| Title: | Graphical Displays for Structured Problem Solving and Diagnosis |
| Version: | 0.7.0 |
| Description: | Powerful graphical displays and statistical tools for structured problem solving and diagnosis. The functions of the 'sherlock' package are especially useful for applying the process of elimination as a problem diagnosis technique. The 'sherlock' package was designed to seamlessly work with the 'tidyverse' set of packages and provides a collection of graphical displays built on top of the 'ggplot' and 'plotly' packages, such as different kinds of small multiple plots as well as helper functions such as adding reference lines, normalizing observations, reading in data or saving analysis results in an Excel file. References: David Hartshorne (2019, ISBN: 978-1-5272-5139-7). Stefan H. Steiner, R. Jock MacKay (2005, ISBN: 0873896467). |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.0 |
| URL: | https://github.com/gaboraszabo/sherlock, https://gaboraszabo.github.io/sherlock/ |
| BugReports: | https://github.com/gaboraszabo/sherlock/issues |
| Imports: | magrittr, rlang (≥ 0.4.11), forcats, ggplot2, dplyr, tidyr, cowplot, scales, ggh4x, stringr, plotly, readr, openxlsx, purrr, fs, rstudioapi, tidytext |
| Suggests: | roxygen2 |
| Depends: | R (≥ 2.10) |
| LazyData: | true |
| NeedsCompilation: | no |
| Packaged: | 2023-06-11 23:37:47 UTC; gabor |
| Author: | Gabor Szabo [aut, cre] |
| Maintainer: | Gabor Szabo <gabor.attila.szabo@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2023-06-11 23:50:02 UTC |
Pipe operator
Description
See magrittr::%>% for details.
Usage
lhs %>% rhs
Arguments
lhs |
A value or the magrittr placeholder. |
rhs |
A function call using the magrittr semantics. |
Value
The result of calling rhs(lhs).
Create Project Folder
Description
Creates a project folder on your computer
Usage
create_project_folder(folder_name, path, subfolders = "generic")
Arguments
folder_name |
Set name of the folder. Examples: "Analysis_20221212", "01_application" (required) |
path |
Set path for folder. Example: "R/Projects/" (required) |
subfolders |
Set type of subfolder structure. Options are "generic" or "shiny". The "generic" option has the following subfolders: "01_data", "02_reports", "03_images", "04_scripts" and "05_misc". The "shiny" option has the following subfolders: "data", "css", "wwww", "images" and "scripts". By default, it is set to "generic". (optional) |
Value
A project folder and sub-folder structure and corresponding .Rproj file on your computer
Draw Cartesian Small Multiples Plot
Description
Draws a cartesian small multiples plot
Usage
draw_cartesian_small_multiples(
data,
x_coord,
y_coord,
grouping_var,
faceting_var_1,
faceting_var_2,
interactive = FALSE,
size = 2,
alpha = 0.4,
analysis_desc_label = NULL,
x_axis_label = NULL,
y_axis_label = NULL,
n_breaks_x_axis = 10,
n_breaks_y_axis = 10,
accuracy = 0.001,
show_axis_values = TRUE
)
Arguments
data |
Input dataset to be plotted (required) |
x_coord |
Column for X coordinate values (required) |
y_coord |
Column for Y coordinate values (required) |
grouping_var |
Grouping variable. Each group is displayed in a different color. (optional) |
faceting_var_1 |
Set first faceting variable (optional) |
faceting_var_2 |
Set second faceting variable (optional) |
interactive |
Set plot interactivity. By default, it is set to FALSE (optional) |
size |
Set point size. By default, it is set to 2 (optional) |
alpha |
Set transparency. By default, it is set to 0.4 (optional) |
analysis_desc_label |
Label (subtitle) for analysis description. By default, it is set to NULL (optional) |
x_axis_label |
Label for x axis. By default, it is set to display x axis column name (optional) |
y_axis_label |
Label for y axis. By default, it is set to display y axis column name (optional) |
n_breaks_x_axis |
Set number of breaks on X axis. By default, it is set to 10 (optional) |
n_breaks_y_axis |
Set number of breaks on Y axis. By default, it is set to 10 (optional) |
accuracy |
Set number of decimal places to be displayed on X and Y axes. Examples: 0.1 - one decimal place, 0.01 - two decimal places, 0.001 - three decimal places etc. By default, it is set to 0.001 (optional) |
show_axis_values |
Logical. if FALSE, default, axis values are not shown (optional) |
Value
A 'ggplot' or 'plotly' object
Draw Categorical Scatter Plot
Description
Draws a Categorical Scatter Plot
Usage
draw_categorical_scatterplot(
data,
y_var,
grouping_var_1,
grouping_var_2,
grouping_var_3,
grouping_var_4,
plot_means = FALSE,
connect_means = FALSE,
group_color = FALSE,
point_size = 2,
alpha = 0.5,
jitter = FALSE,
x_axis_text_size = 11,
panel_text_size = 11
)
Arguments
data |
Input dataset to be plotted (required) |
y_var |
Y variable to be plotted on Y axis (required) |
grouping_var_1 |
Select column for lowest level grouping variable (optional) |
grouping_var_2 |
Select column for second level grouping variable (optional) |
grouping_var_3 |
Select column for third level grouping variable (optional) |
grouping_var_4 |
Select column for fourth level grouping variable (optional) |
plot_means |
Logical. if TRUE, means for lowest-level grouping variable are plotted. By default, it is set to FALSE. (optional) |
connect_means |
Logical. if TRUE, means for lowest-level grouping variable are connected with a line. By default, it is set to FALSE. (optional) |
group_color |
Set whether to color by grouping_var_1. By default, it is set to FALSE (optional) |
point_size |
Set point size. By default, it is set to 2 (optional) |
alpha |
Set transparency. By default, it is set to 0.5 (optional) |
jitter |
Set whether to add jitter. By default, it is set to FALSE (optional) |
x_axis_text_size |
Set X axis text size. By default, it is set to 11 (optional) |
panel_text_size |
Set panel text size. By default, it is set to 11 (optional) |
Value
A 'ggplot' object
Examples
multi_vari_data_2 %>%
draw_categorical_scatterplot(y_var = Length,
grouping_var_1 = Part,
grouping_var_2 = Operator,
jitter = FALSE)
Draw horizontal reference line
Description
Draws a horizontal reference line or multiple reference lines to plots
Usage
draw_horizontal_reference_line(
reference_line,
color = "grey",
linetype = "dashed",
size = 0.7
)
Arguments
reference_line |
input y coordinate of reference line(s). for multiple reference lines, concatenate individual values into a vector (required) |
color |
change reference line color. options are "grey", "blue" and "red". by default, it is set to "grey" (optional) |
linetype |
change line type. identical to linetype ggplot2 aesthetic. by default, it is set to "dashed" (optional) |
size |
change line thickness. identical to size ggplot2 aesthetic. by default, it is set to 0.7 (optional) |
Value
A horizontal reference line plotted on top of a 'ggplot' object
Draw Interaction Plot
Description
Draws an Interaction Plot
Usage
draw_interaction_plot(
data,
y_var,
x_var_1_levels,
x_var_2_levels,
point_size = 4,
line_size = 1,
alpha = 0.5,
analysis_desc_label = NULL
)
Arguments
data |
input dataset to be plotted (required) |
y_var |
Y variable to be plotted on Y axis (required) |
x_var_1_levels |
First grouping variable levels, e.g. -1/1 or "low"/"high" (required) |
x_var_2_levels |
Second grouping variable levels, e.g. -1/1 or "low"/"high" (required) |
point_size |
Set point size. By default, it is set to 4 (optional) |
line_size |
Set line size. By default, it is set to 1 (optional) |
alpha |
Set transparency. By default, it is set to 0.5 (optional) |
analysis_desc_label |
analysis_desc_label Label (subtitle) for analysis description. By default, it is set to NULL (optional) |
Value
A 'ggplot' object
Draw Multivari Plot
Description
Draws a multivari small multiples plot
Usage
draw_multivari_plot(
data,
y_var,
grouping_var_1,
grouping_var_2,
grouping_var_3,
grouping_var_4,
data_point_label = NULL,
plot_means = FALSE,
x_axis_text_size = 11,
panel_text_size = 14,
point_size = 2.5,
line_size = 0.7,
alpha = 0.6
)
Arguments
data |
Input dataset to be plotted (required) |
y_var |
Response variable, Y (required) |
grouping_var_1 |
Select column for lowest level grouping variable (required) |
grouping_var_2 |
Select column for second level grouping variable (required) |
grouping_var_3 |
Select column for third level grouping variable (optional) |
grouping_var_4 |
Select column for fourth level grouping variable (optional) |
data_point_label |
Select column to label data points (optional) |
plot_means |
Logical. if FALSE, default, means for mid-level factor are not plotted (optional) |
x_axis_text_size |
Set X axis text size. By default, it is set to 11 (optional) |
panel_text_size |
Set panel text size. By default, it is set to 14 (optional) |
point_size |
Set point size. By default, it is set to 2.5 (optional) |
line_size |
Set line size. By default, it is set to 0.7 (optional) |
alpha |
Set transparency. By default, it is set to 0.6 (optional) |
Value
A 'ggplot' object
Examples
library(dplyr)
library(ggh4x)
polar_small_multiples_data %>%
filter(ID_Measurement_Angle %in% c(0, 45, 90, 135)) %>%
normalize_observations(y_var = ID,
grouping_var = Tip_Bottom,
ref_values = c(0.2075, 0.2225)) %>%
draw_multivari_plot(y_var = ID_normalized,
grouping_var_1 = ID_Measurement_Angle,
grouping_var_2 = Mold_Cavity_Number,
grouping_var_3 = Tip_Bottom,
x_axis_text = 6) +
draw_horizontal_reference_line(reference_line = 0)
Draw Multivari Plot for Counts
Description
Draws a multivari small multiples plot for count data
Usage
draw_multivari_plot_count(
data,
y_var,
grouping_var_1,
grouping_var_2,
grouping_var_3,
grouping_var_4,
x_axis_text_size = 11,
panel_text_size = 14,
alpha = 0.6
)
Arguments
data |
Input dataset to be plotted (required) |
y_var |
Response variable, Y (required) |
grouping_var_1 |
Select column for lowest level grouping variable (required) |
grouping_var_2 |
Select column for second level grouping variable (required) |
grouping_var_3 |
Select column for third level grouping variable (optional) |
grouping_var_4 |
Select column for fourth level grouping variable (optional) |
x_axis_text_size |
Set X axis text size. By default, it is set to 11 (optional) |
panel_text_size |
Set panel text size. By default, it is set to 14 (optional) |
alpha |
Set transparency. By default, it is set to 0.6 (optional) |
Value
A 'ggplot' object
Draw Pareto Chart
Description
Draws a Pareto Chart
Usage
draw_pareto_chart(
data,
cat_var,
summarize = FALSE,
continuous_var,
drop_na = TRUE,
highlight_first_n_items = 0,
lump_last_n_items = 0,
lumped_cat_name = "Other",
column_fill = scale_fill_sherlock(3),
scale = "numeric",
accuracy = 1,
title_label = "Pareto Chart",
analysis_desc_label = NULL,
axis_text_size = 10
)
Arguments
data |
input dataset to be plotted (required) |
cat_var |
Categorical variable (required) |
summarize |
Logical. If FALSE, default, the function expects total counts of each category of the categorical variable. If TRUE, individual values within each category are automatically summed up and ranked. (required) |
continuous_var |
Continuous variable to rank by (e.g. sum, frequency etc.). Not required if summarize argument is set to TRUE. (required) |
drop_na |
Logical. If TRUE, default, NA values of the categorical variable are dropped. (required) |
highlight_first_n_items |
Specify the top n items to be highlighted. By default, it is set to 0. (optional) |
lump_last_n_items |
Specify the last n items to be lumped into one category. By default, it is set to 0. (optional) |
lumped_cat_name |
Name lumped category. By default, it is set to "Other". (optional) |
column_fill |
Column fill color. By default, it is set to scale_fill_sherlock(3) (optional) |
scale |
Specify an acceptable argument for scale. Acceptable arguments are "numeric", "percent", "dollar", "dollar-k" or "dollar-M". By default, it is set to "numeric" (optional) |
accuracy |
Number to round to. Default value is set to 1. If NULL, values will be rounded to the nearest integer. (optional) |
title_label |
Specify plot title. By default, it is set to display "Pareto Chart" (optional) |
analysis_desc_label |
Specify plot analysis desc label (subtitle). By default, it is set to display CONTINUOUS VARIABLE COLUMN NAME "by" CATEGORICAL VARIABLE COLUMN NAME (optional) |
axis_text_size |
Set axis text size. By default, it is set at 10. (optional) |
Value
A 'ggplot' object
Draw Grouped Pareto Chart
Description
Draws a small multiples type of Pareto Chart grouped by a categorical variable
Usage
draw_pareto_chart_grouped(
data,
cat_var,
grouping_var,
summarize = FALSE,
continuous_var,
drop_na = TRUE,
highlight_first_n_items = 0,
lump_last_n_items = 0,
lumped_cat_name = "Other",
color = "one",
scale = "numeric",
accuracy = 1,
title_label = "Pareto Chart",
analysis_desc_label = NULL,
axis_text_size = 10,
x_axis_span = "free"
)
Arguments
data |
input dataset to be plotted (required) |
cat_var |
Categorical variable (required) |
grouping_var |
Grouping variable (required) |
summarize |
Logical. If FALSE, default, the function expects total counts of each category of the categorical variable. If TRUE, individual values within each category are automatically summed up and ranked. (required) |
continuous_var |
Continuous variable to rank by (e.g. sum, frequency etc.). Not required if summarize argument is set to TRUE. (required) |
drop_na |
Logical. If TRUE, default, NA values of the categorical variable are dropped. (required) |
highlight_first_n_items |
Specify the top n items to be highlighted. By default, it is set to 0. (optional) |
lump_last_n_items |
Specify the last n items to be lumped into one category. By default, it is set to 0. (optional) |
lumped_cat_name |
Name lumped category. By default, it is set to "Other". (optional) |
color |
Set panel fill color for facets. Options are "one" (one color) or "multi" (each panel is a different color). By default, it is set to "one". (optional) |
scale |
Specify an acceptable argument for scale. Acceptable arguments are "numeric", "percent", "dollar", "dollar-k" or "dollar-M". By default, it is set to "numeric" (optional) |
accuracy |
Number to round to. Default value is set to 1. If NULL, values will be rounded to the nearest integer. (optional) |
title_label |
Specify plot title. By default, it is set to display "Pareto Chart" (optional) |
analysis_desc_label |
Specify plot analysis desc label (subtitle). By default, it is set to display CONTINUOUS VARIABLE COLUMN NAME "by" CATEGORICAL VARIABLE COLUMN NAME (optional) |
axis_text_size |
Set axis text size. By default, it is set at 10. (optional) |
x_axis_span |
Set X axis span. Options are "free" (a different span for each panel based on range of values for each panel) and "fixed" (the X axes in all panels are set to span the total range of all values). By default, it is set to "free". (optional) |
Value
A 'ggplot' object
Draw Polar Small Multiples
Description
Draws a Polar Small Multiples Plot
Usage
draw_polar_small_multiples(
data,
angular_axis,
x_y_coord_axis,
grouping_var,
faceting_var_1,
faceting_var_2,
connect_with_lines = FALSE,
connect_start_and_end_points = TRUE,
x_y_coord_axis_limits = c(0, NA),
point_size = 2,
line_size = 0.6,
point_alpha = 0.6,
line_alpha = 0.5,
label_text_size = 11,
analysis_desc_label = ""
)
Arguments
data |
input dataset to be plotted (required) |
angular_axis |
angular coordinate values (required) |
x_y_coord_axis |
x-y coordinate values (required) |
grouping_var |
grouping variable (required) |
faceting_var_1 |
Set first faceting variable (optional) |
faceting_var_2 |
Set second faceting variable (optional) |
connect_with_lines |
Logical. If set to TRUE, values within each group are connected with a line. By default, it is set to FALSE (optional) |
connect_start_and_end_points |
Logical. If set to TRUE, the start and end points of the lines get connected. It is useful when trying to draw a complete circle but may not be useful when only trying to draw a shape different than that (e.g. a semicircle). By default, it is set to TRUE (optional) |
x_y_coord_axis_limits |
Set x-y coordinate axis limits. By default, it is set to start at 0. (optional) |
point_size |
Set point size. By default, it is set to 2 (optional) |
line_size |
Set line size. By default, it is set to 0.6 (optional) |
point_alpha |
Set point transparency. By default, it is set to 0.6 (optional) |
line_alpha |
Set line transparency. By default, it is set to 0.5 (optional) |
label_text_size |
Size of text for labels. By default, it is set to 11. (optional) |
analysis_desc_label |
Label (subtitle) for analysis description. By default, it is set to NULL. (optional) |
Value
A 'ggplot' object
Examples
library(dplyr)
polar_small_multiples_data %>%
filter(Mold_Cavity_Number %in% c(4, 6)) %>%
draw_polar_small_multiples(angular_axis = ID_Measurement_Angle,
x_y_coord_axis = ID_2,
grouping_var = Tip_Bottom,
faceting_var_1 = Mold_Cavity_Number,
point_size = 0.5,
connect_with_lines = TRUE,
label_text_size = 7)
Draw Process Behavior Chart
Description
Draws a Process Behavior Chart
Usage
draw_process_behavior_chart(
data,
y_var,
grouping_var,
limits = TRUE,
interactive = TRUE
)
Arguments
data |
input dataset to be plotted (required) |
y_var |
Y variable to be plotted on Y axis (required) |
grouping_var |
Variable to group by (optional) |
limits |
Logical. If TRUE, natural process limits (control limits) are plotted. By default, it is set to FALSE (optional) |
interactive |
Set plot interactivity. By default, it is set to TRUE (optional) |
Value
A 'ggplot' or 'plotly' object
Draw Small Multiples Line Plot
Description
Draws a Small Multiples Line Plot
Usage
draw_small_multiples_line_plot(
data,
x_axis_var,
y_axis_var,
grouping_var,
faceting_var_1,
faceting_var_2,
plot_max_values = FALSE,
lowest_highest_units,
unique_color_by_group = FALSE,
size = 0.7,
alpha = 0.4,
interactive = TRUE,
analysis_desc_label = NULL,
x_axis_label = NULL,
y_axis_label = NULL,
n_breaks_x_axis = 10,
n_breaks_y_axis = 10,
accuracy = 0.01
)
Arguments
data |
input dataset to be plotted (required) |
x_axis_var |
variable to be plotted on x axis (required) |
y_axis_var |
variable to be plotted on x axis (required) |
grouping_var |
set grouping variable (required) |
faceting_var_1 |
Set first faceting variable (optional) |
faceting_var_2 |
Set second faceting variable (optional) |
plot_max_values |
Highlights maximum values per group. By default, it is set to FALSE (optional) |
lowest_highest_units |
takes a vector of strings corresponding to the lowest/highest units to be highlighted (optional) |
unique_color_by_group |
set whether to display each group in a unique color. By default, it is set to FALSE (optional) |
size |
Set line size. By default, it is set to 0.7 (optional) |
alpha |
Set transparency. By default, it is set to 0.4 (optional) |
interactive |
set plot interactivity. By default, it is set to TRUE (optional) |
analysis_desc_label |
Label (subtitle) for analysis description. By default, it is set to NULL (optional) |
x_axis_label |
Label for x axis. By default, it is set to display x axis column name (optional) |
y_axis_label |
Label for y axis. By default, it is set to display y axis column name (optional) |
n_breaks_x_axis |
Set number of breaks on X axis. By default, it is set to 10 (optional) |
n_breaks_y_axis |
Set number of breaks on Y axis. By default, it is set to 10 (optional) |
accuracy |
Set number of decimal places to be displayed on X and Y axes. Examples: 0.1 - one decimal place, 0.01 - two decimal places, 0.001 - three decimal places etc. By default, it is set to 0.01 (optional) |
Value
A 'ggplot' or 'plotly' object
Draw Timeseries Scatterplot
Description
Draws a Timeseries Scatterplot
Usage
draw_timeseries_scatterplot(
data,
y_var,
grouping_var_1,
grouping_var_1_type = "date-time",
grouping_var_2,
faceting = FALSE,
limits = FALSE,
date_breaks = "1 month",
date_labels = "%b %y",
analysis_desc_label = NULL,
x_axis_text_size = 11,
point_size = 1,
alpha = 0.3,
line_size = 1,
interactive = TRUE
)
Arguments
data |
input dataset to be plotted (required) |
y_var |
Y variable to be plotted on Y axis (required) |
grouping_var_1 |
Time variable to be plotted on x axis (required) |
grouping_var_1_type |
Time variable type. Options are "date-time" or "factor" |
grouping_var_2 |
Additional variable for faceting (optional) |
faceting |
Set whether to display each group in a separate plot. By default, it is set to FALSE (optional) |
limits |
Logical. If TRUE, process behavior chart control limits for the individual group means are plotted. By default, it is set to FALSE (optional) |
date_breaks |
Set date breaks. Takes a string, for example "1 week" or "2 days". By default, it is set to "1 month" (optional) |
date_labels |
Set date labels. Identical to the date labels argument of the scale_x_date() ggplot function (optional) |
analysis_desc_label |
Label (subtitle) for analysis description. By default, it is set to NULL (optional) |
x_axis_text_size |
X axis text size. By default, it is set to 11. (optional) |
point_size |
Set point size. By default, it is set to 1 (optional) |
alpha |
Set transparency for individual observations. Identical to the alpha ggplot argument. By default, it is set to 0.3 (optional) |
line_size |
Set line size. By default, it is set to 1 (optional) |
interactive |
Set plot interactivity. By default, it is set to TRUE (optional) |
Value
A 'ggplot' or 'plotly' object
Examples
timeseries_scatterplot_data %>%
draw_timeseries_scatterplot(y_var = y,
grouping_var_1 = date,
grouping_var_2 = cavity,
faceting = TRUE,
limits = TRUE,
alpha = 0.15,
line_size = 0.5,
x_axis_text = 7,
interactive = FALSE)
Draw vertical reference line
Description
Draws a vertical reference line or multiple reference lines to plots
Usage
draw_vertical_reference_line(
reference_line,
color = "grey",
linetype = "dashed",
size = 0.7
)
Arguments
reference_line |
input x coordinate of reference line(s). for multiple reference lines, concatenate individual values into a vector (required) |
color |
change reference line color. options are "grey", "blue" and "red". by default, it is set to "grey" (optional) |
linetype |
change line type. identical to linetype ggplot2 aesthetic. by default, it is set to "dashed" (optional) |
size |
change line thickness. identical to size ggplot2 aesthetic. by default, it is set to 0.7 (optional) |
Value
A vertical reference line plotted on top of 'ggplot' object
Draw Youden Plot
Description
Draws a Youden Plot
Usage
draw_youden_plot(
data,
x_axis_var,
y_axis_var,
grouping_var,
lsl,
usl,
median_line = FALSE,
size = 2,
alpha = 0.4,
analysis_desc_label = NULL,
x_axis_label = NULL,
y_axis_label = NULL
)
Arguments
data |
input dataset to be plotted (required) |
x_axis_var |
variable to be plotted on x axis (required) |
y_axis_var |
variable to be plotted on x axis (required) |
grouping_var |
grouping variable (optional) |
lsl |
lower specification limit (optional) |
usl |
upper specification limit (optional) |
median_line |
logical. If TRUE, a median bias line is plotted. By default, it is set to FALSE (optional) |
size |
Set point size. By default, it is set to 2 (optional) |
alpha |
Set transparency. By default, it is set to 0.4 (optional) |
analysis_desc_label |
Label (subtitle) for analysis description. By default, it is set to NULL (optional) |
x_axis_label |
Label for x axis. By default, it is set to display x axis column name (optional) |
y_axis_label |
Label for y axis. By default, it is set to display y axis column name (optional) |
Value
A 'ggplot' object
Examples
youden_plot_data %>%
draw_youden_plot(x_axis_var = measurement_1,
y_axis_var = measurement_2,
grouping_var = location)
youden_plot_data_2 %>%
draw_youden_plot(x_axis_var = gage_1,
y_axis_var = gage_2,
median_line = TRUE)
Load File
Description
Reads either an .xlsx or a .csv file into a table
Usage
load_file(path, filetype = ".xlsx", col_names = TRUE)
Arguments
path |
path for the file (required) |
filetype |
set whether to read an .xlsx file or a .csv file. It takes either ".xlsx" or ".csv". By default, it is set to ".xlsx" (optional) |
col_names |
Either TRUE, FALSE or a character vector of column names. If TRUE, the first row of the input will be used as the column names, and will not be included in the data frame. If FALSE, column names will be generated automatically: X1, X2, X3 etc. If col_names is a character vector, the values will be used as the names of the columns, and the first row of the input will be read into the first row of the output data frame. |
Value
Returns data in the form of a tibble object.
Load Files
Description
Reads a series of either .xlsx or .csv files into a table. Particularly useful when reading in multiple files having the same variables, for example reading in data from an experiment where data was logged and saved separately for each individual unit. Integration of a custom data cleaning function.
Usage
load_files(
folder,
filetype = ".csv",
data_cleaning_function = NULL,
id_by_filename = FALSE,
id_col_name = "index"
)
Arguments
folder |
Folder where the files to be read in are located (required) |
filetype |
Set whether to read in .xlsx or .csv files. It takes either ".xlsx" or ".csv". By default, it is set to ".csv" (required) |
data_cleaning_function |
Add a custom data cleaning function built for individual files. Use no brackets when referencing the function, for example clean_data_from_data_logger. The function being added must be saved in the environment (optional) |
id_by_filename |
Logical. If set to TRUE, the output will contain a column, storing the name of each file being read in. Ideally, the names of the individual files should be pertinent to their content, e.g. if 20 files are being read in with experimental data from parts 1 through 20, the files should be named 1-20. (optional) |
id_col_name |
Specify a name for the .id column. By default, it is set to "index" (optional) |
Value
Returns data in the form of a tibble object.
Multivari Plot Sample Dataset 1
Description
Contains a sample Multivari Plot dataset
Usage
multi_vari_data
Format
An object of class tbl_df (inherits from tbl, data.frame) with 18 rows and 4 columns.
Examples
multi_vari_data
Multi-Vari Plot Sample Dataset 2
Description
Contains a sample Multi-Vari Plot dataset
Usage
multi_vari_data_2
Format
An object of class tbl_df (inherits from tbl, data.frame) with 54 rows and 4 columns.
Examples
multi_vari_data_2
Normalize observations
Description
This function takes an input dataset and normalizes observations
Usage
normalize_observations(data, y_var, grouping_var, ref_values)
Arguments
data |
input dataset to be plotted (required) |
y_var |
response variable, Y (required) |
grouping_var |
select grouping variable to normalize by (required) |
ref_values |
add reference (nominal) values. takes a string of values with values appearing in the same order as in grouping variable. string length must be equal to unique values in grouping variable (required) |
Value
A tibble object with observations normalized and saved in a new column.
Examples
library(dplyr)
polar_small_multiples_data %>%
filter(ID_Measurement_Angle %in% c(0, 45, 90, 135)) %>%
normalize_observations(y_var = ID,
grouping_var = Tip_Bottom,
ref_values = c(0.2075, 0.2225))
Plot Tukey-Duckworth Paired Test
Description
Plots Tukey-Duckworth Paired Test
Usage
plot_tukey_duckworth_paired_test(data, y_var, x_vars, arrows = FALSE)
Arguments
data |
input dataset (required) |
y_var |
Y variable of interest (required) |
x_vars |
X variables of interest (required) |
arrows |
Set whether to display arrows in the plot. By default, it is set to FALSE (optional) |
Value
A 'ggplot' object
Plot Tukey-Duckworth Test
Description
Plots Tukey-Duckworth Paired Test
Usage
plot_tukey_duckworth_test(
data,
y_var,
x_var_levels,
point_size = 3,
point_type = "solid",
split_levels = FALSE,
analysis_desc_label = NULL
)
Arguments
data |
input dataset (required) |
y_var |
Y variable of interest (required) |
x_var_levels |
Levels of X variable of interest (required) |
point_size |
Set point size. By default, it is set to 3. (optional) |
point_type |
Set point size. Options are "solid" (default) and "no fill". (optional) |
split_levels |
Set whether to plot the two levels in separately on the X axis. By default, it is set to FALSE (optional) |
analysis_desc_label |
Label (subtitle) for analysis description. By default, it is set to NULL (optional) |
Value
A 'ggplot' object
Polar Small Multiples Sample Dataset
Description
Contains a sample dataset to demonstrate the use of Polar Small Multiples plot
Usage
polar_small_multiples_data
Format
An object of class tbl_df (inherits from tbl, data.frame) with 144 rows and 5 columns.
Examples
polar_small_multiples_data
Save Analysis
Description
Saves analysis results, both data and plot, into an .xlsx file
Usage
save_analysis(data, plot, filename, filepath)
Arguments
data |
Data to be saved (required) |
plot |
Plot to be saved (optional) |
filename |
Name of the Excel file in a string format without the .xlsx extension. Example: "analysis_results" (required) |
filepath |
Path for the file. Example: "Documents/" (required) |
Value
An Excel file
Sherlock Color Palettes
Description
Set color scheme to one of the Sherlock color palettes
Usage
scale_color_sherlock(palette = 1)
Arguments
palette |
color palette to be used (required). options are 1, 2 and 3 (2 and 3 are only one color for no grouping). by default it is set to 1. |
Value
A 'ggplot' color scheme that uses one of the Sherlock color palettes
Sherlock Fill Color Palettes
Description
Set fill color scheme to one of the Sherlock color palettes
Usage
scale_fill_sherlock(palette = 1)
Arguments
palette |
fill color palette to be used (required). options are 1, 2 and 3 (2 and 3 are only one color for no grouping). by default it is set to 1. |
Value
A 'ggplot' color scheme that uses one of the Sherlock color fill palettes
Select Low-High Units
Description
Automatically selects low-high units in a tibble as well as assigns them into groups
Usage
select_low_high_units(data, var, number_of_pairs)
Arguments
data |
input dataset (required) |
var |
variable of interest (required) |
number_of_pairs |
Number of low-high pairs to be created. Takes a numeric value (required) |
Value
A tibble object filtered down to the low-high units selected
Select Low-High Units
Description
Select low-high units manually in a tibble and assign them into groups
Usage
select_low_high_units_manual(
data,
select_units_by = "row_number",
lowest_units,
highest_units,
part_id_col
)
Arguments
data |
input dataset (required) |
select_units_by |
Set to select units either based on row number or part ID. Options are "row_number" and "part_id". By default, it is set to "row_number". (required) |
lowest_units |
A numerical or character vector of the lowest units selected. Examples: c(1, 6, 8, 12), c("part5", "part45", "part9", "part23"). (required) |
highest_units |
A numerical or character vector of the lowest units selected. Examples: c(1, 6, 8, 12), c("part5", "part45", "part9", "part23"). (required) |
part_id_col |
Set column for part id. Only to be used when select_units_by is set to "part_id". |
Value
A tibble object filtered down to the low-high units selected
Small Multiples Sample Dataset
Description
Contains a sample dataset for small multiples
Usage
small_multiples_data
Format
An object of class tbl_df (inherits from tbl, data.frame) with 2900 rows and 4 columns.
Examples
small_multiples_data
Theme Sherlock
Description
Set Sherlock plot theme
Usage
theme_sherlock(axis_text_size = "normal")
Arguments
axis_text_size |
set axis text and axis title size. options are "normal" or "small". by default, it is set to "normal" |
Value
A 'theme' object with Sherlock plot theme
Tidy eval helpers
Description
This page lists the tidy eval tools reexported in this package from rlang. To learn about using tidy eval in scripts and packages at a high level, see the dplyr programming vignette and the ggplot2 in packages vignette. The Metaprogramming section of Advanced R may also be useful for a deeper dive.
The tidy eval operators
{{,!!, and!!!are syntactic constructs which are specially interpreted by tidy eval functions. You will mostly need{{, as!!and!!!are more advanced operators which you should not have to use in simple cases.The curly-curly operator
{{allows you to tunnel data-variables passed from function arguments inside other tidy eval functions.{{is designed for individual arguments. To pass multiple arguments contained in dots, use...in the normal way.my_function <- function(data, var, ...) { data %>% group_by(...) %>% summarise(mean = mean({{ var }})) }-
enquo()andenquos()delay the execution of one or several function arguments. The former returns a single expression, the latter returns a list of expressions. Once defused, expressions will no longer evaluate on their own. They must be injected back into an evaluation context with!!(for a single expression) and!!!(for a list of expressions).my_function <- function(data, var, ...) { # Defuse var <- enquo(var) dots <- enquos(...) # Inject data %>% group_by(!!!dots) %>% summarise(mean = mean(!!var)) }In this simple case, the code is equivalent to the usage of
{{and...above. Defusing withenquo()orenquos()is only needed in more complex cases, for instance if you need to inspect or modify the expressions in some way. The
.datapronoun is an object that represents the current slice of data. If you have a variable name in a string, use the.datapronoun to subset that variable with[[.my_var <- "disp" mtcars %>% summarise(mean = mean(.data[[my_var]]))
Another tidy eval operator is
:=. It makes it possible to use glue and curly-curly syntax on the LHS of=. For technical reasons, the R language doesn't support complex expressions on the left of=, so we use:=as a workaround.my_function <- function(data, var, suffix = "foo") { # Use `{{` to tunnel function arguments and the usual glue # operator `{` to interpolate plain strings. data %>% summarise("{{ var }}_mean_{suffix}" := mean({{ var }})) }Many tidy eval functions like
dplyr::mutate()ordplyr::summarise()give an automatic name to unnamed inputs. If you need to create the same sort of automatic names by yourself, useas_label(). For instance, the glue-tunnelling syntax above can be reproduced manually with:my_function <- function(data, var, suffix = "foo") { var <- enquo(var) prefix <- as_label(var) data %>% summarise("{prefix}_mean_{suffix}" := mean(!!var)) }Expressions defused with
enquo()(or tunnelled with{{) need not be simple column names, they can be arbitrarily complex.as_label()handles those cases gracefully. If your code assumes a simple column name, useas_name()instead. This is safer because it throws an error if the input is not a name as expected.
Value
No return value, called for side effects
Timeseries Scatterplot Sample Dataset
Description
Contains a sample Timerseries Scatterplot dataset
Usage
timeseries_scatterplot_data
Format
An object of class tbl_df (inherits from tbl, data.frame) with 1170 rows and 5 columns.
Examples
timeseries_scatterplot_data
Youden Plot Sample Dataset
Description
Contains a sample Youden Plot dataset
Usage
youden_plot_data
Format
An object of class data.frame with 40 rows and 3 columns.
Examples
youden_plot_data
Youden Plot Sample Dataset 2
Description
Contains a sample Youden Plot dataset
Usage
youden_plot_data_2
Format
An object of class data.frame with 30 rows and 2 columns.
Examples
youden_plot_data_2