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Plot Advanced Employment Gantt Chart with Career Metrics Summary

Source: R/vecshift_plots.R
plot_employment_gantt_advanced.Rd

Creates a sophisticated two-panel visualization combining employment Gantt charts with career metrics summary displays. This advanced function integrates employment timelines with comprehensive career performance indicators, providing deep insights into career trajectories and professional development patterns. The function ensures perfect color consistency with plot_employment_gantt() and uses identical person selection logic for reproducible research.

Usage

plot_employment_gantt_advanced(
  data,
  career_metrics_data = NULL,
  person_ids = NULL,
  metrics_to_show = c("career_success_index", "career_advancement_index",
    "employment_security_index", "career_complexity_index"),
  metrics_viz_type = "bar",
  max_persons = 5,
  palette = "Set2",
  title = "Employment Timeline and Career Metrics",
  show_legend = TRUE
)

Arguments

data

Data.table or data.frame containing employment segments with required columns: cf (person ID), inizio (start date), fine (end date), stato (employment status). Should be output from vecshift() or compatible format.

career_metrics_data

Data.table or data.frame from calculate_comprehensive_career_metrics() containing career performance indicators. Must include 'cf' column for person matching. When NULL, shows only the Gantt chart (default: NULL)

person_ids

Character or numeric vector. Specific person identifiers to visualize. For reproducible research, always specify person_ids explicitly. When provided, shows only these persons regardless of max_persons parameter. When NULL, uses max_persons to select first N individuals. Example: c(6, 8, 21) (default: NULL)

metrics_to_show

Character vector. Career metrics to display in right panel. Must match column names in career_metrics_data. Common metrics include: "career_success_index", "career_advancement_index", "employment_security_index", "career_complexity_index", "mobility_rate", "employment_rate" (default: c("career_success_index", "career_advancement_index", "employment_security_index", "career_complexity_index"))

metrics_viz_type

Character. Visualization type for career metrics panel: "bar" (side-by-side bars), "dot" (dot plot with faceting), "radar" (circular/polar plot) (default: "bar")

max_persons

Integer. Maximum number of persons to show when person_ids is NULL. Used only for exploratory analysis; specify person_ids for reproducible research (default: 5)

palette

Character. Color palette for career metrics: "Set2" uses RColorBrewer Set2 palette (recommended for accessibility), or fallback to vecshift colors (default: "Set2")

title

Character. Main title for the combined visualization (default: "Employment Timeline and Career Metrics")

show_legend

Logical. Whether to show legends for both panels (default: TRUE). Set to FALSE for cleaner multi-panel publications where legends appear elsewhere

Value

A list containing three elements:

combined_plot

Combined plot object using patchwork if available, otherwise a list of plots or single plot

gantt_plot

Individual Gantt chart (ggplot2 object) showing employment timeline

metrics_plot

Individual career metrics visualization (ggplot2 object), NULL if no career_metrics_data provided

The combined_plot can be directly printed or saved. Individual plots allow for custom arrangements or separate analysis.

Details

Two-Panel Design: The visualization consists of two perfectly aligned panels:

  • Left Panel: Employment Gantt chart showing contract timelines, employment statuses, and transitions using standardized employment colors

  • Right Panel: Career metrics summary displayed as bar charts, dot plots, or radar charts showing comparative performance indicators across individuals

Perfect Alignment: Both panels use identical y-axis scaling and person ordering to ensure visual alignment. This is critical for comparing individual employment patterns with their corresponding career metrics.

Color Consistency:

  • Employment statuses use identical colors to plot_employment_gantt()

  • Career metrics use Set2 palette (RColorBrewer) for accessibility

  • All colors are colorblind-friendly and print-compatible

Publication Reproducibility: Like plot_employment_gantt(), this function supports explicit person_ids specification for identical results across analyses. The person selection logic is identical between both functions.

Accessibility Features:

  • Uses colorblind-friendly palettes (Set2, employment colors) with good contrast ratios

  • Clear legends and comprehensive annotations

  • Graceful handling of missing data and mismatched datasets

  • Optimized for both screen display and print reproduction

  • Supports black and white output for print publications

Supported Career Metrics Visualizations:

  • Bar Charts: Best for comparing metric values across individuals with clear visual distinction

  • Dot Plot: Effective for precise value comparison with minimal visual clutter and faceting support

  • Radar Chart: Ideal for showing multi-dimensional metric profiles per person in circular format

Color Standards and Consistency

This function maintains perfect color consistency with other longworkR functions:

  • Employment statuses use identical colors to plot_employment_gantt()

  • Career metrics use Set2 palette for clear distinction from employment colors

  • All palettes are colorblind-accessible and print-friendly

  • Black and white mode available for print publications

Perfect Panel Alignment

The function ensures perfect vertical alignment between panels:

  • Identical y-axis scaling and person ordering

  • Consistent person labeling across both panels

  • Synchronized data filtering and validation

See also

plot_employment_gantt for basic Gantt charts with identical color consistency, calculate_comprehensive_career_metrics for computing career performance indicators, theme_vecshift for the underlying plot theme used in both panels, get_standardized_employment_colors for employment color standardization, vecshift_colors for the broader color palette system

Examples

if (FALSE) { # \dontrun{
# Load sample employment data
employment_data <- readRDS("data/sample.rds")

# Basic Gantt chart only (no metrics) - exploratory analysis
gantt_only <- plot_employment_gantt_advanced(
  data = employment_data,
  max_persons = 3
)
print(gantt_only$combined_plot)

# Calculate comprehensive career metrics first
career_metrics <- calculate_comprehensive_career_metrics(employment_data)

# Publication-ready: Advanced Gantt with career metrics using specific persons
advanced_plot <- plot_employment_gantt_advanced(
  data = employment_data,
  career_metrics_data = career_metrics,
  person_ids = c(6, 8, 21),  # Explicit specification for reproducibility
  title = "Employment and Career Development Analysis"
)
print(advanced_plot$combined_plot)

# Dot plot visualization with custom metrics selection
dot_analysis <- plot_employment_gantt_advanced(
  data = employment_data,
  career_metrics_data = career_metrics,
  person_ids = c("Person_A", "Person_B", "Person_C"),
  metrics_viz_type = "dot",
  metrics_to_show = c("career_success_index", "employment_security_index"),
  title = "Career Development Analysis: Selected Metrics"
)

# Radar chart for multi-dimensional profile comparison
radar_profiles <- plot_employment_gantt_advanced(
  data = employment_data,
  career_metrics_data = career_metrics,
  person_ids = c(1, 5, 10, 15),
  metrics_viz_type = "radar",
  show_legend = FALSE,
  title = "Career Profile Comparison"
)

# Access individual plots for custom arrangements
gantt_chart <- advanced_plot$gantt_plot
metrics_chart <- advanced_plot$metrics_plot

# Print individual components
print(gantt_chart)
print(metrics_chart)

# Save for publication
ggsave("employment_analysis.png", advanced_plot$combined_plot, 
       width = 12, height = 8, dpi = 300)
} # }