From 54fc9f37e2a009a27a394a684c5e0bd2f010a2e4 Mon Sep 17 00:00:00 2001
From: GitHub Actions <actions@github.com>
Date: Wed, 16 Oct 2024 14:30:04 +0000
Subject: [PATCH] differences for PR #142

---
 looping-data-sets.md | 1 +
 md5sum.txt           | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/looping-data-sets.md b/looping-data-sets.md
index 6c98c183..dbbacdab 100644
--- a/looping-data-sets.md
+++ b/looping-data-sets.md
@@ -23,6 +23,7 @@ exercises: 10
 If you recall from episode 06, the `pd.read_csv()` method takes a text string referencing a filename as an argument. If we have a list of strings that point to our filenames, we can loop through the list to read in each CSV file as a DataFrame. Let's print out the maximum values from the 'ytd' (year to date) column for each DataFrame.
 
 ```python
+import pandas as pd
 for filename in ['data/2011_circ.csv', 'data/2012_circ.csv']:
   data = pd.read_csv(filename)
   print(filename, data['ytd'].max())
diff --git a/md5sum.txt b/md5sum.txt
index 21ca5091..786b1884 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -9,7 +9,7 @@
 "episodes/functions.md" "499deb6ac29cdd4a00134176ef890616" "site/built/functions.md" "2024-06-17"
 "episodes/libraries.md" "e1ea10719dd52d371c0a5a2bf03f687b" "site/built/libraries.md" "2024-06-17"
 "episodes/for-loops.md" "a44b90e5f6f451c1659b7f877e0c0c4d" "site/built/for-loops.md" "2024-06-27"
-"episodes/looping-data-sets.md" "56880c06991a04425c2cf8fe52ddbede" "site/built/looping-data-sets.md" "2024-06-17"
+"episodes/looping-data-sets.md" "ff153b594bf9543fa2ed4890c4d3ef71" "site/built/looping-data-sets.md" "2024-10-16"
 "episodes/pandas.md" "5f2461a95e56e8aa3aa6851f12d3d566" "site/built/pandas.md" "2024-06-17"
 "episodes/conditionals.md" "b567ac5270b3dc82c4ed119870a0a890" "site/built/conditionals.md" "2024-06-17"
 "episodes/writing-functions.md" "99171306646b8b63c66a493acef12e63" "site/built/writing-functions.md" "2024-06-17"