library(ggplot2)library(reshape2)# 绘制直方图ggplot(train_df, aes(x = Age)) + geom_histogram(binwidth = 5, fill = "lightblue", col = "black") + labs(title = "Age Distribution", x = "Age", y = "Count")# 绘制条形图ggplot(train_df, aes(x = Sex, y = Survived, fill = factor(Sex))) + geom_bar(stat = "summary", fun = mean, position = "dodge") + scale_fill_manual(values = c("lightblue", "pink"), name = "Sex") + labs(title = "Survival Rate by Sex", x = "Sex", y = "Survival Rate")# 绘制热力图cor_matrix <- cor(train_df)melted_cor_matrix <- melt(cor_matrix)ggplot(melted_cor_matrix, aes(x = Var1, y = Var2, fill = value)) + geom_tile() + scale_fill_gradient2(low = "lightblue", mid = "white", high = "pink") + theme(axis.text.x = element_text(angle = 90, hjust = 1)) + labs(title = "Correlation Matrix")出现以下错误Error in cor(train_df): 'x' must be numeric Traceback: 1. cor(train_df) 2. stop("'x' must be numeric")

这个错误的原因是你尝试计算一个非数值变量的相关性。在这种情况下，应该先将非数值变量转换为数值变量，例如将 "Sex" 变量转换为二进制变量。可以使用以下代码来实现：

train_df$Sex <- ifelse(train_df$Sex == "male", 1, 0) # 将 "Sex" 变量转换为二进制变量
cor_matrix <- cor(train_df) # 计算相关性
melted_cor_matrix <- melt(cor_matrix)
ggplot(melted_cor_matrix, aes(x = Var1, y = Var2, fill = value)) + 
  geom_tile() + 
  scale_fill_gradient2(low = "lightblue", mid = "white", high = "pink") + 
  theme(axis.text.x = element_text(angle = 90, hjust = 1)) + 
  labs(title = "Correlation Matrix")

这段代码将 "Sex" 变量转换为二进制变量，并计算相关性，然后绘制热力图。