solmos

library(httr)
library(jsonlite)
library(rfeb)

# Función para obtener los resultados de los partidos que aparecen en Baloncesto en Vivo en este momento
# competition puede ser: "Liga LEB Oro", "Liga Dia", "Liga LEB Plata", "L.F.-2", "EBA"
get_round_results <- function(competition = "Liga LEB Oro") {
    api <- GET("http://baloncestoenvivo.feb.es/api/OverView/")
    data_json <- content(api, as = "text", encoding = "UTF-8")
    data <- fromJSON(data_json)

solmos

library(tidyverse)

pbp2018 <- read_csv("pbp2018.csv")

pbp2018 %>% 
  group_by(player_name) %>% 
  summarise(
    # Partidos disputados
    games = length(unique(game_code)),
    # Tiros de 2 anotados

solmos

# Elo Rating System

library(eurolig)
library(tidyverse)
library(lubridate)

load("data/results.rds")

# Helpers -----------------------------------------------------------------

solmos

## Scorekeeper bias in LEB Oro

library(tidyverse)

data_file <- "https://github.com/solmos/feb-data/raw/master/assists-leb-oro.csv"
assists_leb_oro <- read_csv(data_file)

# Players -----------------------------------------------------------------

ast_player <- assists_leb_oro %>%

solmos

readFireCounts <- function(file) {
  fire_counts <- read_delim(file, delim = ";") %>%
    rename(date = "ACQ_DATE") %>%
    count(date) %>%
    as_tibble()
  dates_expanded <- seq(min(fire_counts$date), max(fire_counts$date), by = "days")
  fires_full <- tibble(date = dates_expanded) %>%
    left_join(fire_counts) %>%
    mutate(
      day = day(date),

solmos

library(tidyverse)
library(tidync)

readNcFiles <- function(files, lat_range = c(8, 37), lon_range = c(68, 98)) {
  nc_list <- map(files, tidync)
  names(nc_list) <- files

  filterNc <- function(nc, lat_range = c(8, 37), lon_range = c(68, 98)) {
    nc %>%
      hyper_filter(LAT = between(LAT, lat_range[1], lat_range[2]),

solmos

library(dplyr)

## Create similar but simpler data frame to yours
df <- data.frame(
  scenario = rep(1:3, 2),
  year = rep(2010:2011, each = 3),
  age_25_29 = rnorm(6),
  age_30_34 = rnorm(6),
  age_35_39 = rnorm(6)
)

solmos

library(splines)
library(dplyr)
library(readr)
library(tidyr)
library(ggplot2)

## Use your path
df <- read_csv("data.csv") %>%
  select(fever, mean.anom.4w, water.safe)

solmos

git clone --depth=1 --single-branch 
--branch emacs-27 https://github.com/emacs-mirror/emacs.git

cd emacs/

sudo apt install -y autoconf make gcc texinfo libgtk-3-dev libxpm-dev \
     libjpeg-dev libgif-dev libtiff5-dev libgnutls28-dev libncurses5-dev \
     libjansson-dev libharfbuzz-dev libharfbuzz-bin

./autogen.sh

solmos

library(tidyverse)

## Simple example dataset
time_on_study <- tibble(
  id = 1:5,
  start_followup = 0,
  time_followup = c(2, 4, 3, 1, 3),
  age_baseline = c(18, 30, 28, 20, 18),
  event = factor(c(1, 0, 1, 1, 0), labels = c("Censored", "Event"))
)