The other useful update is a brand new[introduction](https://seaborn.pydata.org/introduction.html) document which very clearly lays out what Seaborn is and how to use it. In the past, one of the biggest challenges with Seaborn was figuring out how to have the “Seaborn mindset.” This introduction goes a long way towards smoothing the transition.

|**No.**|**Name**|

| -------| --------|

| 01|**[Seaborn_Loading_Dataset](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/001_Seaborn_Loading_Dataset.ipynb)**|

| 02|**[Seaborn_Controlling_Aesthetics](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/002_Seaborn_Controlling_Aesthetics.ipynb)**|

| 03|**[Seaborn_Matplotlib_vs_Seaborn](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/003_Seaborn_Matplotlib_vs_Seaborn.ipynb)**|

| 04|**[Seaborn_Color_Palettes](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/004_Seaborn_Color_Palettes.ipynb)**|

| 05|**[Seaborn_LM Plot_&_Reg_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/005_Seaborn_LM%20Plot_%26_Reg_Plot.ipynb)**|

| 06|**[Seaborn_Scatter_Plot_&_Joint_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/006_Seaborn_Scatter_Plot_%26_Joint_Plot.ipynb)**|

| 07|**[Seaborn_Additional_Regression_Plots](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/007_Seaborn_Additional_Regression_Plots.ipynb)**|

| 08|**[Seaborn_Categorical_Data_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/008_Seaborn_Categorical_Data_Plot.ipynb)**|

| 09|**[Seaborn_Dist_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/009_Seaborn_Dist_Plot.ipynb)**|

| 10|**[Seaborn_Strip_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/010_Seaborn_Strip_Plot.ipynb)**|

| 11|**[Seaborn_Box_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/011_Seaborn_Box_Plot.ipynb)**|

| 12|**[Seaborn_Violin_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/012_Seaborn_Violin_Plot.ipynb)**|

| 13|**[Seaborn_Bar_Plot_and_Count_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/013_Seaborn_Bar_Plot_and_Count_Plot.ipynb)**|

| 14|**[Seaborn_TimeSeries_and_LetterValue_Plot](XXX)**|

| 15|**[Seaborn_Factor_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/015_Seaborn_Factor_Plot.ipynb)**|

| 16|**[Seaborn_PairGrid_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/016_Seaborn_PairGrid_Plot.ipynb)**|

| 17|**[Seaborn_FacetGrid_Plot](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/017_Seaborn_FacetGrid_Plot.ipynb)**|

| 18|**[Seaborn_Heat_Map](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/018_Seaborn_Heat_Map.ipynb)**|

| 19|**[Seaborn_Cluster_Map](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/019_Seaborn_Cluster_Map.ipynb)**|

||**[datasets](https://github.com/milaan9/12_Python_Seaborn_Module/tree/main/datasets)**|

| 11|**[Python Seaborn Statistical Data Visualization.pdf](https://github.com/milaan9/12_Python_Seaborn_Module/blob/main/Python%20Seaborn%20Statistical%20Data%20Visualization.pdf)**|

These are online **read-only** versions. However you can "Run ▶" the code **online** by clicking here &#8594; <a href="https://mybinder.org/v2/gh/milaan9/02_Python_Datatypes/HEAD"><img src="https://img.shields.io/badge/Open in-binder-579aca.svg?logo=data:image/png;base64,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" alt="binder"/></a>