Description Usage Arguments Details Author(s) See Also Examples
This function ouputs a pie map from the dataset provided as input
1 2 3 |
con |
a wrapper of rpostgresql connection (connection to a database) |
df_input |
data.frame to map |
dimension_group_by |
string. Name of the dimension that will be the classes in the pies or NULL if no aggregation dimension. |
df_spatial_code_list_name |
string. Name of the spatial coding system used in df_input (column 'geographic_identifier') |
area_filter_wkt |
sting. A spatial filter (WKT format) or NULL if no spatial filter. |
number_of_classes |
integer. Number of classes to visualize in the pies. |
function_pie_size |
string. square_root, square, proportional, unique |
bounding_box |
vector of bounding box for vizualisation (c(xmîn,xmax,ymin,ymax)) |
All values in df_input
must be expressed with the same unit (since the function aggregates the data).
Column of spatial codes must be named 'geographic_identifier'.
Paul Taconet, paul.taconet@ird.fr
Other visualize data: functions_visualize_data
,
time_series_plot
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | # Connect to Tuna atlas database
con<-db_connection_tunaatlas_world()
# Extract IOTC (Indian Ocean) georeferenced catch time series of catches from Sardara DB, in 5° resolution
ind_catch_tunaatlasird_level2<-extract_dataset(con,list_metadata_datasets(con,identifier="indian_ocean_catch_5deg_1m_1952_11_01_2016_01_01_tunaatlasIRD_level2"))
head(ind_catch_tunaatlasird_level2)
# filter the data to keep only catches on log schools in 2014:
ind_catch_tunaatlasird_level2 <- ind_catch_tunaatlasird_level2 %>% filter (year==2014) %>% filter (schooltype=="LS")
# Map the catches made on log schools in 2014 by species:
pie_map(con,
df_input=ind_catch_tunaatlasird_level2,
dimension_group_by="species",
df_spatial_code_list_name="areas_tuna_rfmos_task2",
number_of_classes=4
)
dbDisconnect(con)
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