{{TITLE}}

TidyTuesday {{DATE}}

Overview

This week’s TidyTuesday focused on [DATASET_DESCRIPTION]. I explored [KEY_INSIGHTS] using {{LANGUAGE}} to [VISUALIZATION_APPROACH].

Dataset

```{{LANGUAGE_CODE}}
#| label: load-data
#| message: false
#| warning: false

# Get data
library(tidytuesdayR)
dat <- tt_load("{{DATE}}")

# Load other required libraries
{{LIBRARY_IMPORTS}}

```

Data Structure

```{{LANGUAGE_CODE}}
#| label: explore-data

# Examine the dataset
{{DATA_EXPLORATION}}
```

Analysis

Data Preparation

```{{LANGUAGE_CODE}}
#| label: prep-data

# Clean and prepare the data
{{DATA_PREPARATION}}
```

Visualization

```{{LANGUAGE_CODE}}
#| label: main-plot
#| fig-width: 12
#| fig-height: 8
#| warning: false

# Create the main visualization
{{MAIN_VISUALIZATION}}
```

Technical Notes

• Data Source: TidyTuesday GitHub Repository
• Analysis Date: {{DATE}}
• Tools Used: {{TOOLS_USED}}
• Key Libraries: {{KEY_LIBRARIES}}

Viz

Next Steps

• [POTENTIAL_IMPROVEMENTS]
• [FUTURE_ANALYSIS_IDEAS]
• [DATA_QUALITY_NOTES]