Themes and Styling

library(ggplot2)
library(benviplot)

Introduction

Visual consistency is key to professional data visualization. This vignette shows you how to use and customize theme_benvi() to create polished, publication-ready graphics.

The theme_benvi() Theme

theme_benvi() provides a clean, modern aesthetic designed for clarity and readability:

• Clean background: White with minimal gridlines
• Professional typography: Poppins font family
• Smart defaults: Legend on top, appropriate text sizes
• Flexible: Easy to customize

Basic Usage

Simply add theme_benvi() to any ggplot:

ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point(color = benvi_palette("purples")[1], size = 3) +
  labs(
    title = "Fuel Efficiency vs. Weight",
    subtitle = "Using theme_benvi()",
    x = "Weight (1000 lbs)",
    y = "Miles per Gallon"
  ) +
  theme_benvi()

Comparing with Default Theme

# Create base plot
p <- ggplot(mtcars, aes(x = wt, y = mpg, color = as.factor(cyl))) +
  geom_point(size = 3) +
  scale_color_benvi_d(pal_name = "qual_5", name = "Cylinders") +
  labs(
    title = "Fuel Efficiency Analysis",
    x = "Weight (1000 lbs)",
    y = "Miles per Gallon"
  )

# Default ggplot2 theme
p1 <- p + labs(subtitle = "Default theme_gray()") + theme_gray()

# benvi theme
p2 <- p + labs(subtitle = "theme_benvi()") + theme_benvi()

# Display side by side (requires patchwork or gridExtra)
# For vignette, we'll show separately
p1

p2

Theme Components

Typography

theme_benvi() uses the Poppins font with carefully chosen sizes:

• Title: 12pt, black
• Subtitle: 8pt, dark gray
• Body text: 10pt, dark gray
• Caption: 6pt, dark gray

ggplot(economics, aes(x = date, y = unemploy / 1000)) +
  geom_line(color = benvi_palette("browns")[1], linewidth = 1) +
  labs(
    title = "Title: Clear and Prominent",
    subtitle = "Subtitle: Provides additional context",
    x = "X-axis label",
    y = "Y-axis label",
    caption = "Caption: Source information or notes"
  ) +
  theme_benvi()

Grid Lines

Only major grid lines are shown for cleaner appearance:

# With theme_benvi (major grid only)
ggplot(mtcars, aes(x = factor(cyl), y = mpg)) +
  geom_boxplot(fill = benvi_palette("greens")[1]) +
  labs(title = "Clean Grid: Major Lines Only") +
  theme_benvi()

Legend Position

Default legend position is on top for better readability:

ggplot(mtcars, aes(x = wt, y = mpg, color = as.factor(cyl))) +
  geom_point(size = 3) +
  scale_color_benvi_d(pal_name = "purples", name = "Cylinders") +
  labs(title = "Legend on Top (Default)") +
  theme_benvi()

Font Management

Modern Font System (v1.1.0+)

benviplot uses a modern font system based on systemfonts. Fonts are installed to your system once and work across all R sessions.

One-Time Font Setup

Install Poppins font to your system:

# Recommended: Complete setup in one command
setup_benvi_fonts()

# Or install just the font
install_poppins()

That’s it! The font is now available system-wide and will work in all R sessions.

Automatic Fallback

If Poppins isn’t installed, theme_benvi() automatically falls back to your system’s default font. You’ll see a one-time message suggesting installation:

# Works even without Poppins installed
ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  theme_benvi()
#> ℹ Poppins font not found. Using system default font instead.
#> ℹ Install Poppins with: benviplot::install_poppins()

Check Font Status

Verify your font setup:

# Check if Poppins is installed
check_poppins_installed()

# Get full status report
font_status()

Using Other Fonts

Override the default font family with theme():

ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  theme_benvi() +
  theme(text = element_text(family = "Roboto"))

For Best Results: Install ragg

For optimal text rendering quality:

install.packages("ragg")

# Then configure RStudio:
# Tools > Global Options > General > Graphics > Backend: AGG

See vignette("font-setup") for detailed instructions and troubleshooting.

Customizing theme_benvi()

theme_benvi() is a starting point. Customize it with additional theme() calls:

Change Legend Position

ggplot(mtcars, aes(x = wt, y = mpg, color = as.factor(cyl))) +
  geom_point(size = 3) +
  scale_color_benvi_d(pal_name = "oranges", name = "Cylinders") +
  labs(title = "Legend on Right") +
  theme_benvi() +
  theme(legend.position = "right")

Adjust Text Sizes

ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point(color = benvi_palette("yellows")[1], size = 3) +
  labs(
    title = "Larger Text for Presentations",
    x = "Weight",
    y = "MPG"
  ) +
  theme_benvi() +
  theme(
    plot.title = element_text(size = 16),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10)
  )

Rotate Axis Labels

products <- data.frame(
  product = c("Product A", "Product B", "Product C", "Product D"),
  sales = c(120, 200, 150, 180)
)

ggplot(products, aes(x = product, y = sales)) +
  geom_col(fill = benvi_palette("blues")[1]) +
  labs(title = "Rotated X-Axis Labels") +
  theme_benvi() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

Remove Grid Lines

ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point(color = benvi_palette("rio_qual")[1], size = 3) +
  labs(title = "No Grid Lines") +
  theme_benvi() +
  theme(
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank()
  )

Add Background Color

ggplot(economics, aes(x = date, y = unemploy)) +
  geom_area(fill = benvi_palette("seq_purples")[5], alpha = 0.7) +
  labs(title = "Custom Background Color") +
  theme_benvi() +
  theme(
    plot.background = element_rect(fill = "#f5f5f5"),
    panel.background = element_rect(fill = "#ffffff")
  )

Creating Publication-Ready Plots

Elements of a Publication Plot

1. Clear title and subtitle
2. Labeled axes with units
3. Data source in caption
4. Appropriate color palette
5. Legend (if needed)
6. Clean, minimal design

# Sample data
housing_subset <- txhousing |>
  dplyr::filter(city %in% c("Austin", "Houston", "Dallas"))

# Publication-ready plot
ggplot(housing_subset, aes(x = date, y = median / 1000, color = city)) +
  geom_line(linewidth = 1.2) +
  scale_color_benvi_d(
    pal_name = "purples",
    name = "City"
  ) +
  labs(
    title = "Median Home Prices in Major Texas Cities",
    subtitle = "2000-2015",
    x = "Year",
    y = "Median Price ($1000s)",
    caption = "Source: Texas A&M Real Estate Center"
  ) +
  theme_benvi() +
  theme(
    plot.title = element_text(size = 14, face = "bold"),
    legend.position = "bottom"
  )

Faceted Plot

ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point(color = benvi_palette("qual_5")[1], size = 2) +
  geom_smooth(
    method = "lm",
    se = FALSE,
    color = benvi_palette("qual_5")[2]
  ) +
  facet_wrap(~ cyl, labeller = label_both) +
  labs(
    title = "Fuel Efficiency by Cylinder Count",
    subtitle = "Linear regression fits shown",
    x = "Weight (1000 lbs)",
    y = "Miles per Gallon",
    caption = "Data: mtcars dataset"
  ) +
  theme_benvi() +
  theme(
    strip.text = element_text(size = 10, face = "bold")
  )

Advanced Customization

Creating a Custom Theme

Build on theme_benvi() to create your own theme:

# Define custom theme
theme_presentation <- function() {
  theme_benvi() +
    theme(
      # Larger text for visibility
      text = element_text(size = 14),
      plot.title = element_text(size = 18, face = "bold"),
      plot.subtitle = element_text(size = 14),
      axis.title = element_text(size = 14),
      axis.text = element_text(size = 12),

      # Legend
      legend.text = element_text(size = 12),
      legend.title = element_text(size = 12, face = "bold"),
      legend.position = "bottom",

      # More spacing
      plot.margin = margin(20, 20, 20, 20)
    )
}

# Use custom theme
ggplot(mtcars, aes(x = wt, y = mpg, color = as.factor(cyl))) +
  geom_point(size = 4) +
  scale_color_benvi_d(pal_name = "purples", name = "Cylinders") +
  labs(
    title = "Presentation-Sized Plot",
    subtitle = "Larger text for readability"
  ) +
  theme_presentation()

Theme for Reports

theme_report <- function() {
  theme_benvi() +
    theme(
      # Smaller, compact
      text = element_text(size = 9),
      plot.title = element_text(size = 11),
      plot.subtitle = element_text(size = 9),

      # No legend title to save space
      legend.title = element_blank(),
      legend.position = "top",

      # Tight margins
      plot.margin = margin(5, 5, 5, 5)
    )
}

# Use in report
ggplot(economics, aes(x = date, y = uempmed)) +
  geom_line(color = benvi_palette("browns")[1]) +
  labs(
    title = "Median Unemployment Duration",
    caption = "Source: FRED"
  ) +
  theme_report()

Combining Themes with Scales

Always use benvi scales with benvi theme for consistency:

ggplot(mtcars, aes(x = factor(cyl), y = mpg, fill = factor(cyl))) +
  geom_boxplot(show.legend = FALSE) +
  scale_fill_benvi_d(pal_name = "pinks") +  # benvi scale
  labs(
    title = "MPG Distribution by Cylinders",
    x = "Number of Cylinders",
    y = "Miles per Gallon"
  ) +
  theme_benvi()  # benvi theme

Saving Plots

Recommended: Use ggsave_benvi()

benviplot provides ggsave_benvi() which automatically uses the ragg graphics device for high-quality output:

p <- ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point(color = benvi_palette("purples")[1], size = 3) +
  labs(title = "Fuel Efficiency") +
  theme_benvi()

# Recommended: Uses ragg automatically for PNG
ggsave_benvi("plot.png", p)

# PDF (vector graphics)
ggsave_benvi("plot.pdf", p, width = 7, height = 5)

Benefits of ggsave_benvi(): - Automatically uses ragg device for PNG files (better quality, no font issues) - Smart defaults (300 DPI, 7x5 inches) - Consistent output across platforms

For Print

# High-resolution for publication
ggsave_benvi("plot.png", p, width = 7, height = 5)

For Presentations

# Larger size for slides
ggsave_benvi("slide.png", p, width = 10, height = 6)

For Web

# Standard web resolution
ggsave_benvi("web_plot.png", p, width = 8, height = 5)

Using Standard ggsave()

You can still use regular ggsave() if preferred:

ggsave("plot.png", p, width = 7, height = 5, dpi = 300)

Accessibility Tips

Color Considerations

# Use patterns in addition to colors
ggplot(mtcars, aes(x = factor(cyl), y = mpg, fill = factor(cyl))) +
  geom_violin(show.legend = FALSE) +
  scale_fill_benvi_d(pal_name = "purples") +
  labs(
    title = "Distribution Shape Helps Convey Information",
    subtitle = "Don't rely solely on color",
    x = "Cylinders"
  ) +
  theme_benvi()

Sufficient Contrast

Ensure text is readable:

# Good contrast between text and background
ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point(size = 3, color = benvi_palette("browns")[1]) +
  labs(
    title = "Clear, High-Contrast Text",
    x = "Weight",
    y = "MPG"
  ) +
  theme_benvi() +
  theme(
    plot.background = element_rect(fill = "white"),
    text = element_text(color = "black")
  )

Alt Text for Reports

When including plots in documents, always add alt text:

# In RMarkdown, use fig.alt
# ```{r, fig.alt="Scatter plot showing negative correlation between weight and MPG"}
# plot here
# ```

Common Styling Patterns

Minimal Plot

ggplot(economics, aes(x = date, y = unemploy)) +
  geom_line(color = benvi_palette("browns")[1], linewidth = 1) +
  theme_benvi() +
  theme(
    axis.title = element_blank(),
    panel.grid = element_blank(),
    plot.title = element_text(face = "bold")
  ) +
  labs(title = "US Unemployment")

Data-Focused (No Decorations)

ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point(size = 3, color = benvi_palette("rio_qual")[1]) +
  theme_benvi() +
  theme(
    panel.grid = element_blank(),
    axis.line = element_line(color = "gray30"),
    axis.ticks = element_line(color = "gray30")
  )

Highlighted Plot

# Emphasize one series
mtcars_highlight <- mtcars
mtcars_highlight$highlight <- ifelse(mtcars$cyl == 6, "Six", "Other")

ggplot(mtcars_highlight, aes(x = wt, y = mpg, color = highlight)) +
  geom_point(size = 3) +
  scale_color_manual(
    values = c("Six" = benvi_palette("purples")[1], "Other" = "gray70")
  ) +
  labs(
    title = "Highlighting 6-Cylinder Vehicles",
    subtitle = "Others shown in gray",
    color = NULL
  ) +
  theme_benvi()

Summary

In this vignette you learned:

• ✓ How to use theme_benvi() for professional plots
• ✓ Font management and troubleshooting
• ✓ Customizing theme elements
• ✓ Creating publication-ready graphics
• ✓ Building custom themes
• ✓ Accessibility considerations
• ✓ Common styling patterns

Best Practices Checklist

• Use theme_benvi() for consistency
• Always label axes with units
• Add informative titles and subtitles
• Include data sources in captions
• Choose appropriate palettes
• Ensure sufficient contrast
• Test in grayscale (for print)
• Keep legends clear and concise
• Remove unnecessary elements
• Consider your audience (presentation vs. report)

Next Steps

• Review vignette("color-palettes") for palette selection
• See vignette("plot-functions") for helper functions
• Explore ?theme_benvi for full documentation

Further Reading

• ggplot2 Theme Elements
• R Graphics Cookbook
• Data Visualization Best Practices