Fixing code that was spilling into the right margin (#170)

* Fixing code that was spilling into the right margin * Adjust style for long lines --------- Co-authored-by: Stephanie Zimmer <[email protected]>
tidy-survey-r · Aug 23, 2024 · 1630dc7 · 1630dc7
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Showing 4 changed files with 28 additions and 11 deletions.
diff --git a/07-modeling.Rmd b/07-modeling.Rmd
@@ -676,7 +676,9 @@ Let's first look at the main effects of income grouping and early voting behavio
 ```{r}
 #| label: model-logisticexamp-biden-main
 log_biden_main <- anes_des_ind %>%
-  mutate(EarlyVote2020 = fct_relevel(EarlyVote2020, "No", after = 0)) %>%
+  mutate(
+    EarlyVote2020 = fct_relevel(EarlyVote2020, "No", after = 0)
+  ) %>%
   svyglm(
     design = .,
     formula = VoteBiden ~ EarlyVote2020 + Income7,
@@ -716,7 +718,9 @@ Although early voting behavior was not significant, there may be an interaction
 ```{r}
 #| label: model-logisticexamp-biden-int
 log_biden_int <- anes_des_ind %>%
-  mutate(EarlyVote2020 = fct_relevel(EarlyVote2020, "No", after = 0)) %>% 
+  mutate(
+    EarlyVote2020 = fct_relevel(EarlyVote2020, "No", after = 0)
+  ) %>% 
   svyglm(design = .,
          formula = VoteBiden ~ (EarlyVote2020 + Income7)^2,
          family = quasibinomial) 

diff --git a/08-communicating-results.Rmd b/08-communicating-results.Rmd
@@ -170,7 +170,9 @@ We can add a few more enhancements, such as a title (which is different from a c
 trust_gov_gt2 <- trust_gov_gt %>%
   tab_header("American voter's trust
              in the federal government, 2020") %>%
-  tab_source_note(md("*Source*: American National Election Studies, 2020")) %>%
+  tab_source_note(
+    md("*Source*: American National Election Studies, 2020")
+  ) %>%
   tab_footnote(
     "Question text: How often can you trust the federal government
     in Washington to do what is right?"
@@ -309,7 +311,9 @@ anes_des_gtsum3 <- anes_des %>%
   as_gt() %>%
   tab_header("American voter's trust
              in the federal government, 2020") %>%
-  tab_source_note(md("*Source*: American National Election Studies, 2020")) %>%
+  tab_source_note(
+    md("*Source*: American National Election Studies, 2020")
+  ) %>%
   tab_footnote(
     "Question text: How often can you trust the federal government
     in Washington to do what is right?"
@@ -356,7 +360,9 @@ anes_des_gtsum4 <- anes_des %>%
   as_gt() %>%
   tab_header(
     "American voter's trust in the federal government, 2020") %>%
-  tab_source_note(md("*Source*: American National Election Studies, 2020")) %>%
+  tab_source_note(
+    md("*Source*: American National Election Studies, 2020")
+  ) %>%
   tab_footnote(
     "Question text: How often can you trust the federal government
     in Washington to do what is right?"
@@ -408,7 +414,9 @@ anes_des_gtsum5 <- anes_des %>%
              in the federal government by whether they voted
              in the 2020 presidential election"
   ) %>%
-  tab_source_note(md("*Source*: American National Election Studies, 2020")) %>%
+  tab_source_note(
+    md("*Source*: American National Election Studies, 2020")
+  ) %>%
   tab_footnote(
     "Question text: How often can you trust the federal government
     in Washington to do what is right?"

diff --git a/13-ncvs-vignette.Rmd b/13-ncvs-vignette.Rmd
@@ -883,12 +883,15 @@ vr_gt<-pers_est_df %>%
     locations = cells_stub(rows = Level == "Other")
   ) %>%
   tab_source_note(
-    source_note = md("*Note*: Rates per 1,000 persons age 12 or older.")) %>%
-  tab_source_note(source_note = md("*Source*: Bureau of Justice Statistics,
-                  National Crime Victimization Survey, 2021.")) %>%
+    source_note = md("*Note*: Rates per 1,000 persons age 12 or older.")
+  ) %>%
+  tab_source_note(
+    source_note = md("*Source*: Bureau of Justice Statistics,
+                     National Crime Victimization Survey, 2021.")
+  ) %>%
   tab_stubhead(label = "Victim Demographic") %>%
   tab_caption("Rate and standard error of violent victimization,
-             by type of crime and demographic characteristics, 2021")
+              by type of crime and demographic characteristics, 2021")
 ```
 
 

diff --git a/90-AppendixA-DataImport.Rmd b/90-AppendixA-DataImport.Rmd
@@ -245,7 +245,9 @@ SAS:
 library(haven)
 
 anes_sas <-
-  read_sas(data_file = "data/anes_timeseries_2020_sas_20220210.sas7bdat")
+  read_sas(
+    data_file = "data/anes_timeseries_2020_sas_20220210.sas7bdat"
+  )
 ```
 
 ### Working with labeled data