python数据分析与机器学习实战-12.Seaborn整体风格布局及细节设置

import seaborn as sns
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
%matplotlib inline

def sinplot(flip=1):
    x=np.linspace(0,14,100)
    for i in range(1,7):
        plt.plot(x,np.sin(x+i*0.5)*(7-i)*flip)
sinplot()

sns.set()
sinplot()

sns.set_style("ticks")
data = np.random.normal(size=(20,6))+np.arange(6)/2
sns.boxplot(data=data)
<matplotlib.axes._subplots.AxesSubplot at 0x1a1d097668>

sns.set_style("white")
sinplot()

sinplot()
sns.despine()

sns.violinplot(data)
sns.despine(offset=10)

with sns.axes_style("darkgrid"):
    plt.subplot(2,1,1)
    sinplot()
plt.subplot(2,1,2)
sinplot(-1)

sns.set()
sns.set_context("paper")
plt.figure(figsize=(8,6))
sinplot()

sns.set_context("talk")
plt.figure(figsize=(8,6))
sinplot()

sns.set_context("poster")
plt.figure(figsize=(8,6))
sinplot()

sns.set_context("notebook",font_scale=2.5,rc={'lines.linewidth':4.5})
plt.figure(figsize=(8,6))
sinplot()

# seaborn