Color palette inspired by this gorgeous image of Mars landscape, captured by HiRISE (NASA) and processed by Seán Doran. I created this color scale with the help of Chroma.js Color Palette Helper.
Image credit: HiRISE & Seán Doran``` | |
################# 4) Build a Balanced Panel data set ------------------------------ | |
# data with one observation for each area each day, even if there was no notification on that day/area | |
# get all dates and munis | |
all_munis <- unique(df$code_muni) | |
all_dates <- seq(min(df$DT_NOTIFIC), | |
max(df$DT_NOTIFIC), | |
by = "day") |
In this gist we show with a reproducible example how to create an animation of public transport networks using GTFS data in R
. We use a few packages to do this. One of the core packages here is the new gtfs2gps. The gtfs2gps package converts public transport data in GTFS format to GPS-like records in a data.frame/data.table
, which we will be using to create a .gif
with the gganimate
package.
The first step is to process a GTFS.zip
file. The function gtfs2gps{gtfs2gps}
interpolates the space-time position of each vehicle in each trip considering the network distance and average speed between stops. The output is a data.table
where each row represents the timestamp of each vehicle at a given spatial resolution. In this example, we use a sample of the public transport network of Sao Paulo (Brazil) mapped e
Using R
and the geobr package to plot Brazilian metropolitan areas in different years.
library(geobr)
library(dplyr)
library(ggplot2)
library(sf)
### how to use R to find your most popular tweet of 2019 | |
# code by @nnstats | |
library(rtweet) | |
library(tidyverse) | |
library(lubridate) | |
show_most_popular_tweet <- function(user, year){ | |
y <- year |
# Libraries | |
library(geobr) | |
library(leafgl) | |
library(leaflet) | |
library(sf) | |
library(colourvalues) | |
# get data of disaster risk areas in Brazil using the geobr package |
The data.table
package has the operator %like%
, which is super handy for partial string matching:
"system with blue screen" %in% "blue"
> FALSE
"system with blue screen" %like% "blue"
> TRUE