Read about our experience with Coding Club and check out our tutorials. Each tutorial post includes instructions and a link to the Github repository from where you can download all files necessary to participate in our workshops remotely.

Intro to spatial analysis in R

26 March 2019

Tutorial Aims: 1. Explore raster data 2. Visualise spectral bands 3. Manipulate rasters: NDVI and KMN classification All the files you need to complete this tutorial can be downloaded from this repository. Click on Clone/Download/Download ZIP and unzip the folder, or clone the repository to your own GitHub account. In...

Writing R packages in Rstudio

20 March 2019

Tutorial Content 1. Introduction: What is an R package? 2. Packages that need to be installed 3. The most basic R package 4. Making a new R project 5. Adding documentation (help files) 6. Uploading to and installing from GitHub 7. Other useful things to know 8. Additional resources This...

Time series analysis with pandas

07 January 2019

In this tutorial we will do some basic exploratory visualisation and analysis of time series data. We will learn how to create a pandas.DataFrame object from an input data file, plot its contents in various ways, work with resampling and rolling calculations, and identify correlations and periodicity. To complete the...

Topic Modelling in Python

10 December 2018

Tutorial aims: 1. Introduction and getting started 2. Exploring text datasets 3. Extracting substrings with regular expressions 4. Finding keyword correlations in text data 5. Introduction to topic modelling 6. Cleaning text data 7. Applying topic modelling 8. Bonus exercises Introduction In this tutorial we are going to be performing...

Intro to modelling using INLA

04 December 2018

Tutorial Aims: 1. Learn about INLA and why it’s useful 2. Perform model selection in INLA 3. Learn the components of an INLA model 4. Set up a spatial analysis 5. Modify and specify spatial models 6. Learn about spatiotemporal analyses All the files needed to complete this tutorial can...

Advanced data manipulation and visualisation

02 December 2018

Tutorial Aims: 1. Create a reproducible report using Markdown 2. Learn about the tidyverse 3. Use pipes to make figures with large datasets 4. Download and map data from large datasets This tutorial was developed for the British Ecological Society Quantitative Ecology Special Interest Group Advanced R workshop. Check out...

Numbers in Python with NumPy

30 November 2018

Tutorial aims: 1. What is NumPy? 2. Basic manipulation NumPy arrays 3. Masked arrays 4. Reading and writing data 5. Cautions when using NumPy arrays What is NumPy? So what is NumPy? According to the official website, NumPy is the fundamental package for scientific computing with Python. One trade-off of...

Intro to the Google Earth Engine

26 November 2018

Tutorial Aims: 1. Learn what the Google Earth Engine is 2. Find out what types of analyses you can do using the GEE 3. Get familiar with the GEE layout 4. Learn the basic principles of JavaScript 5. Import and explore data - forest cover change as a case study...

Python Crash Course

05 November 2018

Tutorial Aims: 1. Learn how to install Python and start coding 2. Learn the basics of Python 3. Explore where you can go next on your Python journey This tutorial is a whistle stop tour of Python, the aim is not to get you to be an expert by the...

Analysing Earth science and climate data with Iris

31 October 2018

Material for this tutorial was adapted from the SciTools tutorial (SciTools is the group that maintain the Iris software.) It was adapted and modified under the GNU public licence v 3.0 for this OurCodingClub tutorial and we acknowledge appreciate the use of original source materials from SciTools - Thank you!...

Intro to Machine Learning in R (K Nearest Neighbours Algorithm)

15 October 2018

Tutorial Aims: 1. What is about machine learning 2. Train your algorithm 3. Asses your model What is Machine Learning? Today machine learning is everywhere. From the content delivered to you on your Facebook newsfeed to the spam emails being filtered out of your emails, we live in an increasingly...

Introduction to Fortran

30 July 2018

Tutorial aims: 1. Understand what the Fortran progamming langauge is 2. Learn about a brief history of Fortran 3. Understand how Fortran differs to other programming languages 4. Learn some of the basic syntax of the Fortran language 5. Learn how to compile a basic Fortran program 6. Learn how...

Introduction to ordination

04 May 2018

Tutorial Aims 1. Get familiar with ordination 2. Learn about the different ordination techniques 3. Interpret ordination results In this tutorial, we will learn to use ordination to explore patterns in multivariate ecological datasets. We will mainly use the vegan package to introduce you to three (unconstrained) ordination techniques: Principal...

Generalised linear models in Stan

30 April 2018

Tutorial Aims: 1. Learn about generalised models in Stan 2. Use the rstanarm package to run a Poisson model 3. Assess model convergence 4. Check priors in rstanarm 5. Extract Stan code 6. Run a model with a negative binomial distribution 7. Compare rstanarm and brms All the files you...

Python Data Analysis with Pandas and Matplotlib

18 April 2018

Welcome to this tutorial about data analysis with Python and the Pandas library. If you did the Introduction to Python tutorial, you’ll rememember we briefly looked at the pandas package as a way of quickly loading a .csv file to extract some data. This tutorial looks at pandas and the...

Intro to Stan

17 April 2018

Tutorial Aims: 1. Learn about Stan 2. Prepare a dataset for modelling 3. Write a programme in Stan 4. Run a Stan programme 5. Specify priors in Stan 6. Assess convergence diagnostics All the files you need to complete this tutorial can be downloaded from this repository. Click on Clone/Download/Download...

Intro to model design

06 April 2018

Tutorial Aims: 1. Learn what a statistical model is 2. Come up with a research question 3. Think about our data 4. Think about our experimental design 5. Turn a question into a model 6. Learn about the different types of models 7. General linear models 8. Hierarchical models using...

GitHub, Tidyverse and Markdown - a coding workshop for the EVENET network

06 March 2018

Tutorial Aims: 1. Create a coding tutorial and host it on GitHub 2. Set up version control with GitHub and RStudio 3. Analyse and visualise data using the tidyverse 4. Create a reproducible report using Markdown All the files you need to complete this tutorial can be downloaded from this...

Analysing ordinal data, surveys, count data

29 January 2018

Tutorial Aims: 1. Learn how to format survey data, coding responses, data types etc. 2. Practise visualising ordinal data, count data, likert scales 3. Mining text responses and comments for keywords. 4. Statistically analyse qualitative data This workshop will explore qualitative data, the sort of data you might collect through...

Intro to Python

26 January 2018

Tutorial aims: Understand why Python is so useful for scientific programming 1. Installing Python and running a simple Python program 2. Reading data from a file 3. Get a feel for how Python looks and feels 4. Load data from a text file into memory 5. Learn about some basic...

Meta-analysis for biologists using MCMCglmm

22 January 2018

This tutorial is aimed at people who are new to meta-analysis and using the MCMCglmm package written by Dr Jarrod Hadfield, to help you become comfortable with using the package, and learn some of the ways you can analyse your data. It isn’t designed to teach you about hardcore Bayesian...

Manipulation and visualisation of spatial and population data

06 January 2018

Tutorial Aims: 1. Download, format and manipulate biodiversity data 2. Clean species occurrence data 3. Visualise & customise species occurrence and population trends All the files you need to complete this tutorial can be downloaded from this repository. Click on Clone/Download/Download ZIP and unzip the folder, or clone the repository...

Transferring quantitative skills among scientists

23 November 2017

Tutorial Aims: 1. Get familiar with the Coding Club model 2. Write your own tutorial 3. Publish your tutorial on Github Key steps Each step is explained in detail as you start going through the workshop resources below. Have a quick read. There is no need to click on links...

Quantifying and visualising population trends

11 November 2017

Tutorial Aims: 1. Tidy dataset 2. Calculate population change 3. Make a map of vertebrate population change in Europe All the files needed to complete this tutorial can be downloaded from this Github repository. Click on Clone or Download/Download ZIP and then unzip the files. This is a short tutorial...

Coding Club is back for the new academic year!

14 September 2017

Coding Club is almost a year old! Time has flown by, many lines of code have rolled in, and we have gathered quite the collection of tutorials on our website! It has been so wonderful to meet people keen to advance their quantitative skills and learn more about coding! It’s...

Coding Club goes to Aberdeen and SEECC 2017!

13 September 2017

It’s been almost a year since we first started pondering the idea of a positive and supportive environment where we can all advance our skills in statistics and programming. We had a vision for a place where we can learn without the pressure of formal assessment, and with the ability...

Setting up a GitHub repository for your lab

15 May 2017

Tutorial Aims: 1. Set up a lab GitHub organisational account 2. Organise your lab repository 3. Develop a coding & GitHub etiquette 4. Learn to use RStudio and Github together What is version control? Version control allows you to keep track of your work and helps you to easily explore...

Analysing Time Series Data

26 April 2017

Tutorial Aims: 1. Formatting time series data 2. Visualising time series data 3. Statistically analysing time series data 4. Challenge yourself with new data In this tutorial, we will explore and analyse time series data in R. Time series analysis is a powerful technique that can be used to understand...

Coding etiquette

25 April 2017

Tutorial Aims: 1. Organising scripts into sections 2. Following a coding syntax etiquette 3. Tidying up old scripts and data frames When analysing data in R, the lines of code can quickly pile up: hundreds of lines to scroll through, numerous objects whose names might make sense to you, but...

Data visualisation 2

29 March 2017

Tutorial aims & steps: 1. Customise histograms in ggplot2 - Add titles, subtitles, captions and axis labels - Change the plot background - Fix the legend and customise colours 2. Create your own colour palette 3. Customise boxplots in ggplot2 4. Add regression lines to your plots 5. Create your...

Intro to data clustering

21 March 2017

Tutorial Aims: 1. Get acquainted with data clustering 2. Learn about different distance metrics 3. Learn about different linkage methods 4. Turn groups into a grouping variable 5. Map cluster groups in geographic space To get all you need for this session, go to the repository for this tutorial, fork...

Working efficiently with large datasets

20 March 2017

Tutorial Aims: 1. Formatting and tidying data using tidyr 2. Efficiently manipulating data using dplyr 3. Automating data manipulation using lapply(), loops and pipes 4. Automating data visualisation using ggplot2 and dplyr 5. Species occurrence maps based on GBIF and Flickr data Quantifying population change This workshop will provide an...

Introduction to linear mixed models

15 March 2017

This workshop is aimed at people new to mixed modeling and as such, it doesn’t cover all the nuances of mixed models, but hopefully serves as a starting point when it comes to both the concepts and the code syntax in R. There are no equations used to keep it...

Getting Started with Shiny

07 March 2017

Tutorial aims: 1. Downloading Shiny 2. Getting familiar with the Shiny app file structure 3. Getting familiar with the Shiny app.R layout 4. Creating a Shiny app 5. Exporting a finished app 6. Challenge yourself to write an app At it’s core, Shiny is merely an R package like dplyr...

Web Scraping

06 March 2017

Tutorial Aims: 1. Isolate and retrieve data from a html web page 2. Automate the download of multiple web pages using R 3. Understand how web scraping can speed up the harvesting of online data Steps: 1. Download the relevant packages 2. Download a .html web page 3. Import a...

From distributions to linear models

28 February 2017

Tutorial Aims & Steps: 1. Get familiar with different data distributions 2. Choosing your model structure 3. Practice linear models (and ANOVAs) - Write and run the models - Understand the outputs - Verify the assumptions 4. Practice generalised linear models 5. Challenge yourself! Things get real in this tutorial!...

Intro to Github for version control

27 February 2017

Tutorial Aims: 1. Get familiar with version control, git and GitHub 2. Create your own repository and project folder structure 3. Sync and interact with your repository through RStudio 4. Sync and interact with your repository through the command line 1. Get familiar with version control, Git and GitHub What...

Intro to functional programming

08 February 2017

Tutorial aims: 1. What is functional programming 2. Building a simple function 3. Functions in loops 4. Functions with lapply 5. Conditional statements 6. BONUS: Write a loop to plot multiple graphs All the resources for this tutorial, including some useful extra reading can be downloaded from this Github repository....

Beautiful and informative data visualisation

29 January 2017

Tutorial aims and steps: 1. Get familiar with the ggplot2 syntax 2. Decide on the right type of plot 3. Practice making different plots with ggplot2 - Histograms - Scatter plots - Box plots - Bar plots 4. Learn to arrange graphs in a panel and to save files 5....

Easy and efficient data manipulation

16 January 2017

This page has moved! Find the updated tutorial here.

Basic data manipulation

06 January 2017

Tutorial aims: 1. Learn base R syntax for data manipulation - logical operators for finer control - creating and assigning objects - `specifying factors 2. Turn messy data into tidy data with tidyr 3. Use efficient tools from the dplyr package to manipulate data Steps: Subset, extract and modify data...

Efficient data manipulation

06 January 2017

Tutorial aims: 1. Chain together multiple lines of codes with pipes %>% 2. Use dplyr to its full potential 3. Automate advanced tasks like plotting without writing a loop Steps: An introduction to pipes Discover more functions of dplyr - summarise_all() - case_when() Rename and reorder factor levels or create...

Coding club progress and future plans

03 January 2017

We are all thrilled to have launched Coding Club at the end of 2016 and are very excited to see it grow in 2017. Coding Club is a peer-to-peer learning community aiming to develop quantitative skills, in particular fluency in statistics and programming. We are working as a team of...

Spatial Data and Maps

11 December 2016

Tutorial Aims: 1. Plot simple maps in ggplot2 2. Manipulate spatial polygons 3. Import, manipulate and plot shapefiles Steps: 1. Why use R to make maps? 2. Downloading the relevant packages 3. Getting your head around spatial data 4. Creating a map using ggplot2 and rworldmap 5. Using shapefiles All...

Getting Started with R Markdown

24 November 2016

Tutorial Aims: 1. Understand what RMarkdown is and why you should use it 2. Learn how to construct an RMarkdown file 3. Export an RMarkdown file into many file formats Steps: 1. What is RMarkdown? 2. Download RMarkdown 3. Create an RMarkdown (.Rmd) file 4. Identify the different parts of...

Troubleshooting and how to find help

15 November 2016

Tutorial aims: 1. Learn how to pick up on errors in R 2. Get familiar with common errors and solutions 3. Learn how to find help online 4. Practice by fixing errors in an example script In our first tutorial, we learned how to import data into RStudio, conduct a...

Getting started with R and RStudio

13 November 2016

Tutorial aims: 1. Understand what are R and R Studio 2. Develop the good habit of working with scripts 3. Learn to import data in R 4. Learn to manipulate R objects like vectors and data frames 5. Make a simple plot Steps: 1. Download R and RStudio 2. Import...

Preparing to launch Coding Club

17 October 2016

Over the summer, we have been preparing to launch Coding Club - lots of excitement and a long to do list! We are all looking forward to Coding Club - our vision of a supportive peer-to-peer learning community becoming a reality! We have been working on grant applications, this website...

Efficient data synthesis and visualisation

01 January 2016

Tutorial Aims: 1. Format and manipulate large datasets 2. Automate repetitive tasks using pipes and functions 3. Synthesise information from different databases 4. Download occurrence data through R 5. Create beautiful and informative figure panels The goal of this tutorial is to advance skills in working efficiently with data from...

Copying and pasting code chunks

01 January 1900

Tutorial aims: 1. Get a script and button that copy and paste the code It works! What is R? R is a statistical programming language that has rapidly gained popularity in many scientific fields. It was developed by Ross Ihaka and Robert Gentleman as an open source implementation of the...