Replace deprecated matplotlib and pandas API calls in notebook

1-Introduction/04-stats-and-probability/notebook.ipynb

@@ -136,7 +136,7 @@
    "outputs": [],
    "source": [
     "plt.figure(figsize=(10,2))\n",
-    "plt.boxplot(df['Height'].ffill(), vert=False, showmeans=True)\n",
+    "plt.boxplot(df['Height'].ffill(), orientation='horizontal', showmeans=True)\n",
     "plt.grid(color='gray', linestyle='dotted')\n",
     "plt.tight_layout()\n",
     "plt.show()"
@@ -272,7 +272,7 @@
     "    return m, h\n",
     "\n",
     "for p in [0.85, 0.9, 0.95]:\n",
-    "    m, h = mean_confidence_interval(df['Weight'].fillna(method='pad'),p)\n",
+    "    m, h = mean_confidence_interval(df['Weight'].ffill(),p)\n",
     "    print(f\"p={p:.2f}, mean = {m:.2f} ± {h:.2f}\")"
    ]
   },
@@ -384,7 +384,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "heights = df['Height'].fillna(method='pad')\n",
+    "heights = df['Height'].ffill()\n",
     "salaries = 1000+(heights-heights.min())/(heights.max()-heights.mean())*100\n",
     "print(list(zip(heights, salaries))[:10])"
    ]
@@ -507,7 +507,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "np.corrcoef(df['Height'].fillna(method='pad'), df['Weight'])"
+    "np.corrcoef(df['Height'].ffill(), df['Weight'])"
    ]
   },
   {