Time to update your data.csv
file with new data which contains a deliberate error for period 462. Download this data and append it to data-raw/data.csv
in your repo, being sure not to duplicate the header row:
period | BA | DM | DO | DS | NA | OL | OT | PB | PE | PF | PH | PI | PL | PM | PP | RF | RM | RO | SF | SH | SO |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
451 | 0 | 35 | 12 | 1 | 1 | 2 | 2 | 4 | 0 | 5 | 0 | 0 | 0 | 0 | 84 | 0 | 0 | 0 | 1 | 0 | 0 |
452 | 0 | 30 | 12 | 1 | 1 | 1 | 4 | 6 | 3 | 2 | 0 | 0 | 0 | 0 | 93 | 0 | 0 | 0 | 0 | 0 | 0 |
453 | 0 | 34 | 9 | 0 | 3 | 2 | 4 | 6 | 5 | 1 | 0 | 0 | 0 | 0 | 76 | 0 | 0 | 0 | 0 | 0 | 0 |
454 | 0 | 34 | 5 | 1 | 3 | 1 | 7 | 5 | 5 | 0 | 0 | 0 | 0 | 0 | 38 | 0 | 0 | 0 | 0 | 0 | 0 |
455 | 0 | 42 | 6 | 1 | 4 | 2 | 10 | 5 | 5 | 0 | 0 | 0 | 1 | 0 | 9 | 0 | 0 | 0 | 0 | 1 | 0 |
458 | 0 | 61 | 16 | 1 | 5 | 1 | 9 | 1 | 4 | 0 | 0 | 0 | 4 | 3 | 0 | 0 | 11 | 2 | 0 | 3 | 0 |
459 | 0 | 62 | 20 | 1 | 7 | 0 | 6 | 2 | 6 | 0 | 0 | 0 | 5 | 2 | 2 | 1 | 10 | 2 | 0 | 1 | 0 |
460 | 0 | 55 | 17 | 0 | 0 | 3 | 11 | 1 | 11 | 0 | 0 | 0 | 3 | 4 | 44 | 0 | 10 | 4 | 0 | 0 | 0 |
461 | 0 | 63 | 19 | 0 | 6 | 2 | 8 | 2 | 11 | 1 | 0 | 0 | 2 | 1 | 44 | 1 | 1 | 0 | 0 | 8 | 0 |
4620 | 0 | 44 | 24 | 0 | 5 | 1 | 11 | 5 | 10 | 1 | 1 | 0 | 1 | 0 | 92 | 0 | 1 | 1 | 0 | 0 | 0 |
463 | 0 | 33 | 7 | 1 | 7 | 0 | 8 | 2 | 2 | 1 | 2 | 0 | 0 | 0 | 108 | 0 | 0 | 0 | 0 | 2 | 0 |
465 | 0 | 33 | 9 | 0 | 1 | 0 | 15 | 8 | 2 | 0 | 1 | 0 | 0 | 0 | 158 | 1 | 0 | 0 | 0 | 0 | 0 |
466 | 0 | 42 | 7 | 0 | 6 | 0 | 15 | 6 | 1 | 0 | 1 | 0 | 0 | 0 | 213 | 0 | 0 | 0 | 0 | 0 | 0 |
467 | 0 | 41 | 5 | 1 | 6 | 0 | 26 | 5 | 9 | 0 | 2 | 0 | 1 | 1 | 94 | 0 | 1 | 0 | 0 | 1 | 0 |
This is more rodent abundance data from Portal, from more recent sampling periods.
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure (test-periods-ga.R:12:5): Period values are valid. ──────────────────
`all_period_values_valid` is not TRUE
`actual`: FALSE
`expected`: TRUE
[ FAIL 1 | WARN 0 | SKIP 0 | PASS 1 ]
library(readr)
rodent_data <- read_csv("data-raw/data.csv")
which(rodent_data$period > 1000)
#> [1] 20
rodent_data[20, ]
#> # A tibble: 1 x 22
#> period BA DM DO DS NA. OL OT PB PE PF PH PI PL PM PP RF RM RO
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 4620 0 44 24 0 5 1 11 5 10 1 1 0 1 0 92 0 1 1
#> # … with 3 more variables: SF <dbl>, SH <dbl>, SO <dbl>
4620
. Correct this to 462
and re-save the data:
rodent_data$period[20] <- 462
write_csv(rodent_data, "data-raw/data.csv")