remove references to excel

Author: JeffKatzy

index.ipynb

@@ -20,7 +20,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Ok, so now we have gotten a sense of how to take data from excel and move into a list in Python.  We also learned about how to work with lists.  In this lab we will practice reading from lists, adding elements to lists, and removing elements from lists."
+    "Ok, so now that we have gotten a sense of how to read from a list and alter a list in Python, let's put this knowledge to practice. "
    ]
   },
   {
@@ -43,86 +43,52 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Our data from a Google Sheet"
+    "### Our initial data structure "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Once again, we will get our data from a Google Sheet, this time a sheet of [Travel Cities and Countries](https://docs.google.com/spreadsheets/d/1BTJMMFH9t4p5UmHj5kiC6PGfMN6yaaaZkocx0mDqTK0/edit#gid=0).  "
+    "In the previous lesson, we had a list of top travel cities."
    ]
   },
   {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "![](./cities-and-countries.png)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We already followed the steps of the previous lesson to download the spreadsheet and move it to the current folder.  You can find the file [in the github repository](https://github.com/learn-co-curriculum/python-lists-lab)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
    "source": [
-    "### From Local File to Python "
+    "top_travel_cities = ['Solta', 'Greenville', 'Buenos Aires', 'Los Cabos', 'Walla Walla Valley', 'Marakesh', 'Albuquerque', 'Archipelago Sea', 'Iguazu Falls', 'Salina Island', 'Toronto', 'Pyeongchang']"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now that we have this file in the folder we are working with, we can get this data into Python code."
+    "In this lesson we can work with a list of each associated countries for each of those travel cities."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pandas\n",
-    "file_name = './cities_and_countries.xlsx'\n",
-    "travel_df = pandas.read_excel(file_name)\n",
-    "travel_data = travel_df.to_dict('records')\n",
-    "countries = list(map(lambda city: city['Country'] ,travel_data))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Croatia',\n",
-       " 'USA',\n",
-       " 'Argentina',\n",
-       " 'Mexico',\n",
-       " 'USA',\n",
-       " 'Morocco',\n",
-       " 'New Mexico',\n",
-       " 'Finland',\n",
-       " 'Argentina',\n",
-       " 'Italy',\n",
-       " 'Canada',\n",
-       " 'South Korea']"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "countries"
+    "countries = ['Croatia',\n",
+    " 'USA',\n",
+    " 'Argentina',\n",
+    " 'Mexico',\n",
+    " 'USA',\n",
+    " 'Morocco',\n",
+    " 'New Mexico',\n",
+    " 'Finland',\n",
+    " 'Argentina',\n",
+    " 'Italy',\n",
+    " 'Canada',\n",
+    " 'South Korea']"
    ]
   },
   {
@@ -149,7 +115,9 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "italy = countries[-3] # 'Italy'"
@@ -313,7 +281,9 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "countries[6] = 'USA'"