diff --git a/R/get_eurostat_json.R b/R/get_eurostat_json.R index 893627f9..eb76ca34 100755 --- a/R/get_eurostat_json.R +++ b/R/get_eurostat_json.R @@ -60,16 +60,17 @@ get_eurostat_json <- function(id, filters = NULL, status <- httr::status_code(resp) # check status and get json + msg <- ". Some datasets are not accessible via the eurostat interface. You can try to search the data manually from the comext database at http://epp.eurostat.ec.europa.eu/newxtweb/ or bulk download facility at http://ec.europa.eu/eurostat/estat-navtree-portlet-prod/BulkDownloadListing or annual Excel files http://ec.europa.eu/eurostat/web/prodcom/data/excel-files-nace-rev.2" if (status == 200){ jdat <- jsonlite::fromJSON(url) } else if (status == 400){ stop("Failure to get data. Probably invalid dataset id. Status code: ", - status) + status, msg) } else if (status == 500){ stop("Failure to get data. Probably filters did not return any data - or data exceeded query size limitation. Status code: ", status) + or data exceeded query size limitation. Status code: ", status, msg) } else { - stop("Failure to get data. Status code: ", status) + stop("Failure to get data. Status code: ", status, msg) } # get json data diff --git a/R/get_eurostat_raw.R b/R/get_eurostat_raw.R index 620ecc35..fa30ce64 100755 --- a/R/get_eurostat_raw.R +++ b/R/get_eurostat_raw.R @@ -35,11 +35,14 @@ get_eurostat_raw <- function(id) { col_types = readr::cols(.default = readr::col_character())) # check validity + if (ncol(dat) < 2 | nrow(dat) < 1) { + msg <- ". Some datasets are not accessible via the eurostat interface. You can try to search the data manually from the comext database at http://epp.eurostat.ec.europa.eu/newxtweb/ or bulk download facility at http://ec.europa.eu/eurostat/estat-navtree-portlet-prod/BulkDownloadListing or annual Excel files http://ec.europa.eu/eurostat/web/prodcom/data/excel-files-nace-rev.2" if (grepl("does not exist or is not readable", dat[1])) { - stop(id, " does not exist or is not readable") + + stop(id, " does not exist or is not readable", msg) } else { - stop(paste("Could not download ", id)) + stop(paste("Could not download ", id, msg)) } } diff --git a/docs/articles/blogposts.html b/docs/articles/blogposts.html index 765e1d5f..c42155e3 100755 --- a/docs/articles/blogposts.html +++ b/docs/articles/blogposts.html @@ -83,7 +83,7 @@

Blog posts

-

2018-05-19

+

2018-05-20

diff --git a/docs/articles/cheatsheet.html b/docs/articles/cheatsheet.html index e1c53096..e77220b7 100755 --- a/docs/articles/cheatsheet.html +++ b/docs/articles/cheatsheet.html @@ -83,7 +83,7 @@

Cheat sheet: eurostat R package

-

2018-05-19

+

2018-05-20

diff --git a/docs/articles/eurostat_tutorial.html b/docs/articles/eurostat_tutorial.html index 012c939d..58556b47 100755 --- a/docs/articles/eurostat_tutorial.html +++ b/docs/articles/eurostat_tutorial.html @@ -83,7 +83,7 @@

Tutorial (vignette) for the eurostat R package

-

2018-05-19

+

2018-05-20

@@ -852,8 +852,8 @@

dplyr::filter(time == 2010, nchar(geo) == 4) %>% # categorise dplyr::mutate(income = cut_to_classes(values, n = 5))

-
## Table tgs00026 cached at /tmp/RtmpFlVxl1/eurostat/tgs00026_raw_code_FF.rds
-
# Download geospatial data from CISGO
+
## Table tgs00026 cached at /tmp/Rtmpabr3HV/eurostat/tgs00026_raw_code_FF.rds

+
# Download geospatial data from GISCO
 geodata <- get_eurostat_geospatial(output_class = "sf", resolution = "60")

 
## 
 ## COPYRIGHT NOTICE
@@ -928,17 +928,22 @@ 

 library(sf)
 library(RColorBrewer)
 
-# Downloading and manipulating the tabular data 
-euro_sf2 <- eurostat::get_eurostat("tgs00026", time_format = "raw", stringsAsFactors = FALSE) %>% 
-  # subsetting to year 2014 and NUTS-3 level
-  dplyr::filter(time == 2014, grepl("PL",geo)) %>% 
+# Downloading and manipulating the tabular data
+print("Let us focus on year 2014 and NUTS-3 level")
+
## [1] "Let us focus on year 2014 and NUTS-3 level"
+
euro_sf2 <- get_eurostat("tgs00026", time_format = "raw",
+                         stringsAsFactors = FALSE,
+             filter = list(time = "2014")) %>% 
+ 
+  # Subset to NUTS-3 level
+  dplyr::filter(grepl("PL",geo)) %>% 
   # label the single geo column
   mutate(label = paste0(label_eurostat(.)[["geo"]], "\n", values, "€"),
-         income = cut_to_classes(values))
-
## Reading cache file /tmp/RtmpFlVxl1/eurostat/tgs00026_raw_code_FF.rds
-
## Table  tgs00026  read from cache file:  /tmp/RtmpFlVxl1/eurostat/tgs00026_raw_code_FF.rds
-
# Download geospatial data from CISGO
-geodata <- get_eurostat_geospatial(output_class = "sf", resolution = "60")
+ income = cut_to_classes(values)) + +print("Download geospatial data from GISCO")
+
## [1] "Download geospatial data from GISCO"
+
geodata <- get_eurostat_geospatial(output_class = "sf", resolution = "60")
## 
 ## COPYRIGHT NOTICE
 ## 
@@ -980,7 +985,7 @@ 

 ## 
 ## # --------------------------          
 ##
-
# merge with attribute data with geodata
+
# Merge with attribute data with geodata
 map_data <- inner_join(geodata, euro_sf2)

 
## Joining, by = "geo"

 
# plot map
@@ -1007,9 +1012,9 @@ 

   dplyr::filter(time == 2014, nchar(geo) == 4) %>% 
   # classifying the values the variable
   dplyr::mutate(cat = cut_to_classes(values))

-
## Reading cache file /tmp/RtmpFlVxl1/eurostat/tgs00026_raw_code_FF.rds

-
## Table  tgs00026  read from cache file:  /tmp/RtmpFlVxl1/eurostat/tgs00026_raw_code_FF.rds

-
# Download geospatial data from CISGO
+
## Reading cache file /tmp/Rtmpabr3HV/eurostat/tgs00026_raw_code_FF.rds

+
## Table  tgs00026  read from cache file:  /tmp/Rtmpabr3HV/eurostat/tgs00026_raw_code_FF.rds

+
# Download geospatial data from GISCO
 geodata <- get_eurostat_geospatial(output_class = "spdf", resolution = "10", nuts_level = 2)

 
## 
 ## COPYRIGHT NOTICE
@@ -1038,7 +1043,7 @@ 

 ## information regarding their licence agreements.
 ## 

 
## No encoding supplied: defaulting to UTF-8.

-
## SpatialPolygonDataFrame at resolution 1: 10  cached at:  /tmp/RtmpFlVxl1/eurostat/spdf102.RData

+
## SpatialPolygonDataFrame at resolution 1: 10  cached at:  /tmp/Rtmpabr3HV/eurostat/spdf102.RData

 
## 
 ## # --------------------------
 ## HEADS UP!!
@@ -1075,9 +1080,9 @@ 

   dplyr::filter(time == 2014, nchar(geo) == 4) %>% 
   # classifying the values the variable
   dplyr::mutate(cat = cut_to_classes(values))

-
## Reading cache file /tmp/RtmpFlVxl1/eurostat/tgs00026_raw_code_FF.rds

-
## Table  tgs00026  read from cache file:  /tmp/RtmpFlVxl1/eurostat/tgs00026_raw_code_FF.rds

-
# Download geospatial data from CISGO
+
## Reading cache file /tmp/Rtmpabr3HV/eurostat/tgs00026_raw_code_FF.rds

+
## Table  tgs00026  read from cache file:  /tmp/Rtmpabr3HV/eurostat/tgs00026_raw_code_FF.rds

+
# Download geospatial data from GISCO
 geodata <- get_eurostat_geospatial(output_class = "df", resolution = "60", nuts_level = "2")

 
## 
 ## COPYRIGHT NOTICE
diff --git a/docs/articles/publications.html b/docs/articles/publications.html
index 0ab93fb4..e93b9f86 100755
--- a/docs/articles/publications.html
+++ b/docs/articles/publications.html
@@ -83,7 +83,7 @@
     

       
Publications using the eurostat R package

             
-            
2018-05-19

+            
2018-05-20

       
       
       
diff --git a/vignettes/eurostat_tutorial.Rmd b/vignettes/eurostat_tutorial.Rmd
index ae110a2c..d08557cd 100755
--- a/vignettes/eurostat_tutorial.Rmd
+++ b/vignettes/eurostat_tutorial.Rmd
@@ -300,7 +300,7 @@ sp_data <- eurostat::get_eurostat("tgs00026", time_format = "raw", stringsAsFact
   # categorise
   dplyr::mutate(income = cut_to_classes(values, n = 5))
 
-# Download geospatial data from CISGO
+# Download geospatial data from GISCO
 geodata <- get_eurostat_geospatial(output_class = "sf", resolution = "60")
 
 # merge with attribute data with geodata
@@ -344,18 +344,22 @@ library(dplyr)
 library(sf)
 library(RColorBrewer)
 
-# Downloading and manipulating the tabular data 
-euro_sf2 <- eurostat::get_eurostat("tgs00026", time_format = "raw", stringsAsFactors = FALSE) %>% 
-  # subsetting to year 2014 and NUTS-3 level
-  dplyr::filter(time == 2014, grepl("PL",geo)) %>% 
+# Downloading and manipulating the tabular data
+print("Let us focus on year 2014 and NUTS-3 level")
+euro_sf2 <- get_eurostat("tgs00026", time_format = "raw",
+                         stringsAsFactors = FALSE,
+			 filter = list(time = "2014")) %>% 
+ 
+  # Subset to NUTS-3 level
+  dplyr::filter(grepl("PL",geo)) %>% 
   # label the single geo column
   mutate(label = paste0(label_eurostat(.)[["geo"]], "\n", values, "€"),
          income = cut_to_classes(values))
 
-# Download geospatial data from CISGO
+print("Download geospatial data from GISCO")
 geodata <- get_eurostat_geospatial(output_class = "sf", resolution = "60")
 
-# merge with attribute data with geodata
+# Merge with attribute data with geodata
 map_data <- inner_join(geodata, euro_sf2)
 
 # plot map
@@ -383,7 +387,7 @@ dat <- get_eurostat("tgs00026", time_format = "raw", stringsAsFactors = FALSE) %
   # classifying the values the variable
   dplyr::mutate(cat = cut_to_classes(values))
 
-# Download geospatial data from CISGO
+# Download geospatial data from GISCO
 geodata <- get_eurostat_geospatial(output_class = "spdf", resolution = "10", nuts_level = 2)
 
 # merge with attribute data with geodata
@@ -410,7 +414,7 @@ dat <- get_eurostat("tgs00026", time_format = "raw", stringsAsFactors = FALSE) %
   # classifying the values the variable
   dplyr::mutate(cat = cut_to_classes(values))
 
-# Download geospatial data from CISGO
+# Download geospatial data from GISCO
 geodata <- get_eurostat_geospatial(output_class = "df", resolution = "60", nuts_level = "2")
 
 # merge with attribute data with geodata
diff --git a/vignettes/eurostat_tutorial.md b/vignettes/eurostat_tutorial.md
index 75190307..b88060c7 100755
--- a/vignettes/eurostat_tutorial.md
+++ b/vignettes/eurostat_tutorial.md
@@ -840,9 +840,9 @@ The mapping examples below use
       # categorise
       dplyr::mutate(income = cut_to_classes(values, n = 5))
 
-    ## Table tgs00026 cached at /tmp/Rtmpn75WwS/eurostat/tgs00026_raw_code_FF.rds
+    ## Table tgs00026 cached at /tmp/Rtmpav96gu/eurostat/tgs00026_raw_code_FF.rds
 
-    # Download geospatial data from CISGO
+    # Download geospatial data from GISCO
     geodata <- get_eurostat_geospatial(output_class = "sf", resolution = "60")
 
     ## 
@@ -927,19 +927,25 @@ Interactive maps can be generated as well
     library(sf)
     library(RColorBrewer)
 
-    # Downloading and manipulating the tabular data 
-    euro_sf2 <- eurostat::get_eurostat("tgs00026", time_format = "raw", stringsAsFactors = FALSE) %>% 
-      # subsetting to year 2014 and NUTS-3 level
-      dplyr::filter(time == 2014, grepl("PL",geo)) %>% 
+    # Downloading and manipulating the tabular data
+    print("Let us focus on year 2014 and NUTS-3 level")
+
+    ## [1] "Let us focus on year 2014 and NUTS-3 level"
+
+    euro_sf2 <- get_eurostat("tgs00026", time_format = "raw",
+                             stringsAsFactors = FALSE,
+                 filter = list(time = "2014")) %>% 
+     
+      # Subset to NUTS-3 level
+      dplyr::filter(grepl("PL",geo)) %>% 
       # label the single geo column
       mutate(label = paste0(label_eurostat(.)[["geo"]], "\n", values, "€"),
              income = cut_to_classes(values))
 
-    ## Reading cache file /tmp/Rtmpn75WwS/eurostat/tgs00026_raw_code_FF.rds
+    print("Download geospatial data from GISCO")
 
-    ## Table  tgs00026  read from cache file:  /tmp/Rtmpn75WwS/eurostat/tgs00026_raw_code_FF.rds
+    ## [1] "Download geospatial data from GISCO"
 
-    # Download geospatial data from CISGO
     geodata <- get_eurostat_geospatial(output_class = "sf", resolution = "60")
 
     ## 
@@ -986,7 +992,7 @@ Interactive maps can be generated as well
     ## # --------------------------          
     ## 
 
-    # merge with attribute data with geodata
+    # Merge with attribute data with geodata
     map_data <- inner_join(geodata, euro_sf2)
 
     ## Joining, by = "geo"
@@ -1016,11 +1022,11 @@ Interactive maps can be generated as well
       # classifying the values the variable
       dplyr::mutate(cat = cut_to_classes(values))
 
-    ## Reading cache file /tmp/Rtmpn75WwS/eurostat/tgs00026_raw_code_FF.rds
+    ## Reading cache file /tmp/Rtmpav96gu/eurostat/tgs00026_raw_code_FF.rds
 
-    ## Table  tgs00026  read from cache file:  /tmp/Rtmpn75WwS/eurostat/tgs00026_raw_code_FF.rds
+    ## Table  tgs00026  read from cache file:  /tmp/Rtmpav96gu/eurostat/tgs00026_raw_code_FF.rds
 
-    # Download geospatial data from CISGO
+    # Download geospatial data from GISCO
     geodata <- get_eurostat_geospatial(output_class = "spdf", resolution = "10", nuts_level = 2)
 
     ## 
@@ -1052,7 +1058,7 @@ Interactive maps can be generated as well
 
     ## No encoding supplied: defaulting to UTF-8.
 
-    ## SpatialPolygonDataFrame at resolution 1: 10  cached at:  /tmp/Rtmpn75WwS/eurostat/spdf102.RData
+    ## SpatialPolygonDataFrame at resolution 1: 10  cached at:  /tmp/Rtmpav96gu/eurostat/spdf102.RData
 
     ## 
     ## # --------------------------
@@ -1097,11 +1103,11 @@ data as `data.frame` with `output_class` argument set as `df`.
       # classifying the values the variable
       dplyr::mutate(cat = cut_to_classes(values))
 
-    ## Reading cache file /tmp/Rtmpn75WwS/eurostat/tgs00026_raw_code_FF.rds
+    ## Reading cache file /tmp/Rtmpav96gu/eurostat/tgs00026_raw_code_FF.rds
 
-    ## Table  tgs00026  read from cache file:  /tmp/Rtmpn75WwS/eurostat/tgs00026_raw_code_FF.rds
+    ## Table  tgs00026  read from cache file:  /tmp/Rtmpav96gu/eurostat/tgs00026_raw_code_FF.rds
 
-    # Download geospatial data from CISGO
+    # Download geospatial data from GISCO
     geodata <- get_eurostat_geospatial(output_class = "df", resolution = "60", nuts_level = "2")
 
     ## 
diff --git a/vignettes/fig/maps2-1.pdf b/vignettes/fig/maps2-1.pdf
index 4c466388..026c75ec 100644
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diff --git a/vignettes/fig/plotGallery-1.pdf b/vignettes/fig/plotGallery-1.pdf
index b2222ed6..564726db 100644
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diff --git a/vignettes/fig/trains_plot-1.pdf b/vignettes/fig/trains_plot-1.pdf
index f6324e12..2b13f871 100644
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