print.epiflows.RdDisplays a short summary of an epiflows object.
# S3 method for epiflows print(x, ...)
| x | An |
|---|---|
| ... | Additional parameters (not used). |
data("Brazil_epiflows") print(Brazil_epiflows)#> #> /// Epidemiological Flows // #> #> // class: epiflows, epicontacts #> // 15 locations; 100 flows; directed #> // optional variables: pop_size, duration_stay, num_cases, first_date, last_date #> #> // locations #> #> # A tibble: 15 x 6 #> id location_popula… num_cases_time_… first_date_cases last_date_cases #> * <chr> <dbl> <dbl> <fct> <fct> #> 1 Espi… 3973697 2600 2017-01-04 2017-04-30 #> 2 Mina… 20997560 4870 2016-12-19 2017-04-20 #> 3 Rio … 16635996 170 2017-02-19 2017-05-10 #> 4 Sao … 44749699 200 2016-12-17 2017-04-20 #> 5 Sout… 86356952 7840 2016-12-17 2017-05-10 #> 6 Arge… NA NA <NA> <NA> #> 7 Chile NA NA <NA> <NA> #> 8 Germ… NA NA <NA> <NA> #> 9 Italy NA NA <NA> <NA> #> 10 Para… NA NA <NA> <NA> #> 11 Port… NA NA <NA> <NA> #> 12 Spain NA NA <NA> <NA> #> 13 Unit… NA NA <NA> <NA> #> 14 Unit… NA NA <NA> <NA> #> 15 Urug… NA NA <NA> <NA> #> # ... with 1 more variable: length_of_stay <dbl> #> #> // flows #> #> # A tibble: 100 x 3 #> from to n #> <chr> <chr> <dbl> #> 1 Espirito Santo Italy 2828. #> 2 Minas Gerais Italy 15714. #> 3 Rio de Janeiro Italy 8164. #> 4 Sao Paulo Italy 34039. #> 5 Southeast Brazil Italy 76282. #> 6 Espirito Santo Spain 3270. #> 7 Minas Gerais Spain 18176. #> 8 Rio de Janeiro Spain 9443. #> 9 Sao Paulo Spain 39371. #> 10 Southeast Brazil Spain 88231. #> # ... with 90 more rows #>