updates till chap 6

04-descriptives.Rmd

@@ -2032,7 +2032,23 @@ gss_cat %>%
 
 Much better! In Chapter 6, we are going to learn about `{ggplot2}`.
 
-`{forcats}` contains other very useful functions, so I urge you to go through the documentation.
+The last family of function I'd like to mention are the `fct_lump*()` functions. These make it possible
+to lump several levels of a factor into a new *other* level:
+
+```{r}
+
+gss_cat %>%
+  mutate(
+    # Description of the different functions taken from help(fct_lump)
+    denom_lowfreq = fct_lump_lowfreq(denom), # lumps together the least frequent levels, ensuring that "other" is still the smallest level.
+    denom_min = fct_lump_min(denom, min = 10), # lumps levels that appear fewer than min times.
+    denom_n = fct_lump_n(denom, n = 3), # lumps all levels except for the n most frequent (or least frequent if n < 0)
+    denom_prop = fct_lump_prop(denom, prop = 0.10) # lumps levels that appear in fewer prop * n times.
+         )
+
+```
+
+There's many other, so I'd advise you go through the package's function [reference](https://forcats.tidyverse.org/reference/index.html).
 
 ### Get your dates right with `{lubridate}`
 
@@ -2070,7 +2086,7 @@ independence <- readRDS("datasets/independence.rds")
 ```
 
 This dataset was scraped from the following Wikipedia [page](https://en.wikipedia.org/wiki/Decolonisation_of_Africa#Timeline).
-It shows when African countries gained independence from which colonial powers. In Chapter 11, I
+It shows when African countries gained independence and from which colonial powers. In Chapter 10, I
 will show you how to scrape Wikipedia pages using R. For now, let's take a look at the contents
 of the dataset:
 

05-graphs.Rmd

@@ -27,7 +27,7 @@ resources that I keep coming back to:
 
 * [ggplot2 extensions](https://exts.ggplot2.tidyverse.org/)
 
-* [ggthemes Vignette](https://cran.r-project.org/web/packages/ggthemes/vignettes/ggthemes.html)
+* [ggthemes function reference](https://jrnold.github.io/ggthemes/reference/index.html)
 
 * [ggplot2 cheatsheet](https://www.rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf)
 
@@ -115,12 +115,34 @@ starwars %>%
     geom_point(aes(height, mass))
 ```
 
-There is a positive correlation between height and mass. Later, we are going to see how we can also plot a regression
-line that goes through the scatter plot, but first, let's discover some other `geom_*()` functions.
+There is a positive correlation between height and mass, by adding `geom_smooth()` with the option `method = "lm"`:
+
+```{r, warning = FALSE}
+starwars %>%
+  filter(!str_detect(name, "Jabba")) %>%
+  ggplot(aes(height, mass)) +
+  geom_point(aes(height, mass)) +
+  geom_smooth(method = "lm")
+```
+
+I've moved the `aes(height, mass)` up to the `ggplot()` function because both `geom_point()` and `geom_smooth()`
+need them, and as explained in the begging of this section, the aesthetics listed in `ggplot()` get passed down
+to the other geoms.
+
+If you omit `method = "lm`, you get a non-parametric curve:
+
+```{r, warning = FALSE}
+starwars %>%
+  filter(!str_detect(name, "Jabba")) %>%
+  ggplot(aes(height, mass)) +
+  geom_point(aes(height, mass)) +
+  geom_smooth()
+```
+
 
 ### Density
 
-`geom_density()` is the *geom* that allows you to get density plots:
+Use `geom_density()` to get density plots:
 
 ```{r}
 ggplot(starwars, aes(height)) +
@@ -173,8 +195,7 @@ ggplot(filtered_data) +
 For the line plots, we are going to use official unemployment data (the same as in the previous
 chapter, but with all the available years). Get it from
 [here](https://github.com/b-rodrigues/modern_R/tree/master/datasets/unemployment/all)
-(downloaded from:
-http://www.statistiques.public.lu/stat/TableViewer/tableView.aspx?ReportId=12950&IF_Language=eng&MainTheme=2&FldrName=3&RFPath=91).
+(downloaded from the website of the [Luxembourguish national statistical institute](https://lustat.statec.lu/vis?pg=0&df[ds]=release&df[id]=DF_X026&df[ag]=LU1&df[vs]=1.0&pd=2021%2C&dq=..A&ly[rw]=SPECIFICATION&ly[cl]=VARIABLE&lc=en).
 
 Let's plot the unemployment for the canton of Luxembourg only:
 
@@ -666,7 +687,7 @@ There are two ways to save plots on disk; one through the *Plots* plane in RStud
 `ggsave()` function. Using RStudio, navigate to the *Plots* pane and click on *Export*. You can
 then choose where to save the plot and other various options:
 
-```{r}
+```{r, echo = FALSE}
 knitr::include_graphics("pics/rstudio_save_plots.gif")
 ```
 

06-statistical_models.Rmd

@@ -166,7 +166,8 @@ model3 <- lm(price ~ ., data = Housing)
 summary(model3)
 ```
 
-You can access different elements of `model3` with `$`, because the result of `lm()` is a list:
+You can access different elements of `model3` with `$`, because the result of `lm()` is a list 
+(you can check this claim with `typeof(model3)`:
 
 ```{r}
 print(model3$coefficients)
@@ -215,13 +216,28 @@ The first `.` in the `lm()` function is used to indicate that we wish to use all
 used to *place* the result from the two `dplyr` instructions that preceded is to be placed there.
 The picture below should help you understand:
 
-```{r}
+```{r, echo = FALSE}
 knitr::include_graphics("pics/pipe_to_second_position.png")
 ```
 
 You have to specify this, because by default, when using `%>%` the left hand side argument gets
 passed as the first argument of the function on the right hand side.
 
+Since version 4.2, R now also natively includes a placeholder, `_`:
+
+```{r}
+Housing |>
+  select(-driveway, -stories) |>
+  lm(price ~ ., data = _) |>
+  broom::tidy()
+
+```
+
+For the example above, I've also switched from `%>%` to  `|>`, or else I can't use the `_` placeholder.
+The advantage of the `_` placeholder is that it disambiguates `.`. So here, the `.` is a placeholder for
+all the variables in the dataset, and `_` is a placeholder for the dataset.
+
+
 ## Diagnostics
 
 Diagnostics are useful metrics to assess model fit. You can read some of these diagnostics, such as

docs/404.html

@@ -24,7 +24,7 @@
 <meta name="author" content="Bruno Rodrigues" />
 
 
-<meta name="date" content="2022-06-10" />
+<meta name="date" content="2022-06-11" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1" />
   <meta name="apple-mobile-web-app-capable" content="yes" />
@@ -121,6 +121,28 @@
 code span.wa { color: #60a0b0; font-weight: bold; font-style: italic; } /* Warning */
 </style>
 
+<style type="text/css">
+/* Used with Pandoc 2.11+ new --citeproc when CSL is used */
+div.csl-bib-body { }
+div.csl-entry {
+  clear: both;
+}
+.hanging div.csl-entry {
+  margin-left:2em;
+  text-indent:-2em;
+}
+div.csl-left-margin {
+  min-width:2em;
+  float:left;
+}
+div.csl-right-inline {
+  margin-left:2em;
+  padding-left:1em;
+}
+div.csl-indent {
+  margin-left: 2em;
+}
+</style>
 
 <link rel="stylesheet" href="style.css" type="text/css" />
 </head>