I would like to store into a csv file the list of all public funded projects in France, which are listed in the website below:
I used the websste API to get the JSON file containing all the projects, with the following command (using "jsonlite" package):
my_url <- "https://aides-territoires.beta.gouv.fr/api/aids/all/"
results <-
httr::content(
httr::GET(my_url),
as="text",
httr::content_type_json(),
encoding= "UTF-8"
)
The problem is after... I am totally beginner with JSON files manipulation, and I do not manage to transpose the information which is contained in "results" to a data frame, with column names corresponding to each project ("id","slug","url","name",etc.). Some project items are lists, others are character vectors, etc.
I tried some commands I found such as below:
df <- data.frame(
lapply(c("id","slug","url","name","name_initial","short_title","financers",
"instructors","programs","description","eligibility","perimeter",
"mobilization_steps","origin_url","is_call_for_project",
"application_url","is_charged",
"destinations","start_date","predeposit_date","submission_deadline",
"subvention_rate_lower_bound","subvention_rate_upper_bound",
"loan_amount","recoverable_advance_amount","contact","recurrence",
"project_examples","import_data_url","import_data_mention",
"import_share_licence","date_created","date_updated"),
function(x){fromJSON(results,flatten = TRUE)$results[[x]]})
)
But I get the message below:
Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows: 1, 2, 0, 3, 4, 11, 7, 5, 15
With httr2 package you can do:
library(tidyverse)
library(httr2)
"https://aides-territoires.beta.gouv.fr/api/aids/all/" %>%
request() %>%
req_perform() %>%
resp_body_json(simplifyVector = TRUE) %>% # SimpplifyVector is the real hero
pluck("results") %>% # Grab the results list
as_tibble() # Create a tibble
# A tibble: 3,282 × 31
id slug url name short_title financers instructors programs
<int> <chr> <chr> <chr> <chr> <list> <list> <list>
1 70202 2d94-se-former… /aid… Se f… "" <chr [1]> <chr [0]> <chr>
2 8075 ae3b-etude-reh… /aid… Mett… "" <chr [1]> <chr [0]> <chr>
3 117392 c650-preserver… /aid… Prés… "" <chr [1]> <chr [0]> <chr>
4 117180 e8e0-soutenir-… /aid… Sout… "" <chr [1]> <chr [0]> <chr>
5 78196 ef73-soutenir-… /aid… Sout… "" <chr [1]> <chr [0]> <chr>
6 22827 c372-aide-a-la… /aid… Fina… "" <chr [1]> <chr [0]> <chr>
7 90762 6564-creer-une… /aid… Crée… "" <chr [2]> <chr [0]> <chr>
8 30762 9e6a-soutien-d… /aid… Sout… "" <chr [1]> <chr [0]> <chr>
9 90797 f299-activites… /aid… Sout… "" <chr [1]> <chr [0]> <chr>
10 94752 46de-accelerer… /aid… Déve… "" <chr [2]> <chr [0]> <chr>
# … with 3,272 more rows, and 23 more variables: description <chr>,
# eligibility <chr>, perimeter <chr>, mobilization_steps <list>,
# origin_url <chr>, categories <list>, is_call_for_project <lgl>,
# application_url <chr>, targeted_audiences <list>, aid_types <list>,
# destinations <list>, start_date <chr>, predeposit_date <chr>,
# submission_deadline <chr>, subvention_rate_lower_bound <int>,
# subvention_rate_upper_bound <int>, loan_amount <int>, …