Seaborn 常用的 10 種數(shù)據(jù)分析圖表
內(nèi)置示例數(shù)據(jù)集
seaborn內(nèi)置了十幾個示例數(shù)據(jù)集,通過load_dataset函數(shù)可以調(diào)用。
其中包括常見的泰坦尼克、鳶尾花等經(jīng)典數(shù)據(jù)集。
- # 查看數(shù)據(jù)集種類
 - import seaborn as sns
 - sns.get_dataset_names()
 

- import seaborn as sns
 - # 導出鳶尾花數(shù)據(jù)集
 - data = sns.load_dataset('iris')
 - data.head()
 

1. 散點圖
函數(shù)sns.scatterplot
- import seaborn as sns
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - # 小費數(shù)據(jù)集
 - tips = sns.load_dataset('tips')
 - ax = sns.scatterplot(x='total_bill',y='tip',data=tips)
 - plt.show()
 

2. 條形圖
函數(shù)sns.barplot
顯示數(shù)據(jù)平均值和置信區(qū)間
- import seaborn as sns
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - # 小費數(shù)據(jù)集
 - tips = sns.load_dataset("tips")
 - ax = sns.barplot(x="day", y="total_bill", data=tips)
 - plt.show()
 

3. 線型圖
函數(shù)sns.lineplot
繪制折線圖和置信區(qū)間
- import seaborn as sns
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - fmri = sns.load_dataset("fmri")
 - ax = sns.lineplot(x="timepoint", y="signal", data=fmri)
 - plt.show()
 

4. 箱線圖
函數(shù)seaborn.boxplot
- import seaborn as sns
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - tips = sns.load_dataset("tips")
 - ax = sns.boxplot(x="day", y="total_bill", data=tips)
 - plt.show()
 

5. 直方圖
函數(shù)seaborn.distplot
- import seaborn as sns
 - import numpy as np
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - np.random.seed(0)
 - x = np.random.randn(1000)
 - ax = sns.distplot(x)
 - plt.show()
 

6. 熱力圖
函數(shù)seaborn.heatmap
- import numpy as np
 - np.random.seed(0)
 - import seaborn as sns
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - uniform_data = np.random.rand(10, 12)
 - ax = sns.heatmap(uniform_data)
 - plt.show()
 

7. 散點圖矩陣
函數(shù)sns.pairplot
- import seaborn as sns
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - iris = sns.load_dataset("iris")
 - ax = sns.pairplot(iris)
 - plt.show()
 

8. 分類散點圖
函數(shù)seaborn.catplot
- import seaborn as sns
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - exercise = sns.load_dataset("exercise")
 - ax = sns.catplot(x="time", y="pulse", hue="kind", data=exercise)\
 - plt.show()
 

9. 計數(shù)條形圖
函數(shù)seaborn.countplot
- import seaborn as sns
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - titanic = sns.load_dataset("titanic")
 - ax = sns.countplot(x="class", data=titanic)
 - plt.show()
 

10. 回歸圖
函數(shù) seaborn.lmplot
繪制散點及回歸圖
- import seaborn as sns
 - sns.set()
 - import matplotlib.pyplot as plt
 - %matplotlib inline
 - tips = sns.load_dataset("tips")
 - ax = sns.lmplot(x="total_bill", y="tip", data=tips)
 - plt.show()
 
















 
 
 










 
 
 
 