From f8f2b9e4bb0ebcbcbcf623d415aa64e9bb75f925 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aur=C3=A9lien=20Geron?= <ageron@users.noreply.github.com>
Date: Wed, 10 Jul 2019 17:08:12 +0200
Subject: [PATCH] Add (USD) after GDP per capita

---
 01_the_machine_learning_landscape.ipynb | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

diff --git a/01_the_machine_learning_landscape.ipynb b/01_the_machine_learning_landscape.ipynb
index 9c51dae..15df3da 100644
--- a/01_the_machine_learning_landscape.ipynb
+++ b/01_the_machine_learning_landscape.ipynb
@@ -353,6 +353,7 @@
     "    plt.annotate(country, xy=(pos_data_x, pos_data_y), xytext=pos_text,\n",
     "            arrowprops=dict(facecolor='black', width=0.5, shrink=0.1, headwidth=5))\n",
     "    plt.plot(pos_data_x, pos_data_y, \"ro\")\n",
+    "plt.xlabel(\"GDP per capita (USD)\")\n",
     "save_fig('money_happy_scatterplot')\n",
     "plt.show()"
    ]
@@ -384,6 +385,7 @@
     "import numpy as np\n",
     "\n",
     "sample_data.plot(kind='scatter', x=\"GDP per capita\", y='Life satisfaction', figsize=(5,3))\n",
+    "plt.xlabel(\"GDP per capita (USD)\")\n",
     "plt.axis([0, 60000, 0, 10])\n",
     "X=np.linspace(0, 60000, 1000)\n",
     "plt.plot(X, 2*X/100000, \"r\")\n",
@@ -421,6 +423,7 @@
    "outputs": [],
    "source": [
     "sample_data.plot(kind='scatter', x=\"GDP per capita\", y='Life satisfaction', figsize=(5,3))\n",
+    "plt.xlabel(\"GDP per capita (USD)\")\n",
     "plt.axis([0, 60000, 0, 10])\n",
     "X=np.linspace(0, 60000, 1000)\n",
     "plt.plot(X, t0 + t1*X, \"b\")\n",
@@ -449,6 +452,7 @@
    "outputs": [],
    "source": [
     "sample_data.plot(kind='scatter', x=\"GDP per capita\", y='Life satisfaction', figsize=(5,3), s=1)\n",
+    "plt.xlabel(\"GDP per capita (USD)\")\n",
     "X=np.linspace(0, 60000, 1000)\n",
     "plt.plot(X, t0 + t1*X, \"b\")\n",
     "plt.axis([0, 60000, 0, 10])\n",
@@ -598,6 +602,7 @@
     "t0full, t1full = lin_reg_full.intercept_[0], lin_reg_full.coef_[0][0]\n",
     "X = np.linspace(0, 110000, 1000)\n",
     "plt.plot(X, t0full + t1full * X, \"k\")\n",
+    "plt.xlabel(\"GDP per capita (USD)\")\n",
     "\n",
     "save_fig('representative_training_data_scatterplot')\n",
     "plt.show()"
@@ -623,6 +628,7 @@
     "pipeline_reg.fit(Xfull, yfull)\n",
     "curve = pipeline_reg.predict(X[:, np.newaxis])\n",
     "plt.plot(X, curve)\n",
+    "plt.xlabel(\"GDP per capita (USD)\")\n",
     "save_fig('overfitting_model_plot')\n",
     "plt.show()"
    ]
@@ -672,6 +678,7 @@
     "\n",
     "plt.legend(loc=\"lower right\")\n",
     "plt.axis([0, 110000, 0, 10])\n",
+    "plt.xlabel(\"GDP per capita (USD)\")\n",
     "save_fig('ridge_model_plot')\n",
     "plt.show()"
    ]
@@ -726,6 +733,13 @@
     "X_new = np.array([[22587.0]])  # Cyprus' GDP per capita\n",
     "print(model.predict(X_new)) # outputs [[ 5.76666667]]"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {