Movatterモバイル変換

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 = 100df = 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 avector

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 = 1000df = 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 = 1000df = 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 afacet_x orfacet_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 = 1000df = 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_plotcreates a plot with a secondary y-axis

Description

secondary_plotcreates 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 textoverlayed 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 verticalfacets.

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)