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

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

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

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

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

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

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

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

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

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,
  sign = FALSE
)

Arguments

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_labels(c(-1, -0.0001, 0, 0.0001, 1, NA), round = 2, sign = FALSE)
ez_labels(c(-1, -0.0001, 0, 0.0001, 1, NA), round = 2, sign = TRUE)

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

ez_server

Description

ez_server

Usage

ez_server(data)

Arguments

ez_ui

Description

ez_ui

Usage

ez_ui(data)

Arguments

get_incr

Description

returns the minimum increment between sorted unique values of a vector

Usage

get_incr(x)

Arguments

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

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

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

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

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

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

Value

A ggplot object.

Examples

na_plot(airquality)

nameifnot

Description

Names unnamed elements of a character vector.

Usage

nameifnot(x, make.names = FALSE)

Arguments

Value

A named vector.

no_null

Description

Converts "NULL" character to NULL.

Usage

no_null(x)

Arguments

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

Value

A character vector.

perf

Description

Precision recall calculation

Usage

perf(fitted, actual, x_measure, y_measure)

Arguments

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

Value

A data.frame summarizing binary classification performance:

• quantile: fitted value quantile (only if !is.null(quantile)

• cutoff: fitted value cutoff

• fp: false positives

• tp: true positives

• tn: true negatives

• fn: false negatives

• pp: positive predictions

• np: negative predictions

• ipp: group positive predictions

• ifp: group false positives

• itp: group true positives

• rpp: rate of positive predictions

• acc: accuracy

• fpr: false positive rate

• tpr: true positive rate

• fnr: false negative rate

• tnr: true negative rate

• prec: precision

• clift: lift

• ilift: group lift

• f1: f1 measure

• ks: Kolmogorov-Smirnov statistic

• auc: area under ROC curve

• aucpr: area under PR curve

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)