期末实验报告由5章节5个图形组成，每个章节需要作一个图形。
每个章节选择作什么图自主选择，作图前补充完整图形标题名称，例如：图形1——多变量条形图。
案例数据自主收集，不同章节可以公用一个数据集。但同学间不允许使用相同数据集。
每个章节的数据集合需要通过datatable 函数展示，并简要解释数据来源和变量意义。
每个输出图形后需要对图形作简要解读，最少需针对图形提出一个观点。
渲染html文件保留代码展示，6月22日前将发布网址提交至共享文档“8、期末报告” 列中。
评分标准：
每章节图形各20分
能有效输出图形和合理解释75%
数据独特性强10%
图形个性化强15%
以下是2010年至2024年中国财政关键数据的整理，主要涵盖一般公共预算收入、支出、赤字、债务及部分金融指标。
数据来源：国家统计局、财政部及审计署等官方报告
时间跨度：2010-2024年
library(readxl)
data1 <- read_excel("zuoye.xlsx")
DT::datatable(data1,rownames = FALSE)# 创建数据框（或从CSV读取）
fiscal_data <- data.frame(
year = 2010:2024,
revenue = c(8.30, 10.37, 11.73, 12.90, 14.04, 15.22, 15.96, 17.26, 18.34, 19.04, 18.29, 20.25, 20.37, 21.68, 21.97),
expenditure = c(8.90, 10.89, 12.60, 14.00, 15.18, 17.58, 18.78, 20.33, 22.09, 23.89, 24.56, 24.63, 26.19, 27.46, 28.46)
)library(ggplot2)
library(dplyr)
library(tidyr)
# 转换数据为长格式（适合ggplot2）
fiscal_long <- fiscal_data %>%
pivot_longer(
cols = c(revenue, expenditure),
names_to = "category",
values_to = "amount"
)
# 绘制玫瑰图
ggplot(fiscal_long, aes(x = factor(year), y = amount, fill = category)) +
geom_bar(stat = "identity", width = 1, color = "white") +
coord_polar(start = 0) + # 转换为极坐标
scale_fill_manual(
values = c("revenue" = "#4E79A7", "expenditure" = "#E15759"),
labels = c("财政收入", "财政支出")
) +
labs(
title = "中国财政收入与支出（2010-2024）",
subtitle = "单位：万亿元",
fill = "类别"
) +
theme_minimal() +
theme(
axis.title = element_blank(),
axis.text.y = element_blank(),
panel.grid = element_blank(),
plot.title = element_text(hjust = 0.5, size = 16, face = "bold"),
plot.subtitle = element_text(hjust = 0.5, size = 12)
)
每个年份的扇形区域代表财政数据。
内环为财政收入（蓝色），外环为财政支出（红色）。
半径长度对应数值大小（单位：万亿元）。
半径长度：代表财政金额（万亿元），半径越长数值越大。
角度范围：每个年份占据相同的角度（360°/15年=24°）。
颜色区分：蓝色（财政收入）和红色（财政支出）形成对比。
财政收入增长：蓝色环半径逐年增大（2010→2024增长2.6倍）。
支出扩张更快：红色环外扩更明显，尤其2020年后。
赤字可视化：红蓝环之间的差距代表赤字（2020年最宽）。
library(readxl)
data1 <- read_excel("zuoye.xlsx")
DT::datatable(data1,rownames = FALSE)# 创建数据框（或从CSV读取）
fiscal_data <- data.frame(
year = 2010:2024,
revenue = c(8.30, 10.37, 11.73, 12.90, 14.04, 15.22, 15.96, 17.26, 18.34, 19.04, 18.29, 20.25, 20.37, 21.68, 21.97),
expenditure = c(8.90, 10.89, 12.60, 14.00, 15.18, 17.58, 18.78, 20.33, 22.09, 23.89, 24.56, 24.63, 26.19, 27.46, 28.46)
)# 加载必要的包
library(ggplot2)
library(tidyr)
library(dplyr)
# 创建2010-2024中国财政数据框
fiscal_data <- data.frame(
Year = 2010:2024,
财政收入 = c(8.30, 10.37, 11.73, 12.90, 14.04, 15.22, 15.96, 17.26, 18.34, 19.04, 18.29, 20.25, 20.37, 21.68, 21.97),
财政支出 = c(8.90, 10.89, 12.60, 14.00, 15.18, 17.58, 18.78, 20.33, 22.09, 23.89, 24.56, 24.63, 26.19, 27.46, 28.46),
财政赤字 = c(0.60, 0.52, 0.87, 1.10, 1.14, 2.36, 2.82, 3.07, 3.75, 4.85, 6.27, 4.38, 5.83, 5.78, 6.49),
国债余额 = c(6.75, 7.20, 7.76, 8.66, 9.56, 10.66, 12.01, 13.48, 14.96, 16.80, 20.89, 23.20, 25.19, 29.50, 34.57),
地方政府债务余额 = c(10.72, 12.38, 15.89, 17.89, 15.40, 16.00, 15.32, 16.47, 18.39, 21.31, 25.66, 30.47, 35.07, 40.74, 47.54)
)
# 将数据转换为长格式（便于ggplot绘图）
fiscal_long <- fiscal_data %>%
pivot_longer(
cols = -Year,
names_to = "指标",
values_to = "数值"
)
# 创建箱线图
ggplot(fiscal_long, aes(x = 指标, y = 数值, fill = 指标)) +
geom_boxplot(
alpha = 0.7, # 填充透明度
outlier.shape = 21, # 异常点形状
outlier.size = 3, # 异常点大小
outlier.color = "red", # 异常点颜色
notch = TRUE # 中位数置信区间
) +
# 添加数据点（半透明显示）
geom_jitter(
width = 0.15,
alpha = 0.5,
color = "blue"
) +
# 添加标签
labs(
title = "中国财政主要指标分布（2010-2024年）",
subtitle = "箱线图展示中位数、四分位距及异常值",
x = "财政指标",
y = "数值（万亿元）",
caption = "数据来源：财政部年度报告"
) +
# 设置颜色
scale_fill_brewer(palette = "Set2") +
# 主题美化
theme_minimal(base_size = 12) +
theme(
legend.position = "none", # 移除图例
axis.text.x = element_text(angle = 45, hjust = 1), # x轴标签倾斜
plot.title = element_text(size = 16, face = "bold", hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5, color = "gray40"),
panel.grid.major.x = element_blank()
) +
# 添加中位数标签
stat_summary(
fun = median,
geom = "text",
aes(label = sprintf("%.1f", ..y..)),
position = position_nudge(x = -0.4),
size = 3.5,
color = "darkred"
)
# 可选：分面显示（避免尺度差异问题）
ggplot(fiscal_long, aes(x = 指标, y = 数值, fill = 指标)) +
geom_boxplot() +
facet_wrap(~指标, scales = "free_y", nrow = 2) +
labs(title = "中国财政指标分布（分面显示）") +
theme(axis.text.x = element_blank())
箱体下边界：第一四分位数(Q1)
箱体中线：中位数(Median)
箱体上边界：第三四分位数(Q3)
箱体高度：四分位距(IQR = Q3-Q1)
上下须线通常延伸至1.5倍IQR内的最远数据点
超出此范围的点为异常值（图中红点）
财政收入/支出：分布相对集中，中位数稳步上升
财政赤字：分布范围扩大，2020年后明显上移
国债余额：呈指数增长趋势，2024年有异常高值
地方政府债务：分布范围最广，离散程度最大
library(readxl)
data1 <- read_excel("zuoye.xlsx")
DT::datatable(data1,rownames = FALSE)# 创建数据框（或从CSV读取）
fiscal_data <- data.frame(
year = 2010:2024,
revenue = c(8.30, 10.37, 11.73, 12.90, 14.04, 15.22, 15.96, 17.26, 18.34, 19.04, 18.29, 20.25, 20.37, 21.68, 21.97),
expenditure = c(8.90, 10.89, 12.60, 14.00, 15.18, 17.58, 18.78, 20.33, 22.09, 23.89, 24.56, 24.63, 26.19, 27.46, 28.46)
)install.packages(
c("GGally", "ggplot2", "scales"),
repos = "https://mirrors.tuna.tsinghua.edu.cn/CRAN/"
)
There is a binary version available but the source version is later:
binary source needs_compilation
scales 1.3.0 1.4.0 FALSE
Error in download.file(url, destfile, method, mode = "wb", ...) :
cannot open URL 'https://mirrors.tuna.tsinghua.edu.cn/CRAN/bin/windows/contrib/4.3/GGally_2.2.1.zip'
Error in download.file(url, destfile, method, mode = "wb", ...) :
cannot open URL 'https://mirrors.tuna.tsinghua.edu.cn/CRAN/src/contrib/scales_1.4.0.tar.gz'library(GGally)
# 创建财政数据框（含GDP假设数据）
fiscal_data <- data.frame(
Year = 2010:2024,
财政收入 = c(8.30, 10.37, 11.73, 12.90, 14.04, 15.22, 15.96, 17.26, 18.34, 19.04, 18.29, 20.25, 20.37, 21.68, 21.97),
财政支出 = c(8.90, 10.89, 12.60, 14.00, 15.18, 17.58, 18.78, 20.33, 22.09, 23.89, 24.56, 24.63, 26.19, 27.46, 28.46),
财政赤字 = c(0.60, 0.52, 0.87, 1.10, 1.14, 2.36, 2.82, 3.07, 3.75, 4.85, 6.27, 4.38, 5.83, 5.78, 6.49),
国债余额 = c(6.75, 7.20, 7.76, 8.66, 9.56, 10.66, 12.01, 13.48, 14.96, 16.80, 20.89, 23.20, 25.19, 29.50, 34.57),
地方债务 = c(10.72, 12.38, 15.89, 17.89, 15.40, 16.00, 15.32, 16.47, 18.39, 21.31, 25.66, 30.47, 35.07, 40.74, 47.54),
GDP = c(40.2, 48.8, 54.0, 59.3, 64.4, 68.9, 74.6, 83.2, 91.9, 99.1, 101.4, 114.9, 121.0, 126.1, 130.0) # 假设GDP数据(万亿元)
)
# 制作散点图矩阵
ggpairs(
fiscal_data[, 2:7], # 选择需要分析的列
columns = c("财政收入", "财政支出", "财政赤字", "国债余额", "地方债务", "GDP"),
title = "中国财政指标关系矩阵（2010-2024）",
upper = list(continuous = wrap("cor", size = 4)), # 上三角显示相关系数
lower = list(continuous = wrap("points", alpha = 0.7, size = 2)), # 下三角散点图
diag = list(continuous = wrap("densityDiag", fill = "lightblue")) # 对角线显示密度曲线
) +
theme_bw(base_size = 12) +
theme(
plot.title = element_text(hjust = 0.5, face = "bold"),
panel.grid.minor = element_blank(),
axis.text.x = element_text(angle = 45, hjust = 1)
)
强协同增长：财政支出、收入与GDP高度同步
债务驱动模式：国债与地方债务呈现”双螺旋”上升
结构性风险：
赤字与债务增速超过经济增速
地方债务离散度增大（部分区域风险积聚）
library(readxl)
data1 <- read_excel("zuoye.xlsx")
DT::datatable(data1,rownames = FALSE)# 创建数据框（或从CSV读取）
fiscal_data <- data.frame(
year = 2010:2024,
revenue = c(8.30, 10.37, 11.73, 12.90, 14.04, 15.22, 15.96, 17.26, 18.34, 19.04, 18.29, 20.25, 20.37, 21.68, 21.97),
expenditure = c(8.90, 10.89, 12.60, 14.00, 15.18, 17.58, 18.78, 20.33, 22.09, 23.89, 24.56, 24.63, 26.19, 27.46, 28.46)
)# 安装必要包
install.packages(
c("ggplot2", "dplyr", "scales"),
repos = "https://mirrors.tuna.tsinghua.edu.cn/CRAN/"
)
There is a binary version available but the source version is later:
binary source needs_compilation
scales 1.3.0 1.4.0 FALSE
Error in download.file(url, destfile, method, mode = "wb", ...) :
cannot open URL 'https://mirrors.tuna.tsinghua.edu.cn/CRAN/src/contrib/scales_1.4.0.tar.gz'library(ggplot2)
library(dplyr)
library(scales)
install.packages("tidyr")
library(tidyr)
# 创建财政数据框（添加GDP假设数据）
fiscal_data <- data.frame(
Year = 2010:2024,
财政收入 = c(8.30, 10.37, 11.73, 12.90, 14.04, 15.22, 15.96, 17.26, 18.34, 19.04, 18.29, 20.25, 20.37, 21.68, 21.97),
财政支出 = c(8.90, 10.89, 12.60, 14.00, 15.18, 17.58, 18.78, 20.33, 22.09, 23.89, 24.56, 24.63, 26.19, 27.46, 28.46),
财政赤字 = c(0.60, 0.52, 0.87, 1.10, 1.14, 2.36, 2.82, 3.07, 3.75, 4.85, 6.27, 4.38, 5.83, 5.78, 6.49),
国债余额 = c(6.75, 7.20, 7.76, 8.66, 9.56, 10.66, 12.01, 13.48, 14.96, 16.80, 20.89, 23.20, 25.19, 29.50, 34.57),
地方债务 = c(10.72, 12.38, 15.89, 17.89, 15.40, 16.00, 15.32, 16.47, 18.39, 21.31, 25.66, 30.47, 35.07, 40.74, 47.54),
GDP = c(40.2, 48.8, 54.0, 59.3, 64.4, 68.9, 74.6, 83.2, 91.9, 99.1, 101.4, 114.9, 121.0, 126.1, 130.0) # 假设GDP数据(万亿元)
)
# 转换为长格式（用于分面）
fiscal_long <- fiscal_data %>%
pivot_longer(
cols = c(财政收入, 财政支出, 国债余额, 地方债务),
names_to = "指标类型",
values_to = "金额"
)
# 分面气泡图
ggplot(fiscal_long, aes(x = Year, y = 金额)) +
geom_point(
aes(size = 财政赤字, # 气泡大小映射赤字规模
color = GDP), # 颜色映射GDP增长
alpha = 0.7) +
scale_size_continuous(
name = "财政赤字(万亿元)",
range = c(3, 15), # 气泡大小范围
breaks = c(1, 3, 6)) +
scale_color_gradientn(
name = "GDP(万亿元)",
colors = c("#377EB8", "#4DAF4A", "#E41A1C"),
values = rescale(c(40, 85, 130))) +
facet_wrap(~指标类型,
ncol = 2,
scales = "free_y") + # y轴独立缩放
labs(
title = "中国财政指标分面气泡图（2010-2024）",
subtitle = "气泡大小=财政赤字 | 颜色=GDP规模",
x = "年份",
y = "金额（万亿元）"
) +
theme_minimal(base_size = 12) +
theme(
strip.background = element_rect(fill = "gray90"),
strip.text = element_text(face = "bold"),
legend.position = "right",
panel.grid.minor = element_blank(),
plot.title = element_text(hjust = 0.5, size = 16, face = "bold")
) +
scale_x_continuous(breaks = seq(2010, 2024, 2)) +
geom_text(
data = filter(fiscal_long, Year %in% c(2010, 2015, 2020, 2024)),
aes(label = Year),
size = 3,
vjust = -1.5)
债务驱动模式：地方债务与国债呈现”双轮驱动”
疫情冲击：2020年所有面板气泡特征突变
非线性关系：GDP增长与财政指标的相关性随时间变化
library(readxl)
data1 <- read_excel("zuoye.xlsx")
DT::datatable(data1,rownames = FALSE)# 创建数据框（或从CSV读取）
fiscal_data <- data.frame(
year = 2010:2024,
revenue = c(8.30, 10.37, 11.73, 12.90, 14.04, 15.22, 15.96, 17.26, 18.34, 19.04, 18.29, 20.25, 20.37, 21.68, 21.97),
expenditure = c(8.90, 10.89, 12.60, 14.00, 15.18, 17.58, 18.78, 20.33, 22.09, 23.89, 24.56, 24.63, 26.19, 27.46, 28.46)
)options(repos = c(CRAN = "https://mirrors.tuna.tsinghua.edu.cn/CRAN/"))
# 安装必要包
install.packages(c("ggplot2", "ggstream", "dplyr", "tidyr"))Error in download.file(url, destfile, method, mode = "wb", ...) :
cannot open URL 'https://mirrors.tuna.tsinghua.edu.cn/CRAN/bin/windows/contrib/4.3/ggstream_0.1.0.zip'library(ggplot2)
library(ggstream) # 流线图专用包
library(dplyr)
library(tidyr)
# 创建财政数据（长格式）
fiscal_long <- data.frame(
Year = rep(2010:2024, 3),
Category = rep(c("财政收入", "财政支出", "财政赤字"), each = 15),
Value = c(
c(8.30, 10.37, 11.73, 12.90, 14.04, 15.22, 15.96, 17.26, 18.34, 19.04, 18.29, 20.25, 20.37, 21.68, 21.97), # 收入
c(8.90, 10.89, 12.60, 14.00, 15.18, 17.58, 18.78, 20.33, 22.09, 23.89, 24.56, 24.63, 26.19, 27.46, 28.46), # 支出
c(0.60, 0.52, 0.87, 1.10, 1.14, 2.36, 2.82, 3.07, 3.75, 4.85, 6.27, 4.38, 5.83, 5.78, 6.49) # 赤字
)
) %>%
mutate(Value = ifelse(Category == "财政赤字", -Value, Value)) # 赤字负向显示
# 绘制基础流线图
ggplot(fiscal_long, aes(x = Year, y = Value, fill = Category)) +
geom_stream(
type = "mirror", # 镜像对称布局
bw = 0.6, # 平滑参数
extra_span = 0.2 # 两端扩展
) +
scale_fill_manual(
values = c("财政收入" = "#4E79A7",
"财政支出" = "#E15759",
"财政赤字" = "#59A14F"),
labels = c("财政收入", "财政支出", "赤字(支出-收入)")
) +
labs(
title = "中国财政收支流线图（2010-2024）",
subtitle = "单位：万亿元 | 赤字显示为支出超出部分",
x = "年份",
y = "金额",
fill = "类别"
) +
theme_minimal(base_size = 12) +
theme(
plot.title = element_text(hjust = 0.5, face = "bold"),
plot.subtitle = element_text(hjust = 0.5, color = "gray40"),
legend.position = "bottom",
panel.grid.major.x = element_line(color = "gray90"),
panel.grid.minor.x = element_blank()
) +
scale_x_continuous(breaks = seq(2010, 2024, 2)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "gray30")
上波浪：财政支出（红色）
下波浪：财政收入（蓝色）
中间绿色区域：财政赤字（支出>收入的部分）