4 and assign it to the variable
ces_dat.
@@ -584,7 +591,7 @@ P.1
ces_boxplot(ces_dat)
## Warning: Removed 11 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
-
+