A sharp tool for data visualization Seaborn easy to get started

Seaborn It's for statistical mapping , Generally speaking ,Seaborn It can meet the needs of data analysis 90% Drawing needs of . Sorted by this site Seaborn Of 41 A sample code , stay github share , For most data visualization problems, please refer to the sample code here .

Matplotlib Try to make simple things simpler , Difficult things become possible , and Seaborn It's about making difficult things easier .

Seaborn It's for statistical mapping , Generally speaking ,Seaborn It can meet the needs of data analysis 90% Drawing needs of .

Seaborn In fact matplotlib On the basis of a more advanced API encapsulation , So it's easier to draw , Use... In most cases Seaborn Can make a very attractive picture , Should put the Seaborn As matplotlib A supplement to , It's not a substitute .

use matplotlib The biggest difficulty is its default parameters , and Seaborn This problem is completely avoided .

seaborn Altogether 5 Two categories: 21 Seed map , Namely ：

• Relational plots Relationship charts

1. relplot() Interface of relational class diagram , In fact, it is the integration of the following two diagrams , By designation kind Parameters can draw the following two diagrams
2. scatterplot() Scatter plot
3. lineplot() Broken line diagram

• Categorical plots Classification chart

1. catplot() Interface of classification chart , In fact, it is the integration of the following eight charts , By designation kind Parameters can draw the following eight diagrams
2. stripplot() Classified scatter plot
3. swarmplot() Can display the classified scatter diagram of distribution density
4. boxplot() Box diagram
5. violinplot() Violin chart
6. boxenplot() Enhancement box diagram
7. pointplot() Point graph
8. barplot() Bar chart
9. countplot() Counting chart

• Distribution plot Distribution map

1. jointplot() Bivariate graph
2. pairplot() Variable relationship group diagram
3. distplot() Histogram , Quality estimation diagram
4. kdeplot() Kernel density estimation diagram
5. rugplot() Draw the data points in the array as data on the axis

• Regression plots Regression chart

1. lmplot() Regression model chart
2. regplot() Linear regression chart
3. residplot() Linear regression residual graph

• Matrix plots Matrix diagram

1. heatmap() Heat map
2. clustermap() Aggregation graph

github Address ：

​ ​https://github.com/fengdu78/machine_learning_beginner/tree/master/seaborn​​

primary coverage ：

Jupyter notebook Format ,Seaborn.ipynb Contains a total of 41 individual Seaborn Sample code for , Just modify the data source to draw a chart like the following figure .

（Seaborn Built in a lot of sample data , by dataframe type , command ：​​df = sns.load_dataset("anscombe")​​​ Read “​​anscombe​​​” Sample data , If you want to view data , Similar to ​​df.head()​​ Command view , When drawing, replace it with your own data .）

Partial effect

Reference resources ：

​ ​http://seaborn.pydata.org/examples/index.html​​

Please follow and share ↓↓↓ 

Beginners of machine learning

QQ Group ：554839127