updated save_data.R

scripts/analysis.R

@@ -3,12 +3,12 @@ library(ggplot2)
 library(purrr)
 library(tidyr)
 
-#Let’s load the datasets:
+#Let's load the datasets:
 
 commune_level_data <- read.csv("datasets/commune_level_data.csv")
 country_level_data <- read.csv("datasets/country_level_data.csv")
 
-#Let’s compute the Laspeyeres index for each commune:
+#Let's compute the Laspeyeres index for each commune:
 
 commune_level_data <- commune_level_data %>%
   group_by(locality) %>%
@@ -21,7 +21,7 @@ commune_level_data <- commune_level_data %>%
          pl_m2 = average_price_m2_nominal_euros/p0_m2*100)
 
 
-#Let’s also compute it for the whole country:
+#Let's also compute it for the whole country:
 
 country_level_data <- country_level_data %>%
   mutate(p0 = ifelse(year == "2010", average_price_nominal_euros, NA)) %>%
@@ -33,7 +33,7 @@ country_level_data <- country_level_data %>%
 
 
 #We are going to create a plot for 5 communes and compare the price evolution in the communes
-#to the national price evolution. Let’s first list the communes:
+#to the national price evolution. Let's first list the communes:
 
 communes <- c("Luxembourg",
               "Esch-sur-Alzette",
@@ -122,7 +122,7 @@ wincrange_plot <- ggplot(data_to_plot) +
                 group = locality,
                 colour = locality))
 
-# Let’s save the plots
+# Let's save the plots
 ggsave("plots/lux_plot.pdf", lux_plot)
 ggsave("plots/esch_plot.pdf", esch_plot)
 ggsave("plots/mamer_plot.pdf", mamer_plot)

scripts/save_data.R

@@ -39,7 +39,7 @@ raw_data <- raw_data |>
 
 str(raw_data)
 
-# Let’s take a look at the spelling
+# Let's take a look at the spelling
 raw_data |>
   dplyr::filter(grepl("Luxembourg", locality)) |>
   dplyr::count(locality)
@@ -91,17 +91,19 @@ country_level_data <- full_join(country_level, offers_country) |>
 
 
 # We need to check if communes are all in our data
-current_communes <- "https://en.wikipedia.org/wiki/List_of_communes_of_Luxembourg" |>
+current_communes <- "https://is.gd/lux_communes" |>
   rvest::read_html() |>
   rvest::html_table() |>
-  purrr::pluck(1) |>
-  janitor::clean_names()
+  purrr::pluck(2) |>
+  janitor::clean_names() |>
+  dplyr::filter(name_2 != "Name") |>
+  dplyr::rename(commune = name_2)
 
 # Test if all communes are there
 setdiff(unique(commune_level_data$locality), current_communes$commune)
 
 # We need former communes
-former_communes <- "https://en.wikipedia.org/wiki/Communes_of_Luxembourg#Former_communes" |>  
+former_communes <- "https://is.gd/lux_former_communes" |>
   rvest::read_html() |>
   rvest::html_table() |>
   purrr::pluck(3) |>