{"id":38654477,"url":"https://github.com/openwashdata/grdwtrsmpkwale","last_synced_at":"2026-01-17T09:25:36.364Z","repository":{"id":192074228,"uuid":"679787061","full_name":"openwashdata/grdwtrsmpkwale","owner":"openwashdata","description":"Groundwater analysis from 2016 in Kwale, Kenya","archived":false,"fork":false,"pushed_at":"2023-10-16T13:43:26.000Z","size":1248,"stargazers_count":0,"open_issues_count":1,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-09-05T04:27:04.284Z","etag":null,"topics":["groundwater","groundwater-data","kenya","opendata","openwashdata","r"],"latest_commit_sha":null,"homepage":"https://openwashdata.github.io/grdwtrsmpkwale/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"cc-by-4.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/openwashdata.png","metadata":{"files":{"readme":"README.Rmd","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2023-08-17T16:04:59.000Z","updated_at":"2024-07-11T09:41:28.000Z","dependencies_parsed_at":"2023-10-16T23:58:55.585Z","dependency_job_id":"b1548eb7-e0f7-4d79-b4d6-fdc07ccdc5ee","html_url":"https://github.com/openwashdata/grdwtrsmpkwale","commit_stats":null,"previous_names":["openwashdata/grdwtrsmpkwale"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/openwashdata/grdwtrsmpkwale","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openwashdata%2Fgrdwtrsmpkwale","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openwashdata%2Fgrdwtrsmpkwale/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openwashdata%2Fgrdwtrsmpkwale/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openwashdata%2Fgrdwtrsmpkwale/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/openwashdata","download_url":"https://codeload.github.com/openwashdata/grdwtrsmpkwale/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openwashdata%2Fgrdwtrsmpkwale/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28505550,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-17T06:57:29.758Z","status":"ssl_error","status_checked_at":"2026-01-17T06:56:03.931Z","response_time":85,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["groundwater","groundwater-data","kenya","opendata","openwashdata","r"],"created_at":"2026-01-17T09:25:35.436Z","updated_at":"2026-01-17T09:25:36.313Z","avatar_url":"https://github.com/openwashdata.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\nalways_allow_html: true\neditor_options: \n  markdown: \n    wrap: 72\n  chunk_output_type: console\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\",\n  message = FALSE,\n  warning = FALSE,\n  fig.retina = 2,\n  fig.align = 'center'\n)\n\nlibrary(lubridate)\nlibrary(sf)\nlibrary(tidyverse)\nlibrary(tmap)\nlibrary(tmaptools)\n```\n\n# grdwtrsmpkwale\n\n\u003c!-- badges: start --\u003e\n\n[![License: CC BY\n4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)\n[![R-CMD-check](https://github.com/openwashdata/grdwtrsmpkwale/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/openwashdata/grdwtrsmpkwale/actions/workflows/R-CMD-check.yaml)\n\n\u003c!-- badges: end --\u003e\n\nThe goal of `grdwtrsmpkwale` is to provide datasets for research and\nplanning of water and solid waste management in Kwale, Kenya. This\npackage includes water anlaysis data collected in 2016 combined with the\ngeospatial data from the collection points. The data is collected part of the project UPGro (Unlocking the Potential of Groundwater for the Poor) which aimed to improve the evidence and understanding of groundwater across Sub-Saharan Africa to help tackle poverty.\n\n## Installation\n\nYou can install the development version of 'grdwtrsmpkwale' from\n[GitHub](https://github.com/openwashdata/grdwtrsmpkwale) with:\n\n``` r\n# install.packages(\"devtools\")\ndevtools::install_github(\"openwashdata/grdwtrsmpkwale\")\n```\n\nAlternatively, you can download the individual datasets as CSV or XLSX\nfile from the table below.\n\n```{r echo=FALSE, message=FALSE, warning=FALSE}\n\nextdata_path \u003c- \"https://github.com/openwashdata/grdwtrsmpkwale/raw/main/inst/extdata/\"\n\nread_csv(\"data-raw/dictionary.csv\") |\u003e \n  distinct(file_name) |\u003e \n  mutate(file_name = str_remove(file_name, \".rda\")) |\u003e \n  rename(dataset = file_name) |\u003e \n  mutate(\n    CSV = paste0(\"[Download CSV](\", extdata_path, dataset, \".csv)\"),\n    XLSX = paste0(\"[Download XLSX](\", extdata_path, dataset, \".xlsx)\")\n  ) |\u003e \n  knitr::kable()\n\n```\n\n# Introduction\n\nThis dataset contains results of two sampling campaigns conducted in\nKwale County Kenya in March and June 2016 by GHS/UPC as part of the Gro\nfor GooD project.[^1]\n\n[^1]: \u003chttps://metadata.bgs.ac.uk/geonetwork/srv/eng/catalog.search#/metadata/50cdcbae-bc14-628b-e054-002128a47908\u003e\n\nWater samples from over 79 groundwater and 6 surface water (SW)\nlocations were analysed for major ions, stable isotopes, selected trace\nconstituents, electrical conductivity, nitrates, ammonia, pH, DO\n(Dissolved Oxygen), Eh (oxidation / reduction potential), Temperature,\nTOC (Total Organic Carbon) and field alkalinity. Most locations were\nsampled in both March (dry season) and June (wet season).\n\n# Data\n\nThis data package has two datasets: `water_samples` and\n`selected_samples`.\n\n```{r}\nlibrary(grdwtrsmpkwale)\n```\n\n## water_samples\n\nThis dataset contains data from an analysis of groundwater in Kwale,\nKenya. The data was collected once in March and once in June of 2016 for\neach sampling spot. In total `r nrow(water_samples)` samples were taken\nin `r nrow(distinct(water_samples, localization))` different\nlocalisations that have their geospatial data included in this data\npackage. The sample analysis includes different measurements including\nconductivity, temperature, pH-values and concentrations of different\nelements/molecules for the groundwater samples.\n\nThe `water_samples` data set has `r ncol(water_samples)` variables and\n`r nrow(water_samples)` observations. For an overview of the variable\nnames, see the following table.\n\n```{r, eval=FALSE}\nwater_samples\n```\n\n```{r echo=FALSE, message=FALSE, warning=FALSE}\nreadr::read_csv(\"data-raw/dictionary.csv\") |\u003e\n  dplyr::filter(file_name == \"water_samples.rda\") |\u003e\n  dplyr::select(variable_name:error) |\u003e \n  knitr::kable() |\u003e \n  kableExtra::kable_styling() |\u003e \n  kableExtra::scroll_box(height = \"400px\")\n```\n\n```{r echo=FALSE, message=FALSE, warning=FALSE}\n#| label: fig-location-plot\n#| fig-cap: Locations of sampling spots\n\nsf_samples \u003c- st_as_sf(water_samples, coords = c(\"utm_x\", \"utm_y\"), crs = 21037) |\u003e\n  st_transform(crs = 4236)\n\ntmap_mode(\"plot\")\n\nsf_samples |\u003e\n  tm_shape() +\n  tm_dots(size = 0.1, col = \"pH\", palette = \"RdBu\") +\n  tm_graticules()\n\n```\n\n## selected_samples\n\nThis dataset contains data from an analysis of groundwater in Kwale,\nKenya. The data was collected three weeks in a row at 8 different\nlocations. The sample analysis includes measurements of conductivity,\ntemperature, pH-values and concentrations of different\nelements/molecules.\n\nThe `selected_samples` data set has `r ncol(selected_samples)` variables\nand `r nrow(selected_samples)` observations. For an overview of the\nvariable names, see the following table.\n\n```{r, eval=FALSE}\nselected_samples\n```\n\n```{r echo=FALSE, message=FALSE, warning=FALSE}\nreadr::read_csv(\"data-raw/dictionary.csv\") |\u003e \n  dplyr::filter(file_name == \"selected_samples.rda\") |\u003e \n  dplyr::select(variable_name:error) |\u003e  \n  knitr::kable(show_col_types = FALSE) |\u003e \n  kableExtra::kable_styling() |\u003e \n  kableExtra::scroll_box(height = \"400px\")\n```\n\n## Example\n\n```{r example, eval=FALSE, echo=TRUE}\nsf_samples \u003c- water_samples |\u003e \n  mutate(date = ymd(date)) |\u003e \n  mutate(month = month(date), .after = date) |\u003e \n  drop_na(month) |\u003e \n  st_as_sf(coords = c(\"utm_x\", \"utm_y\"), crs = 21037) |\u003e\n  st_transform(crs = 4236)\n\ntmap_mode(\"view\")\n\ntm_shape(sf_samples) +\n  tm_dots(col = \"pH\", size = 0.1, alpha = 0.7, palette = \"RdBu\") +\n  tm_facets(by = \"month\", as.layers = TRUE) +\n  tm_layout(panel.labels = c(\"March\", \"June\"))\n\n```\n\n```{r, echo=FALSE, fig.cap=\"Screenshot of an interactive map with OpenStreetMap layer.\"}\nknitr::include_graphics(\"man/figures/screenshot-map-sampling-spots.png\")\n```\n\n# License\n\nData are available as\n[CC-BY](https://github.com/openwashdata/grdwtrsmpkwale/blob/main/LICENSE.md).\n\n# Citation\n\n```{r echo=FALSE}\ncitation(\"grdwtrsmpkwale\")\n```\n\n## Related References\n\n[1] Ferrer et al, \"[First step to understand the importance of new deep aquifer pumping\nregime in groundwater system in a developing country, Kwale,\nKenya](http://meetingorganizer.copernicus.org/EGU2016/EGU2016-16969.pdf)\",\nGeophysical Research Abstracts, Vol. 18, EGU2016-16969,\n2016; Poster Avaiblable: \u003chttps://upgro.files.wordpress.com/2015/09/egu16_groforgood_v1.pdf\u003e;\nUPC - The Departement of Civil Enginyering de la Universitat Politecnica\nde Catalunya GHS - Grupo de Hidrologia Subterranea\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenwashdata%2Fgrdwtrsmpkwale","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopenwashdata%2Fgrdwtrsmpkwale","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenwashdata%2Fgrdwtrsmpkwale/lists"}