From a2d5831c0c7ff3fa4629a97d8679c515f8794824 Mon Sep 17 00:00:00 2001
From: "Y. Yu" <54338793+PursuitOfDataScience@users.noreply.github.com>
Date: Tue, 11 Jan 2022 20:17:11 -0500
Subject: [PATCH] Update analysis.Rmd

Fixed the expired link by replacing the valid one.
---
 analysis.Rmd | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/analysis.Rmd b/analysis.Rmd
index 82e89ab..8238451 100644
--- a/analysis.Rmd
+++ b/analysis.Rmd
@@ -429,7 +429,7 @@ ggplot(aes(as.factor(cyl), mpg), data = car_group) +
 render_image("images/analysis-visualizations-1.png")
 ```
 
-Any other `ggplot2` visualization can be made to work using this approach; however, this is beyond the scope of the book. Instead, we recommend that you read [_R Graphics Cookbook_](https://oreil.ly/bIF4), by Winston Chang (O'Reilly) to learn additional visualization techniques applicable to Spark. Now, to ease this transformation step before visualizing, the `dbplot` package provides a few ready-to-use visualizations that automate aggregation in Spark.
+Any other `ggplot2` visualization can be made to work using this approach; however, this is beyond the scope of the book. Instead, we recommend that you read [_R Graphics Cookbook_](https://r-graphics.org/), by Winston Chang (O'Reilly) to learn additional visualization techniques applicable to Spark. Now, to ease this transformation step before visualizing, the `dbplot` package provides a few ready-to-use visualizations that automate aggregation in Spark.
 
 ### Using dbplot