Seaborn简单画图(二) -- 直方图和密度图

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pandas import Series, DataFrame
%matplotlib inline
import seaborn as sns

# 使用matplotlib
s1 = Series(np.random.randn(1000))  
plt.hist(s1)
(array([   6.,   33.,   98.,  154.,  230.,  218.,  163.,   61.,   29.,    8.]),
 array([-2.96113056, -2.35197999, -1.74282942, -1.13367884, -0.52452827,
         0.08462231,  0.69377288,  1.30292346,  1.91207403,  2.52122461,
         3.13037518]),
 <a list of 10 Patch objects>)

![这里写图片描述](https://img-blog.csdn.net/20180721160403550?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTc3ODU3MA==/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70)

s1.plot(kind='kde')
<matplotlib.axes._subplots.AxesSubplot at 0x277853b9a20>

Seaborn

# 同时绘制密度图和直方图
sns.distplot(s1, hist=True, kde=True)
<matplotlib.axes._subplots.AxesSubplot at 0x277853b9a20>

sns.distplot(s1, hist=True, kde=False, rug=True)
<matplotlib.axes._subplots.AxesSubplot at 0x277859199e8>

sns.distplot(s1, bins=20, hist=True, kde=False, rug=True, color='k')

# 绘制密度图的另一种方法，shada阴影填充
sns.kdeplot(s1, shade=True, color='r')