fixtures.md
In epidatr: Client for Delphi's 'Epidata' API

fixture parses: classic-covidcast.json

Code
  print(vapply(result, function(col) paste(class(col), collapse = "/"), character(
    1)))
Output
            geo_value              signal              source            geo_type 
          "character"         "character"         "character"            "factor" 
            time_type          time_value           direction               issue 
             "factor"              "Date"           "numeric"              "Date" 
                  lag       missing_value      missing_stderr missing_sample_size 
            "numeric"           "numeric"           "numeric"           "numeric" 
                value              stderr         sample_size 
            "numeric"           "numeric"           "numeric" 
Code
  print(head(as.data.frame(result), 3))
Output
    geo_value                        signal   source geo_type time_type
  1        ca confirmed_7dav_incidence_prop jhu-csse    state       day
  2        ca confirmed_7dav_incidence_prop jhu-csse    state       day
  3        ca confirmed_7dav_incidence_prop jhu-csse    state       day
    time_value direction      issue  lag missing_value missing_stderr
  1 2020-06-01        NA 2023-03-10 1012             0              5
  2 2020-06-02        NA 2023-03-10 1011             0              5
  3 2020-06-03        NA 2023-03-10 1010             0              5
    missing_sample_size    value stderr sample_size
  1                   5 6.843108     NA          NA
  2                   5 6.825690     NA          NA
  3                   5 6.664936     NA          NA

fixture parses: classic-fluview.json

Code
  print(vapply(result, function(col) paste(class(col), collapse = "/"), character(
    1)))
Output
   release_date        region         issue       epiweek           lag 
         "Date"   "character"        "Date"        "Date"     "numeric" 
        num_ili  num_patients num_providers     num_age_0     num_age_1 
      "numeric"     "numeric"     "numeric"     "numeric"     "numeric" 
      num_age_2     num_age_3     num_age_4     num_age_5          wili 
      "numeric"     "numeric"     "numeric"     "numeric"     "numeric" 
            ili 
      "numeric" 
Code
  print(head(as.data.frame(result), 3))
Output
    release_date region      issue    epiweek lag num_ili num_patients
  1   2021-10-08    nat 2021-09-26 2019-12-29  91   88731      1426691
  2   2021-10-08    nat 2021-09-26 2020-01-05  90   75614      1492251
  3   2021-10-08    nat 2021-09-26 2020-01-12  89   79783      1489132
    num_providers num_age_0 num_age_1 num_age_2 num_age_3 num_age_4 num_age_5
  1          2970     21594     23392        NA     27655      9209      6881
  2          3002     15564     22756        NA     23634      8196      5464
  3          2995     16587     29668        NA     21413      7386      4729
       wili     ili
  1 5.90066 6.21936
  2 4.94020 5.06711
  3 5.33135 5.35768

fixture parses: classic-delphi.json

Code
  str(result, max.level = 3)
Output
  List of 1
   $ :List of 3
    ..$ epiweek : int 201501
    ..$ forecast:List of 10
    .. ..$ _version    : int 1
    .. ..$ baselines   :List of 11
    .. ..$ data        :List of 11
    .. ..$ epiweek     : int 201501
    .. ..$ ili_bin_size: int 1
    .. ..$ ili_bins    : int 11
    .. ..$ name        : chr "DELPHI-Epicast-(Carnegie-Mellon-University)"
    .. ..$ season      : int 2014
    .. ..$ season_weeks: int 34
    .. ..$ year_weeks  : int 53
    ..$ system  : chr "ec"

fixture parses: cast-snapshot.csv

Code
  print(vapply(result, function(col) paste(class(col), collapse = "/"), character(
    1)))
Output
            signal      report_time         geo_type        geo_value 
       "character" "POSIXct/POSIXt"      "character"      "character" 
       fill_method   reference_time            value 
       "character"           "Date"        "numeric" 
Code
  print(head(as.data.frame(result), 3))
Output
                     signal report_time geo_type geo_value fill_method
  1 pct_ed_visits_influenza  2024-12-27   nation        us      source
  2 pct_ed_visits_influenza  2024-12-27   nation        us      source
  3 pct_ed_visits_influenza  2024-12-27   nation        us      source
    reference_time value
  1     2022-10-01  0.48
  2     2022-10-08  0.67
  3     2022-10-15  0.90

fixture parses: cast-archive.csv

Code
  print(vapply(result, function(col) paste(class(col), collapse = "/"), character(
    1)))
Output
            signal      report_time         geo_type        geo_value 
       "character" "POSIXct/POSIXt"      "character"      "character" 
       fill_method   reference_time            value 
       "character"           "Date"        "numeric" 
Code
  print(head(as.data.frame(result), 3))
Output
                     signal report_time geo_type geo_value fill_method
  1 pct_ed_visits_influenza  2024-12-27   nation        us      source
  2 pct_ed_visits_influenza  2024-12-27   nation        us      source
  3 pct_ed_visits_influenza  2024-12-27   nation        us      source
    reference_time value
  1     2022-10-01  0.48
  2     2022-10-08  0.67
  3     2022-10-15  0.90

fixture parses: cast-meta.json

Code
  str(result, max.level = 3)
Output
  List of 8
   $ report_time_range   :List of 2
    ..$ latest: chr "2026-08-19T00:00:00Z"
    ..$ first : chr "2024-04-18T00:00:00Z"
   $ reference_time_range:List of 2
    ..$ latest: chr "2026-08-15"
    ..$ first : chr "2022-10-01"
   $ signals             : chr [1:9] "pct_ed_visits_ari" "pct_ed_visits_combined" "pct_ed_visits_covid" "pct_ed_visits_influenza" ...
   $ geo_types           : chr [1:9] "census_division" "census_region" "county" "hhs" ...
   $ key_columns         : chr [1:6] "signal" "report_time" "geo_type" "geo_value" ...
   $ extra_key_columns   : list()
   $ value_columns       : chr "value"
   $ column_types        :List of 7
    ..$ report_time   : chr "timestamp without time zone"
    ..$ signal        : chr "text"
    ..$ geo_type      : chr "text"
    ..$ geo_value     : chr "text"
    ..$ fill_method   : chr "text"
    ..$ reference_time: chr "date"
    ..$ value         : chr "double precision"

fixture parses: aux-data.csv

Code
  print(vapply(result, function(col) paste(class(col), collapse = "/"), character(
    1)))
Output
            report_time             geo_value        reference_time 
       "POSIXct/POSIXt"           "character"                "Date" 
            nwss_source          sample_index            pcr_target 
            "character"           "character"           "character" 
  report_ts_nominal_end       state_territory           county_fips 
            "character"           "character"           "character" 
        counties_served     population_served           sample_type 
            "character"           "character"           "character" 
          sample_matrix       sample_location             flow_rate 
            "character"           "character"           "character" 
   concentration_method           pasteurized              pcr_type 
            "character"           "character"           "character" 
      extraction_method      major_lab_method     inhibition_detect 
            "character"           "character"           "character" 
      inhibition_adjust           ntc_amplify   pcr_gene_target_agg 
            "character"           "character"           "character" 
       pcr_target_units            lod_sewage   hum_frac_target_mic 
            "character"           "character"           "character" 
      hum_frac_mic_conc     hum_frac_mic_unit       rec_eff_percent 
            "character"           "character"           "character" 
    rec_eff_target_name  rec_eff_spike_matrix    rec_eff_spike_conc 
            "character"           "character"           "character" 
        pipeline_run_id      report_ts_actual              comments 
            "character"           "character"           "character" 
Code
  print(head(as.data.frame(result), 3))
Output
    report_time geo_value reference_time nwss_source sample_index pcr_target
  1  2026-06-26        10     2022-12-13  CDC_Biobot      5639533        nvo
  2  2026-06-19        10     2022-12-13  CDC_Biobot      5639533        nvo
  3  2026-06-12        10     2022-12-13  CDC_Biobot      5639533        nvo
    report_ts_nominal_end state_territory county_fips counties_served
  1                  <NA>              al       01095        Marshall
  2   2026-06-26 00:00:00              al       01095        Marshall
  3   2026-06-19 00:00:00              al       01095        Marshall
    population_served                   sample_type  sample_matrix
  1              9000 24-hr time-weighted composite raw wastewater
  2              9000 24-hr time-weighted composite raw wastewater
  3              9000 24-hr time-weighted composite raw wastewater
    sample_location flow_rate concentration_method pasteurized pcr_type
  1            wwtp      4.14       ceres nanotrap           t     qpcr
  2            wwtp      4.14       ceres nanotrap           t     qpcr
  3            wwtp      4.14       ceres nanotrap           t     qpcr
                                            extraction_method major_lab_method
  1 thermo magmax microbiome ultra nucleic acid isolation kit                4
  2 thermo magmax microbiome ultra nucleic acid isolation kit                4
  3 thermo magmax microbiome ultra nucleic acid isolation kit                4
    inhibition_detect inhibition_adjust ntc_amplify pcr_gene_target_agg
  1                 f                 f           f            e9l-nvar
  2                 f                 f           f            e9l-nvar
  3                 f                 f           f            e9l-nvar
       pcr_target_units lod_sewage      hum_frac_target_mic hum_frac_mic_conc
  1 copies/l wastewater       1150 pepper mild mottle virus    17722821.72669
  2 copies/l wastewater       1150 pepper mild mottle virus    17722821.72669
  3 copies/l wastewater       1150 pepper mild mottle virus    17722821.72669
      hum_frac_mic_unit rec_eff_percent rec_eff_target_name
  1 copies/l wastewater        49.83329        brsv vaccine
  2 copies/l wastewater        49.83329        brsv vaccine
  3 copies/l wastewater        49.83329        brsv vaccine
              rec_eff_spike_matrix rec_eff_spike_conc pipeline_run_id
  1 raw sample post pasteurization            5.08798            7961
  2 raw sample post pasteurization            5.08798            7904
  3 raw sample post pasteurization            5.08798            7886
       report_ts_actual comments
  1 2026-06-26 21:12:39     <NA>
  2 2026-06-26 21:03:00     <NA>
  3 2026-06-26 21:01:20     <NA>