From 6d6840352ad6a349094fadcd068c2957241b4ca4 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:48:40 +0000
Subject: [PATCH 01/35] Automatically backed up by Learn

---
 index.ipynb | 308 +++++++++++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 307 insertions(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index cd283629c8d..76371cc1950 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1 +1,307 @@
-{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["# Python For loops Lab"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Learning Objectives"]}, {"cell_type": "markdown", "metadata": {}, "source": ["* Understand how for loops can help us reduce repetition\n", "* Understand the syntax of for loops "]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Picking up where we last left off"]}, {"cell_type": "markdown", "metadata": {}, "source": ["In the last lesson, we worked with some of our travel data.  Let's retrieve a list with our travel information again from excel.  First, we read the information from excel as a list of dictionaries, with each dictionary representing a location.  And we assign this list to the variable `cities`."]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["import pandas\n", "file_name = './cities.xlsx'\n", "travel_df = pandas.read_excel(file_name)\n", "cities = travel_df.to_dict('records')"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Next, we retrieve the first three city names, stored as the `'City'` attribute of each dictionary, and `'Population'` of each of the cities.  Then we plot the names as our `x_values` and the populations as our `y_values`."]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["import plotly\n", "\n", "plotly.offline.init_notebook_mode(connected=True)\n", "\n", "x_values = [cities[0]['City'], cities[1]['City'], cities[2]['City']]\n", "y_values = [cities[0]['Population'], cities[1]['Population'], cities[2]['Population']]\n", "trace_first_three_pops = {'x': x_values, 'y': y_values, 'type': 'bar'}\n", "plotly.offline.iplot([trace_first_three_pops])"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Of course, as you may have spotted, there is a good amount of repetition in displaying this data.  Just take a look at how we retrieved the data for our `x_values` and `y_values`.  "]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["x_values = [cities[0]['City'], cities[1]['City'], cities[2]['City']]\n", "y_values = [cities[0]['Population'], cities[1]['Population'], cities[2]['Population']]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["So in this lesson, we will use our `for` loop to display information about our travel locations with less repetition."]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Working with the For Loop"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Our `cities` list contains information about the top 12 cities by population.  For our upcoming iteration tasks, it will be useful to have a list of the numbers 0 through 11.  Use what we know about `len` and `range`to generate a list of numbers 0 through 11.  Assign this to a variable called `city_indices`."]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["city_indices = None\n", "city_indices # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Now we want to create labels for each of the cities. We'll provide a list of the `city_names` for you. "]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["city_names = ['Buenos Aires',\n", " 'Toronto',\n", " 'Marakesh',\n", " 'Albuquerque',\n", " 'Los Cabos',\n", " 'Greenville',\n", " 'Archipelago Sea',\n", " 'Pyeongchang',\n", " 'Walla Walla Valley',\n", " 'Salina Island',\n", " 'Solta',\n", " 'Iguazu Falls']"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Your task is to assign the variable `names_and_ranks` to a list, with each element equal to the city name and it's corresponding rank.  For example, the first element would be, `\"1. Buenos Aires\"` and the second would be `\"2. Toronto\"`.  Use a `for` loop and the lists `city_indices` and `city_names` to accomplish this.  We'll need to perform some nifty string interpolation to format our strings properly.  Check out [f-string interpolation](https://www.programiz.com/python-programming/string-interpolation#f) to see how we can pass values into a string.  Remember that list indices start at zero, but we want our `names_and_ranks` list to start at one!"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["names_and_ranks = [] \n", "# write a for loop that adds the properly formatted string to the names_and_ranks list"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["names_and_ranks[0] # '1. Buenos Aires'\n", "names_and_ranks[1] # '2. Toronto'\n", "names_and_ranks[-1] # '12. Iguazu Falls'"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Ok, now let's create a new variable called `city_populations`.  Use a `for` loop to iterate through `cities` and have `city_populations` equal to each of the populations."]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["city_populations = []"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["city_populations[0] # 2891\n", "city_populations[1] # 2732\n", "city_populations[-1] # 0"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Great! Now we can begin to plot this data.  First, let's create a trace of our populations and set it to the variable `trace_populations`."]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["trace_populations = {'x': names_and_ranks, \n", "                     'y': city_populations, \n", "                     'text': names_and_ranks, \n", "                     'type': 'bar', \n", "                     'name': 'populations'}"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["import plotly\n", "plotly.offline.init_notebook_mode(connected=True)\n", "plotly.offline.iplot([trace_populations])"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Now we want declare a variable called `city_areas` that points to a list of all of the areas of the cities.  Let's use a `for` loop to iterate through our `cities` and have `city_areas` equal to each area of the city.  "]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["city_areas = []"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["trace_areas = {'x': names_and_ranks, 'y': city_areas, 'text': names_and_ranks, 'type': 'bar', 'name': 'areas'}"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["import plotly\n", "plotly.offline.init_notebook_mode(connected=True)\n", "plotly.offline.iplot([trace_populations, trace_areas])"]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Summary"]}, {"cell_type": "markdown", "metadata": {}, "source": ["In this section we saw how we can use `for` loops to go through elements of a list and perform the same operation on each.  By using `for` loops we were able to reduce the amount of code that we wrote and while also writing more expressive code."]}], "metadata": {"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.6"}}, "nbformat": 4, "nbformat_minor": 2}
\ No newline at end of file
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Python For loops Lab"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Learning Objectives"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* Understand how for loops can help us reduce repetition\n",
+    "* Understand the syntax of for loops "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Picking up where we last left off"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the last lesson, we worked with some of our travel data.  Let's retrieve a list with our travel information again from excel.  First, we read the information from excel as a list of dictionaries, with each dictionary representing a location.  And we assign this list to the variable `cities`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas\n",
+    "file_name = './cities.xlsx'\n",
+    "travel_df = pandas.read_excel(file_name)\n",
+    "cities = travel_df.to_dict('records')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we retrieve the first three city names, stored as the `'City'` attribute of each dictionary, and `'Population'` of each of the cities.  Then we plot the names as our `x_values` and the populations as our `y_values`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plotly\n",
+    "\n",
+    "plotly.offline.init_notebook_mode(connected=True)\n",
+    "\n",
+    "x_values = [cities[0]['City'], cities[1]['City'], cities[2]['City']]\n",
+    "y_values = [cities[0]['Population'], cities[1]['Population'], cities[2]['Population']]\n",
+    "trace_first_three_pops = {'x': x_values, 'y': y_values, 'type': 'bar'}\n",
+    "plotly.offline.iplot([trace_first_three_pops])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Of course, as you may have spotted, there is a good amount of repetition in displaying this data.  Just take a look at how we retrieved the data for our `x_values` and `y_values`.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_values = [cities[0]['City'], cities[1]['City'], cities[2]['City']]\n",
+    "y_values = [cities[0]['Population'], cities[1]['Population'], cities[2]['Population']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So in this lesson, we will use our `for` loop to display information about our travel locations with less repetition."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Working with the For Loop"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Our `cities` list contains information about the top 12 cities by population.  For our upcoming iteration tasks, it will be useful to have a list of the numbers 0 through 11.  Use what we know about `len` and `range`to generate a list of numbers 0 through 11.  Assign this to a variable called `city_indices`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "city_indices = None\n",
+    "city_indices # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we want to create labels for each of the cities. We'll provide a list of the `city_names` for you. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "city_names = ['Buenos Aires',\n",
+    " 'Toronto',\n",
+    " 'Marakesh',\n",
+    " 'Albuquerque',\n",
+    " 'Los Cabos',\n",
+    " 'Greenville',\n",
+    " 'Archipelago Sea',\n",
+    " 'Pyeongchang',\n",
+    " 'Walla Walla Valley',\n",
+    " 'Salina Island',\n",
+    " 'Solta',\n",
+    " 'Iguazu Falls']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Your task is to assign the variable `names_and_ranks` to a list, with each element equal to the city name and it's corresponding rank.  For example, the first element would be, `\"1. Buenos Aires\"` and the second would be `\"2. Toronto\"`.  Use a `for` loop and the lists `city_indices` and `city_names` to accomplish this.  We'll need to perform some nifty string interpolation to format our strings properly.  Check out [f-string interpolation](https://www.programiz.com/python-programming/string-interpolation#f) to see how we can pass values into a string.  Remember that list indices start at zero, but we want our `names_and_ranks` list to start at one!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "names_and_ranks = [] \n",
+    "# write a for loop that adds the properly formatted string to the names_and_ranks list"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "names_and_ranks[0] # '1. Buenos Aires'\n",
+    "names_and_ranks[1] # '2. Toronto'\n",
+    "names_and_ranks[-1] # '12. Iguazu Falls'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ok, now let's create a new variable called `city_populations`.  Use a `for` loop to iterate through `cities` and have `city_populations` equal to each of the populations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "city_populations = []"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "city_populations[0] # 2891\n",
+    "city_populations[1] # 2732\n",
+    "city_populations[-1] # 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Great! Now we can begin to plot this data.  First, let's create a trace of our populations and set it to the variable `trace_populations`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trace_populations = {'x': names_and_ranks, \n",
+    "                     'y': city_populations, \n",
+    "                     'text': names_and_ranks, \n",
+    "                     'type': 'bar', \n",
+    "                     'name': 'populations'}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plotly\n",
+    "plotly.offline.init_notebook_mode(connected=True)\n",
+    "plotly.offline.iplot([trace_populations])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we want declare a variable called `city_areas` that points to a list of all of the areas of the cities.  Let's use a `for` loop to iterate through our `cities` and have `city_areas` equal to each area of the city.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "city_areas = []"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trace_areas = {'x': names_and_ranks, 'y': city_areas, 'text': names_and_ranks, 'type': 'bar', 'name': 'areas'}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plotly\n",
+    "plotly.offline.init_notebook_mode(connected=True)\n",
+    "plotly.offline.iplot([trace_populations, trace_areas])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Summary"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this section we saw how we can use `for` loops to go through elements of a list and perform the same operation on each.  By using `for` loops we were able to reduce the amount of code that we wrote and while also writing more expressive code."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

From 0377fa25f2ae788eae2b1326f7dba1a6af403c7b Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:49:10 +0000
Subject: [PATCH 02/35] Automatically backed up by Learn

---
 index.ipynb | 893 +++++++++++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 890 insertions(+), 3 deletions(-)

diff --git a/index.ipynb b/index.ipynb
index 76371cc1950..5495eea80a6 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -38,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -57,9 +57,896 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        requirejs.config({\n",
+       "            paths: {\n",
+       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
+       "            }\n",
+       "        });\n",
+       "        require(['plotly'], function(Plotly) {\n",
+       "            window._Plotly = Plotly;\n",
+       "        });\n",
+       "        }\n",
+       "        </script>\n",
+       "        "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "linkText": "Export to plot.ly",
+        "plotlyServerURL": "https://plot.ly",
+        "showLink": false
+       },
+       "data": [
+        {
+         "type": "bar",
+         "x": [
+          "Buenos Aires",
+          "Toronto",
+          "Marakesh"
+         ],
+         "y": [
+          2891,
+          2732,
+          929
+         ]
+        }
+       ],
+       "layout": {
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
+             [
+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
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[0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
+       "                        {\"responsive\": true}\n",
+       "                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('51257a58-b9ff-4137-b003-78aa378ed893');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })\n",
+       "                };\n",
+       "                });\n",
+       "            </script>\n",
+       "        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "import plotly\n",
     "\n",

From 33036e8198fb0925011809a6b3904e5552a3118b Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:49:30 +0000
Subject: [PATCH 03/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 5495eea80a6..68e63cdb939 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -967,7 +967,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [

From bd9eca58dfbbd1355b85adae8283045b85f2a41c Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:50:00 +0000
Subject: [PATCH 04/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 68e63cdb939..5cb6ecb52af 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1002,7 +1002,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "city_indices = None\n",
+    "city_indices = list(range(0, len(countries)))\n",
     "city_indices # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]"
    ]
   },

From 5f4935072758c7765700baa4c939c52a50aa89c2 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:50:10 +0000
Subject: [PATCH 05/35] Automatically backed up by Learn

---
 index.ipynb | 17 ++++++++++++++---
 1 file changed, 14 insertions(+), 3 deletions(-)

diff --git a/index.ipynb b/index.ipynb
index 5cb6ecb52af..66b937c0a92 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -998,11 +998,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "city_indices = list(range(0, len(countries)))\n",
+    "city_indices = list(range(0, len(cities)))\n",
     "city_indices # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]"
    ]
   },

From 001f67b0438a9a7fa022ec2ad652ae1594ebb9af Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:50:20 +0000
Subject: [PATCH 06/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 66b937c0a92..405ddfcecf2 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1026,7 +1026,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [

From ffe471c063bd370ce3fac70ecfc67ef1b65c05c5 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:50:40 +0000
Subject: [PATCH 07/35] Automatically backed up by Learn

---
 index.ipynb | 1 +
 1 file changed, 1 insertion(+)

diff --git a/index.ipynb b/index.ipynb
index 405ddfcecf2..2fa47c1d260 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1058,6 +1058,7 @@
    "outputs": [],
    "source": [
     "names_and_ranks = [] \n",
+    "\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From e7ca68b126c010f8e7dcc9030febaf2e18075f2e Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:50:50 +0000
Subject: [PATCH 08/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 2fa47c1d260..1bad20fc67a 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1058,7 +1058,7 @@
    "outputs": [],
    "source": [
     "names_and_ranks = [] \n",
-    "\n",
+    "for city\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From 3d30b7ca4cc14221aa9dd0dc30ed3fb5c21f6dff Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:51:00 +0000
Subject: [PATCH 09/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 1bad20fc67a..bea19f572a9 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1058,7 +1058,7 @@
    "outputs": [],
    "source": [
     "names_and_ranks = [] \n",
-    "for city\n",
+    "for city_index in city_indices\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From b854eacd446d90c7a1a5348988f830f7789c4cdb Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:51:10 +0000
Subject: [PATCH 10/35] Automatically backed up by Learn

---
 index.ipynb | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index bea19f572a9..d3b94b28f74 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1058,7 +1058,8 @@
    "outputs": [],
    "source": [
     "names_and_ranks = [] \n",
-    "for city_index in city_indices\n",
+    "for city_index in city_indices:\n",
+    "    nam\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From 8bfc55e16ee7a02abdb1e7cce829e23e82060001 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:51:21 +0000
Subject: [PATCH 11/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index d3b94b28f74..a70a178604e 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1059,7 +1059,7 @@
    "source": [
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
-    "    nam\n",
+    "    names_and_ranks.append()\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From 3c11a8d1bb7f7a2cadd4adaa4727eab29628daa6 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:51:30 +0000
Subject: [PATCH 12/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index a70a178604e..fd2b540e6fb 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1059,7 +1059,7 @@
    "source": [
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
-    "    names_and_ranks.append()\n",
+    "    names_and_ranks.append(cityind)\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From 34b3345ee160c2637eee513e75fa04fe93c47117 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:51:40 +0000
Subject: [PATCH 13/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index fd2b540e6fb..bbd7d0367fa 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1059,7 +1059,7 @@
    "source": [
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
-    "    names_and_ranks.append(cityind)\n",
+    "    names_and_ranks.append(city_index+1)\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From fd7fb38c4b2fcfd0be4e248b126b7923263817b1 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:51:50 +0000
Subject: [PATCH 14/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index bbd7d0367fa..a70a178604e 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1059,7 +1059,7 @@
    "source": [
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
-    "    names_and_ranks.append(city_index+1)\n",
+    "    names_and_ranks.append()\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From 0aaca07269e8b488b427e00b8888c52186bff567 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:52:00 +0000
Subject: [PATCH 15/35] Automatically backed up by Learn

---
 index.ipynb | 1 +
 1 file changed, 1 insertion(+)

diff --git a/index.ipynb b/index.ipynb
index a70a178604e..9de612d2443 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1059,6 +1059,7 @@
    "source": [
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
+    "    rank = city_\n",
     "    names_and_ranks.append()\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]

From be52be7930452f0f19a2ad38158a240010920382 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:52:11 +0000
Subject: [PATCH 16/35] Automatically backed up by Learn

---
 index.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/index.ipynb b/index.ipynb
index 9de612d2443..4b776b7a30d 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1059,8 +1059,8 @@
    "source": [
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
-    "    rank = city_\n",
-    "    names_and_ranks.append()\n",
+    "    rank = city_index + 1\n",
+    "    names_and_ranks.append(rank)\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From 63326867906d0c814e75e9f8ef264ebd900b04e2 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:52:40 +0000
Subject: [PATCH 17/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 4b776b7a30d..370c08c6baf 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1060,7 +1060,7 @@
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
     "    rank = city_index + 1\n",
-    "    names_and_ranks.append(rank)\n",
+    "    names_and_ranks.append(f')\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From b4d22c79b0ceb18347adb215b12038662f165bdc Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:52:50 +0000
Subject: [PATCH 18/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 370c08c6baf..87e49e1f2cd 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1060,7 +1060,7 @@
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
     "    rank = city_index + 1\n",
-    "    names_and_ranks.append(f')\n",
+    "    names_and_ranks.append(f'{rank} ')\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From 7ac9175d705960c6e758856adffc258cb2255797 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:53:00 +0000
Subject: [PATCH 19/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 87e49e1f2cd..45548cdb260 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1060,7 +1060,7 @@
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
     "    rank = city_index + 1\n",
-    "    names_and_ranks.append(f'{rank} ')\n",
+    "    names_and_ranks.append(f'{rank}. ')\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From 52d29d0be5cd2f5369dde5d110fe704d14ef7763 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:53:10 +0000
Subject: [PATCH 20/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 45548cdb260..e5f10a355f7 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1060,7 +1060,7 @@
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
     "    rank = city_index + 1\n",
-    "    names_and_ranks.append(f'{rank}. ')\n",
+    "    names_and_ranks.append(f'{rank}. {city_names[city_index]}')\n",
     "# write a for loop that adds the properly formatted string to the names_and_ranks list"
    ]
   },

From b29cadb423b6844540b774c668f6cc4f52c6c1e2 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:53:30 +0000
Subject: [PATCH 21/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index e5f10a355f7..83d72e1e819 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1053,7 +1053,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [

From cef73d2dde41bcae40c56f71f0200927bdc56d60 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:53:40 +0000
Subject: [PATCH 22/35] Automatically backed up by Learn

---
 index.ipynb | 15 +++++++++++++--
 1 file changed, 13 insertions(+), 2 deletions(-)

diff --git a/index.ipynb b/index.ipynb
index 83d72e1e819..606e64c652f 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1066,9 +1066,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'12. Iguazu Falls'"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "names_and_ranks[0] # '1. Buenos Aires'\n",
     "names_and_ranks[1] # '2. Toronto'\n",

From 4da40ec096c9d85819045fe08277b7892db16db0 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:53:50 +0000
Subject: [PATCH 23/35] Automatically backed up by Learn

---
 index.ipynb | 15 ++++++++++++---
 1 file changed, 12 insertions(+), 3 deletions(-)

diff --git a/index.ipynb b/index.ipynb
index 606e64c652f..59e4acc7ce5 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1053,15 +1053,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['1. Buenos Aires', '2. Toronto', '3. Marakesh', '4. Albuquerque', '5. Los Cabos', '6. Greenville', '7. Archipelago Sea', '8. Pyeongchang', '9. Walla Walla Valley', '10. Salina Island', '11. Solta', '12. Iguazu Falls']\n"
+     ]
+    }
+   ],
    "source": [
     "names_and_ranks = [] \n",
     "for city_index in city_indices:\n",
     "    rank = city_index + 1\n",
     "    names_and_ranks.append(f'{rank}. {city_names[city_index]}')\n",
-    "# write a for loop that adds the properly formatted string to the names_and_ranks list"
+    "# write a for loop that adds the properly formatted string to the names_and_ranks list\n",
+    "print(names_and_ranks)"
    ]
   },
   {

From 4946f59d8e7403a08a0725279d21ed2d460a7e99 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:54:20 +0000
Subject: [PATCH 24/35] Automatically backed up by Learn

---
 index.ipynb | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 59e4acc7ce5..7ba7e593aa8 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1108,7 +1108,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "city_populations = []"
+    "city_populations = []\n",
+    "for "
    ]
   },
   {

From 72611c1b2f95883299420f0de00559298fc0d434 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:54:30 +0000
Subject: [PATCH 25/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 7ba7e593aa8..8ca118e26b0 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1109,7 +1109,7 @@
    "outputs": [],
    "source": [
     "city_populations = []\n",
-    "for "
+    "for city_index in city_indices"
    ]
   },
   {

From f6ca60c4fa3bcd7ca5024123e170b9935632c578 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:54:40 +0000
Subject: [PATCH 26/35] Automatically backed up by Learn

---
 index.ipynb | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 8ca118e26b0..90c3c3de7e5 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1109,7 +1109,8 @@
    "outputs": [],
    "source": [
     "city_populations = []\n",
-    "for city_index in city_indices"
+    "for city_index in city_indices:\n",
+    "    city_populations.append()"
    ]
   },
   {

From d464c49b09ef3e01c1508c63f04f71f7200e38a0 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:54:50 +0000
Subject: [PATCH 27/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 90c3c3de7e5..868bbfa14e3 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1110,7 +1110,7 @@
    "source": [
     "city_populations = []\n",
     "for city_index in city_indices:\n",
-    "    city_populations.append()"
+    "    city_populations.append(cities[])"
    ]
   },
   {

From ed0368f4e351a394415b145ede490cc2b9d02f43 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:55:00 +0000
Subject: [PATCH 28/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 868bbfa14e3..8917247e8e5 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1110,7 +1110,7 @@
    "source": [
     "city_populations = []\n",
     "for city_index in city_indices:\n",
-    "    city_populations.append(cities[])"
+    "    city_populations.append(cities[city_index]['Population'])"
    ]
   },
   {

From dc5e426b9c546f4bd49b5823b1d742aed678c1d8 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:55:10 +0000
Subject: [PATCH 29/35] Automatically backed up by Learn

---
 index.ipynb | 33 ++++++++++++++++++++++++++++-----
 1 file changed, 28 insertions(+), 5 deletions(-)

diff --git a/index.ipynb b/index.ipynb
index 8917247e8e5..f98fe07be4c 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1104,20 +1104,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[2891, 2732, 929, 559, 288, 93, 60, 44, 33, 3, 2, 0]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "city_populations = []\n",
     "for city_index in city_indices:\n",
-    "    city_populations.append(cities[city_index]['Population'])"
+    "    city_populations.append(cities[city_index]['Population'])\n",
+    "city_populations"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "city_populations[0] # 2891\n",
     "city_populations[1] # 2732\n",

From b4d6a64b205c6cfe805be321e70767b861432001 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:55:30 +0000
Subject: [PATCH 30/35] Automatically backed up by Learn

---
 index.ipynb | 926 +++++++++++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 923 insertions(+), 3 deletions(-)

diff --git a/index.ipynb b/index.ipynb
index f98fe07be4c..fbcc5502a1a 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -1156,7 +1156,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1169,9 +1169,929 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        requirejs.config({\n",
+       "            paths: {\n",
+       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
+       "            }\n",
+       "        });\n",
+       "        require(['plotly'], function(Plotly) {\n",
+       "            window._Plotly = Plotly;\n",
+       "        });\n",
+       "        }\n",
+       "        </script>\n",
+       "        "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "linkText": "Export to plot.ly",
+        "plotlyServerURL": "https://plot.ly",
+        "showLink": false
+       },
+       "data": [
+        {
+         "name": "populations",
+         "text": [
+          "1. Buenos Aires",
+          "2. Toronto",
+          "3. Marakesh",
+          "4. Albuquerque",
+          "5. Los Cabos",
+          "6. Greenville",
+          "7. Archipelago Sea",
+          "8. Pyeongchang",
+          "9. Walla Walla Valley",
+          "10. Salina Island",
+          "11. Solta",
+          "12. Iguazu Falls"
+         ],
+         "type": "bar",
+         "x": [
+          "1. Buenos Aires",
+          "2. Toronto",
+          "3. Marakesh",
+          "4. Albuquerque",
+          "5. Los Cabos",
+          "6. Greenville",
+          "7. Archipelago Sea",
+          "8. Pyeongchang",
+          "9. Walla Walla Valley",
+          "10. Salina Island",
+          "11. Solta",
+          "12. Iguazu Falls"
+         ],
+         "y": [
+          2891,
+          2732,
+          929,
+          559,
+          288,
+          93,
+          60,
+          44,
+          33,
+          3,
+          2,
+          0
+         ]
+        }
+       ],
+       "layout": {
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             }
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+             "startlinecolor": "#2a3f5f"
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+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
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+              0.8888888888888888,
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+              1,
+              "#f0f921"
+             ]
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+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
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+              0.2222222222222222,
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+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "heatmap"
+           }
+          ],
+          "heatmapgl": [
+           {
+            "colorbar": {
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+             "ticks": ""
+            },
+            "colorscale": [
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+              0.5555555555555556,
+              "#d8576b"
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+              0.6666666666666666,
+              "#ed7953"
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+              0.7777777777777778,
+              "#fb9f3a"
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+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
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+            ],
+            "type": "heatmapgl"
+           }
+          ],
+          "histogram": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "histogram"
+           }
+          ],
+          "histogram2d": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
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+              "#0d0887"
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+              "#46039f"
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+              "#9c179e"
+             ],
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+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
+             ],
+             [
+              0.6666666666666666,
+              "#ed7953"
+             ],
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+          "scattergeo": [
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+              "ticks": ""
+             }
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+          ],
+          "scattergl": [
+           {
+            "marker": {
+             "colorbar": {
+              "outlinewidth": 0,
+              "ticks": ""
+             }
+            },
+            "type": "scattergl"
+           }
+          ],
+          "scattermapbox": [
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+              "ticks": ""
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+           }
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+          "scatterpolar": [
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+              "#f0f921"
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+           {
+            "cells": {
+             "fill": {
+              "color": "#EBF0F8"
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+             "line": {
+              "color": "white"
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+             "fill": {
+              "color": "#C8D4E3"
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+            ],
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+             "#fde0ef"
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+             "#b8e186"
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+             "#7fbc41"
+            ],
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+            ],
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+             0.1111111111111111,
+             "#46039f"
+            ],
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+             0.2222222222222222,
+             "#7201a8"
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+            [
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+             "#9c179e"
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+             "#ed7953"
+            ],
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+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
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+             "#7201a8"
+            ],
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+             0.3333333333333333,
+             "#9c179e"
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+             "#ed7953"
+            ],
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+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
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+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
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+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        }
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "        \n",
+       "        \n",
+       "            <div id=\"58d0a984-71a9-41c3-aec2-f40d5fee0cb4\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
+       "            <script type=\"text/javascript\">\n",
+       "                require([\"plotly\"], function(Plotly) {\n",
+       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
+       "                    \n",
+       "                if (document.getElementById(\"58d0a984-71a9-41c3-aec2-f40d5fee0cb4\")) {\n",
+       "                    Plotly.newPlot(\n",
+       "                        '58d0a984-71a9-41c3-aec2-f40d5fee0cb4',\n",
+       "                        [{\"name\": \"populations\", \"text\": [\"1. Buenos Aires\", \"2. Toronto\", \"3. Marakesh\", \"4. Albuquerque\", \"5. Los Cabos\", \"6. Greenville\", \"7. Archipelago Sea\", \"8. Pyeongchang\", \"9. Walla Walla Valley\", \"10. Salina Island\", \"11. Solta\", \"12. Iguazu Falls\"], \"type\": \"bar\", \"x\": [\"1. Buenos Aires\", \"2. Toronto\", \"3. Marakesh\", \"4. Albuquerque\", \"5. Los Cabos\", \"6. Greenville\", \"7. Archipelago Sea\", \"8. Pyeongchang\", \"9. Walla Walla Valley\", \"10. Salina Island\", \"11. Solta\", \"12. Iguazu Falls\"], \"y\": [2891, 2732, 929, 559, 288, 93, 60, 44, 33, 3, 2, 0]}],\n",
+       "                        {\"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, 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{\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
+       "                        {\"responsive\": true}\n",
+       "                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('58d0a984-71a9-41c3-aec2-f40d5fee0cb4');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })\n",
+       "                };\n",
+       "                });\n",
+       "            </script>\n",
+       "        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "import plotly\n",
     "plotly.offline.init_notebook_mode(connected=True)\n",

From 3af9dac56465ce195af25a1dfe447a2e92342ec2 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:56:10 +0000
Subject: [PATCH 31/35] Automatically backed up by Learn

---
 index.ipynb | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index fbcc5502a1a..dca4d5a89f1 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -2111,7 +2111,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "city_areas = []"
+    "city_areas = []\n",
+    "for city_"
    ]
   },
   {

From 70b438b3322be77cc14c97c53bab317cdad4b92c Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:56:20 +0000
Subject: [PATCH 32/35] Automatically backed up by Learn

---
 index.ipynb | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index dca4d5a89f1..7f1bc5a29fb 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -2112,7 +2112,8 @@
    "outputs": [],
    "source": [
     "city_areas = []\n",
-    "for city_"
+    "for city_index in city_indices:\n",
+    "    city_areas."
    ]
   },
   {

From 3f11dcd9dd12bfc8ac955e994a5814849c945551 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:56:30 +0000
Subject: [PATCH 33/35] Automatically backed up by Learn

---
 index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 7f1bc5a29fb..44958990898 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -2113,7 +2113,7 @@
    "source": [
     "city_areas = []\n",
     "for city_index in city_indices:\n",
-    "    city_areas."
+    "    city_areas.append(cities[city_index][''])"
    ]
   },
   {

From 1ed90f5d43aeb1566c52c5d46cde0fe8bfeb9149 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:58:00 +0000
Subject: [PATCH 34/35] Automatically backed up by Learn

---
 index.ipynb | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/index.ipynb b/index.ipynb
index 44958990898..8623811817f 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -2113,7 +2113,8 @@
    "source": [
     "city_areas = []\n",
     "for city_index in city_indices:\n",
-    "    city_areas.append(cities[city_index][''])"
+    "    city_areas.append(cities[city_index]['Area'])\n",
+    "city_areas"
    ]
   },
   {

From 1720043865846274d7fa3b70b5098bc3a1f75737 Mon Sep 17 00:00:00 2001
From: Laurell McCaffrey <laurellmccaffrey@gmail.com>
Date: Sun, 2 Feb 2020 21:58:10 +0000
Subject: [PATCH 35/35] Automatically backed up by Learn

---
 index.ipynb | 987 +++++++++++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 982 insertions(+), 5 deletions(-)

diff --git a/index.ipynb b/index.ipynb
index 8623811817f..ad06e8f2ac9 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -2107,9 +2107,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[203, 630, 230, 491, 3751, 68, 2000, 1464, 35, 26, 59, 2396]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "city_areas = []\n",
     "for city_index in city_indices:\n",
@@ -2119,7 +2130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2128,9 +2139,975 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
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+       "                        [{\"name\": \"populations\", \"text\": [\"1. Buenos Aires\", \"2. Toronto\", \"3. Marakesh\", \"4. Albuquerque\", \"5. Los Cabos\", \"6. Greenville\", \"7. Archipelago Sea\", \"8. Pyeongchang\", \"9. Walla Walla Valley\", \"10. Salina Island\", \"11. Solta\", \"12. Iguazu Falls\"], \"type\": \"bar\", \"x\": [\"1. Buenos Aires\", \"2. Toronto\", \"3. Marakesh\", \"4. Albuquerque\", \"5. Los Cabos\", \"6. Greenville\", \"7. Archipelago Sea\", \"8. Pyeongchang\", \"9. Walla Walla Valley\", \"10. Salina Island\", \"11. Solta\", \"12. Iguazu Falls\"], \"y\": [2891, 2732, 929, 559, 288, 93, 60, 44, 33, 3, 2, 0]}, {\"name\": \"areas\", \"text\": [\"1. Buenos Aires\", \"2. Toronto\", \"3. Marakesh\", \"4. Albuquerque\", \"5. Los Cabos\", \"6. Greenville\", \"7. Archipelago Sea\", \"8. Pyeongchang\", \"9. Walla Walla Valley\", \"10. Salina Island\", \"11. Solta\", \"12. Iguazu Falls\"], \"type\": \"bar\", \"x\": [\"1. Buenos Aires\", \"2. Toronto\", \"3. Marakesh\", \"4. Albuquerque\", \"5. Los Cabos\", \"6. Greenville\", \"7. Archipelago Sea\", \"8. Pyeongchang\", \"9. Walla Walla Valley\", \"10. Salina Island\", \"11. Solta\", \"12. Iguazu Falls\"], \"y\": [203, 630, 230, 491, 3751, 68, 2000, 1464, 35, 26, 59, 2396]}],\n",
+       "                        {\"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}},\n",
+       "                        {\"responsive\": true}\n",
+       "                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('fc910ef1-b269-4615-b723-b59e8374750c');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })\n",
+       "                };\n",
+       "                });\n",
+       "            </script>\n",
+       "        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "import plotly\n",
     "plotly.offline.init_notebook_mode(connected=True)\n",