Mini Project 1 for Applied Data Science course.
This project analyses a dataset of new listed properties on 2024-02-01 from iProperty.com.my.
Team members
- Teh Woei Xiang
- Boo Soon Ting
- web_scraping folder, contains notebook to scrape data from iProperty.com.my
- eda folder, contians notebook for EDA
- word_cloud folder, contains notebook for word cloud
- django, contains file related to a dashboard application developed with Django web framework
- data, contains data generated from notebooks in web_scraping and eda
- Install Anaconda, Anaconda Installation
- Create a virtual environment with the name 'mini_project_1' and python 3.10
conda create -n mini_project_1 python=3.10 - Activate mini_project_1
conda activate mini_project_1 - Download the code
git clone https://github.com/Bsting/fc_aps_mini_project_1.git cd fc_aps_mini_project_1
- Go to web_scraping folder
cd web_scraping - Install required packages
pip install -r requirements.txt - open iproperty.ipynb notebook and run the cells to scrape data from iProperty.com.my for new listed properties
- Go to eda folder
cd eda - Install required packages
pip install -r requirements.txt - open iproperty_eda.ipynb notebook and run the cells for EDA for data scrapped from iProperty.com.my on 2024-02-01
- Go to word_cloud folder
cd word_cloud eda - Install required packages
pip install -r requirements.txt - open iproperty_word_cloud.ipynb notebook and run the cells to generate word cloud images for data scrapped from iProperty.com.my on 2024-02-01
View Django Web Application at Team D (AWS) or Team D (Render) or Run It Locally
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Go to django folder
cd django -
Install required packages
pip install -r requirements.txt -
Set up database
python manage.py makemigrations python manage.py migrate -
Create the Superuser
python manage.py createsuperuser -
Start the app
python manage.py runserver -
The app runs at http://127.0.0.1:8000/
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Login page
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User registration page
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Admin page
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Dashboard in light mode
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Dashboard in dark mode
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Word cloud