edit figures

analysis/paper/.~lock.paper.docx#

+,jaccard,jaccard-Latitude-E6440,06.02.2021 16:54,file:///home/jaccard/.config/libreoffice/4;
\ No newline at end of file

analysis/paper/paper.Rmd

@@ -125,6 +125,19 @@ cols_ex = c("year", "eu_q_rank", "sector_agg_id")
 pdat_sector_summary_by_eu_ntile =
   pivot_results_longer_adorn(dat_sector_summary_by_eu_ntile, cols_ex)
 
+# European decile names
+eu_q_rank = seq(1:10)
+eu_decile_name = c("D01",
+                            "D02",
+                            "D03",
+                            "D04",
+                            "D05",
+                            "D06",
+                            "D07",
+                            "D08",
+                            "D09",
+                            "D10")
+eu_decile_name = data.frame(eu_q_rank,eu_decile_name)
 
 ```
 
@@ -185,10 +198,11 @@ As inequality measure through the study, we divide the value in the top European
 p1 = pdat_country_summary_by_eu_ntile %>%
   filter(year == 2015, 
          indicator == "total_fd_me") %>%
+  left_join(eu_decile_name, by = "eu_q_rank") %>%
   group_by(eu_q_rank) %>%
   summarise(value = sum(value)*0.000001,
-            eu_ntile_name = first(eu_ntile_name)) %>%
-  ggplot(aes(x=eu_ntile_name, y=value)) +
+            eu_decile_name = first(eu_decile_name)) %>%
+  ggplot(aes(x=eu_decile_name, y=value)) +
     geom_col(position = position_dodge(), fill=pal[1]) +
     #theme_ipsum() +
     theme_minimal() +
@@ -199,10 +213,11 @@ p1 = pdat_country_summary_by_eu_ntile %>%
 p2 = pdat_country_summary_by_eu_ntile %>%
   filter(year == 2015, 
          indicator == "total_energy_use_tj") %>%
+  left_join(eu_decile_name, by = "eu_q_rank") %>%
   group_by(eu_q_rank) %>%
   summarise(value = sum(value)*0.000001,
-            eu_ntile_name = first(eu_ntile_name)) %>%
-  ggplot(aes(x=eu_ntile_name, y=value)) +
+            eu_decile_name = first(eu_decile_name)) %>%
+  ggplot(aes(x=eu_decile_name, y=value)) +
     geom_col(position = position_dodge(), fill=pal[1]) +
     #theme_ipsum() +
     theme_minimal() +
@@ -213,10 +228,11 @@ p2 = pdat_country_summary_by_eu_ntile %>%
 p3 = pdat_country_summary_by_eu_ntile %>%
   filter(year == 2015, 
          indicator == "total_co2eq_kg") %>%
+  left_join(eu_decile_name, by = "eu_q_rank") %>%
   group_by(eu_q_rank) %>%
   summarise(value = sum(value)*0.000000001,
-            eu_ntile_name = first(eu_ntile_name)) %>%
-  ggplot(aes(x=eu_ntile_name, y=value)) +
+            eu_decile_name = first(eu_decile_name)) %>%
+  ggplot(aes(x=eu_decile_name, y=value)) +
     geom_col(position = position_dodge(), fill=pal[1]) +
     #theme_ipsum() +
     theme_minimal() +