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Wrapper for data() and can get memory size of objects

Usage

datapack(pkg = "EJAM", len = 30, sortbysize = TRUE, simple = TRUE)

Arguments

pkg

a character vector giving the package(s) to look in for data sets

len

Only affects what is printed to console - specifies the number of characters to limit Title to, making it easier to see in the console.

sortbysize

if TRUE (and simple=F), sort by increasing size of object, within each package, not alpha.

simple

FALSE to get object sizes, etc., or TRUE to just get names in each package, like data(package = "EJAM")$results[, c("Package", 'Item')]

Value

If simple = TRUE, data.frame with colnames Package and Item. If simple = FALSE, data.frame with colnames Package, Item, size, Title.Short

Details

do not rely on this much - it was a quick utility. It may create and leave objects in global envt - not careful about that.

Examples

 # see just a vector of the data object names
 data(package = "EJAM")$results[, 'Item']
#>   [1] "NAICS"                                     
#>   [2] "SIC"                                       
#>   [3] "avg.in.us"                                 
#>   [4] "bg_cenpop2020"                             
#>   [5] "bgpts"                                     
#>   [6] "blockgroupstats"                           
#>   [7] "censusplaces"                              
#>   [8] "custom"                                    
#>   [9] "default_points_shown_at_startup"           
#>  [10] "ejamdata_version"                          
#>  [11] "ejampackages"                              
#>  [12] "ejscreenRESTbroker2table_na_filler"        
#>  [13] "epa_programs"                              
#>  [14] "epa_programs_defined"                      
#>  [15] "formulas_all"                              
#>  [16] "formulas_d"                                
#>  [17] "frsprogramcodes"                           
#>  [18] "high_pctiles_tied_with_min"                
#>  [19] "islandareas"                               
#>  [20] "lat_alias"                                 
#>  [21] "lon_alias"                                 
#>  [22] "mact_table"                                
#>  [23] "map_headernames"                           
#>  [24] "metadata4pins"                             
#>  [25] "meters_per_mile"                           
#>  [26] "modelDoaggregate"                          
#>  [27] "modelEjamit"                               
#>  [28] "naics_counts"                              
#>  [29] "naicstable"                                
#>  [30] "names_age"                                 
#>  [31] "names_age_count"                           
#>  [32] "names_all"                                 
#>  [33] "names_all_r"                               
#>  [34] "names_climate"                             
#>  [35] "names_climate_avg"                         
#>  [36] "names_climate_pctile"                      
#>  [37] "names_climate_state_avg"                   
#>  [38] "names_climate_state_pctile"                
#>  [39] "names_community"                           
#>  [40] "names_community_count"                     
#>  [41] "names_countabove"                          
#>  [42] "names_criticalservice"                     
#>  [43] "names_criticalservice_avg"                 
#>  [44] "names_criticalservice_pctile"              
#>  [45] "names_criticalservice_state_avg"           
#>  [46] "names_criticalservice_state_pctile"        
#>  [47] "names_d"                                   
#>  [48] "names_d_avg"                               
#>  [49] "names_d_count"                             
#>  [50] "names_d_demogindexstate"                   
#>  [51] "names_d_extra"                             
#>  [52] "names_d_extra_count"                       
#>  [53] "names_d_language"                          
#>  [54] "names_d_language_count"                    
#>  [55] "names_d_languageli"                        
#>  [56] "names_d_languageli_count"                  
#>  [57] "names_d_other_count"                       
#>  [58] "names_d_pctile"                            
#>  [59] "names_d_ratio_to_avg"                      
#>  [60] "names_d_ratio_to_state_avg"                
#>  [61] "names_d_state_avg"                         
#>  [62] "names_d_state_pctile"                      
#>  [63] "names_d_subgroups"                         
#>  [64] "names_d_subgroups_alone"                   
#>  [65] "names_d_subgroups_alone_avg"               
#>  [66] "names_d_subgroups_alone_count"             
#>  [67] "names_d_subgroups_alone_pctile"            
#>  [68] "names_d_subgroups_alone_ratio_to_avg"      
#>  [69] "names_d_subgroups_alone_ratio_to_state_avg"
#>  [70] "names_d_subgroups_alone_state_avg"         
#>  [71] "names_d_subgroups_alone_state_pctile"      
#>  [72] "names_d_subgroups_avg"                     
#>  [73] "names_d_subgroups_count"                   
#>  [74] "names_d_subgroups_nh"                      
#>  [75] "names_d_subgroups_nh_avg"                  
#>  [76] "names_d_subgroups_nh_count"                
#>  [77] "names_d_subgroups_nh_pctile"               
#>  [78] "names_d_subgroups_nh_ratio_to_avg"         
#>  [79] "names_d_subgroups_nh_ratio_to_state_avg"   
#>  [80] "names_d_subgroups_nh_state_avg"            
#>  [81] "names_d_subgroups_nh_state_pctile"         
#>  [82] "names_d_subgroups_pctile"                  
#>  [83] "names_d_subgroups_ratio_to_avg"            
#>  [84] "names_d_subgroups_ratio_to_state_avg"      
#>  [85] "names_d_subgroups_state_avg"               
#>  [86] "names_d_subgroups_state_pctile"            
#>  [87] "names_e"                                   
#>  [88] "names_e_avg"                               
#>  [89] "names_e_other"                             
#>  [90] "names_e_pctile"                            
#>  [91] "names_e_ratio_to_avg"                      
#>  [92] "names_e_ratio_to_state_avg"                
#>  [93] "names_e_state_avg"                         
#>  [94] "names_e_state_pctile"                      
#>  [95] "names_ej"                                  
#>  [96] "names_ej_pctile"                           
#>  [97] "names_ej_state"                            
#>  [98] "names_ej_state_pctile"                     
#>  [99] "names_ej_supp"                             
#> [100] "names_ej_supp_pctile"                      
#> [101] "names_ej_supp_state"                       
#> [102] "names_ej_supp_state_pctile"                
#> [103] "names_featuresinarea"                      
#> [104] "names_flag"                                
#> [105] "names_geo"                                 
#> [106] "names_health"                              
#> [107] "names_health_avg"                          
#> [108] "names_health_count"                        
#> [109] "names_health_pctile"                       
#> [110] "names_health_ratio_to_avg"                 
#> [111] "names_health_ratio_to_state_avg"           
#> [112] "names_health_state_avg"                    
#> [113] "names_health_state_pctile"                 
#> [114] "names_misc"                                
#> [115] "names_pct_as_fraction_blockgroupstats"     
#> [116] "names_pct_as_fraction_ejamit"              
#> [117] "names_pct_as_fraction_ejscreenit"          
#> [118] "names_sitesinarea"                         
#> [119] "names_these"                               
#> [120] "names_these_avg"                           
#> [121] "names_these_ratio_to_avg"                  
#> [122] "names_these_ratio_to_state_avg"            
#> [123] "names_these_state_avg"                     
#> [124] "names_wts"                                 
#> [125] "namez"                                     
#> [126] "sictable"                                  
#> [127] "stateinfo"                                 
#> [128] "stateinfo2"                                
#> [129] "states_shapefile"                          
#> [130] "statestats"                                
#> [131] "testinput_address_2"                       
#> [132] "testinput_address_9"                       
#> [133] "testinput_address_parts"                   
#> [134] "testinput_address_table"                   
#> [135] "testinput_address_table_9"                 
#> [136] "testinput_address_table_goodnames"         
#> [137] "testinput_address_table_withfull"          
#> [138] "testinput_fips_blockgroups"                
#> [139] "testinput_fips_cities"                     
#> [140] "testinput_fips_counties"                   
#> [141] "testinput_fips_states"                     
#> [142] "testinput_fips_tracts"                     
#> [143] "testinput_mact"                            
#> [144] "testinput_naics"                           
#> [145] "testinput_program_name"                    
#> [146] "testinput_program_sys_id"                  
#> [147] "testinput_regid"                           
#> [148] "testinput_registry_id"                     
#> [149] "testinput_shapes_2"                        
#> [150] "testinput_sic"                             
#> [151] "testinput_xtrac"                           
#> [152] "testoutput_doaggregate_1000pts_1miles"     
#> [153] "testoutput_doaggregate_100pts_1miles"      
#> [154] "testoutput_doaggregate_10pts_1miles"       
#> [155] "testoutput_ejamit_1000pts_1miles"          
#> [156] "testoutput_ejamit_100pts_1miles"           
#> [157] "testoutput_ejamit_10pts_1miles"            
#> [158] "testoutput_ejamit_fips_cities"             
#> [159] "testoutput_ejamit_fips_counties"           
#> [160] "testoutput_ejamit_shapes_2"                
#> [161] "testoutput_ejscreenRESTbroker_1pts_1miles" 
#> [162] "testoutput_ejscreenapi_1pts_1miles"        
#> [163] "testoutput_ejscreenapi_plus_5"             
#> [164] "testoutput_ejscreenit_5"                   
#> [165] "testoutput_ejscreenit_50"                  
#> [166] "testoutput_ejscreenit_500"                 
#> [167] "testoutput_getblocksnearby_1000pts_1miles" 
#> [168] "testoutput_getblocksnearby_100pts_1miles"  
#> [169] "testoutput_getblocksnearby_10pts_1miles"   
#> [170] "testpoints_10"                             
#> [171] "testpoints_100"                            
#> [172] "testpoints_1000"                           
#> [173] "testpoints_10000"                          
#> [174] "testpoints_100_dt"                         
#> [175] "testpoints_5"                              
#> [176] "testpoints_50"                             
#> [177] "testpoints_500"                            
#> [178] "testpoints_bad"                            
#> [179] "testpoints_overlap3"                       
#> [180] "testshapes_2"                              
#> [181] "usastats"                                  
#> [182] "x_anyother"                                

 # not actually sorted within each pkg by default
 datapack()
#> Error in datapack(): could not find function "datapack"
 # not actually sorted by default
 datapack("EJAM")$Item
#> Error in datapack("EJAM"): could not find function "datapack"
 ##datapack("MASS", simple=T)

 # sorted by size if simple=F
 ##datapack("datasets", simple=F)
 x <- datapack(simple = F)
#> Error in datapack(simple = F): could not find function "datapack"
 # sorted by size already, to see largest ones among all these pkgs:
 tail(x[, 1:3], 20)
#> Error: object 'x' not found

 # sorted alphabetically within each pkg
 x[order(x$Package, x$Item), 1:2]
#> Error: object 'x' not found
 # sorted alphabetically across all the pkgs
 x[order(x$Item), 1:2]
#> Error: object 'x' not found
 
# datasets as lazyloaded objects vs. files installed with package

topic = "fips"  # or "shape" or "latlon" or "naics" or "address" etc.

# datasets / R objects
cbind(data.in.package  = sort(grep(topic, EJAM:::datapack()$Item, value = T)))
#> Get more info with datapack(simple = FALSE)
#> 
#> ignoring sortbysize because simple=TRUE 
#> 
#>      data.in.package                  
#> [1,] "testinput_fips_blockgroups"     
#> [2,] "testinput_fips_cities"          
#> [3,] "testinput_fips_counties"        
#> [4,] "testinput_fips_states"          
#> [5,] "testinput_fips_tracts"          
#> [6,] "testoutput_ejamit_fips_cities"  
#> [7,] "testoutput_ejamit_fips_counties"

# files
cbind(files.in.package = sort(basename(testdata(topic, quiet = T))))
#>       files.in.package                   
#>  [1,] "cities_2.xlsx"                    
#>  [2,] "counties_in_AL_detailed.xlsx"     
#>  [3,] "counties_in_Alabama.xlsx"         
#>  [4,] "counties_in_Delaware.xlsx"        
#>  [5,] "counties_in_Delaware_invalid.xlsx"
#>  [6,] "county_10.xlsx"                   
#>  [7,] "county_100.xlsx"                  
#>  [8,] "county_1000.xlsx"                 
#>  [9,] "county_state_300.xlsx"            
#> [10,] "fips"                             
#> [11,] "state_10.xlsx"                    
#> [12,] "state_50.xlsx"                    
#> [13,] "state_county_tract_10.xlsx"       
#> [14,] "tract_10.csv"                     
#> [15,] "tract_100.csv"                    
#> [16,] "tract_1000.csv"                   
#> [17,] "tract_state_285.xlsx"