From d2daa6d13696813e7d968389fdb73439b96e4f84 Mon Sep 17 00:00:00 2001
From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Fri, 27 Feb 2026 08:07:13 +0000
Subject: [PATCH] fix: correct variable name cuisines_feature_df to
 cuisines_features_df in 4-Classification/3-Classifiers-2

Co-authored-by: leestott <2511341+leestott@users.noreply.github.com>
---
 4-Classification/3-Classifiers-2/README.md               | 2 +-
 4-Classification/3-Classifiers-2/notebook.ipynb          | 4 ++--
 4-Classification/3-Classifiers-2/solution/notebook.ipynb | 6 +++---
 3 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/4-Classification/3-Classifiers-2/README.md b/4-Classification/3-Classifiers-2/README.md
index d5d190a33..dd996336c 100644
--- a/4-Classification/3-Classifiers-2/README.md
+++ b/4-Classification/3-Classifiers-2/README.md
@@ -53,7 +53,7 @@ Following this path, we should start by importing some libraries to use.
 1. Split your training and test data:
 
     ```python
-    X_train, X_test, y_train, y_test = train_test_split(cuisines_feature_df, cuisines_label_df, test_size=0.3)
+    X_train, X_test, y_train, y_test = train_test_split(cuisines_features_df, cuisines_label_df, test_size=0.3)
     ```
 
 ## Linear SVC classifier
diff --git a/4-Classification/3-Classifiers-2/notebook.ipynb b/4-Classification/3-Classifiers-2/notebook.ipynb
index 4659a7b62..8f675b0a4 100644
--- a/4-Classification/3-Classifiers-2/notebook.ipynb
+++ b/4-Classification/3-Classifiers-2/notebook.ipynb
@@ -116,8 +116,8 @@
     }
    ],
    "source": [
-    "cuisines_feature_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n",
-    "cuisines_feature_df.head()"
+    "cuisines_features_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n",
+    "cuisines_features_df.head()"
    ]
   }
  ],
diff --git a/4-Classification/3-Classifiers-2/solution/notebook.ipynb b/4-Classification/3-Classifiers-2/solution/notebook.ipynb
index a089b21fa..d94f313b9 100644
--- a/4-Classification/3-Classifiers-2/solution/notebook.ipynb
+++ b/4-Classification/3-Classifiers-2/solution/notebook.ipynb
@@ -116,8 +116,8 @@
     }
    ],
    "source": [
-    "cuisines_feature_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n",
-    "cuisines_feature_df.head()"
+    "cuisines_features_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n",
+    "cuisines_features_df.head()"
    ]
   },
   {
@@ -148,7 +148,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "X_train, X_test, y_train, y_test = train_test_split(cuisines_feature_df, cuisines_label_df, test_size=0.3)"
+    "X_train, X_test, y_train, y_test = train_test_split(cuisines_features_df, cuisines_label_df, test_size=0.3)"
    ]
   },
   {