In vegawidget/altair: Interface to 'Altair'
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
This document is adapted from the Bar Charts section of the Altair Example Gallery.
Our first step is to set up our environment:
library("altair")
library("tibble")
library("jsonlite")
vega_data <- import_vega_data()
Bar Chart with Highlighted Bar
Data
glimpse(vega_data$wheat())
Chart
chart <-
alt$Chart(vega_data$wheat())$
mark_bar()$
encode(
x = "year:O",
y = "wheat:Q",
# The highlight will be set on the result of a conditional statement
color=alt$condition(
"datum.year == 1810", # If the year is 1810 this test returns True,
alt$value("orange"), # which sets the bar orange.
alt$value("steelblue") # If it's not True, it sets the bar steelblue.
)
)$properties(width=600)
chart
Bar Chart with Labels
Data
glimpse(vega_data$wheat())
Chart
bars <-
alt$Chart(vega_data$wheat())$
mark_bar()$
encode(
x = "wheat:Q",
y = "year:O"
)
text <-
bars$
mark_text(align = "left", baseline = "middle", dx = 3)$
encode(
text = "wheat:Q"
)
chart <- (bars + text)$properties(height = 800)
chart
Bar Chart with Line as Mean
Data
glimpse(vega_data$wheat())
Chart
source <- vega_data$wheat()
bar <-
alt$Chart(source)$
mark_bar()$
encode(
x = "year:O",
y = "wheat:Q"
)
rule <-
alt$Chart(source)$
mark_rule(color = "red")$
encode(
y = "mean(wheat):Q"
)
chart <- (bar + rule)$properties(width = 600)
chart
Bar Chart with Line on Dual Axis
This seems exemplary of why dual-axes should be used with caution.
Data
glimpse(vega_data$wheat())
Chart
base <-
alt$Chart(vega_data$wheat())$
encode(
x = "year:O"
)
bar <-
base$
mark_bar()$
encode(
y = "wheat:Q"
)
line <-
base$
mark_line(color = "red")$
encode(
y = "wages:Q"
)
chart <-
(bar + line)$
properties(width = 600)
chart
Bar Chart with Negative Values
Data
glimpse(vega_data$us_employment())
Chart
chart <-
alt$Chart(vega_data$us_employment())$
mark_bar()$
encode(
x = "month:T",
y = "nonfarm_change:Q",
color = alt$condition(
"datum.nonfarm_change > 0",
alt$value("steelblue"), # positive color
alt$value("orange") # negative color
)
)$properties(width = 600)
chart
Bar and Tick Chart
Data
Definition
data <-
tibble(
project = c("a", "b", "c", "d", "e", "f", "g"),
score = c(25, 57, 23, 19, 8, 47, 8),
goal = c(25, 47, 30, 27, 38, 19, 4)
)
glimpse(data)
Chart
bar <-
alt$Chart(data = data)$
mark_bar()$
encode(
x = "project:O",
y = "score:Q"
)$
properties(width = alt$Step(40))
tick <-
alt$Chart(data = data)$
mark_tick(
color = "red",
thickness = 2,
size = 40 * 0.9
)$
encode(
x = "project:O",
y = "goal:Q"
)
chart <- (bar + tick)
chart
Calculating Percentage of Total
In the Altair example, we see some code like this:
alt.WindowFieldDef(op='sum', field='Time', **{'as': 'TotalTime'})
In R, supply the stuff inside the **{} as additional arguments to the function:
alt$WindowFieldDef(op = "sum", field = "Time", as = "TotalTime")
See the Field Guide to Python Issues for more details
and more examples.
Data
Definition
activities <-
tibble(
Activity = c("Sleeping", "Eating", "TV", "Work", "Exercise"),
Time = c(8, 2, 4, 8, 2)
)
glimpse(activities)
Chart
chart <-
alt$Chart(activities)$
transform_joinaggregate(
TotalTime = "sum(Time)"
)$
transform_calculate(PercentOfTotal = "datum.Time / datum.TotalTime")$
mark_bar()$
encode(
alt$X("PercentOfTotal:Q", axis = alt$Axis(format = ".0%")),
y = "Activity:N"
)
chart
Diverging Stacked Bar Chart
This example shows a diverging stacked bar chart for sentiments towards a set of eight questions, displayed as percentages with neutral responses straddling the 0% mark.
Data
Definition
data <- fromJSON('[
{
"question": "Question 1",
"type": "Strongly disagree",
"value": 24,
"percentage": 0.7,
"percentage_start": -19.1,
"percentage_end": -18.4
},
{
"question": "Question 1",
"type": "Disagree",
"value": 294,
"percentage": 9.1,
"percentage_start": -18.4,
"percentage_end": -9.2
},
{
"question": "Question 1",
"type": "Neither agree nor disagree",
"value": 594,
"percentage": 18.5,
"percentage_start": -9.2,
"percentage_end": 9.2
},
{
"question": "Question 1",
"type": "Agree",
"value": 1927,
"percentage": 59.9,
"percentage_start": 9.2,
"percentage_end": 69.2
},
{
"question": "Question 1",
"type": "Strongly agree",
"value": 376,
"percentage": 11.7,
"percentage_start": 69.2,
"percentage_end": 80.9
},
{
"question": "Question 2",
"type": "Strongly disagree",
"value": 2,
"percentage": 18.2,
"percentage_start": -36.4,
"percentage_end": -18.2
},
{
"question": "Question 2",
"type": "Disagree",
"value": 2,
"percentage": 18.2,
"percentage_start": -18.2,
"percentage_end": 0
},
{
"question": "Question 2",
"type": "Neither agree nor disagree",
"value": 0,
"percentage": 0,
"percentage_start": 0,
"percentage_end": 0
},
{
"question": "Question 2",
"type": "Agree",
"value": 7,
"percentage": 63.6,
"percentage_start": 0,
"percentage_end": 63.6
},
{
"question": "Question 2",
"type": "Strongly agree",
"value": 11,
"percentage": 0,
"percentage_start": 63.6,
"percentage_end": 63.6
},
{
"question": "Question 3",
"type": "Strongly disagree",
"value": 2,
"percentage": 20,
"percentage_start": -30,
"percentage_end": -10
},
{
"question": "Question 3",
"type": "Disagree",
"value": 0,
"percentage": 0,
"percentage_start": -10,
"percentage_end": -10
},
{
"question": "Question 3",
"type": "Neither agree nor disagree",
"value": 2,
"percentage": 20,
"percentage_start": -10,
"percentage_end": 10
},
{
"question": "Question 3",
"type": "Agree",
"value": 4,
"percentage": 40,
"percentage_start": 10,
"percentage_end": 50
},
{
"question": "Question 3",
"type": "Strongly agree",
"value": 2,
"percentage": 20,
"percentage_start": 50,
"percentage_end": 70
},
{
"question": "Question 4",
"type": "Strongly disagree",
"value": 0,
"percentage": 0,
"percentage_start": -15.6,
"percentage_end": -15.6
},
{
"question": "Question 4",
"type": "Disagree",
"value": 2,
"percentage": 12.5,
"percentage_start": -15.6,
"percentage_end": -3.1
},
{
"question": "Question 4",
"type": "Neither agree nor disagree",
"value": 1,
"percentage": 6.3,
"percentage_start": -3.1,
"percentage_end": 3.1
},
{
"question": "Question 4",
"type": "Agree",
"value": 7,
"percentage": 43.8,
"percentage_start": 3.1,
"percentage_end": 46.9
},
{
"question": "Question 4",
"type": "Strongly agree",
"value": 6,
"percentage": 37.5,
"percentage_start": 46.9,
"percentage_end": 84.4
},
{
"question": "Question 5",
"type": "Strongly disagree",
"value": 0,
"percentage": 0,
"percentage_start": -10.4,
"percentage_end": -10.4
},
{
"question": "Question 5",
"type": "Disagree",
"value": 1,
"percentage": 4.2,
"percentage_start": -10.4,
"percentage_end": -6.3
},
{
"question": "Question 5",
"type": "Neither agree nor disagree",
"value": 3,
"percentage": 12.5,
"percentage_start": -6.3,
"percentage_end": 6.3
},
{
"question": "Question 5",
"type": "Agree",
"value": 16,
"percentage": 66.7,
"percentage_start": 6.3,
"percentage_end": 72.9
},
{
"question": "Question 5",
"type": "Strongly agree",
"value": 4,
"percentage": 16.7,
"percentage_start": 72.9,
"percentage_end": 89.6
},
{
"question": "Question 6",
"type": "Strongly disagree",
"value": 1,
"percentage": 6.3,
"percentage_start": -18.8,
"percentage_end": -12.5
},
{
"question": "Question 6",
"type": "Disagree",
"value": 1,
"percentage": 6.3,
"percentage_start": -12.5,
"percentage_end": -6.3
},
{
"question": "Question 6",
"type": "Neither agree nor disagree",
"value": 2,
"percentage": 12.5,
"percentage_start": -6.3,
"percentage_end": 6.3
},
{
"question": "Question 6",
"type": "Agree",
"value": 9,
"percentage": 56.3,
"percentage_start": 6.3,
"percentage_end": 62.5
},
{
"question": "Question 6",
"type": "Strongly agree",
"value": 3,
"percentage": 18.8,
"percentage_start": 62.5,
"percentage_end": 81.3
},
{
"question": "Question 7",
"type": "Strongly disagree",
"value": 0,
"percentage": 0,
"percentage_start": -10,
"percentage_end": -10
},
{
"question": "Question 7",
"type": "Disagree",
"value": 0,
"percentage": 0,
"percentage_start": -10,
"percentage_end": -10
},
{
"question": "Question 7",
"type": "Neither agree nor disagree",
"value": 1,
"percentage": 20,
"percentage_start": -10,
"percentage_end": 10
},
{
"question": "Question 7",
"type": "Agree",
"value": 4,
"percentage": 80,
"percentage_start": 10,
"percentage_end": 90
},
{
"question": "Question 7",
"type": "Strongly agree",
"value": 0,
"percentage": 0,
"percentage_start": 90,
"percentage_end": 90
},
{
"question": "Question 8",
"type": "Strongly disagree",
"value": 0,
"percentage": 0,
"percentage_start": 0,
"percentage_end": 0
},
{
"question": "Question 8",
"type": "Disagree",
"value": 0,
"percentage": 0,
"percentage_start": 0,
"percentage_end": 0
},
{
"question": "Question 8",
"type": "Neither agree nor disagree",
"value": 0,
"percentage": 0,
"percentage_start": 0,
"percentage_end": 0
},
{
"question": "Question 8",
"type": "Agree",
"value": 0,
"percentage": 0,
"percentage_start": 0,
"percentage_end": 0
},
{
"question": "Question 8",
"type": "Strongly agree",
"value": 2,
"percentage": 100,
"percentage_start": 0,
"percentage_end": 100
}
]')
glimpse(data)
Chart
color_scale <-
alt$Scale(
domain = list(
"Strongly disagree",
"Disagree",
"Neither agree nor disagree",
"Agree",
"Strongly agree"
),
range = list("#c30d24", "#f3a583", "#cccccc", "#94c6da", "#1770ab")
)
y_axis <-
alt$Axis(
title = "Question",
offset = 5,
ticks = FALSE,
minExtent = 60,
domain = FALSE
)
chart <-
alt$Chart(data)$
mark_bar()$
encode(
x = "percentage_start:Q",
x2 = "percentage_end:Q",
y = alt$Y("question:N", axis = y_axis),
color = alt$Color(
"type:N",
legend = alt$Legend(title = "Response"),
scale = color_scale
)
)
chart
Grouped Bar Chart
Data
source <- vega_data$barley()
glimpse(source)
Chart
chart <-
alt$Chart(vega_data$barley())$
mark_bar()$
encode(
x = "year:O",
y = "sum(yield):Q",
color = "year:N",
column = "site:N"
)
chart
Grouped Bar Chart with Error Bars
This example shows how to show error bars using confidence intervals. The confidence intervals are computed internally in vega by a non-parametric bootstrap of the mean.
Data
source <- vega_data$barley()
glimpse(source)
Chart
bars <-
alt$Chart()$
mark_bar()$
encode(
x = "year:O",
y = alt$Y(
"mean(yield):Q",
axis = alt$Axis(title = "Mean Yield")
),
color = "year:N"
)
error_bars <-
alt$Chart()$
mark_errorbar(extent = "ci")$
encode(
x = "year:O",
y = "yield:Q"
)
chart <-
alt$layer(bars, error_bars, data = source)$
facet(
column = "site:N"
)
chart
Horizontal Bar Chart
Note that the argument to the transform_filter() function is a JavaScript expression that refers to a variable in the data using the datum. prefix.
Data
glimpse(vega_data$wheat())
Chart
chart <-
alt$Chart(vega_data$wheat())$
mark_bar()$
encode(
x = "wheat:Q",
y = "year:O"
)$
properties(height = 700)
chart
Horizontal Grouped Bar Chart
Data
glimpse(vega_data$barley())
Chart
chart <-
alt$Chart(vega_data$barley())$
mark_bar()$
encode(
x = "sum(yield):Q",
y = "year:O",
color = "year:N",
row = "site:N"
)
chart
Horizontal Stacked Bar Chart
Data
glimpse(vega_data$barley())
Chart
chart <-
alt$Chart(vega_data$barley())$
mark_bar()$
encode(
x = "sum(yield)",
y = "variety",
color = "site"
)
chart
Layered Bar Chart
Data
glimpse(vega_data$iowa_electricity())
Chart
chart <-
alt$Chart(vega_data$iowa_electricity())$
mark_bar(opacity = 0.7)$
encode(
x = "year:O",
y = alt$Y("net_generation:Q", stack = NULL),
color = "source"
)
chart
Normalized Stacked Bar Chart
Data
glimpse(vega_data$barley())
Chart
chart <-
alt$Chart(vega_data$barley())$
mark_bar()$
encode(
x = alt$X("sum(yield)", stack = "normalize"),
y = "variety",
color = "site"
)
chart
Sorted Bar Chart
glimpse(vega_data$barley())
Chart
chart <-
alt$Chart(vega_data$barley())$
mark_bar()$
encode(
x = "sum(yield):Q",
y = alt$Y(
"site:N",
sort = alt$EncodingSortField(
field = "yield", # field to use for the sort
op = "sum", # operation to run on the field prior to sorting
order = "descending" # order to sort in
)
)
)
chart
Stacked Bar Chart
glimpse(vega_data$barley())
Chart
chart <-
alt$Chart(vega_data$barley())$
mark_bar()$
encode(
x = "variety",
y = "sum(yield)",
color = "site"
)
chart
Stacked Bar Chart with Sorted Segments
glimpse(vega_data$barley())
Chart
chart <-
alt$Chart(vega_data$barley())$
mark_bar()$
encode(
y = "variety",
x = "sum(yield)",
color = "site",
order = alt$Order(
# Sort the segments of the bars by this field
"site",
sort ="ascending"
)
)
chart
Stacked Bar Chart with Text Overlay
glimpse(vega_data$barley())
Chart
source <- vega_data$barley()
bars <-
alt$Chart(source)$
mark_bar()$
encode(
x = alt$X("sum(yield):Q", stack = "zero"),
y = "variety:N",
color ="site:N"
)
text = alt$Chart(source)$
mark_text(dx = -15, dy = 3, color = "white")$
encode(
x =alt$X("sum(yield):Q", stack = "zero"),
y = "variety:N",
detail = "site:N",
text=alt$Text("sum(yield):Q", format = ".1f")
)
chart <- (bars + text)
chart
Trellis Stacked Bar Chart
glimpse(vega_data$barley())
Chart
chart <-
alt$Chart(vega_data$barley())$
mark_bar()$
encode(
x = "yield",
y = "variety",
color = "site",
column = "year"
)$
properties(width = 220)
chart
vegawidget/altair documentation built on Feb. 3, 2024, 7:47 p.m.
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knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
This document is adapted from the Bar Charts section of the Altair Example Gallery.
Our first step is to set up our environment:
library("altair") library("tibble") library("jsonlite") vega_data <- import_vega_data()
Bar Chart with Highlighted Bar
Data
glimpse(vega_data$wheat())
Chart
chart <- alt$Chart(vega_data$wheat())$ mark_bar()$ encode( x = "year:O", y = "wheat:Q", # The highlight will be set on the result of a conditional statement color=alt$condition( "datum.year == 1810", # If the year is 1810 this test returns True, alt$value("orange"), # which sets the bar orange. alt$value("steelblue") # If it's not True, it sets the bar steelblue. ) )$properties(width=600) chart
Bar Chart with Labels
Data
glimpse(vega_data$wheat())
Chart
bars <- alt$Chart(vega_data$wheat())$ mark_bar()$ encode( x = "wheat:Q", y = "year:O" ) text <- bars$ mark_text(align = "left", baseline = "middle", dx = 3)$ encode( text = "wheat:Q" ) chart <- (bars + text)$properties(height = 800) chart
Bar Chart with Line as Mean
Data
glimpse(vega_data$wheat())
Chart
source <- vega_data$wheat() bar <- alt$Chart(source)$ mark_bar()$ encode( x = "year:O", y = "wheat:Q" ) rule <- alt$Chart(source)$ mark_rule(color = "red")$ encode( y = "mean(wheat):Q" ) chart <- (bar + rule)$properties(width = 600) chart
Bar Chart with Line on Dual Axis
This seems exemplary of why dual-axes should be used with caution.
Data
glimpse(vega_data$wheat())
Chart
base <- alt$Chart(vega_data$wheat())$ encode( x = "year:O" ) bar <- base$ mark_bar()$ encode( y = "wheat:Q" ) line <- base$ mark_line(color = "red")$ encode( y = "wages:Q" ) chart <- (bar + line)$ properties(width = 600) chart
Bar Chart with Negative Values
Data
glimpse(vega_data$us_employment())
Chart
chart <- alt$Chart(vega_data$us_employment())$ mark_bar()$ encode( x = "month:T", y = "nonfarm_change:Q", color = alt$condition( "datum.nonfarm_change > 0", alt$value("steelblue"), # positive color alt$value("orange") # negative color ) )$properties(width = 600) chart
Bar and Tick Chart
Data
Definition
data <- tibble( project = c("a", "b", "c", "d", "e", "f", "g"), score = c(25, 57, 23, 19, 8, 47, 8), goal = c(25, 47, 30, 27, 38, 19, 4) )
glimpse(data)
Chart
bar <- alt$Chart(data = data)$ mark_bar()$ encode( x = "project:O", y = "score:Q" )$ properties(width = alt$Step(40)) tick <- alt$Chart(data = data)$ mark_tick( color = "red", thickness = 2, size = 40 * 0.9 )$ encode( x = "project:O", y = "goal:Q" ) chart <- (bar + tick) chart
Calculating Percentage of Total
In the Altair example, we see some code like this:
alt.WindowFieldDef(op='sum', field='Time', **{'as': 'TotalTime'})
In R, supply the stuff inside the **{} as additional arguments to the function:
alt$WindowFieldDef(op = "sum", field = "Time", as = "TotalTime")
See the Field Guide to Python Issues for more details and more examples.
Data
Definition
activities <- tibble( Activity = c("Sleeping", "Eating", "TV", "Work", "Exercise"), Time = c(8, 2, 4, 8, 2) )
glimpse(activities)
Chart
chart <- alt$Chart(activities)$ transform_joinaggregate( TotalTime = "sum(Time)" )$ transform_calculate(PercentOfTotal = "datum.Time / datum.TotalTime")$ mark_bar()$ encode( alt$X("PercentOfTotal:Q", axis = alt$Axis(format = ".0%")), y = "Activity:N" ) chart
Diverging Stacked Bar Chart
This example shows a diverging stacked bar chart for sentiments towards a set of eight questions, displayed as percentages with neutral responses straddling the 0% mark.
Data
Definition
data <- fromJSON('[ { "question": "Question 1", "type": "Strongly disagree", "value": 24, "percentage": 0.7, "percentage_start": -19.1, "percentage_end": -18.4 }, { "question": "Question 1", "type": "Disagree", "value": 294, "percentage": 9.1, "percentage_start": -18.4, "percentage_end": -9.2 }, { "question": "Question 1", "type": "Neither agree nor disagree", "value": 594, "percentage": 18.5, "percentage_start": -9.2, "percentage_end": 9.2 }, { "question": "Question 1", "type": "Agree", "value": 1927, "percentage": 59.9, "percentage_start": 9.2, "percentage_end": 69.2 }, { "question": "Question 1", "type": "Strongly agree", "value": 376, "percentage": 11.7, "percentage_start": 69.2, "percentage_end": 80.9 }, { "question": "Question 2", "type": "Strongly disagree", "value": 2, "percentage": 18.2, "percentage_start": -36.4, "percentage_end": -18.2 }, { "question": "Question 2", "type": "Disagree", "value": 2, "percentage": 18.2, "percentage_start": -18.2, "percentage_end": 0 }, { "question": "Question 2", "type": "Neither agree nor disagree", "value": 0, "percentage": 0, "percentage_start": 0, "percentage_end": 0 }, { "question": "Question 2", "type": "Agree", "value": 7, "percentage": 63.6, "percentage_start": 0, "percentage_end": 63.6 }, { "question": "Question 2", "type": "Strongly agree", "value": 11, "percentage": 0, "percentage_start": 63.6, "percentage_end": 63.6 }, { "question": "Question 3", "type": "Strongly disagree", "value": 2, "percentage": 20, "percentage_start": -30, "percentage_end": -10 }, { "question": "Question 3", "type": "Disagree", "value": 0, "percentage": 0, "percentage_start": -10, "percentage_end": -10 }, { "question": "Question 3", "type": "Neither agree nor disagree", "value": 2, "percentage": 20, "percentage_start": -10, "percentage_end": 10 }, { "question": "Question 3", "type": "Agree", "value": 4, "percentage": 40, "percentage_start": 10, "percentage_end": 50 }, { "question": "Question 3", "type": "Strongly agree", "value": 2, "percentage": 20, "percentage_start": 50, "percentage_end": 70 }, { "question": "Question 4", "type": "Strongly disagree", "value": 0, "percentage": 0, "percentage_start": -15.6, "percentage_end": -15.6 }, { "question": "Question 4", "type": "Disagree", "value": 2, "percentage": 12.5, "percentage_start": -15.6, "percentage_end": -3.1 }, { "question": "Question 4", "type": "Neither agree nor disagree", "value": 1, "percentage": 6.3, "percentage_start": -3.1, "percentage_end": 3.1 }, { "question": "Question 4", "type": "Agree", "value": 7, "percentage": 43.8, "percentage_start": 3.1, "percentage_end": 46.9 }, { "question": "Question 4", "type": "Strongly agree", "value": 6, "percentage": 37.5, "percentage_start": 46.9, "percentage_end": 84.4 }, { "question": "Question 5", "type": "Strongly disagree", "value": 0, "percentage": 0, "percentage_start": -10.4, "percentage_end": -10.4 }, { "question": "Question 5", "type": "Disagree", "value": 1, "percentage": 4.2, "percentage_start": -10.4, "percentage_end": -6.3 }, { "question": "Question 5", "type": "Neither agree nor disagree", "value": 3, "percentage": 12.5, "percentage_start": -6.3, "percentage_end": 6.3 }, { "question": "Question 5", "type": "Agree", "value": 16, "percentage": 66.7, "percentage_start": 6.3, "percentage_end": 72.9 }, { "question": "Question 5", "type": "Strongly agree", "value": 4, "percentage": 16.7, "percentage_start": 72.9, "percentage_end": 89.6 }, { "question": "Question 6", "type": "Strongly disagree", "value": 1, "percentage": 6.3, "percentage_start": -18.8, "percentage_end": -12.5 }, { "question": "Question 6", "type": "Disagree", "value": 1, "percentage": 6.3, "percentage_start": -12.5, "percentage_end": -6.3 }, { "question": "Question 6", "type": "Neither agree nor disagree", "value": 2, "percentage": 12.5, "percentage_start": -6.3, "percentage_end": 6.3 }, { "question": "Question 6", "type": "Agree", "value": 9, "percentage": 56.3, "percentage_start": 6.3, "percentage_end": 62.5 }, { "question": "Question 6", "type": "Strongly agree", "value": 3, "percentage": 18.8, "percentage_start": 62.5, "percentage_end": 81.3 }, { "question": "Question 7", "type": "Strongly disagree", "value": 0, "percentage": 0, "percentage_start": -10, "percentage_end": -10 }, { "question": "Question 7", "type": "Disagree", "value": 0, "percentage": 0, "percentage_start": -10, "percentage_end": -10 }, { "question": "Question 7", "type": "Neither agree nor disagree", "value": 1, "percentage": 20, "percentage_start": -10, "percentage_end": 10 }, { "question": "Question 7", "type": "Agree", "value": 4, "percentage": 80, "percentage_start": 10, "percentage_end": 90 }, { "question": "Question 7", "type": "Strongly agree", "value": 0, "percentage": 0, "percentage_start": 90, "percentage_end": 90 }, { "question": "Question 8", "type": "Strongly disagree", "value": 0, "percentage": 0, "percentage_start": 0, "percentage_end": 0 }, { "question": "Question 8", "type": "Disagree", "value": 0, "percentage": 0, "percentage_start": 0, "percentage_end": 0 }, { "question": "Question 8", "type": "Neither agree nor disagree", "value": 0, "percentage": 0, "percentage_start": 0, "percentage_end": 0 }, { "question": "Question 8", "type": "Agree", "value": 0, "percentage": 0, "percentage_start": 0, "percentage_end": 0 }, { "question": "Question 8", "type": "Strongly agree", "value": 2, "percentage": 100, "percentage_start": 0, "percentage_end": 100 } ]')
glimpse(data)
Chart
color_scale <- alt$Scale( domain = list( "Strongly disagree", "Disagree", "Neither agree nor disagree", "Agree", "Strongly agree" ), range = list("#c30d24", "#f3a583", "#cccccc", "#94c6da", "#1770ab") ) y_axis <- alt$Axis( title = "Question", offset = 5, ticks = FALSE, minExtent = 60, domain = FALSE ) chart <- alt$Chart(data)$ mark_bar()$ encode( x = "percentage_start:Q", x2 = "percentage_end:Q", y = alt$Y("question:N", axis = y_axis), color = alt$Color( "type:N", legend = alt$Legend(title = "Response"), scale = color_scale ) ) chart
Grouped Bar Chart
Data
source <- vega_data$barley() glimpse(source)
Chart
chart <- alt$Chart(vega_data$barley())$ mark_bar()$ encode( x = "year:O", y = "sum(yield):Q", color = "year:N", column = "site:N" ) chart
Grouped Bar Chart with Error Bars
This example shows how to show error bars using confidence intervals. The confidence intervals are computed internally in vega by a non-parametric bootstrap of the mean.
Data
source <- vega_data$barley() glimpse(source)
Chart
bars <- alt$Chart()$ mark_bar()$ encode( x = "year:O", y = alt$Y( "mean(yield):Q", axis = alt$Axis(title = "Mean Yield") ), color = "year:N" ) error_bars <- alt$Chart()$ mark_errorbar(extent = "ci")$ encode( x = "year:O", y = "yield:Q" ) chart <- alt$layer(bars, error_bars, data = source)$ facet( column = "site:N" ) chart
Horizontal Bar Chart
Note that the argument to the transform_filter() function is a JavaScript expression that refers to a variable in the data using the datum. prefix.
Data
glimpse(vega_data$wheat())
Chart
chart <- alt$Chart(vega_data$wheat())$ mark_bar()$ encode( x = "wheat:Q", y = "year:O" )$ properties(height = 700) chart
Horizontal Grouped Bar Chart
Data
glimpse(vega_data$barley())
Chart
chart <- alt$Chart(vega_data$barley())$ mark_bar()$ encode( x = "sum(yield):Q", y = "year:O", color = "year:N", row = "site:N" ) chart
Horizontal Stacked Bar Chart
Data
glimpse(vega_data$barley())
Chart
chart <- alt$Chart(vega_data$barley())$ mark_bar()$ encode( x = "sum(yield)", y = "variety", color = "site" ) chart
Layered Bar Chart
Data
glimpse(vega_data$iowa_electricity())
Chart
chart <- alt$Chart(vega_data$iowa_electricity())$ mark_bar(opacity = 0.7)$ encode( x = "year:O", y = alt$Y("net_generation:Q", stack = NULL), color = "source" ) chart
Normalized Stacked Bar Chart
Data
glimpse(vega_data$barley())
Chart
chart <- alt$Chart(vega_data$barley())$ mark_bar()$ encode( x = alt$X("sum(yield)", stack = "normalize"), y = "variety", color = "site" ) chart
Sorted Bar Chart
glimpse(vega_data$barley())
Chart
chart <- alt$Chart(vega_data$barley())$ mark_bar()$ encode( x = "sum(yield):Q", y = alt$Y( "site:N", sort = alt$EncodingSortField( field = "yield", # field to use for the sort op = "sum", # operation to run on the field prior to sorting order = "descending" # order to sort in ) ) ) chart
Stacked Bar Chart
glimpse(vega_data$barley())
Chart
chart <- alt$Chart(vega_data$barley())$ mark_bar()$ encode( x = "variety", y = "sum(yield)", color = "site" ) chart
Stacked Bar Chart with Sorted Segments
glimpse(vega_data$barley())
Chart
chart <- alt$Chart(vega_data$barley())$ mark_bar()$ encode( y = "variety", x = "sum(yield)", color = "site", order = alt$Order( # Sort the segments of the bars by this field "site", sort ="ascending" ) ) chart
Stacked Bar Chart with Text Overlay
glimpse(vega_data$barley())
Chart
source <- vega_data$barley() bars <- alt$Chart(source)$ mark_bar()$ encode( x = alt$X("sum(yield):Q", stack = "zero"), y = "variety:N", color ="site:N" ) text = alt$Chart(source)$ mark_text(dx = -15, dy = 3, color = "white")$ encode( x =alt$X("sum(yield):Q", stack = "zero"), y = "variety:N", detail = "site:N", text=alt$Text("sum(yield):Q", format = ".1f") ) chart <- (bars + text) chart
Trellis Stacked Bar Chart
glimpse(vega_data$barley())
Chart
chart <- alt$Chart(vega_data$barley())$ mark_bar()$ encode( x = "yield", y = "variety", color = "site", column = "year" )$ properties(width = 220) chart
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