fix(flow): transition before moneyball section

Author: Goku-kun

projects/analyze-baseball-stats-with-pandas-and-matplotlib/analyze-baseball-stats-with-pandas-and-matplotlib.mdx

@@ -4,7 +4,7 @@ author: Alex Kuntz
 uid: ZjTU0yoJGgNolU9xIJGOR3bxYKm2
 datePublished: 2026-02-02
 published: beta
-description: In this project tutorial, we're going to step into Moneyball and analyze and visualize real MLB baseball data with Python and its two data science ibraries, Pandas and Matplotlib.
+description: In this project tutorial, we're going to step into Moneyball and analyze and visualize real MLB baseball data with Python and its two data science libraries, Pandas and Matplotlib.
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 readTime: 50
@@ -290,6 +290,8 @@ The graph should look like:
 
 As expected, the altitude in Denver has caused some pretty high home run numbers!
 
+Now that we've explored some basic data analysis and visualization, let's put our skills to the test with a more advanced challenge.
+
 ## Replicating Moneyball
 
 Finally, let's take on a challenge of replicating the work Billy Bean and Peter Brand did for the Oakland A's in _Moneyball_. While they almost certainly considered many statistics, they are most famous for finding players with a high **on-base percentage** (OBP) relative to their cost.