In Python, which library is commonly used for geospatial data analysis and mapping, especially in geographic information systems (GIS)?

Plotly
Seaborn
Pandas
GeoPandas

The correct answer is D. GeoPandas.

GeoPandas is a Python package that provides a geospatial extension for the pandas data analysis library. It allows you to work with spatial data in a variety of ways, including reading and writing data, performing spatial joins, and plotting maps.

Plotly is a Python library for creating interactive, publication-quality graphs and charts. It can be used to create a variety of different types of graphs, including line charts, bar charts, scatter plots, and maps.

Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for creating attractive and informative statistical graphics.

Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language.

GeoPandas is a powerful tool for working with geospatial data in Python. It is a great choice for anyone who needs to analyze or visualize spatial data.

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