Lab work
We will conduct our lab work using the open source software R. You may find this cheat sheet useful.
To learn advanced programming techniques in R and its functional nature, see Hadley Wickman, Advanced R (electronic book), and the same author's paper on The Split-Apply-Combine strategy for data analysis (the plyr package). Another useful source of tips for good R programming practices: P. Burns, The R Inferno.
- LAB 1 (18-Sep): Introduction to igraph [guide] [data]
- Deadline for deliverable is Oct. 1, 23:00, please submit your solution via the Raco
- R as functional language: a script to show advantages of functional R versus procedural R. [R_functional_Proc]
- LAB 2 (2-Oct): Analysis of the degree distribution [files]
- Deadline for deliverable is Oct. 15th, please submit your solution via the Raco
- LAB 3 (16-Oct): Significance of network metrics [guide]
- Deadline for deliverable is Oct. 29th, please submit your solution via the Raco
- LAB 4 (6-Nov): Non-linear regression on dependency trees [guide]
- Deadline for deliverable is Nov. 19th, please submit your solution via the Raco
- LAB 5 (20-Nov): Network dynamics [guide]
- Deadline for deliverable is Dec. 3rd, please submit your solution via the Raco
© 2025 Marta Arias, Ramon Ferrer-i-Cancho, Argimiro Arratia | Template design by Andreas Viklund