RunyangWang

# Load packages
library("plotly")
library("tidyverse")
library("data.table")
library("gridExtra")
library("knitr")

data <- read_csv("athlete_events.csv",
                 col_types = cols(
                   ID = col_character(),

RunyangWang

require(altair)
require(fmsb)
require(dplyr)


#Year 1996, Tier 1
d1996t1 <- as.data.frame(rbind(c(100,100,100,78,76),c(86,100,30,74,77),c(72,100,55,73,66)))
colnames(d1996t1) <- c("GDP" , "Primary School Enrollment" , "Population" , "Urban Population", "Life Expectancy at Birth")
rownames(d1996t1) <- c("US", "Germany", "Russia")

RunyangWang

{
  "$schema": "https://vega.github.io/schema/vega/v5.json",
  "width": 800,
  "height": 400,
  "padding": 0,
  "autosize": "none",
  "signals": [
    {
      "description": "Any datapoint is activated",
      "name": "datapoint_is_activated",

RunyangWang

{
  "$schema": "https://vega.github.io/schema/vega-lite/v4.json",
  "width": "container",
  "height": "container",
  "data": {
    "url": "https://raw.githubusercontent.com/vda-lab/vda-lab.github.io/master/assets/station_366.json"
  },
  "transform": [
    {
      "filter": {"field": "endstation_id", "equal": "336"}

RunyangWang

{
  "$schema": "https://vega.github.io/schema/vega-lite/v4.json",
  "width": "container",
  "height": "container",
  "data": {
    "url": "https://raw.githubusercontent.com/vda-lab/vda-lab.github.io/master/assets/station_366.json"
  },
  "transform": [
    {
      "filter": {"field": "endstation_id", "equal": "336"}

RunyangWang

{
  "$schema": "https://vega.github.io/schema/vega-lite/v4.json",
  "width": "container",
  "height": "container",
  "data": {
    "url": "https://raw.githubusercontent.com/vda-lab/vda-lab.github.io/master/assets/station_366.json"
  },
  "transform": [
    {
      "filter": {"field": "tripduration", "lte": "5000"}