Geo-Data Science and GIS

Hello there,

Today, I want to discuss about the Best programming language for Geo-Data Science and GIS.

What is Geo-Data Science and GIS?

Geo-Data Science: Geo-Data Science is a subset of Data science which according to wikipedia; is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, data mining, and predictive analytics, similar to Knowledge Discovery in Databases (KDD). Source...

Geodata is information about geographic locations that is stored in a format that can be used with a geographic information system (GIS).

Geodata can be stored in a database, geodatabase, shapefile, coverage, raster image, or even a dbf table or Microsoft Excel spreadsheet.

A data scientist is someone who knows more statistics than a computer scientist and more computer science than a statistician. To be mre formal, we can say a data scientist is someone who extracts insights from messy data.

GIS: According to National Geographic Society;- A geographic information system (GIS) is a computer system for capturing, storing, checking, and displaying data related to positions on Earth’s surface. GIS can show many different kinds of data on one map. This enables people to more easily see, analyze, and understand patterns and relationships. 

According to WikiPedia;- A geographic information system or geographical information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present all types of spatial or geographical data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics.

In the contemporary Geo-Data Science and GIS fields, the common programming languages are R and Python.

R is a programming language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

Python is a programming language that lets you work more quickly and integrate your systems more effectively. You can learn to use Python and see almost immediate gains in productivity and lower maintenance costs.

The infographic below by DataCamp summaries everything you need to know about R and Python 

 

Thanks for reading.