Python | Seaborn可视化合集 | 分布图（Distribution）之箱线图

分布图（Distribution）

3 箱线图 （Boxplot）

# 数据设置及库导入
import seaborn as sns
import matplotlib.pyplot as plt
df = sns.load_dataset('iris')

# 绘图
sns.boxplot( x=df["species"], y=df["sepal_width"] )

OUTPUT:

3.1 颜色设置

import seaborn as sns
import matplotlib.pyplot as plt
df = sns.load_dataset('iris')

# 背景以及用自带调色盘设置颜色
sns.set(style="darkgrid")
sns.boxplot(x=df["species"], y=df["sepal_width"], palette="Blues")
plt.show()

# 若用参数 color=blue 则所有箱线图均为一种颜色

OUTPUT:

import seaborn as sns
import matplotlib.pyplot as plt
df = sns.load_dataset('iris')

# 背景以及用自定义调色盘设置颜色
sns.set(style="darkgrid")
mypal = {"versicolor": "green", "setosa": "cyan", "virginica":"skyblue"}
sns.boxplot(x=df["species"], y=df["sepal_width"], palette=mypal)
plt.show()

 OUTPUT:

 3.2 多组数据

# 数据以及库的设置
import seaborn as sns
import matplotlib.pyplot as plt
df = sns.load_dataset('tips')

# 根据性别将数据分为两组并绘图
sns.boxplot(x="day", y="total_bill", hue="sex", data=df, palette="Set2")
plt.show()

 OUTPUT:

3.3 添加抖动点 

# 库和数据设置
import seaborn as sns
import matplotlib.pyplot as plt
df = sns.load_dataset('iris')

# 绘制箱线图
ax = sns.boxplot(x='species', y='sepal_width', data=df)
 
# 添加抖动点
ax = sns.swarmplot(x='species', y='sepal_width', data=df, color="black")
plt.show()

 OUTPUT:

 3.4 添加数据标签

# 库和数据设置
import seaborn as sns
import matplotlib.pyplot as plt
df = sns.load_dataset('iris')

# 绘制箱线图
ax = sns.boxplot(x="species", y="sepal_width", data=df)
 
# 计算中位数
medians = df.groupby(['species'])['sepal_width'].median().values
nobs = df['species'].value_counts().values
nobs = [str(x) for x in nobs.tolist()]
nobs = ["n: " + i for i in nobs]
 
# 将数据标签添加入箱线图中
pos = range(len(nobs))
for tick,label in zip(pos,ax.get_xticklabels()):
    ax.text(pos[tick],
            medians[tick] + 0.03,
            nobs[tick],
            horizontalalignment='center',
            size='large',
            color='white',
            weight='semibold')
 
plt.show()

 OUTPUT:

 3.5 设置形状和大小

# 库和数据设置
import seaborn as sns
import matplotlib.pyplot as plt
df = sns.load_dataset('iris')

# linewidth设置箱线图线条粗细
sns.boxplot(x=df["species"], y=df["sepal_width"], linewidth=5)
plt.show()

OUTPUT:

# 库和数据设置
import seaborn as sns
import matplotlib.pyplot as plt
df = sns.load_dataset('iris')

# width改变箱线图大小
sns.boxplot(x=df["species"], y=df["sepal_width"], width=0.5)
plt.show()

OUTPUT:

# 库和数据设置
import seaborn as sns
import matplotlib.pyplot as plt
df = sns.load_dataset('iris')

# notch设置箱线图凹槽
sns.boxplot(x=df["species"], y=df["sepal_width"], notch=True)
plt.show()

OUTPUT: