Exploring Udine and its Municipalities

Course

Geospatial Analysis and Representation for Data Science (2021-2022)

Aim of the Project

The project initially focuses on Udine, and then examines the municipalities in the province. It is mainly addressed to students interested in studying and moving to the city. The aim is to provide students with useful tools and information for their future life in Udine, by means of various kinds of representations and a geospatial analysis of house prices and rents.

Structure

The project is divided into three main parts:

1. Static map of Udine, with universities and points of interest

   It provides the main information about the city.

   

2. Interactive map of Udine with real walking and cycling routes

   The map is designed for those who want to train and test themselves.

   

3. Geospatial analysis of average house prices and rents in the province of Udine

   Interesting for those planning to move to Udine or its vicinity. It provides useful hints and considerations about the influence of each municipality on prices in neighbouring municipalities.

   

How to execute the code (Python)

The following is a list of methods by which you can install the necessary tools to run the Python code on your system.

Solution 1: Anaconda environment

Note: this solution has been tested on Windows and Linux operating systems.

• If you want to run the code on your own machine, it is strongly recommended to use the package manager conda of the Anaconda distribution.

• In the environment folder you will find the file environment.yaml, download it.

• You can recreate the environment using the command:

  conda env create --file environment.yaml

  Note that you don't need to specify the env name, which is GEO_PROJ and is already contained within the .yaml file. It is not needed to specify the version of Python either, as Python 3.9.9 will be installed automatically.

• You can now activate the environment with the command:

  conda activate GEO_PROJ

  This is usually recognised by the terminal, which will look like this:

  (GEO_PROJ) ...

• It is now possible to execute the code.

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Why not use pip?

Some packages are installed using the conda or conda-forge channel. Not all dependencies are available in pip, and this leads to errors.

However, a requirements.txt file has been created which shows the list of required packages.

It is not recommended to use the classic pip install -r requirements.txt command, as it will almost certainly lead to errors.

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Solution 2: install the packages manually

If you don't want to use conda or can't use the .yaml file, you can try installing the main needed packages manually.

It is recommended to create a new virtual environment, activate it and then follow the package documentation for installation.

• pandas==1.3.5
• geopandas==0.10.2
• pygeos==0.12.0
• pyrosm==0.6.1 --> it must be installed after geopandas in Windows
• matplotlib==3.5.1
• geopy==2.2.0
• osmnx==1.1.2
• gpxpy==1.5.0
• movingpandas==0.8rc1
• contextily==1.2.0
• folium==0.12.1.post1
• leafmap==0.7.0

Alternative Solution: Online Notebooks

All the notebooks are freely explorable on this webpage. The code is already executed and you do not need to download anything.

How to execute the code (R)

The list of libraries needed to execute the R code follows:

• dplyr
• rgdal
• spdep
• ggplot2

All packages can be installed with the following command:

install.packages("package name", dependencies = TRUE)

Alternative Solution: Online Notebook

The notebook is freely explorable here. The code is already executed and you do not need to download anything.