From d59dd3e91fec6816a75ae2b60452c529cfaac219 Mon Sep 17 00:00:00 2001
From: "jeffey97@gmail.com" <jeffey97@gmail.com>
Date: Sun, 10 Nov 2024 16:57:43 -0500
Subject: [PATCH] Comment on immediate recording of target variable income
 provided

---
 02_activities/assignments/assignment_2.ipynb | 58 ++++++++++++++------
 1 file changed, 40 insertions(+), 18 deletions(-)

diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb
index 5008f2cdd..13d0a2459 100644
--- a/02_activities/assignments/assignment_2.ipynb
+++ b/02_activities/assignments/assignment_2.ipynb
@@ -25,7 +25,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -57,7 +57,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -84,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [
     {
@@ -151,7 +151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -214,7 +214,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -242,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
@@ -310,7 +310,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
@@ -320,11 +320,11 @@
       "Sorted Cross-Validation Results by Test Negative Log Loss:\n",
       "\n",
       "   fit_time  score_time  test_neg_log_loss  train_neg_log_loss  test_roc_auc  \\\n",
-      "1  3.270346    0.146423          -0.331249           -0.309713      0.906679   \n",
-      "0  3.128752    0.165946          -0.330795           -0.311253      0.907006   \n",
-      "2  3.231312    0.153061          -0.329205           -0.313765      0.910617   \n",
-      "4  2.981757    0.148714          -0.325861           -0.313799      0.914390   \n",
-      "3  2.921376    0.148241          -0.323481           -0.310539      0.914494   \n",
+      "1  3.632418    0.175431          -0.331249           -0.309713      0.906679   \n",
+      "0  3.129728    0.156102          -0.330795           -0.311253      0.907006   \n",
+      "2  2.931507    0.144618          -0.329205           -0.313765      0.910617   \n",
+      "4  3.292911    0.146331          -0.325861           -0.313799      0.914390   \n",
+      "3  3.131725    0.149254          -0.323481           -0.310539      0.914494   \n",
       "\n",
       "   train_roc_auc  test_accuracy  train_accuracy  test_balanced_accuracy  \\\n",
       "1       0.926736       0.855651        0.865331                0.747288   \n",
@@ -362,7 +362,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [
     {
@@ -370,8 +370,8 @@
      "output_type": "stream",
      "text": [
       "Mean values for each metric across the folds:\n",
-      "fit_time                   3.106709\n",
-      "score_time                 0.152477\n",
+      "fit_time                   3.223658\n",
+      "score_time                 0.154347\n",
       "test_neg_log_loss         -0.328118\n",
       "train_neg_log_loss        -0.311814\n",
       "test_roc_auc               0.910637\n",
@@ -403,7 +403,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
@@ -449,10 +449,32 @@
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 69,
    "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[92mThe target variable 'income' was recoded to:\n",
+      "  -  1 for >50K \n",
+      "  -  0 for <=50K \n",
+      "1.This transformation ensures compatibility with machine learning algorithms that expect numeric targets.\n",
+      "2.Simplifies data processing and avoids the need for later conversions.\n",
+      "3.Removes extra whitespace using 'str.strip()' for consistent data.\n",
+      "4.Makes subsequent modeling steps more efficient by treating 'income' as a clean, binary numeric variable.\u001b[0m\n"
+     ]
+    }
+   ],
    "source": [
-    "(Answer here.)"
+    "print(\"\\033[92mThe target variable 'income' was recoded to:\")\n",
+    "print(\"  -  1 for >50K \")\n",
+    "print(\"  -  0 for <=50K \")\n",
+    "print(\"1.This transformation ensures compatibility with machine learning algorithms that expect numeric targets.\")\n",
+    "print(\"2.Simplifies data processing and avoids the need for later conversions.\")\n",
+    "print(\"3.Removes extra whitespace using 'str.strip()' for consistent data.\")\n",
+    "print(\"4.Makes subsequent modeling steps more efficient by treating 'income' as a clean, binary numeric variable.\\033[0m\")\n"
    ]
   },
   {