分别使用python、R读取excel数据并进行统计分析，绘制箱线图、直方图并添加显著性

Python读取Excel数据进行统计分析并绘制图表：

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# 读取Excel数据
data = pd.read_excel("data.xlsx")

# 统计分析
mean = np.mean(data["value"])
median = np.median(data["value"])
std = np.std(data["value"])

# 绘制箱线图
plt.boxplot(data["value"])
plt.title("Boxplot of Data")
plt.show()

# 绘制直方图
plt.hist(data["value"], bins=10)
plt.title("Histogram of Data")
plt.xlabel("Value")
plt.ylabel("Frequency")
plt.show()

# 添加显著性
plt.boxplot(data["value"], notch=True)
plt.title("Boxplot of Data with Notch")
plt.show()

plt.hist(data["value"], bins=10, edgecolor="black", alpha=0.5)
plt.title("Histogram of Data with Alpha and Edgecolor")
plt.xlabel("Value")
plt.ylabel("Frequency")
plt.axvline(mean, color="red", linestyle="dashed", linewidth=2)
plt.axvline(median, color="green", linestyle="dashed", linewidth=2)
plt.show()

R读取Excel数据进行统计分析并绘制图表：

library(readxl)
library(ggplot2)

# 读取Excel数据
data <- read_excel("data.xlsx")

# 统计分析
mean <- mean(data$value)
median <- median(data$value)
sd <- sd(data$value)

# 绘制箱线图
ggplot(data, aes(x="", y=value)) + 
  geom_boxplot(fill="white", colour="black") + 
  theme_void() + 
  labs(title="Boxplot of Data")

# 绘制直方图
ggplot(data, aes(x=value)) + 
  geom_histogram(binwidth=1, colour="black", fill="white", alpha=0.5) + 
  labs(title="Histogram of Data", x="Value", y="Frequency")

# 添加显著性
ggplot(data, aes(x="", y=value)) + 
  geom_boxplot(fill="white", colour="black", notch=TRUE) + 
  theme_void() + 
  labs(title="Boxplot of Data with Notch")

ggplot(data, aes(x=value)) + 
  geom_histogram(binwidth=1, colour="black", fill="white", alpha=0.5) + 
  labs(title="Histogram of Data with Alpha and Edgecolor", x="Value", y="Frequency") + 
  geom_vline(xintercept=mean, color="red", linetype="dashed", size=1) + 
  geom_vline(xintercept=median, color="green", linetype="dashed", size=1)