The purpose of this project is to assist people in researching the most optimal and resourceful locations near their neighborhood. It will provide the necessary information in making the best decision on selecting the neighborhood you would like to live in.
Many people move into parts of Canada and need tons of prior research dealing with factors such as suitable housing prices, well-known schools for their children, and so on. This project will focus on people who are interested in looking for better neighborhoods with many factors including accessing nearby cafes, schools, supermarkets, pharmacies, malls, hospitals, etc.
The aim is to create an analysis of features for people migrating specifically to the city Center Toronto, Ontario searching for the best neighborhood as a comparative analysis between other neighborhoods. The features include median housing price and better school according to ratings, crime rates in the particular area, road connectivity, weather conditions, good management for emergency, recreational facilities, etc.
This will help people to gain awareness of the area and neighborhood before moving to a new city and prepare them for their new work or fresh life ahead.
Determined the best neighborhoods to live in Center Toronto, which houses had the most ideal price median, schools that had the best ratings according to the neighbourhoods.
I use Python3 in my Jupyter Notebook:
- Numpy
- Pandas
- Scikit Learn
- Matplotlib
- Seaborn
- Folium
- Collections
- Math
Week 4 - First Part of the Battle of Neighborhoods Project Week 5 - Final Part of the Battle of Neighborhoods Project
Week 5
FinalCapstone-BotN-NorthYork Report.ipynb - contains the detailed report of the final project with full explainations
FinalCapstone-BotN-NorthYork Final.ipynb - notebook of the main project
TorHousePrice.xlsx - dataset of toronto houses