vardaansinha / FastPages

MIT License
3 stars 3 forks source link

Project Check #7 Data Structures Algorithms [Individual] #36

Open vardaansinha opened 1 year ago

vardaansinha commented 1 year ago
  1. Complete popcorn hacks in tech talks:

Python Sorting Python 2D Iteration and Animation

  1. Data Structures Algorithms Work and Progress

For my individual feature, instead of only choosing one of these algorithms, I am working to include two in my feature:

  1. Plan and Work Progress to Incorporate Sorting into Project

For incorporating sorting into my project feature, which are NBA Player Statistics, I am working to be able to provide a sorting button at the top of each column which allows me to filter each statistic from worst to best and vice versa, so that more insights can be had on the player stats. Right now, I am having trouble with DB generation, but the frameworks of the model and API files have been completed for my feature and I am working on troubleshooting and then creating a sorting algorithm.

Right now, for sorting in SQLite, I have been researching, and have mainly seen a commonality of the ORDER BY command in SQLite. Therefore, my current idea is the following:

  1. Populate the DB with data based on Kaggle API Statistics (cut and paste since 2023 season is almost over, statistics will be stable for the next couple of months)
  2. Add a "SORT" button on the top of each column (section of stat) in the frontend.
  3. Clicking the SORT button will call this SQLite command, causing the column to sort.

There is definitely more work needed to be done for this, but this is what I have so far for the backend.

image

MODEL FILE

  1. Plan and Work Progress to Incorporate Other Individually Selected Data Structures Algorithm, ie Pandas DF and Analysis

Here, for the "Who Said What" feature, I am planning to utilize Pandas DF to sort quotes. Though this can also be done using SQLite, I'd like to use Pandas DF in order to learn more about its connection to the frontend and its utilization in an actual project.

The "Who Said What" feature is a feature which captures the recent groundbreaking quotes of different athletes and the date on which they said these quotes.

The framework for this backend is as follows:

  1. A Python file containing the Pandas import and the respective sorting functions for Pandas.
  2. A JSON file containing all the data, organized by the different categories (name, date, quote)

I have entirely finished this framework. Now, it is about 1) populating the JSON file (possibly from an API or manually, decision has to be made), and 2) connecting it to the frontend page.

image

image

image


REMAINING PLAN FOR PROJECT:

  1. HOME PAGE: Nicolas will be done with designing and styling this page by 5/25.

  2. NBA STATISTICS: I will be finished with this feature by 5/29.

  3. NBA BRACKET GENERATOR: Justin and Shivansh will be finished with this feature by 5/29.

  4. NFL STATISTICS: Dhruva, Vyaan, and Prasith will be finished with this feature by 5/29.

  5. NFL BRACKET GENERATOR: Shaurya and Justin will be finished with this feature by 5/29.

  6. WHO SAID WHAT? I will attempt to be finished with this feature by 5/30. If I am running into too many issues or other sections are behind, this feature will likely be scrapped.