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MOBCAT

About Me

Create diurnal trend for field campaign data. Functions automatically convert string times and characters.

Installation

If you need to install devtools

install.packages("devtools")
library(devtools)

Installing diurnals package

devtools::install_github("bhoover59/diurnals")

Or if that doesn't work

remotes::install_github("bhoover59/diurnals")

To remove the package go to Packages in RStudio and hit X on right side. If that doesn't work, try this

remove.packages("diurnals")

Or if that doesn't work

detach("package:diurnals", unload = TRUE)
unloadNamespace("diurnals")

Diurnal

  1. Inputs
    • df: data frame with field campaign data
    • TimeColumn: name of column with times. Can be any string format. Edit char_to_time function if additional formats needed
  2. Outputs:
    • diurnal average
    • diurnal median
    • standard deviation for each bin
    • count for each bin
    • DOES NOT CALCULATE SEM but that can easily be done by SEM = sd / sqrt(count)
diurnal <- Diurnal(df = df_name, TimeColumn = time_column_name)

DiurnalAvg

  1. Inputs
    • df: data frame with field campaign data
    • TimeColumn: name of column with times. Can be any string format. Edit char_to_time function if additional formats needed
  2. Outputs:
    • diurnal average
    • standard deviation for each bin
    • count for each bin
    • DOES NOT CALCULATE SEM but that can easily be done by SEM = sd / sqrt(count)
diurnal_average <- DiurnalAvg(df = df_name, TimeColumn = time_column_name)

DiurnalMed

  1. Inputs
    • df: data frame with field campaign data
    • TimeColumn: name of column with times. Can be any string format. Edit char_to_time function if additional formats needed
  2. Outputs:
    • diurnal median
    • standard deviation for each bin
    • count for each bin
    • DOES NOT CALCULATE SEM but that can easily be done by SEM = sd / sqrt(count)
diurnal_median <- DiurnalMed(df = df_name, TimeColumn = time_column_name)

time_average

  1. Inputs
    • df: data frame with field campaign data
    • interval: time step interval in minutes to average
    • TimeColumn: name of column with times. Can be any string format. Edit char_to_time function if additional formats needed
  2. Outputs:
    • averaged data frame by input in minutes
averaged_df <- time_average(df = df_name, interval = interval_minutes, time_column = 'time_column_name')

Future work:

  • Calculate standard error mean (SEM)
  • Bin size for time_average