This is my first heading

This is how I went about doing my assignment…

2nd paragraph… paragraph

  • Hi
  • How
  • are
  • you?
  1. Hi
  2. How
  3. are
  4. you? 
my_path <- "U:/"
setwd(my_path)

library(data.table)
library(ggplot2)
library(dplyr)
library(tidytext)
library(RColorBrewer)

df <- fread("GamesGitHub.csv")
cols_to_use <- c("season", "away_team", "away_score", "home_team", "home_score")

df <- subset(df, select = cols_to_use)

df$winner <- ifelse(df$away_score > df$home_score, df$away_team, df$home_team)
df$loser <- ifelse(df$away_score > df$home_score, df$home_team, df$away_team)

df <- na.omit(df)

df$score_diff <- abs(df$away_score - df$home_score)

table(df$score_diff == 0)
## 
## FALSE  TRUE 
##  6188    13
winners <- df %>%
  mutate(team = winner) %>%
  group_by(season, team) %>%
  summarise(win_count = n(), .groups = "keep" ) %>%
  data.frame()

losers <- df %>%
  mutate(team = loser) %>%
  group_by(season, team) %>%
  summarise(lose_count = n(), .groups = "keep" ) %>%
  data.frame()
head(losers, 10)
##    season team lose_count
## 1    1999  ARI         10
## 2    1999  ATL         11
## 3    1999  BAL          8
## 4    1999  BUF          6
## 5    1999  CAR          8
## 6    1999  CHI         10
## 7    1999  CIN         12
## 8    1999  CLE         14
## 9    1999  DAL          9
## 10   1999  DEN         10
df1 <- merge(x = winners, y = losers, by = c("season", "team"), all = TRUE)

df1[is.na(df1)] <- 0

df2 <- df1 %>%
  mutate(team = recode(team, 'OAK' = 'LV', 'SD' = 'LAC', 'STL' = 'LA') ) %>%
  group_by(team) %>%
  summarise(wins = sum(win_count), losses = sum(lose_count), .groups = "keep") %>%
  mutate(total_games = wins + losses, 
         win_percentage = round(100*wins/total_games, 0),
         loss_percentage = round(100*losses/total_games, 0)) %>%
  data.frame()
ggplot(df2, aes(x = reorder(team, -wins), y = wins, fill = win_percentage)) + 
  geom_bar(stat = "identity") +
  labs(x = "team", y = "win count", title = "Wins by Team", fill = "Win Percentage") +
  geom_text(aes(label = paste0(win_percentage, "%")), vjust = -0.5) +
  scale_fill_continuous(
    limits = c(31,80),
    labels = paste0(seq(30,80,10), "%"),
    breaks = seq(30,80,10),
    low = "red",
    high = "dark green") +
  theme(plot.title = element_text(hjust = 0.5))

This is my second heading

More paragraph text,,,

df2 <- df1 %>%
  filter(season >= 2019 & season <= 2021) %>%
  mutate(team = recode(team, 'OAK' = 'LV', 'SD' = 'LAC', 'STL' = 'LA') ) %>%
  group_by(season) %>%
  mutate(total = win_count + lose_count,
         win_percentage = round(100*win_count/total, 0),
         loss_percentage = round(100*lose_count/total, 0),
         team = reorder_within(team, win_count, season),
         team_abbr = substr(team, 0, nchar(as.character(team))-7),
         rank = rank(-win_percentage, ties.method = "random"  )) %>%
  data.frame()

df2$team
##  [1] ARI___2019 ATL___2019 BAL___2019 BUF___2019 CAR___2019 CHI___2019
##  [7] CIN___2019 CLE___2019 DAL___2019 DEN___2019 DET___2019 GB___2019 
## [13] HOU___2019 IND___2019 JAX___2019 KC___2019  LA___2019  LAC___2019
## [19] MIA___2019 MIN___2019 NE___2019  NO___2019  NYG___2019 NYJ___2019
## [25] LV___2019  PHI___2019 PIT___2019 SEA___2019 SF___2019  TB___2019 
## [31] TEN___2019 WAS___2019 ARI___2020 ATL___2020 BAL___2020 BUF___2020
## [37] CAR___2020 CHI___2020 CIN___2020 CLE___2020 DAL___2020 DEN___2020
## [43] DET___2020 GB___2020  HOU___2020 IND___2020 JAX___2020 KC___2020 
## [49] LA___2020  LAC___2020 LV___2020  MIA___2020 MIN___2020 NE___2020 
## [55] NO___2020  NYG___2020 NYJ___2020 PHI___2020 PIT___2020 SEA___2020
## [61] SF___2020  TB___2020  TEN___2020 WAS___2020 ARI___2021 ATL___2021
## [67] BAL___2021 BUF___2021 CAR___2021 CHI___2021 CIN___2021 CLE___2021
## [73] DAL___2021 DEN___2021 DET___2021 GB___2021  HOU___2021 IND___2021
## [79] JAX___2021 KC___2021  LA___2021  LAC___2021 LV___2021  MIA___2021
## [85] MIN___2021 NE___2021  NO___2021  NYG___2021 NYJ___2021 PHI___2021
## [91] PIT___2021 SEA___2021 SF___2021  TB___2021  TEN___2021 WAS___2021
## 96 Levels: CIN___2019 DET___2019 WAS___2019 NYG___2019 ... LA___2021
ggplot(df2, aes(x = reorder(team, -win_count), y = win_count, fill = win_percentage)) + 
  geom_bar(stat = "identity") +
  geom_text(aes(label = paste0(win_percentage, "%")), vjust = -0.5, size = 3 ) +
  labs(x = "team", y = "win count", title = "Wins by Team", fill = "Win Percentage") +
  scale_y_continuous(limits = c(0, max(df2$win_count)*1.1) ) +
  scale_x_reordered() +
  scale_fill_continuous(
    limits = c(1,90),
    labels = paste0(seq(0,90,10), "%"),
    breaks = seq(0,90,10),
    low = "red",
    high = "dark green") +
  facet_wrap(ncol = 1, nrow = 8, ~season, scales = "free") +
  theme(plot.title = element_text(hjust = 0.5))

cols <- colorRampPalette(brewer.pal(8,"Set2") )
my_Pal <- cols(32)

ggplot(df2, aes(x = season, y = rank, group = team_abbr) ) +
  geom_line(aes(color = team_abbr), size = 2 ) +
  geom_point(shape = 21, size = 4, fill = "white") +
  scale_y_reverse(breaks = seq(max(df2$rank), 1, -1) ) +
  geom_text(data = df2 %>% filter(season == min(season)),
            aes(x = season - 0.05,
                y = rank,
                label = team_abbr),
            size = 3,
            hjust = 1) +
  geom_text(data = df2 %>% filter(season == max(season)),
            aes(x = season - 0.05,
                y = rank,
                label = team_abbr),
            size = 3,
            hjust = 0) +
  scale_x_continuous(breaks = min(df2$season):max(df2$season),
                     labels = as.character(min(df2$season):max(df2$season))) +
  scale_color_manual(values = my_Pal) +
  labs(title = "Bump Chart",
       x = "Season",
       y = "Rank",
       color = "Teams") +
  theme(plot.title = element_text(hjust = 0.5))

More stuff goes here if u want it.