Master's Thesis Project
Through public open data generated and collected by many of the largest international cities, we can develope tech products in order to analise and forecast sociodemographic parameters such as crimes, emergencies, incomes, etc. This allows us to manage and optimise public services and infrastructures.
The main goals of this project are:
- Crime analysis by districts in the city of Philadelphia
- 12 months Crime Forecast by districts using diffent time series models
- data Inputs and outputs files are storaged in this folder
- notebooks Jupyter Notebooks: Data preprocessing and time series models
- src Source code related to data adquisition and data preprocessing
- dashboard Tableau file where the results are shown
- img Images
From Philadelphia Open Data Portal: https://www.opendataphilly.org/dataset/crime-incidents
From Raw Data to Monthly Data
Data Analysis by Districts, Type of Crime and Date
Using SARIMA, Facebook Prophet and Keras LSTM Neuronal Network
pip3 install -r requirements.txt
Before you can begin using Boto 3, you should set up authentication credentials. Credentials for your AWS account can be found in the IAM Console
create the credential file yourself. By default, its location is at ~/.aws/credentials
:
[default]
aws_access_key_id = YOUR_ACCESS_KEY
aws_secret_access_key = YOUR_SECRET_KEY
You may also want to set a default region. This can be done in the configuration file. By default, its location is at ~/.aws/config
:
[default]
region = eu-west-1
After this, one of these files must be run:
./src/data/dataAdquisitionAWS.py
or
./data/01_Data_Adquisition_AWS_S3.ipynb
Then, you are ready to run all the notebooks ./notebooks/
The Dashboard has been developed using Tableau Link: Tableau Public Dashboard
Forecast
Analysis
User Interface