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 when they use the term ‘units’, it often means the weight in US pounds. The HAB does not provide (at least publicly) actual piece-count sales to retailers.
The {avocadoo} package consists of 6 different PLUs:
Source: Love One Today
Another distinction that the HAB makes is between bags versus bulk. Bulk typically means avocados sold as individual pieces and are easily distinguishable with their PLU codes. Hence, the PLU refers to a bulk sale. On the other hand, the bags indicates a pre-packaged container consisting of a variable number of avocados of mixed PLU type. For instance, a package of six avocados may consist of 2 PLU 4046, 3 PLU 4770 and 1 PLU 4225. In other words, bagged sales are unable to account for individual PLU sales.
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
: weekly contiguous US avocado sales at the city/sub-region levelThe hass
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)
#> Rows: 8,865
#> Columns: 17
#> $ week_ending <dttm> 2017-01-02, 2017-01-02, 2017-01-02, 2017-01-02, 20…
#> $ location <chr> "Albany", "Atlanta", "Baltimore/Washington", "Boise…
#> $ region <chr> "Northeast", "Southeast", "Midsouth", "West", "Nort…
#> $ avg_price_nonorg <dbl> 1.47, 0.93, 1.47, 0.92, 1.29, 1.43, 1.21, 1.15, 0.6…
#> $ plu4046 <dbl> 4845.77, 224073.54, 54530.42, 27845.16, 4119.90, 12…
#> $ plu4225 <dbl> 117027.41, 118926.37, 408952.26, 9408.92, 371223.34…
#> $ plu4770 <dbl> 200.36, 337.48, 14387.01, 11341.75, 3933.72, 102.52…
#> $ small_nonorg_bag <dbl> 7866.86, 111599.58, 151345.59, 53093.47, 79339.78, …
#> $ large_nonorg_bag <dbl> 7.83, 92628.91, 2542.41, 2793.61, 213.75, 255.65, 1…
#> $ xlarge_nonorg_bag <dbl> 0.00, 0.00, 3.12, 27.20, 0.00, 18.06, 46.67, 5089.3…
#> $ avg_price_org <dbl> 1.87, 1.81, 1.92, 1.05, 2.06, 1.64, 1.70, 1.34, 1.2…
#> $ plu94046 <dbl> 71.65, 956.73, 1420.47, 0.00, 14.80, 8.52, 120.83, …
#> $ plu94225 <dbl> 192.63, 2862.95, 6298.07, 368.63, 2181.53, 320.56, …
#> $ plu94770 <dbl> 0.00, 0.00, 325.44, 0.00, 0.00, 0.00, 489.12, 0.00,…
#> $ small_org_bag <dbl> 1112.42, 5.55, 5857.48, 577.91, 10636.25, 2585.10, …
#> $ large_org_bag <dbl> 0.00, 1517.62, 0.00, 1877.28, 605.64, 511.31, 353.9…
#> $ xlarge_org_bag <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …