schochastics

library(tidyverse)
library(rvest)
library(ggimage)
library(lubridate)

#get first 25 leagues in Europe ----
url <- "https://www.transfermarkt.de/wettbewerbe/europa"
doc <- read_html(url)

leagues <- doc %>% html_nodes(".hauptlink a") %>% html_attr("href")

schochastics

#install UMAP from https://github.com/lmcinnes/umap
#install.packages("rPython")

umap <- function(x,n_neighbors=10,n_components=2,min_dist=0.1,metric="euclidean"){
  x <- as.matrix(x)
  colnames(x) <- NULL
  rPython::python.exec( c( "def umap(data,n,d,mdist,metric):",
                           "\timport umap" ,
                           "\timport numpy",
                           "\tembedding = umap.UMAP(n_neighbors=n,n_components=d,min_dist=mdist,metric=metric).fit_transform(data)",

schochastics

#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
double SampleEntropy(NumericVector data, int m, double r, int N, double sd)
{
  int Cm = 0, Cm1 = 0;
  double err = 0.0, sum = 0.0;
  
  err = sd * r;

schochastics

schochastics

################################################################################
# replication of https://i.redd.it/q0udc4wfhvjz.gif
# originally posted to r/dataisbeautiful by u/Tjukanov
################################################################################
library(tidyverse)
library(gganimate)
library(lubridate)

#data from: https://www.ncdc.noaa.gov/ibtracs/index.php?name=wmo-data
df <- read_csv("Allstorms.ibtracs_wmo.v03r09.csv")