BUYANULZII_TS

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(readr)
library(ggplot2)
data <- read.csv("/Users/buyanulziitserennadmid/Downloads/olympic_running.csv")

#clean
dc <- na.omit(data)


#Ergtei 100m eer scatter plot hiih
men_100 <- dc %>%
  filter( Sex == 'men', Length == "100")
ggplot(men_100, aes(x = Year, y = Time)) + 
  geom_point() + 
  theme_classic()+
labs(
  title = "Olympic Men's 100m Sprint",
  x = 'Year',
  y = "Time (seconds)"
)

#ergteigiin ehnii 5hurdiig oloh
fastest_5time <- men_100 %>%
  arrange(Time) %>%
  head(5)
mutate(fastest_5time,Holder = c('Usain Bolt','Usain Bolt','Usain Bolt','Justin Gatlin','Yohan Blake')) %>%
  select (-rownames)

#emegteigiin 200m iin histogramm
women_200m <- dc %>%
  filter(Sex == 'women', Length == '200')
library(ggplot2)

ggplot(women_200m, aes(x = Time)) +
  geom_histogram(binwidth = 0.1, fill = "lightblue", color = "black") + 
  labs(
    title = "Histogram of Olympic Women's 200m Sprint Times",
    x = "Time (seconds)",
    y = "Frequency"
  ) +
  theme_minimal() 

#2008 bolon 2012 onii eregtei emegteichuudiin tsagnuudiig negtgesen
result_2008 <- filter(dc, Year == '2008') %>%
  select(Time)
result_2012 <- filter(dc, Year == '2012') %>%
  select(-rownames,-Year)
combined_result <- bind_cols(result_2008, result_2012) %>%
  select(Length, Sex, Time...1, Time...4) %>%
  rename("2008's Time" = Time...1, "2012's Time" = Time...4)

## New names:
## • `Time` -> `Time...1`
## • `Time` -> `Time...4`

#speed nertei shine baganad sekunded tuulah zamiig ilerhiilne
speedtei_dc <- dc %>%
  mutate(speed = Length/Time)