Project II | Sara Benitez-Inglott

[sarabenitezinglott]

https://github.com/sarabenitezinglott/project-2 Be kind :((

[sh-ih]

You did great on this project! Some comments:

• Repository You have a good folder structure. I would change the name of the dataframes folder to data, it is the regularly used name, and the excel file (data_nike_vs_addidas_unsupervised.xlsx) can be stored there, instead of in the top level of your repository.

I saw you added this file to the .gitignore but the name of the file had two extra characters at the beginning (~$). You need to delete those if you do not want to push this file to your repository.

Good job naming your graphs. Using clear names helps everyone know what they’ll find inside each image.

• Acquisition and enrichment of database You did great combining the public Kaggle dataset con extra and up to date information directly from the official Nike website.

• Reporting I like how you organized tour visualizations.ipynb notebook, with titles and clearly stated questions. I would recommend you add your analysis and interpretations right there too, where you can explain at length. Later on, you can list the highlights on your README.

And I am not talking about saying which brand is better, because you don’t have the information to conclude something so subjective, but an analysis of something like: Adidas portfolio is more geared towards women and Lifestyle but Nike is focused on men and sports, for example. Or The portfolio of products analyzed is 54% Nike and 46% Adidas and the range of prices goes from 50 to 3,500 US dollars. Products geared towards men have a highest mean price than women's. Not saying that your data support those conclusions, but you need to put in words what you find after running your code.

• README Your README is organized, but it is lacking on the analysis and conclusions sections: list the questions you wanted to answer and your findings. Accompany that text with your visualizations right there on the README. Remember that this is your opportunity to capture the interest of a reader.

• Bonus: modularization/encapsulation You created your functions directly on main,py, instead of leaving them on different files. To keep your repository organized, it is better to have a .py with cleaning functions, another with visualization functions and so on.