Type: Package
Title: Functions for Common Chart Types
Version: 0.7.13
Author: Wojtek Kostelecki
Maintainer: Wojtek Kostelecki <wojtek.kostelecki@gmail.com>
Description: Wrapper for the 'ggplot2' package that creates a variety of common charts (e.g. bar, line, area, ROC, waterfall, pie) while aiming to reduce typing.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (≥ 3.3)
RoxygenNote: 7.3.1
Imports: dplyr, forcats, ggplot2, lubridate, rlang
Suggests: covr, DT, e1071, ggrepel, knitr, methods, miniUI, rmarkdown, ROCR, shiny, stats, testthat, tibble, tidyr, tsibble, tsibbledata
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-01-28 10:45:40 UTC; wkost
Repository: CRAN
Date/Publication: 2024-01-28 11:30:05 UTC

Aggregates data

Description

Aggregates data

Usage

agg_data(
  data,
  cols = names(data),
  group_by = NULL,
  agg_fun = function(x) sum(x, na.rm = TRUE),
  group_by2 = NULL,
  env = parent.frame()
)

Arguments

data

A data.frame.

cols

Named character vector of column names.

group_by

Vector of grouping columns.

agg_fun

Function to use for aggregating.

group_by2

Vector of grouping column names to use for delayed (post aggregation) calculation.

env

Environment for extra variables.

Value

An aggregated data.frame.

Examples

suppressPackageStartupMessages(library(tsibble))
library(tsibbledata)
agg_data(ansett, c("Passengers", count = "1"))
agg_data(ansett["Class"])
agg_data(ansett[c("Class", "Passengers")])
agg_data(ansett, "Passengers", "Class")
agg_data(ansett, "Passengers", c("Class", "Airports"))
agg_data(ansett, c(x = "Airports", y = "Passengers"), c(x = "Airports"))
agg_data(ansett, c(x = "Class", y = "1", group = "Airports"), c(x = "Class", group = "Airports"))

area_plot

Description

Aggregates a data.frame and creates a stacked area chart.

Usage

area_plot(
  data,
  x,
  y = "1",
  group = NULL,
  facet_x = NULL,
  facet_y = NULL,
  size = 11,
  reorder = c("group", "facet_x", "facet_y"),
  palette = ez_col,
  labels_y = if (position == "fill") {
     function(x) ez_labels(100 * x, append =
    "%")
 } else {
     ez_labels
 },
  labels_x = NULL,
  use_theme = theme_ez,
  position = c("stack", "fill"),
  facet_scales = "fixed",
  facet_ncol = NULL,
  legend_ncol = NULL,
  env = parent.frame()
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

size

theme size for use_theme(). Default is 14.

reorder

A character vector specifying the group variables to reorder. Default is c("group", "facet_x", "facet_y").

palette

Colour function.

labels_y

label formatting function

labels_x

label formatting function

use_theme

ggplot theme function

position

Either "stack" (default) or "fill"

facet_scales

Option passed to scales argument in facet_wrap or facet_grid. Default is "fixed".

facet_ncol

Option passed to ncol argument in facet_wrap or facet_grid. Default is NULL.

legend_ncol

Number of columns in legend.

env

environment for evaluating expressions.

Value

A ggplot object.

Examples


library(tsibble)
library(tsibbledata)
area_plot(ansett, x = "as.Date(Week)", y = "Passengers")
area_plot(ansett,
          x = "as.Date(Week)", y = c("Weekly Passengers" = "Passengers"), "Class")
area_plot(ansett, "as.Date(Week)",
          y = c("Weekly Passengers" = "Passengers"),
          group = "substr(Airports, 5, 7)",
          facet_x = "substr(Airports, 1, 3)",
          facet_y = "Class",
          facet_scales = "free_y")

bar_plot

Description

bar_plot

Usage

bar_plot(
  data,
  x,
  y = "1",
  group = NULL,
  facet_x = NULL,
  facet_y = NULL,
  size = 11,
  width = NULL,
  reorder = c("group", "facet_x", "facet_y"),
  palette = ez_col,
  labels_y = if (position == "fill") {
     function(x) ez_labels(100 * x, append =
    "%")
 } else {
     ez_labels
 },
  labels_x = identity,
  label_pos = c("auto", "inside", "top", "both", "none"),
  label_inside = c("y", "absolute", "share", "percent", "both"),
  rescale_y = 1.1,
  label_cutoff = 0.12,
  use_theme = theme_ez,
  position = "stack",
  facet_scales = "fixed",
  legend_ncol = NULL,
  coord_flip = FALSE,
  angle = 0,
  repel = FALSE
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

size

theme size for use_theme(). Default is 14.

width

Width of bar.

reorder

A character vector specifying the group variables to reorder. Default is c("group", "facet_x", "facet_y").

palette

Colour function.

labels_y

label formatting function

labels_x

label formatting function

label_pos

Position of labels. Can be "auto", "inside", "top", "both" or "none".

label_inside

Value to display inside bar segments. Options are "y", "absolute", "percent", "share" or "both".

rescale_y

Rescaling factor for y-axis limits

label_cutoff

Cutoff size (proportion of y data range) for excluding labels

use_theme

ggplot theme function

position

Either "stack" (default), "fill" or "dodge"

facet_scales

Option passed to scales argument in facet_wrap or facet_grid. Default is "fixed".

legend_ncol

Number of columns in legend.

coord_flip

logical (default is FALSE). If TRUE, flips the x and y coordinate using ggplot2::coord_flip()

angle

angle for geom_text(_repel)

repel

logical (default if FALSE). If TRUE, uses ggrepel for geom_text

Value

A ggplot object.

Examples

library(tsibble)
library(tsibbledata)
library(lubridate)

bar_plot(ansett, "year(Week)", "Passengers")
bar_plot(ansett, "year(Week)", "Passengers", "Class", label_pos = "both")
bar_plot(ansett, "year(Week)", "Passengers", "Class", label_pos = "both", label_inside = "both")
bar_plot(ansett, "year(Week)", "Passengers", "Class", coord_flip = TRUE)

calendar_plot

Description

calendar_plot

Usage

calendar_plot(data, x, y, ...)

Arguments

data

A data.frame.

x

date column

y

A named character value. Evaluates to a column.

...

additional arguments for tile_plot

Examples

library(tsibbledata)
calendar_plot(vic_elec, "Time", "Demand", zlim = c(NA, NA))

density_plot

Description

creates a density plot

Usage

density_plot(
  data,
  x,
  group = NULL,
  facet_x = NULL,
  facet_y = NULL,
  palette = ez_col,
  adjust = 1,
  alpha = 0.5,
  facet_scales = "fixed",
  facet_ncol = NULL,
  legend_ncol = NULL,
  env = parent.frame()
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

palette

Colour function.

adjust

multiplicate bandwidth adjustment

alpha

alpha

facet_scales

Option passed to scales argument in facet_wrap or facet_grid. Default is "fixed".

facet_ncol

Option passed to ncol argument in facet_wrap or facet_grid. Default is NULL.

legend_ncol

Number of columns in legend.

env

environment for evaluating expressions.

Examples

library(tsibbledata)
density_plot(mtcars, "wt", "cyl")
density_plot(subset(tsibbledata::olympic_running, Length == 100 & Year >= 1980),
             "Time", "Year - Year %% 10", "Sex", facet_scales = "free", facet_ncol = 1, adjust = 2)

distribution_plot

Description

distribution_plot

Usage

distribution_plot(
  data,
  x,
  facet_x = NULL,
  nbins = 20,
  use_theme = theme_ez,
  size = 11,
  env = parent.frame()
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

nbins

Number of bins for histogram. Default is 20.

use_theme

ggplot theme function

size

theme size for use_theme(). Default is 14.

env

environment for evaluating expressions.

Examples

n = 100
df = data.frame(residuals = rnorm(n),
                group1 = sample(c("a", "b"), n, replace = TRUE))
distribution_plot(df, "residuals")
distribution_plot(df, "residuals", "group1")

ez_app

Description

ez_app

Usage

ez_app(data = NULL)

Arguments

data

A data frame

Examples

## Not run: 
library(tsibble)
library(tsibbledata)
ez_app(ansett)

## End(Not run)

Color palette interpolation

Description

Color palette interpolation

Usage

ez_col(n = 50, palette = NULL)

Arguments

n

number of colours

palette

palette to interpolate from

Value

rgb

Examples

ez_col(15)
ez_col(2, c("blue", "red"))
ez_col(3, c("blue", "red"))

ez_jet

Description

color palette for

Usage

ez_jet(
  n = 100,
  palette = c("dodgerblue4", "steelblue2", "olivedrab3", "darkgoldenrod1", "brown")
)

Arguments

n

Number of colours to return.

palette

Vector of colours.

Examples

ez_jet(100)
ez_jet(1)

Function for formatting numeric labels

Description

Function for formatting numeric labels

Usage

ez_labels(
  x,
  prepend = "",
  append = "",
  as_factor = FALSE,
  round = Inf,
  signif = Inf
)

Arguments

x

numeric

prepend

character

append

character

as_factor

logical

round

numeric passed to round()

signif

numeric passed to signif()

Value

y

Examples

ez_labels(10^(0:10))
ez_labels(2000, append = " apples")
ez_labels(0:10, append = " apples", as_factor = TRUE)
ez_labels(c(0, 0.1, 0.01, 0.001, 0.0001))

ez_png

Description

Saves ggplot or ezplot objects to png (with useful defaults).

Usage

ez_png(
  g,
  file,
  width = 1200,
  height = 600,
  res = 72,
  resx = 1,
  ...,
  vp = NULL,
  dir.create = FALSE,
  check = TRUE
)

Arguments

g

A ggplot or ezplot object.

file

A png file path.

width

Image width (in pixels). Default is 1200.

height

Image height (in pixels). Default is 600.

res

Resolution (PPI) of output image. Default is 72.

resx

Resolution multiplier. Default is 1.

...

Further arguments to pass to png().

vp

A viewport object created with grid::viewport.

dir.create

Logical. If TRUE, creates the directory to save into. Default is FALSE.

check

Logical. If TRUE, opens png file after saving. Default is TRUE.

ez_server

Description

ez_server

Usage

ez_server(data)

Arguments

data

A data frame

ez_ui

Description

ez_ui

Usage

ez_ui(data)

Arguments

data

A data frame

get_incr

Description

returns the minimum increment between sorted unique values of a vector

Usage

get_incr(x)

Arguments

x

A numeric or date vector

histogram_plot

Description

creates a histogram plot

Usage

histogram_plot(
  data,
  x,
  y = "count",
  group = NULL,
  facet_x = NULL,
  facet_y = NULL,
  palette = ez_col,
  position = "stack",
  bins = 30,
  alpha = 0.5,
  facet_scales = "fixed",
  facet_ncol = NULL,
  legend_ncol = NULL,
  env = parent.frame()
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

palette

Colour function.

position

Either "stack" (default) or "fill"

bins

number of bins

alpha

fill alpha

facet_scales

Option passed to scales argument in facet_wrap or facet_grid. Default is "fixed".

facet_ncol

Option passed to ncol argument in facet_wrap or facet_grid. Default is NULL.

legend_ncol

Number of columns in legend.

env

environment for evaluating expressions.

Examples

histogram_plot(airquality, "Wind", group = "Month")
histogram_plot(airquality, "Wind", "density", facet_x = "Month")

ks_plot

Description

ks plot

Usage

ks_plot(
  data,
  fitted,
  actual,
  palette = ez_col,
  size_line = 1,
  size = 11,
  env = parent.frame()
)

Arguments

data

A data.frame.

fitted

Vector of fitted values

actual

Vector of actual values

palette

Colour function.

size_line

width of line for geom_line(). Default is 1.

size

theme size for use_theme(). Default is 14.

env

environment for evaluating expressions.

Examples

ks_plot(mtcars, "-disp", "am")
x = c(rnorm(100), rnorm(100) + 2)
label = c(rep('low', 100), rep('high', 100))
ks_plot(data.frame(x, label), "x", "label")
ks_plot(data.frame(x, label = factor(label, c('low', 'high'))), "x", "label")

lift_plot

Description

precision-recall plot

Usage

lift_plot(
  data,
  fitted,
  actual,
  group = NULL,
  facet_x = NULL,
  facet_y = NULL,
  size_line = 1,
  size = 11,
  env = parent.frame()
)

Arguments

data

A data.frame.

fitted

Vector of fitted values

actual

Vector of actual values

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

size_line

width of line for geom_line(). Default is 1.

size

theme size for use_theme(). Default is 14.

env

environment for evaluating expressions.

Examples

library(ggplot2)
n = 1000
df = data.frame(actual = sample(c(FALSE, TRUE), n, replace = TRUE),
                runif = runif(n))
df[["fitted"]] = runif(n) ^ ifelse(df[["actual"]] == 1, 0.5, 2)

density_plot(df, "fitted", "actual")

lift_plot(df, "fitted", "actual")
lift_plot(df, "fitted", "actual") + scale_y_log10()
lift_plot(df, "runif", "actual", size_line = 0.5)


library(dplyr, warn.conflicts = FALSE)
lift_plot(df, "fitted", "actual", "sample(c(1, 2), n(), TRUE)")

lift_plot(df, "fitted", "actual",
        "sample(c(1, 2), n(), TRUE)",
        "sample(c(3, 4), n(), TRUE)")

lift_plot(df, "fitted", "actual",
        "sample(c(1, 2), n(), TRUE)",
        "sample(c(3, 4), n(), TRUE)",
        "sample(c(5, 6), n(), TRUE)")

line_plot

Description

Creates line plots.

Usage

line_plot(
  data,
  x,
  y = "1",
  group = NULL,
  facet_x = NULL,
  facet_y = NULL,
  yoy = FALSE,
  size_line = 1,
  points = FALSE,
  size = 11,
  reorder = c("group", "facet_x", "facet_y"),
  palette = ez_col,
  labels_y = ez_labels,
  limits_y = c(NA, NA),
  use_theme = theme_ez,
  facet_scales = "fixed",
  na.rm = FALSE,
  legend_ncol = NULL
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

yoy

Logical used to indicate whether a YOY grouping should be created. Default is FALSE.

size_line

width of line for geom_line(). Default is 1.

points

logical. Option to include points

size

theme size for use_theme(). Default is 14.

reorder

A character vector specifying the group variables to reorder. Default is c("group", "facet_x", "facet_y").

palette

Colour function.

labels_y

label formatting function

limits_y

vector of c(min, max) y-axis limits

use_theme

ggplot theme function

facet_scales

Option passed to scales argument in facet_wrap or facet_grid. Default is "fixed".

na.rm

logical. Option to exclude NAs

legend_ncol

Number of columns in legend.

Value

A ggplot object.

Examples

suppressPackageStartupMessages(library(tsibble))
library(tsibbledata)
line_plot(pelt, "Year", c("Hare", "Lynx"), points = TRUE, limits_y = c(0, NA))

model_plot

Description

model_plot

Usage

model_plot(
  data,
  x,
  actual,
  fitted,
  facet_x = NULL,
  point_size = 2,
  res_bins = NA_real_,
  size = 11
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

actual

A character value. Evaluates to a logical or binary column.

fitted

A character value. Evaluates to a numeric column.

facet_x

A character value. Evaluates to a column.

point_size

Numeric. Default is 2.

res_bins

Number of bins in the residual distribution. Default value (NA) doesn't show the distribution.

size

theme size for use_theme(). Default is 14.

Value

A ggplot object.

Examples

y = rnorm(26)
df = data.frame(ID = 1:26, actual = y + rnorm(26), fitted = y, id = letters)
model_plot(df, "ID", "actual", "fitted")
model_plot(df, "id", "actual", "fitted")
model_plot(df, "ID", "actual", "fitted", res_bins = 10)
model_plot(df, "id", "actual", "fitted", res_bins = 10)

na_plot

Description

Visual representation of the NAs in a data.frame

Usage

na_plot(data, palette = ez_col)

Arguments

data

A data.frame.

palette

Colour function.

Value

A ggplot object.

Examples

na_plot(airquality)

nameifnot

Description

Names unnamed elements of a character vector.

Usage

nameifnot(x, make.names = FALSE)

Arguments

x

A character vector.

make.names

Logical. Whether to force names of x to be valid variable names. Default is FALSE.

Value

A named vector.

no_null

Description

Converts "NULL" character to NULL.

Usage

no_null(x)

Arguments

x

A character vector.

Value

y

Examples

no_null(NULL)
no_null("NULL")
no_null("NOPE")

not_numeric

Description

Returns names of non-numeric columns.

Usage

not_numeric(x)

Arguments

x

A data.frame.

Value

A character vector.

perf

Description

Precision recall calculation

Usage

perf(fitted, actual, x_measure, y_measure)

Arguments

fitted

Vector with values between 0 and 1

actual

Vector with two levels

x_measure

metric for ROCR::performance

y_measure

metric for ROCR::performance

Examples

ezplot:::perf(runif(1), sample(c(TRUE, FALSE), 1, replace = TRUE), "rpp", "lift")
ezplot:::perf(runif(10), sample(c(TRUE, FALSE), 10, replace = TRUE), "rpp", "lift")
ezplot:::perf(runif(5), sample(c(TRUE, FALSE), 5, replace = TRUE), "rec", "prec")
ezplot:::perf(runif(5), sample(c(TRUE, FALSE), 5, replace = TRUE), "fpr", "tpr")
ezplot:::perf(runif(5), sample(c(TRUE, FALSE), 5, replace = TRUE), "cutoff", "tpr")

perf_df

Description

shows classification performance statistics as a table

Usage

perf_df(fitted, actual, quantiles = NULL)

Arguments

fitted

A character value. Evaluates to a numeric column.

actual

A character value. Evaluates to a logical or binary column.

quantiles

Number of quantiles to show. If NULL, uses distinct values of fitted for the cutoffs rather than showing quantiles.

Value

A data.frame summarizing binary classification performance:

Examples

perf_df(mtcars$mpg, mtcars$am)
perf_df(mtcars$mpg, mtcars$am, quantiles = 4)
perf_df(mtcars$mpg, mtcars$am, quantiles = 8)
perf_df(mtcars$mpg, mtcars$am, quantiles = 10)
perf_df(mtcars$wt, mtcars$am==0)

performance_plot

Description

plots binary classification performance metrics

Usage

performance_plot(
  data,
  fitted,
  actual,
  group = NULL,
  facet_x = NULL,
  facet_y = NULL,
  x = "fpr",
  y = "tpr",
  auc = c("title", "group"),
  size_line = 1,
  size = 11,
  env = parent.frame()
)

Arguments

data

A data.frame.

fitted

A character value. Evaluates to a numeric column.

actual

A character value. Evaluates to a logical or binary column.

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

x

ROCR::performance() measure

y

ROCR::performance() measure

auc

character vector indicating which AUC values should be displayed. Options are 'title' and 'group'

size_line

width of line for geom_line(). Default is 1.

size

theme size for use_theme(). Default is 14.

env

environment for evaluating expressions.

Examples

performance_plot(mtcars, "-disp", "am")
performance_plot(mtcars, "-disp", "am", "cyl")
performance_plot(mtcars, "-disp", "am", "cyl", x = "rec", y = "prec")
performance_plot(mtcars, "-disp", "am", x = "rpp", y = "gain")
performance_plot(mtcars, "-disp", "am", x = "rpp", y = "lift")
performance_plot(mtcars, "-disp", "am", x = "cutoff", y = "tpr")

pie_plot

Description

Creates pie charts.

Usage

pie_plot(
  data,
  x,
  y = "1",
  facet_x = NULL,
  facet_y = NULL,
  labels_y = function(x) ez_labels(x * 100, append = "%", round = round, signif =
    signif),
  size = 11,
  label_cutoff = 0.04,
  round = Inf,
  signif = 3,
  palette = ez_col,
  reorder = c("x", "facet_x", "facet_y"),
  label_x = 0.8,
  legend_ncol = NULL
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

labels_y

label formatting function

size

theme size for use_theme(). Default is 14.

label_cutoff

Cutoff size (proportion of y data range) for excluding labels

round

Option for rounding label.

signif

Option for retaining significant figures in label.

palette

Colour function.

reorder

A character vector specifying the group variables to reorder. Default is c("group", "facet_x", "facet_y").

label_x

Position of label from centre of pie. 0 is the centre of the pie and 1 is the outer edge.

legend_ncol

Number of columns in legend.

Value

ggplot object

Examples


suppressPackageStartupMessages(library(tsibble))
library(tsibbledata)
pie_plot(ansett, "Class", "Passengers")
pie_plot(ansett, "Class", "Passengers", reorder = NULL, label_x = 0.5)
pie_plot(ansett, "Class", "Passengers", "Airports", reorder = NULL, label_x = 0.5)

pr_plot

Description

precision-recall plot

Usage

pr_plot(
  data,
  fitted,
  actual,
  group = NULL,
  facet_x = NULL,
  facet_y = NULL,
  palette = ez_col,
  size_line = 1,
  size = 11,
  labs = "short",
  env = parent.frame()
)

Arguments

data

A data.frame.

fitted

Vector of fitted values

actual

Vector of actual values

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

palette

Colour function.

size_line

width of line for geom_line(). Default is 1.

size

theme size for use_theme(). Default is 14.

labs

'short' or 'long'

env

environment for evaluating expressions.

Examples

library(ggplot2)
n = 1000
df = data.frame(actual = sample(c(FALSE, TRUE), n, replace = TRUE),
                runif = runif(n))
df[["fitted"]] = runif(n) ^ ifelse(df[["actual"]] == 1, 0.5, 2)

density_plot(df, "fitted", "actual")

pr_plot(df, "fitted", "actual")
pr_plot(df, "runif", "actual", size_line = 0.5)


library(dplyr, warn.conflicts = FALSE)
pr_plot(df, "fitted", "actual", "sample(c(1, 2), n(), TRUE)")

pr_plot(df, "fitted", "actual",
        "sample(c(1, 2), n(), TRUE)",
        "sample(c(3, 4), n(), TRUE)")

pr_plot(df, "fitted", "actual",
        "sample(c(1, 2), n(), TRUE)",
        "sample(c(3, 4), n(), TRUE)",
        "sample(c(5, 6), n(), TRUE)")

prec_rec

Description

Precision recall calculation

Usage

prec_rec(fitted, actual)

Arguments

fitted

Vector with values between 0 and 1

actual

Vector with two levels

Examples

ezplot:::prec_rec(runif(1), sample(c(TRUE, FALSE), 1, replace = TRUE))
ezplot:::prec_rec(runif(5), sample(c(TRUE, FALSE), 5, replace = TRUE))

Quick facet

Description

Applies faceting to ggplot objects when g[["data"]] has a facet_x or facet_y column.

Usage

quick_facet(g, ncol = NULL, ...)

Arguments

g

A ggplot object.

ncol

Number of facet columns.

...

Arguments to pass to facet_grid or facet_wrap.

Order levels of factor columns using fct_reorder

Description

Order levels of factor columns using fct_reorder

Usage

reorder_levels(
  data,
  cols = c("group", "facet_x", "facet_y"),
  y = "y",
  .desc = rep(TRUE, length(cols))
)

Arguments

data

A data.frame.

cols

Names of columns to reorder.

y

Numeric column for order priority.

.desc

A logical vector of length 1 or ncol(data). Default is TRUE for all columns in cols.

Value

A data.frame.

Examples

str(ezplot:::reorder_levels(mtcars, "cyl", "1"))
str(ezplot:::reorder_levels(mtcars, "cyl", "1", FALSE))
str(ezplot:::reorder_levels(mtcars, "cyl", "mpg"))

roc

Description

Calculates ROC and AUC

Usage

roc(fitted, actual)

Arguments

fitted

Vector with values between 0 and 1

actual

Vector with two levels

Examples

ezplot:::roc(runif(1), sample(c(TRUE, FALSE), 1, replace = TRUE))
ezplot:::roc(runif(3), sample(c(TRUE, FALSE), 3, replace = TRUE))

roc_plot

Description

roc_plot

Usage

roc_plot(
  data,
  fitted,
  actual,
  group = NULL,
  facet_x = NULL,
  facet_y = NULL,
  palette = ez_col,
  size_line = 1,
  size = 11,
  env = parent.frame()
)

Arguments

data

A data.frame.

fitted

Vector of fitted values

actual

Vector of actual values

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

palette

Colour function.

size_line

width of line for geom_line(). Default is 1.

size

theme size for use_theme(). Default is 14.

env

environment for evaluating expressions.

Examples

library(ggplot2)
n = 1000
df = data.frame(actual = sample(c(FALSE, TRUE), n, replace = TRUE),
                runif = runif(n))
df[["fitted"]] = runif(n) ^ ifelse(df[["actual"]] == 1, 0.5, 2)

ggplot(df) +
  geom_density(aes(fitted, fill = actual), alpha = 0.5)

roc_plot(df, "actual", "actual")
roc_plot(df, "fitted", "actual")
roc_plot(df, "runif", "actual", size_line = 0.5)


library(dplyr, warn.conflicts = FALSE)
roc_plot(df, "fitted", "actual", "sample(c(1, 2), n(), TRUE)")

roc_plot(df, "fitted", "actual",
         "sample(c(1, 2), n(), TRUE)",
         "sample(c(3, 4), n(), TRUE)")

roc_plot(df, "fitted", "actual",
         "sample(c(1, 2), n(), TRUE)",
         "sample(c(3, 4), n(), TRUE)",
         "sample(c(5, 6), n(), TRUE)")

save_png

Description

Saves ggplot or ezplot objects to png.

Usage

save_png(g, file, width, height, res, ..., vp = NULL)

Arguments

g

A ggplot or ezplot object.

file

A png file path.

width

Width of output image.

height

Height or output image.

res

Resolution of output image.

...

Further arguments to pass to png().

vp

A viewport object created with grid::viewport.

scatter plot

Description

create a scatter plot

Usage

scatter_plot(
  data,
  x,
  y,
  group = NULL,
  palette = ez_col,
  size = 11,
  point_size = 2.5,
  smooth = FALSE,
  env = parent.frame()
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

group

A character value. Evaluates to a column.

palette

Colour function.

size

theme size for use_theme(). Default is 14.

point_size

Numeric. Default is 2.

smooth

logical. If TRUE, adds geom_smooth().

env

environment for evaluating expressions.

Examples

scatter_plot(mtcars, "wt", "hp")
scatter_plot(mtcars, "wt", "hp", "factor(cyl)")
scatter_plot(mtcars, "factor(cyl)", "hp")

secondary_plot creates a plot with a secondary y-axis

Description

secondary_plot creates a plot with a secondary y-axis

Usage

secondary_plot(
  data,
  x,
  y1 = "1",
  y2 = "1",
  facet_x = NULL,
  facet_y = NULL,
  palette = ez_col,
  size_line = 1,
  labels_y1 = ez_labels,
  labels_y2 = ez_labels,
  ylim1 = NULL,
  ylim2 = NULL,
  reorder = c("facet_x", "facet_y"),
  size = 11
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y1

Variable to plot on the left-hand axis

y2

Variable to plot on the right-hand axis

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

palette

Colour function.

size_line

line size

labels_y1

label formatting function

labels_y2

label formatting function

ylim1

(optional) left axis limits

ylim2

(optional) right axis limits

reorder

A character vector specifying the group variables to reorder. Default is c("group", "facet_x", "facet_y").

size

theme size for use_theme(). Default is 14.

Value

A ggplot object.

Examples

suppressPackageStartupMessages(library(tsibble))
library(tsibbledata)
secondary_plot(pelt, "Year", "Hare", "Lynx")
secondary_plot(pelt, "Year", c("Hare Population" = "Hare"), c("Lynx Population" = "Lynx"))
secondary_plot(aus_production, "Quarter",
               c("Quarterly Beer Production (megalitres)" = "Beer"),
               c("Quarterly Cement Production (tonnes)" = "Cement"),
               "lubridate::quarter(Quarter)",
               ylim1 = c(0, 600), ylim2 = c(0, 3000),
               size = 10)

side_plot

Description

side_plot

Usage

side_plot(
  data,
  x,
  y = "1",
  labels_y = ez_labels,
  size = 11,
  palette = ez_col,
  signif = 3,
  reorder = TRUE,
  rescale_y = 1.25
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

labels_y

label formatting function

size

theme size for use_theme(). Default is 14.

palette

Colour function.

signif

Number of significant digits.

reorder

A character vector specifying the group variables to reorder. Default is c("group", "facet_x", "facet_y").

rescale_y

Rescaling factor for y-axis limits

Examples

side_plot(mtcars, "gear", "1", rescale_y = 4/3)
side_plot(mtcars, "cyl", c("Cars with <120 HP" = "hp < 120"))
side_plot(mtcars, "cyl", c(count = "ifelse(cyl == 4, 1, -1)", "hp <= 120"))
side_plot(mtcars, "cyl", c("hp <= 120", "~ - wt / cyl"), rescale_y = 1.5)
side_plot(mtcars, "cyl", c("1", "-1"))

text_contrast

Description

text_contrast

Usage

text_contrast(x)

Arguments

x

Vector of colours.

Value

Vector indicating whether black or white should be used for text overlayed on x.

Examples

text_contrast("#000000")
text_contrast("black")

Default theme

Description

Default theme

Usage

theme_ez(base_size = 11, base_family = "")

Arguments

base_size

base font size

base_family

base fond family

Value

theme

Examples

library(ggplot2)
ggplot(mtcars) + geom_point(aes(cyl, mpg)) + theme_ez()

tile_plot

Description

Creates tile plots.

Usage

tile_plot(
  data,
  x,
  y,
  z = c(Count = "1"),
  facet_x = NULL,
  facet_y = NULL,
  size = 11,
  facet_ncol = NULL,
  labels_x = NULL,
  labels_y = NULL,
  labels_z = ez_labels,
  zlim = function(x) c(pmin(0, x[1]), pmax(0, x[2])),
  palette = ez_jet,
  reorder = c("facet_x", "facet_y")
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

z

A named character. Evaluates to a column and is mapped to the fill colour of the tiles.

facet_x

A character value. Evaluates to a column.

facet_y

A character. Evaluates to a column.

size

theme size for use_theme(). Default is 14.

facet_ncol

Option passed to ncol argument in facet_wrap or facet_grid. Default is NULL.

labels_x

label formatting function

labels_y

label formatting function

labels_z

label formatting function

zlim

argument for scale_fill_grandientn(limits = zlim)

palette

Colour function.

reorder

A character vector specifying the group variables to reorder. Default is c("group", "facet_x", "facet_y").

Examples

## Not run: 
library(tsibbledata)
library(dplyr)
nyc_bikes %>%
  mutate(duration = as.numeric(stop_time - start_time)) %>%
  filter(between(duration, 0, 16)) %>%
  tile_plot(c("Hour of Day" = "lubridate::hour(start_time) + 0.5"),
            c("Ride Duration (min)" = "duration - duration %% 2 + 1"))

## End(Not run)

Unpack cols argument to agg_data

Description

Unpack cols argument to agg_data

Usage

unpack_cols(x)

Arguments

x

cols

Value

list

Examples

ezplot:::unpack_cols("x")
ezplot:::unpack_cols(c(x = "x", y = "x + y", expr = "~ x + y"))

variable_plot

Description

Plots variables (multiple "y" values) broken out as vertical facets.

Usage

variable_plot(
  data,
  x,
  y,
  group = NULL,
  facet_x = NULL,
  palette = ez_col,
  size = 14,
  labels_y = ez_labels,
  geom = "line",
  size_line = 1,
  legend_ncol = NULL,
  ylab = NULL,
  yoy = FALSE,
  switch = "y",
  rescale_y = 1
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

group

A character value. Evaluates to a column.

facet_x

A character value. Evaluates to a column.

palette

Colour function.

size

theme size for use_theme(). Default is 14.

labels_y

label formatting function

geom

Either "line", "col" or "bar". Default is "line"

size_line

width of line for geom_line(). Default is 1.

legend_ncol

Number of columns in legend.

ylab

y label text

yoy

Logical used to indicate whether a YOY grouping should be created. Default is FALSE.

switch

Option to switch location of variable (facet) labels. Default is 'y' (yes) which shows facet strips on left side of panels.

rescale_y

Rescaling factor for y-axis limits

Examples

suppressPackageStartupMessages(library(tsibble))
library(tsibbledata)
variable_plot(ansett, "Week", "Passengers", facet_x = "Class", yoy = TRUE)
variable_plot(pelt, "Year", c("Lynx", "Hare"), "round(Year, -1)")

waterfall_plot

Description

function for creating waterfall charts

Usage

waterfall_plot(
  data,
  x,
  y,
  group,
  size = 11,
  labels = ez_labels,
  label_rescale = 1,
  y_min = "auto",
  rescale_y = 1.1,
  n_signif = 3,
  rotate_xlabel = FALSE,
  bottom_label = TRUE,
  ingroup_label = FALSE,
  n_x = 2,
  env = parent.frame()
)

Arguments

data

A data.frame.

x

A named character value. Evaluates to a column.

y

A named character value. Evaluates to a column.

group

A character value. Evaluates to a column.

size

theme size for use_theme(). Default is 14.

labels

Function for formatting labels.

label_rescale

Scaling factor for chart labels (relative to axis labels).

y_min

Minimum limit of y axis.

rescale_y

Rescaling factor for y-axis limits

n_signif

Number of significant figures in labels.

rotate_xlabel

Logical.

bottom_label

Logical.

ingroup_label

Logical. Shows in-group percentage change.

n_x

Number of x levels to show in chart.

env

environment for evaluating expressions.

Examples

library(tsibbledata)
waterfall_plot(aus_retail,
               "lubridate::year(Month)",
               "Turnover",
               "sub(' Territory', '\nTerritory', State)",
               rotate_xlabel = TRUE)
waterfall_plot(aus_retail,
               "lubridate::year(Month)",
               "Turnover",
               "sub(' Territory', '\nTerritory', State)",
               rotate_xlabel = TRUE,
               label_rescale = 0.5,
               ingroup_label = TRUE,
               bottom_label = FALSE,
               n_x = 3,
               size = 20,
               y_min = 0)