Update Bar chart section for Plotly 4 and colab.

Author: cwant

.gitignore

@@ -104,3 +104,5 @@ venv.bak/
 .mypy_cache/
 
 notebooks/my-first-scatter.html
+Untitled.ipynb
+gapminder_gdp_americas.csv

notebooks/03b-plotly-bar.ipynb

@@ -40,7 +40,9 @@
     "if 'google.colab' in sys.modules:\n",
     "    get_ipython().events.register('pre_run_cell', enable_plotly_in_cell)\n",
     "    !mkdir -p data\n",
-    "    !wget -P data https://raw.githubusercontent.com/ualberta-rcg/python-plotting/master/notebooks/data/gapminder_gdp_europe.csv"
+    "    !wget -P data https://raw.githubusercontent.com/ualberta-rcg/python-plotting/master/notebooks/data/gapminder_gdp_europe.csv\n",
+    "    !mkdir -p solutions\n",
+    "    !wget -P solutions https://github.com/ualberta-rcg/python-plotting/blob/master/notebooks/solutions/plotly-bar-chart-north-america.py"
    ]
   },
   {
@@ -161,6 +163,65 @@
     "fig = go.Figure(data=data, layout=layout)\n",
     "py.iplot(fig)"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercise"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's grab some North American GDP data (code to download below).\n",
+    "\n",
+    "Using what you learned here and in the scatter plot section, do the following:\n",
+    "\n",
+    "* Using this data set, make a bar chart of the per-capita GDP growth of Canada, the United States, and Mexico.\n",
+    "* Label the chart \"Per-capita GDP Growth in North America\".\n",
+    "* Make the Canada bar red, the US bar blue, and the Mexico bar green. **Hint!** Check the documentation on how to set the color of the bars: https://plot.ly/python/bar-charts/\n",
+    "* Label the axes!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Grabbing the data:\n",
+    "!mkdir -p data\n",
+    "!wget -P data https://raw.githubusercontent.com/ualberta-rcg/python-intro/gh-pages/data/gapminder_gdp_americas.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv('data/gapminder_gdp_americas.csv', index_col='country')\n",
+    "df = df.drop(columns=['continent'])\n",
+    "years = df.columns.str.strip('gdpPercap_')\n",
+    "df.columns = years.astype(int)\n",
+    "\n",
+    "# Your code goes here ..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load solutions/plotly-bar-chart-north-america.py\n",
+    "\n",
+    "# SOLUTION\n",
+    "# Run this cell once to load the solution\n",
+    "# Run this cell a second time to actually run the code"
+   ]
   }
  ],
  "metadata": {

notebooks/solutions/plotly-bar-chart-north-america.py

@@ -0,0 +1,36 @@
+df = pd.read_csv('data/gapminder_gdp_americas.csv', index_col='country')
+df = df.drop(columns=['continent'])
+years = df.columns.str.strip('gdpPercap_')
+df.columns = years.astype(int)
+
+trace0 = go.Bar(
+    x = df.columns,
+    y = df.loc['Canada'],
+    name = 'Canada',
+    marker_color = 'rgb(200, 0, 0)'
+)
+trace1 = go.Bar(
+    x = df.columns,
+    y = df.loc['United States'],
+    name = 'United States',
+    marker_color = 'rgb(0, 0, 200)'
+)
+trace2 = go.Bar(
+    x = df.columns,
+    y = df.loc['Mexico'],
+    name = 'Mexico',
+    marker_color = 'rgb(0, 200, 0)'
+)
+
+data = [trace0, trace1, trace2]
+layout = dict(
+    title = 'Per-capita GDP Growth in North America',
+    xaxis = dict(
+        title = 'Year'
+    ),
+    yaxis = dict(
+        title = 'GDP per-capita'
+    )
+)
+fig = dict(data=data, layout=layout)
+py.iplot(fig)