Python

To run the analysis and reproduce the code in Python, you will need to set up the Python environment to:

Important

Do not try to run Python code in RStudio. Only run in Jupyter Notebooks (.ipynb) with the Python environment provided.

We will use Miniconda to handle our working environment.

Set up Miniconda (and Python) on Ms Windows

Installation

  1. Install Miniconda:

    • Option 1: On a UoL Machine: Anaconda is installed on many university machines. Please check whether it is installed. If not, download and install Anaconda through from Install University Applications, type and choose Anaconda.

    • Option 2: Recommended - Install Miniconda on your personal Laptop: Follow the instructions here.

  2. During the installation, leave the default settings. In particular, when asked whom to “Install Miniconda for”, choose “Just for me”.

University Machines

If you do choose to work on University Machines

  1. Chose a machine where Anaconda has been pre-installed.
  2. Always use the same machine. For example if on the first day you are using CT60 Station 17 - Orange Zone, continue using this machine for the rest of the course. If you change machine you will need to re-install the environment every time.

Set up the Directories

  1. Create a folder where you want to keep your work conducted throughout this course. For example, call it envs363_563. You can save it wherever you want. If you are working on a university machine, it could be worth creating it in M:/, which is your “virtual” hard-disk.

  1. Download the data to run and render the jupyter notebooks. To learn how to download folders from github see here.
  2. Unzip the folders and move the nested folders into the folder envs363_563.
  3. Create another folder called labs

The folder structure should look like:

envs363_563/
├── data/
└── labs/

Set up the Python Environment

  1. Download the envs363_563.yml from GitHub by cliciking Download raw file, top right at this page
  2. Save it in the folder envs363_563 created before.
  3. Type in the search bar and find the Anaconda Powershell Prompt if working on University Machine or Anaconda Prompt (miniconda 3) if on your personal. Launch it. The terminal should appear.

  1. In the Anaconda Terminal write: conda env create -n envs363_563 --file M:\envs363\envs363_563.yml and press Enter; if the file is located elsewhere you’ll need to use the corresponding file path.
  2. If you are prompted any questions, press y. This process will install all the packages necessary to carry out the lab sessions.
  3. In the Anaconda Terminal write conda activate envs363_563 and press Enter. This activates your working environment.

  1. Necessary on University machines, otherwise Optional: Configuration of Jupyter Notebooks
    • In the Anaconda Terminal, write jupyter server --generate-config and press enter. This, at least in Windows, should create a file to: C:\Users\username\.jupyter\jupyter_server_config.py.
    • Open the file with a text editor (e.g. Notepad++), do a ctrl-f search for: c.ServerApp.root_dir, uncomment it by removing the # and change it to c.ServerApp.notebook_dir = 'M:\\your\\new\\path, for example the directory where you created the envs363_563 folder. In the University Machines, it is advised to work on the directory M:\.
    • Save the file and close it.

Start a Lab Session

  1. Download the Jupyter Notebook of the session in your folder. Choose one jupyter notebook and click Dowload raw file as shown below.

  1. Save the file in the labs folder within your envs363_563 folder on your machine.
  2. Type in the search bar, find and open the Anaconda Prompt (miniconda 3).
  3. In the Anaconda Terminal write and run conda activate envs363_563.
  4. In the Anaconda Terminal write and run jupyter notebook. This should open Jupyter Notebook in your default browser.

  1. Navigate to your course folder in and double click on the notebook downloaded in step 1.
  2. You can now work on your copy of the notebook.

Follow these instructions and test your installation prior to the first Lab Session. If you experience any issues, write a message on the Ms Teams channel of the module. Setting up the Python environment is necessary for:

  • Executing the Jupyter Notebooks of the Lab sessions of the course.
  • Preparing your own Jupyter Notebooks for the assignments (one each).

Set up Miniconda (and Python) on MAC

Installation

To install Miniconda on your personal laptop, Follow the instructions here. During the installation, leave the default settings. In particular, when asked whom to “Install Miniconda for”, choose “Just for me”.

Set up the Directories

  1. Create a folder where you want to keep your work conducted throughout this course. For example, call it envs363_563. You can save it wherever you want. For example, Elisabetta has named her folder envs363_563 and it’s in her Dropbox in Users/PIETROST/Library/CloudStorage/Dropbox/envs363_563
  2. Download the data to run and render the jupyter notebooks. To learn how to download folders from github see here.
  3. Unzip the folders and move the nested folders into the folder envs363_563.
  4. Create another folder called labs

The folder structure should look like:

envs363_563/ ├── data/ └── labs/

Set up the Python Environment

  1. Download the envs363_563.yml from GitHub by clicking Download raw file, top right at this page
  2. Save it in the folder envs363_563 created before.
  3. Type in the search bar and open the Terminal.
  4. In the Terminal write conda env create -n envs363 --file envs363_563.yml and press Enter. This will need to be modified according to where you placed the envs363_563 folder. For example, Elisabetta has named her folder envs363_563 and it’s in her Dropbox in Users/PIETROST/Library/CloudStorage/Dropbox/envs363_563/envs363_563.yml. If you created the envs363_563 folder on your desktop, the path would be Desktop/envs363_563.

  1. If you are prompted any questions, press y. This process will install all the packages necessary to carry out the lab sessions.
  2. You should then see this

Start a Lab Session

  1. Download the Jupyter Notebook of the session in your folder. Choose one jupyter notebook and click Dowload raw file as shown below

  1. Save the file in the labs folder within your envs363 folder on your machine.
  2. Type in the search bar, find and open the Terminal.
  3. In the Terminal write and run conda activate envs363.
  4. In the Terminal write and run jupyter notebook.

  1. This should open Jupyter Notebook in your default browser. You should see something like this:

  1. Navigate to your folder. You can now work on your copy of the notebook.

Py Basics

Please refer to the tutorials from learnpython.org for an introduction to coding in Python. We particularly recommend the tutorials listed under the “Learn the Basics” section.

Resources

Some help along the way with:

  1. Geographic Data Science with Python.

  2. Python for Geographic Data Analysis