From 1f7fe3391533951577f13e719be6f9be38788f92 Mon Sep 17 00:00:00 2001
From: scuti <scuti@tutamail.com>
Date: Sun, 27 Apr 2025 16:23:33 -0700
Subject: [PATCH] Added function show_model_stats().

---
 stackoverflow-survey.ipynb | 45 ++++++++++++++++++--------------------
 1 file changed, 21 insertions(+), 24 deletions(-)

diff --git a/stackoverflow-survey.ipynb b/stackoverflow-survey.ipynb
index 0277e01..41a9311 100644
--- a/stackoverflow-survey.ipynb
+++ b/stackoverflow-survey.ipynb
@@ -240,8 +240,10 @@
     "        X = X + x_shift\n",
     "        y = y + y_shift\n",
     "    \n",
-    "        X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,\n",
-    "                                                            random_state=random)\n",
+    "        X_train, X_test, y_train, y_test = train_test_split(\n",
+    "                                                X, y, \n",
+    "                                                test_size=0.2, \n",
+    "                                                random_state=random)\n",
     "\n",
     "        model = LinearRegression()\n",
     "        model.fit(X_train, y_train)\n",
@@ -249,17 +251,8 @@
     "    \n",
     "        m = model.coef_[0][0]\n",
     "        b = model.intercept_[0]\n",
-    "        print('+----------------------+')\n",
-    "        print('%s regression line for %s' % (color, self.language))\n",
-    "        print('coefficient = %0.2f' % m)\n",
-    "        print('intercept = %0.2f' % b)\n",
-    "        rmse = root_mean_squared_error(y_test, y_pred)\n",
-    "        print('rmse = %0.2f' % rmse)\n",
-    "        r2   = r2_score(y_test, y_pred)\n",
-    "        print('r2 score = %0.2f' % r2)\n",
-    "        print('sample predictions:')\n",
-    "        print(y_pred[3:6])\n",
-    "        print('+----------------------+')\n",
+    "        label = '%s log regression line for %s' % (color, self.language)\n",
+    "        show_model_stats(m, b, y_test, y_pred, label)\n",
     "\n",
     "        plt.figure(self.canvas)\n",
     "        plt.plot(X_test, y_pred, color=color, label=name, linestyle=style)\n",
@@ -282,17 +275,9 @@
     "\n",
     "        m = model.coef_[0][0]\n",
     "        b = model.intercept_[0]\n",
-    "        print('+----------------------+')\n",
-    "        print('%s log regression line for %s' % (color, self.language))\n",
-    "        print('coefficient = %0.2f' % m)\n",
-    "        print('intercept = %0.2f' % b)\n",
-    "        rmse = root_mean_squared_error(y, y_pred)\n",
-    "        print('rmse = %0.2f' % rmse)\n",
-    "        r2   = r2_score(y, y_pred)\n",
-    "        print('r2 score = %0.2f' % r2)\n",
-    "        print('sample predictions:')\n",
-    "        print(y_pred[3:6])\n",
-    "        print('+----------------------+')\n",
+    "        label = '%s log regression line for %s' % (color, self.language)\n",
+    "        show_model_stats(m, b, y, y_pred, label)\n",
+    "\n",
     "        if nodraw:\n",
     "            return\n",
     "        plt.plot(X, y_pred, color=color, label=\"Log regression\")\n",
@@ -303,6 +288,18 @@
     "        filename = base_filename % (self.language, self.country)\n",
     "        plt.savefig(filename.replace(' ', '-'), bbox_inches='tight')\n",
     "\n",
+    "def show_model_stats(coef, intercept, y_test, y_pred, label):\n",
+    "    print('+----------------------+')\n",
+    "    print(label)\n",
+    "    print('coefficient = %0.2f' % coef)\n",
+    "    print('intercept = %0.2f' % intercept)\n",
+    "    rmse = root_mean_squared_error(y_test, y_pred)\n",
+    "    print('rmse = %0.2f' % rmse)\n",
+    "    r2   = r2_score(y_test, y_pred)\n",
+    "    print('r2 score = %0.2f' % r2)\n",
+    "    print('sample predictions:')\n",
+    "    print(y_pred[3:6])\n",
+    "    print('+----------------------+')\n",
     "\n",
     "# the higher a is, the steeper the line gets\n",
     "def log_base_a(x, a=1.07):\n",