favstats

# Import the required modules
from selenium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
import time
import json

def get_perf_log_on_load(url, headless = True, filter = None):
    
    # Main Function
    # Enable Performance Logging of Chrome.

favstats

library(tidyverse)
library(rvest)
library(ggpubr)
library(COVID19)

## 1st step:
# go to http://www.sharkattackdata.com/place/united_states_of_america
## 2nd step:
# save HTML file to same location as script

favstats

library(tidyverse)

## this r code is taking from here: https://github.com/mkearney/pkguse
read_r_files <- function(...) {
    dirs <- unlist(list(...))
    r <- unlist(lapply(dirs, list.files,
                       pattern = "\\.(R|Rmd|Rmarkdown|rmd|r|Rhistory)$",
                       recursive = TRUE,
                       full.names = TRUE,
                       all.files = TRUE))

favstats

#===============================================================================
# 2022-07-12
# Extract data from Latent GOLD within R
# Fabio Votta (@favstats)
#===============================================================================

library(tidyverse)
library(data.table)

setwd(here::here())

favstats

#===============================================================================
# 2022-07-10
# Year progress twitter
# Fabio Votta (@favstats)
# Idea blatantly stolen from Ilya Kashnitsky (@ikashnitsky)
#===============================================================================

library(tidyverse)
library(magrittr)
library(lubridate)

favstats

save_csv <- function(d, path) {
  
  if(file.exists(path)){
    readr::write_csv(d, append = T, file = path)
  } else {
    
    dirs_to_create <- stringr::str_split(path, "\\/") %>% 
      unlist() %>% 
      purrr::discard(~stringr::str_detect(.x, "\\.")) %>% 
      paste0(collapse = "/")

favstats

library(tidyverse)
library(httr)

token <- Sys.getenv("fb_marketing_token")

#link to fb api
my_lin k<- "https://graph.facebook.com"

#define fields you are interested in
search_fields=c("ad_creation_time", 

favstats

library(tidyverse)
library(modelbased)
library(magrittr)

overview <- readRDS("data/overview.rds")

## helper function
get_plabs <- function (pval) {
  dplyr::case_when(is.na(pval) ~ "", pval < 0.001 ~ "***", 
                   pval < 0.01 ~ "**", pval < 0.05 ~ "*", 

favstats

  ## Create NYT Spiral Animations
  ## Most Code comes from here: https://bydata.github.io/nyt-corona-spiral-chart/
  
  
  library(tidyverse)
  library(lubridate)
  library(gganimate)
  library(viridis)
  
  owid_url <- "https://github.com/owid/covid-19-data/blob/master/public/data/owid-covid-data.csv?raw=true"

favstats

### Code mostly inspired by https://github.com/HudsonJamie/tidy_tuesday/blob/main/2021/week_46/afrilearndata.R

library(pdftools)
library(tidygeocoder)
library(tidyverse)
library(janitor)
library(rgdal)
library(osmdata)
library(sf)
library(ggfx)