portawaterperu

The goal of the package portawaterperu is to provide access to data about community portable water systems in Peru. The data is collected from SIASAR database consisted of information and surveys about water catchments, storage system, treatment, distribution networks and maintainance.

Installation

You can install the development version of portawaterperu from GitHub with:

# install.packages("devtools")
devtools::install_github("openwashdata/portawaterperu")

## Run the following code in console if you don't have the packages
## install.packages(c("dplyr", "knitr", "readr", "stringr", "gt", "kableExtra"))
library(dplyr)
library(knitr)
library(readr)
library(stringr)
library(gt)
library(kableExtra)

Alternatively, you can download the individual datasets as a CSV or XLSX file from the table below.

dataset	CSV	XLSX
portawaterperu	Download CSV	Download XLSX

Data

The package provides access to one dataset portawaterperu.

library(portawaterperu)

portawaterperu

The dataset portawaterperu contains data abour portable water system from 32 communities in Peru. It has 32 observations and 51 variables

portawaterperu |> 
  head(3) |> 
  gt::gt() |>
  gt::as_raw_html()

name	ID	div	lat	long	alt	year	community	service_provider	pop_serviced	hh_serviced	type_gravity	type_pump	type_well	type_rain	water_dry_season	water_rain_season	source_id	source_type	source_lat	source_long	source_alt	catch_macromeasure	catch_status	maintenance_date	catch_abcd	cond_abcd	treat_type	treat_abcd	storage_abcd	dist_abcd	flow	flow_unit	chlorine_res	chlorine_res_unit	treatment_ID	treatment_type	treatment_function	treatment_lat	treatment_long	treatment_alt	storage_ID	storage_clean_unit	storage_lat	storage_long	storage_alt	storage_status	dist_ID	dist_hour	dist_connection	dist_status
Sistema de QQUENCO	147509	CUSCO,CHUMBIVILCAS,SANTO TOMAS	-14.4436	-72.0530	3686	2003	QQUENCO	JASS QUENCCO	400	300	TRUE	FALSE	FALSE	FALSE	FALSE	FALSE	440657	lake	-14.4436	-72.0530	3686	Ninguno	A - BUENO	2015-09-02	B	B	desinfection with chlorine	B	B	B	1	LITROS POR SEGUNDO	1	MILIGRAMOS POR LITRO	446651	Desinfección con cloro	FALSE	-14.4436	-72.0530	3686	438659	MESES	-14.4436	-72.0530	3686	D - CAIDO	444653	24	300	A - BUENO
Sistema de MIRAFLORES	147710	CUSCO,LA CONVENCION,ECHARATE	-12.7440	-72.5662	1064	2001	MIRAFLORES	jass miraflores	400	100	TRUE	FALSE	FALSE	FALSE	FALSE	FALSE	441235	river	-12.7440	-72.5662	1064	Ninguno	A - BUENO	2015-12-09	B	B	slow filtration	B	B	B	3	LITROS POR SEGUNDO	0	MILIGRAMOS POR LITRO	447229	Filtración lenta	TRUE	-12.7440	-72.5662	1064	439237	MESES	-12.7440	-72.5662	1064	D - CAIDO	445231	24	100	A - BUENO
Sistema de CHILCACHACA	147725	CUSCO,LA CONVENCION,HUAYOPATA	-13.0236	-72.4919	1886	2000	CHILCACHACA	jass chillcachaca	90	30	TRUE	FALSE	FALSE	FALSE	FALSE	FALSE	440654	river	-13.0236	-72.4919	1886	Ninguno	A - BUENO	2015-09-09	B	B	desinfection with chlorine	B	B	B	2	LITROS POR SEGUNDO	0	MILIGRAMOS POR LITRO	446648	Desinfección con cloro	TRUE	-13.0236	-72.4919	1886	438656	MESES	-13.0236	-72.4919	1886	D - CAIDO	444650	24	30	A - BUENO

For an overview of the variable names, see the following table.

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

Example

library(portawaterperu)
library(ggplot2)
# Provide some example code here
portawaterperu |> 
  #dplyr::filter(stringr::str_starts(divisiones, "AMAZONAS")) |>
  #dplyr::group_by(divisiones) |> 
  #dplyr::summarise(mean = mean(pob_servida)) |> 
  ggplot(aes(y = pop_serviced, color = type_gravity))+
  geom_boxplot(outliers = F)+
  labs(title = "Population served given different gravity types",
       y= "Population") +
  theme_classic()

Capstone Project

This dataset is shared as part of a capstone project in Data Science for openwashdata. For more information about the project and to explore further insights, please visit the project page at https://ds4owd-001.github.io/project-laurenjudah/ (to be public available)

Methodology

The data 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.

SIASAR does not provide a matching data dictionary. openwashdata developer went through the attachements of the original questionnaire:

• https://globalsiasar.org/es/content/documentacion-tecnica
• https://globalsiasar.org/en/content/technical-documentation

The variable description is written with our best guess with the information from the attachements.

License

Data are available as CC-BY.

Citation

Please cite this package using:

citation("portawaterperu")
#> To cite package 'portawaterperu' in publications use:
#> 
#>   Judah L, Loos S, Zhong M, Schöbitz L (2024). "portawaterperu: A
#>   Preliminary Review of Peruvian Potable Water System Data."
#>   doi:10.5281/zenodo.13134309
#>   <https://doi.org/10.5281/zenodo.13134309>.
#>   <https://github.com/openwashdata/portawaterperu>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Misc{judah_etall:2024,
#>     title = {portawaterperu: A Preliminary Review of Peruvian Potable Water System Data},
#>     author = {Lauren Judah and Sebastian Camilo Loos and Mian Zhong and Lars Schöbitz},
#>     year = {2024},
#>     doi = {10.5281/zenodo.13134309},
#>     url = {https://github.com/openwashdata/portawaterperu},
#>     abstract = {Data to gain preliminary understanding of community potable water systems in Peru.},
#>     keywords = {open data,washdata,water supply,community water systems,drinking water,SIASAR,Peru},
#>     version = {0.0.1},
#>   }