peterhurford

1.) If I have a data.frame df <- data.frame(a = c(1, 2, 3), b = c(4, 5, 6), c(7, 8, 9))...

1a.) How do I select the c(4, 5, 6)?

1b.) How do I select the 1?

1c.) How do I select the 5?

1d.) What is df[, 3]?

craigmbooth

ATL - Atlanta - FALCONS
BUF - Buffalo - BILLS
CHI - Chicago - BEARS
CIN - Cincinnati - BENGALS
CLE - Cleveland - BROWNS
BAL - Baltimore - RAVENS
DAL - Dallas - COWBOYS
DEN - Denver - BRONCOS
DET - Detroit - LIONS
GB  - Green Bay - PACKERS

isaactpetersen

#Load libraries
library("XML")

#Download fantasy football projections from FantasyPros.com
qb_fp <- readHTMLTable("http://www.fantasypros.com/nfl/projections/qb.php", stringsAsFactors = FALSE)$data
rb_fp <- readHTMLTable("http://www.fantasypros.com/nfl/projections/rb.php", stringsAsFactors = FALSE)$data
wr_fp <- readHTMLTable("http://www.fantasypros.com/nfl/projections/wr.php", stringsAsFactors = FALSE)$data
te_fp <- readHTMLTable("http://www.fantasypros.com/nfl/projections/te.php", stringsAsFactors = FALSE)$data

ramhiser

# The following script scrapes ESPN's MLB Standings Grid and writes the
# standings for each American League (AL) team to a CSV file, which has the following
# format:
# Team, Opponent, Wins, Losses

from bs4 import BeautifulSoup
import urllib2
import re
import csv

Protonk

library(AER)
library(lmtest)
data("CollegeDistance")
cd.d<-CollegeDistance
simple.ed.1s<- lm(education ~ distance,data=cd.d)
cd.d$ed.pred<- predict(simple.ed.1s)
simple.ed.2s<- lm(wage ~ urban + gender + ethnicity + unemp + ed.pred , data=cd.d)
simple.comp<- encomptest(wage ~ urban + gender + ethnicity + unemp + ed.pred , wage ~ urban + gender + ethnicity + unemp + education , data=cd.d)
1s.ftest<- encomptest(education ~ tuition + gender + ethnicity + urban , education ~ distance , data=cd.d)