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