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This course is designed for researchers who are complete beginners with no prior knowledge of coding and data analysis. Through lectures and exercises, attendees will learn how to code in Python, starting from core concepts such as variables and loops, through to coding live data visualisation. Go to the readme file for more info

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Summer School 2023 Stream 1: Intro to Code

Hello Everyone! This is the Readme File for the Summer School 2023 Stream 1: Intro to Code.

This course is designed for researchers who are complete beginners with no prior knowledge of coding and data analysis. Through lectures and exercises, attendees will learn how to code in Python, starting from core concepts such as variables and loops, through to coding live data visualisation. The course explores the basics of programming: variables, functions, loops, operating on data structures, data wrangling, visualisation, and publishing to the web. By the end of the course, attendees will understand how to bridge the gap between humans and computers, and how to apply the skills they have learnt to their own data analysis and research. This course is intended to be a foundation for those intending to start a journey towards analysing Humanities and Social Sciences research data.

The material in this repo was developed and curated by Pawel Orzechowski.

How to use the Jupyter Notebooks

1. Run the notebooks via GoogleColab

Open Google Colab: https://colab.research.google.com If you are not already logged you will be prompted to log-in via Gmail

Upload the Notebook to Google Colab

  1. Go to the GitHub header and copy and paste the link to this repo and select the notebook you want to use and press enter

Using the Notebook

The Notebook contains paragraphs of explanatory text interspersed with grey cells containing code blocks. To run a code block and see the result:

  1. Place your cursor within the cell
  2. Click the 'Run' button on the top menu
  3. The results of running this code will appear below
  4. If the results don't appear immediately, check the icon in the browser tab. AN egg-timer icon indicates it is processing the code.
  5. It is best to follow the Notebook from top to bottom as some code blocks will depend on results from previous cells
  6. You can edit code blocks yourself and run them to see the results of your changes

Clearing the cells

To clear the results and run the code again you can use the 'Cell' menu on the top menu bar

  1. To clear the results of the current cell: Cell > Current Outputs > Clear
  2. To clear the results of all cells: Cell > All Output > Clear

2. Installing Python via Anaconda

Python is great for general-purpose programming and is a popular language for scientific computing as well. Installing all of the packages required for this lessons individually can be a bit difficult, however, so we recommend the all-in-one installer Anaconda.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., Python 3.6 version).

Windows - Video tutorial

  1. Open anaconda.com/download with your web browser.

  2. Download the Python 3 installer for Windows.

  3. Double-click the executable and install Python 3 using MOST of the default settings. The only exception is to check the Make Anaconda the default Python option.

  1. Open anaconda.com/download with your web browser.

  2. Download the Python 3 installer for macOS.

  3. Install Python 3 using all of the defaults for installation.

Starting Python

To start Jupyter Notebook Open the Anaconda Navigator and Launch Jupyter Notebook

Upload the Notebook

  1. Download the notebook on your machine
  2. Go to Upload
  3. Navigate to where you have downloaded your file
  4. Select Upload again
  5. Double-click on the uploaded file

3. Run the notebook in Noteable

If you are part of the University of Edinburgh you can use Noteable the cloud-based computational notebook system that work on your browser from any device.

To get started:

Get the Notebook files for this tutorial

Download the files listed on the right to a location on your computer Make sure you know the location they have been downloaded to (usually your 'Downloads' folder) as you will need to upload them to Noteable. (The filename should end with '.ipynb'. If your computer has appended '.txt' to the end of the file make sure this is removed)

Start Noteable

  1. Open the following link in a new tab: https://noteable.edina.ac.uk/login
  2. Login with your EASE credentials
  3. Under 'Standard Notebook' click 'Start'

Upload the Notebook to Noteable

  1. From the Noteable home page, click on the 'Upload' button at the top right of the screen and browse to one of the files you saved earlier to select it.
  2. Now click the blue 'Upload' button to load it into Noteable
  3. Once the file has been uploaded, click on the filename to start the Notebook

License

All material collected here is free to use but is covered by a License: License: CC BY-NC 4.0 license

About

This course is designed for researchers who are complete beginners with no prior knowledge of coding and data analysis. Through lectures and exercises, attendees will learn how to code in Python, starting from core concepts such as variables and loops, through to coding live data visualisation. Go to the readme file for more info

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