yaojenkuo

from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import time
import random
import pandas as pd

def get_github_activities(keywords):
    '''
    Getting search results of activities from GitHub
    keywords: an iterable of the key-words to search on GitHub, e.g. ['TensorFlow', 'Pytorch']

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import plotly

plotly.offline.init_notebook_mode()
trace_rep = plotly.graph_objs.Bar(x = dl_activities.repositories, y = dl_activities.keyword, name = "Repositories", orientation = 'h', marker = dict(color = 'rgba(0, 0, 255, 1)'))
trace_commits = plotly.graph_objs.Bar(x = dl_activities.commits, y = dl_activities.keyword, name = "Commits", orientation = 'h', marker = dict(color = 'rgba(255, 165, 0, 1)'))
trace_issues = plotly.graph_objs.Bar(x = dl_activities.issues, y = dl_activities.keyword, name = "Issues", orientation = 'h', marker = dict(color = 'rgba(0, 255, 0, 1)'))
trace_wikis = plotly.graph_objs.Bar(x = dl_activities.wikis, y = dl_activities.keyword, name = "Wikis", orientation = 'h', marker = dict(color = 'rgba(255, 0, 0, 1)'))
data = [trace_rep, trace_commits, trace_issues, trace_wikis]
updatemenus = list([
    dict(

yaojenkuo

library(RSelenium)

# Define function
get_zipped_csv <- function(x) {
  for (indicator in x) {
    remDr$navigate("https://data.worldbank.org/")
    query_box <- remDr$findElement(using = 'css', "#selector")
    # Keyboard input
    query_box$sendKeysToElement(list(indicator))
    Sys.sleep(5)

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library(tidyr)
library(magrittr)
library(dplyr)

get_tidy_df <- function(x) {
  setwd(x)
  ex_dir <- paste0(x, "/world_bank_csv")
  zipfiles <- c("API_NY.GDP.PCAP.CD_DS2_en_csv_v2.zip", "API_SP.DYN.LE00.IN_DS2_en_csv_v2.zip", "API_SP.POP.TOTL_DS2_en_csv_v2.zip")
  for (zipfile in zipfiles) {
    unzip(zipfile, exdir = ex_dir)

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region_list <- tidy_df$Region %>%
  unique()

# Define UI for application that mimics a Gapminder visualization
shinyUI(fluidPage(
  
  # Application title
  titlePanel("Gapminder Replica"),
  
  # Sidebar with a slider input for year 

yaojenkuo

# Define server logic required to draw a Gapminder visualization
shinyServer(function(input, output) {
  
  tidy_data <- reactive(
    tidy_df %>%
      filter(Region %in% input$regions)
  )
  output$bubble <- renderPlotly({
    
    # draw the bubble chart with the specified continents or year

yaojenkuo

# global.R template for Plotly/Shiny apps

library(plotly)
library(shiny)
library(magrittr)
library(dplyr)

py <- plot_ly(username="rAPI", key="yu680v5eii")
tidy_df <- read.csv("data/tidy_df.csv", stringsAsFactors = FALSE)
bubble_radius <- sqrt(tidy_df$pop / pi)

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#This script is necessary in the app folder
#but the user should not have to edit it

#Output Graph Function
graphOutput <- function(inputId, width="100%", height="550px") {
  tagList(
    singleton(tags$head(
      tags$script(src="plotlyGraphWidget.js")
    )),
    tags$iframe(id=inputId, src="https://plot.ly/~playground/7.embed",

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var binding = new Shiny.OutputBinding();

binding.find = function(scope) {
    // not sure what this function does, or
    // why its necessary...
    console.log('binding.scope');
    return $(scope).find('.graphs');
};

binding.renderValue = function(el, messages) {

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def get_runner_record(url):
    driver.get(url)
    odd_even_l = ['OL', 'EL']
    odd_even_r = ['OR', 'ER']
    runner_record = {
        'bib_num': [],
        'name': [],
        'cate': [],
        'official_time': [],
        'rank_all': [],