Python Pandas – 使用Seaborn在箱线图上绘制一组观测数据

Seaborn的Swarm Plot用于绘制非重叠点的分类散点图。可以使用seaborn.swarmplot()方法来实现。使用seaborn.boxplot()方法绘制箱线图，可以在其上方绘制观测数据点的swarmplot。

假设以下是我们的数据集，以CSV文件的形式呈现− Cricketers2.csv

首先，导入所需的库−

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

从CSV文件中加载数据到Pandas DataFrame中−

dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers2.csv")

在箱线图上方绘制swarms观测数据点−

sb.boxplot(x = "Matches", y = "Role", data= dataFrame, whis=np.inf)
sb.swarmplot(x = "Matches", y = "Role", data= dataFrame, color=".3")

示例代码

下面是代码

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

# Load data from a CSV file into a Pandas DataFrame
dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers2.csv")

sb.set_theme(style="whitegrid")

# draw swarms of observations on top of a box plot
sb.boxplot(x = "Matches", y = "Role", data= dataFrame, whis=np.inf)
sb.swarmplot(x = "Matches", y = "Role", data= dataFrame, color=".3")

# display
plt.show()