Package 'medacoPlot'

Title: Renders plots of medaco csv data
Description: Plot power input and output.
Authors: Joerg Sesterhenn [aut, cre]
Maintainer: Joerg Sesterhenn <[email protected]>
License: MIT + file LICENSE
Version: 0.1.1
Built: 2024-11-24 13:28:54 UTC
Source: https://github.com/joergsesterhenn/medaco-plot

Help Index

Get List of Files in Directory

Description

Retrieves a list of all .CSV files in the specified directory.

Usage

get_files_in_path(data_path)

Arguments

data_path

Character string specifying the directory path to search.

Value

A character vector of file paths for .CSV files in the directory.

Examples

get_files_in_path("data/")

Get Hourly Data in Long Format

Description

Aggregates and reshapes the data by hour, returning it in a long format.

Usage

get_hourly_data_long(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A data frame with hourly total_input and total_output values.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
       as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
       as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
       as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
       as.POSIXct("2000-02-02 02:00:00", tz = "UTC")),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
get_hourly_data_long(power_data)

Get Hourly and Monthly Data in Long Format

Description

Aggregates and reshapes the data by both hour and month, returning it.

Usage

get_hourly_monthly_data_long(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A data frame with hourly and monthly values.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
       as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
       as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
       as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
       as.POSIXct("2000-02-02 02:00:00", tz = "UTC")),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
get_hourly_monthly_data_long(power_data)

Get Monthly Data in Long Format

Description

Aggregates and reshapes the data by month, returning it in a long format.

Usage

get_monthly_data_long(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A data frame with monthly total_input and total_output values.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
       as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
       as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
       as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
       as.POSIXct("2000-02-02 02:00:00", tz = "UTC")),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
get_monthly_data_long(power_data)

Get Monthly Data in Long Format

Description

Aggregates and reshapes the data by year, returning it in a long format.

Usage

get_yearly_data_long(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A data frame with yearly total_input and total_output values.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
       as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
       as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
       as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
       as.POSIXct("2000-02-02 02:00:00", tz = "UTC")),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
get_monthly_data_long(power_data)

Pivot Data to Long Format for Input and Output

Description

Transforms data from a wide format to a long format, creating separate rows for total_input and total_output.

Usage

pivot_longer_data(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A data frame in long format with a type column indicating input or output, and a value column for the corresponding values.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
       as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
       as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
       as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
       as.POSIXct("2000-02-02 02:00:00", tz = "UTC")),
  total_input = c(1.0, 2.0, 3.0, 4.0),
  total_output = c(4.0, 3.0, 2.0, 1.0)
)
pivot_longer_data(power_data)

Generic Plot Function

Description

Selects a plot function based on the specified type and plots the dataset.

Usage

plot(plot_type, power_data)

Arguments

plot_type

Character, the plot type from the dropdown menu.
power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object created by the appropriate plotting function.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
    as.POSIXct("2000-02-02 02:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot("by month", power_data)

Plot Aggregated Data by Hour

Description

Generates a bar plot showing hourly input and output sums.

Usage

plot_aggregated_by_hour(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object showing hourly aggregated values.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
    as.POSIXct("2000-02-02 02:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot_aggregated_by_hour(power_data)

Plot Aggregated Data by Month

Description

Generates a bar plot showing monthly input and output sums.

Usage

plot_aggregated_by_month(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object showing monthly aggregated values.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
    as.POSIXct("2000-02-02 02:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot_aggregated_by_month(power_data)

Plot Aggregated Data by Year

Description

Generates a bar plot showing yearly input and output sums.

Usage

plot_aggregated_by_year(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object showing yearly aggregated values.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
    as.POSIXct("2000-02-02 02:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot_aggregated_by_year(power_data)

Plot Hourly Data by Month

Description

Generates a bar plot showing hourly input and output sums by month.

Usage

plot_by_hour_and_month(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object showing hourly values by month in facets.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
    as.POSIXct("2000-02-02 02:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot_by_hour_and_month(power_data)

Generate a Heatmap of Hourly Data by Month

Description

Creates a heatmap to show hourly input and output data across months.

Usage

plot_heatmap(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object with a heatmap representing input/output.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-01 02:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 02:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot_heatmap(power_data)

Generate a Line Chart of Hourly Data by Month

Description

Creates a line chart to show input/output data by hour for each month.

Usage

plot_line_chart(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object with a line chart.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-01 02:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 02:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot_line_chart(power_data)

Map of Dropdown Items to Plot Functions

Description

A data frame mapping dropdown box items to corresponding plot functions.

Usage

plot_map

Format

A data frame with dropdown items as row names and plot function names as column values.

Generate a Ridgeline Plot of Hourly Data by Month

Description

Creates a ridgeline plot to show distribution of input/output data by month.

Usage

plot_ridgeline(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object with a ridgeline plot.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-02-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-02-02 01:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot_ridgeline(power_data)

Generate a Stacked Area Chart of Hourly Data by Month

Description

Creates a stacked area chart to visualize input/output data by month.

Usage

plot_stacked_area(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object with a stacked area chart.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-02-01 02:00:00", tz = "UTC"),
    as.POSIXct("2000-02-02 02:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot_stacked_area(power_data)

Generate a Bar Chart of top 10 days of power input vs output

Description

Creates a Bar Chart and also displays mean and percentile values.

Usage

plot_top_days(power_data)

Arguments

power_data

data frame with timestamp, INPUT, and OUTPUT columns.

Value

A ggplot object with a line chart.

Examples

# Example using a small sample data frame
power_data <- data.frame(
  timestamp = c(
    as.POSIXct("2000-01-01 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 01:00:00", tz = "UTC"),
    as.POSIXct("2000-01-01 02:00:00", tz = "UTC"),
    as.POSIXct("2000-01-02 02:00:00", tz = "UTC")
  ),
  INPUT = c(1.0, 2.0, 3.0, 4.0),
  OUTPUT = c(4.0, 3.0, 2.0, 1.0)
)
plot_top_days(power_data)

Read Power Data

Description

Reads power data from .CSV files in the specified directory, selecting specific columns and using a custom locale for decimal and grouping marks.

Usage

read_power_data(data_path)

Arguments

data_path

Character string specifying the directory containing .CSV files to read.

Value

A data frame containing timestamp, input, and output columns from the files.

Examples

read_power_data("data/")