bhoover59 / diurnals

Create diurnal trend for field campaign data along with some other useful functions

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, TimeColumn = time_column_name)

Future work:

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