update first notebooks

geopandas · Jun 18, 2018 · 9147e4e · 9147e4e
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diff --git a/01-introduction-geospatial-data.ipynb b/01-introduction-geospatial-data.ipynb
@@ -36,7 +36,7 @@
     "\n",
     "We can use the GeoPandas library to read many of those GIS file formats (relying on the `fiona` library under the hood, which is an interface to GDAL/OGR), using the `geopandas.read_file` function.\n",
     "\n",
-    "For example, let's start by reading a shapefile with all the countries of the world (from https://www.naturalearthdata.com/http//www.naturalearthdata.com/download/110m/cultural/ne_110m_admin_0_countries.zip), and inspect the data:"
+    "For example, let's start by reading a shapefile with all the countries of the world (adapted from http://www.naturalearthdata.com/downloads/110m-cultural-vectors/110m-admin-0-countries/, zip file is available in the `/data` directory), and inspect the data:"
    ]
   },
   {
@@ -251,7 +251,7 @@
    "source": [
     "Let's import some other datasets with different types of geometry objects.\n",
     "\n",
-    "A dateset about cities in the world (from https://www.naturalearthdata.com/http//www.naturalearthdata.com/download/110m/cultural/ne_110m_populated_places.zip), consisting of Point data:"
+    "A dateset about cities in the world (adapted from http://www.naturalearthdata.com/downloads/110m-cultural-vectors/110m-populated-places/, zip file is available in the `/data` directory), consisting of Point data:"
    ]
   },
   {
@@ -276,7 +276,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "And a dataset of rivers in the world (from http://www.naturalearthdata.com/downloads/50m-physical-vectors/50m-rivers-lake-centerlines/) where each river is a (multi-)line:"
+    "And a dataset of rivers in the world (from http://www.naturalearthdata.com/downloads/50m-physical-vectors/50m-rivers-lake-centerlines/, zip file is available in the `/data` directory) where each river is a (multi-)line:"
    ]
   },
   {
@@ -538,12 +538,12 @@
     "from shapely.geometry import shape\n",
     "\n",
     "with fiona.drivers():\n",
-    "    with fiona.open(\"data/ne_110m_admin_0_countries.shp\") as collection:\n",
+    "    with fiona.open(\"data/ne_110m_admin_0_countries/ne_110m_admin_0_countries.shp\") as collection:\n",
     "        for feature in collection:\n",
     "            # ... do something with geometry\n",
     "            geom = shape(feature['geometry'])\n",
     "            # ... do something with properties\n",
-    "            print(feature['properties']['NAME'])"
+    "            print(feature['properties']['name'])"
    ]
   },
   {

diff --git a/03-spatial-joins.ipynb b/03-spatial-joins.ipynb
@@ -100,15 +100,6 @@
     "Joining the `cities` dataframe with `countries` will transfer extra information about the countries (the full name, the continent) to the `cities` dataframe, based on a common key:"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "cities2.head()"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,

diff --git a/04-more-on-visualization.ipynb b/04-more-on-visualization.ipynb
@@ -99,15 +99,6 @@
     "Let's first create a new column with the GDP per capita:"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "countries = countries.rename(str.lower, axis='columns')"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -331,13 +322,6 @@
     "m"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": null,