seaborn与matplotlib
import matplotlib.pyplot as plt
plt.style.use('classic')
%matplotlib inline
import numpy as np
import pandas as pd
# Create some data
rng = np.random.RandomState(0)
x = np.linspace(0, 10, 500)
y = np.cumsum(rng.randn(500, 6), 0)
plt.plot(x, y)
plt.legend('ABCDEF', ncol=2, loc='upper left');
使用seaborn
import seaborn as sns
sns.set()
# same plotting code as above!
plt.plot(x, y)
plt.legend('ABCDEF', ncol=2, loc='upper left');
深入seaborn绘图
sns有很多绘图方法,例如:
for col in 'xy':
plt.hist(data[col], normed=True, alpha=0.5)
sns.kdeplot(data[col], shade=True)
sns.distplot(data['x'])
sns.kdeplot(data);
with sns.axes_style('white'):
sns.jointplot("x", "y", data, kind='kde');
with sns.axes_style('white'):
sns.jointplot("x", "y", data, kind='hex')
sns.violinplot("gender", "split_frac", data=data,
palette=["lightblue", "lightpink"]);
pair 分图
iris = sns.load_dataset("iris")
iris.head()
sns.pairplot(iris, hue='species', size=2.5);
各向分图
with sns.axes_style('white'):
sns.jointplot("total_bill", "tip", data=tips, kind='hex')

sns.jointplot("total_bill", "tip", data=tips, kind='reg');
