The {avocado} package provides a summary of weekly Hass avocado sales for the contiguous United States. The underlying data are from The Hass Avocado Board (free registration required). Hass Avocados are the most popular variety of avocados sold in the United States and the Haas Avocado Board (HAB) provides crucial data on them to growers and marketers.
The HAB makes this information available to anyone who may be interested (free registration required). An important note to remember is that the term ‘units’ typically refers to 1 avocado. It does not refer to avocados in terms of weight, bags, etc. The HAB does not provide (at least publicly) actual piece-count sales to retailers or consumers.
The {avocadoo} package consists of 3 primary PLUs:
Organic avocados have the digit 9 prefixed to the non-organic PLUs: * 94046: organic small/medium Hass Avocados (~3-5 oz) * 94225: organic large Hass Avocados (~8-10 oz) * 94770: organic extra large Hass Avocados (~10-15 oz)
Source: Love One Today
HAB also tracks avocado sales in bags of varying sizes. Since 2021, HAB does not break down units of avocados sold by bag size (e.g., small, large, extra large). Bags can consist of multiple avocados and can weights of bags can vary.
See this vignette for more information.
Install the development version from GitHub:
# install.packages("devtools")
devtools::install_github("nikdata/avocado", ref = 'main')The {avocado} package consists of three different datasets:
hass_usa: weekly contiguous US avocado sales at the
country levelhass_region: weekly contiguous US avocado sales at the
region levelhass_market: weekly contiguous US avocado sales at the
city/sub-region (i.e., market) levelThe hass_market dataset provides a weekly sales summary
of Hass Avocado sales in the contiguous US (subdivided by region and
select cites/sub-regions within each ‘parent’ region):
library(avocado)
dplyr::glimpse(hass_market)
#> Rows: 38,522
#> Columns: 13
#> $ region <chr> "Northeast", "Southeast", "Midsouth", "West"…
#> $ market <chr> "Albany", "Atlanta", "Baltimore/Washington",…
#> $ week_ending <date> 2017-01-02, 2017-01-02, 2017-01-02, 2017-01…
#> $ type <chr> "Conventional", "Conventional", "Conventiona…
#> $ avg_selling_price <dbl> 1.47, 0.93, 1.47, 0.92, 1.29, 1.43, 1.21, 1.…
#> $ total_bulk_and_bags_units <dbl> 129949, 547566, 631761, 104511, 458831, 1053…
#> $ plu4046_units <dbl> 4846, 224074, 54531, 27846, 4120, 1286, 4776…
#> $ plu4225_units <dbl> 117028, 118927, 408953, 9409, 371224, 58532,…
#> $ plu4770_units <dbl> 201, 338, 14388, 11342, 3934, 103, 15037, 11…
#> $ total_bagged_units <dbl> 7875, 204229, 153892, 55915, 79554, 45430, 5…
#> $ sml_bagged_units <dbl> 7867, 111600, 151346, 53094, 79340, 45156, 4…
#> $ lrg_bagged_units <dbl> 8, 92629, 2543, 2794, 214, 256, 13712, 1079,…
#> $ xlrg_bagged_units <dbl> 0, 0, 4, 28, 0, 19, 47, 5090, 2, 0, 917, 98,…Some potential use cases include: