Telemetry Reports - Imports
Overview
Teaching: 10 min
Exercises: 0 minQuestions
What datasets do I need from the Node?
How do I import all the datasets?
Objectives
Importing all the datasets
Now that we have an idea of what an exploratory workflow might look like with Tidyverse libraries like dplyr and ggplot2, let’s look at how we might implement a common telemetry workflow using these tools.
View(lamprey_dets) #already have our Lamprey tag matches
#import walleye dets
walleye_dets <- read_csv("inst_extdata_walleye_detections.csv", guess_max = 9595) #remember guess_max from prev section!
#Warning: 9595 parsing failures.
#row col expected actual file
#3047 sensor_value 1/0/T/F/TRUE/FALSE 11 'inst_extdata_walleye_detections.csv'
#3047 sensor_unit 1/0/T/F/TRUE/FALSE ADC 'inst_extdata_walleye_detections.csv'
#3048 sensor_value 1/0/T/F/TRUE/FALSE 11 'inst_extdata_walleye_detections.csv'
#3048 sensor_unit 1/0/T/F/TRUE/FALSE ADC 'inst_extdata_walleye_detections.csv'
#3049 sensor_value 1/0/T/F/TRUE/FALSE 11 'inst_extdata_walleye_detections.csv'
#lets join these two detection files together!
all_dets <- rbind(lamprey_dets, walleye_dets)
# lets import GLATOS receiver station data for the whole network
glatos_receivers <- read_csv("inst_extdata_sample_receivers.csv")
View(glatos_receivers)
#Lets import our workbook now!
library(readxl)
walleye_deploy <- read_excel('inst_extdata_walleye_workbook.xlsm', sheet = 'Deployment') #pull in deploy
View(walleye_deploy)
walleye_recovery <- read_excel('inst_extdata_walleye_workbook.xlsm', sheet = 'Recovery') #pull in recovery
View(walleye_recovery)
#join the deploy and recovery sheets together
walleye_recovery <- walleye_recovery %>% rename(INS_SERIAL_NO = INS_SERIAL_NUMBER) #first, rename INS_SERIAL_NUMBER
walleye_recievers = merge(walleye_deploy, walleye_recovery,
by.x = c("GLATOS_PROJECT", "GLATOS_ARRAY", "STATION_NO",
"CONSECUTIVE_DEPLOY_NO", "INS_SERIAL_NO"),
by.y = c("GLATOS_PROJECT", "GLATOS_ARRAY", "STATION_NO",
"CONSECUTIVE_DEPLOY_NO", "INS_SERIAL_NO"),
all.x=TRUE, all.y=TRUE) #keep all the info from each, merged using the above columns
View(walleye_recievers)
#need Tagging metadata too!
walleye_tag <- read_excel('inst_extdata_walleye_workbook.xlsm', sheet = 'Tagging')
View(walleye_tag)
#remember: we learned how to switch timezone of datetime columns above,
# if that is something you need to do with your dataset!!
#hint: check GLATOS_TIMEZONE column to see if its what you want!
#the glatos R package (will be reviewed in the workshop tomorrow) can import your workbook in one step
#will format all datetimes to UTC, check for conflicts, join the deploy/recovery tabs etc.
library(glatos) #this won't work unless you happen to have this installed - just an teaser today, will be covered tomorrow
data <- read_glatos_workbook('inst_extdata_walleye_workbook.xlsm')
receivers <- data$receivers
animals <- data$animals
Key Points