This project was completed as part of Udacity's Data Analyst Nanodegree.
In this analysis, I examine global weather data and compare it to weather data from San Jose, CA (where I currently live) and Portland, OR (where I grew up). All of the CSV data files were downloaded from a database on Udacity's website that provides annual average temperatures for select cities around the world. The question that guides this analysis is: What are the overall trends of annual average temperatures and how do these trends differ between global data, San Jose, and Portland?
- Jupyter Notebook
- Pandas
- Matplotlib
- Scipy
To get the Jupyter Notebook running, execute the following in the command line and select weather-trends.ipynb from the Jupyter Notebook dashboard. The conda environment setup is optional; I have provided the base environment in base.yaml.
$ git clone https://github.com/evanchen13/weather-trends.git
$ cd weather-trends
$ conda env create -f base.yaml
$ jupyter notebook
The contents of this repository are covered under the GNU General Public License v3.0.