A fictional consumer-feedback survey from a Boonta Eve-style pod-racing
meeting – an affectionate Star Wars parody used throughout the ezrsurvey
examples and tests (the package's literal answer to starwars, but
survey-shaped). A latent enjoyment drives correlated attribute ratings and the
recommend score, the demographics use international-standard categories
(ISO/IEC 5218 sex, ISCED education, ILO labour-force status, ISIC sectors,
ISO 3166 countries), and the multi-select, sponsor and open-text columns mirror
the shapes the helpers consume. The open-text comments deliberately name many
drivers, places and races, so they exercise the text / NER helpers. Blanks and
"Prefer not to answer" responses are sprinkled in so cleaning helpers have
something to do.
Format
A tibble with 1,000 rows and 32 columns:
- respondent_id
Unique respondent id (character).
- collector
Survey source: email, panel, socials or in_app.
- demo_age
Age in years (integer, 16-70).
- demo_gender
Sex/gender: Male, Female, Non-binary (ISO/IEC 5218, extended), some blank / "Prefer not to answer".
- demo_edu
Highest education level (ISCED 2011 broad categories).
- demo_country
Country of residence (ISO 3166 names).
- region
World region derived from
demo_country.- demo_job
Labour-force status (ILO categories).
- demo_sector
Industry sector (ISIC Rev.4 sections).
- race_attended
Which meeting they attended (e.g. "Boonta Eve Classic"); long labels that exercise the auto bar layout.
- fav_driver
Favourite pod-racer (e.g. "Anakin Skywalker", "Sebulba").
- nps_value
0-10 "how likely to recommend attending" rating (integer).
- satis_return
Likelihood of returning next season (Very unlikely .. Very likely).
- ratings_atmosphere, ratings_commentary, ratings_safety, ratings_speed, ratings_value, ratings_venue
Worded 1-5 attribute ratings (Very bad .. Very good).
- motivations_speed, motivations_drivers, motivations_betting, motivations_social, motivations_tradition
Multi-select reasons for attending; each holds its option text when chosen, otherwise
"".- partner_recall_PodTech, partner_recall_BanthaBrew, partner_recall_JawaJuice
Sponsor recall per brand (Sponsor / Not a sponsor / Don't know this brand).
- partner_likeability_PodTech, partner_likeability_BanthaBrew, partner_likeability_JawaJuice
Sponsor likeability (Very likeable .. Very unlikeable).
- nps_com, show_com
Open-text comments (mostly blank).
See also
Other data:
country_region,
currency_rates,
shopping_survey
Examples
calc_percentage(podracing_survey, demo_gender, sort = "desc")
#> # A tibble: 3 × 3
#> demo_gender n pct
#> <fct> <int> <dbl>
#> 1 Male 525 55
#> 2 Female 399 42
#> 3 Non-binary 27 3
calc_nps(podracing_survey, nps_value)
#> # A tibble: 1 × 8
#> n nps pct_detractors pct_passives pct_promoters detractors passives
#> <int> <dbl> <dbl> <dbl> <dbl> <int> <int>
#> 1 1000 7 25 43 32 252 426
#> # ℹ 1 more variable: promoters <int>