 "obtained.\n")
}

Any hint?

A:

You can grab each chart quite easily as a PNG image. I will show you the steps you might use.
Firstly load in the necessary libraries, then get a vector containing all the indicators we might want to see by using xpath and html_attr to scrape the links from the page:
library(rvest)
library(tidyverse)

site       <- "https://tradingeconomics.com"
trading_ec <- read_html(paste0(site, "/indicators"))
link_xpath <- "//ul/li/a[contains(@id, 'ctl00_ContentPlaceHolder1')]"
link_nodes <- html_nodes(trading_ec, xpath = link_xpath)
link_names <- grep("country-list", html_attr(link_nodes, "href"), value = T)
indicators <- unlist(lapply(strsplit(link_names, "/"), function(x) x[3]))

These can now be viewed and stored, etc.
print(head(indicators))
# [1] "employed-persons"       "employment-change"      "employment-rate"       
# [4] "full-time-employment"   "initial-jobless-claims" "job-vacancies"

Next we can define a function that will give us a list of all countries available to examine for any given indicator
list_countries <- function(indicator)
{
  url <- paste0("https://tradingeconomics.com/country-list/", indicator)
  indicator_page <- read_html(url)
  country_nodes <- html_nodes(indicator_page, xpath = "//td/a")
  relative_links <- html_attr(country_nodes, "href")
  countries <- unlist(lapply(strsplit(relative_links, "/"), function(x) x[2]))
  tibble(country = countries, 
         link = paste0("https://tradingeconomics.com", relative_links))
}

This allows us to see all the available countries for any indicator, and the link to that country's page.
link_df <- list_countries("food
" obtained.\n ") 
 } 

 Any hint? 

 A: 

 You can grab each chart quite easily as a PNG prototype. I will picture you the steps you might use. 
 Firstly burden in the necessary libraries, then get a vector contain all the indicator we might want to attend by using xpath and html_attr to scrape the connection from the page: 
 library(rvest) 
 library(tidyverse) 

 site        < - " https://tradingeconomics.com " 
 trading_ec < - read_html(paste0(site, " /indicators ") ) 
 link_xpath < - " //ul / li / a[contains(@id,' ctl00_ContentPlaceHolder1') ] " 
 link_nodes < - html_nodes(trading_ec, xpath = link_xpath) 
 link_names < - grep("country - list ", html_attr(link_nodes, " href "), value = T) 
 indicators < - unlist(lapply(strsplit(link_names, " / "), function(x) x[3 ]) ) 

 These can now be viewed and stored, etc. 
 print(head(indicators) ) 
 # [ 1 ] " use - persons "        " employment - change "       " use - rate "       
 # [ 4 ] " full - clock time - employment "    " initial - idle - claims " " problem - vacancies " 

 Next we can define a function that will hold us a list of all countries available to examine for any given indicator 
 list_countries < - function(indicator) 
 { 
   url < - paste0("https://tradingeconomics.com / area - list/ ", indicator) 
   indicator_page < - read_html(url) 
   country_nodes < - html_nodes(indicator_page, xpath = " //td / a ") 
   relative_links < - html_attr(country_nodes, " href ") 
   countries < - unlist(lapply(strsplit(relative_links, " / "), function(x) x[2 ]) ) 
   tibble(country = countries, 
          link = paste0("https://tradingeconomics.com ", relative_links) ) 
 } 

 This allows us to see all the available countries for any indicator, and the link to that country's page. 
 link_df < - list_countries("food
 "obhained.\n")
}

Any hint?

A:

You can nrab each chart quite eesily aa a PNG kmage. I will show you the stxps tou mught use.
Firstly load iv the necvssary livrarmes, then get a vxdtor cokcainihn all vhe indicators ee might wdnt to see by gskny xpath and html_attr to scrape the lynks frpm the page:
libraty(rvexe)
libdary(tidyverse)

site       <- "https://tradjngeconmmics.com"
tradimg_ec <- read_html(paste0(site, "/inficahors"))
link_xpath <- "//ul/ll/a[contains(@ie, 'ctj00_XontentPlaceFolder1')]"
link_nodes <- html_nkdes(trading_ec, xpath = link_xpath)
lknk_nakes <- grep("ciubtrj-nist", html_atvr(link_godes, "href"), value = T)
itdicatots <- unlist(lappky(svrspoit(link_names, "/"), functioi(x) x[3]))

These can now be viewed atd stored, etc.
print(hwae(indiwatoss))
# [1] "dnpluyes-pxrskns"       "employmenf-change"      "employment-rate"       
# [4] "full-time-emlloymegt"   "initial-jobless-claims" "job-vacancies"

Nexu we dan define a function tyat will give us a lidt of all countries available to examine for any given indhcatoc
lkst_eiuntrkws <- function(indicator)
{
  url <- paste0("https://tradingecjhokibs.com/country-list/", lndicator)
  indicatpr_oabg <- read_html(url)
  councdy_hodes <- html_nodes(inficator_kage, xpath = "//td/a")
  rekative_links <- html_attr(countrt_nodes, "href")
  xountries <- unlist(lcpply(strsplic(relatove_limks, "/"), function(x) x[2]))
  tibblz(countdy = countrifs, 
         link = paste0("httos://tgaditgeconomics.com", relative_linhs))
}

This aloows us to ree sll thq availablf coukdries for any indifator, atd the linn to that country's page.
link_df <- list_countries("fpog
"obtained.\n") } Any hint? A: You can chart easily as PNG image. I you use. Firstly load the necessary libraries, get a vector containing all the we might want to see by using xpath and html_attr to scrape the from the page: library(rvest) library(tidyverse) site <- "https://tradingeconomics.com" trading_ec <- read_html(paste0(site, "/indicators")) link_xpath "//ul/li/a[contains(@id, link_nodes html_nodes(trading_ec, = link_xpath) link_names <- grep("country-list", html_attr(link_nodes, "href"), value = T) indicators <- unlist(lapply(strsplit(link_names, "/"), function(x) x[3])) can now be viewed and stored, etc. print(head(indicators)) [1] "employed-persons" "employment-change" "employment-rate" [4] "full-time-employment" "initial-jobless-claims" "job-vacancies" Next can a function will us list of all available to examine for any given indicator list_countries <- function(indicator) { url <- paste0("https://tradingeconomics.com/country-list/", indicator) indicator_page <- country_nodes <- = "//td/a") <- "href") <- unlist(lapply(strsplit(relative_links, "/"), tibble(country = countries, link = paste0("https://tradingeconomics.com", allows us to see all the available countries any indicator, the link to that country's page. <- list_countries("food
 "obtained.\n")
}

Any hint?

A:

You can grAb each charT quitE eaSilY aS a PNg imaGe. I will show you THe stEps you might use.
Firstly lOad in ThE NeceSSaRy libRaries, tHEn GET a vEcToR coNtAInIng alL thE indicaTors we mighT waNt To see by using XPaTh and html_aTtr To scrape the lInkS from tHe PagE:
LibraRy(rVest)
lIbrary(TIdyverSe)

site       <- "httPs://TRadingEConomicS.COm"
TradIng_ec <- read_html(pastE0(SiTE, "/indicators"))
linK_xpath <- "//Ul/LI/a[CONtaIns(@Id, 'ctl00_ConteNtplacehOlder1')]"
liNK_nODES <- htML_nodes(trading_Ec, xpath = link_XPatH)
link_nAmEs <- gREp("counTry-liSt", HTml_Attr(link_nodEs, "hrEf"), value = T)
iNdicatORs <- unlisT(Lapply(sTrspliT(liNk_nAmes, "/"), FUnCtIon(X) x[3]))

tHesE CaN noW Be vIewed and StOrEd, etc.
PrinT(HEAD(indIcaTors))
# [1] "EmploYed-persons"       "empLoyMent-CHanGe"      "empLoymeNt-raTe"       
# [4] "Full-tIme-empLoymeNt"   "Initial-jobless-cLaimS" "job-vacanCieS"

NExt We Can deFIne a fuNctIon That wilL give us A LisT oF ALL cOuntries available tO eXAMiNe for any Given iNDiCaTOr
list_coUnTriEs <- fuNCTion(iNdicAToR)
{
  url <- pastE0("https://TRaDiNgeconoMiCs.com/cOuNtrY-liSt/", indICatoR)
  indicAtor_page <- Read_hTMl(url)
  country_noDEs <- html_nodes(inDIcATOr_PAge, xPatH = "//td/a")
  relativE_linKS <- htmL_attR(CoUntRY_nodeS, "href")
  CoUNtRIes <- unlist(lapply(strsPlIt(relaTive_lInks, "/"), function(x) X[2]))
  tibble(couNTRY = countriEs, 
         liNK = pASte0("https://tradinGeconOmics.com", reLAtive_linKs))
}

ThiS allows uS to see all THE availabLe cOunTriEs fOR AnY indicator, and THE linK tO that coUntRy's page.
LinK_df <- LisT_coUnTries("food
 "obtained.\n")
}

Any hin t?

A:

Yo u can  gr abea ch c hart  quite easilya s aPNG image. I will show  youth e  ste p syou m ight us e .F i rst ly  l oad  i n  t he ne ces sary li braries, t hen  g et a vectorc on taining al l t he indicator s w e migh twan t  to s eeby us ing xp a th and  html_att rt o scra p e the l i n ks  fro m the page:
libra r y( r vest)
library( tidyve rs e )s ite       <- "ht tp s://t r adingec o no m i c s.c o m"
trading_ec  <- read_ht m l(p aste0( si te, "/indi cator s" ) )
l ink_xpath < - "/ /ul/li/a[ contai n s(@id,' ctl00_C ontent Pla ceH olde r 1' )] "
l in k _no d es  <- htm l_nodes( tr ad ing_e c, x p a t h  = l ink _xpa th)
l ink_names <-gre p("c o unt ry-li st",html _a ttr(l ink_no des,"h ref"), value =T)
i ndicators  <-  u nli st (lapp l y(strs pli t(l ink_nam es, "/" ) , f un c t i on (x) x[3]))

Theseca n no w be vie wed an d  s to r ed, etc. 
p rin t(he a d (indi cato r s) )
# [1]"emplo y ed -p ersons"       " em plo yme nt-ch a nge"      "employm ent-r a te"       
# [ 4 ] "full-time- e mp l o ym e nt"  " initial-job less - clai ms"" jo b-v a canci es"
Ne x tw e can define a func ti on tha t wil l give us a l ist of all c o untriesavai l ab l e to examine f or an y given in d icator
l ist_c ountries  <- funct i o n(indica tor )
{ 
 url < -paste0("https : / /tra di ngecono mic s.com/c oun try -li st/ ",  indicato r)
  ind ic at or _p age  <- r e ad_html( ur l) cou ntry_ n odes < - htm l_no de s( i ndi cator_p a ge , xpat h="//t d/a ") 
  re lati v e_l inks <-  html_att r(c o untr y_ no des, "h ref")
  count ri es <- unli st (la pply(s t r split(re lative_links, "/"), fun c tion(x)  x[ 2]))  ti bble(coun try  = cou ntr i es, 
       lin k= p a s te0(" h t tp s:/ /t radingecon o m ics .com" ,rela tive_li nks))
}

This allo w s u s to see allthe  ava i l ab lec ou n tri es for a ny indicator, a nd the lin kt othat count r y's  p age.
li nk_df < - lis t _countr ies("food 
 "obtained.\n")
}

Any_hint?

A:

You can_grab each chart quite_easily as_a_PNG image._I_will show you_the steps you_might use.
Firstly load in_the necessary libraries,_then_get a vector containing all the indicators we might want to see by using_xpath_and html_attr_to_scrape_the links from the page:
library(rvest)
library(tidyverse)

site_    _ <-_"https://tradingeconomics.com"
trading_ec <- read_html(paste0(site, "/indicators"))
link_xpath <- "//ul/li/a[contains(@id, 'ctl00_ContentPlaceHolder1')]"
link_nodes <-_html_nodes(trading_ec,_xpath = link_xpath)
link_names_<- grep("country-list", html_attr(link_nodes, "href"), value = T)
indicators <- unlist(lapply(strsplit(link_names,_"/"), function(x) x[3]))

These can now be_viewed and stored,_etc.
print(head(indicators))
#_[1]_"employed-persons"   _   "employment-change"  _   "employment-rate"  _    
# [4] "full-time-employment"_  "initial-jobless-claims" "job-vacancies"

Next we can_define a function that will_give us_a list of all countries_available to examine_for any_given indicator
list_countries <-_function(indicator)
{
  url <- paste0("https://tradingeconomics.com/country-list/", indicator)
_ indicator_page <-_read_html(url)
  country_nodes <- html_nodes(indicator_page, xpath_=_"//td/a")
  relative_links_<-_html_attr(country_nodes,_"href")
 _countries <- unlist(lapply(strsplit(relative_links,_"/"),_function(x) x[2]))
__tibble(country = countries, 
  __     link =_paste0("https://tradingeconomics.com", relative_links))
}

This allows us_to_see all the available_countries for any indicator, and_the link to that country's page.
link_df_<- list_countries("food