pyplot：在直方图上绘制平滑曲线

Question

有一个使用 DataFrame 作为数据源渲染的直方图：

import seaborn as sns
import matplotlib.pyplot as plt

plt.rcParams["figure.figsize"] = (14,14)

df['rawValue'].hist(bins=100)
    
plt.show()

Q.如何在直方图前面添加平滑曲线？（曲线与直方图共享相同的数据源）？

PS只是对想要的内容的描述（纯粹是示意性的）：

Answer 1

据我所知，最常见的方法是使用核密度估计。您可以在此处和此处阅读有关如何在 Python 中实现它的信息。以下是如何使用pandas和seaborn在直方图上绘制 KDE 的几个示例：

导入包并为两个示例创建示例数据集

import numpy as np                 # v 1.19.2
import pandas as pd                # v 1.1.3
import matplotlib.pyplot as plt    # v 3.3.2
import seaborn as sns              # v 0.11.0

# Create sample dataset
rng = np.random.default_rng(seed=123)  # random number generator
df = pd.DataFrame(dict(variable = rng.normal(size=1000)))

熊猫

# Plot pandas histogram from dataframe with df.plot.hist (not df.hist)
ax = df['variable'].plot.hist(bins=20, density=True, edgecolor='w', linewidth=0.5)

# Save default x-axis limits for final formatting because the pandas kde
# plot uses much wider limits which usually decreases readability
xlim = ax.get_xlim()

# Plot pandas KDE
df['variable'].plot.density(color='k', alpha=0.5, ax=ax) # same as df['var'].plot.kde()

# Reset x-axis limits and edit legend and add title
ax.set_xlim(xlim)
ax.legend(labels=['KDE'], frameon=False)
ax.set_title('Pandas histogram overlaid with KDE', fontsize=14, pad=15)

plt.show()

西博恩

# Plot seaborn histogram overlaid with KDE
ax = sns.histplot(data=df['variable'], bins=20, stat='density', alpha= 1, kde=True,
                  edgecolor='white', linewidth=0.5,
                  line_kws=dict(color='black', alpha=0.5, linewidth=1.5, label='KDE'))
ax.get_lines()[0].set_color('black') # edit line color due to bug in sns v 0.11.0

# Edit legemd and add title
ax.legend(frameon=False)
ax.set_title('Seaborn histogram overlaid with KDE', fontsize=14, pad=15)

plt.show()