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Table of contents

  • 1 Introduction
  • 2 Required Packages and Setup
  • 3 The Problem/Data
  • 4 Analysis/Tutorial Steps
    • 4.1 Step 1: Initial Data Exploration
    • 4.2 Step 2: Main Analysis
    • 4.3 Step 3: Results and Visualization
  • 5 Key Takeaways
  • 6 Reproducibility
  • 7 Next Steps
  • 8 References

Your Technical Blog Post Title

R
Analysis
Tutorial

A brief, engaging description of your post (appears in previews and social sharing). Keep it under 2-3 sentences.

Author

Your Name

Published

December 22, 2024

PDF Version Available
This article can be generated as a PDF for offline reading or printing.
To generate PDF: Run this command in your terminal:
./generate_pdf.sh posts/setupquarto/quarto-blog-template.qmd

1 Introduction

Brief introduction that:

  • Hooks the reader with an interesting problem or observation
  • States the purpose of your analysis/tutorial
  • Outlines what readers will learn or gain

2 Required Packages and Setup

# List the packages readers will need
library(tidyverse)
# Add other packages

Brief explanation of why these packages were chosen and any setup requirements.

3 The Problem/Data

# Data loading and initial preparation
# Load sample dataset
data <- mtcars
glimpse(data)
Rows: 32
Columns: 11
$ mpg  <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 19.2, 17.8,…
$ cyl  <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8,…
$ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7, 140.8, 16…
$ hp   <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180…
$ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,…
$ wt   <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.…
$ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00, 22.90, 18…
$ vs   <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0,…
$ am   <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0,…
$ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3,…
$ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2,…
  • Describe your data source
  • Explain the problem you’re addressing
  • Share any initial data preparation steps

4 Analysis/Tutorial Steps

4.1 Step 1: Initial Data Exploration

# Your analysis code here
glimpse(mtcars)
Rows: 32
Columns: 11
$ mpg  <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 19.2, 17.8,…
$ cyl  <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8,…
$ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7, 140.8, 16…
$ hp   <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180…
$ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,…
$ wt   <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.…
$ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00, 22.90, 18…
$ vs   <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0,…
$ am   <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0,…
$ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3,…
$ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2,…
ggplot(mtcars, aes(x=cyl, y=mpg)) +
  geom_point()

Description of your visualization
  # Your visualization

Explain what you found and why it’s interesting.

4.2 Step 2: Main Analysis

# Core analysis code

Walk through your analysis, explaining: - Why you chose this approach - What the code does - What the results mean

4.3 Step 3: Results and Visualization

# Create compelling visualizations

Interpret your results and explain their significance.

5 Key Takeaways

  • Bullet point summary of main findings
  • Practical applications
  • Important insights

6 Reproducibility

# Print session info for reproducibility
sessionInfo()
R version 4.5.0 (2025-04-11)
Platform: aarch64-apple-darwin20
Running under: macOS Sequoia 15.5

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Los_Angeles
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] here_1.0.1      lubridate_1.9.4 forcats_1.0.0   stringr_1.5.1  
 [5] dplyr_1.1.4     purrr_1.0.4     readr_2.1.5     tidyr_1.3.1    
 [9] tibble_3.3.0    ggplot2_3.5.2   tidyverse_2.0.0

loaded via a namespace (and not attached):
 [1] gtable_0.3.6       jsonlite_2.0.0     compiler_4.5.0     tidyselect_1.2.1  
 [5] scales_1.4.0       yaml_2.3.10        fastmap_1.2.0      R6_2.6.1          
 [9] labeling_0.4.3     generics_0.1.4     knitr_1.50         htmlwidgets_1.6.4 
[13] rprojroot_2.0.4    pillar_1.10.2      RColorBrewer_1.1-3 tzdb_0.5.0        
[17] rlang_1.1.6        stringi_1.8.7      xfun_0.52          timechange_0.3.0  
[21] cli_3.6.5          withr_3.0.2        magrittr_2.0.3     digest_0.6.37     
[25] grid_4.5.0         hms_1.1.3          lifecycle_1.0.4    vctrs_0.6.5       
[29] evaluate_1.0.3     glue_1.8.0         farver_2.1.2       rmarkdown_2.29    
[33] tools_4.5.0        pkgconfig_2.0.3    htmltools_0.5.8.1 

7 Next Steps

  • Suggest areas for further exploration
  • Mention potential improvements
  • Invite reader engagement

8 References

  • Cite your sources
  • Link to relevant documentation
  • Credit other contributors

Reuse

CC BY 4.0

Citation

BibTeX citation:
@online{(ryy)_glenn_thomas2024,
  author = {(Ryy) Glenn Thomas, Ronald and Name, Your},
  title = {Your {Technical} {Blog} {Post} {Title}},
  date = {2024-12-22},
  url = {https://focusonr.org/posts/setupquarto/quarto-blog-template.html},
  langid = {en}
}
For attribution, please cite this work as:
(Ryy) Glenn Thomas, Ronald, and Your Name. 2024. “Your Technical Blog Post Title.” December 22, 2024. https://focusonr.org/posts/setupquarto/quarto-blog-template.html.
Source Code
---
title: "Your Technical Blog Post Title"
author: "Your Name"
date: "2024-12-22"
categories: [R, Analysis, Tutorial]
image: "~/img/Rlogo.png"
description: |
  A brief, engaging description of your post (appears in previews and social sharing).
  Keep it under 2-3 sentences.
tags:
  - r
  - data-analysis
  - visualization
format:
  html:
    toc: true
    code-fold: false
    code-tools: true
execute:
  warning: false
  message: false
---

```{r}
#| label: load-packages
#| include: false

library(tidyverse)
library(here)
# Add other required packages
```

## Introduction

Brief introduction that:

- Hooks the reader with an interesting problem or observation
- States the purpose of your analysis/tutorial
- Outlines what readers will learn or gain

## Required Packages and Setup

```{r}
#| label: package-demo
#| code-fold: false

# List the packages readers will need
library(tidyverse)
# Add other packages
```

Brief explanation of why these packages were chosen and any setup requirements.

## The Problem/Data

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

# Data loading and initial preparation
# Load sample dataset
data <- mtcars
glimpse(data)
```

- Describe your data source
- Explain the problem you're addressing
- Share any initial data preparation steps

## Analysis/Tutorial Steps

### Step 1: Initial Data Exploration

```{r}
#| label: exploration
#| fig-cap: "Description of your visualization"

# Your analysis code here
glimpse(mtcars)
ggplot(mtcars, aes(x=cyl, y=mpg)) +
  geom_point()
  # Your visualization
```

Explain what you found and why it's interesting.

### Step 2: Main Analysis

```{r}
#| label: analysis

# Core analysis code
```

Walk through your analysis, explaining:
- Why you chose this approach
- What the code does
- What the results mean

### Step 3: Results and Visualization

```{r}
#| label: visualization
#| fig-width: 8
#| fig-height: 6

# Create compelling visualizations
```

Interpret your results and explain their significance.

## Key Takeaways

- Bullet point summary of main findings
- Practical applications
- Important insights

## Reproducibility

```{r}
#| label: reproducibility
#| code-fold: false

# Print session info for reproducibility
sessionInfo()
```

## Next Steps

- Suggest areas for further exploration
- Mention potential improvements
- Invite reader engagement

## References

- Cite your sources
- Link to relevant documentation
- Credit other contributors

<!-- R-bloggers submission metadata -->
<!-- Tags: R, your-topic-tags -->
<!-- Category: R -->

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