Check on key when create cubble from two components (spatial/temporal)

When creating a cubble from separate spatial and temporal component, make_cubble() will informed users about potential disagreement of the key values in the two datasets (some sites appear in one table but not the other). This function summarises the key values into those match, potentially can be matched, and can't be matched.

Usage

check_key(spatial, temporal, by = NULL)

Arguments

spatial: a tibble object or an sf object, the spatial component containing the key and coords variable (coords can be automatically created from an sf object if not supplied).
temporal: a tibble object or a tsibble object, the temporal component containing the key and index variable.
by: in the syntax of the by argument in dplyr::left_join(), used in make_cubble() when the key variable has different names in the spatial and temporal data.

Value

a list with three elements: 1) paired: a tibble of paired ID from spatial and temporal data, 2) potential_pairs: a tibble of pairs that could potentially match from both datasets, 3) others: other key values that can't be matched in a list: others$temporal and others$spatial

Examples

check_key(stations, meteo)
#> $paired
#> # A tibble: 3 × 2
#>   spatial     temporal   
#>   <chr>       <chr>      
#> 1 ASN00086038 ASN00086038
#> 2 ASN00086077 ASN00086077
#> 3 ASN00086282 ASN00086282
#> 
#> $potential_pairs
#> # A tibble: 0 × 0
#> 
#> $others
#> $others$temporal
#> character(0)
#> 
#> $others$spatial
#> character(0)
#> 
#> 
#> attr(,"class")
#> [1] "key_tbl" "list"   

# make_cubble() will prompt to use check_key if there are key mis-match:
colnames(lga) <- c("lga", "geometry")
cb <- make_cubble(spatial = lga, temporal = covid)
#> Warning: st_centroid assumes attributes are constant over geometries
#> ! Some sites in the spatial table don't have temporal information
#> ! Some sites in the temporal table don't have spatial information
#> ! Use `check_key()` to check on the unmatched key
#> The cubble is created only with sites having both spatial and
#> temporal information
(check_res <- check_key(lga, covid))
#> $paired
#> # A tibble: 78 × 2
#>    spatial        temporal      
#>    <chr>          <chr>         
#>  1 Alpine (S)     Alpine (S)    
#>  2 Ararat (RC)    Ararat (RC)   
#>  3 Ballarat (C)   Ballarat (C)  
#>  4 Banyule (C)    Banyule (C)   
#>  5 Bass Coast (S) Bass Coast (S)
#>  6 Baw Baw (S)    Baw Baw (S)   
#>  7 Bayside (C)    Bayside (C)   
#>  8 Benalla (RC)   Benalla (RC)  
#>  9 Boroondara (C) Boroondara (C)
#> 10 Brimbank (C)   Brimbank (C)  
#> # ℹ 68 more rows
#> 
#> $potential_pairs
#> # A tibble: 2 × 2
#>   spatial             temporal    
#>   <chr>               <chr>       
#> 1 Kingston (C) (Vic.) Kingston (C)
#> 2 Latrobe (C) (Vic.)  Latrobe (C) 
#> 
#> $others
#> $others$spatial
#> character(0)
#> 
#> $others$temporal
#> [1] "Interstate" "Overseas"   "Unknown"   
#> 
#> 
#> attr(,"class")
#> [1] "key_tbl" "list"   
make_cubble(spatial = lga, temporal = covid, potential_match = check_res)
#> Warning: st_centroid assumes attributes are constant over geometries
#> ! Some sites in the temporal table don't have spatial information
#> ! Use `check_key()` to check on the unmatched key
#> The cubble is created only with sites having both spatial and
#> temporal information
#> # cubble:   key: lga [80], index: date, nested form, [sf]
#> # spatial:  [140.96, -39.13, 149.98, -34], WGS 84
#> # temporal: date [date], n [dbl], avg_7day [dbl]
#>    lga             long   lat                                  geometry ts      
#>    <chr>          <dbl> <dbl>                            <GEOMETRY [°]> <list>  
#>  1 Alpine (S)      147. -36.9 POLYGON ((146.7258 -36.45922, 146.7198 -… <tbl_ts>
#>  2 Ararat (RC)     143. -37.5 POLYGON ((143.1807 -37.73152, 143.0609 -… <tbl_ts>
#>  3 Ballarat (C)    144. -37.5 POLYGON ((143.6622 -37.57241, 143.68 -37… <tbl_ts>
#>  4 Banyule (C)     145. -37.7 POLYGON ((145.1357 -37.74091, 145.1437 -… <tbl_ts>
#>  5 Bass Coast (S)  146. -38.5 MULTIPOLYGON (((145.5207 -38.30667, 145.… <tbl_ts>
#>  6 Baw Baw (S)     146. -38.0 POLYGON ((145.765 -37.89858, 145.7414 -3… <tbl_ts>
#>  7 Bayside (C)     145. -37.9 POLYGON ((144.985 -37.891, 144.9855 -37.… <tbl_ts>
#>  8 Benalla (RC)    146. -36.6 POLYGON ((146.1314 -36.25512, 146.0369 -… <tbl_ts>
#>  9 Boroondara (C)  145. -37.8 POLYGON ((145.1067 -37.79216, 145.0953 -… <tbl_ts>
#> 10 Brimbank (C)    145. -37.7 POLYGON ((144.8862 -37.70775, 144.8594 -… <tbl_ts>
#> # ℹ 70 more rows