Geoviews Features – Datasets and Usage

In recent years it has become easier for scientists and companies to analyze their data with Python-based programs. Two key factors are the interactive notebooks and the range of freely available, combinable, and free analysis tools. Another useful tool is a Geoview Python library for visualizing geographical datasets. Here is more about it.

The purpose of the Geoview tool

Python is a multi-purpose programming language that allows you to write code that is easy to read. In addition, the relative brevity of the Python language allows you to create a program that will be much shorter than its counterpart written in another language. It is used for various purposes: to create games and web applications and to develop internal tools for various projects. The language is also widely used in the scientific field for research and solving applied problems.

Since Python is a server-side programming language, it is used to write web applications. According to statistics from various resources, Python is the leader among languages for backend development. Business logic and database interaction can be built on Python. Its libraries expand the possibilities of language. For example, Numpy is designed for data analysis and mathematical algorithms, or Geoview, for analyzing geographical objects.

The processing of geographic data requires appropriate software, language, and analytical tools, which are implemented, as a rule, only within the framework of specialized and, mainly, commercial geoinformation systems. Working with countries or regions is often found in real Data Science projects, so you often have to deal with geographic coordinates and maps. GeoView is a powerful mapping tool designed for Windows application developers who need to provide advanced geospatial data visualization capabilities with support for standard vector formats and layered rendering. The tool offers powerful support for a variety of meteorological and oceanographic datasets. These can be data that are used in weather, climate, and remote sensing research.

Basic features

One of the biggest challenges for data scientists is the lack of data in datasets. These missing values must be handled properly for adequate data analysis. So, the Geoview library is designed to visualize real-time data on demand by the user. The Geoview provides tools for creating maps and plotting geographic data. This Python library can be used to create various types of maps and graphs:

• choropleths,
• heatmaps,
• dot density maps,
• spatial graphs.

You can build graphs and draw lines, rectangles, and bubbles on the maps. You will get access to almost all the functionality of real-time metrics, but with fewer lines of code and more aesthetically pleasing charts. You can add multiple component layers to create the visualization’s final version using this library. This package has great visualization features such as block histograms and multi-axis contour plots. All charts are interactive. Thus, the plotting process is simplified, and the number of lines of code is reduced. In addition, it is possible to make interactive charts. In most cases, static graphs are sufficient to convey information. However, you may want to add user interaction to your charts in some cases.

Necessary operations at this stage include preparation (selection) of a mathematical projection, base layers (as a rule, these are elements of a topographic base), and thematic layers. A prerequisite for obtaining a high-quality digital model should be the availability of automatic verification procedures for all layers (geometry and attributes). The current standards for the digital representation of cartographic information describe the attribute part (classifier) in detail but often do not provide requirements for the topological relationships of different layers or only declare a set of such requirements.