portawaterperu: A Preliminary Review of Peruvian Potable Water System Data

Data for this project was obtained from @SIASAR, an information system containing data on rural water supply and sanitation services. Using SIASAR's "download data by country" tool, all available data for Peru (10 excel files) were downloaded. After examining the 10 excel files, only 5 pertained to potable water systems. Those 5 data sets were imported into R and subsequently empty values and unnecessary columns were deleted from them. Finally, the 5 data sets were combined into 1 data frame based on community ID. The combined, cleaned data set contains data from 32 communities.

Usage

portawaterperu

Format

A tibble with 32 rows and 51 variables

name: Name of the community water system
ID: ID of the water system
div: Geographical division of the community
lat: Latitude of the community
long: Longitude of the community
alt: Altitude of the community
year: Year of data collection about communities. (Use in caution)
community: Community name
service_provider: Service provider (PSE stands for Prestador de servicio)
pop_serviced: Population served
hh_serviced: Household served
type_gravity: Is the community served by a gravity water supply system?
type_pump: Is the community served by a pumped water supply system?
type_well: Is the community served by a well/hand pump water supply system?
type_rain: Is the community served by a rainwater harvesting water supply system?
water_dry_season: Are there adequate water resources (at the source) to meet demand in dry season?
water_rain_season: Are there adequate water resources (at the source) to meet demand in rainy season?
source_id: ID of the water source
source_type: Type of the water source, options including (1) lake, (2) river, (3) dug well, and (4) drilled well.
source_lat: Latitude of the water source
source_long: Longitude of the water source
source_alt: Altitude of the water source
catch_macromeasure: Macro measurement of catchment
catch_status: Status of the catchment, options including (1) A: good, (2) B: fair, (3) C: poor, and (4) D: Inoperable.
maintenance_date: Date of the maintainance data collection
catch_abcd: Status of catchment at maintainance, options including (1) A: good, (2) B: fair, (3) C: poor, and (4) D: Inoperable.
cond_abcd: Status of condition at maintainance, options including (1) A: good, (2) B: fair, (3) C: poor, and (4) D: Inoperable.
treat_type: Type of treatment, options including (1) desinfection with chlorine and (2) slow filtration.
treat_abcd: Status of treatment at maintainance, options including (1) A: good, (2) B: fair, (3) C: poor, and (4) D: Inoperable.
storage_abcd: Status of the storage system at maintainance, options including (1) A: good, (2) B: fair, (3) C: poor, and (4) D: Inoperable.
dist_abcd: Status of the distribution network at maintainance, options including (1) A: good, (2) B: fair, (3) C: poor, and (4) D: Inoperable.
flow: Flow rate, check unit with column
flow_unit: Unit of flow rate
chlorine_res: Chlorine residual
chlorine_res_unit: Unit of chlorine residual
treatment_ID: ID of the treatment
treatment_type: Type of the treatment
treatment_function: Is treatment functional?
treatment_lat: Latitude of the water treatment
treatment_long: Longitude of the water treatment
treatment_alt: Altitude of the water treatment
storage_ID: ID of the water storage infrastructure.
storage_clean_unit: Unit of cleaning frequency of the storage system
storage_lat: Latitude of the water storage infrastructure.
storage_long: Longitude of the water storage infrastructure.
storage_alt: Altitude of the water storage infrastructure.
storage_status: Status of the water storage infrastructure, options including (1) A: good, (2) B: fair, (3) C: poor, and (4) D: Inoperable.
dist_ID: ID of the distribution system
dist_hour: Hours of service per day
dist_connection: Number of distribution network connections
dist_status: Status of the distribution system, options including (1) A: good, (2) B: fair, (3) C: poor, and (4) D: Inoperable.