knitr::opts_chunk$set(
warning = FALSE, # show warnings during codebook generation
message = FALSE, # show messages during codebook generation
error = TRUE, # do not interrupt codebook generation in case of errors,
# usually better for debugging
echo = TRUE # show R code
)
ggplot2::theme_set(ggplot2::theme_bw())
# set base directory
basedir = "/home/ecco_rais/data/clean/RAIS-homogenized/output/"
# adjust as necessary
startyear = 2003
endyear = 2004
# libraries
library(codebook)
library(rio)
# Start the codebook loop
#for ( year in startyear:endyear) {
year = "2014"
# for CSV
codebook_data <- fread(file.path(basedir, paste0("harmo_", year, ".csv")))
# omit the following lines, if your missing values are already properly labelled
codebook_data <- detect_missing(codebook_data,
only_labelled = TRUE, # only labelled values are autodetected as
# missing
negative_values_are_missing = FALSE, # negative values are missing values
ninety_nine_problems = TRUE, # 99/999 are missing values, if they
# are more than 5 MAD from the median
)
# If you are not using formr, the codebook package needs to guess which items
# form a scale. The following line finds item aggregates with names like this:
# scale = scale_1 + scale_2R + scale_3R
# identifying these aggregates allows the codebook function to
# automatically compute reliabilities.
# However, it will not reverse items automatically.
codebook_data <- detect_scales(codebook_data)
## Warning in detect_scales(codebook_data): cbo items found, but no aggregate
## Warning in detect_scales(codebook_data): cnae items found, but no aggregate
## Warning in detect_scales(codebook_data): active items found, but no aggregate
codebook_data <- as.data.table(codebook_data)
codebook(codebook_data)
## Warning in max(f): no non-missing arguments to max; returning -Inf
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning in grepl("^\\s+$", x): input string 1 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 2 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 3 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 4 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 5 is invalid in this locale
## Warning in max(f): no non-missing arguments to max; returning -Inf
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning in grepl("^\\s+$", x): input string 1 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 2 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 3 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 4 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 5 is invalid in this locale
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning: Couldn't find skimmers for class: integer64; No user-defined `sfl` provided. Falling
## back to `character`.
## Warning in grepl("^\\s+$", x): input string 1 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 2 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 3 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 4 is invalid in this locale
## Warning in grepl("^\\s+$", x): input string 5 is invalid in this locale
Dataset name: codebook_data
The dataset has N=76107279 rows and 49 columns. 0 rows have no missing values on any column.
|
#Variables
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
adm_date | numeric | 0 | 1 | 1e+06 | 5062014 | 3.1e+07 | 8720374 | 8433694 | ▇▂▂▂▁ | NA |
## Error in if (stats::median(table(x)) == 1) {: missing value where TRUE/FALSE needed
## No non-missing values to show.
76107279 missing values.
name | data_type | n_missing | complete_rate | count | label |
---|---|---|---|---|---|
cbo94 | logical | 76107279 | 0 | : | NA |
66204 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
cbo02 | numeric | 66204 | 0.9991301 | 10105 | 514225 | 992225 | 510843.9 | 204853.8 | ▁▃▇▅▁ | NA |
## Error in `ggplot2::geom_histogram()`:
## ! Problem while computing position.
## ℹ Error occurred in the 1st layer.
## Caused by error in `if (...) NULL`:
## ! missing value where TRUE/FALSE needed
0 missing values.
name | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace | label |
---|---|---|---|---|---|---|---|---|---|
cei | character | 0 | 1 | 57343 | 0 | 1 | 21 | 0 | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
cnae20 | numeric | 0 | 1 | 1113 | 49213 | 99008 | 55356.54 | 25602.96 | ▂▂▇▂▆ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
cnae20sub | numeric | 0 | 1 | 111301 | 4921301 | 9900800 | 5535662 | 2560294 | ▂▂▇▂▆ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
cnae95 | numeric | 0 | 1 | 1112 | 55212 | 99007 | 55860.7 | 22284.89 | ▂▂▇▇▂ | NA |
## Error in `ggplot2::geom_histogram()`:
## ! Problem while computing stat.
## ℹ Error occurred in the 1st layer.
## Caused by error in `seq_len()`:
## ! argument must be coercible to non-negative integer
0 missing values.
name | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace | label |
---|---|---|---|---|---|---|---|---|---|
firmID | character | 0 | 1 | 3895042 | 0 | 15 | 21 | 0 | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
cnpj_root | numeric | 0 | 1 | 0 | 1.2e+07 | 1e+08 | 23792433 | 26390537 | ▇▁▁▁▁ | NA |
## Error in `ggplot2::geom_histogram()`:
## ! Problem while computing position.
## ℹ Error occurred in the 1st layer.
## Caused by error in `if (...) NULL`:
## ! missing value where TRUE/FALSE needed
0 missing values.
name | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace | label |
---|---|---|---|---|---|---|---|---|---|
cpf | character | 0 | 1 | 61346291 | 0 | 1 | 21 | 0 | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
dob | numeric | 0 | 1 | 1e+06 | 1.5e+07 | 3.1e+07 | 15662478 | 8782776 | ▇▇▇▇▇ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace | label |
---|---|---|---|---|---|---|---|---|---|
termination_day | character | 0 | 1 | 32 | 0 | 2 | 2 | 0 | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
schooling | numeric | 0 | 1 | 1 | 7 | 11 | 6.552912 | 1.75707 | ▁▂▇▃▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
age | numeric | 0 | 1 | 0 | 33 | 100 | 35.11246 | 11.63437 | ▁▇▃▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
cei_avail | numeric | 0 | 1 | 0 | 0 | 1 | 0.0229845 | 0.1498541 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
pat | numeric | 0 | 1 | 0 | 0 | 1 | 0.2980996 | 0.4574235 | ▇▁▁▁▃ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
disabled | numeric | 0 | 1 | 0 | 0 | 1 | 0.0066148 | 0.081062 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
simples | numeric | 0 | 1 | 0 | 0 | 1 | 0.2404565 | 0.4273607 | ▇▁▁▁▂ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
alvara_ind | numeric | 0 | 1 | 0 | 0 | 1 | 0.0001161 | 0.0107761 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
termination_month | numeric | 0 | 1 | 0 | 0 | 12 | 2.323161 | 3.789632 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
separation_cause | numeric | 0 | 1 | 0 | 0 | 80 | 5.448714 | 8.914253 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
muni | numeric | 0 | 1 | 110001 | 351840 | 530010 | 345262.2 | 87214.21 | ▁▂▇▂▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
nationality | numeric | 0 | 1 | 10 | 10 | 80 | 10.07749 | 1.713616 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
legal_form | numeric | 0 | 1 | 1015 | 2062 | 5037 | 2052.321 | 642.2704 | ▂▇▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace | label |
---|---|---|---|---|---|---|---|---|---|
name | character | 0 | 1 | 44243159 | 0 | 2 | 52 | 0 | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
ctps | numeric | 0 | 1 | 0 | 64709 | 1e+08 | 1291180 | 4029381 | ▇▁▁▁▁ | NA |
## Error in `ggplot2::geom_histogram()`:
## ! Problem while computing stat.
## ℹ Error occurred in the 1st layer.
## Caused by error in `seq_len()`:
## ! argument must be coercible to non-negative integer
0 missing values.
name | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace | label |
---|---|---|---|---|---|---|---|---|---|
pis | character | 0 | 1 | 61492767 | 0 | 13 | 21 | 0 | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
hired_hours | numeric | 0 | 1 | 1 | 44 | 44 | 41.22135 | 6.346977 | ▁▁▁▁▇ | NA |
10264819 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
race_color | numeric | 10264819 | 0.865127 | 1 | 2 | 9 | 4.714975 | 3.006341 | ▇▁▁▁▆ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
sex | numeric | 0 | 1 | 0 | 0 | 1 | 0.4195451 | 0.4934846 | ▇▁▁▁▆ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
establishment_size | numeric | 0 | 1 | 1 | 6 | 10 | 6.307805 | 2.80918 | ▃▅▆▅▇ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
tenure | numeric | 0 | 1 | 0 | 16 | 600 | 45.70281 | 73.93379 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
adm_type | numeric | 0 | 1 | 0 | 0 | 14 | 0.7313827 | 1.044689 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
disability_type | numeric | 0 | 1 | 0 | 0 | 6 | 0.0141634 | 0.2151506 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
firmID_type | numeric | 0 | 1 | 0 | 1 | 1 | 0.9733842 | 0.1609577 | ▁▁▁▁▇ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
wage_type | numeric | 0 | 1 | 1 | 1 | 7 | 1.349411 | 1.160358 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
contract_type | numeric | 0 | 1 | 10 | 10 | 97 | 15.98705 | 14.04444 | ▇▂▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
active1231 | numeric | 0 | 1 | 0 | 1 | 1 | 0.6513373 | 0.476547 | ▅▁▁▁▇ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
earn_dec_mw | numeric | 0 | 1 | 0 | 1.4 | 150 | 2.199391 | 4.124937 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
earn_dec | numeric | 0 | 1 | 0 | 987 | 108600 | 1594.63 | 2987.146 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
mean_earn_mw | numeric | 0 | 1 | 0 | 1.7 | 150 | 2.76563 | 3.912825 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
mean_earn | numeric | 0 | 1 | 0 | 1224 | 108606 | 2008.202 | 2833.175 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
hired_wage | numeric | 0 | 1 | 0 | 1012 | 9600000 | 1544.357 | 6815.664 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
last_wage | numeric | 0 | 1 | 0 | 980 | 9932149 | 1651.664 | 5873.981 | ▇▁▁▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
yr | numeric | 0 | 1 | 2014 | 2014 | 2014 | 2014 | 0 | ▁▁▇▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
termination_year | numeric | 0 | 1 | 2014 | 2014 | 2014 | 2014 | 0 | ▁▁▇▁▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
adm_day | numeric | 0 | 1 | 1 | 5 | 31 | 8.654756 | 8.43445 | ▇▂▂▂▁ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
adm_month | numeric | 0 | 1 | 1 | 6 | 12 | 6.360751 | 3.417452 | ▇▅▅▅▇ | NA |
0 missing values.
name | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | label |
---|---|---|---|---|---|---|---|---|---|---|
adm_year | numeric | 0 | 1 | 1938 | 2013 | 2014 | 2010.546 | 6.092831 | ▁▁▁▁▇ | NA |
The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.
{
"name": "codebook_data",
"datePublished": "2024-06-03",
"description": "The dataset has N=76107279 rows and 49 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n|name |label | n_missing|\n|:------------------|:-----|---------:|\n|adm_date |NA | 0|\n|cbo94 |NA | 76107279|\n|cbo02 |NA | 66204|\n|cei |NA | 0|\n|cnae20 |NA | 0|\n|cnae20sub |NA | 0|\n|cnae95 |NA | 0|\n|firmID |NA | 0|\n|cnpj_root |NA | 0|\n|cpf |NA | 0|\n|dob |NA | 0|\n|termination_day |NA | 0|\n|schooling |NA | 0|\n|age |NA | 0|\n|cei_avail |NA | 0|\n|pat |NA | 0|\n|disabled |NA | 0|\n|simples |NA | 0|\n|alvara_ind |NA | 0|\n|termination_month |NA | 0|\n|separation_cause |NA | 0|\n|muni |NA | 0|\n|nationality |NA | 0|\n|legal_form |NA | 0|\n|name |NA | 0|\n|ctps |NA | 0|\n|pis |NA | 0|\n|hired_hours |NA | 0|\n|race_color |NA | 10264819|\n|sex |NA | 0|\n|establishment_size |NA | 0|\n|tenure |NA | 0|\n|adm_type |NA | 0|\n|disability_type |NA | 0|\n|firmID_type |NA | 0|\n|wage_type |NA | 0|\n|contract_type |NA | 0|\n|active1231 |NA | 0|\n|earn_dec_mw |NA | 0|\n|earn_dec |NA | 0|\n|mean_earn_mw |NA | 0|\n|mean_earn |NA | 0|\n|hired_wage |NA | 0|\n|last_wage |NA | 0|\n|yr |NA | 0|\n|termination_year |NA | 0|\n|adm_day |NA | 0|\n|adm_month |NA | 0|\n|adm_year |NA | 0|\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.2).",
"keywords": ["adm_date", "cbo94", "cbo02", "cei", "cnae20", "cnae20sub", "cnae95", "firmID", "cnpj_root", "cpf", "dob", "termination_day", "schooling", "age", "cei_avail", "pat", "disabled", "simples", "alvara_ind", "termination_month", "separation_cause", "muni", "nationality", "legal_form", "name", "ctps", "pis", "hired_hours", "race_color", "sex", "establishment_size", "tenure", "adm_type", "disability_type", "firmID_type", "wage_type", "contract_type", "active1231", "earn_dec_mw", "earn_dec", "mean_earn_mw", "mean_earn", "hired_wage", "last_wage", "yr", "termination_year", "adm_day", "adm_month", "adm_year"],
"@context": "http://schema.org/",
"@type": "Dataset",
"variableMeasured": [
{
"name": "adm_date",
"@type": "propertyValue"
},
{
"name": "cbo94",
"@type": "propertyValue"
},
{
"name": "cbo02",
"@type": "propertyValue"
},
{
"name": "cei",
"@type": "propertyValue"
},
{
"name": "cnae20",
"@type": "propertyValue"
},
{
"name": "cnae20sub",
"@type": "propertyValue"
},
{
"name": "cnae95",
"@type": "propertyValue"
},
{
"name": "firmID",
"@type": "propertyValue"
},
{
"name": "cnpj_root",
"@type": "propertyValue"
},
{
"name": "cpf",
"@type": "propertyValue"
},
{
"name": "dob",
"@type": "propertyValue"
},
{
"name": "termination_day",
"@type": "propertyValue"
},
{
"name": "schooling",
"@type": "propertyValue"
},
{
"name": "age",
"@type": "propertyValue"
},
{
"name": "cei_avail",
"@type": "propertyValue"
},
{
"name": "pat",
"@type": "propertyValue"
},
{
"name": "disabled",
"@type": "propertyValue"
},
{
"name": "simples",
"@type": "propertyValue"
},
{
"name": "alvara_ind",
"@type": "propertyValue"
},
{
"name": "termination_month",
"@type": "propertyValue"
},
{
"name": "separation_cause",
"@type": "propertyValue"
},
{
"name": "muni",
"@type": "propertyValue"
},
{
"name": "nationality",
"@type": "propertyValue"
},
{
"name": "legal_form",
"@type": "propertyValue"
},
{
"name": "name",
"@type": "propertyValue"
},
{
"name": "ctps",
"@type": "propertyValue"
},
{
"name": "pis",
"@type": "propertyValue"
},
{
"name": "hired_hours",
"@type": "propertyValue"
},
{
"name": "race_color",
"@type": "propertyValue"
},
{
"name": "sex",
"@type": "propertyValue"
},
{
"name": "establishment_size",
"@type": "propertyValue"
},
{
"name": "tenure",
"@type": "propertyValue"
},
{
"name": "adm_type",
"@type": "propertyValue"
},
{
"name": "disability_type",
"@type": "propertyValue"
},
{
"name": "firmID_type",
"@type": "propertyValue"
},
{
"name": "wage_type",
"@type": "propertyValue"
},
{
"name": "contract_type",
"@type": "propertyValue"
},
{
"name": "active1231",
"@type": "propertyValue"
},
{
"name": "earn_dec_mw",
"@type": "propertyValue"
},
{
"name": "earn_dec",
"@type": "propertyValue"
},
{
"name": "mean_earn_mw",
"@type": "propertyValue"
},
{
"name": "mean_earn",
"@type": "propertyValue"
},
{
"name": "hired_wage",
"@type": "propertyValue"
},
{
"name": "last_wage",
"@type": "propertyValue"
},
{
"name": "yr",
"@type": "propertyValue"
},
{
"name": "termination_year",
"@type": "propertyValue"
},
{
"name": "adm_day",
"@type": "propertyValue"
},
{
"name": "adm_month",
"@type": "propertyValue"
},
{
"name": "adm_year",
"@type": "propertyValue"
}
]
}`
# } # end year loop