Improve sample notebook

examples/nbtohtml/sample-notebook.ipynb

@@ -34,13 +34,13 @@
  "name": "stdout",
  "output_type": "stream",
  "text": [
- "This is Python code!\n"
+ "This is Python output!\n"
  ]
  }
  ],
  "source": [
  "def my_function():\n",
- " print(\"This is Python code!\")\n",
+ " print(\"This is Python output!\")\n",
  "\n",
  "my_function()"
  ]
@@ -150,7 +150,7 @@
  {
  "data": {
  "text/plain": [
- "<matplotlib.axes._subplots.AxesSubplot at 0x113191290>"
+ "<matplotlib.axes._subplots.AxesSubplot at 0x11a4234c0>"
  ]
  },
  "execution_count": 3,
@@ -159,7 +159,7 @@
  },
  {
  "data": {
- "image/png": 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\n",
+ "image/png": "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\n",
  "text/plain": [
  "<Figure size 432x288 with 1 Axes>"
  ]
@@ -171,7 +171,7 @@
  }
  ],
  "source": [
- "df.plot()"
+ "df.plot.bar()"
  ]
  },
  {
@@ -194,6 +194,27 @@
  "source": [
  "df.std()"
  ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "Exception",
+ "evalue": "This is an error message",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mException\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-5-bf872f0b08d0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"This is an error message\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mException\u001b[0m: This is an error message"
+ ]
+ }
+ ],
+ "source": [
+ "raise Exception(\"This is an error message\")"
+ ]
  }
  ],
  "metadata": {
@@ -212,7 +233,7 @@
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
- "version": "3.7.6"
+ "version": "3.8.2"
  }
  },
  "nbformat": 4,