A collection of data analysis and visualization projects designed to uncover insights from diverse datasets. These projects include analyses on COVID-19 trends, stock trading patterns, housing market prices, IoT data, and more, showcasing the power of data-driven storytelling.

An AI-driven multi-agent trading platform for options trading and stock trends analysis. This project leverages advanced machine learning, real-time market data, and a modular multi-agent framework.

An AI-powered investment analysis tool 📈 that leverages simple ReAct AI agent flow framework and financial analysis techniques to provide comprehensive portfolio insights. This intelligent agent helps investors make data-driven decisions by offering deep portfolio risk assessment, stock profiling, and personalized recommendations.

“My name is Gregory Guy. I have just purchased a video store, and I need an up to date, GUI driven system to keep track of all the stock in my store. I am not happy with the existing system where everything is done by hand. “Currently, the store operates on a cash basis, although a contract system might be in the pipeline. You will be contacted to do this at a later stage, if necessary. I have a shop next door that sells sweets, drinks, chocolates etc, which runs from a separate cash register. This should not be included in the system you develop. “My store not only stocks videos, but also video machines, as well as DVD’s. At a later stage, I would like to also stock Sony PlayStation games, controls, and possibly other stock items. I want to be able to add these into the stock list with the minimum of hassle, and without calling in the help of a programmer / system designer. “I want to store all transactional information in a database, so that my accounting system can interface with the data. “I charge as follows: New Release: (Video or DVD) R16 Older Stock: (Video or DVD) R12 • Video Machine R30 • Video Machine & any two videos: R50 “When I start stocking PlayStation games and/or consoles (or any other stock items), I would probably want to have a two-tier pricing system for them as well (where I can charge more for newer stock). “It would also be nice to be able to change my prices if and when I need to. I therefore would like the ability to change the price of a ‘New Release’, and that should affect all the videos/DVD’s that fall into that category. The same should apply to the other prices mentioned above. “I have a couple of shop assistants that helps me out, and I would like some security built in so that the assistants cannot get access to my financial and other important data. Functionality: “I obviously need the system to take care of the most important part of the business:- the quick and accurate ‘booking out’ of all stock items. The customer, upon bringing me his/her selection, must be charged accordingly, and the items must be marked as ‘out’. “The system should also allow me to quickly and easily record the returned stock items, as and when they do come in. “Sometimes I also want to credit the customer for something, as the tape/DVD/game might have been damaged before they rented it. The item should then be marked as returned, but as money is then given back to the customer, some sort of record should be kept about this credit transaction so that I can trace which assistant allowed the credit. This will help me minimize fraudulent behaviour where assistants can basically book out resources ‘for free’. “I also want the system to have an advance booking facility, where an existing customer can call in and book a certain video/DVD/other item for a certain day. The system should not allow an item to be booked out twice for a certain date, and if something has been booked out and another customer tries to rent it, at least a warning should be displayed, informing the teller that this is the case. In special cases, such a booking can then be ignored, but most times the teller will inform the customer that s/he cannot have that item for the day. A facility should also be included where the booking can be cancelled at any time, if necessary. (For example, if a customer cancels the booking telephonically, whether it is on the day, or some time in advance). “Although it could be considered part of the accounting package, I would like this system to be able to do a daily summary, where I am presented with total sales (monetary value), total number of rentals (total videos; total DVD’s, total machines,) etc. This can be shown to me either on the screen, or in a printed form. I would like you to decide on the format and content of this screen/report. “Another function that I would like you to incorporate, is that the system should be able to do some analysis for me. Examples of this include: • Top Ten rentals • Top Ten customers • Stock items that have not been rented out in 6 months or more. I would like the above three to be done, but if you can think of other examples, feel free to add them in if you have time. “The system should allow me to add/edit all customer details, and if necessary (not often) delete a customer. Customer details to be stored include, but are not limited to: Name Surname Title I.D. Number Address and Postal Code Telephone Number (Work) Telephone Number (Home) Telephone Number (Mobile) “The system should also allow me to update the information regarding my stock items, for example: • Mark a tape as damaged. • Change a video from a ‘New Release’ to ‘Older Stock’. • Change the category it belongs to. “I have several working, but old machines lying around at my house, and they are already network-capable. I would like you to build some functionality where these machines can be linked to the system you are designing so that they can be used as ‘look-up’ machines. Basically, if a shop assistant is not available, but a customer knows the title of the movie they are looking for, they should be able to go to one of these terminals that I will set up throughout my shop, and enter or select the movie name, and perhaps what they are looking for (video/dvd/game etc). If my shop carries the chosen item, then the system should give them enough information (shelf number/category etc.) to be able to locate the item in the shop. It should also show if an item is unavailable, and when it is due back. If they select an invalid item, they should be informed of this. “The above program should run independently of the main system, and should not access the database directly. The video store will have employees, customers, stock and suppliers. Employees, customers and suppliers related to the video store can be created, deleted or updated. Creating / updating / deleting a customer profile (video store) will be very similar to that of creating / updating / deleting a customer’s account in the banking industry. The stock status also needs to be up to date (available, rented, late or damaged). An ATM will be inside the video store. The ATM is available to both the public and the employees. The ATM can be used for: Bank account balance inquiry, money withdrawal, funds transfer and transaction history (last 5 transactions with dates, time, type of transaction and outcome). The ATM should also cancel a transaction request and swallow a debit card when the user has entered a wrong pin number three times in succession. The ATM can only be used by clients who have existing bank accounts and existing (valid) debit cards. Make provision for situations such as expired debit cards, frozen accounts, insufficient funds, daily withdrawal limit exceeded, etc. The video store works on a cash-only-basis. Customers can withdraw money at the ATM if they don't have cash on them. The ATM is also available to public who only wants to use the ATM (without having to do business with the video store). Payment for stock rented: A Point Of Sale screen (electronic cash register screen) needs to be displayed. The product and the quantity thereof needs to be entered. You can make use of drop boxes if you want to. The system will calculate the total amount due (and the due date back for the products). Enter the cash amount offered by the customer. Calculate the change amount. Update the video store transaction register. Stock returned: Update the electronic system. Make provision for the condition in which the stock items were returned (in a working state or damaged, on time or late - individually). Capture a history record of products rented. Know the value of the stock outside the store. Capture a history record of products currently late. Capture a history record of products damaged. Capture a history record of products currently in store. Calculate the value of stock in-store. Capture a history record of each registered client's rental record. Capture a history record of a client's ATM transactions.

The Financial Analysis Crew is a Streamlit app that simplifies financial stock analysis. With the power of LLM-driven agents, users can seamlessly gather and analyze stock market data to generate comprehensive financial insights. Perfect for investors, analysts, and anyone interested in making data-driven financial decisions.

In the dynamic world of stock trading, leveraging data-driven insights is key to staying ahead. Here’s a breakdown of a recent analysis I conducted, combining predictive modeling, technical indicators, and strategy backtesting to navigate market trends:

Discover the trading in Python with many strategies, including deep learning approaches. TradingInPython is an open software platform that empowers traders with advanced tools for stock market analysis and trading strategies. Leverage data-driven insights and automate your trading decisions with an open, flexible solution.

The basic idea of the project is to perform various data and time-series analysis on the live, present and past records of the stocks. This data driven approach will help to manage portfolio of an indivdual and will eventually increase the profits margin. Here, we will be importing data from yfinance library. And the data have been considered from the year 2010. The yfinance dataset consists of the columns such as Date, Open, High, Low, Close, Volume, and Dividend. During the flow of this notebook, you will see stock analysis, time series analysis, time series model prediction with the help of FB Prophet, LSTM, ARIMA, SARIMA and XGBoost.

Streamlit-based interactive Stock Analysis Tool that integrates Yahoo Finance (yfinance) and Google Gemini AI to evaluate stocks' fundamental data and technical indicators. The tool aims to deliver AI-driven investment recommendations in an accessible format.

This project aims to perform a detailed data-driven analysis of the S&P 500 stock market using historical stock price data from the period 2014 to 2017. Leveraging Python and essential data science tools, the project uncovers key financial insights through statistical analysis, exploratory data analysis (EDA), and visualizations.

Professional quantitative investment analysis system based on TradingView data providing intelligent stock screening, technical pattern recognition, market review, risk management, and event-driven analysis.

The Financial Analysis Crew is a Streamlit app that simplifies financial stock analysis. With the power of LLM-driven agents, users can seamlessly gather and analyze stock market data to generate comprehensive financial insights. Perfect for investors, analysts, and anyone interested in making data-driven financial decisions.

An end-to-end application that predicts stock price movements using sentiment analysis of financial news headlines. Powered by machine learning, NLP, and real-time data integration, this project offers investors a reliable tool for data-driven decision-making.

The Stock Market Analysis Dashboard is a Power BI project that visualizes stock trends, technical indicators, and market performance for data-driven investment insights.

This project was developed by a single developer with a passion for combining financial data analysis with cutting-edge AI technologies. The NSE Option Chain With Gen AI tool brings together real-time stock market data and AI-driven insights to help users make informed decisions. By leveraging the power of the NSE API and generative AI.

A Flask-based API that enables users to retrieve financial data, perform AI-driven analysis, and receive stock trading recommendations based on financial quantitave data.

The objective of this project is to design a Stock & Inventory Management Analysis system that helps retail managers make data-driven decisions about inventory, pricing, and promotions.

Explore the world of data-driven customer analysis and lifetime value estimation. This project dives into customer segmentation, geographic analysis, time series insights, stock trends, and product descriptions. Join us on our journey of data exploration and optimization.

Aistox– A hybrid AI-driven system that combines financial fundamentals, technical indicators, macroeconomic data, and real-time sentiment analysis from news and social media to predict stock price movements with greater contextual accuracy.

A data-driven algorithmic trading strategy that leverages Twitter sentiment analysis to construct and rebalance a stock portfolio. This project aims to outperform traditional market benchmarks by prioritizing stocks with strong positive social media engagement.

Python library for lifecycle portfolio allocation inspired by Choi et al. Combines human capital PV, risk aversion, and market assumptions to produce data-driven stock/bond recommendations. Includes glide paths, sensitivity analysis, strategy comparisons, and visual analytics. Educational/research use only.

EDA (Exploratory Data Analysis) & Hypothesis Testing on FCI dataset along with various visualisations.

A big data-driven system for real-time stock market analysis, trend prediction, and investment suggestions.

Stock Analysis is a Python-based project that performs data-driven analysis of stock market trends using historical price data. It includes tools for data collection, cleaning, visualization, and statistical analysis to help identify patterns, compare stock performance, and generate actionable insights.

Sentiment-driven stock market analysis using Yahoo Finance, Twitter, Reddit, and NLP. CMSC320 Data Science Final Project.

An AI-powered trading platform that leverages real-time sentiment analysis to make smarter, data-driven stock market decisions.

MarketMind AI Analyst is a web-based financial intelligence tool designed to democratize access to professional-grade stock market analysis. By leveraging Large Language Models (LLMs) like Google's Gemini 2.5 with real-time search grounding, it provides instant, data-driven technical, fundamental, and sentiment analysis for Indian (NSE) and global

💹 PractoTrade – AI-driven stock prediction using historical data and real-time sentiment analysis. Combines dual regression models for smarter, more accurate forecasts.

Stockify is a cutting-edge demand prediction and product stock analysis system, meticulously designed to empower retail store managers with data-driven inventory decisions.

Sentiment-Driven Stock Predictor (SDSP) leverages sentiment analysis and financial data to build datasets and classify to BUY, SELL, or HOLD stock actions. Features include automated data gathering, advanced metric calculations, and bootstrap aggregation models for predictions.