python - 具有多个分布的 seaborn distplot/displot

Question

我正在使用 seaborn 绘制分布图。我想用不同的颜色在同一个图上绘制多个分布:

这是我开始分布图的方式:

import numpy as np
import pandas as pd
from sklearn.datasets import load_iris
iris = load_iris()
iris = pd.DataFrame(data= np.c_[iris['data'], iris['target']],columns= iris['feature_names'] + ['target'])

   sepal length (cm)  sepal width (cm)  petal length (cm)  petal width (cm)  target
0                5.1               3.5                1.4               0.2     0.0
1                4.9               3.0                1.4               0.2     0.0
2                4.7               3.2                1.3               0.2     0.0
3                4.6               3.1                1.5               0.2     0.0
4                5.0               3.6                1.4               0.2     0.0

sns.distplot(iris[['sepal length (cm)']], hist=False, rug=True);

'target' 列包含 3 个值:0、1、2。

我希望看到一个萼片长度分布图，其中 target ==0、target ==1 和 target ==2，一共3个地 block 。

Answer 1

重要的是按 target 为 0、1 或 2 的值对数据帧进行排序.

import numpy as np
import pandas as pd
from sklearn.datasets import load_iris
import seaborn as sns

iris = load_iris()
iris = pd.DataFrame(data=np.c_[iris['data'], iris['target']],
                    columns=iris['feature_names'] + ['target'])

# Sort the dataframe by target
target_0 = iris.loc[iris['target'] == 0]
target_1 = iris.loc[iris['target'] == 1]
target_2 = iris.loc[iris['target'] == 2]

sns.distplot(target_0[['sepal length (cm)']], hist=False, rug=True)
sns.distplot(target_1[['sepal length (cm)']], hist=False, rug=True)
sns.distplot(target_2[['sepal length (cm)']], hist=False, rug=True)

plt.show()

输出如下:

如果您不知道 target 可能有多少个值，请在 target 列中找到唯一值，然后对数据框进行切片并适本地添加到图中。

import numpy as np
import pandas as pd
from sklearn.datasets import load_iris
import seaborn as sns

iris = load_iris()
iris = pd.DataFrame(data=np.c_[iris['data'], iris['target']],
                    columns=iris['feature_names'] + ['target'])

unique_vals = iris['target'].unique()  # [0, 1, 2]

# Sort the dataframe by target
# Use a list comprehension to create list of sliced dataframes
targets = [iris.loc[iris['target'] == val] for val in unique_vals]

# Iterate through list and plot the sliced dataframe
for target in targets:
    sns.distplot(target[['sepal length (cm)']], hist=False, rug=True)