在直方图上添加密度曲线 [英] Add density curve on the histogram

问题描述

我能够在 python 中制作直方图，但我无法添加密度曲线，我看到许多代码使用不同的方式在直方图上添加密度曲线，但我不知道如何使用我的代码

我添加了 density = true 但无法在直方图上获得密度曲线

  df = pd.DataFrame(np.random.randn(100，4)，columns = list('ABCD'))X = df ['A']hist，bins = np.histogram(X，bins = 10，density = True)宽度 = 0.7 * (bins[1] - bins[0])中心=(bins [:-1] + bins [1:])/2plt.bar(center, hist, align='center', width=width)plt.show()

解决方案

以下是使用

但是， distplot 将

sns.displot

将pandas导入为pd导入matplotlib.pyplot作为plt将 seaborn 作为 sns 导入将numpy导入为npdf = pd.DataFrame(np.random.randn(100，4)，columns = list('ABCD'))X = df ['A']sns.displot(X, kde=True, bins=20)plt.show()

I am able to make histogram in python but I am unable to add density curve , I see many code which are using different ways to add density curve on histogram but I am not sure how to get on my code

I have added density = true but not able to get density curve on histogram

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

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)
plt.show()

解决方案

Here is an approach using distplot method of seaborn. Also, mentioned in the comments:

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()

However, distplot will be removed in a future version of seaborn. Therefore, alternatives are to use histplot and 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()

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