# load the data "/Users/liopaper/Downloads/NNdata_cleaned.csv"
NNdata <- read.csv("/Users/liopaper/Downloads/NNdata_cleaned.csv")
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(tidyr)
library(ggplot2)
library(forcats)
# install the showtext package
library(showtext)
## Loading required package: sysfonts
## Loading required package: showtextdb
# 添加并加載 '標楷體' 字體
font_add("KaiTi", regular = "/Users/liopaper/Library/Fonts/標楷體.ttc")
showtext_auto()
#畫圖:
#A1. 請問您平常會使用哪些社群媒體？
# 處理 A1 的數據，提取出社群媒體名稱
A1_data <- NNdata %>%
select(starts_with("請問您平常會使用哪些社群媒體")) %>%
pivot_longer(cols = everything(), names_to = "SocialMedia", values_to = "Usage") %>%
mutate(SocialMedia = gsub("請問您平常會使用哪些社群媒體.", "", SocialMedia)) %>% # 提取選項名稱
group_by(SocialMedia) %>%
summarize(Count = sum(Usage))
ggplot(A1_data, aes(x = fct_reorder(SocialMedia, Count), y = Count)) +
geom_bar(stat = "identity", fill = "grey40") +
geom_text(aes(label = Count), hjust = -0.3, size = 3, family = "KaiTi") + # 添加數字標籤
coord_flip() +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 9, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 9, hjust = 0.5, face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
panel.grid.major = element_line(color = "grey90"), # 使用更淡的網格線
panel.grid.minor = element_blank(), # 移除次要網格線
axis.line = element_line(color = "black")
) +
labs(title = "使用社群媒體的情況", x = "社\n群\n媒\n體", y = "使用人數")
#A2. 請問您是否去過以下這幾間宮廟？
# 處理 A2 的數據，提取出宮廟名稱
A2_data <- NNdata %>%
select(starts_with("請問您是否去過以下這幾間宮廟")) %>%
pivot_longer(cols = everything(), names_to = "Temple", values_to = "Visited") %>%
mutate(Temple = gsub("請問您是否去過以下這幾間宮廟.", "", Temple)) %>%
# 提取宮廟名稱
group_by(Temple) %>%
summarize(Count = sum(Visited))
# 繪製條形圖
ggplot(A2_data, aes(x = fct_reorder(Temple, Count), y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.4) +
coord_flip() +
geom_text(aes(label = Count), hjust = -0.3, size = 3, family = "KaiTi") + # 添加數字標籤
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 9, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 9, hjust = 0.5, face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
panel.grid.major = element_line(color = "grey90"), # 使用更淡的網格線
panel.grid.minor = element_blank(), # 移除次要網格線
axis.line = element_line(color = "black")
) +
labs(title = "去過的宮廟情況", x = "宮\n廟", y = "去過的人數")
#A3. 您平常去宮廟的主要原因有哪些？
# 處理 A3 的數據，提取出去宮廟的原因
A3_data <- NNdata %>%
select(starts_with("您平常去宮廟的主要原因有哪些")) %>%
pivot_longer(cols = everything(), names_to = "Reason", values_to = "Selected") %>%
mutate(Reason = gsub("您平常去宮廟的主要原因有哪些.", "", Reason)) %>% # 提取原因名稱
group_by(Reason) %>%
summarize(Count = sum(Selected))
# 繪製條形圖
ggplot(A3_data, aes(x = fct_reorder(Reason, Count), y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.7) +
geom_text(aes(label = Count), hjust = -0.3, size = 3, family = "KaiTi") + # 添加數字標籤
coord_flip() +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 9, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 9, hjust = 0.5, face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
panel.grid.major = element_line(color = "grey90"), # 使用更淡的網格線
panel.grid.minor = element_blank(), # 移除次要網格線
axis.line = element_line(color = "black")
) +
labs(title = "去宮廟的主要原因", x = "原\n因", y = "選擇人數")
# 處理 A4 的數據，提取祈求的事情
A4_data <- NNdata %>%
select(starts_with("您平常在宮廟主要祈求哪些事情")) %>%
pivot_longer(cols = everything(), names_to = "Prayer", values_to = "Selected") %>%
mutate(Prayer = gsub("您平常在宮廟主要祈求哪些事情.", "", Prayer)) %>% # 提取祈求的事項名稱
group_by(Prayer) %>%
summarize(Count = sum(Selected))
# 繪製條形圖
ggplot(A4_data, aes(x = fct_reorder(Prayer, Count), y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.7) +
geom_text(aes(label = Count), hjust = -0.3, size = 3, family = "KaiTi") + # 添加數字標籤
coord_flip() +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 9, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 9, hjust = 0.5, face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
panel.grid.major = element_line(color = "grey90"), # 使用更淡的網格線
panel.grid.minor = element_blank(), # 移除次要網格線
axis.line = element_line(color = "black")
) +
labs(title = "宮廟主要祈求事項", x = "祈\n求\n事\n項", y = "選擇人數")
maintheme <- theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 9, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 9, hjust = 0.5, face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
panel.grid.major = element_line(color = "grey90"), # 使用更淡的網格線
panel.grid.minor = element_blank(), # 移除次要網格線
axis.line = element_line(color = "black")
)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ lubridate 1.9.3 ✔ stringr 1.5.0
## ✔ purrr 1.0.2 ✔ tibble 3.2.1
## ✔ readr 2.1.4
## ── 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
# 定義 Likert Scale 的排序
likert_scale <- c("從來沒有" = 1, "一年一次" = 2, "一年數次" = 3,
"一個月一次" = 4, "一個月數次" = 5, "每週一次" = 6,
"每週數次" = 7)
# 數據處理
A5_data <- NNdata %>%
select(
`請問您平常到宮廟從事以下各種宗教儀式或活動的頻率如何....拜拜`,
`請問您平常到宮廟從事以下各種宗教儀式或活動的頻率如何....擲筊`,
`請問您平常到宮廟從事以下各種宗教儀式或活動的頻率如何....求籤`,
`請問您平常到宮廟從事以下各種宗教儀式或活動的頻率如何....捐香油錢`
) %>%
pivot_longer(cols = everything(), names_to = "Activity", values_to = "Frequency") %>%
filter(!is.na(Frequency)) %>% # 過濾掉 NA 值
mutate(
Activity = gsub("請問您平常到宮廟從事以下各種宗教儀式或活動的頻率如何....", "", Activity),
Frequency = factor(Frequency, levels = likert_scale, labels = names(likert_scale))
) %>%
group_by(Activity, Frequency) %>%
summarize(Count = n(), .groups = 'drop')
ggplot(A5_data, aes(x = Frequency, y = Count, fill = Frequency)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.6) + # 設置填充顏色為灰色
geom_text(aes(label = Count), , size = 3, vjust = -1, family = "KaiTi") + # 添加數字標籤
facet_wrap(~ Activity, scales = "free_y", nrow = 2) + # 每個活動一個獨立的子圖
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 9, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 6.5, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
panel.grid.major = element_line(color = "grey90"), # 使用更淡的網格線
panel.grid.minor = element_blank(), # 移除次要網格線
axis.line = element_line(color = "black")
) +
labs(title = "各宗教儀式或活動的頻率分布", x = "頻率", y = "人\n數") +
expand_limits(y = max(A5_data$Count) * 1.1) # 增加 y 軸範圍
# 加載並設置字體
font_add("KaiTi", regular = "/path_to_your_font/標楷體.ttc")
showtext_auto()
# 處理 B1 的數據，提取與宮廟相關的數位服務
B1_data <- NNdata %>%
select(starts_with("請問您是否使用過以下與宮廟相關的數位服務")) %>%
pivot_longer(cols = everything(), names_to = "Service", values_to = "Used") %>%
mutate(Service = gsub("請問您是否使用過以下與宮廟相關的數位服務..", "", Service)) %>% # 提取服務名稱
group_by(Service) %>%
summarize(Count = sum(Used, na.rm = TRUE))
# 繪製條形圖
ggplot(B1_data, aes(x = fct_reorder(Service, Count), y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.6) +
coord_flip() +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 9, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 9, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")) +
labs(title = "宮廟相關數位服務的使用情況", x = "數\n位\n服\n務", y = "使用人數")
# 處理 B2a 的數據，提取「線上求籤」經驗評價
B2a_data <- NNdata %>%
select("整題而言.您認為.線上求籤.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.線上求籤.的經驗好或不好.") %>%
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n())
# 繪製條形圖
ggplot(B2a_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") + # 添加數字標籤
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 9, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 9, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")) +
labs(title = "線上求籤的經驗評價分布", x = "評價", y = "人\n數")
# B2a. 整體而言，您認為「線上求籤」的經驗好或不好？
B2a_data <- NNdata %>%
select("整題而言.您認為.線上求籤.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.線上求籤.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>% # 去除 NA
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0)) # 確保所有標籤顯示
ggplot(B2a_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 9, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 9, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")) +
labs(title = "線上求籤的經驗評價分布", x = "評價", y = "人\n數")
# B2b. 整體而言，您認為「線上點光明燈」的經驗好或不好？
B2b_data <- NNdata %>%
select("整題而言.您認為.線上點光明燈.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.線上點光明燈.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>% # 去除 NA
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0)) # 確保所有標籤顯示
ggplot(B2b_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")) +
labs(title = "線上點光明燈的經驗評價分布", x = "評價", y = "人\n數")
# B2c. 整體而言，您認為「光明燈尋燈系統」的經驗好或不好？
B2c_data <- NNdata %>%
select("整題而言.您認為.光明燈尋燈系統.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.光明燈尋燈系統.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>% # 去除 NA
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0)) # 確保所有標籤顯示
ggplot(B2c_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")) +
labs(title = "光明燈尋燈系統的經驗評價分布", x = "評價", y = "人\n數")
# B2d. 整體而言，您認為「LINE 上傳祈福語」的經驗好或不好？
B2d_data <- NNdata %>%
select("整題而言.您認為.LINE.上傳祈福語.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.LINE.上傳祈福語.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>% # 去除 NA
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0)) # 確保所有標籤顯示
# 繪製條形圖
ggplot(B2d_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")) +
labs(title = "LINE 上傳祈福語的經驗評價分布", x = "評價", y = "人\n數")
# B2e. 整題而言，您認為「籤詩解籤機」的經驗好或不好？
B2e_data <- NNdata %>%
select("整題而言.您認為.籤詩解籤機.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.籤詩解籤機.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>% # 去除 NA
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0)) # 確保所有標籤顯示
# 繪製條形圖
ggplot(B2e_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")) +
labs(title = "籤詩解籤機的經驗評價分布", x = "評價", y = "人\n數")
# B2f. 整題而言，您認為「悠遊卡捐香油錢或買金紙」的經驗好或不好？
B2f_data <- NNdata %>%
select("整題而言.您認為.悠遊卡捐香油錢或買金紙.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.悠遊卡捐香油錢或買金紙.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>% # 去除 NA
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0)) # 確保所有標籤顯示
# 繪製條形圖
ggplot(B2f_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")) +
labs(title = "悠遊卡捐香油錢或買金紙的經驗評價分布", x = "評價", y = "人\n數")
# B2g. 整題而言，您認為「AI 聊天機器人解籤或問事」的經驗好或不好？
B2g_data <- NNdata %>%
select("整題而言.您認為.AI.聊天機器人解籤或問事.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.AI.聊天機器人解籤或問事.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>% # 去除 NA
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0)) # 確保所有標籤顯示
# 繪製條形圖
ggplot(B2g_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "AI 聊天機器人解籤或問事的經驗評價分布", x = "評價", y = "人\n數")
# B2h. 整題而言，您認為「廟裡的機器人導覽」的經驗好或不好？
B2h_data <- NNdata %>%
select("整題而言.您認為.廟裡的機器人導覽.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.廟裡的機器人導覽.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>% # 去除 NA
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0)) # 確保所有標籤顯示
# 繪製條形圖
ggplot(B2h_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "廟裡的機器人導覽的經驗評價分布", x = "評價", y = "人\n數")
# B2i. 整體而言，您認為「NFT 錢母」的經驗好或不好？
B2i_data <- NNdata %>%
select("整題而言.您認為.NFT.錢母.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.NFT.錢母.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>%
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0))
# 繪製條形圖
ggplot(B2i_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "NFT 錢母的經驗評價分布", x = "評價", y = "人\n數")
# B2j. 整體而言，您認為「虛擬實境參拜（VR、XR、元宇宙）」的經驗好或不好？
B2j_data <- NNdata %>%
select("整題而言.您認為.虛擬實境參拜.VR.XR.元宇宙..的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.虛擬實境參拜.VR.XR.元宇宙..的經驗好或不好.") %>%
filter(!is.na(Experience)) %>%
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0))
# 繪製條形圖
ggplot(B2j_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5 ) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "虛擬實境參拜（VR、XR、元宇宙）的經驗評價分布", x = "評價", y = "人\n數")
# B2k. 整體而言，您認為「銀行 ATM 捐款或點燈等」的經驗好或不好？
B2k_data <- NNdata %>%
select("整題而言.您認為.銀行.ATM.捐款或點燈等.的經驗好或不好.") %>%
rename(Experience = "整題而言.您認為.銀行.ATM.捐款或點燈等.的經驗好或不好.") %>%
filter(!is.na(Experience)) %>%
mutate(Experience = factor(Experience, levels = c(1, 2, 3, 4, 5),
labels = c("非常好", "好", "普通", "不太好", "非常不好"))) %>%
group_by(Experience) %>%
summarize(Count = n()) %>%
complete(Experience = factor(c("非常好", "好", "普通", "不太好", "非常不好"),
levels = c("非常好", "好", "普通", "不太好", "非常不好")),
fill = list(Count = 0))
# 繪製條形圖
ggplot(B2k_data, aes(x = Experience, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "銀行 ATM 捐款或點燈等的經驗評價分布", x = "評價", y = "人\n數")
# B3. 整體經驗
B3_data <- NNdata %>%
select("請問您家中的長輩.是否曾使用過以上任何宮廟提供的數位服務.") %>%
rename(Usage = "請問您家中的長輩.是否曾使用過以上任何宮廟提供的數位服務.") %>%
filter(!is.na(Usage)) %>% # 去除 NA
mutate(Usage = factor(Usage, levels = c(1, 2, 3, 4),
labels = c("經常使用", "有時使用", "不曾使用", "不清楚"))) %>%
group_by(Usage) %>%
summarize(Count = n()) %>%
complete(Usage = factor(c("經常使用", "有時使用", "不曾使用", "不清楚"),
levels = c("經常使用", "有時使用", "不曾使用", "不清楚")),
fill = list(Count = 0)) # 確保所有標籤顯示
ggplot(B3_data, aes(x = Usage, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "長輩使用宮廟數位服務的情況", x = "使用情況", y = "人\n數")
# C1. 性別
C1_data <- NNdata %>%
select("請問您的性別是.") %>%
rename(Gender = "請問您的性別是.") %>%
filter(!is.na(Gender)) %>% # 去除 NA
mutate(Gender = factor(Gender, levels = c(1, 2, 3),
labels = c("男性", "女性", "其他"))) %>%
group_by(Gender) %>%
summarize(Count = n()) %>%
complete(Gender = factor(c("男性", "女性", "其他"),
levels = c("男性", "女性", "其他")),
fill = list(Count = 0)) # 確保所有標籤顯示
ggplot(C1_data, aes(x = Gender, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
)+
labs(title = "性別分布", x = "性別", y = "人\n數")
# C2. 最高學歷
C2_data <- NNdata %>%
select("請問您的最高學歷是.") %>%
rename(Education = "請問您的最高學歷是.") %>%
filter(!is.na(Education)) %>% # 去除 NA
mutate(Education = factor(Education, levels = c(1, 2, 3, 4, 5, 6),
labels = c("小學或未就學", "國中／初中", "高中／高職",
"專科", "大學", "研究所"))) %>%
group_by(Education) %>%
summarize(Count = n()) %>%
complete(Education = factor(c("小學或未就學", "國中／初中", "高中／高職",
"專科", "大學", "研究所"),
levels = c("小學或未就學", "國中／初中", "高中／高職",
"專科", "大學", "研究所")),
fill = list(Count = 0)) # 確保所有標籤顯示
ggplot(C2_data, aes(x = Education, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.5) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "最高學歷分布", x = "最高學歷", y = "人\n數")
# 根據地理位置調整順序
C3_data <- NNdata %>%
select("請問您現在的.居住地.在哪個縣市.") %>%
rename(Location = "請問您現在的.居住地.在哪個縣市.") %>%
filter(!is.na(Location)) %>%
mutate(Location = factor(Location, levels = c(1:23),
labels = c("台北市", "新北市", "基隆市", "桃園市", "新竹市",
"新竹縣", "宜蘭縣", "苗栗縣", "台中市", "彰化縣",
"南投縣", "雲林縣", "嘉義市", "嘉義縣", "台南市",
"高雄市", "屏東縣", "花蓮縣", "台東縣", "澎湖縣",
"金門縣", "連江縣", "海外地區"))) %>%
group_by(Location) %>%
summarize(Count = n()) %>%
complete(Location = factor(c("台北市", "新北市", "基隆市", "桃園市", "新竹市",
"新竹縣", "宜蘭縣", "苗栗縣", "台中市", "彰化縣",
"南投縣", "雲林縣", "嘉義市", "嘉義縣", "台南市",
"高雄市", "屏東縣", "花蓮縣", "台東縣", "澎湖縣",
"金門縣", "連江縣", "海外地區"),
levels = c("台北市", "新北市", "基隆市", "桃園市", "新竹市",
"新竹縣", "宜蘭縣", "苗栗縣", "台中市", "彰化縣",
"南投縣", "雲林縣", "嘉義市", "嘉義縣", "台南市",
"高雄市", "屏東縣", "花蓮縣", "台東縣", "澎湖縣",
"金門縣", "連江縣", "海外地區")),
fill = list(Count = 0))
# 繪製長條圖
ggplot(C3_data, aes(x = Count, y = fct_rev(Location))) +
geom_bar(stat = "identity", fill = "grey40" ,width = 0.9) +
geom_text(aes(label = Count), hjust = -0.3, size = 3, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "居住地分布", x = "人數", y = "居\n住\n地")
# 假設 NNdata 是你的原始資料框
# 計算年齡
NNdata <- NNdata %>%
mutate(
Birth_Year_Western = `請問您是民國幾年出生.` + 1911, # 將民國年換算成西元年
Age = 2024 - Birth_Year_Western # 計算年齡
)
# 確保字體顯示正常
font_add("KaiTi", regular = "path_to_your_font/標楷體.ttc")
showtext_auto()
# 計算平均年齡和中位數
mean_age <- mean(NNdata$Age, na.rm = TRUE)
median_age <- median(NNdata$Age, na.rm = TRUE)
# 繪製年齡分布圖，並添加參考線
ggplot(NNdata, aes(x = Age)) +
geom_histogram(binwidth = 5, fill = "grey40") +
scale_x_continuous(breaks = seq(0, max(NNdata$Age, na.rm = TRUE), by = 5)) + # 設置 x 軸每 5 歲顯示一個刻度
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "年齡分布", x = "年齡", y = "人\n數")
# D1. 訪談意願
D1_data <- NNdata %>%
select("請問您是否有意願接受訪談.") %>%
rename(Willingness = "請問您是否有意願接受訪談.") %>%
filter(!is.na(Willingness)) %>% # 去除 NA
mutate(Willingness = factor(Willingness, levels = c(1, 2),
labels = c("是", "否"))) %>%
group_by(Willingness) %>%
summarize(Count = n()) %>%
complete(Willingness = factor(c("是", "否"),
levels = c("是", "否")),
fill = list(Count = 0)) # 確保所有標籤顯示
ggplot(D1_data, aes(x = Willingness, y = Count)) +
geom_bar(stat = "identity", fill = "grey40", width = 0.4) +
geom_text(aes(label = Count), vjust = -0.5, size = 4, family = "KaiTi") +
theme_minimal(base_family = "KaiTi") +
theme(
text = element_text(size = 10, family = "KaiTi", hjust = 0.5, vjust = 0.5), # 文字置中
axis.text.y = element_text(size = 10, hjust = 0.5, family = "KaiTi"), # y 軸標籤置中
axis.text.x = element_text(size = 10, hjust = 0.5, angle = , face = "bold", family = "KaiTi"), # x 軸標籤置中
axis.title.x = element_text(size = 12, hjust = 0.5, vjust = 1, family = "KaiTi"), # x 軸標題置中
axis.title.y = element_text(size = 12, angle = 0, vjust = 0.5, hjust = 0.5, family = "KaiTi"), # y 軸標題置中
plot.title = element_text(size = 14, face = "bold", hjust = 0.5, family = "KaiTi"), # 標題置中
legend.position = "none", # 隱藏圖例
axis.line = element_line(color = "black")
) +
labs(title = "訪談意願分布", x = "訪談意願", y = "人\n數")
