adding plotly section to maps_exercise

Author: jurajkapasny

maps_exercise.ipynb

@@ -119,44 +119,100 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "* create choropleth map of world\n",
-    "* the colors of countries from 'world_filtered' are based on population\n",
-    "* other countries are white with black edgecolor"
+    "## Part I: \n",
+    "Create choropleth map of world:\n",
+    "   - using **Geopandas**\n",
+    "   - using **Plotly**\n",
+    "\n",
+    "> #### Notes\n",
+    "> * the colors of countries from 'world_filtered' are based on population\n",
+    "> * other countries can stay white"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### GeoPandas"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2020-04-23T18:44:34.403050Z",
-     "start_time": "2020-04-23T18:44:34.398818Z"
-    }
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# create figure and axes\n",
     "\n",
     "\n",
     "\n",
-    "\n",
     "# create map from world_filtered data-frame\n",
     "\n",
     "\n",
     "\n",
-    "# add the rest of the countries\n",
-    "\n",
-    "\n"
+    "# add the rest of the countries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plotly"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "## Part II:\n",
+    "\n",
+    "In Geopandas:\n",
+    "\n",
     "* add New York, Berlin, Paris, Toronto, Calgary, Tokyo to the map you have created before\n",
     "* to get geometry of these cities use gpd.tools.geocode(['New York', 'Berlin', 'Paris','Toronto', 'Calgary', 'Tokyo'])\n",
-    "* if you do not have geopy library instaled, install it with the following command in the jupyter notebook cell\n",
-    "* !pip install geopy"
+    "* if you do not have geopy library instaled, install it with the following command in the jupyter notebook cell `!pip install geopy`"
    ]
   },
   {
@@ -187,9 +243,7 @@
     "\n",
     "\n",
     "\n",
-    "# add cities\n",
-    "\n",
-    "\n"
+    "# add cities\n"
    ]
   },
   {
@@ -230,7 +284,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.6"
   },
   "toc": {
    "base_numbering": 1,
@@ -276,5 +330,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

matplotlib_3D_exercise.ipynb

@@ -141,7 +141,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.6"
   },
   "toc": {
    "base_numbering": 1,
@@ -187,5 +187,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }