README.md

In matteodefelice/panas: Reduce the friction when working with maps & time-series

panas

The goal of this package is to reduce the friction when working with maps & time-series.

It provides two main functionalities: the visualisation of gridded data & choropleths, and the aggregation from gridded data to time-series using geographical borders.

The package is not available on CRAN, you can get the development version from github using devtools:

devtools::install_github("matteodefelice/panas")

Load the panas package:

library(panas)

Dealing with NUTS boundaries

The function get_region_from_coordinates returns the NUTS region where a set of points lie.

> x = data.frame(lat = c(48.5, 49), lon = c(12, 4))
> get_region_from_coordinates(x, shapefile = 'NUTS1')
[1] DE2 FRF
121 Levels: AL0 AT1 AT2 AT3 BE1 BE2 BE3 BG3 BG4 CH0 CY0 ... UKN

Visualisation

This package gives you the possibility to visualise gridded data with the function plot_field_discrete and choropleths using NUTS classification (this means only Europe).

Gridded data

> data(ncep)
> g = plot_field_discrete(z, lon, lat, latlim = c(-30, 70), breaks = c(5e-5, 1e-4), color_scale = 'PuBu', varname = 'prec.', grid_step = 60)
> print(g + coord_equal())

Choropleths

> my_data = tibble(area = c('IT', 'ITC', 'UKG', 'ITC1'), value = c('a','b','b', 'c'))
> g = get_european_choropleth(my_data)
> print(g + coord_map('lambert', 35, 58, ylim = c(35, 68), xlim = c(-15, 25)))

matteodefelice/panas documentation built on March 4, 2020, 4:19 a.m.