R/datareader.r

In okugami79/googletrend: R google trend ( automated download google trend data to R)

# parsing google trend file, extract information 
 
datareader <- function(file, simple=FALSE)
  # file : google trend download file 
  # geom : Location Code in character 
  # year : numeric integer, indicating single year 
{

#  x<- read.csv(file=file, skip=5,col.names=c("week", "index"), stringsAsFactors=FALSE)
   x<- read.csv(file=file, skip=4,col.names=c("week", "index"), stringsAsFactors=FALSE)
  
  TOP.REGION = "^Top regions for" 
  TOP.SUBREGION = "^Top subregions for"   
  TOP.CITY   = "^Top cities for"
  TOP.SEARCH = "^Top searches for"
  RISING.SEARCH="^Rising searches for"
  INTEREST.OVER.TIME="^Interest over time"

  find.keyword.idx<-function(key)
  {
    # grep through key term in first column of google trend data 
    return( grep(key,x[,1]) )  
  }
  
  
  # 
  TOP.REGION.IDX=find.keyword.idx(TOP.REGION) # Range(TOP.REGION.IDX-TOP.CITY.IDX, Countries)
  TOP.SUBREGION.IDX=find.keyword.idx(TOP.SUBREGION) # Range(TOP.REGION.IDX-TOP.CITY.IDX, Countries)
  TOP.CITY.IDX=find.keyword.idx(TOP.CITY)
  TOP.SEARCH.IDX=find.keyword.idx(TOP.SEARCH)
  RISING.SEARCH.IDX=find.keyword.idx(RISING.SEARCH)
  INTEREST.OVER.TIME=find.keyword.idx(INTEREST.OVER.TIME)
  
  message(
    paste("TOP.REGION.IDX",TOP.REGION.IDX, 
          "TOP.SUBREGION.IDX",TOP.SUBREGION.IDX,
          "TOP.CITY.IDX",TOP.CITY.IDX,
          "TOP.SEARCH.IDX",TOP.SEARCH.IDX,
          "RISING.SEARCH.IDX",RISING.SEARCH.IDX )    
    )
  
  
  # trend data 
  if ( 
    # checking only single entry form 
    is.null( 
      unlist(sapply(c(TOP.REGION.IDX,TOP.SUBREGION.IDX,TOP.CITY.IDX,TOP.SEARCH.IDX,RISING.SEARCH.IDX,INTEREST.OVER.TIME),FUN=function(X)length(x)))    
    )    
    ) 
    { # single entry, no associatge 
      if(nrow(x) == 0 )
        return (NULL)
      
      MIN.IDX<-nrow(x)
      trend <- .parse.trend.data(x,0,MIN.IDX)
      plot(trend, type='l')  
      
      ret<-list() 
      ret$trend <- trend
      return(ret)      
    }
      
  MIN.IDX<-min(TOP.REGION.IDX,TOP.SUBREGION.IDX,TOP.CITY.IDX,TOP.SEARCH.IDX,RISING.SEARCH.IDX,INTEREST.OVER.TIME, na.rm=T)  
  
  trend <- .parse.trend.data(x,0,MIN.IDX)  
  plot(trend, type='l')  
  
  ret<-list() 
  ret$trend <- trend 
   
  if(simple==FALSE)
  {
    # parsing additional data 
    MIN.IDX<-min(TOP.CITY.IDX,TOP.SEARCH.IDX,RISING.SEARCH.IDX,INTEREST.OVER.TIME, na.rm=T)    
    if( length(TOP.REGION.IDX) > 0 &  length(MIN.IDX) > 0 )
    { 
      ret$top.region <- .parse.top.region(x,
                                          start.idx=TOP.REGION.IDX,
                                          end.idx=MIN.IDX )    
    }else if( length(TOP.SUBREGION.IDX) > 0 &  length(MIN.IDX) > 0 )
    {
      ret$top.region <- .parse.top.region(x,
                                          start.idx=TOP.SUBREGION.IDX,
                                          end.idx=MIN.IDX )    
    }else 
      ret$top.region <- NULL 
    
    if(length(TOP.CITY.IDX) > 0 & length(RISING.SEARCH.IDX) > 0 )
    {
      MIN.IDX<-min(TOP.SEARCH.IDX,RISING.SEARCH.IDX, na.rm=T)        
      ret$top.city <- .parse.top.region(x,
                                        start.idx=TOP.CITY.IDX,
                                        end.idx=MIN.IDX )    
    }else 
      ret$top.city <- NULL 
    
    if( length(TOP.SEARCH.IDX) > 0 &  length(RISING.SEARCH.IDX) > 0  )
    {
      ret$top.search <- .parse.top.search(x,
                                          start.idx=TOP.SEARCH.IDX,
                                          end.idx=RISING.SEARCH.IDX )    
    } else 
      if( length(TOP.SEARCH.IDX) > 0 )
      {
        ret$top.search <- .parse.top.search(x,
                                            start.idx=TOP.SEARCH.IDX,
                                            end.idx=nrow(x) )          
      } else ret$top.search <- NULL 
    
  } # simple = FALSE
   
  # return value 
  return(ret)
  
}

.parse.trend.data <- function(x, start.idx=0, end.idx)
{
  # hard code parsing  
  # y <- x[start.idx+1:(end.idx-4),]
  y <- x[start.idx+1:(end.idx-1),]
  
  # convert to ordinary data frame 
  y[,1] <- as.character(y[,1])
  date <- do.call(rbind, (strsplit( y[,1], ' - ' ) ) ) 
  
  # need code to handle monthly & weekly data data 
  if ( length( strsplit(date[,1],'-')[[1]]) == 2 ) # monthly data 
    y[,1] <- as.Date( sprintf('%s-01',date[,1]) ) else 
      y[,1] <- as.Date( date[,1] )
    
  y[,2] <- as.numeric( y[,2] )
   
  return(y)
}

.parse.top.region<-function(x,start.idx,end.idx)
{
  # hard code parsing  
  y <- x[(start.idx+2):(end.idx-1),] 
  colnames(y) <- c('region','index')
  
  y[,1] <- as.character(y[,1])
  y[,2] <- as.numeric( y[,2] ) 
  return(y)  
}

.parse.top.city<-function(x,start.idx,end.idx)
{
  # hard code parsing  
  y <- x[(start.idx+2):(end.idx-1),] 
  colnames(y) <- c('city','index')
  
  y[,1] <- as.character(y[,1])
  y[,2] <- as.numeric( y[,2] ) 
  return(y)  
}

.parse.top.search <-function(x,start.idx,end.idx)
{
  # hard code parsing  
  y <- x[(start.idx+2):(end.idx-1),]
  y
  colnames(y) <- c('top.search','index')
  
  y[,1] <- as.character(y[,1])
  y[,2] <- as.numeric( y[,2] ) 
  return(y)  
}