This repository contains code and data for performing an initial data analysis of the weather sensor data installed across the city of Trollhättan. The sensors record basic measurements such as temperature and humidity.
The main objectives of this project are:
- Validate data sanity through an initial data analysis
- Conduct non-supervised analysis to report any interesting insights from the data
- Meet with city officials to receive further direction
- Run deep learning algorithms to extract information of interest for the city
The data used in this project is collected from weather sensors installed across the city of Trollhättan. The data is available in the Datasets/ directory.
To get started, clone this repository and follow the instructions in the README.md file. The code in this repository requires Python 3.7 or higher and the following libraries:
- Pandas
- NumPy
- Matplotlib
- Scikit-Learn
- TensorFlow
- Seaborn
- Scipy
The initial data analysis will focus on validating the data sanity, identifying any missing or inconsistent values, and exploring the basic statistical properties of the data. The non-supervised analysis will involve clustering and visualizing the data to identify any interesting patterns or trends.
Based on the initial findings, the project will be further developed in collaboration with the city officials to explore potential applications of the data. This may involve running deep learning algorithms to extract information of interest for the city.