analysing-house-prices-in-different-boroughs-in-london

Analysis of Property Prices In the different Boroughs In London and other influences on the property price.

analysing-school-district-data-with-pandas

My evaluation of the school district's performance included the examination of standardised test results in math and reading, school budgets, and grade point averages. The information was organised by school size and type, with an emphasis on district and charter schools, using pandas.

analysing-uk-food-hygiene-ratings-using-mongodb

In this analysis, I delve into UK Food Hygiene Ratings data to assist Eat Safe, Love magazine. With the aim of guiding their food critics, I explore establishments' ratings, focusing on hygiene, location, and scores.

citibike

Explore the usage patterns and demographics of Citi Bike, a bike-sharing system in New Jersey, based on 2021 data. Discover popular starting stations, user types, gender distribution, and trip durations. Gain insights for improving the system's efficiency and enhancing transportation infrastructure.

climate-data-analysis-flask-api-for-vacation-planning

Planning a relaxing vacation in Honolulu, Hawaii? Here's how to analyse the climate data using Python, SQLAlchemy, Pandas, and Matplotlib and design a Flask API to help make your trip unforgettable.

covid-19-dashboard

Our project analyses the global impact of COVID-19 vaccination, examining progress, disparities, and correlations. We utilise reliable datasets to provide insights into vaccination coverage, distribution, and its relationship with factors like GDP per capita. Our findings emphasize the importance of equitable vaccine access for all.

credit-risk-classification

Use various techniques to train and evaluate a model based on loan risk.

crowdfunding_etl

This project aims to demonstrate the process of ETL (Extract, Transform & Load) using Python and SQL. It involves extracting data from multiple sources, cleaning and transforming the data using Jupyter Notebook with pandas, numpy, and datetime packages, and loading the cleaned data into a relational database using pgAdmin.

cryptoclustering

Using Python and unsupervised learning to predict if cryptocurrencies are affected by 24-hour or 7-day price changes

enhancing-deep-learning-model-performance

Nonprofit foundation Alphabet Soup wants a tool that can help it select the applicants for funding with the best chance of success in their ventures. Using machine learning and neural networks, you’ll use the features in the provided dataset to create a binary classifier that can predict whether applicants will be successful if funded.

exploring-cancer-treatment-data-using-matplotlib

Analysing an animal study on potential skin cancer treatments. 249 mice received various regimens, observing tumor development over 45 days. My roles were to generate: tables, figures, and a summary

exploring-financial-data-and-election-results-with-python

Using Python to analyse distinct datasets. Through financial analysis, we aim to extract essential metrics like total months, net "Profit/Losses," average changes, and significant profit fluctuations. Through election analysis, we aim to extract total votes, candidates' performance percentages and counts, revealing the winner by popular vote.

exploring-microbial-samples-with-d3-data-visualisation

Creating interactive data visualisation using D3 package.

exploring-weather-patterns-and-planning-vacations-with-apis

Utilising Python's capabilities, we answer questions about the relationship between weather variables and latitude and go beyond by planning vacation destinations based on specific weather conditions.

financial-data-analysis-through-vba-scripting

This project involves delving into dynamically generated stock market data to extract insights. I have crafted a VBA script that computes yearly changes, percentage variations, and cumulative stock volumes, while also identifying stocks with the most substantial percentage fluctuations and trading volumes.

hamim

hamim-hussain

home_sales

Use SparkSQL to determine key metrics about home sales data. Then use Spark to create temporary views, partition the data, cache and uncache a temporary table, and verify that the table has been uncached.

mars-data-scraping-and-analysis

Embarking on Mars data exploration! Using Jupyter Notebooks, I'll scrape Mars news and weather details. Firstly, I'll extract titles and preview text from the Mars News site using Beautiful Soup. Then, I'll dive into Mars weather data, analysing temperatures, atmospheric pressure, and more.

sql-data-exploration

In this data exploration project, we delve into Pewlett Hackard's employee data from the 1980s and 1990s. The primary objective is to design and analyse a SQL database containing information from six CSV files. This process encompasses data modeling, engineering, and analysis.

to-graduate-or-not-to-graduate

Our project leverages Python, pandas, Tableau, and machine learning techniques to analyse and predict student outcomes in higher education. Using a comprehensive dataset, we employ data preprocessing, visualisation with Tableau, and advanced machine learning models built with Python to uncover insights into graduation rates and factors influencing

unveiling-kickstarter-trends-an-excel-data-analysis

Diving into 4,000 past Kickstarter projects, I aim to unveil trends and patterns. Using Excel, I analyse data, visualise outcomes, calculate success rates, and dissect categories. Insights about funding, donations, and timing emerge. Statistical analysis enriches understanding. Let's embark on this data journey.

visualising-earthquake-data-with-leaflet

USGS wants better earthquake data visualisation to educate public/govt. Collecting global data daily, they seek meaningful tools for informative presentations, boosting support/funding for vital planetary issues.