fifaWorldCup

Output R

plot_ly(data=df_rankings2,x=~logGDP,y=~fifaRanking,type='scatter',mode='markers') %>% 
  add_trace(text=~nombrePais,
            color=~catColor_GDP,
            marker = list(size = 10)
            ) %>% 
  add_trace(y=~prediccion,mode='lines') %>% 
  add_text(x=28,y=200,text='<b>Corr= -0.6</b>',
           textfont = list(color = '#000000', size = 18))

Codigo Python:

from selenium import webdriver #check
from selenium.webdriver.common.by import By #check
from selenium.webdriver.support.ui import WebDriverWait #check
from selenium.webdriver.support import expected_conditions as EC #check
from selenium.webdriver.common.keys import Keys #check
import os 
import wget 
import time 


#jalando info de Fifa Ranking
chrome_options = webdriver.ChromeOptions()
prefs = {"profile.default_content_setting_values.notifications" : 2}
chrome_options.add_experimental_option("prefs",prefs)
chrome_options.add_argument('--no-sandbox')

#specify the path to chromedriver.exe (download and save on your computer)
driver = webdriver.Chrome('D:\Downloads_D\chromedriver_win32\chromedriver.exe', chrome_options= chrome_options)

#open the webpage
driver.get("https://www.fifa.com/fifa-world-ranking/men?dateId=id13407")
time.sleep(5)
button = WebDriverWait(driver, 2).until(EC.element_to_be_clickable((By.CSS_SELECTOR, "#onetrust-accept-btn-handler"))).click()


time.sleep(5)


nombrePais=[]
elRanking=[]

for j in range(5):
    todasLasRows=driver.find_elements_by_class_name("fc-ranking-item-full_rankingTableFullRow__1nbp7")
    for i in todasLasRows:
        #paises
        estePais=i.find_elements_by_css_selector("td")[2].find_elements_by_css_selector("span")[0].text
        nombrePais.append(estePais)

        esteRank=i.find_elements_by_css_selector("td")[0].text
        elRanking.append(esteRank)

    #ir a siguiente pagina
    if j<= 3:
        driver.find_elements_by_css_selector(".fc-pagination_iconColor__3TNop")[1].click()
        time.sleep(5)
        

import pandas as pd 

df_Fifa=pd.DataFrame(nombrePais).reset_index()


### Haciendo lo mismo para el PIB

#specify the path to chromedriver.exe (download and save on your computer)
driver = webdriver.Chrome('D:\Downloads_D\chromedriver_win32\chromedriver.exe', chrome_options= chrome_options)

#open the webpage
driver.get("https://www.worldometers.info/gdp/gdp-by-country/")
time.sleep(5)
driver.find_elements_by_class_name("cc-dismiss")[0].click()

time.sleep(5)
filas = driver.find_elements_by_css_selector("tbody")[0].find_elements_by_css_selector("tr")

vectorDiccionarios = []
for i in filas:
    columnas = i.find_elements_by_css_selector("td")
    elDiccionario = {
        'elRanking': columnas[0].text,
        'nombrePais': columnas[1].text,
        'GPD': columnas[2].text,
        'GDPgrowth': columnas[4].text,
        'Population': columnas[5].text,
        'GDPcapita': columnas[6].text,
        'shareWorldGDP': columnas[7].text
    }

    vectorDiccionarios.append(elDiccionario)
    
    
### Guardando DF

df_gdp=pd.DataFrame(vectorDiccionarios)

df_gdp.to_excel("gdpMundia.xlsx")

df_Fifa.to_excel("fifaRank.xlsx")