[Seaborn] seaborn 라이브러리 연습

 

 

In [12]:

import seaborn as sns
import pandas as pd
import numpy as np

In [2]:

sns.__version__

Out[2]:

'0.9.0'

In [3]:

sns.set()
sns.set_style('whitegrid')
sns.set_color_codes()

In [4]:

current_palette = sns.color_palette()
sns.palplot(current_palette)

 

In [5]:

tips = sns.load_dataset("tips")

In [17]:

tips.head(10)

Out[17]:

	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4
5	25.29	4.71	Male	No	Sun	Dinner	4
6	8.77	2.00	Male	No	Sun	Dinner	2
7	26.88	3.12	Male	No	Sun	Dinner	4
8	15.04	1.96	Male	No	Sun	Dinner	2
9	14.78	3.23	Male	No	Sun	Dinner	2

 

relplot¶

In [8]:

sns.relplot(x='total_bill', y = 'tip', hue = 'smoker', style = 'smoker', data=tips)

Out[8]:

<seaborn.axisgrid.FacetGrid at 0x7fd120c69898>

 

In [15]:

df = pd.DataFrame(dict(time=np.arange(500), value=np.random.randn(500).cumsum()))
g = sns.relplot(x='time', y='value', kind= 'line', data=df)
g.fig.autofmt_xdate()

 

 

catplot¶

In [16]:

sns.catplot(x='day', y='total_bill', hue='smoker',
           col='time', aspect=.6,
           kind = 'swarm', data = tips)

Out[16]:

<seaborn.axisgrid.FacetGrid at 0x7fd140964f60>

 

In [19]:

titanic = sns.load_dataset('titanic')
g = sns.catplot(x='fare', y='survived', row='class', kind='box', orient='h', height=1.5, aspect=4,
               data=titanic.query('fare > 0'))
g.set(xscale='log');

 

 

pairplot¶

In [21]:

iris = sns.load_dataset('iris')
sns.pairplot(iris, hue = 'species')

Out[21]:

<seaborn.axisgrid.PairGrid at 0x7fd140cf7940>

 

In [22]:

sns.pairplot(iris, hue='species', palette='husl')

Out[22]:

<seaborn.axisgrid.PairGrid at 0x7fd0f0ce2b70>

 

In [23]:

sns.pairplot(iris, vars=['sepal_width', 'sepal_length'])

Out[23]:

<seaborn.axisgrid.PairGrid at 0x7fd16150ae48>

 

 

Heatmap¶

In [27]:

from matplotlib import pyplot as plt

flights = sns.load_dataset('flights')
flights = flights.pivot('month', 'year', 'passengers')
plt.figure(figsize=(15, 15))
ax = sns.heatmap(flights, annot=True, fmt='d')