Ironhack-data-bcn-oct-2023 / project-IV-sql-tableau

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Project IV - Junior #12

Open linharesjunior opened 9 months ago

linharesjunior commented 9 months ago

https://github.com/linharesjunior/Project-IV-sql-tableau.git

sahernandezr commented 9 months ago

🐬📊Congrats on your project!

README Your README is well organized and very interesting. The way you show the hypothesis and the visualizations right next to it is a great idea. I would just suggest that you either add the analysis to the hypothesis that don’t have it (Browsing Habits and Cart Usage) or remove those two, so it doesn’t look incomplete.

It is always good practice to explain a little bit more of your data, if you have the information: how many instances do you have, are they from a particular country/state? Time period? Whatever info you have to clarify the scope of this project. And also some descriptive information may be useful: age range represented, gender distribution.

When you add static images, like in the Frequency of Purchase, it is advisable to show the value of each category, since we lose the interactive tool tip included in Tableau and in this particular case, where you are explaining the whole dataset, a pie chart or a treemap could be easier to interpret than the different sized circles.

Code You should try adding more comments to your notebooks and docstrings to your functions.

SQL You created great queries to answer your questions and there is a lot of opportunity to extend this project if you’d like with analysis of the abandonment cart reasons and if there is a relationship with other characteristics like frequency of usage.

Tableau Your Story is well organized and your analysis alongside the visualizations are a great addition. You could add a new story point with some information about the characteristics and composition of your dataset: distribution by age, by gender, for example. In the Improvement story point, the Customer review importance vs Review left, your variables are discrete, so a line graph is not advisable. A bar graph works better for this type of data.