The objective is to explore and analyse climate change and its relation to natural disasters (occurrence and economic impact). For this analysis, global temperature rise is used as an indicator of climate change.

Python is used as the tool for the analysis. The analysis is presented in the Jupyter Notebook 'EDA of climate change and natural disasters.ipynb'. The data used for the analysis are stored in the 'datasets' folder as csv files.
The key insights uncovered by the analysis are:

• There has been a steady warming of the Earth from around 1920 onwards.
• There is a strong positive correlation between global temperature rise and global occurrences of natural disasters.
• Economic damage from natural disasters has a relatively lower correlation with global warming as it depends on several other factors.

The source of the global temperature data is the Kaggle dataset https://www.kaggle.com/berkeleyearth/climate-change-earth-surface-temperature-data by Berkeley Earth.
Natural diasaster data is taken from https://ourworldindata.org/natural-disasters (data published by EMDAT (2019): OFDA/CRED International Disaster Database, Université catholique de Louvain – Brussels – Belgium)