Open Webinar: Analysis of long term temperature data with Python and Pandas

Temperature data needs to be evaluated with the use of tools that can process thousands of records with capabilities to make plots, regressions and statistics. This webinar covers an applied example of temperature data analysis with Python, Pandas and related libraries. The study case corresponds to the Central Park, NY US meteorological station with data for precipitation, snow and temperature for a period of 150 years. The Python code developed for the webinar allows us to explore data in a comprehensive way, to get metrics and to diagnose the development of the weather parameters regarding climate change.

Instructor / Instructor:

Saul Montoya M.Sc

Hydrogeologist - Numerical Modeler

Mr. Montoya is a Civil Engineer graduated from the Catholic University in Lima with postgraduate studies in Management and Engineering of Water Resources (WAREM Program) from Stuttgart University – Germany with mention in Groundwater Engineering and Hydroinformatics. Mr Montoya has a strong analytical capacity for the interpretation, conceptualization and modeling of the surface and underground water cycle and their interaction. He is in charge of numerical modeling for contaminant transport and remediation systems of contaminated sites. Inside his hydrological and hydrogeological investigations Mr. Montoya has developed an holistic comprehension of the water cycle, understanding and quantifying the main hydrological dynamic process of precipitation, runoff, evaporation and recharge to the groundwater system.

Language / Lenguaje:

English

Event date / Fecha del evento:

Monday, December 6, 2021 at 6:00 p.m. New York Time (EST)

Hosted by / Organizado por:

Hatarilabs

Stream link / Enlace de transmisión:

https://meet.google.com/jjx-duvr-osm

Input data / Datos de entrada:

https://owncloud.hatarilabs.com/s/3P1nC4HR55yXWdl

Additional instructions / Instrucciones adicionales:

Password to download input data: Hatarilabs. You need Anaconda installed on your computer. Please download it from this link: https://www.anaconda.com/products/individual