From c221536a1d69775ed1ebef198bd38401975a4c3b Mon Sep 17 00:00:00 2001 From: Geraldine Klarenberg Date: Mon, 12 Aug 2024 22:07:08 -0400 Subject: [PATCH 1/9] Created script to merge WIN and Guana spreadsheet WQ data together. Created new Rds file with all this data. All in long format, so it works with Chris' setup for plotting. --- 02_Cleaning_scripts/WQ_WIN_merge.R | 56 +++++++++++++++++++++++++++++ 03_Data_for_app/WQ_all.Rds | Bin 0 -> 418221 bytes 2 files changed, 56 insertions(+) create mode 100644 02_Cleaning_scripts/WQ_WIN_merge.R create mode 100644 03_Data_for_app/WQ_all.Rds diff --git a/02_Cleaning_scripts/WQ_WIN_merge.R b/02_Cleaning_scripts/WQ_WIN_merge.R new file mode 100644 index 0000000..26af8a0 --- /dev/null +++ b/02_Cleaning_scripts/WQ_WIN_merge.R @@ -0,0 +1,56 @@ +######################################################################## +########## NERRS Science Transfer project - GTMNERR ############# +######################################################################## + +# Geraldine Klarenberg, PhD +# gklarenberg@ufl.edu +# 12 August 2024 + +# Load packages +library(tidyverse) + +# Merge WIN and WQ data into one + +WIN <- readRDS("03_Data_for_app/WIN.Rds") +WQ_GTMNERR <- readRDS("03_Data_for_app/WQ.Rds") + +# Make WQ_GTMNERR long format as well, just like WIN +# Having a column for the dates is advisable though, as it is a separate data +# type. Update that later, not right now. + +# First make sure that every row has a UNID +WQ_GTMNERR <- WQ_GTMNERR %>% + arrange(UNID, StationCode, SampleDate, ComponentShort) + +for (i in 1:nrow(WQ_GTMNERR)){ + if (is.na(WQ_GTMNERR$UNID[i])){ + WQ_GTMNERR$UNID[i] <- WQ_GTMNERR$UNID[i-1] + 1 + } +} +# Check there are no duplicates +sum(duplicated(WQ_GTMNERR$UNID)) + +WQ_GTMNERR_long <- WQ_GTMNERR %>% + mutate(across(everything(), as.character)) %>% + mutate_all(~ na_if(., "")) %>% + pivot_longer(cols = -UNID, + names_to = "variable", + values_to = "value") + +# How to deal with UNID when merging? Start counting anew (or add however far the +# one dataset is?) + +min(as.numeric(WQ_GTMNERR_long$UNID)) # 1 +max(as.numeric(WQ_GTMNERR_long$UNID)) # 17098 + +min(as.numeric(WIN$RowID)) # 55135 +max(as.numeric(WIN$RowID)) # 3677602 +# Appears there will be no overlap. Merge. + +WQ_GTMNERR_long <- WQ_GTMNERR_long %>% + rename(RowID = UNID) + +WQ_all <- WIN %>% + full_join(WQ_GTMNERR_long) + +saveRDS(WQ_all, "03_Data_for_app/WQ_all.Rds") \ No newline at end of file diff --git a/03_Data_for_app/WQ_all.Rds b/03_Data_for_app/WQ_all.Rds new file mode 100644 index 0000000000000000000000000000000000000000..21eba8894d724fc931994b95552fc235ac75052a GIT binary patch literal 418221 zcmeFZ2UJs8*FHXuV;e-Qpw!V(u>mSgYE)EgfDS6sMWr{9UgKCmMZ^&W2_+&*kg5cv z6BPjwLc~y{1!)OAKn#$O@;jlUWPHDGt?&O|uiRPVfcM;c%HGd@_H*{Rcf|Y`|1$c| z{BGv4GFycdmkyDw($3qLoLE#bZ{Eg$r|XpNN!szya3+#X6|3%ixwM6C-VblTaN4ef{?}=Ag4XG?RVXVx@JF}Guk%hy0YrE_PoULwSoGECt1e(5w9vsC|mkm#L zDML2?ty?8vH9jLwb6l{gcg&N5BV%)ky9?%NW(|7Q3#NwF=GMMSkUC8Ue;v2UDUA~P zVWya8SE%%HN?Ujg?Q)D|UbrbjinI&siq?BXj8|~!8vCoCqYU0lA=@$!;TVw#Zmyqk zv!5dhv{X9Uf_v~X#$~&)A(ThNYMzY&>CW?8Xg};j8?GjMY>iV zr@T>)p?Y@;<7mn-KM}tzysHP}`ehgx0Rz%U4;J4#=FWGqYhnzb+A~h%-V4gOS45r5mOVwb{QZq0~ z7>*)`HFpe@)u7ZcNba1~m4NwOK=6^s>0nZcjOs;>MKWS#cwnz?Fx)b{m%Mow=%-A1 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z1H->X7zlSH{`>ov&ohacdk^8>eP76(@Vb+XjV5NltHykubMgS|qu!bHo>| z62+&1EH`#S(Dj$;+5r$)WX4xHVZJx&5QRumd-hqJJp(>;59K6wqSp(AXKZau;0+FR z{zK&AGGX6r2O~v?@q%PVXKL Yv^!fZx*hL2{68Ul&&`3v>N?>62b4L)<^TWy literal 0 HcmV?d00001 From d66757b92c950b1f2b7d226499dbf22a1870bc2e Mon Sep 17 00:00:00 2001 From: Geraldine Klarenberg Date: Mon, 12 Aug 2024 22:26:09 -0400 Subject: [PATCH 2/9] Started updating the WQ page (i.e. the WIN page). But realized we should standardize the names for things like lat, lon, station name, analyte, etc. --- 02_Cleaning_scripts/WQ_WIN_merge.R | 4 +++ modules/main_page.R | 15 ++++++++++ modules/win.R | 48 ++++++++++++++++++------------ 3 files changed, 48 insertions(+), 19 deletions(-) diff --git a/02_Cleaning_scripts/WQ_WIN_merge.R b/02_Cleaning_scripts/WQ_WIN_merge.R index 26af8a0..7ca9a8b 100644 --- a/02_Cleaning_scripts/WQ_WIN_merge.R +++ b/02_Cleaning_scripts/WQ_WIN_merge.R @@ -53,4 +53,8 @@ WQ_GTMNERR_long <- WQ_GTMNERR_long %>% WQ_all <- WIN %>% full_join(WQ_GTMNERR_long) +##### NOTE ###### +# We should make the names for lat, long, station name etc the same, so we can use +# everything together properly in the functions that select and search + saveRDS(WQ_all, "03_Data_for_app/WQ_all.Rds") \ No newline at end of file diff --git a/modules/main_page.R b/modules/main_page.R index f35ec56..ea00e84 100644 --- a/modules/main_page.R +++ b/modules/main_page.R @@ -1,3 +1,14 @@ +######################################################################## +########## NERRS Science Transfer project - GTMNERR ############# +######################################################################## + +# Geraldine Klarenberg, PhD +# gklarenberg@ufl.edu +# Created June 2024 +# Last updated: 12 August 2024 + +# This page shows a map, with a dropdown menu to pick types of +# datasets, as well as shapefiles for the area #### Get WIN data locations # I am putting this here right now, but I feel we should move this to a cleaning @@ -38,6 +49,10 @@ datasets_location <- st_as_sf(datasets_location, coords = c("long", "lat"), crs color_palette <- colorFactor(palette = c("red"), #, "blue", "green", "purple" domain = datasets_location$type) +#### HAB locations data ------------------------------------------------ +# Add this at some point so there is another dataset that shows up in the dropdown +# menu + ### Define the UI ------------------------------------------------------------- mainPageUI <- function(id) { ns <- NS(id) # This is an important part to add to all subpages so they use the diff --git a/modules/win.R b/modules/win.R index 53cf4b2..409747b 100644 --- a/modules/win.R +++ b/modules/win.R @@ -1,9 +1,19 @@ -# import data for this page -WIN_df <- readRDS("./03_Data_for_app/WIN.Rds") +######################################################################## +########## NERRS Science Transfer project - GTMNERR ############# +######################################################################## + +# Geraldine Klarenberg, PhD +# Email: gklarenberg@ufl.edu +# Christopher Marais +# Email: +# Last updated: 12 August 2024 + +# import all WQ data for this page (WIN and Guana spreadsheet) +WQ_df <- readRDS("./03_Data_for_app/WQ_all.Rds") #### Process data further #### # make datframe for map display and hover data -WIN_data_locations = WIN_df %>% +WQ_data_locations = WQ_df %>% filter(variable %in% c("geometry", "HUC12.Name", "Start.Date", @@ -23,7 +33,7 @@ WIN_data_locations = WIN_df %>% longitude = as.numeric(longitude) ) -WIN_data_units = WIN_df %>% +WQ_data_units = WQ_df %>% filter(variable %in% c("DEP.Analyte.Name", "DEP.Result.Unit") ) %>% @@ -156,7 +166,7 @@ WINPageServer <- function(id, parentSession) { # Create the dropdown UI output$dropdown_ui <- renderUI({ print("Rendering dropdown UI") - df <- filter_dataframe(WIN_df) + df <- filter_dataframe(WQ_df) create_dropdown(df, ns) }) @@ -164,15 +174,15 @@ WINPageServer <- function(id, parentSession) { observeEvent(selected_column(), { print(paste("Updating plot for", selected_column())) output$plot <- renderPlotly({ - df <- filter_dataframe(WIN_df) - create_plot(df, units_df = WIN_data_units, selected_column = selected_column()) + df <- filter_dataframe(WQ_df) + create_plot(df, units_df = WQ_data_units, selected_column = selected_column()) }) }, ignoreInit = FALSE) # Default plot output$plot <- renderPlotly({ - df <- filter_dataframe(WIN_df) - create_plot(df, units_df = WIN_data_units, selected_column = selected_column()) + df <- filter_dataframe(WQ_df) + create_plot(df, units_df = WQ_data_units, selected_column = selected_column()) }) # Create the map @@ -195,15 +205,15 @@ WINPageServer <- function(id, parentSession) { group = "Counties", popup = ~NAME, layerId = ~NAME ) %>% addMarkers( - data = WIN_data_locations, + data = WQ_data_locations, popup = ~ paste("Station Name: ", HUC12.Name, "
", "Start Date: ", Start.Date, "
" ), - group = "WIN", + group = "WQ", layerId = ~geometry ) %>% addLayersControl( - overlayGroups = c("Counties", "GTMNERR boundaries", "WIN"), + overlayGroups = c("Counties", "GTMNERR boundaries", "WQ"), options = layersControlOptions(collapsed = FALSE) ) %>% addMeasure(primaryLengthUnit = "miles", primaryAreaUnit = "sqmiles") @@ -214,14 +224,14 @@ WINPageServer <- function(id, parentSession) { click <- input$map_marker_click if (!is.null(click)) { clicked_id <- click$id - clicked_data <- WIN_data_locations %>% + clicked_data <- WQ_data_locations %>% filter(geometry == clicked_id) popup_visible(TRUE) output$plot <- renderPlotly({ - df <- filter_dataframe(WIN_df, filter_value = clicked_data$HUC12.Name) - create_plot(df, units_df = WIN_data_units, loc_name = clicked_data$HUC12.Name, selected_column = selected_column()) + df <- filter_dataframe(WQ_df, filter_value = clicked_data$HUC12.Name) + create_plot(df, units_df = WQ_data_units, loc_name = clicked_data$HUC12.Name, selected_column = selected_column()) }) } }) @@ -237,8 +247,8 @@ WINPageServer <- function(id, parentSession) { popup_visible(TRUE) output$plot <- renderPlotly({ - df <- filter_dataframe(WIN_df, filter_value = clicked_data$NAME) - create_plot(df, units_df = WIN_data_units, loc_name = clicked_data$NAME, selected_column = selected_column()) + df <- filter_dataframe(WQ_df, filter_value = clicked_data$NAME) + create_plot(df, units_df = WQ_data_units, loc_name = clicked_data$NAME, selected_column = selected_column()) }) } }) @@ -249,8 +259,8 @@ WINPageServer <- function(id, parentSession) { # Default plot output$plot <- renderPlotly({ - df <- filter_dataframe(WIN_df) - create_plot(df, units_df = WIN_data_units, selected_column = selected_column()) + df <- filter_dataframe(WQ_df) + create_plot(df, units_df = WQ_data_units, selected_column = selected_column()) }) }) From 705b93921251c74ead35cf932931dfde634dc548 Mon Sep 17 00:00:00 2001 From: Geraldine Klarenberg Date: Tue, 13 Aug 2024 17:51:32 -0400 Subject: [PATCH 3/9] Added a column to both WIN and WQ data to indicate the data source --- 02_Cleaning_scripts/WIN_data_clean.R | 3 +++ 02_Cleaning_scripts/WQ_WIN_merge.R | 15 ++++++++++++--- 03_Data_for_app/WIN.Rds | Bin 35772 -> 36118 bytes 03_Data_for_app/WQ_all.Rds | Bin 418221 -> 422074 bytes 4 files changed, 15 insertions(+), 3 deletions(-) diff --git a/02_Cleaning_scripts/WIN_data_clean.R b/02_Cleaning_scripts/WIN_data_clean.R index 1182e36..adbe5eb 100644 --- a/02_Cleaning_scripts/WIN_data_clean.R +++ b/02_Cleaning_scripts/WIN_data_clean.R @@ -92,6 +92,8 @@ WIN_df <- WIN_df %>% "Org.Detection.Unit", "Org.Result.Unit", "Activity.End.Date.Time"))) %>% + # Add a column to record the data source/provider + mutate(data_source = "WIN") %>% # or change this to DEP? mutate(across(everything(), as.character)) %>% mutate_all(~ na_if(., "")) %>% pivot_longer( @@ -108,4 +110,5 @@ WIN_df <- WIN_df %>% # "03_Data_for_app/Filtered_WIN_data_merged_20240501.csv", # row.names = FALSE) # Save the filtered data to a .RDs file + saveRDS(WIN_df, "03_Data_for_app/WIN.Rds") diff --git a/02_Cleaning_scripts/WQ_WIN_merge.R b/02_Cleaning_scripts/WQ_WIN_merge.R index 7ca9a8b..59dc934 100644 --- a/02_Cleaning_scripts/WQ_WIN_merge.R +++ b/02_Cleaning_scripts/WQ_WIN_merge.R @@ -18,8 +18,10 @@ WQ_GTMNERR <- readRDS("03_Data_for_app/WQ.Rds") # Having a column for the dates is advisable though, as it is a separate data # type. Update that later, not right now. -# First make sure that every row has a UNID +# First make sure that every row has a UNID and also add a column for the data +# source / provider WQ_GTMNERR <- WQ_GTMNERR %>% + mutate(data_source = "GTMNERR") %>% arrange(UNID, StationCode, SampleDate, ComponentShort) for (i in 1:nrow(WQ_GTMNERR)){ @@ -53,8 +55,15 @@ WQ_GTMNERR_long <- WQ_GTMNERR_long %>% WQ_all <- WIN %>% full_join(WQ_GTMNERR_long) +unique(WQ_all$variable) + ##### NOTE ###### # We should make the names for lat, long, station name etc the same, so we can use -# everything together properly in the functions that select and search +# everything together properly in the functions that select and search. Probably +# best to do this in the cleaning files - change the headers, with a lookup +# table. +# Other solution: pick the dataset first and then we can keep the column names +# the same...? 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z1H->X7zlSH{`>ov&ohacdk^8>eP76(@Vb+XjV5NltHykubMgS|qu!bHo>| z62+&1EH`#S(Dj$;+5r$)WX4xHVZJx&5QRumd-hqJJp(>;59K6wqSp(AXKZau;0+FR z{zK&AGGX6r2O~v?@q%PVXKL Yv^!fZx*hL2{68Ul&&`3v>N?>62b4L)<^TWy From f7566b051e5b7ecf95b8b04c712a3961836d5b02 Mon Sep 17 00:00:00 2001 From: Geraldine Klarenberg Date: Tue, 13 Aug 2024 19:05:26 -0400 Subject: [PATCH 4/9] Created a lookup file (manually, see accompanying text file lookup_creation_manual) to change and align the column names for WIN and WQ. Put those changes also in the cleaning scripts and created new .Rds files. --- .../guana_data_dictionary_updateGK.csv | 2 +- .../Guana_WQ/~$Guana_masterdata.xlsx | Bin 0 -> 165 bytes 02_Cleaning_scripts/WIN_data_clean.R | 31 +++-- 02_Cleaning_scripts/WQ_GTMNERR.R | 24 ++-- 03_Data_for_app/WIN.Rds | Bin 36118 -> 35066 bytes 03_Data_for_app/WQ.Rds | Bin 174646 -> 57236 bytes 03_Data_for_app/WQ_locations.Rds | Bin 875 -> 769 bytes 03_Data_for_app/WQ_lookup_names.csv | 111 ++++++++++++++++++ 03_Data_for_app/lookup_creation_manual.txt | 16 +++ 9 files changed, 162 insertions(+), 22 deletions(-) create mode 100644 01_Data_raw/Water_Quality/Guana_WQ/~$Guana_masterdata.xlsx create mode 100644 03_Data_for_app/WQ_lookup_names.csv create mode 100644 03_Data_for_app/lookup_creation_manual.txt diff --git a/01_Data_raw/Water_Quality/Guana_WQ/guana_data_dictionary_updateGK.csv b/01_Data_raw/Water_Quality/Guana_WQ/guana_data_dictionary_updateGK.csv index 92d4b8e..1fd73a0 100644 --- a/01_Data_raw/Water_Quality/Guana_WQ/guana_data_dictionary_updateGK.csv +++ b/01_Data_raw/Water_Quality/Guana_WQ/guana_data_dictionary_updateGK.csv @@ -1,4 +1,4 @@ -site,alternate_name,site_friendly,station_code,site_acronym,lat,long,start_date,end,wbid,location +site,alternate_name,site_friendly,station_code,site_acronym,Latitude,Longitude,start_date,end,wbid,location MICKLERS,N,Micklers,GTMMKNUT,MK,30.16073611,-81.36027778,,N,Lake,water_control DEPGL1,N,Guana Lake 1,GTMGL1NUT,GL1,30.1504,-81.3604,,N,Lake,open_water DEPGL2,N,Guana Lake 2,GTMGL2NUT,GL2,30.1161,-81.3511,,N,Lake,open_water diff --git a/01_Data_raw/Water_Quality/Guana_WQ/~$Guana_masterdata.xlsx b/01_Data_raw/Water_Quality/Guana_WQ/~$Guana_masterdata.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..5a932052db2a5d1e1d32a453f59be330b8becc3b GIT binary patch literal 165 zcmWgj%}g%JFV0UZQSeVo%S=vH2rW)6QXm9G8GIQs8Il=_81fm4fjEt!gh7G9A4sQx R#Z!U2P@qgIP=x};5CA3W7%cz* literal 0 HcmV?d00001 diff --git a/02_Cleaning_scripts/WIN_data_clean.R b/02_Cleaning_scripts/WIN_data_clean.R index adbe5eb..383161c 100644 --- a/02_Cleaning_scripts/WIN_data_clean.R +++ b/02_Cleaning_scripts/WIN_data_clean.R @@ -9,7 +9,14 @@ library(tidyverse) GTMNERR <- st_read("03_Data_for_app/shapefiles_new/counties_GTMNERR.shp") # CRS: NAD83 / UTM zone 17N # WIN Data -gps_data <- read.csv("./01_Data_raw/Water_Quality/WIN/WIN_data_merged_20240501.csv") +gps_data <- read_csv("./01_Data_raw/Water_Quality/WIN/WIN_data_merged_20240501.csv") + +lookup_names <- read_csv("03_Data_for_app/WQ_lookup_names.csv") + +# Change column names so we can later merge this with other WQ data +recode_vec <- setNames(lookup_names$original_name, lookup_names$dashboard_name) +gps_data <- gps_data %>% + rename(any_of(recode_vec)) #### GTMNERR boundary and aquatic preserves #### @@ -41,7 +48,7 @@ bound_box <- st_bbox(st_sfc(pt1, pt3, pt4, pt2, crs = st_crs(GTMNERR))) # Filter GPS coordinates # Convert to sf object -gps_sf <- st_as_sf(gps_data, coords = c("Location_2", "Location_1"), crs = 4326) +gps_sf <- st_as_sf(gps_data, coords = c("Longitude", "Latitude"), crs = 4326) # Crop GPS points within the bounding box gps_cropped <- st_crop(gps_sf, bound_box) @@ -65,7 +72,7 @@ coordinates <- st_coordinates(gps_cropped) WIN_df <- cbind(WIN_df, coordinates) # Rename the coordinates columns if necessary -colnames(WIN_df)[(ncol(WIN_df)-1):ncol(WIN_df)] <- c("longitude", "latitude") +colnames(WIN_df)[(ncol(WIN_df)-1):ncol(WIN_df)] <- c("Longitude", "Latitude") #### Keep only columns with varying information #### # Function to remove columns with the same value in the whole column @@ -83,15 +90,15 @@ WIN_df <- remove_constant_columns(WIN_df) # Convert all columns to character before pivoting and retain the original row identifier WIN_df <- WIN_df %>% - select(-all_of(c("Station.ID", - "Station.Name", - "Org.Analyte.Name", - "DEP.Result.Value.Number", - "DEP.MDL", - "DEP.PQL", - "Org.Detection.Unit", - "Org.Result.Unit", - "Activity.End.Date.Time"))) %>% + select(-all_of(c("StationID", + "StationName", + "OrgAnalyteName", + "OrgResultValue", #GK: changed this from "DEPResultValueNumber", as I believe it is the DEP value we want to keep? + "DEPMDL", + "DEPPQL", + "OrgDetectionUnit", + "OrgResultUnit", + "ActivityEndDateTime"))) %>% # Add a column to record the data source/provider mutate(data_source = "WIN") %>% # or change this to DEP? mutate(across(everything(), as.character)) %>% diff --git a/02_Cleaning_scripts/WQ_GTMNERR.R b/02_Cleaning_scripts/WQ_GTMNERR.R index 4010ff2..99c1a26 100644 --- a/02_Cleaning_scripts/WQ_GTMNERR.R +++ b/02_Cleaning_scripts/WQ_GTMNERR.R @@ -28,6 +28,13 @@ WQ_meta <- read_csv("01_Data_raw/Water_Quality/Guana_WQ/guana_data_dictionary_up # Some stations have two codes due to a name change (see Word doc with metadata) # Don't remove +lookup_names <- read_csv("03_Data_for_app/WQ_lookup_names.csv") + +# Change column names so we can later merge this with other WQ data +recode_vec <- setNames(lookup_names$original_name, lookup_names$dashboard_name) +WQ <- WQ %>% + rename(any_of(recode_vec)) + ### 2. Check categorical values ------------------------------------------------ # Check station names, componentLong and componentShort (spelling etc) unique(WQ$StationCode) @@ -61,24 +68,23 @@ unique(WQ$Remark) # inconsistent... But there are some capital letters that names(WQ_meta)[names(WQ_meta) == "station_code"] <- "StationCode" WQ <- WQ %>% - left_join(WQ_meta) %>% - select(-Lat, -Long) + left_join(WQ_meta) # Stations missing from metadata: GL1.5, GL2.5 and GL3.5 -> added manually and # emailed Nikki -which(is.na(WQ$lat)) -which(is.na(WQ$long)) +which(is.na(WQ$Latitude)) +which(is.na(WQ$Longitude)) -WQ[which(is.na(WQ$lat)),] # duplicates?? Remove for now; emailed Nikki -WQ <- WQ[-which(is.na(WQ$lat)),] +WQ[which(is.na(WQ$Latitude)),] # duplicates?? Remove for now; emailed Nikki +WQ <- WQ[-which(is.na(WQ$Latitude)),] # Create a separate dataframe with only station info, not the data (makes map # too heavy) WQ_locations <- WQ %>% mutate(Year = year(SampleDate)) %>% - select(site_friendly, Year, site_acronym, lat, long, wbid, location) %>% - group_by(site_friendly, site_acronym, lat, long, wbid, location) %>% + select(site_friendly, Year, site_acronym, Latitude, Longitude, wbid, location) %>% + group_by(site_friendly, site_acronym, Latitude, Longitude, wbid, location) %>% summarize(maxYear = max(Year), minYear = min(Year)) %>% mutate(type = "Water quality", dataset = "Guana Water Quality Monitoring (GTMNERR)") @@ -86,7 +92,7 @@ WQ_locations <- WQ %>% WQ_data_available <- WQ %>% mutate(Year = year(SampleDate)) %>% select(StationCode, Year, SampleType, ComponentShort, ComponentLong, site_friendly, - site_acronym, lat, long, wbid, location) %>% + site_acronym, Latitude, Longitude, wbid, location) %>% distinct() ### 4. 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+WIN,Organization ID,OrganizationID +WIN,Monitoring Location ID,MonitoringLocationID +WIN,HUC12 Name,HUC12Name +WIN,Project ID,ProjectID +WIN,Activity ID,ActivityID +WIN,Activity Type,SampleType +WIN,Activity Start Date Time,SampleDate +WIN,Activity End Date Time,ActivityEndDateTime +WIN,Activity Time Zone,ActivityTimeZone +WIN,Media,Media +WIN,Matrix,Matrix +WIN,Sample Collection Type,SampleCollectionType +WIN,Sampling Agency Name,SamplingAgencyName +WIN,SampleCollectionEquipmentName,SampleCollectionEquipmentName +WIN,Activity Depth,ActivityDepth +WIN,Activity Depth Unit,ActivityDepthUnit +WIN,Relative Depth,RelativeDepth +WIN,Activity Top Depth,ActivityTopDepth +WIN,Activity Bottom Depth,ActivityBottomDepth +WIN,Activity Depth Top Bottom Unit,ActivityDepthTopBottomUnit +WIN,Total Depth,TotalDepth +WIN,Total Depth Unit,TotalDepthUnit +WIN,Activity Representative Ind,ActivityRepresentativeInd +WIN,Activity Comments,ActivityComments +WIN,Sampler Name,SamplerName +WIN,Field Blank Batch ID,FieldBlankBatchID +WIN,Equipment Blank Batch ID,EquipmentBlankBatchID +WIN,Trip Blank Batch ID,TripBlankBatchID +WIN,Master Activity ID,MasterActivityID +WIN,Activity Loaded Date,ActivityLoadedDate +WIN,Activity Updated Date,ActivityUpdatedDate +WIN,DEP Result ID,DEPResultID +WIN,Org Result ID,OrgResultID +WIN,DEP Analyte Group,DEPAnalyteGroup +WIN,DEP Analyte Name,ComponentLong +WIN,ADaPT Analyte ID,ADaPTAnalyteID +WIN,Org Analyte Name,OrgAnalyteName +WIN,Org Result Value,OrgResultValue +WIN,Org Result Unit,OrgResultUnit +WIN,Org MDL,OrgMDL +WIN,Org PQL,OrgPQL +WIN,Org Detection Unit,OrgDetectionUnit +WIN,DEP Result Value Number,Result +WIN,DEP Result Value Text,DEPResultValueText +WIN,DEP Result Unit,Unit +WIN,DEP MDL,DEPMDL +WIN,DEP PQL,DEPPQL +WIN,Value Qualifier,ValueQualifier +WIN,Sample Fraction,SampleFraction +WIN,Prep Method,PrepMethod +WIN,Preparation Date Time,PreparationDateTime +WIN,Preparation Time Zone,PreparationTimeZone +WIN,Analysis Method,AnalysisMethod +WIN,Analysis Date Time,AnalysisDateTime +WIN,Analysis Time Zone,AnalysisTimeZone +WIN,Lab ID,LabID +WIN,Lab Name,LabName +WIN,Lab Accreditation Authority,LabAccreditationAuthority +WIN,Result Comments,ResultComments +WIN,Lab Sample ID,LabSampleID +WIN,Method Batch ID,MethodBatchID +WIN,Analytical Batch ID,AnalyticalBatchID +WIN,Dilution,Dilution +WIN,Percent Moisture,PercentMoisture +WIN,Percent Recovery,PercentRecovery +WIN,Relative Percent Difference,RelativePercentDifference +WIN,Error,Error +WIN,Target Species,TargetSpecies +WIN,Finfish Size,FinfishSize +WIN,Finfish Unit,FinfishUnit +WIN,Result Value Type,ResultValueType +WIN,Statistical Base,StatisticalBase +WIN,Audit Censored Decisions,AuditCensoredDecisions +WIN,Result Loaded Date,ResultLoadedDate +WIN,Result Updated Date,ResultUpdatedDate +WIN,RowID,RowID +WIN,LocationID,LocationID +WIN,ProgramID,ProgramID +WIN,Station ID,StationID +WIN,Station Name,StationName +WIN,Station Type,StationType +WIN,County,County +WIN,Start Date,StartDate +WIN,End Date,EndDate +WIN,Location_1,Latitude +WIN,Location_2,Longitude +GTMNERR,UNID,UNID +GTMNERR,StationCode,StationCode +GTMNERR,SampleDate,SampleDate +GTMNERR,SampleType,SampleType +GTMNERR,Lat,Latitude +GTMNERR,Long,Longitude +GTMNERR,ComponentShort,ComponentShort +GTMNERR,ComponentLong,ComponentLong +GTMNERR,Result,Result +GTMNERR,Remark,Remark +GTMNERR,Flag,Flag +GTMNERR,Unit,Unit +GTMNERR,MRL,MRL +GTMNERR,MDL,MDL +GTMNERR,Dilution,Dilution +GTMNERR,PQL,PQL +GTMNERR,DateRecieved,DateRecieved +GTMNERR,DateAnalyzed,DateAnalyzed +GTMNERR,TestComments,TestComments +GTMNERR,AnalysisMethod,AnalysisMethod +GTMNERR,Lab ID,LabID +GTMNERR,Lab Accredidation Authority,LabAccredidationAuthority +GTMNERR,Laboratory,Laboratory +GTMNERR,RQ#,RQ# \ No newline at end of file diff --git a/03_Data_for_app/lookup_creation_manual.txt b/03_Data_for_app/lookup_creation_manual.txt new file mode 100644 index 0000000..54778df --- /dev/null +++ b/03_Data_for_app/lookup_creation_manual.txt @@ -0,0 +1,16 @@ +Guana Dashboard development +13 August 2024 + +For the water quality page, to streamline showing all the WQ data on one page, I manually created +a lookup table to change the headers of the separate files so they are the same. This way we can use +merge the datasets and use the existing functions on them. + +The headers comfr from the files App_dev/01_Data_raw/Water_Quality/WIN/WIN_data_merged_20240501.csv and +App_dev/01_Data_raw/Water_Quality/Guana_WQ/Guana_masterdata.xlsx. + +1. Copy-pasted the header names to App_dev/03_Data_for_app/WQ_lookup_names.csv and named the column original_name +2. Added a column data_sources with either WIN or GTMNERR +3. Created a column dashboard_name and copied all the names from original_name to it +4. For now (08/13/2024) I am only changing latitude, longitude, dates, sample type, components/analytes measured (DEP, not org). For visualization purposes. We can rename the rest later (analytes themselves will +also need to be renamed, as well as info on station names and types). +5. For the new names I also removed the spaces (because R inserts points there). \ No newline at end of file From d09e1f0f14cfa6b5d12a8d3d322e511bb934bf86 Mon Sep 17 00:00:00 2001 From: Geraldine Klarenberg Date: Tue, 13 Aug 2024 22:25:00 -0400 Subject: [PATCH 5/9] After making changes to cleaning files for GTMNERR WQ and WIN data, I still had to run the merge file to create the new .Rds file --- 02_Cleaning_scripts/WQ_WIN_merge.R | 12 ++---------- 03_Data_for_app/WQ_all.Rds | Bin 422074 -> 135123 bytes 2 files changed, 2 insertions(+), 10 deletions(-) diff --git a/02_Cleaning_scripts/WQ_WIN_merge.R b/02_Cleaning_scripts/WQ_WIN_merge.R index 59dc934..63325bd 100644 --- a/02_Cleaning_scripts/WQ_WIN_merge.R +++ b/02_Cleaning_scripts/WQ_WIN_merge.R @@ -43,7 +43,7 @@ WQ_GTMNERR_long <- WQ_GTMNERR %>% # one dataset is?) min(as.numeric(WQ_GTMNERR_long$UNID)) # 1 -max(as.numeric(WQ_GTMNERR_long$UNID)) # 17098 +max(as.numeric(WQ_GTMNERR_long$UNID)) # 5016 (used to be 17098?) min(as.numeric(WIN$RowID)) # 55135 max(as.numeric(WIN$RowID)) # 3677602 @@ -57,13 +57,5 @@ WQ_all <- WIN %>% unique(WQ_all$variable) -##### NOTE ###### -# We should make the names for lat, long, station name etc the same, so we can use -# everything together properly in the functions that select and search. 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b/04_Tests/leaflet_test.R index c125916..baf9dd6 100644 --- a/04_Tests/leaflet_test.R +++ b/04_Tests/leaflet_test.R @@ -17,7 +17,7 @@ GTMNERR <- st_transform(GTMNERR, crs = 4326) # Leaflet uses EPSG 3857, change this # https://gis.stackexchange.com/questions/48949/epsg-3857-or-4326-for-web-mapping -epsg4326 <- leafletCRS(crsClass = "L.CRS.EPSG4326") +#epsg4326 <- leafletCRS(crsClass = "L.CRS.EPSG4326") # BUT! It actually seems that Leaflet does still want shapefiles in 4326, see # https://github.com/Leaflet/Leaflet/issues/4146 I also tried to change GTMNERR # to crs 3857 but that threw errors. See second paragraph here: @@ -27,11 +27,11 @@ m <- leaflet(data = GTMNERR, options = leafletOptions(#crs = epsg4326, minZoom = 9, maxZoom = 18)) %>% - #setView(lng=-81.347388, lat=30.075, zoom = 11) %>% + setView(lng=-81.289, lat=29.905, zoom = 11) %>% clearBounds() %>% addTiles() %>% # Add default OpenStreetMap map tiles - addPolygons(color = "purple", fill = NA) #%>% - #addMarkers(lng=-81.347388, lat=30.075, popup="Guana") + addPolygons(color = "purple", fill = NA) %>% + addMarkers(lng=-81.347388, lat=30.075, popup="Guana") m counties_select <- st_read("03_Data_for_app/shapefiles_new/counties_GTMNERR.shp") @@ -43,7 +43,7 @@ HAB_data_locations <- HAB_data %>% distinct() %>% st_as_sf(coords = c("Longitude", "Latitude"), crs = 4326) -leaflet(options = leafletOptions(crs = epsg4326, minZoom = 9, maxZoom = 18)) %>% +leaflet(options = leafletOptions(minZoom = 9, maxZoom = 18)) %>% setView(lng=-81.347388, lat=30.075, zoom = 11) %>% # Base map addTiles() %>% # Add default OpenStreetMap map tiles @@ -56,10 +56,15 @@ leaflet(options = leafletOptions(crs = epsg4326, minZoom = 9, maxZoom = 18)) %>% highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE), group = "Counties", popup = ~NAME) %>% - addMarkers(data = HAB_data_locations, - popup = ~paste("Site: ", Site, "
", - "County: ", County), - group = "HAB") %>% + addAwesomeMarkers(icon = makeAwesomeIcon(icon = "flask", markerColor = "blue", library = "fa", + iconColor = "black"), #"", + data = HAB_data_locations, + #lng= rep(-81.347388, 34), lat = rep(30.075,34) + ) %>% + # addMarkers(data = HAB_data_locations, + # popup = ~paste("Site: ", Site, "
", + # "County: ", County), + # group = "HAB") %>% # # Layers control (turning layers on and off) addLayersControl(overlayGroups = c("Counties", "GTMNERR boundaries", "HAB"), options = layersControlOptions(collapsed = FALSE)) From 7194a2e749017aeaebc38c2c427e6292095a7b34 Mon Sep 17 00:00:00 2001 From: Geraldine Klarenberg Date: Tue, 20 Aug 2024 17:19:21 -0400 Subject: [PATCH 7/9] Put WIN and WQ data together and created new .Rds file --- 02_Cleaning_scripts/WQ_WIN_merge.R | 6 ++++++ 03_Data_for_app/WQ_all.Rds | Bin 135123 -> 138639 bytes 2 files changed, 6 insertions(+) diff --git a/02_Cleaning_scripts/WQ_WIN_merge.R b/02_Cleaning_scripts/WQ_WIN_merge.R index 63325bd..9738bb5 100644 --- a/02_Cleaning_scripts/WQ_WIN_merge.R +++ b/02_Cleaning_scripts/WQ_WIN_merge.R @@ -32,6 +32,12 @@ for (i in 1:nrow(WQ_GTMNERR)){ # Check there are no duplicates sum(duplicated(WQ_GTMNERR$UNID)) +# Add a geometry column, to later use for clicking markers (we might change this) +WQ_GTMNERR <- st_as_sf(WQ_GTMNERR, coords = c("Longitude", "Latitude"), + crs = 4326, remove = FALSE) +# Turn back into dataframe with geometry as a column +WQ_GTMNERR <- as.data.frame(WQ_GTMNERR) + WQ_GTMNERR_long <- WQ_GTMNERR %>% mutate(across(everything(), as.character)) %>% mutate_all(~ na_if(., "")) %>% diff --git a/03_Data_for_app/WQ_all.Rds b/03_Data_for_app/WQ_all.Rds index ca2eb6675c2397832138b0f50444d6961e2866fd..dc4b1c9ed9acd0171a525c5cfa1946d3e39913b1 100644 GIT binary patch literal 138639 zcmeFad0bQ17B<{l+tOYuw6!f&gxFd|MTs*q=C%&B4xmM(2qf15qoPC!5C|k`OO;yG zXc41ANRHpYa&hI$m2Ze>j56t=!{0Iy zAIyJ)EI8@ga}dnK#CJQPw9Nr!fRYF5v*?Bz8qmW<#Ktv+fT9jx=u-@#I~yEilDhj* z+FCin^&G+8{@gkiO&J>8Q{7#|xWw-MciHXQPvU1e2T0bI1mETE`IO?Mm>b6DKo1HZ z1Q!PggL7YI~n)Q&NVqAyY`c~Ss|uPWYm6w-)?+n@<4+c zTG)SR&2sL`h)qaR8_wuq(;#ep>bjn4=Z4P0ZV+@thW7?j*-z5822j~&(?a`nmC)zK zZqydntpez?0n^ip2i6(&#n-SAZZ45*AHga1=sQ_W!q!K{3i*21aTE4Si)K>U?xatl 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Subject: [PATCH 8/9] On the main app page, added icons for the menu on the left. Changed win.R to waterquality.R (main script to use for WQ page) and waterquality.R to waterquality2.R (to keep as a back up). made sure app.R refers to the correct pages. Added awesome markers to main_page.R, and changed the zoom level at which the dashboards starts. --- app.R | 83 +++++------ modules/main_page.R | 65 +++++---- modules/waterquality.R | 295 ++++++++++++++++++++++++++++++++-------- modules/waterquality2.R | 100 ++++++++++++++ modules/win.R | 271 ------------------------------------ 5 files changed, 416 insertions(+), 398 deletions(-) create mode 100644 modules/waterquality2.R delete mode 100644 modules/win.R diff --git a/app.R b/app.R index 39efe18..1d38a62 100644 --- a/app.R +++ b/app.R @@ -1,40 +1,43 @@ -# This is the main app page, which will run and read in all the other pages -# and modules, and render the dashboard - -# Note: not necessary to load packages here: this all happens in global.R - -source("global.R") -source("functions.R") -source("modules/main_page.R") -source("modules/waterquality.R") -source("modules/algae.R") -source("modules/win.R") - -ui <- dashboardPage( - dashboardHeader(title = "Guana River Data Dashboard"), - dashboardSidebar( - sidebarMenu(id = "tabs", - menuItem("Main Page", tabName = "main_page", icon = icon("home")), - menuItem("Water Quality Data", tabName = "waterquality", icon = icon("link")), - menuItem("Harmful Algal Bloom Data", tabName = "algae", icon = icon("link")), - menuItem("Water Information Network", tabName = "win", icon = icon("bridge-water", lib="font-awesome")) - ) - ), - dashboardBody( - tabItems( - tabItem(tabName = "main_page", mainPageUI(id = "main_page")), - tabItem(tabName = "waterquality", WQPageUI(id = "waterquality")), - tabItem(tabName = "algae", HABPageUI(id = "algae")), - tabItem(tabName = "win", WINPageUI(id = "win")) - ) - ) -) - -server <- function(input, output, session) { - moduleServer(module = mainPageServer, id = "main_page", session = session) - WQPageServer("waterquality", parentSession = session) - HABPageServer("algae", parentSession = session) - WINPageServer("win", parentSession = session) -} - -shinyApp(ui, server) +# This is the main app page, which will run and read in all the other pages +# and modules, and render the dashboard + +# Note: not necessary to load packages here: this all happens in global.R + +source("global.R") +source("functions.R") +source("modules/main_page.R") +source("modules/waterquality.R") +source("modules/algae.R") +#source("modules/win.R") + +ui <- dashboardPage( + dashboardHeader(title = "Guana River Data Dashboard"), + dashboardSidebar( + sidebarMenu(id = "tabs", + menuItem("Main Page", tabName = "main_page", icon = icon("home")), + #menuItem("Water Quality Data", tabName = "waterquality", icon = icon("link")), + menuItem("Harmful Algal Bloom Data", tabName = "algae", icon = icon("microscope", lib = "font-awesome")), + menuItem("Water Quality Data", tabName = "waterquality", icon = icon("flask-vial", lib="font-awesome")), + menuItem("Water Level Data", tabName = "waterlevel", icon = icon("water", lib="font-awesome")), + menuItem("Fish and Shellfish Data", tabName = "shellfish", icon = icon("fish", lib="font-awesome")), + menuItem("Terrestrial Animal Data", tabName = "animal", icon = icon("paw", lib="font-awesome")) + ) + ), + dashboardBody( + tabItems( + tabItem(tabName = "main_page", mainPageUI(id = "main_page")), + #tabItem(tabName = "waterquality", WQPageUI(id = "waterquality")), + tabItem(tabName = "algae", HABPageUI(id = "algae")), + tabItem(tabName = "waterquality", WINPageUI(id = "waterquality")) + ) + ) +) + +server <- function(input, output, session) { + moduleServer(module = mainPageServer, id = "main_page", session = session) + #WQPageServer("waterquality", parentSession = session) + HABPageServer("algae", parentSession = session) + WINPageServer("waterquality", parentSession = session) +} + +shinyApp(ui, server) diff --git a/modules/main_page.R b/modules/main_page.R index ea00e84..14d5afc 100644 --- a/modules/main_page.R +++ b/modules/main_page.R @@ -18,10 +18,10 @@ WIN_df <- readRDS("./03_Data_for_app/WIN.Rds") WIN_data_locations = WIN_df %>% filter(variable %in% c("geometry", - "HUC12.Name", - "Start.Date", - "latitude", - "longitude") + "HUC12Name", + "SampleDate", + "Latitude", + "Longitude") ) %>% select(c(RowID, variable, value)) %>% distinct(RowID, variable, value) %>% @@ -30,24 +30,28 @@ WIN_data_locations = WIN_df %>% values_from = value, values_fill = list(value = NA) ) %>% - distinct(geometry, HUC12.Name, Start.Date, latitude, longitude) %>% + distinct(geometry, HUC12Name, SampleDate, Latitude, Longitude) %>% mutate( - lat = as.numeric(latitude), - long = as.numeric(longitude), + SampleDate = ymd_hms(SampleDate), + Latitude = as.numeric(Latitude), + Longitude = as.numeric(Longitude), type = "Water quality", - dataset = "Watershed Information Network (DEP)" + dataset = "Watershed Information Network (DEP)", # Update this so we use data_source + minYear = min(year(SampleDate)), + maxYear = max(year(SampleDate)) ) %>% - select(-geometry, - latitude, -longitude) + select(-geometry, -SampleDate) #### WQ locations data ------------------------------------------------ WQ_data_locations <- readRDS("./03_Data_for_app/WQ_locations.Rds") # For now, for testing, make WQ_locations the dataframe to be used for filtering datasets_location <- full_join(WQ_data_locations, WIN_data_locations) -datasets_location <- st_as_sf(datasets_location, coords = c("long", "lat"), crs = 4326) +datasets_location <- st_as_sf(datasets_location, coords = c("Longitude", "Latitude"), crs = 4326) +datasets_location <- datasets_location[!duplicated(datasets_location),] -color_palette <- colorFactor(palette = c("red"), #, "blue", "green", "purple" - domain = datasets_location$type) +color_palette <- colorFactor(palette = c("red", "goldenrod1"), #, "blue", "green" + domain = datasets_location$dataset) #### HAB locations data ------------------------------------------------ # Add this at some point so there is another dataset that shows up in the dropdown @@ -94,8 +98,8 @@ mainPageServer <- function(input, output, session) { # Create the map output$map <- renderLeaflet({ leaflet(options = leafletOptions(minZoom = 9, maxZoom = 18)) %>% - #setView(lng=-81.347388, lat=30.075, zoom = 11) %>% - clearBounds() %>% # centers map on all min/max coords + setView(-81.289, lat=29.905, zoom = 10) %>% + #clearBounds() %>% # centers map on all min/max coords # Base map addTiles() %>% # Add default OpenStreetMap map tiles # Polygons, add groups @@ -142,25 +146,28 @@ mainPageServer <- function(input, output, session) { observeEvent(input$datatype_selector, { # Filter data based on selected group filtered_data <- datasets_location[datasets_location$type == input$datatype_selector,] - + print(filtered_data) # Add markers to the map - commented out the popup bc this only works for WQ data print("Adding markers") leafletProxy(ns("map")) %>% clearMarkers() %>% - addCircleMarkers( - data = filtered_data, - color = ~color_palette(type), - opacity = 1, - fillOpacity = 0.5, - fillColor = ~color_palette(type), - fill = TRUE, - weight = 3, - radius = 8, - # popup = ~paste("Station: ", site_friendly, "
", - # "Location: ", wbid, "
", - # "Latest year of sampling: ", maxYear, "% + # addCircleMarkers( + # data = filtered_data, + # color = ~color_palette(dataset), + # opacity = 1, + # fillOpacity = 0.5, + # fillColor = ~color_palette(dataset), + # fill = TRUE, + # weight = 3, + # radius = 8, + # popup = ~paste("Station: ", site_friendly, "
", + # "Location: ", wbid, "
", + # "Latest year of sampling: ", maxYear, "% - st_as_sf(coords = c("long", "lat"), crs = 4326) +######################################################################## +########## NERRS Science Transfer project - GTMNERR ############# +######################################################################## -#### WQ data ------------------------------------------------ -WQ <- readRDS("./03_Data_for_app/WQ.Rds") +# Geraldine Klarenberg, PhD +# Email: gklarenberg@ufl.edu +# Christopher Marais +# Email: +# Last updated: 12 August 2024 -WQPageUI <- function(id) { - ns <- NS(id) # This is an important part to add to all sub pages so they use the - # correct sessions / ID's that connect the ui and server here +library(tidyverse) + +# import all WQ data for this page (WIN and Guana spreadsheet) +WQ_df <- readRDS("./03_Data_for_app/WQ_all.Rds") + +#### Process data further #### +# make datframe for map display and hover data +WQ_data_locations = WQ_df %>% + filter(variable %in% c("geometry", # we don't need this? + #"HUC12Name", # Changed for now (bc GTM WQ data does not have that variable) BUT we should also include a station name of some sort + "SampleDate", # changed, from StartDate - but also not necessary for locations + "Latitude", + "Longitude", + "data_source") + ) %>% + #select(c(RowID, variable, value)) %>% # not necessary + #distinct(RowID, variable, value) %>% # not necessary + pivot_wider( + names_from = variable, + values_from = value, + values_fill = list(value = NA) + ) %>% + distinct(Latitude, Longitude, data_source, geometry) %>% + mutate( + Latitude = as.numeric(Latitude), + Longitude = as.numeric(Longitude) + ) + +WQ_data_units = WQ_df %>% + filter(variable %in% c("ComponentLong", # some will be duplicated because they differ between the 2 sets + "Unit", "data_source") + ) %>% + #select(c(RowID, variable, value)) %>% + distinct(RowID, variable, value) %>% # strictly speaking also not necessary + pivot_wider( + names_from = variable, + values_from = value, + values_fill = list(value = NA), + values_fn = list(value = ~ first(.)) + ) %>% + distinct(ComponentLong, Unit, data_source) + +#### Functions #### +# make dataframe for click plots +filter_dataframe <- function(df, filter_value = NULL) { + if (!is.null(filter_value)) { + # Step 1: Identify the relevant RowIDs + relevant_row_ids <- df %>% + filter(value == filter_value) %>% + pull(RowID) + + # Step 2: Filter the entire dataframe to keep only rows with the relevant RowIDs + filtered_df <- df %>% + filter(RowID %in% relevant_row_ids) + } else { + # If no filter_value is provided, skip the filtering step + filtered_df <- df + } + + # Step 3: Create wide dataframe + wide_df <- filtered_df %>% + pivot_wider(names_from = variable, values_from = value) %>% + select(SampleDate, # we could also make these arguments for the function? + ComponentLong, + Result) %>% + pivot_wider(names_from = ComponentLong, + values_from = Result, + values_fn = list(Result = ~ mean(as.numeric(.), na.rm = TRUE))) %>% + mutate(SampleDate = ymd_hms(SampleDate)) %>% # + #mutate(SampleDate = str_extract(SampleDate, "[0-9]{4}-[0-9]{2}-[0-9]{2}")) %>% + #mutate(SampleDate = ymd(SampleDate)) %>% # these two lines are another option to only get ymd + mutate(across(-SampleDate, ~ as.numeric(.))) %>% + mutate(SampleDate = as.Date(SampleDate)) %>% + group_by(SampleDate) %>% + summarize(across(everything(), ~mean(.x, na.rm = TRUE))) %>% + select(where(~ n_distinct(.) > 2)) + + return(wide_df) +} + +# New function to create the dropdown +create_dropdown <- function(df, ns) { + column_names <- sort(colnames(df)[colnames(df) != "SampleDate"]) + print(paste("Creating dropdown with choices:", paste(column_names, collapse=", "))) + + selectInput( + inputId = ns("column_selector"), + label = "Select a Column", + choices = column_names, + selected = column_names[1] + ) +} + +# Modified create_plot function +create_plot <- function(df, units_df, loc_name = "GTMNERR", selected_column) { + print(paste("Creating plot for", selected_column)) + # Initialize the plot with the x-axis + fig <- plot_ly(df, x = ~SampleDate) + + # Get the column names except the one for the x-axis + column_names <- sort(colnames(df)[colnames(df) != "SampleDate"]) + + # Create a named vector for Y-axis titles + y_axis_titles <- setNames(units_df$Unit, units_df$ComponentLong) + + # Ensure selected_column is not NULL or empty + if (is.null(selected_column) || selected_column == "") { + selected_column <- column_names[1] + } + + # Loop through each column and add a trace + for (i in seq_along(column_names)) { + fig <- fig %>% + add_trace(y = df[[column_names[i]]], name = column_names[i], type = 'scatter', mode = 'lines', + showlegend = FALSE, + visible = if (column_names[i] == selected_column) TRUE else FALSE) + } + + # Customize the layout + fig <- fig %>% + layout(xaxis = list(title = 'Date'), + yaxis = list(title = y_axis_titles[selected_column]), + title = paste("Mean ", selected_column, " for ", loc_name)) + + return(fig) +} + + +#### Run the app #### +find_directory_of_file("app.R") + +# Updated UI in WINPageUI +WINPageUI <- function(id) { + ns <- NS(id) tagList( h2("Water Quality Data"), fluidRow( - # Map occupies 1st column - column(width = 7, leafletOutput(ns("map"), height=750)), # make sure to put the input inside ns() - # histogram occupies rows in the 2nd column - column(width = 5, plotOutput(ns("distPlot")), - sliderInput(ns("bins"), "Number of bins:", - min = 1, max = 50, value = 30) - ) + column(width = 7, leafletOutput(ns("map"), height="500px")), + column(width = 5, plotlyOutput(ns("plot"), height="500px")) + ), + fluidRow( + column(width = 12, uiOutput(ns("dropdown_ui"))) ), actionButton(inputId = ns("go_back"), label = "Back to Main Page") ) } -WQPageServer <- function(id, parentSession) { - moduleServer(id, function(input, output, session) { # this nested approach is - # necessary to be able to us the "back" button, otherwise Shiny cannot find - # the id for "tabs" +# Updated Server logic in WINPageServer +WINPageServer <- function(id, parentSession) { + moduleServer(id, function(input, output, session) { ns <- session$ns - - # Create the histogram - output$distPlot <- renderPlot({ - # generate bins based on input$bins from ui.R - x <- filter(WQ, ComponentShort == "ATEMP") %>% - select(Result) %>% - pull() - x <- as.numeric(x) # stop-gap measure because everything is characters - bins <- seq(min(x, na.rm = TRUE), max(x, na.rm = TRUE), - length.out = input$bins + 1 - ) - - # draw the histogram with the specified number of bins - hist(x, - breaks = bins, col = "darkgray", border = "white", - xlab = "Air temperature (degrees Celsius)", - main = "Histogram of air temperatures" - ) + + # Reactive value for the selected column + selected_column <- reactive({ + print(paste("Selected column changed to:", input$column_selector)) + input$column_selector }) - + + # Reactive value to track popup bubble state + popup_visible <- reactiveVal(FALSE) + + # Create the dropdown UI + output$dropdown_ui <- renderUI({ + print("Rendering dropdown UI") + df <- filter_dataframe(WQ_df) + create_dropdown(df, ns) + }) + + # Update plot when dropdown selection changes + observeEvent(selected_column(), { + print(paste("Updating plot for", selected_column())) + output$plot <- renderPlotly({ + df <- filter_dataframe(WQ_df) + create_plot(df, units_df = WQ_data_units, selected_column = selected_column()) + }) + }, ignoreInit = FALSE) + + # Default plot + output$plot <- renderPlotly({ + df <- filter_dataframe(WQ_df) + create_plot(df, units_df = WQ_data_units, selected_column = selected_column()) + }) + # Create the map output$map <- renderLeaflet({ leaflet(options = leafletOptions(minZoom = 9, maxZoom = 18)) %>% - # setView(lng=-81.347388, lat=30.075, zoom = 11) %>% - clearBounds() %>% # centers map on all min/max coords - # Base map - addTiles() %>% # Add default OpenStreetMap map tiles - # Polygons, add groups + clearBounds() %>% + addTiles() %>% addPolygons( data = GTMNERR, color = "purple", fill = NA, weight = 2, opacity = 1, group = "GTMNERR boundaries" @@ -69,32 +208,72 @@ WQPageServer <- function(id, parentSession) { color = "white", weight = 2, bringToFront = TRUE ), - group = "Counties", popup = ~NAME + group = "Counties", popup = ~NAME, layerId = ~NAME ) %>% - # addMarkers(data = HAB_data_locations, - # popup = ~paste("Site: ", Site, "
", - # "County: ", County), - # group = "HAB") %>% addMarkers( data = WQ_data_locations, - popup = ~ paste( - "Station: ", site_friendly, "
", - "Location: ", wbid, "
", - "Latest year of sampling: ", maxYear, ""#, #changed from HUC12Name + #"Start Date: ", SampleDate, "
" ), - group = "WQ" + group = "WQ", + layerId = ~geometry ) %>% - # # Layers control (turning layers on and off) addLayersControl( overlayGroups = c("Counties", "GTMNERR boundaries", "WQ"), options = layersControlOptions(collapsed = FALSE) ) %>% addMeasure(primaryLengthUnit = "miles", primaryAreaUnit = "sqmiles") }) - + + # Observe marker clicks + observeEvent(input$map_marker_click, { + click <- input$map_marker_click + if (!is.null(click)) { + clicked_id <- click$id + clicked_data <- WQ_data_locations %>% + filter(geometry == clicked_id) #GK: I don't think this is a great approach, as + # geometry is a specific "thing" for sf objects, so it has specific meaning. And + # that is not how we are using it here + + popup_visible(TRUE) + + output$plot <- renderPlotly({ + df <- filter_dataframe(WQ_df, filter_value = clicked_data$RowID) # Changed from HUC12.Name + create_plot(df, units_df = WQ_data_units, loc_name = clicked_data$RowID, selected_column = selected_column()) + }) + } + }) + + # Add observeEvent function for input$map_shape_click + observeEvent(input$map_shape_click, { + click <- input$map_shape_click + if (!is.null(click)) { + clicked_id <- click$id + clicked_data <- counties_select %>% + filter(NAME == clicked_id) + + popup_visible(TRUE) + + output$plot <- renderPlotly({ + df <- filter_dataframe(WQ_df, filter_value = clicked_data$NAME) + create_plot(df, units_df = WQ_data_units, loc_name = clicked_data$NAME, selected_column = selected_column()) + }) + } + }) + + # Observe map clicks to hide the popup + observeEvent(input$map_click, { + popup_visible(FALSE) + + # Default plot + output$plot <- renderPlotly({ + df <- filter_dataframe(WQ_df) + create_plot(df, units_df = WQ_data_units, selected_column = selected_column()) + }) + }) + observeEvent(input$go_back, { updateTabItems(session = parentSession, inputId = "tabs", selected = "main_page") }) }) -} \ No newline at end of file +} diff --git a/modules/waterquality2.R b/modules/waterquality2.R new file mode 100644 index 0000000..813c5bb --- /dev/null +++ b/modules/waterquality2.R @@ -0,0 +1,100 @@ +#### WQ locations data ------------------------------------------------ +WQ_locations <- readRDS("./03_Data_for_app/WQ_locations.Rds") +WQ_data_locations <- WQ_locations %>% + st_as_sf(coords = c("Longitude", "Latitude"), crs = 4326) + +#### WQ data ------------------------------------------------ +WQ <- readRDS("./03_Data_for_app/WQ.Rds") + +WQPageUI <- function(id) { + ns <- NS(id) # This is an important part to add to all sub pages so they use the + # correct sessions / ID's that connect the ui and server here + tagList( + h2("Water Quality Data"), + fluidRow( + # Map occupies 1st column + column(width = 7, leafletOutput(ns("map"), height=750)), # make sure to put the input inside ns() + # histogram occupies rows in the 2nd column + column(width = 5, plotOutput(ns("distPlot")), + sliderInput(ns("bins"), "Number of bins:", + min = 1, max = 50, value = 30) + ) + ), + actionButton(inputId = ns("go_back"), label = "Back to Main Page") + ) +} + +WQPageServer <- function(id, parentSession) { + moduleServer(id, function(input, output, session) { # this nested approach is + # necessary to be able to us the "back" button, otherwise Shiny cannot find + # the id for "tabs" + ns <- session$ns + + # Create the histogram + output$distPlot <- renderPlot({ + # generate bins based on input$bins from ui.R + x <- filter(WQ, ComponentShort == "ATEMP") %>% + select(Result) %>% + pull() + x <- as.numeric(x) # stop-gap measure because everything is characters + bins <- seq(min(x, na.rm = TRUE), max(x, na.rm = TRUE), + length.out = input$bins + 1 + ) + + # draw the histogram with the specified number of bins + hist(x, + breaks = bins, col = "darkgray", border = "white", + xlab = "Air temperature (degrees Celsius)", + main = "Histogram of air temperatures" + ) + }) + + # Create the map + output$map <- renderLeaflet({ + leaflet(options = leafletOptions(minZoom = 9, maxZoom = 18)) %>% + # setView(lng=-81.347388, lat=30.075, zoom = 11) %>% + clearBounds() %>% # centers map on all min/max coords + # Base map + addTiles() %>% # Add default OpenStreetMap map tiles + # Polygons, add groups + addPolygons( + data = GTMNERR, color = "purple", fill = NA, + weight = 2, opacity = 1, group = "GTMNERR boundaries" + ) %>% + addPolygons( + data = counties_select, + color = "black", weight = 2, opacity = 1, + fill = TRUE, fillColor = "white", fillOpacity = 0.01, + highlightOptions = highlightOptions( + color = "white", weight = 2, + bringToFront = TRUE + ), + group = "Counties", popup = ~NAME + ) %>% + # addMarkers(data = HAB_data_locations, + # popup = ~paste("Site: ", Site, "
", + # "County: ", County), + # group = "HAB") %>% + addMarkers( + data = WQ_data_locations, + popup = ~ paste( + "Station: ", site_friendly, "
", + "Location: ", wbid, "
", + "Latest year of sampling: ", maxYear, "% + # # Layers control (turning layers on and off) + addLayersControl( + overlayGroups = c("Counties", "GTMNERR boundaries", "WQ"), + options = layersControlOptions(collapsed = FALSE) + ) %>% + addMeasure(primaryLengthUnit = "miles", primaryAreaUnit = "sqmiles") + }) + + observeEvent(input$go_back, { + updateTabItems(session = parentSession, inputId = "tabs", selected = "main_page") + }) + }) +} \ No newline at end of file diff --git a/modules/win.R b/modules/win.R deleted file mode 100644 index 409747b..0000000 --- a/modules/win.R +++ /dev/null @@ -1,271 +0,0 @@ -######################################################################## -########## NERRS Science Transfer project - GTMNERR ############# -######################################################################## - -# Geraldine Klarenberg, PhD -# Email: gklarenberg@ufl.edu -# Christopher Marais -# Email: -# Last updated: 12 August 2024 - -# import all WQ data for this page (WIN and Guana spreadsheet) -WQ_df <- readRDS("./03_Data_for_app/WQ_all.Rds") - -#### Process data further #### -# make datframe for map display and hover data -WQ_data_locations = WQ_df %>% - filter(variable %in% c("geometry", - "HUC12.Name", - "Start.Date", - "latitude", - "longitude") - ) %>% - select(c(RowID, variable, value)) %>% - distinct(RowID, variable, value) %>% - pivot_wider( - names_from = variable, - values_from = value, - values_fill = list(value = NA) - ) %>% - distinct(geometry, HUC12.Name, Start.Date, latitude, longitude) %>% - mutate( - latitude = as.numeric(latitude), - longitude = as.numeric(longitude) - ) - -WQ_data_units = WQ_df %>% - filter(variable %in% c("DEP.Analyte.Name", - "DEP.Result.Unit") - ) %>% - select(c(RowID, variable, value)) %>% - distinct(RowID, variable, value) %>% - pivot_wider( - names_from = variable, - values_from = value, - values_fill = list(value = NA), - values_fn = list(value = ~ first(.)) - ) %>% - distinct(DEP.Analyte.Name, DEP.Result.Unit) - -#### Functions #### -# make dataframe for click plots -filter_dataframe <- function(df, filter_value = NULL) { - if (!is.null(filter_value)) { - # Step 1: Identify the relevant RowIDs - relevant_row_ids <- df %>% - filter(value == filter_value) %>% - pull(RowID) - - # Step 2: Filter the entire dataframe to keep only rows with the relevant RowIDs - filtered_df <- df %>% - filter(RowID %in% relevant_row_ids) - } else { - # If no filter_value is provided, skip the filtering step - filtered_df <- df - } - - # Step 3: Create wide dataframe - wide_df <- filtered_df %>% - pivot_wider(names_from = variable, values_from = value) %>% - select(Activity.Start.Date.Time, - DEP.Analyte.Name, - Org.Result.Value) %>% - pivot_wider(names_from = DEP.Analyte.Name, - values_from = Org.Result.Value, - values_fn = list(Org.Result.Value = ~ mean(as.numeric(.), na.rm = TRUE))) %>% - mutate(Activity.Start.Date.Time = ymd_hms(Activity.Start.Date.Time)) %>% - mutate(across(-Activity.Start.Date.Time, ~ as.numeric(.))) %>% - mutate(Activity.Start.Date.Time = as.Date(Activity.Start.Date.Time)) %>% - group_by(Activity.Start.Date.Time) %>% - summarize(across(everything(), ~mean(.x, na.rm = TRUE))) %>% - select(where(~ n_distinct(.) > 2)) - - return(wide_df) -} - -# New function to create the dropdown -create_dropdown <- function(df, ns) { - column_names <- sort(colnames(df)[colnames(df) != "Activity.Start.Date.Time"]) - print(paste("Creating dropdown with choices:", paste(column_names, collapse=", "))) - - selectInput( - inputId = ns("column_selector"), - label = "Select a Column", - choices = column_names, - selected = column_names[1] - ) -} - -# Modified create_plot function -create_plot <- function(df, units_df, loc_name = "GTMNERR", selected_column) { - print(paste("Creating plot for", selected_column)) - # Initialize the plot with the x-axis - fig <- plot_ly(df, x = ~Activity.Start.Date.Time) - - # Get the column names except the one for the x-axis - column_names <- sort(colnames(df)[colnames(df) != "Activity.Start.Date.Time"]) - - # Create a named vector for Y-axis titles - y_axis_titles <- setNames(units_df$DEP.Result.Unit, units_df$DEP.Analyte.Name) - - # Ensure selected_column is not NULL or empty - if (is.null(selected_column) || selected_column == "") { - selected_column <- column_names[1] - } - - # Loop through each column and add a trace - for (i in seq_along(column_names)) { - fig <- fig %>% - add_trace(y = df[[column_names[i]]], name = column_names[i], type = 'scatter', mode = 'lines', - visible = if (column_names[i] == selected_column) TRUE else FALSE) - } - - # Customize the layout - fig <- fig %>% - layout(xaxis = list(title = 'Date'), - yaxis = list(title = y_axis_titles[selected_column]), - title = paste("Mean ", selected_column, " for ", loc_name)) - - return(fig) -} - - -#### Run the app #### -find_directory_of_file("app.R") - -# Updated UI in WINPageUI -WINPageUI <- function(id) { - ns <- NS(id) - tagList( - h2("Water Information Network"), - fluidRow( - column(width = 7, leafletOutput(ns("map"), height="500px")), - column(width = 5, plotlyOutput(ns("plot"), height="500px")) - ), - fluidRow( - column(width = 12, uiOutput(ns("dropdown_ui"))) - ), - actionButton(inputId = ns("go_back"), label = "Back to Main Page") - ) -} - -# Updated Server logic in WINPageServer -WINPageServer <- function(id, parentSession) { - moduleServer(id, function(input, output, session) { - ns <- session$ns - - # Reactive value for the selected column - selected_column <- reactive({ - print(paste("Selected column changed to:", input$column_selector)) - input$column_selector - }) - - # Reactive value to track popup bubble state - popup_visible <- reactiveVal(FALSE) - - # Create the dropdown UI - output$dropdown_ui <- renderUI({ - print("Rendering dropdown UI") - df <- filter_dataframe(WQ_df) - create_dropdown(df, ns) - }) - - # Update plot when dropdown selection changes - observeEvent(selected_column(), { - print(paste("Updating plot for", selected_column())) - output$plot <- renderPlotly({ - df <- filter_dataframe(WQ_df) - create_plot(df, units_df = WQ_data_units, selected_column = selected_column()) - }) - }, ignoreInit = FALSE) - - # Default plot - output$plot <- renderPlotly({ - df <- filter_dataframe(WQ_df) - create_plot(df, units_df = WQ_data_units, selected_column = selected_column()) - }) - - # Create the map - output$map <- renderLeaflet({ - leaflet(options = leafletOptions(minZoom = 9, maxZoom = 18)) %>% - clearBounds() %>% - addTiles() %>% - addPolygons( - data = GTMNERR, color = "purple", fill = NA, - weight = 2, opacity = 1, group = "GTMNERR boundaries" - ) %>% - addPolygons( - data = counties_select, - color = "black", weight = 2, opacity = 1, - fill = TRUE, fillColor = "white", fillOpacity = 0.01, - highlightOptions = highlightOptions( - color = "white", weight = 2, - bringToFront = TRUE - ), - group = "Counties", popup = ~NAME, layerId = ~NAME - ) %>% - addMarkers( - data = WQ_data_locations, - popup = ~ paste("Station Name: ", HUC12.Name, "
", - "Start Date: ", Start.Date, "
" - ), - group = "WQ", - layerId = ~geometry - ) %>% - addLayersControl( - overlayGroups = c("Counties", "GTMNERR boundaries", "WQ"), - options = layersControlOptions(collapsed = FALSE) - ) %>% - addMeasure(primaryLengthUnit = "miles", primaryAreaUnit = "sqmiles") - }) - - # Observe marker clicks - observeEvent(input$map_marker_click, { - click <- input$map_marker_click - if (!is.null(click)) { - clicked_id <- click$id - clicked_data <- WQ_data_locations %>% - filter(geometry == clicked_id) - - popup_visible(TRUE) - - output$plot <- renderPlotly({ - df <- filter_dataframe(WQ_df, filter_value = clicked_data$HUC12.Name) - create_plot(df, units_df = WQ_data_units, loc_name = clicked_data$HUC12.Name, selected_column = selected_column()) - }) - } - }) - - # Add observeEvent function for input$map_shape_click - observeEvent(input$map_shape_click, { - click <- input$map_shape_click - if (!is.null(click)) { - clicked_id <- click$id - clicked_data <- counties_select %>% - filter(NAME == clicked_id) - - popup_visible(TRUE) - - output$plot <- renderPlotly({ - df <- filter_dataframe(WQ_df, filter_value = clicked_data$NAME) - create_plot(df, units_df = WQ_data_units, loc_name = clicked_data$NAME, selected_column = selected_column()) - }) - } - }) - - # Observe map clicks to hide the popup - observeEvent(input$map_click, { - popup_visible(FALSE) - - # Default plot - output$plot <- renderPlotly({ - df <- filter_dataframe(WQ_df) - create_plot(df, units_df = WQ_data_units, selected_column = selected_column()) - }) - }) - - observeEvent(input$go_back, { - updateTabItems(session = parentSession, inputId = "tabs", selected = "main_page") - }) - }) -} From 505a3b334cc242012728d90e6f6bf7b56664d319 Mon Sep 17 00:00:00 2001 From: Geraldine Klarenberg Date: Wed, 21 Aug 2024 15:10:33 -0400 Subject: [PATCH 9/9] Added more icons to the menubar on the left --- app.R | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/app.R b/app.R index 1d38a62..13da537 100644 --- a/app.R +++ b/app.R @@ -19,8 +19,9 @@ ui <- dashboardPage( menuItem("Harmful Algal Bloom Data", tabName = "algae", icon = icon("microscope", lib = "font-awesome")), menuItem("Water Quality Data", tabName = "waterquality", icon = icon("flask-vial", lib="font-awesome")), menuItem("Water Level Data", tabName = "waterlevel", icon = icon("water", lib="font-awesome")), - menuItem("Fish and Shellfish Data", tabName = "shellfish", icon = icon("fish", lib="font-awesome")), - menuItem("Terrestrial Animal Data", tabName = "animal", icon = icon("paw", lib="font-awesome")) + menuItem("Fish, Shellfish & Other Aquatic Organisms Data", tabName = "shellfish", icon = icon("fish", lib="font-awesome")), + menuItem("Terrestrial Animal Data", tabName = "animal", icon = icon("paw", lib="font-awesome")), + menuItem("Vegetation Data", tabName = "animal", icon = icon("seedling", lib="font-awesome")) ) ), dashboardBody(

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