After a couple of weeks of work I’m excited to have completed my first guided project and to share it with you.
I work full time in finance and I am trying to learn python to expand my career into data analytics. As I continue my Data Analyst study plan I am looking forward to engaging with fellow students.
All the best,
Antonio
This is a link to the last mission screen of the Guided Project.
You can download my guided project here. Basics.ipynb (57.6 KB)
Congratulations on finishing your first project here!
Your work looks nice, comprehensive and well-balanced in terms of code cells, code comments and markdown explanations.
What I would suggest you from my side is to add more internal structure to your project: subheadings, introduction and especially conclusion, laconically summarizing all your findings and insights. Also, it would be a good idea to add somewhere in the beginning a link on the data set documentation. The same thing about the paragraph outlining the wrong data to delete: it would be good to add a link on the discussion where that wrong data was discovered.
Hope my suggestions were helpful.
Happy coding with your next projects!
Congratulations on finishing your first project. Your work looks good. Though I can see a few places where you can do things slightly differently.
It would be great if the markdown cells are used to its full advantage with Headings, subheading, lists etc for better readability. It makes it easier for others to quickly run through your project and still get complete idea.
Another point I have seen is with the print() function. You can actually include multiple elements inside the print() function. Maybe you have used separate line for a better aesthetic of the code.
print('App Store genre frequency')
print(app_store_genre_frequency)
print('\n')
You can combine these three lines into one
print("App Store genre frequency \n" , app_store_genre_frequency, "\n")
The last point is that you have done a good observation of the inferences we have made from our analysis. So if you could conclude your observations in accordance with the aim of your project, that would be great. Here in our example, we are trying to find which is the most profitable app segment. So we have seen the ‘Game’ category has many apps. It either means, we can still make it work in that category or there is a high competition to survive.
Depending on the strengths of your client/company you are working for you have to make a conclusion on what kind of app you are going to suggest to them after the analysis. So if you can work a bit more on your structure of the project, it would be super.
