Prepare datasets for trip rate calculations
Usage
hts_prep_triprate(
summarize_by = NULL,
variables_dt = variable_list,
trip_name = "trip",
day_name = "day",
ids = c("hh_id", "person_id", "day_id", "trip_id", "vehicle_id"),
wts = c("hh_weight", "person_weight", "day_weight", "trip_weight", "hh_weight"),
remove_outliers = FALSE,
threshold = 0.975,
weighted = TRUE,
hts_data = list(hh = hh, person = person, day = day, trip = trip, vehicle = vehicle)
)Arguments
- summarize_by
Name of the variable to summarize trip rates by. Default is NULL.
- variables_dt
List of variable locations and descriptions in data.table format.
- trip_name
Name of the trip dataset in hts_data.
- day_name
Name of the day dataset in hts_data.
- ids
name of unique identifier in each table in hts_data
- wts
name of weight column in each table in hts_data
- remove_outliers
Boolean whether or not to remove outliers from dataset. Default is TRUE.
- threshold
Threshold to define outliers. Default is 0.975.
- weighted
Whether the data is weighted. Default is TRUE.
- hts_data
List containing household, person, day, trip, and vehicle datasets in data.table format.
Value
List of binned number of trips with key columns and summarize by variable, unbinned number of trips with key columns and summarize by variable, and a breakdown of outliers if removed.
Examples
require(data.table)
require(stringr)
hts_prep_triprate(
variables_dt = variable_list,
trip_name = "trip",
day_name = "day",
hts_data = list(
"hh" = hh,
"person" = person,
"day" = day,
"trip" = trip,
"vehicle" = vehicle
)
)
#> $num
#> day_id person_id hh_id day_weight num_trips_wtd
#> 1: 1 820 642 583 4.1509434
#> 2: 2 24 24 220 3.5090909
#> 3: 3 1866 888 73 9.2465753
#> 4: 4 1915 875 63 30.0793651
#> 5: 5 415 976 139 13.2805755
#> ---
#> 4121: 4121 1321 595 755 0.6556291
#> 4122: 4122 1619 47 996 2.8945783
#> 4123: 4123 886 474 818 3.8581907
#> 4124: 4124 964 764 460 2.9608696
#> 4125: 4125 1684 876 762 5.1679790
#>
#> $cat
#> day_id person_id hh_id day_weight num_trips_wtd
#> 1: 1 820 642 583 0-13
#> 2: 2 24 24 220 0-13
#> 3: 3 1866 888 73 0-13
#> 4: 4 1915 875 63 26-39
#> 5: 5 415 976 139 13-26
#> ---
#> 4121: 4121 1321 595 755 0-13
#> 4122: 4122 1619 47 996 0-13
#> 4123: 4123 886 474 818 0-13
#> 4124: 4124 964 764 460 0-13
#> 4125: 4125 1684 876 762 0-13
#>
hts_prep_triprate(
summarize_by = "age",
variables_dt = variable_list,
trip_name = "trip",
day_name = "day",
hts_data = list(
"hh" = hh,
"person" = person,
"day" = day,
"trip" = trip,
"vehicle" = vehicle
)
)
#> $num
#> hh_id person_id day_id day_weight person_weight age trip_count_wtd
#> 1: 2 425 388 613 130 12 1284
#> 2: 2 425 1320 593 130 12 233
#> 3: 2 892 1559 983 715 3 2326
#> 4: 2 973 1178 556 57 5 2293
#> 5: 2 973 3183 518 57 5 2406
#> ---
#> 4121: 999 1305 3055 463 836 10 2337
#> 4122: 1000 352 1165 245 883 10 1633
#> 4123: 1000 352 1222 10 883 10 1254
#> 4124: 1000 352 1663 751 883 10 1141
#> 4125: 1000 352 3389 969 883 10 1760
#> num_trips_wtd
#> 1: 2.0946166
#> 2: 0.3929174
#> 3: 2.3662258
#> 4: 4.1241007
#> 5: 4.6447876
#> ---
#> 4121: 5.0475162
#> 4122: 6.6653061
#> 4123: 125.4000000
#> 4124: 1.5193076
#> 4125: 1.8163055
#>
#> $cat
#> hh_id person_id day_id day_weight person_weight age trip_count_wtd
#> 1: 2 425 388 613 130 12 1284
#> 2: 2 425 1320 593 130 12 233
#> 3: 2 892 1559 983 715 3 2326
#> 4: 2 973 1178 556 57 5 2293
#> 5: 2 973 3183 518 57 5 2406
#> ---
#> 4121: 999 1305 3055 463 836 10 2337
#> 4122: 1000 352 1165 245 883 10 1633
#> 4123: 1000 352 1222 10 883 10 1254
#> 4124: 1000 352 1663 751 883 10 1141
#> 4125: 1000 352 3389 969 883 10 1760
#> num_trips_wtd
#> 1: 0-13
#> 2: 0-13
#> 3: 0-13
#> 4: 0-13
#> 5: 0-13
#> ---
#> 4121: 0-13
#> 4122: 0-13
#> 4123: 67 or more
#> 4124: 0-13
#> 4125: 0-13
#>