census

The 2015 census data come from the Lao Statistics Bureau.

The census is based on this questionaire and its data are in 3 files in the raw_data/census folder of the DropBox Ecomore2 folder:

Villages data from PHC2015 01 province.xlsx with village identifiers and names in Lao and English, and 11 variables for 480 villages;
Households data from PHC2015_Household_Record.sav with 168,949 households and 33 questions;
Individuals data from PHC2015_Person_Record_Province1.sav with 820,940 individuals and 61 questions.

The cleaning pipeline summarises these 3 data sets per village and merge them into a data frame of 485 villages and 260 variables available in a CSV file that can be copied and pasted from the data/census.csv CSV file or can be downloaded directly from R as:

> if (! "readr" %in% rownames(installed.packages())) install.packages("readr")
> pacs <- readr::read_csv("https://raw.githubusercontent.com/ecomore2/census/master/data/census.csv",
+                         col_types = paste(c("ddccciiiiilllc", rep("d", 246)), collapse = ""))

Below is a description of the variables. The proportions and percentages variables in the household-based and individual-bases statistics are computed from categorical variables in the original census data and then averaged over villages. Quantitative variables in the original census data are averaged over villages.

Unique key:
- District_ID
- Village_ID
Village statistics
- District_Name: character string
- Village_Name: character string
- village_type: “Urban”, “Rural with road”, “Rural without road”
- private_household: number
- collective_household: number
- male: number
- female: number
- total_pop: number
- water_supply: boolean
- market: boolean
- health_center: boolean
- primaryschool: “Complete”, “Incomplete”, “No School”
Household-based statistics:
- Household_type: collective_households, private_households: percentages
- Q49._Tenure_status_of_household: Employer.provided, Owner, Rent, Rentfree: percentages
- Q50._Roof_of_building: Bamboo_roof, Grass, Tile.sipax.concrete, Wood_roof, Zinc: percentages
- Q51._Walls_of_building: Bamboo_wall, Brick.concrete, Wood_wall: percentages
- Q52._Floor_of_building: Bamboo_floor, Ceramic.tile, Concrete, Wood_floor: percentages
- Q53._Have_electicity: No.electricity, Own.generator, Publicly.distributed...own.meter, Publicly.distributed...shared.meter, Using.batteries: percentages
- Q56._Main_drinking_water_source: Bottled.or.canned.water, Mountain.source, Piped.water, Rain.water, River.stream.dam, Tank, Well.borehole.protected, Well.borehole.unprotected: percentages
- Q57._Distance_of_water_source: Less.than.200.meters, On.premises, X1000.meters.or.more, X200.to.499.meters, X500.to.999.meters: percentages
- Q58._Type_of_toilet: Bucket, Composting.toilet, Flush.pour.flush, Hang.toilet.hang.latrine, Pit.latrine.other, Pit.latrine.ventilated: percentages
- Q59._Energy_for_cooking: Charcoal, Coal, Electricity, Gas, Paraffin.fuel, Sawdust, Wood_cooking: percentages
- Q36._Death_last_12_month: proportion
- Q40._Moved_in_HH: proportion
- Q44._Moved_out_of_household: proportion
- Q54._Area_occupied: mean over villages
- Q55._Number_of_room: mean over villages
- Q60.1._Tractor: proportion of households own
- Q60.2._Car/van: proportion of households own
- Q60.3._MotorBike: proportion of households own
- Q60.4._Bicycle: proportion of households own
- Q60.5._Boat: proportion of households own
- Q60.6._Radio: proportion of households own
- Q60.7._Television: proportion of households own
- Q60.8._Fixed_phone: proportion of households own
- Q60.9._Cell_phone: proportion of households own
- Q60.10._Computer: proportion of households own
- Q60.11._Washing_machine: proportion of households own
- Q60.12._Air_conditioner: proportion of households own
- Q60.13._Fan: proportion of households own
- Q60.14._Fridge/freezer: proportion of households own
- Q60.15._Agriculture_land: proportion of households own
- Q61._Males: mean over households
- Q62._Females: mean over households
- Q63_Total_persons: mean over households
- area_per_person: computed from Q54._Area_occupied and Q63_Total_persons and then averaged over villages
- rooms_per_person: computed from Q55._Number_of_room and Q63_Total_persons and then averaged over villages
Person-based statistics:
- Household_type: collective_persons, private_persons: percentages
- Q4._Sex: Female, Male: percentages
- Q5._Age: a0, …, a99: percentages
- Q6._Marital_Status: Divorced.separated, Married, Never.married, Stay.together, Widowed: percentages
- Q10A._Born_this_district: Other.district.or.abroad, Same.district: percentages
- Q18._Can_read_and_write: Not.at.all, Yes..Lao, Yes..other: percentages
- Q19._Attended_school: Attended.before, Attending, Never: percentages
- Q20._Highest_education: No.grade, Grade.1, Grade.2, Grade.3, Grade.4, Grade.5, Grade.6, Lower.secondary.1, Lower.secondary.2, Lower.secondary.3, Lower.secondary.4, Upper.secondary.1, Upper.secondary.2, Upper.secondary.3, Vocation.education.first.level, Vocation.education.middle.level, Vocation.education.high.level, Graduate.degree.holder, Post.graduate.masters.degree, Higher.than.post.graduate: percentages
- Q21._Main_subject_of_study: Agriculture, forestry.and.fishing, Architecture.and.building, Arts, Business.and.administration, Computer, Engineering.and.trade, Environmental.protection, Health, Humanities, Journalism.and.information, Law, Life.science, Manufacturing.and.processing, Mathematics.and.statistics, Personal.services, Physical.science, Security.services, Social.science, Social.services, Teacher.training.and.education.science, Transportation.services, Veterinary: percentages
- Q22A._Place_living_2005: Other.District.or.abroad, Same.District: percentages
- Q24._Main_activity_12_month: Employer, Government.employee, Household.duties, International.or.NGO, Own.account.worker, Private.employee, State.enterprise.employee, Student, Unemployed, Unpaid.family.worker: percentages
- Q32M_Age_first_birth: number

Note that some variables are thus available in different versions depending on whether they have been averaged from individual or household data. This is the case for the 4 variables listed below:

household-based	person-based
`Q61._Males`	`Male`
`Q62._Females`	`Female`
`collective_households`	`collective_persons`
`private_households`	`private_persons`