Homework 3

homework_3

nfl_2019

Author

Sanjana Jhaveri

Published

December 7, 2022

library(tidyverse)

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)

library(readr)
nfl <- read_csv("_data/nfl2019.csv")
View(nfl)

nfl <- read_csv("_data/nfl2019.csv",
                          skip = 1,
                          col_names = c("delete", "Opponent", "Home_Ranking", "Opponent_Ranking", "Home_1st_Downs", "Home_Total_Yards", "Home_Passing_Yards", "Home_Rushing_Yards", "Home_Turnovers", "Opponent_1st_Downs", "Opponent_Total_Yards","Opponent_Passing_Yards", "Opponent_Rushing_Yards", "Opponent_Turnovers", "Home_Offensive_Ranking", "Home_Defensive_Ranking", "Home_Special_Teams", "Home", "Year", "Winner")) %>%
  select(!starts_with("delete")) %>%
  na_if("Skipped")

mean(nfl$Home_Total_Yards)

[1] 348.048

mean(nfl$Opponent_Total_Yards)

[1] 346.2134

mean(nfl$Home_Passing_Yards)

[1] 231.8302

mean(nfl$Opponent_Passing_Yards)

[1] 230.5542

mean(nfl$Home_Rushing_Yards)

[1] 116.2179

mean(nfl$Opponent_Rushing_Yards)

[1] 115.6592

nfl%>%
  ggplot(aes(x=`Home_Passing_Yards`, y=`Year`)) +
  geom_point()

nfl%>%
  ggplot(aes(x=`Opponent_Passing_Yards`, y=`Year`)) +
  geom_point()

nfl$home_winner <- with(nfl, ifelse(Home == Winner, 'Win', 'Loss'))

view(nfl)

nrow(filter(nfl,home_winner == "Win"))

[1] 451

sum(nfl$Home_Passing_Yards > nfl$Opponent_Passing_Yards & nfl$home_winner == "Win")

[1] 262

sum(nfl$Home_Rushing_Yards > nfl$Opponent_Rushing_Yards & nfl$home_winner == "Win")

[1] 311

library(ggplot2)

scatter <- nfl %>%
  ggplot(mapping=aes(x = Year, y = `Home_Passing_Yards`))+ 
  geom_point(aes(color=home_winner))
scatter

library(ggplot2)

scatter <- nfl %>%
  ggplot(mapping=aes(x = Year, y = `Home_Rushing_Yards`))+ 
  geom_point(aes(color=home_winner))
scatter