鐵達尼號資料分析專案

這是 Quarto 的示範文件

• 我們繼續使用老朋友 titanic 資料集

library(titanic)
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(magrittr)

titanic::titanic_train %>% head

  PassengerId Survived Pclass
1           1        0      3
2           2        1      1
3           3        1      3
4           4        1      1
5           5        0      3
6           6        0      3
                                                 Name    Sex Age SibSp Parch
1                             Braund, Mr. Owen Harris   male  22     1     0
2 Cumings, Mrs. John Bradley (Florence Briggs Thayer) female  38     1     0
3                              Heikkinen, Miss. Laina female  26     0     0
4        Futrelle, Mrs. Jacques Heath (Lily May Peel) female  35     1     0
5                            Allen, Mr. William Henry   male  35     0     0
6                                    Moran, Mr. James   male  NA     0     0
            Ticket    Fare Cabin Embarked
1        A/5 21171  7.2500              S
2         PC 17599 71.2833   C85        C
3 STON/O2. 3101282  7.9250              S
4           113803 53.1000  C123        S
5           373450  8.0500              S
6           330877  8.4583              Q

生成表格

knitr::kable()：以表格呈現資料

• 因為 titanic 資料集共有 891 筆資料，長度過長，因此擷取前20 筆資料呈現之

library(knitr)

titanic_train %>% head(20) %>% kable()

PassengerId	Survived	Pclass	Name	Sex	Age	SibSp	Parch	Ticket	Fare	Cabin	Embarked
1	0	3	Braund, Mr. Owen Harris	male	22	1	0	A/5 21171	7.2500		S
2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Thayer)	female	38	1	0	PC 17599	71.2833	C85	C
3	1	3	Heikkinen, Miss. Laina	female	26	0	0	STON/O2. 3101282	7.9250		S
4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35	1	0	113803	53.1000	C123	S
5	0	3	Allen, Mr. William Henry	male	35	0	0	373450	8.0500		S
6	0	3	Moran, Mr. James	male	NA	0	0	330877	8.4583		Q
7	0	1	McCarthy, Mr. Timothy J	male	54	0	0	17463	51.8625	E46	S
8	0	3	Palsson, Master. Gosta Leonard	male	2	3	1	349909	21.0750		S
9	1	3	Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)	female	27	0	2	347742	11.1333		S
10	1	2	Nasser, Mrs. Nicholas (Adele Achem)	female	14	1	0	237736	30.0708		C
11	1	3	Sandstrom, Miss. Marguerite Rut	female	4	1	1	PP 9549	16.7000	G6	S
12	1	1	Bonnell, Miss. Elizabeth	female	58	0	0	113783	26.5500	C103	S
13	0	3	Saundercock, Mr. William Henry	male	20	0	0	A/5. 2151	8.0500		S
14	0	3	Andersson, Mr. Anders Johan	male	39	1	5	347082	31.2750		S
15	0	3	Vestrom, Miss. Hulda Amanda Adolfina	female	14	0	0	350406	7.8542		S
16	1	2	Hewlett, Mrs. (Mary D Kingcome)	female	55	0	0	248706	16.0000		S
17	0	3	Rice, Master. Eugene	male	2	4	1	382652	29.1250		Q
18	1	2	Williams, Mr. Charles Eugene	male	NA	0	0	244373	13.0000		S
19	0	3	Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)	female	31	1	0	345763	18.0000		S
20	1	3	Masselmani, Mrs. Fatima	female	NA	0	0	2649	7.2250		C

DT::datatable()： 如果想要能夠更清楚的觀察資料

#install.packages("DT")
library(DT)

# 更多 DT::datatable 的設定可查閱文件：https://rstudio.github.io/DT/
datatable(titanic_train, extensions = 'Scroller', 
          options = list(scrollY = 400, scroller = TRUE))

生成圖表

生成 ggplot 分析圖

library(ggplot2)
library(dplyr)

p <- titanic_train %>% 
  mutate(Pclass = factor(Pclass, levels=c(3, 2, 1), label = c("三等艙", "二等艙", "頭等艙"))) %>%
  mutate(Survived = factor(Survived)) %>% 
  ggplot(., aes(x = Pclass, fill = Survived)) +
  geom_bar(position = "fill") +  # Stacked bar plot
  facet_wrap(~ Sex) +  # Separate by gender
  labs(
    title = "Survival Rate by Pclass and Sex",
    x = "Pclass (Passenger Class)",
    y = "Proportion of Survivors",
    fill = "Survived"
  ) +
  scale_fill_manual(values = c("#888", "red"), labels = c("Did not survive", "Survived")) +
  theme_minimal() +
  theme(text = element_text(family = '黑體-繁 中黑')) # 設定顯示中文字(Mac)

p

生成互動式圖表

• 由於讀取套件 plotly 時會出現系統訊息，因此可以在 code chunk 中設定 message=FALSE，以避免訊息出現

library(plotly)

ggplotly(p)