Worked through factors

new_pages/factors.qmd

@@ -84,7 +84,7 @@ table(linelist$delay_cat, useNA = "always")
 Likewise, if we make a bar plot, the values also appear in this order on the x-axis (see the [ggplot basics](ggplot_basics.qmd) page for more on **ggplot2** - the most common visualization package in R).  
 
 ```{r, warning=F, message=F}
-ggplot(data = linelist)+
+ggplot(data = linelist) +
   geom_bar(mapping = aes(x = delay_cat))
 ```
 
@@ -125,7 +125,7 @@ levels(linelist$delay_cat)
 Now the plot order makes more intuitive sense as well.  
 
 ```{r, warning=F, message=F}
-ggplot(data = linelist)+
+ggplot(data = linelist) +
   geom_bar(mapping = aes(x = delay_cat))
 ```
 
@@ -164,8 +164,8 @@ The package **forcats** offers useful functions to easily adjust the order of a
 
 These functions can be applied to a factor column in two contexts:  
 
-1) To the column in the data frame, as usual, so the transformation is available for any subsequent use of the data  
-2) *Inside of a plot*, so that the change is applied only within the plot  
+1) To the column in the data frame, as usual, so the transformation is available for any subsequent use of the data.  
+2) *Inside of a plot*, so that the change is applied only within the plot.  
 
 
 
@@ -175,8 +175,8 @@ This function is used to manually order the factor levels. If used on a non-fact
 
 Within the parentheses first provide the factor column name, then provide either:  
 
-* All the levels in the desired order (as a character vector `c()`), or  
-* One level and it's corrected placement using the `after = ` argument  
+* All the levels in the desired order (as a character vector `c()`), or,  
+* One level and it's corrected placement using the `after = ` argument.  
 
 Here is an example of redefining the column `delay_cat` (which is already class Factor) and specifying all the desired order of levels.  
 
@@ -214,11 +214,11 @@ linelist <- linelist %>%
 
 ```{r, warning=F, message=F, out.width = c('50%', '50%'), fig.show='hold'}
 # Alpha-numeric default order - no adjustment within ggplot
-ggplot(data = linelist)+
+ggplot(data = linelist) +
     geom_bar(mapping = aes(x = delay_cat))
 
 # Factor level order adjusted within ggplot
-ggplot(data = linelist)+
+ggplot(data = linelist) +
   geom_bar(mapping = aes(x = fct_relevel(delay_cat, c("<2 days", "2-5 days", ">5 days"))))
 ```
 
@@ -244,14 +244,14 @@ This function can be used within a `ggplot()`, as shown below.
 
 ```{r, out.width = c('50%', '50%', '50%'), fig.show='hold', warning=F, message=F}
 # ordered by frequency
-ggplot(data = linelist, aes(x = fct_infreq(delay_cat)))+
-  geom_bar()+
+ggplot(data = linelist, aes(x = fct_infreq(delay_cat))) +
+  geom_bar() +
   labs(x = "Delay onset to admission (days)",
        title = "Ordered by frequency")
 
 # reversed frequency
-ggplot(data = linelist, aes(x = fct_rev(fct_infreq(delay_cat))))+
-  geom_bar()+
+ggplot(data = linelist, aes(x = fct_rev(fct_infreq(delay_cat)))) +
+  geom_bar() +
   labs(x = "Delay onset to admission (days)",
        title = "Reverse of order by frequency")
 ```
@@ -272,26 +272,26 @@ In the first example below, the default order alpha-numeric level order is used.
 
 ```{r, fig.show='hold', message=FALSE, warning=FALSE, out.width=c('50%', '50%')}
 # boxplots ordered by original factor levels
-ggplot(data = linelist)+
+ggplot(data = linelist) +
   geom_boxplot(
     aes(x = delay_cat,
         y = ct_blood, 
-        fill = delay_cat))+
+        fill = delay_cat)) +
   labs(x = "Delay onset to admission (days)",
-       title = "Ordered by original alpha-numeric levels")+
-  theme_classic()+
+       title = "Ordered by original alpha-numeric levels") +
+  theme_classic() +
   theme(legend.position = "none")
 
 
 # boxplots ordered by median CT value
-ggplot(data = linelist)+
+ggplot(data = linelist) +
   geom_boxplot(
     aes(x = fct_reorder(delay_cat, ct_blood, "median"),
         y = ct_blood,
-        fill = delay_cat))+
+        fill = delay_cat)) +
   labs(x = "Delay onset to admission (days)",
-       title = "Ordered by median CT value in group")+
-  theme_classic()+
+       title = "Ordered by median CT value in group") +
+  theme_classic() +
   theme(legend.position = "none")
 ```
 
@@ -312,12 +312,12 @@ epidemic_data <- linelist %>%         # begin with the linelist
       hospital                                            
     ) 
   
-ggplot(data = epidemic_data)+                       # start plot
+ggplot(data = epidemic_data) +                       # start plot
   geom_line(                                        # make lines
     aes(
       x = epiweek,                                  # x-axis epiweek
       y = n,                                        # height is number of cases per week
-      color = fct_reorder2(hospital, epiweek, n)))+ # data grouped and colored by hospital, with factor order by height at end of plot
+      color = fct_reorder2(hospital, epiweek, n))) + # data grouped and colored by hospital, with factor order by height at end of plot
   labs(title = "Factor levels (and legend display) by line height at end of plot",
        color = "Hospital")                          # change legend title
 ```
@@ -350,7 +350,7 @@ You can adjust the level displays manually manually with `fct_recode()`. This is
 
 This tool can also be used to "combine" levels, by assigning multiple levels the same re-coded value. Just be careful to not lose information! Consider doing these combining steps in a new column (not over-writing the existing column).  
 
-`fct_recode()` has a different syntax than `recode()`. `recode()` uses `OLD = NEW`, whereas `fct_recode()` uses `NEW = OLD`.     
+<span style="color: red;">**_DANGER:_** `fct_recode()` has a different syntax than `recode()`. `recode()` uses `OLD = NEW`, whereas `fct_recode()` uses `NEW = OLD`. </span>   
 
 The current levels of `delay_cat` are:  
 ```{r, echo=F}
@@ -444,10 +444,10 @@ In a `ggplot()` figure, simply add the argument `drop = FALSE` in the relevant `
 
 This example is a stacked bar plot of age category, by hospital. Adding `scale_fill_discrete(drop = FALSE)` ensures that all age groups appear in the legend, even if not present in the data. 
 
-```{r}
-ggplot(data = linelist)+
+```{r, fig.width = 10.5}
+ggplot(data = linelist) +
   geom_bar(mapping = aes(x = hospital, fill = age_cat)) +
-  scale_fill_discrete(drop = FALSE)+                        # show all age groups in the legend, even those not present
+  scale_fill_discrete(drop = FALSE) +                        # show all age groups in the legend, even those not present
   labs(
     title = "All age groups will appear in legend, even if not present in data")
 ```
@@ -463,8 +463,7 @@ Read more in the [Descriptive tables](tables_descriptive.qmd) page, or at the [s
 
 ## Epiweeks  
 
-Please see the extensive discussion of how to create epidemiological weeks in the [Grouping data](grouping.qmd) page.  
-Please also see the [Working with dates](dates.qmd) page for tips on how to create and format epidemiological weeks.  
+Please see the extensive discussion of how to create epidemiological weeks in the [Grouping data](grouping.qmd) page.  Also see the [Working with dates](dates.qmd) page for tips on how to create and format epidemiological weeks.  
 
 
 ### Epiweeks in a plot {.unnumbered}  
@@ -476,8 +475,8 @@ In this approach, you can adjust the *display* of the dates on an axis with `sca
 ```{r, warning=F, message=F}
 linelist %>% 
   mutate(epiweek_date = floor_date(date_onset, "week")) %>%  # create week column
-  ggplot()+                                                  # begin ggplot
-  geom_histogram(mapping = aes(x = epiweek_date))+           # histogram of date of onset
+  ggplot() +                                                  # begin ggplot
+  geom_histogram(mapping = aes(x = epiweek_date)) +           # histogram of date of onset
   scale_x_date(date_labels = "%Y-W%W")                       # adjust disply of dates to be YYYY-WWw
 ```
 
@@ -486,7 +485,7 @@ linelist %>%
 
 However, if your purpose in factoring is *not* to plot, you can approach this one of two ways:  
 
-1) *For fine control over the display*, convert the **lubridate** epiweek column (YYYY-MM-DD) to the desired display format (YYYY-WWw) *within the data frame itself*, and then convert it to class Factor.  
+1) *For fine control over the display*, convert the **lubridate** epiweek column (YYYY-MM-DD) to the desired display format (YYYY-Www) *within the data frame itself*, and then convert it to class Factor.  
 
 First, use `format()` from **base** R to convert the date display from YYYY-MM-DD to YYYY-Www display (see the [Working with dates](dates.qmd) page). In this process the class will be converted to character. Then, convert from character to class Factor with `factor()`.