markdown source builds

Auto-generated via {sandpaper}
Source  : 64fb4bf
Branch  : main
Author  : David Palmquist <[email protected]>
Time    : 2024-02-05 16:28:33 +0000
Message : Merge pull request #584 from datacarpentry/improveExpandJoinsDiscussion

Update join types in pandas merge function

Author: actions-user

05-merging-data.md

@@ -434,16 +434,20 @@ case, `PF`) does not occur in `species_sub`.
 
 ### Other join types
 
-The pandas `merge` function supports two other join types:
+The pandas `merge` function supports other join types:
 
 - Right (outer) join: Invoked by passing `how='right'` as an argument. Similar
   to a left join, except *all* rows from the `right` DataFrame are kept, while
   rows from the `left` DataFrame without matching join key(s) values are
   discarded.
 - Full (outer) join: Invoked by passing `how='outer'` as an argument. This join
-  type returns the all pairwise combinations of rows from both DataFrames; i.e.,
-  the result DataFrame will `NaN` where data is missing in one of the dataframes. This join type is
-  very rarely used.
+  type returns the all pairwise combinations of rows from both DataFrames; i.e., the
+  *Cartesian product* and the result DataFrame will use `NaN` where data is missing in one 
+  of the dataframes. This join type is very rarely used, but can be helpful to see all
+  the qualities of both tables, including each common and duplicate column.
+- Self-join: Joins a data frame with itself. Self-joins can be useful when you want to, for
+  instance, compare records within the same dataset based on a given criteria. A fuller discussion 
+  of how and when it might be useful to do so can be found in [Self-Join and Cross Join in Pandas DataFrame](https://blog.devgenius.io/self-join-and-cross-join-in-pandas-dataframe-b30bfbc0e52a)
 
 ## Final Challenges
 

md5sum.txt

@@ -9,7 +9,7 @@
 "episodes/02-starting-with-data.md" "bcd4e9564bd01585a52754fe4ad46f45" "site/built/02-starting-with-data.md" "2023-05-29"
 "episodes/03-index-slice-subset.md" "84263a14ba3f492bf6aa17435a78d905" "site/built/03-index-slice-subset.md" "2023-08-18"
 "episodes/04-data-types-and-format.md" "e57b9b771e5d2dcf4c9e2521822f8d5a" "site/built/04-data-types-and-format.md" "2023-06-05"
-"episodes/05-merging-data.md" "d7c67295a4bc6ba9b4237cff0f8fd322" "site/built/05-merging-data.md" "2023-05-19"
+"episodes/05-merging-data.md" "5e0cb1f86b8cb29a87d57b8eaee9acf5" "site/built/05-merging-data.md" "2024-02-05"
 "episodes/06-loops-and-functions.md" "d41f11e6c162c86393cd9bd4431c0687" "site/built/06-loops-and-functions.md" "2023-05-18"
 "episodes/07-visualization-ggplot-python.md" "814b6fc361595a0c9ea7db393b1424db" "site/built/07-visualization-ggplot-python.md" "2023-05-19"
 "episodes/08-putting-it-all-together.md" "b279a4ab47789abda7f71609a78022ed" "site/built/08-putting-it-all-together.md" "2024-01-31"