如何使用不同的参数进行排序和着色

import pandas as pd

# 创建一个示例DataFrame
data = {
    'Name': ['Alice', 'Bob', 'Charlie', 'David'],
    'Age': [24, 27, 22, 32],
    'Score': [85, 90, 88, 78]
}
df = pd.DataFrame(data)

# 按Age列升序排序
df_sorted_by_age = df.sort_values(by='Age')

# 按Score列降序排序
df_sorted_by_score = df.sort_values(by='Score', ascending=False)

# 创建一个示例数据框
data <- data.frame(
  Name = c("Alice", "Bob", "Charlie", "David"),
  Age = c(24, 27, 22, 32),
  Score = c(85, 90, 88, 78)
)

# 按Age列升序排序
df_sorted_by_age <- data[order(data$Age), ]

# 按Score列降序排序
df_sorted_by_score <- data[order(-data$Score), ]

import pandas as pd
import matplotlib.pyplot as plt

# 创建一个示例DataFrame
data = {
    'Name': ['Alice', 'Bob', 'Charlie', 'David'],
    'Age': [24, 27, 22, 32],
    'Score': [85, 90, 88, 78]
}
df = pd.DataFrame(data)

# 绘制散点图，根据Age着色
plt.scatter(df['Score'], df['Age'], c=df['Age'], cmap='viridis')
plt.colorbar(label='Age')
plt.xlabel('Score')
plt.ylabel('Age')
plt.show()

# 安装和加载ggplot2包
install.packages("ggplot2")
library(ggplot2)

# 创建一个示例数据框
data <- data.frame(
  Name = c("Alice", "Bob", "Charlie", "David"),
  Age = c(24, 27, 22, 32),
  Score = c(85, 90, 88, 78)
)

# 绘制散点图，根据Age着色
ggplot(data, aes(x = Score, y = Age, color = Age)) +
  geom_point() +
  scale_color_gradient(low = "blue", high = "red") +
  labs(x = "Score", y = "Age", color = "Age")