Update analyze-baseball-stats-with-pandas-and-matplotlib.mdx

Author: sonnynomnom

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

@@ -56,7 +56,7 @@ As a brief example, this is what the top of the **Batting.csv** file looks like:
 
 Each row represents the batting information for a player for a given year. For example, the first row shows that the player with the ID of `aardsda01` only played in 11 games in 2004 and had no hits or runs!
 
-When looking at new data, it can also be helpful to look for the official data dictionary for the dataset. It can often be hard to interpret column names – for example, if you're not a baseball fan, you might not know what the column `AB` represents. Looking at the documentation file can help clear up any questions. In this case, we can look at **readme2025.txt** to learn that `AB` is "At Bats" (the number of times the player was up to the plate).
+When looking at new data, it can also be helpful to look for the official data dictionary for the dataset. It can often be hard to interpret column names – for example, if you're not a baseball fan, you might not know what the column `AB` represents. Looking at the documentation file can help clear up any questions. In this case, we can look at **[readme2025.txt](https://sabr.app.box.com/s/y1prhc795jk8zvmelfd3jq7tl389y6cd/file/2084259918153)** to learn that `AB` is "At Bats" (the number of times the player was up to the plate).
 
 So with all of that setup out of the way, let's start diving into some data analysis!