Physical measurements of 4177 abalones, a species of sea snail.
Format
A tibble with 4,177 observations and 9 variables:
- sex
Sex of the abalone,
F
is female,M
male, andI
infant.- length
Longest shell measurement.
- diameter
Diameter perpendicular to length.
- height
Height with with meat in shell.
- whole_weight
Grams whole abalone.
- shucked_weight
Grams weight of meat.
- viscera_weight
Grams gut weight (after bleeding).
- shell_weight
Grams after being dried.
- rings
+1.5 gives the age in years.
Source
Dua, D. and Graff, C. (2019). UCI Machine Learning Repository https://archive.ics.uci.edu/ml/. Irvine, CA: University of California, School of Information and Computer Science.
Details
See the web page https://archive.ics.uci.edu/ml/datasets/Abalone for more information about the data set.
References
Ko, V., Hjort, N. L., & Hobaek Haff, I. (2019). Focused information criteria for copulas. Scandinavian Journal of Statistics.
Examples
abalone
#> # A tibble: 4,177 × 9
#> sex length diameter height whole_weight shucked_weight viscera_weight
#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 M 0.455 0.365 0.095 0.514 0.224 0.101
#> 2 M 0.35 0.265 0.09 0.226 0.0995 0.0485
#> 3 F 0.53 0.42 0.135 0.677 0.256 0.142
#> 4 M 0.44 0.365 0.125 0.516 0.216 0.114
#> 5 I 0.33 0.255 0.08 0.205 0.0895 0.0395
#> 6 I 0.425 0.3 0.095 0.352 0.141 0.0775
#> 7 F 0.53 0.415 0.15 0.778 0.237 0.142
#> 8 F 0.545 0.425 0.125 0.768 0.294 0.150
#> 9 M 0.475 0.37 0.125 0.509 0.216 0.112
#> 10 F 0.55 0.44 0.15 0.894 0.314 0.151
#> # ℹ 4,167 more rows
#> # ℹ 2 more variables: shell_weight <dbl>, rings <int>