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

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")

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)

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)

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)

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')

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