The Fast & Furious franchise has evolved from street racing in Los Angeles to global espionage and high-stakes heists. To fully enjoy the saga, you need to understand the timeline, which isn't as straightforward as the release dates suggest. The Chronological Watch Order
: The original street-racing heist. 2 Fast 2 Furious (2003) : Brian O'Conner moves to Miami.
: The beginning of the end, featuring Dante Reyes. Core Themes & Elements
: The crew works with Hobbs to stop a mercenary.
: The former cop who becomes Dom's brother. Luke Hobbs (Dwayne Johnson) : The powerhouse federal agent. Deckard Shaw (Jason Statham) : The villain-turned-ally.
: The series shifted from tuner car culture to "superhero" espionage around Fast Five .
: Dom is coerced into betraying the family.
install.packages(repos=c(FLR="https://flr.r-universe.dev", CRAN="https://cloud.r-project.org"))
The Fast & Furious franchise has evolved from street racing in Los Angeles to global espionage and high-stakes heists. To fully enjoy the saga, you need to understand the timeline, which isn't as straightforward as the release dates suggest. The Chronological Watch Order
: The original street-racing heist. 2 Fast 2 Furious (2003) : Brian O'Conner moves to Miami.
: The beginning of the end, featuring Dante Reyes. Core Themes & Elements
: The crew works with Hobbs to stop a mercenary.
: The former cop who becomes Dom's brother. Luke Hobbs (Dwayne Johnson) : The powerhouse federal agent. Deckard Shaw (Jason Statham) : The villain-turned-ally.
: The series shifted from tuner car culture to "superhero" espionage around Fast Five .
: Dom is coerced into betraying the family.
The FLR project has been developing and providing fishery scientists with a powerful and flexible platform for quantitative fisheries science based on the R statistical language. The guiding principles of FLR are openness, through community involvement and the open source ethos, flexibility, through a design that does not constraint the user to a given paradigm, and extendibility, by the provision of tools that are ready to be personalized and adapted. The main aim is to generalize the use of good quality, open source, flexible software in all areas of quantitative fisheries research and management advice.
Development code for FLR packages is available both on Github and on R-Universe. Bugs can be reported on Github as well as suggestions for further development.
Studies and publications citing or using FLR
.You can subscribe to the FLR mailing list.
Please submit an issue for the relevant package, or at the tutorials repository.
