rloopsweb-scrapingapply
R loop takes too long, how can I approach this another way?
I'm scraping and cleaning data off a particular site that collects NFL data so I end up with different lengths of a data frame that looks like this:
Now i'm going to want to summarize data in particular ways starting with team away and home yard averages. So I use a NFL team vector and loop these lines as shown below:
teamList <- as.matrix(c("New England Patriots", "Dallas Cowboys", "Denver Broncos",
"Pittsburgh Steelers", "Seattle Seahawks","Oakland Raiders", "Philadelphia Eagles", "Green Bay Packers"
,"San Francisco 49ers", "New York Giants","Chicago Bears", "Minnesota Vikings", "Washington Redskins",
"Carolina Panthers", "Carolina Panthers", "New Orleans Saints", "St. Louis Rams", "New York Jets",
"Baltimore Ravens", "San Diego Chargers", "Indianapolis Colts", "Houston Texans", "Arizona Cardinals",
"Detroit Lions", "Cleveland Browns", "Atlanta Falcons", "Buffalo Bills", "Jacksonville Jaguars", "Cincinnati Bengals",
"Kansas City Chiefs", "Tampa Bay Buccaneers", "Tennesee Titans", "Miami Dolphins"))
#Calcuating average yards per game vs any opponent for each team (home and away)
for (i in 1:nrow(teamList)){
for (y in 1:nrow(grossM)){
homeV1 <- matrix(0,1000000,1)
awayV1 <- matrix(0,1000000,1)
homeV2 <- matrix(0,1000000,1)
awayV2 <- matrix(0,1000000,1)
if (teamList[i,]==grossM[y,4]&grossM[y,5]=="@")(awayV1[y,1] <- grossM[y,9]) else 0
if (teamList[i,]==grossM[y,4]&grossM[y,5]=="")(homeV1[y,1] <- grossM[y,9]) else 0
if (teamList[i,]==grossM[y,6]&grossM[y,5]=="")(awayV2[y,1] <- grossM[y,11]) else 0
if (teamList[i,]==grossM[y,6]&grossM[y,5]=="@")(homeV2[y,1] <- grossM[y,11]) else 0
....
which is obviously inefficient but I haven't had to worry about the efficiency of my writing until now since the loop takes entirely too long (I haven't actually let it complete since it takes somewhere over an hour). Can someone please point me in the write direction, perhaps some type of matrix operation I'm not thinking of?
Thanks in advance for a response!
edit: just randomly realized I should be using aggregate in some way here right?
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Solution
Forgive me if this isn't clear, but this is my first Stack overflow post.
I assume you are reading this in from pro-football-reference. I cleaned it up as presumably you did.
library(XML)
library(dplyr)
First read in the data
url <- "http://www.pro-football-reference.com/years/2015/games.htm"
nfl_weeks <- XML::readHTMLTable(url)[[1]]
Then clean the data
nfl_weeks <- nfl_weeks[nfl_weeks$Week != "Week",][,-7]
names(nfl_weeks)[5] <- 'vs'
nfl_weeks[,7:ncol(nfl_weeks)] <- apply(nfl_weeks[,7:ncol(nfl_weeks)],2,as.numeric)
Followed by split-apply-combine strategy
# split
s <- split(nfl_weeks, nfl_weeks$`Winner/tie`)[2:33]
YdsW <- lapply(s, function(i) mYdsW = mean(i$YdsW))
YdsW <- do.call("c", YdsW)
# apply
YdsL<- lapply(s, function(i) mYdsW = mean(i$YdsL))
# combine
YdsL <- do.call("c", YdsL)
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