R/data download/carpenter_2016.r

In chase-lab/BioTIMEx: Aggregating long-term ecological communities data

## carpenter_2016

# Package ID: knb-lter-ntl.355.4 Cataloging System:https://pasta.edirepository.org.
# Data set title: Cascade Project at North Temperate Lakes LTER Core Data Zooplankton 1984 - 2016.
# Data set creator:  Stephen Carpenter - University of Wisconsin
# Data set creator:  Jim Kitchell - University of Wisconsin
# Data set creator:  Jon Cole - Cary Institute of Ecosystem Studies
# Data set creator:  Mike Pace - University of Virginia
# Contact:  Stephen Carpenter -  University of Wisconsin  - steve.carpenter@wisc.edu
# Contact:  Mike Pace -  University of Virginia  - pacem@virginia.edu
# Contact:  NTL Information Manager -  University of Wisconsin  - ntl.infomgr@gmail.com
# Stylesheet v2.10 for metadata conversion into program: John H. Porter, Univ. Virginia, jporter@virginia.edu



infile1 <- 'data/raw data/carpenter_2016/cascade_zooplankton_v0.5_upload.csv'
if(!dir.exists('data/raw data/carpenter_2016/') || !file.exists(infile1))   {
   dir.create('data/raw data/carpenter_2016/', showWarnings = FALSE)
   inUrl1  <- "https://pasta.lternet.edu/package/data/eml/knb-lter-ntl/355/4/8084d8a30424cbf3feb4f69621e6c0a1"
   download.file(inUrl1, infile1, method="curl")
}


dt1 <-read.csv(infile1,header=F
               ,skip=1
               ,sep=","
               ,quot='"'
               , col.names=c(
                  "lakeid",
                  "lakename",
                  "year4",
                  "daynum",
                  "sampledate",
                  "standard_taxon_code",
                  "group_code",
                  "taxon_name",
                  "number_per_net",
                  "mean_length",
                  "mean_individ_biomass",
                  "net_efficiency_measured",
                  "net_efficiency_mean",
                  "abundance_raw",
                  "abundance",
                  "biomass"    ), check.names=TRUE)


# Fix any interval or ratio columns mistakenly read in as nominal and nominal columns read as numeric or dates read as strings

if (class(dt1$lakeid)!="factor") dt1$lakeid<- as.factor(dt1$lakeid)
if (class(dt1$lakename)!="factor") dt1$lakename<- as.factor(dt1$lakename)
if (class(dt1$year4)=="factor") dt1$year4 <-as.numeric(levels(dt1$year4))[as.integer(dt1$year4) ]
if (class(dt1$year4)=="character") dt1$year4 <-as.numeric(dt1$year4)
if (class(dt1$daynum)=="factor") dt1$daynum <-as.numeric(levels(dt1$daynum))[as.integer(dt1$daynum) ]
if (class(dt1$daynum)=="character") dt1$daynum <-as.numeric(dt1$daynum)
# attempting to convert dt1$sampledate dateTime string to R date structure (date or POSIXct)
tmpDateFormat<-"%Y-%m-%d"
tmp1sampledate<-as.Date(dt1$sampledate,format=tmpDateFormat)
# Keep the new dates only if they all converted correctly
if(length(tmp1sampledate) == length(tmp1sampledate[!is.na(tmp1sampledate)])){dt1$sampledate <- tmp1sampledate } else {print("Date conversion failed for dt1$sampledate. Please inspect the data and do the date conversion yourself.")}
rm(tmpDateFormat,tmp1sampledate)
if (class(dt1$standard_taxon_code)!="factor") dt1$standard_taxon_code<- as.factor(dt1$standard_taxon_code)
if (class(dt1$group_code)!="factor") dt1$group_code<- as.factor(dt1$group_code)
if (class(dt1$taxon_name)!="factor") dt1$taxon_name<- as.factor(dt1$taxon_name)
if (class(dt1$number_per_net)=="factor") dt1$number_per_net <-as.numeric(levels(dt1$number_per_net))[as.integer(dt1$number_per_net) ]
if (class(dt1$number_per_net)=="character") dt1$number_per_net <-as.numeric(dt1$number_per_net)
if (class(dt1$mean_length)=="factor") dt1$mean_length <-as.numeric(levels(dt1$mean_length))[as.integer(dt1$mean_length) ]
if (class(dt1$mean_length)=="character") dt1$mean_length <-as.numeric(dt1$mean_length)
if (class(dt1$mean_individ_biomass)=="factor") dt1$mean_individ_biomass <-as.numeric(levels(dt1$mean_individ_biomass))[as.integer(dt1$mean_individ_biomass) ]
if (class(dt1$mean_individ_biomass)=="character") dt1$mean_individ_biomass <-as.numeric(dt1$mean_individ_biomass)
if (class(dt1$net_efficiency_measured)=="factor") dt1$net_efficiency_measured <-as.numeric(levels(dt1$net_efficiency_measured))[as.integer(dt1$net_efficiency_measured) ]
if (class(dt1$net_efficiency_measured)=="character") dt1$net_efficiency_measured <-as.numeric(dt1$net_efficiency_measured)
if (class(dt1$net_efficiency_mean)=="factor") dt1$net_efficiency_mean <-as.numeric(levels(dt1$net_efficiency_mean))[as.integer(dt1$net_efficiency_mean) ]
if (class(dt1$net_efficiency_mean)=="character") dt1$net_efficiency_mean <-as.numeric(dt1$net_efficiency_mean)
if (class(dt1$abundance_raw)=="factor") dt1$abundance_raw <-as.numeric(levels(dt1$abundance_raw))[as.integer(dt1$abundance_raw) ]
if (class(dt1$abundance_raw)=="character") dt1$abundance_raw <-as.numeric(dt1$abundance_raw)
if (class(dt1$abundance)=="factor") dt1$abundance <-as.numeric(levels(dt1$abundance))[as.integer(dt1$abundance) ]
if (class(dt1$abundance)=="character") dt1$abundance <-as.numeric(dt1$abundance)
if (class(dt1$biomass)=="factor") dt1$biomass <-as.numeric(levels(dt1$biomass))[as.integer(dt1$biomass) ]
if (class(dt1$biomass)=="character") dt1$biomass <-as.numeric(dt1$biomass)

# Convert Missing Values to NA for non-dates

dt1$number_per_net <- ifelse((trimws(as.character(dt1$number_per_net))==trimws("NA")),NA,dt1$number_per_net)
dt1$mean_length <- ifelse((trimws(as.character(dt1$mean_length))==trimws("NA")),NA,dt1$mean_length)
dt1$mean_individ_biomass <- ifelse((trimws(as.character(dt1$mean_individ_biomass))==trimws("NA")),NA,dt1$mean_individ_biomass)
dt1$net_efficiency_measured <- ifelse((trimws(as.character(dt1$net_efficiency_measured))==trimws("NA")),NA,dt1$net_efficiency_measured)
dt1$net_efficiency_mean <- ifelse((trimws(as.character(dt1$net_efficiency_mean))==trimws("NA")),NA,dt1$net_efficiency_mean)
dt1$abundance_raw <- ifelse((trimws(as.character(dt1$abundance_raw))==trimws("NA")),NA,dt1$abundance_raw)
dt1$abundance <- ifelse((trimws(as.character(dt1$abundance))==trimws("NA")),NA,dt1$abundance)
dt1$biomass <- ifelse((trimws(as.character(dt1$biomass))==trimws("NA")),NA,dt1$biomass)


ddata <- dt1
save(ddata, file = 'data/raw data/carpenter_2016/ddata')





if( FALSE ) {
      # Here is the structure of the input data frame:
      str(dt1)
      attach(dt1)
      # The analyses below are basic descriptions of the variables. After testing, they should be replaced.

      summary(lakeid)
      summary(lakename)
      summary(year4)
      summary(daynum)
      summary(sampledate)
      summary(standard_taxon_code)
      summary(group_code)
      summary(taxon_name)
      summary(number_per_net)
      summary(mean_length)
      summary(mean_individ_biomass)
      summary(net_efficiency_measured)
      summary(net_efficiency_mean)
      summary(abundance_raw)
      summary(abundance)
      summary(biomass)
      detach(dt1)

}