skrypt

raportowanie.r

@@ -11,6 +11,19 @@ con <- DBI::dbConnect(
 countries <- tbl(con, "dim_countries")
 drugs <- tbl(con, "dim_drugs")
 time <- tbl(con, "dim_time")
+status <- tbl(con, "dim_claim_statuses")
+
+tbl(con, "FT_Refund") %>%
+  inner_join(time, by = c("response_time_fk" = "time_sk")) %>%
+  inner_join(status, by = c("claim_status_fk" = "claim_status_sk")) %>%
+  filter(year >= 2008 && year <= 2016) %>%
+  group_by(year, status_description) %>%
+  summarize(how_many = sum(cnt)) %>%
+  ungroup() %>%
+  ggplot(aes(year, how_many, fill = status_description)) + 
+  geom_bar(stat = "identity") +
+  scale_x_continuous(breaks = 2009:2016) +
+  facet_grid(. ~ status_description)
 
 tbl(con, "FT_Refund") %>%
   inner_join(countries, by = c("country_fk" = "country_sk")) %>%
@@ -20,11 +33,26 @@ tbl(con, "FT_Refund") %>%
   geom_point() +
   xlab("Cena") +
   ylab("% zniki")
-
   
 tbl(con, "FT_Refund") %>%
   inner_join(time, by = c("response_time_fk" = "time_sk")) %>%
-  filter(year == 2009) %>%
+  inner_join(drugs, by = c("drug_fk" = "drug_sk")) %>%
-  head(n = 500) %>%
+  filter(year %in% c(2009, 2010)) %>%
-  select(year, month, day, price)
+  mutate(sale = ifelse(reimbursement_amountPercent > 30, "on sale", "not on sale")) %>%
-  
+  ggplot(aes(month, price, fill = drug_product_family_name)) + 
+    geom_bar(stat = "identity") +
+    scale_x_continuous("month", breaks = 1:12) +
+    facet_grid(sale ~ year)
+
+tbl(con, "FT_Registration") %>%
+  inner_join(time, by = c("response_time_fk" = "time_sk")) %>%
+  group_by(year) %>%
+  summarize(how_many = sum(cnt)) %>%
+  filter(how_many > 0) %>%
+  mutate(decade = floor(year / 10) * 10) %>%
+  ggplot(aes(year, how_many)) + 
+    geom_area()
+
+
+
+