We spoke to four participants in the programme about their experiences of learning to code in a podcast episode hosted by Code for Thought, the podcast on software, engineering, research and anything in between.
Below-the-line conversations: A computer-facilitated case study of Guardian reader comments
Thank you to the mentors for giving your time and expertise to make this programme possible.
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Below are some useful resources recommended by the Learning to Code participants.
SPSS to R notes: https://www.melissagwolf.com/spss-to-r/ conversion of standard statistical analyses from SPSS to R. Probably not what you need right now, but could be helpful to replicate something you’re used to seeing.
Official Matlab tutorials: https://matlabacademy.mathworks.com/ - these look quite practical, especially “MATLAB Onramp” and “MATLAB for Data Processing and Visualization” courses. Not clear if they are free for you - would be good to know!
Actually a comprehensive reference: has sections on customizing particular types of plots, e.g. “Line plots” as well as sections on types of customization, e.g. “ Add text annotations to a graph”. Bit of a spammy site unfortunately (e.g. pop-up ads) but useful.
Used to have regular informal pub meetups (turn up and trouble-shoot R issues/share what you’re working on) and occasional events with more formal talks. Since COVID, have had occasional Zoom meetings, mostly working on Tidy Tuesday example data sets (https://github.com/rfordatascience/tidytuesday), plus a Shiny tutorial (tidyverse package for building web apps). New R users very welcome!