Open ibidyouadu opened 2 years ago
A nearly complete dataset is found in the dive surveys project. The only columns missing are level1_name
and level2_name
. To get these, we can map the information from global footprint data.
The idea is to take an ma_name
from the nearly complete dataset and find a row in the footprint data with that ma_name
. Then grab the level1_name
and level2_name
of that row. This assumes that there is a one-to-one mapping between ma_name
and level1_name
-level2_name
pairs. As it turns out, there is not. Here is the result of checking for ma_names
with different level1_name
-level2_name
pairs:
country level1_name level2_name ma_name
<fct> <fct> <fct> <fct>
1 Brazil Pará Augusto Corrêa RESEX Marinha de Araí-Pe…
2 Brazil Pará Augusto Corrêa RESEX Marinha Mestre Luc…
3 Brazil Pará Maracanã RESEX Maracanã
4 Brazil Pará Maracanã RESEX Marinha Mestre Luc…
5 Brazil Pará Marapanim RESEX Marinha Mestre Luc…
6 Brazil Pará Marapanim RESEX Marinha de Araí-Pe…
7 Brazil Pará Marapanim RESEX Maracanã
8 Honduras Islas de la Bahía Roatán Roatan
9 Honduras Islas de la Bahía Jose Santos Guardio… Roatan
10 Federated States of Microne… Pohnpei Nett Kolonia - Nett
11 Federated States of Microne… Pohnpei Kolonia Kolonia - Nett
The managed access areas from Brazil and FSM are no problem since the dashboard currently does not show data from there. But the newest data is made up entirely of Roatan data. So then we cannot map simply ma_name
to level1_name
/level2_name
; we need another distinguishing column besides ma_name
. Looking at the footprint data, there doesn't seem to be any. Thus the current problem is that the newest data will have NA level1_name
and level2_name
.
Either dig around the data.world datasets more or simply remove filtering by subnational/local gov't.
Included 2021 IDN fish data with d812799
The script previously used to update code (not in this repo but in the Ecological_Dashboard repo) is pretty simple:
fish.surveys <- data.table::fread("https://query.data.world/s/beo5xpafq24c45b4a6bdzvbgxa3c5l", ... )
The problem is that that link is dead. And looking at the fish surveys dataset, it is not obvious what the query to produce
fish.surveys
was. Sure, a lot of the columns are there in separate files and it will take a few joins, but there's still some columns missing, namely the subnational and local regions. Digging around through the other Rare datasets, it looks like this missing info may be completely available in various datasets from the global footprint datasets. Look into these