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A project used Flask to present a stock-insight dashboard. Utilised google trend to catch recently the hottest topics regarding to ASX, imported a python library, yfinanace, to scrap targeted stock’s data which users interested in, and provided users with a NoSQL database to store and delete their records of stocks' relative data.

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LynHJ/FlaskApp-StockInsights

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Stock Insights

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Background

Welcome to StockInsights. Your one stop shop for all things stock related. Our aim is to keep you up to date with the latest news and relevant information of your searched company to help you make the best educated financial decision.

About This APP:

HOW TO USE?

At first glance of our website you are greeted with a word cloud which contains the most searched words of the past seven days in relation to the Australian markets. This is designed to give you ideas about which company or industry you would like to research.

Once you have decided which company to search, simply enter it into the search bar. We then return the price of the stock and it’s increase or decrease in price since the previous day's closing price, the historic pirce which can be viewed from three months to five years as well as a detailed description of the company. Below the description is a view of the assets and liabilities for the past four years which change in size in accordance to the increase or decrease of the value of the business.

If you would like to keep your eye on this stock, simply click the Add To My List. This saves the searched stock in your “My List” menu. It is saved there for future reference, containing the price of when it was added, as well as the date.

WHO ARE WE?

StockInsights was created by three budding data analysts with a background in finance and a keen interest in the movements of the markets.

Lin is a multi-lingual analyst with a great thirst for financial and analytical knowledge. When he isn’t buried deep in code, he explores the other side of his mind by creating culinary oriental delights.

Rajiv’s strong IT background, paired with his love of cryptocurrency has moulded him into an analyst with a strong eye for detail.

Nick has spent the past ten years in international education, where he was able to use his love of teaching and exploring cultures into a profession. It is his love of problem solving and numbers has led him down the data analytics path.

Summary:

This assignment has been a great venture for us all, as it has allowed us to revise and put into action our newly gained data analytic skills which we have precured over the past few months. It has allowed us to find our strengths and weaknesses within all the new languages and libraries that we have learnt, which then allowed us to turn to each other and ask/ give support and guidance.

We believe that we have filled in many gaps of knowledge needed to make us better data analysts, as well as making us better collaborators within a group environment.

Of course many challenges were met along the way. Coordinating our schedules outside of class time was a challenge, as we all work full time, as well as other life commitments. There was also time pressure, as we had to review and, in some cases, relearn what we have studied to apply it to our assignment. This created a bit of a concern for us as we were not too sure if we were on the right track to deliver a completed final product.

In terms of the technical challenges, the main one was the continual errors in code we encountered and then having to find out where we went wrong and why. However, we know that these errors make us better at understanding the code and what syntax is required.

In conclusion, we are very proud with our end result and the journey of ups and downs we met along the way to get the desired functioning application. We definitely learnt a lot in terms of working in a team, putting our knowledge to the test and time managent.

Content:

Project  
├── README.md
├── Resources
│   ├── DashBoard1.png
│   ├── DashBoard2.png
│   ├── FlaskStructure.png
│   ├── HomePage.png
│   ├── MyList.png
│   ├── NavBar.png
│   └── wordCloudBase.png
├── StockInsights.pdf
├── StockInsights.pptx
├── app.py
├── proposal.docx
├── requirements.txt
├── scripts
│   ├── fundamentals.py
│   └── plotlylayout.py
├── static
│   ├── css
│   │   └── style.css
│   ├── images
│   │   ├── 2022-10-20.png
│   │   ├── 2022-10-21.png
│   │   ├── 2022-10-22.png
│   │   ├── 2022-10-23.png
│   │   ├── 2022-10-24.png
│   │   ├── 2022-10-25.png
│   │   ├── 2022-10-27.png
│   │   └── bg.jpg
│   └── js
│       ├── anime.js
│       └── app.js
├── templates
    ├── about.html
    ├── base.html
    ├── dashboard.html
    ├── error.html
    ├── index.html
    ├── mylist.html
    └── stockholder.html

Installation

pip install -r requirements.txt

Reference

  1. https://towardsdatascience.com/google-trends-api-for-python-a84bc25db88f
  2. https://www.digitalocean.com/community/tutorials/how-to-make-a-web-application-using-flask-in-python-3
  3. https://blog.qsearch.cc/2020/03/tokyo2020/
  4. https://github.com/tony1966/colab/blob/main/yfinance_test.ipynb
  5. https://www.youtube.com/watch?v=xihD23_fTk8&list=PLrC-HcVNfULaP6y6z57MaF2L9fZz0RQJq&index=5
  6. https://www.codeforests.com/2020/12/22/google-trends-data-in-word-cloud/
  7. https://www.geeksforgeeks.org/web-scraping-financial-news-using-python/
  8. https://wire.insiderfinance.io/develop-your-own-financial-dashboard-with-flask-and-plotly-46f8150364e6
  9. https://www.digitalocean.com/community/tutorials/how-to-use-flask-sqlalchemy-to-interact-with-databases-in-a-flask-application
  10. https://www.digitalocean.com/community/tutorials/how-to-use-mongodb-in-a-flask-application
  11. https://www.plus2net.com/python/tkinter-sqlite-delete.php
  12. https://www.shouxicto.com/article/5843.html
  13. https://tobiasahlin.com/moving-letters/

About

A project used Flask to present a stock-insight dashboard. Utilised google trend to catch recently the hottest topics regarding to ASX, imported a python library, yfinanace, to scrap targeted stock’s data which users interested in, and provided users with a NoSQL database to store and delete their records of stocks' relative data.

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