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    https://sophisticatedspectra.com/article/drosia-serenity-a-modern-oasis-in-the-heart-of-larnaca.2521391.html

    DROSIA SERENITY
    A Premium Residential Project in the Heart of Drosia, Larnaca

    ONLY TWO FLATS REMAIN!

    Modern and impressive architectural design with high-quality finishes Spacious 2-bedroom apartments with two verandas and smart layouts Penthouse units with private rooftop gardens of up to 63 m² Private covered parking for each apartment Exceptionally quiet location just 5–8 minutes from the marina, Finikoudes Beach, Metropolis Mall, and city center Quick access to all major routes and the highway Boutique-style building with only 8 apartments High-spec technical features including A/C provisions, solar water heater, and photovoltaic system setup.
    Drosia Serenity is not only an architectural gem but also a highly attractive investment opportunity. Located in the desirable residential area of Drosia, Larnaca, this modern development offers 5–7% annual rental yield, making it an ideal choice for investors seeking stable and lucrative returns in Cyprus' dynamic real estate market. Feel free to check the location on Google Maps.
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    Geospatial Data Science with Python: Data Visualization

    Posted By: IrGens
    Geospatial Data Science with Python: Data Visualization

    Geospatial Data Science with Python: Data Visualization
    .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 7h 58m | 4.64 GB
    Instructor: Michael Miller

    Tabular and Geospatial visualizations with Matplotlib, Pandas, Seaborn, Plotly, Bokeh, and more!

    Description

    Pandas and GeoPandas within a Jupyter Notebook environment provide a powerful alternative to traditional desktop GIS methods for geospatial analysis. The ability to incorporate visualizations of both tabular data and geospatial data from within your analysis workflow is one of the big advantages of this approach.

    This course provides detail on how to create beautiful tabular and geospatial visualizations using Matplotlib, Pandas, GeoPandas, Rasterio, Contextily, Seaborn, Plotly, Bokeh and other Python packages within a Jupyter Notebook environment.

    We start with Matplotlib because it is the core upon which all of the other static plotting methods are based. Pandas, GeoPandas, Rasterio, Contextily, and Seaborn all produce Matplotlib objects as output. If you understand Matplotlib you can use that knowledge to modify the lots put out by any of these other packages. You can control the labels and titles, place annotation on the maps, include ticks and gridlines, place legends, set the x and y limits and more. And you can control every detail of those outputs, even when the higher level plotting API's make it easy to produce the base output with a single line of code.

    Plotly and Bokeh produce dynamic output that is based on JavaScript and are able to respond to mouse movements, clicks, etc.

    Who this course is for:

    Geospatial professionals who want to increase their knowledge of the Python Geospatial Data Science stack, especially with regards to data visualization.


    Geospatial Data Science with Python: Data Visualization