Title: The Fisheries Scientist's Toolbox
Version: 1.2.3
Description: A bundle of analytics tools for fisheries scientists. A 'shiny' R App is included for a 'no-code' solution for retrieval, analysis, and visualization.
License: AGPL (≥ 3)
Depends: R (≥ 2.10)
Imports: config (≥ 0.3.1), countrycode, dplyr, ggplot2, golem (≥ 0.3.3), httr, jsonlite, maps, sf, shiny (≥ 1.7.1), shinyBS, shinyjs, shinyWidgets, stats, utils, viridis
Suggests: testthat (≥ 3.0.0)
Config/testthat/edition: 3
Encoding: UTF-8
RoxygenNote: 7.2.3
Date: 2024-03-26
URL: https://github.com/Shyentist/fish-r-man
BugReports: https://github.com/Shyentist/fish-r-man/issues
NeedsCompilation: no
Packaged: 2024-03-26 17:21:59 UTC; pico
Author: Pasquale Buonomo ORCID iD [cre, aut]
Maintainer: Pasquale Buonomo <pasqualebuonomo@hotmail.it>
Repository: CRAN
Date/Publication: 2024-03-26 23:00:06 UTC

Check the type of dataframe in relation to fishRman

Description

Function to check the type of dataframe in relation to fishRman. Most of the times the user will not call this function directly, but it can be useful for debug.

Usage

df.type(df)

Arguments

df

The dataframe to check.

Value

A string explaining how the input dataframe is treated by fishRman.

Examples


dated <- c("2020-01-01", "2020-01-02")
lat <- c(40, 41)
lon <- c(12,13)
mmsi <- c("34534555", "25634555")
hours <- c(0, 5)
fishing_hours <- c(1,9)

df <- data.frame(dated, lat, lon, mmsi, hours, fishing_hours)

what.type <- df.type(df)

print(what.type)

# "GFW Fishing Effort By Vessel"

Summarize GFW data on fishing effort

Description

Wrapper function for 'dplyr::summarise()' that summarizes GFW data into the most important measures of central tendency for fishing_hours and hours, creating a new dataframe. It will have one (or more) rows for each combination of grouping variables; if there are no grouping variables, the output will have a single row summarising all observations in the input.

Usage

gfw.summarize(df)

Arguments

df

A dataframe object as downloaded from GFW's Google Big Data Query.

Value

A dataframe.

See Also

[dplyr::summarise()] [dplyr::group_by()]

Examples


dated <- c("2020-01-01", "2020-01-02")
lat <- c(40, 41)
lon <- c(12,13)
mmsi <- c("34534555", "25634555")
hours <- c(0, 5)
fishing_hours <- c(1,9)

df <- data.frame(dated, lat, lon, mmsi, hours, fishing_hours)

summary <- gfw.summarize(df)

print(summary)

Run the Shiny Application

Description

Run the Shiny Application

Usage

run_app(
  onStart = NULL,
  options = list(),
  enableBookmarking = NULL,
  uiPattern = "/",
  ...
)

Arguments

onStart

A function that will be called before the app is actually run. This is only needed for shinyAppObj, since in the shinyAppDir case, a global.R file can be used for this purpose.

options

Named options that should be passed to the runApp call (these can be any of the following: "port", "launch.browser", "host", "quiet", "display.mode" and "test.mode"). You can also specify width and height parameters which provide a hint to the embedding environment about the ideal height/width for the app.

enableBookmarking

Can be one of "url", "server", or "disable". The default value, NULL, will respect the setting from any previous calls to enableBookmarking(). See enableBookmarking() for more information on bookmarking your app.

uiPattern

A regular expression that will be applied to each GET request to determine whether the ui should be used to handle the request. Note that the entire request path must match the regular expression in order for the match to be considered successful.

...

arguments to pass to golem_opts. See '?golem::get_golem_options' for more details.

Value

Does not return a value. This function launches the embedded Shiny application, making it accessible through a web browser. The user interacts with the Shiny app through the browser interface.

Subset the top percent of a dataframe by a specific column

Description

Function that sorts a dataframe in descending order for a specific column, calculates the sum of all rows for that column, applies the chosen percentage to said sum, and subsets the minimum number of consecutive rows needed to reach this value.

Usage

top.percent.by(df, percentage, by)

Arguments

df

A dataframe object as downloaded from GFW's Google Big Data Query.

percentage

Number. The 'x' in 'the top x percent of the dataframe'.

by

Character. The name of the column for which the percentage will be calculated.

Value

A dataframe.

Examples


dated <- c("2020-01-01", "2020-01-02")
lat <- c(40, 41)
lon <- c(12,13)
mmsi <- c("34534555", "25634555")
hours <- c(0, 5)
fishing_hours <- c(1,9)

df <- data.frame(dated, lat, lon, mmsi, hours, fishing_hours)

who.fishs.the.most <- top.percent.by(df, 90, "fishing_hours")

print(who.fishs.the.most)