distplot已删除：removed in a future version of seaborn。因此，替代方案是使用histplot和displot。

sns.histplot

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

df = pd.DataFrame(np.random.randn(100, 4), columns=list('ABCD'))
X = df['A']

sns.histplot(X, kde=True, bins=20)
plt.show()

sns.displot

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

df = pd.DataFrame(np.random.randn(100, 4), columns=list('ABCD'))
X = df['A']

sns.displot(X, kde=True, bins=20)
plt.show()

distplot已移除

下面是使用seaborn的distplot方法的方法。此外，在评论中提到：

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

df = pd.DataFrame(np.random.randn(100, 4), columns=list('ABCD'))
X = df['A']

sns.distplot(X, kde=True, bins=20, hist=True)
plt.show()

Pandas也有kde图：

hist, bins = np.histogram(X, bins=10,density=True)
width = 0.7 * (bins[1] - bins[0])
center = (bins[:-1] + bins[1:]) / 2
plt.bar(center, hist, align='center', width=width, zorder=1)

# density plot
df['A'].plot.kde(zorder=2, color='C1')
plt.show()

输出：