diff --git a/Hiplot/051-eulerr.qmd b/Hiplot/051-eulerr.qmd
index 2fb6f93fa..9c5f0d25f 100644
--- a/Hiplot/051-eulerr.qmd
+++ b/Hiplot/051-eulerr.qmd
@@ -2,7 +2,6 @@
 title: "Eulerr Plot"
 author:
   - "**[Editor]** [Hu Zheng](https://github.com/ZhengTiger);"
-  - "**[Contributors]** "
 ---
 
 ::: callout-note
@@ -19,16 +18,10 @@ This page is the tutorial for source code version of the Hiplot `Eulerr Plot` pl
 
 -   Programming language: R
 
--   Dependent packages: `data.table`; `jsonlite`; `eulerr`; `ggplotify`
+-   Dependent packages: `eulerr`; `ggplotify`
 
 ```{r packages setup, message=FALSE, warning=FALSE, output=FALSE}
 # Install packages
-if (!requireNamespace("data.table", quietly = TRUE)) {
-  install.packages("data.table")
-}
-if (!requireNamespace("jsonlite", quietly = TRUE)) {
-  install.packages("jsonlite")
-}
 if (!requireNamespace("eulerr", quietly = TRUE)) {
   install.packages("eulerr")
 }
@@ -37,8 +30,6 @@ if (!requireNamespace("ggplotify", quietly = TRUE)) {
 }
 
 # Load packages
-library(data.table)
-library(jsonlite)
 library(eulerr)
 library(ggplotify)
 ```
@@ -50,17 +41,16 @@ sessioninfo::session_info("attached")
 ## Data Preparation
 
 ```{r load data, message=FALSE, warning=FALSE}
-# Load data
-data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/eulerr/data.json")$exampleData$textarea[[1]])
-data <- as.data.frame(data)
-
-# convert data structure
-genes <- as.numeric(data[, 2])
-names(genes) <- as.character(data[, 1])
+# Self-contained example: synthetic gene counts for three cancer types
+genes <- c(
+  "LUAD" = 1000, "BRCA" = 1200, "COAD" = 800,
+  "LUAD&BRCA" = 200, "LUAD&COAD" = 150, "BRCA&COAD" = 180,
+  "LUAD&BRCA&COAD" = 80
+)
 euler_set <- euler(genes)
-  
+
 # View data
-head(data)
+print(genes)
 ```
 
 ## Visualization
@@ -75,15 +65,16 @@ head(data)
 #| message: false
 
 # Eulerr Plot
-fill <- c("#3B4992FF","#EE0000FF","#008B45FF","#631879FF","#008280FF","#BB0021FF",
-          "#5F559BFF","#A20056FF")
+fill_colors <- c("#3B4992FF", "#EE0000FF", "#008B45FF", "#631879FF",
+                 "#008280FF", "#BB0021FF", "#5F559BFF", "#A20056FF")
 n_sets <- length(euler_set$sets)
+n_subsets <- length(euler_set$original.values)
 p <- as.ggplot(
   plot(euler_set,
-    labels = list(col = rep("white", length(genes))),
-    fills = list(fill = fill[seq_len(n_sets)]),
+    labels = list(col = rep("white", n_sets)),
+    fills = list(fill = rep_len(fill_colors, n_sets)),
     quantities = list(type = c("percent", "counts"),
-    col = rep("white", length(genes))),
+    col = rep("white", n_subsets)),
     main = "Eulerr")
 )
 
diff --git a/Hiplot/051-eulerr.zh.qmd b/Hiplot/051-eulerr.zh.qmd
index 43ad18652..20bce86c3 100644
--- a/Hiplot/051-eulerr.zh.qmd
+++ b/Hiplot/051-eulerr.zh.qmd
@@ -2,7 +2,6 @@
 title: "比例韦恩图"
 author:
   - "**[编辑]** [郑虎](https://github.com/ZhengTiger);"
-  - "**[审核]** ."
 ---
 
 ::: callout-note
@@ -19,16 +18,10 @@ author:
 
 -   编程语言: R
 
--   依赖包: `data.table`; `jsonlite`; `eulerr`; `ggplotify`
+-   依赖包: `eulerr`; `ggplotify`
 
 ```{r packages setup, message=FALSE, warning=FALSE, output=FALSE}
 # 安装包
-if (!requireNamespace("data.table", quietly = TRUE)) {
-  install.packages("data.table")
-}
-if (!requireNamespace("jsonlite", quietly = TRUE)) {
-  install.packages("jsonlite")
-}
 if (!requireNamespace("eulerr", quietly = TRUE)) {
   install.packages("eulerr")
 }
@@ -37,8 +30,6 @@ if (!requireNamespace("ggplotify", quietly = TRUE)) {
 }
 
 # 加载包
-library(data.table)
-library(jsonlite)
 library(eulerr)
 library(ggplotify)
 ```
@@ -50,17 +41,16 @@ sessioninfo::session_info("attached")
 ## 数据准备
 
 ```{r load data, message=FALSE, warning=FALSE}
-# 加载数据
-data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/eulerr/data.json")$exampleData$textarea[[1]])
-data <- as.data.frame(data)
-
-# 整理数据格式
-genes <- as.numeric(data[, 2])
-names(genes) <- as.character(data[, 1])
+# 自包含示例：三种癌症类型的模拟基因数目
+genes <- c(
+  "LUAD" = 1000, "BRCA" = 1200, "COAD" = 800,
+  "LUAD&BRCA" = 200, "LUAD&COAD" = 150, "BRCA&COAD" = 180,
+  "LUAD&BRCA&COAD" = 80
+)
 euler_set <- euler(genes)
-  
+
 # 查看数据
-head(data)
+print(genes)
 ```
 
 ## 可视化
@@ -75,15 +65,16 @@ head(data)
 #| message: false
 
 # 比例韦恩图
-fill <- c("#3B4992FF","#EE0000FF","#008B45FF","#631879FF","#008280FF","#BB0021FF",
-          "#5F559BFF","#A20056FF")
+fill_colors <- c("#3B4992FF", "#EE0000FF", "#008B45FF", "#631879FF",
+                 "#008280FF", "#BB0021FF", "#5F559BFF", "#A20056FF")
 n_sets <- length(euler_set$sets)
+n_subsets <- length(euler_set$original.values)
 p <- as.ggplot(
   plot(euler_set,
-    labels = list(col = rep("white", length(genes))),
-    fills = list(fill = fill[seq_len(n_sets)]),
+    labels = list(col = rep("white", n_sets)),
+    fills = list(fill = rep_len(fill_colors, n_sets)),
     quantities = list(type = c("percent", "counts"),
-    col = rep("white", length(genes))),
+    col = rep("white", n_subsets)),
     main = "Eulerr")
 )