[Seaborn] seaborn scatter tutorial

참고: https://seaborn.pydata.org/tutorial/relational.html

Visualizing statistical relationships — seaborn 0.9.0 documentation

 

 

 

In [1]:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style="darkgrid")

In [7]:

tips = sns.load_dataset('tips')
tips.head(10)

Out[7]:

	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

In [3]:

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

Out[3]:

<seaborn.axisgrid.FacetGrid at 0x7ff0b1d74390>

 

 

라벨링을 매기고싶다면 relplot의 hue변수를 이용¶

In [4]:

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

Out[4]:

<seaborn.axisgrid.FacetGrid at 0x7ff0b1af2fd0>

 

 

라벨링과 더불어 마크유형도 바꾸고싶다면 style변수를 이용¶

In [5]:

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

Out[5]:

<seaborn.axisgrid.FacetGrid at 0x7ff070ab4b70>

 

 

마크유형을 다른 column정보를 이용하여 변형이 가능함¶

In [6]:

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

Out[6]:

<seaborn.axisgrid.FacetGrid at 0x7ff0b1cbf9e8>

 

 

column에서 카테고리형이 아닌 변수형에도 적용이 가능¶

In [8]:

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

Out[8]:

<seaborn.axisgrid.FacetGrid at 0x7ff080af3b38>

 

 

hue는 카테고리를 지정하고, size변수는 변수형타입일때 표시해주는 크기를 설정해줌¶

In [9]:

sns.relplot(x= 'total_bill', y='tip', size='size', data=tips)

Out[9]:

<seaborn.axisgrid.FacetGrid at 0x7ff0b20ff780>

 

 

size변수를 이용할때 원 크기를 조정이 가능함¶

In [10]:

sns.relplot(x= 'total_bill', y='tip', size='size', sizes=(15,200), data=tips)

Out[10]:

<seaborn.axisgrid.FacetGrid at 0x7ff070b94358>