output from WGRDBES-EST 2023.
This functions requires the user to specify a variable of interest and produce a barplot.
The function allows to treat landing, effort and sampling data.
The user can addionally add one or more grouping variable.
Parameters of the functions:
RDBESobj = RDBESobject to be explored.
var = Variable of interest (to be plotted).
by = One (or more) factor(s) to split the data.
year = year(s) to filter the data.
output_type: one of (table | plot).
The output of the function depends on the user selection. We see three main group of outputs depending on the nature of the data to be visualized.
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Effort: if the user chooses effort related columns, the function can represent hours, days at sea, power (kW), number of trips, etc… . Possible splitting variables are in this case: area, metier, vessel length, quarter.
-
Landing: if the user chooses landing related columns, the function can represent weight and value.
Possible splitting variables are in this case: area, metier, vessel length, species (group of species?), catch category (LAN, REGDIS, BMS), landing country.
-
Sampling: if the user chooses sampling data, the function can represent
i. n trips
ii. n samples
iii. n auction days
iv. n species sampled
v. n individuals sampled
Possible splitting variables are in this case: Species, Area[ICES Division, ICES Sd., ICES Rect], Time [Year, Semester, Quarter, Month].
output from WGRDBES-EST 2023.
This functions requires the user to specify a variable of interest and produce a barplot.
The function allows to treat landing, effort and sampling data.
The user can addionally add one or more grouping variable.
Parameters of the functions:
RDBESobj = RDBESobject to be explored.
var = Variable of interest (to be plotted).
by = One (or more) factor(s) to split the data.
year = year(s) to filter the data.
output_type: one of (table | plot).
The output of the function depends on the user selection. We see three main group of outputs depending on the nature of the data to be visualized.
Effort: if the user chooses effort related columns, the function can represent hours, days at sea, power (kW), number of trips, etc… . Possible splitting variables are in this case: area, metier, vessel length, quarter.
Landing: if the user chooses landing related columns, the function can represent weight and value.
Possible splitting variables are in this case: area, metier, vessel length, species (group of species?), catch category (LAN, REGDIS, BMS), landing country.
Sampling: if the user chooses sampling data, the function can represent
i. n trips
ii. n samples
iii. n auction days
iv. n species sampled
v. n individuals sampled
Possible splitting variables are in this case: Species, Area[ICES Division, ICES Sd., ICES Rect], Time [Year, Semester, Quarter, Month].