---

title: “Untitled” output: html_document date: “2025-11-14”

#1

#把你蒐集到的資料key入
Statistic <- c(68,85,74,88,63,78,90,80,58,63)
Math <- c(85,91,74,100,82,84,78,100,51,70)
## C 固定值意思
## x,y 兩個變項,比方身高體重,你有興趣的變項皆可



colors <- c("#FDAE61", # Orange
            "#D9EF8B") # Light green

##畫圖
plot(Statistic,Math,
     pch = 19,
     col = colors,
     main="統計與數學成績的散佈圖")

     #2
     
     library(ggplot2)

ggplot(data = iris, aes(x = Sepal.Length)) +
  geom_histogram(binwidth = 0.5, fill = "forestgreen", color = "black") +
  labs(title = "數學成績直方圖",
       x = "數學成績",
       y = "人數")

       #3
       
       # Load ggplot2
library(ggplot2)

# Create data
data <- data.frame(
  社團類型=c("公益活動","知識閱讀","科學創新","娛樂休閒","體育競技") ,
  次數=c(3,12,5,18,45)
  )

# Barplot
ggplot(data, aes(x=社團類型, y=次數)) + 
  geom_bar(stat = "identity")

  #4
  
  Prop <- c(3,7,9,1,2)
  pie(Prop , labels =
 c("公益活動","知識閱讀","科學創新","娛樂休閒","體育競技"))

 #5
 
# Library
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ lubridate 1.9.4     ✔ tibble    3.3.0
## ✔ purrr     1.2.0     ✔ tidyr     1.3.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

# Create data
data <- data.frame(
  x=LETTERS[1:26],
  y=abs(rnorm(26))
)
 
# plot
ggplot(data, aes(x=x, y=y)) +
  geom_segment( aes(x=x, xend=x, y=0, yend=y)) +
  geom_point( size=5, color="red", fill=alpha("orange", 0.3), alpha=0.7, shape=21, stroke=2) 

library (readr)

Data <- read.csv("D:/table1_1.csv")