GeoPandas is a Python library for working with vector data. It is based on the pandas library that is part of the SciPy stack. SciPy is a popular library for data inspection and analysis, but unfortunately, it cannot read spatial data. GeoPandas was created to fill this gap, taking pandas data objects as a starting point. The library also adds functionality from geographical Python packages. 

GeoPandas offers two data objects—a GeoSeries object that is based on a pandas Series object and a GeoDataFrame, based on a pandas DataFrame object, but adding a geometry column for each row. Both GeoSeries and GeoDataFrame objects can be used for spatial data processing, similar to spatial databases. Read and write functionality is provided for almost every vector data format. Also, because both Series and DataFrame objects are subclasses from pandas data objects, you can use the same properties to select or subset data, for example .loc or .iloc.

GeoPandas is a library that employs the capabilities of newer tools, such as Jupyter Notebooks, pretty well, whereas GDAL enables you to interact with data records inside of vector and raster datasets through Python code. GeoPandas takes a more visual approach by loading all records into a GeoDataFrame so that you can see them all together on your screen. The same goes for plotting data. These functionalities were lacking in Python 2 as developers were dependent on IDEs without extensive data visualization capabilities which are now available with Jupyter Notebooks.