DATA ANALYSIS & VISUALIZATION WITH PYTHON

NATURAL RESOURCE DATA SETS

DELVING INTO EARTH DATA SCIENCE RESEARCH

Image by Gerd Altmann from Pixabay

Data Science is an interdisciplinary subject, blending statistics, mathematics and computer science. Data Science provides the methods, tools and techniques to collect, process, analyse, visualize and extract valuable insights from complex and often large datasets.

Earth Science is an interdisciplinary subject, using physics, chemistry, biology, geology and mathematics to understand how the solid earth, oceans and atmosphere work, how people impact the environment and how we can manage the earth’s natural resources in a sustainable manner. Earth Science datasets are increasing in size and complexity, and Earth Scientists need new approaches to data analysis and problem solving. Which is why Earth Data Science is a rapidly emerging field, as data science provides the toolbox to deal with data from a variety of sources and scales. From data acquisition, processing, visualizing, analysis and modeling, data science skills are increasingly core to the work of Earth Scientists.

This blog aims to introduce data science methods for analyzing and visualizing data using Python. Jupyter notebooks for these posts can be found in my Github repository. It will also highlight the innovative and exciting Earth Data Science research that is currently being carried out. I hope you find the posts informative and interesting, and are inspired to learn more about the potential of merging Data and Earth Science.

I’m happy to hear any feedback on my technical posts or about exciting Earth Data Science projects. You can comment at the end of each post or tweet me @ImparoAnalytics.