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Loads information about college basketball venues.

Usage

load_venues()

Value

a dataframe of information about college basketball venues.

See also

https://john-b-edwards.github.io/cbbreadr/articles/dictionary_venues.html for a web version of the data dictionary

dictionary_venues for the data dictionary as bundled within the package

Issues with this data should be filed here: https://github.com/john-b-edwards/cbbd-data/issues

Examples

# \donttest{
try({ # avoid cran errors
load_venues()
})
#>      venue_id venue_source_id
#>         <int>          <char>
#>   1:     1237            2292
#>   2:     1258            2566
#>   3:     1621            6289
#>   4:     1500            5287
#>   5:     1501            5288
#>  ---                         
#> 968:      409           10886
#> 969:       94           10887
#> 970:       30           10949
#> 971:      401           10970
#> 972:      410           10971
#>                                              venue_name            venue_city
#>                                                  <char>                <char>
#>   1:                                Cancha Del Atletico               Tucuman
#>   2:                           St. George's High School              Freeport
#>   3:                              CARSA Performance Gym              Victoria
#>   4:                                        Youth Arena        Rio De Janeiro
#>   5:                                    Carioca Arena 1        Rio De Janeiro
#>  ---                                                                         
#> 968:                     Mohegan Sun Arena Wilkes-Barre Wilkes Barre Township
#> 969:                                  John Glaser Arena          Philadelphia
#> 970:                      John Wooden Family Fieldhouse                 Xenia
#> 971: Florida State College at Jacksonville South Campus          Jacksonville
#> 972:                    Sturrus Sports & Fitness Center          Grand Rapids
#>      venue_state venue_country
#>           <char>        <char>
#>   1:        <NA>     Argentina
#>   2:        <NA>          <NA>
#>   3:          BC        Canada
#>   4:        <NA>        Brazil
#>   5:        <NA>        Brazil
#>  ---                          
#> 968:          PA United States
#> 969:          PA United States
#> 970:          OH United States
#> 971:          FL United States
#> 972:          MI United States
# }