This page demonstrates standalone charts (no tabsets) for key findings.
For example, you could use this layout to visualize the most important trends or overarching themes of your data.
This standalone chart shows the overall distribution of happiness across education levels.
Subtitle for your standalone chart.
---
title: "{{< iconify ph chart-pie >}} Standalone Charts"
format: html
---
This page demonstrates standalone charts (no tabsets) for key findings.
For example, you could use this layout to visualize the most important trends or overarching themes of your data.
```{r setup}
#| echo: false
#| warning: false
#| message: false
#| error: false
#| results: 'hide'
# Load required libraries
library(dashboardr)
library(dplyr)
library(highcharter)
# Global chunk options
knitr::opts_chunk$set(
echo = FALSE,
warning = FALSE,
message = FALSE,
error = FALSE,
fig.width = 12,
fig.height = 8,
dpi = 300
)
# Load data from dataset_2867obs.rds
data <- readRDS('dataset_2867obs.rds')
# Data summary
cat('Dataset loaded:', nrow(data), 'rows,', ncol(data), 'columns\n')
```
## {{< iconify ph chart-bar >}} This is a standalone chart.
This standalone chart shows the overall distribution of happiness across education levels.
```{r stackedbar-degree-1a-happy-1a}
# This is a standalone chart.
result <- create_stackedbar(
data = data,
title = "This is a standalone chart.",
x_var = "degree_1a",
stack_var = "happy_1a",
subtitle = "Here you'll notice that this is a standalone plot.",
x_label = "Education Level",
y_label = "Percentage of Respondents",
stack_label = "Happiness Level",
stacked_type = "percent",
x_order = c("Lt High School", "High School", "Junior College", "Bachelor", "Graduate"),
stack_order = c("Very Happy", "Pretty Happy", "Not Too Happy"),
tooltip_suffix = "%",
color_palette = c("#2E86AB", "#A23B72", "#F18F01")
)
# Apply height to highcharter object
if (inherits(result, 'highchart')) {
result <- highcharter::hc_chart(result, height = 600)
}
result
```
## {{< iconify ph shield-check >}} Here's another summary chart
```{r heatmap-partyid-1a-polviews-1a}
# Here's another summary chart
result <- create_heatmap(
data = data,
title = "Here's another summary chart",
x_var = "partyid_1a",
y_var = "polviews_1a",
value_var = "trust_1a",
subtitle = "This summary chart visualizes trust patterns across political groups",
x_label = "Party Identification",
y_label = "Political Views",
value_label = "Trust Level",
x_order = c("Strong Democrat", "Not Very Strong Democrat", "Independent, Close to Democrat", "Independent", "Independent, Close to Republican", "Not Very Strong Republican", "Strong Republican"),
y_order = c("Extremely Liberal", "Liberal", "Slightly Liberal", "Moderate", "Slightly Conservative", "Conservative", "Extremely Conservative"),
color_palette = c("#d7191c", "#fdae61", "#ffffbf", "#abdda4", "#2b83ba"),
tooltip_prefix = "Trust: ",
tooltip_suffix = "/3",
tooltip_labels_format = "{point.value:.2f}"
)
# Apply height to highcharter object
if (inherits(result, 'highchart')) {
result <- highcharter::hc_chart(result, height = 700)
}
result
```
Subtitle for your standalone chart.