【數據分析可視化】seaborn介紹

存在意義

是matplotlib的擴展封裝

簡單使用

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

/Users/bennyrhys/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
  return f(*args, **kwds)
/Users/bennyrhys/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
  return f(*args, **kwds)
/Users/bennyrhys/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
  return f(*args, **kwds)
/Users/bennyrhys/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
  return f(*args, **kwds)

iris = pd.read_csv('/Users/bennyrhys/Desktop/數據分析可視化-數據集/homework/iris.csv')

iris.head()

	SepalLength	SepalWidth	PetalLength	PetalWidth	Name
0	5.1	3.5	1.4	0.2	Iris-setosa
1	4.9	3.0	1.4	0.2	Iris-setosa
2	4.7	3.2	1.3	0.2	Iris-setosa
3	4.6	3.1	1.5	0.2	Iris-setosa
4	5.0	3.6	1.4	0.2	Iris-setosa

需求：畫一個花瓣（petal）和花萼（sepal）長度的散點圖，並且點的顏色要區分鳶尾花的種類

# 花的種類
iris.Name.unique()

array(['Iris-setosa', 'Iris-versicolor', 'Iris-virginica'], dtype=object)

# 設置對應顏色字典
color_map = dict(zip(iris.Name.unique(),['blue','green','red']))
color_map

{'Iris-setosa': 'blue', 'Iris-versicolor': 'green', 'Iris-virginica': 'red'}

# 原本畫圖
for species, group in iris.groupby('Name'):
    plt.scatter(group['PetalLength'],group['SepalLength'],
               color = color_map[species],
               alpha=0.3,edgecolor=None,
               label = species)
plt.legend(frameon=True, title='None')
plt.xlabel('PetalLength')
plt.ylabel('SepalLength')

Text(0, 0.5, 'SepalLength')

# 封裝之後的seaborn畫圖
sns.lmplot('PetalLength','SepalLength',iris, hue='Name', fit_reg=False)  

<seaborn.axisgrid.FacetGrid at 0x1a2a36c150>

生態