Context
For the Maven Bookshelf Challenge my the task is to design a tool that helps users build their ideal summer reading list. Use Goodreads data to discover and recommend books that fit their unique tastes, from classics to hidden gems, and bring each pick to life with insights from real reviews!
The primary goal was to discover the number of books for each genre and from there I could simply caculate the average ratings. By using the average ratings I could discover which books were popular based off the ratings.
The task involved me cleaning both the spreadsheet as there was alot of unecessary information and blanks. This was simply using using a python script that reads the file and drop columns and rows. Doing this not only cleaned the data up, it also made it faster to read and open the files which is very important especially on github.
What i discovered lastly is fantasy and fiction books were popular at the top end while there was less popularity in historical and non fiction werent.
I am aware the work is light and only a week but this is just using a demonstration what i learned off python recently and its my first attempt.
I made a dashboard using python to interact with. Interactive Maven July 2025 Dashboard
Actions
- 🔹 Step 1: Clean the database and remove duplicates, missing numbers and remove columns to reduce the file size.
- 🔹 Step 2: Use Jupiter Notebook /Python to read in the files look through the data.
- 🔹 Step 3: Visualize the data using Seaborn and create plots.
- 🔹 Step 4: Looked at the trends and then put the results on Streamlit to create a dashboard using python Steam lit.
- 🔹 Step 5: Deployed on Steamlit.
Result
Below is the result.
- 📌 Python Dashboard:
- 📝 Summary of Key Findings:
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Using Python to clean spreadsheets and reduce file sizes.
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Data Visualization.
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Creating Dashboards using Python.
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Jupiter Notebook.
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Future Considerations
- 💡 Potential improvements:
- explore how to deploy in Jupiter notebook for easier viewing.