From 3aa7aa7071ae67f703b05f95f86b1a3c48c86a7b Mon Sep 17 00:00:00 2001
From: ljwolf <levi.john.wolf@gmail.com>
Date: Mon, 1 May 2017 14:42:30 -0400
Subject: [PATCH 1/7] add encode/decode into shapely shapes

---
 cartoframes/context.py | 30 ++++++++++++++++++++++++++----
 1 file changed, 26 insertions(+), 4 deletions(-)

diff --git a/cartoframes/context.py b/cartoframes/context.py
index 62fef2420..4b748b358 100644
--- a/cartoframes/context.py
+++ b/cartoframes/context.py
@@ -12,6 +12,7 @@
 import sys
 import time
 import collections
+import binascii as ba
 
 import requests
 import IPython
@@ -92,7 +93,7 @@ def __init__(self, base_url, api_key, session=None, verbose=0):
         self._verbose = verbose
 
 
-    def read(self, table_name, limit=None, index='cartodb_id'):
+    def read(self, table_name, limit=None, index='cartodb_id', decode_geom=True):
         """Read tables from CARTO into pandas DataFrames.
 
         Example:
@@ -119,11 +120,11 @@ def read(self, table_name, limit=None, index='cartodb_id'):
             else:
                 raise ValueError("`limit` parameter must an integer >= 0")
 
-        return self.query(query)
+        return self.query(query, decode_geom=decode_geom)
 
 
     def write(self, df, table_name, temp_dir='/tmp', overwrite=False,
-              lnglat=None):
+              lnglat=None, encode_geom=True, geom_col='geometry'):
         """Write a DataFrame to a CARTO table.
 
         Example:
@@ -148,6 +149,9 @@ def write(self, df, table_name, temp_dir='/tmp', overwrite=False,
         Returns:
             None
         """
+        if encode_geom:
+            df['the_geom'] = df[geom_col].apply(_encode_geom)
+            df.drop(geom_col, axis=1, inplace=True)
         table_exists = True
         if not overwrite:
             try:
@@ -218,7 +222,7 @@ def sync(self, dataframe, table_name):
         pass
 
 
-    def query(self, query, table_name=None):
+    def query(self, query, table_name=None, decode_geom=True):
         """Pull the result from an arbitrary SQL query from a CARTO account
         into a pandas DataFrame.
 
@@ -276,6 +280,9 @@ def query(self, query, table_name=None):
             columns=[k for k in fields]).astype(schema)
         if 'cartodb_id' in fields:
             df.set_index('cartodb_id', inplace=True)
+
+        if decode_geom:
+            df['geometry'] = df.the_geom.apply(_decode_geom)
         return df
 
 
@@ -679,3 +686,18 @@ def _debug_print(self, **kwargs):
                 str_value = '{}\n\n...\n\n{}'.format(str_value[:250], str_value[-50:])
             print('{key}: {value}'.format(key=key,
                                           value=str_value))
+
+
+def _encode_geom(geom):
+    """
+    Encode geometries into hex-encoded wkb 
+    """
+    from shapely import wkb
+    return ba.hexlify(wkb.dumps(geom)).decode()
+
+def _decode_geom(ewkb):
+    """
+    Decode encoded wkb into a shapely geometry
+    """
+    from shapely import wkb
+    return wkb.loads(ba.unhexlify(ewkb))

From 0edc8f2b2cb3dc3895afc0174084bc6ece2214b4 Mon Sep 17 00:00:00 2001
From: ljwolf <levi.john.wolf@gmail.com>
Date: Mon, 1 May 2017 15:05:28 -0400
Subject: [PATCH 2/7] switch drop statement and avoid conversion in non-geom
 queries

---
 cartoframes/context.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/cartoframes/context.py b/cartoframes/context.py
index 4b748b358..fd4912e7a 100644
--- a/cartoframes/context.py
+++ b/cartoframes/context.py
@@ -151,7 +151,6 @@ def write(self, df, table_name, temp_dir='/tmp', overwrite=False,
         """
         if encode_geom:
             df['the_geom'] = df[geom_col].apply(_encode_geom)
-            df.drop(geom_col, axis=1, inplace=True)
         table_exists = True
         if not overwrite:
             try:
@@ -175,7 +174,7 @@ def remove_tempfile():
             """removes temporary file"""
             os.remove(tempfile)
 
-        df.to_csv(tempfile)
+        df.drop(geom_col,axis=1,errors='ignore').to_csv(tempfile)
 
         with open(tempfile, 'rb') as f:
             res = self._auth_send('api/v1/imports', 'POST',
@@ -660,7 +659,8 @@ def _get_bounds(self, layers):
                FROM (
                    SELECT st_extent(the_geom) AS ext
                    FROM ({union_query}) AS wrap1
-               ) AS wrap2'''.format(union_query=union_query))
+               ) AS wrap2'''.format(union_query=union_query),
+                 decode_geom=False)
 
         west, south, east, north = extent.values[0]
 

From 5b6c4e3ceae0adef2e341c4f37947cb7b94cc278 Mon Sep 17 00:00:00 2001
From: ljwolf <levi.john.wolf@gmail.com>
Date: Tue, 2 May 2017 14:24:36 -0400
Subject: [PATCH 3/7] allow direct publishing of geopandas dataframes

---
 cartoframes/context.py | 18 +++++++++++++++++-
 1 file changed, 17 insertions(+), 1 deletion(-)

diff --git a/cartoframes/context.py b/cartoframes/context.py
index fd4912e7a..6a5f5b78a 100644
--- a/cartoframes/context.py
+++ b/cartoframes/context.py
@@ -13,6 +13,7 @@
 import time
 import collections
 import binascii as ba
+from warnings import warn
 
 import requests
 import IPython
@@ -124,7 +125,7 @@ def read(self, table_name, limit=None, index='cartodb_id', decode_geom=True):
 
 
     def write(self, df, table_name, temp_dir='/tmp', overwrite=False,
-              lnglat=None, encode_geom=True, geom_col='geometry'):
+              lnglat=None, encode_geom=True, geom_col=None):
         """Write a DataFrame to a CARTO table.
 
         Example:
@@ -150,7 +151,22 @@ def write(self, df, table_name, temp_dir='/tmp', overwrite=False,
             None
         """
         if encode_geom:
+            is_geopandas = getattr(df, '_geometry_column_name')
+            if is_geopandas is None and geom_col is None:
+                geom_col = df.get('geometry')
+                if geom_col is None:
+                    raise KeyError('Geometries were requested to be encoded'
+                                   ' but no "geom_col" was not found in the' 
+                                   ' dataframe and no default geometry column was set.')
+            elif is_geopandas is not None and geom_col is not None:
+                warn('geometry column of the input dataframe does not '
+                     ' match the geometry column supplied! Using user-supplied column...'
+                     ' \n\tGeopandas geometry column: {}'
+                     ' \n\tSupplied geom_col: {}'.format(is_geopandas, geom_col))
+            elif is_geopandas is not None and geom_col is None:
+                geom_col = is_geopandas
             df['the_geom'] = df[geom_col].apply(_encode_geom)
+
         table_exists = True
         if not overwrite:
             try:

From b63412e6536c02d1ea56b9880485f97f6ce93e18 Mon Sep 17 00:00:00 2001
From: ljwolf <levi.john.wolf@gmail.com>
Date: Mon, 8 May 2017 08:29:15 -0700
Subject: [PATCH 4/7] add example shapely notebook to folder

---
 .../Shapely, Geopandas, and Cartoframes.ipynb | 647 ++++++++++++++++++
 1 file changed, 647 insertions(+)
 create mode 100644 examples/Shapely, Geopandas, and Cartoframes.ipynb

diff --git a/examples/Shapely, Geopandas, and Cartoframes.ipynb b/examples/Shapely, Geopandas, and Cartoframes.ipynb
new file mode 100644
index 000000000..3c6e681e2
--- /dev/null
+++ b/examples/Shapely, Geopandas, and Cartoframes.ipynb	
@@ -0,0 +1,647 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here, I'll show the relationship between cartoframes and geopandas."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import cartoframes as cf\n",
+    "import geopandas as gpd\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "cxn = cf.CartoContext() # remember, store your credentials \n",
+    "                        # using cf.credentials.set_credentials!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "I have an example dataset in my CARTO account which contains some data on criminology from 1960 onwards at the county level. I'll load that now using the standard read function from cartoframes:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "df = cxn.read('nat')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, by default, CARTO uses the typical Well-known-binary (WKB) serialization for geometries that come out of PostGIS. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>fipsno</th>\n",
+       "      <th>the_geom</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cartodb_id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1505</th>\n",
+       "      <td>17165.0</td>\n",
+       "      <td>0103000020E6100000010000000700000000000000661A...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1720</th>\n",
+       "      <td>40053.0</td>\n",
+       "      <td>0103000020E61000000100000007000000000000205F86...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             fipsno                                           the_geom\n",
+       "cartodb_id                                                            \n",
+       "1505        17165.0  0103000020E6100000010000000700000000000000661A...\n",
+       "1720        40053.0  0103000020E61000000100000007000000000000205F86..."
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head(2)[['fipsno', 'the_geom']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "With [PR#86](https://github.com/CartoDB/cartoframes/pull/86), these strings are now deserialized into `shapely` objects! This means a dataframe from `cartoframes` is almost directly mapped to `Geopandas` dataframes. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>fipsno</th>\n",
+       "      <th>geometry</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cartodb_id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1505</th>\n",
+       "      <td>17165.0</td>\n",
+       "      <td>POLYGON ((-88.4124755859375 37.60790252685547,...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1720</th>\n",
+       "      <td>40053.0</td>\n",
+       "      <td>POLYGON ((-98.09955596923828 36.59130859375, -...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             fipsno                                           geometry\n",
+       "cartodb_id                                                            \n",
+       "1505        17165.0  POLYGON ((-88.4124755859375 37.60790252685547,...\n",
+       "1720        40053.0  POLYGON ((-98.09955596923828 36.59130859375, -..."
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head(2)[['fipsno', 'geometry']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This allows you to do GIS operations locally in Geopandas. To send a dataframe with shapely geometries into a Geopandas dataframe, you only need to call the constructor directly on the dataframe:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "gdf = gpd.GeoDataFrame(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f97958c81d0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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nWrBjC3iGYeyJm6CUIBHpkY2uUmrkaXeaKG6JRrtBInUiLDrNKsUn2RdPLz+n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tu5vf4Nto7u45c92AwbplcmnV2lXNjDKVjEPUkeljfx+2NgzlBVhXxilaPWPrPJFIddZjAeEg8n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\nM1rYlVIqz/w/0UGGCMlxOmAAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f97958aee80>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "gpd.GeoDataFrame(df).plot('hr90', linewidth=.1) #to prove we're in geopandas"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The nice thing with having the code to serialize/deserialize `shapely` objects is that you can publish directly to CARTO (and make CARTO maps) directly from (geo)pandas:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "cxn.write(df, encode_geom=True, table_name='new_table', overwrite=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If you change the geometries locally, the changes propagate back to CARTO:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "gdf['geometry'] = gdf.geometry.apply(lambda x: x.buffer(2))\n",
+    "df['geometry'] = df.geometry.apply(lambda x: x.buffer(2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "cxn.write(gdf, encode_geom=True, table_name='buffered', overwrite=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>ma90</th>\n",
+       "      <th>south</th>\n",
+       "      <th>fp89</th>\n",
+       "      <th>dnl60</th>\n",
+       "      <th>mfil79</th>\n",
+       "      <th>rd90</th>\n",
+       "      <th>dv80</th>\n",
+       "      <th>hc60</th>\n",
+       "      <th>po70</th>\n",
+       "      <th>ps90</th>\n",
+       "      <th>...</th>\n",
+       "      <th>blk90</th>\n",
+       "      <th>rd60</th>\n",
+       "      <th>state_fips</th>\n",
+       "      <th>dv90</th>\n",
+       "      <th>fp69</th>\n",
+       "      <th>field_1</th>\n",
+       "      <th>fipsno</th>\n",
+       "      <th>fh90</th>\n",
+       "      <th>pol80</th>\n",
+       "      <th>geometry</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cartodb_id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1505</th>\n",
+       "      <td>38.2</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>15.828502</td>\n",
+       "      <td>4.226510</td>\n",
+       "      <td>9.695417</td>\n",
+       "      <td>0.377041</td>\n",
+       "      <td>5.412968</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>25721.0</td>\n",
+       "      <td>0.207842</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.506459</td>\n",
+       "      <td>0.457671</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>8.403532</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>1504.0</td>\n",
+       "      <td>17165.0</td>\n",
+       "      <td>13.172442</td>\n",
+       "      <td>10.255833</td>\n",
+       "      <td>POLYGON ((-88.35277784856117 35.60879368035607...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1720</th>\n",
+       "      <td>39.5</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>11.474435</td>\n",
+       "      <td>2.089815</td>\n",
+       "      <td>9.738908</td>\n",
+       "      <td>-0.342290</td>\n",
+       "      <td>4.069299</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>7117.0</td>\n",
+       "      <td>-1.178859</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.052733</td>\n",
+       "      <td>-0.358385</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>5.862884</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>1719.0</td>\n",
+       "      <td>40053.0</td>\n",
+       "      <td>7.134364</td>\n",
+       "      <td>8.782323</td>\n",
+       "      <td>POLYGON ((-98.09408038595517 34.59131608926712...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2799</th>\n",
+       "      <td>36.7</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>9.645150</td>\n",
+       "      <td>3.555298</td>\n",
+       "      <td>9.842463</td>\n",
+       "      <td>-0.553942</td>\n",
+       "      <td>4.230542</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>24165.0</td>\n",
+       "      <td>0.554042</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.854684</td>\n",
+       "      <td>-0.498175</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>7.072922</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>2798.0</td>\n",
+       "      <td>48091.0</td>\n",
+       "      <td>9.104427</td>\n",
+       "      <td>10.503587</td>\n",
+       "      <td>POLYGON ((-99.342072998125 27.87317430656412, ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>43.9</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>8.383961</td>\n",
+       "      <td>1.454312</td>\n",
+       "      <td>9.708567</td>\n",
+       "      <td>-0.737595</td>\n",
+       "      <td>3.135889</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>4564.0</td>\n",
+       "      <td>-1.724842</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.034495</td>\n",
+       "      <td>-0.173043</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>5.452946</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>38023.0</td>\n",
+       "      <td>9.113001</td>\n",
+       "      <td>8.158802</td>\n",
+       "      <td>POLYGON ((-100.9549124845266 49.24699589679899...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>68</th>\n",
+       "      <td>35.5</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.930828</td>\n",
+       "      <td>2.602347</td>\n",
+       "      <td>9.551587</td>\n",
+       "      <td>-0.652795</td>\n",
+       "      <td>2.569074</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>5388.0</td>\n",
+       "      <td>-1.070270</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>-0.089455</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>5.014409</td>\n",
+       "      <td>21.2</td>\n",
+       "      <td>67.0</td>\n",
+       "      <td>27125.0</td>\n",
+       "      <td>6.746371</td>\n",
+       "      <td>8.607217</td>\n",
+       "      <td>POLYGON ((-98.481259264152 48.00606406878377, ...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 73 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            ma90  south       fp89     dnl60    mfil79      rd90      dv80  \\\n",
+       "cartodb_id                                                                   \n",
+       "1505        38.2    0.0  15.828502  4.226510  9.695417  0.377041  5.412968   \n",
+       "1720        39.5    1.0  11.474435  2.089815  9.738908 -0.342290  4.069299   \n",
+       "2799        36.7    1.0   9.645150  3.555298  9.842463 -0.553942  4.230542   \n",
+       "14          43.9    0.0   8.383961  1.454312  9.708567 -0.737595  3.135889   \n",
+       "68          35.5    0.0  10.930828  2.602347  9.551587 -0.652795  2.569074   \n",
+       "\n",
+       "                hc60     po70      ps90  \\\n",
+       "cartodb_id                                \n",
+       "1505        1.000000  25721.0  0.207842   \n",
+       "1720        0.000000   7117.0 -1.178859   \n",
+       "2799        0.666667  24165.0  0.554042   \n",
+       "14          0.000000   4564.0 -1.724842   \n",
+       "68          0.000000   5388.0 -1.070270   \n",
+       "\n",
+       "                                  ...                             blk90  \\\n",
+       "cartodb_id                        ...                                     \n",
+       "1505                              ...                          3.506459   \n",
+       "1720                              ...                          0.052733   \n",
+       "2799                              ...                          0.854684   \n",
+       "14                                ...                          0.034495   \n",
+       "68                                ...                          0.000000   \n",
+       "\n",
+       "                rd60  state_fips      dv90  fp69  field_1   fipsno       fh90  \\\n",
+       "cartodb_id                                                                      \n",
+       "1505        0.457671        17.0  8.403532  19.3   1504.0  17165.0  13.172442   \n",
+       "1720       -0.358385        40.0  5.862884  14.6   1719.0  40053.0   7.134364   \n",
+       "2799       -0.498175        48.0  7.072922  13.0   2798.0  48091.0   9.104427   \n",
+       "14         -0.173043        38.0  5.452946  14.6     13.0  38023.0   9.113001   \n",
+       "68         -0.089455        27.0  5.014409  21.2     67.0  27125.0   6.746371   \n",
+       "\n",
+       "                pol80                                           geometry  \n",
+       "cartodb_id                                                                \n",
+       "1505        10.255833  POLYGON ((-88.35277784856117 35.60879368035607...  \n",
+       "1720         8.782323  POLYGON ((-98.09408038595517 34.59131608926712...  \n",
+       "2799        10.503587  POLYGON ((-99.342072998125 27.87317430656412, ...  \n",
+       "14           8.158802  POLYGON ((-100.9549124845266 49.24699589679899...  \n",
+       "68           8.607217  POLYGON ((-98.481259264152 48.00606406878377, ...  \n",
+       "\n",
+       "[5 rows x 73 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gdf.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<iframe srcdoc=\"<!DOCTYPE html>\n",
+       "<html>\n",
+       "  <head>\n",
+       "    <title>Carto</title>\n",
+       "    <meta name='viewport' content='initial-scale=1.0, user-scalable=no' />\n",
+       "    <meta http-equiv='content-type' content='text/html; charset=UTF-8' />\n",
+       "    <link rel='shortcut icon' href='http://cartodb.com/assets/favicon.ico' />\n",
+       "\n",
+       "    <style>\n",
+       "     html, body, #map {\n",
+       "       height: 100%;\n",
+       "       padding: 0;\n",
+       "       margin: 0;\n",
+       "     }\n",
+       "     #zoom-center {\n",
+       "       position: absolute;\n",
+       "       right: 0;\n",
+       "       top: 0;\n",
+       "       background-color: rgba(255, 255, 255, 0.7);\n",
+       "       width: 240px;\n",
+       "       z-index: 100;\n",
+       "       padding: 4px;\n",
+       "     }\n",
+       "    </style>\n",
+       "\n",
+       "    <link rel='stylesheet' href='https://cartodb-libs.global.ssl.fastly.net/cartodb.js/v3/3.15/themes/css/cartodb.css' />\n",
+       "  </head>\n",
+       "  <body>\n",
+       "    <div id='zoom-center'>\n",
+       "      zoom=<span id='zoom'>4</span>,\n",
+       "      lng=<span id='lon'>No data</span>, lat=<span id='lat'>No data</span></div>\n",
+       "    <div id='map'></div>\n",
+       "    <script src='https://cartodb-libs.global.ssl.fastly.net/cartodb.js/v3/3.15/cartodb.js'></script>\n",
+       "\n",
+       "    <script>\n",
+       "     const config  = {'maps_api_template': 'https://lwolf-carto.carto.com', 'user_name': 'lwolf-carto', 'tiler_protocol': 'https', 'tiler_port': '80', 'sql_api_template': 'https://lwolf-carto.carto.com', 'named_map': {'name': 'cartoframes_ver20170406_layers1_time0_baseid1_labels0_zoom0', 'params': {'south': 22.9569580927926, 'sql_0': 'SELECT * FROM buffered', 'north': 51.370932923985499, 'cartocss_0': &quot;#layer[&#92;'mapnik::geometry_type&#92;'=1] {  marker-line-color: #000; marker-line-opacity: 1; marker-fill: ramp([gi69], cartocolor(Mint), quantiles(5)); marker-fill-opacity: 1; marker-line-width: 0.5; marker-width: 10; marker-allow-overlap: true;} #layer[&#92;'mapnik::geometry_type&#92;'=2] {  line-width: 1.5; line-color: ramp([gi69], cartocolor(Mint), quantiles(5));} #layer[&#92;'mapnik::geometry_type&#92;'=3] {  line-color: #FFF; polygon-gamma: 0.5; polygon-opacity: 0.9; line-opacity: 0.25; line-width: 0.5; line-comp-op: hard-light; polygon-fill: ramp([gi69], cartocolor(Mint), quantiles(5));} &quot;, 'west': -126.729647650788, 'basemap_url': 'https://cartodb-basemaps-{s}.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png', 'east': -64.969860407846895}}, 'type': 'namedmap', 'tiler_domain': 'carto.com'};\n",
+       "     const bounds  = [[51.370932923985499, -64.969860407846895], [22.9569580927926, -126.729647650788]];\n",
+       "     const options = {'https': true, 'filter': ['http', 'mapnik', 'torque']};\n",
+       "\n",
+       "     const adjustLongitude = (lng) => (\n",
+       "       lng - ((Math.ceil((lng + 180) / 360) - 1) * 360)\n",
+       "     );\n",
+       "     const map = L.map('map', {\n",
+       "       zoom: 3,\n",
+       "       center: [0, 0],\n",
+       "     });\n",
+       "     const updateMapInfo = () => {\n",
+       "       $('#zoom').text(map.getZoom());\n",
+       "       $('#lat').text(map.getCenter().lat.toFixed(4));\n",
+       "       $('#lon').text(adjustLongitude(map.getCenter().lng).toFixed(4));\n",
+       "     };\n",
+       "\n",
+       "     cartodb.createLayer(map, config, options)\n",
+       "            .addTo(map)\n",
+       "            .done((layer) => {\n",
+       "              if (bounds.length) {\n",
+       "                map.fitBounds(bounds);\n",
+       "              }\n",
+       "              updateMapInfo();\n",
+       "              map.on('move', () => {\n",
+       "                updateMapInfo();\n",
+       "              });\n",
+       "            })\n",
+       "            .error((err) => {\n",
+       "              console.log('ERROR: ', err);\n",
+       "            });\n",
+       "    </script>\n",
+       "\n",
+       "  </body>\n",
+       "</html>\n",
+       "\" width=800 height=400>  Preview image: <img src=\"https://lwolf-carto.carto.com/api/v1/map/static/named/cartoframes_ver20170406_layers1_time0_baseid1_labels0_zoom0/800/400.png?config=%7B%22cartocss_0%22%3A+%22%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D1%5D+%7B++marker-line-color%3A+%23000%3B+marker-line-opacity%3A+1%3B+marker-fill%3A+ramp%28%5Bgi69%5D%2C+cartocolor%28Mint%29%2C+quantiles%285%29%29%3B+marker-fill-opacity%3A+1%3B+marker-line-width%3A+0.5%3B+marker-width%3A+10%3B+marker-allow-overlap%3A+true%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D2%5D+%7B++line-width%3A+1.5%3B+line-color%3A+ramp%28%5Bgi69%5D%2C+cartocolor%28Mint%29%2C+quantiles%285%29%29%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D3%5D+%7B++line-color%3A+%23FFF%3B+polygon-gamma%3A+0.5%3B+polygon-opacity%3A+0.9%3B+line-opacity%3A+0.25%3B+line-width%3A+0.5%3B+line-comp-op%3A+hard-light%3B+polygon-fill%3A+ramp%28%5Bgi69%5D%2C+cartocolor%28Mint%29%2C+quantiles%285%29%29%3B%7D+%22%2C+%22basemap_url%22%3A+%22https%3A%2F%2Fcartodb-basemaps-%7Bs%7D.global.ssl.fastly.net%2Fdark_all%2F%7Bz%7D%2F%7Bx%7D%2F%7By%7D.png%22%2C+%22sql_0%22%3A+%22SELECT+%2A+FROM+buffered%22%7D&anti_cache=0.3092037769690339\" /></iframe>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cxn.map(layers=[cf.BaseMap(), cf.Layer('buffered', \n",
+    "                                       color=dict(column='gi69'))],\n",
+    "        interactive=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python [conda env:py36]",
+   "language": "python",
+   "name": "conda-env-py36-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

From 686c1d84bf9a3e492d124f0d555f9ad2e12d92c2 Mon Sep 17 00:00:00 2001
From: Andy Eschbacher <andy.eschbacher@gmail.com>
Date: Fri, 19 May 2017 15:17:56 -0400
Subject: [PATCH 5/7] small edits

---
 .../Shapely, Geopandas, and Cartoframes.ipynb | 896 ++++++++++++------
 1 file changed, 581 insertions(+), 315 deletions(-)

diff --git a/examples/Shapely, Geopandas, and Cartoframes.ipynb b/examples/Shapely, Geopandas, and Cartoframes.ipynb
index 3c6e681e2..f8f2d6986 100644
--- a/examples/Shapely, Geopandas, and Cartoframes.ipynb	
+++ b/examples/Shapely, Geopandas, and Cartoframes.ipynb	
@@ -4,15 +4,15 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Here, I'll show the relationship between cartoframes and geopandas."
+    "# Shapely, Geopandas, and CartoFrames\n",
+    "\n",
+    "Here, you can see the relationship between cartoframes and geopandas."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import cartoframes as cf\n",
@@ -23,9 +23,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "cxn = cf.CartoContext() # remember, store your credentials \n",
@@ -42,14 +40,267 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "df = cxn.read('nat')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>the_geom</th>\n",
+       "      <th>the_geom_webmercator</th>\n",
+       "      <th>name</th>\n",
+       "      <th>state_name</th>\n",
+       "      <th>state_fips</th>\n",
+       "      <th>cnty_fips</th>\n",
+       "      <th>fips</th>\n",
+       "      <th>stfips</th>\n",
+       "      <th>cofips</th>\n",
+       "      <th>fipsno</th>\n",
+       "      <th>...</th>\n",
+       "      <th>blk90</th>\n",
+       "      <th>gi59</th>\n",
+       "      <th>gi69</th>\n",
+       "      <th>gi79</th>\n",
+       "      <th>gi89</th>\n",
+       "      <th>fh60</th>\n",
+       "      <th>fh70</th>\n",
+       "      <th>fh80</th>\n",
+       "      <th>fh90</th>\n",
+       "      <th>geometry</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cartodb_id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>364</th>\n",
+       "      <td>0106000020E61000000100000001030000000100000007...</td>\n",
+       "      <td>0106000020110F00000100000001030000000100000007...</td>\n",
+       "      <td>Murray</td>\n",
+       "      <td>Minnesota</td>\n",
+       "      <td>27</td>\n",
+       "      <td>101</td>\n",
+       "      <td>27101</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>27101.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.340082</td>\n",
+       "      <td>0.414127</td>\n",
+       "      <td>0.382432</td>\n",
+       "      <td>0.364256</td>\n",
+       "      <td>9.146341</td>\n",
+       "      <td>5.1</td>\n",
+       "      <td>5.566097</td>\n",
+       "      <td>4.782767</td>\n",
+       "      <td>(POLYGON ((-95.46772003173828 44.1970138549804...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1660</th>\n",
+       "      <td>0106000020E61000000100000001030000000100000006...</td>\n",
+       "      <td>0106000020110F00000100000001030000000100000006...</td>\n",
+       "      <td>Chautauqua</td>\n",
+       "      <td>Kansas</td>\n",
+       "      <td>20</td>\n",
+       "      <td>019</td>\n",
+       "      <td>20019</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>20019.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.521897</td>\n",
+       "      <td>0.368538</td>\n",
+       "      <td>0.437940</td>\n",
+       "      <td>0.401030</td>\n",
+       "      <td>0.395566</td>\n",
+       "      <td>9.501188</td>\n",
+       "      <td>6.8</td>\n",
+       "      <td>7.728495</td>\n",
+       "      <td>8.073541</td>\n",
+       "      <td>(POLYGON ((-96.00579071044922 36.9982643127441...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>115</th>\n",
+       "      <td>0106000020E6100000010000000103000000010000000A...</td>\n",
+       "      <td>0106000020110F0000010000000103000000010000000A...</td>\n",
+       "      <td>Becker</td>\n",
+       "      <td>Minnesota</td>\n",
+       "      <td>27</td>\n",
+       "      <td>005</td>\n",
+       "      <td>27005</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>27005.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.071733</td>\n",
+       "      <td>0.328578</td>\n",
+       "      <td>0.390693</td>\n",
+       "      <td>0.374987</td>\n",
+       "      <td>0.375178</td>\n",
+       "      <td>12.385242</td>\n",
+       "      <td>7.2</td>\n",
+       "      <td>8.790072</td>\n",
+       "      <td>11.961039</td>\n",
+       "      <td>(POLYGON ((-95.16522216796874 46.7163505554199...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55</th>\n",
+       "      <td>0106000020E6100000010000000103000000010000000A...</td>\n",
+       "      <td>0106000020110F0000010000000103000000010000000A...</td>\n",
+       "      <td>Pennington</td>\n",
+       "      <td>Minnesota</td>\n",
+       "      <td>27</td>\n",
+       "      <td>113</td>\n",
+       "      <td>27113</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>27113.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.082669</td>\n",
+       "      <td>0.264746</td>\n",
+       "      <td>0.361857</td>\n",
+       "      <td>0.357659</td>\n",
+       "      <td>0.370818</td>\n",
+       "      <td>11.554969</td>\n",
+       "      <td>7.1</td>\n",
+       "      <td>10.775000</td>\n",
+       "      <td>10.980841</td>\n",
+       "      <td>(POLYGON ((-96.48169708251953 47.9642181396484...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>62</th>\n",
+       "      <td>0106000020E61000000100000001030000000100000035...</td>\n",
+       "      <td>0106000020110F00000100000001030000000100000035...</td>\n",
+       "      <td>Shoshone</td>\n",
+       "      <td>Idaho</td>\n",
+       "      <td>16</td>\n",
+       "      <td>079</td>\n",
+       "      <td>16079</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>16079.0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.114852</td>\n",
+       "      <td>0.185961</td>\n",
+       "      <td>0.296188</td>\n",
+       "      <td>0.328998</td>\n",
+       "      <td>0.364126</td>\n",
+       "      <td>7.810136</td>\n",
+       "      <td>5.4</td>\n",
+       "      <td>8.762984</td>\n",
+       "      <td>12.869565</td>\n",
+       "      <td>(POLYGON ((-114.9637680053711 46.92529296875, ...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 72 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                     the_geom  \\\n",
+       "cartodb_id                                                      \n",
+       "364         0106000020E61000000100000001030000000100000007...   \n",
+       "1660        0106000020E61000000100000001030000000100000006...   \n",
+       "115         0106000020E6100000010000000103000000010000000A...   \n",
+       "55          0106000020E6100000010000000103000000010000000A...   \n",
+       "62          0106000020E61000000100000001030000000100000035...   \n",
+       "\n",
+       "                                         the_geom_webmercator        name  \\\n",
+       "cartodb_id                                                                  \n",
+       "364         0106000020110F00000100000001030000000100000007...      Murray   \n",
+       "1660        0106000020110F00000100000001030000000100000006...  Chautauqua   \n",
+       "115         0106000020110F0000010000000103000000010000000A...      Becker   \n",
+       "55          0106000020110F0000010000000103000000010000000A...  Pennington   \n",
+       "62          0106000020110F00000100000001030000000100000035...    Shoshone   \n",
+       "\n",
+       "           state_name state_fips cnty_fips   fips  stfips  cofips   fipsno  \\\n",
+       "cartodb_id                                                                   \n",
+       "364         Minnesota         27       101  27101    27.0   101.0  27101.0   \n",
+       "1660           Kansas         20       019  20019    20.0    19.0  20019.0   \n",
+       "115         Minnesota         27       005  27005    27.0     5.0  27005.0   \n",
+       "55          Minnesota         27       113  27113    27.0   113.0  27113.0   \n",
+       "62              Idaho         16       079  16079    16.0    79.0  16079.0   \n",
+       "\n",
+       "                                  ...                             blk90  \\\n",
+       "cartodb_id                        ...                                     \n",
+       "364                               ...                          0.000000   \n",
+       "1660                              ...                          0.521897   \n",
+       "115                               ...                          0.071733   \n",
+       "55                                ...                          0.082669   \n",
+       "62                                ...                          0.114852   \n",
+       "\n",
+       "                gi59      gi69      gi79      gi89       fh60  fh70  \\\n",
+       "cartodb_id                                                            \n",
+       "364         0.340082  0.414127  0.382432  0.364256   9.146341   5.1   \n",
+       "1660        0.368538  0.437940  0.401030  0.395566   9.501188   6.8   \n",
+       "115         0.328578  0.390693  0.374987  0.375178  12.385242   7.2   \n",
+       "55          0.264746  0.361857  0.357659  0.370818  11.554969   7.1   \n",
+       "62          0.185961  0.296188  0.328998  0.364126   7.810136   5.4   \n",
+       "\n",
+       "                 fh80       fh90  \\\n",
+       "cartodb_id                         \n",
+       "364          5.566097   4.782767   \n",
+       "1660         7.728495   8.073541   \n",
+       "115          8.790072  11.961039   \n",
+       "55          10.775000  10.980841   \n",
+       "62           8.762984  12.869565   \n",
+       "\n",
+       "                                                     geometry  \n",
+       "cartodb_id                                                     \n",
+       "364         (POLYGON ((-95.46772003173828 44.1970138549804...  \n",
+       "1660        (POLYGON ((-96.00579071044922 36.9982643127441...  \n",
+       "115         (POLYGON ((-95.16522216796874 46.7163505554199...  \n",
+       "55          (POLYGON ((-96.48169708251953 47.9642181396484...  \n",
+       "62          (POLYGON ((-114.9637680053711 46.92529296875, ...  \n",
+       "\n",
+       "[5 rows x 72 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -59,10 +310,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 5,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -83,14 +332,14 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1505</th>\n",
-       "      <td>17165.0</td>\n",
-       "      <td>0103000020E6100000010000000700000000000000661A...</td>\n",
+       "      <th>364</th>\n",
+       "      <td>27101.0</td>\n",
+       "      <td>0106000020E61000000100000001030000000100000007...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1720</th>\n",
-       "      <td>40053.0</td>\n",
-       "      <td>0103000020E61000000100000007000000000000205F86...</td>\n",
+       "      <th>1660</th>\n",
+       "      <td>20019.0</td>\n",
+       "      <td>0106000020E61000000100000001030000000100000006...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -99,11 +348,11 @@
       "text/plain": [
        "             fipsno                                           the_geom\n",
        "cartodb_id                                                            \n",
-       "1505        17165.0  0103000020E6100000010000000700000000000000661A...\n",
-       "1720        40053.0  0103000020E61000000100000007000000000000205F86..."
+       "364         27101.0  0106000020E61000000100000001030000000100000007...\n",
+       "1660        20019.0  0106000020E61000000100000001030000000100000006..."
       ]
      },
-     "execution_count": 4,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -121,10 +370,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 6,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -145,14 +392,14 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1505</th>\n",
-       "      <td>17165.0</td>\n",
-       "      <td>POLYGON ((-88.4124755859375 37.60790252685547,...</td>\n",
+       "      <th>364</th>\n",
+       "      <td>27101.0</td>\n",
+       "      <td>(POLYGON ((-95.46772003173828 44.1970138549804...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1720</th>\n",
-       "      <td>40053.0</td>\n",
-       "      <td>POLYGON ((-98.09955596923828 36.59130859375, -...</td>\n",
+       "      <th>1660</th>\n",
+       "      <td>20019.0</td>\n",
+       "      <td>(POLYGON ((-96.00579071044922 36.9982643127441...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -161,11 +408,11 @@
       "text/plain": [
        "             fipsno                                           geometry\n",
        "cartodb_id                                                            \n",
-       "1505        17165.0  POLYGON ((-88.4124755859375 37.60790252685547,...\n",
-       "1720        40053.0  POLYGON ((-98.09955596923828 36.59130859375, -..."
+       "364         27101.0  (POLYGON ((-95.46772003173828 44.1970138549804...\n",
+       "1660        20019.0  (POLYGON ((-96.00579071044922 36.9982643127441..."
       ]
      },
-     "execution_count": 5,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -178,31 +425,18 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This allows you to do GIS operations locally in Geopandas. To send a dataframe with shapely geometries into a Geopandas dataframe, you only need to call the constructor directly on the dataframe:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "gdf = gpd.GeoDataFrame(df)"
+    "This allows you to do GIS operations locally in Geopandas. To send a dataframe with shapely geometries into a Geopandas DataFrame, you only need to call the constructor directly on the DataFrame:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f97958c81d0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x10efd0c88>"
       ]
      },
      "execution_count": 7,
@@ -211,9 +445,9 @@
     },
     {
      "data": {
-      "image/png": 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nWrBjC3iGYeyJm6CUIBHpkY2uUmrkaXeaKG6JRrtBInUiLDrNKsUn2RdPLz+n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tu5vf4Nto7u45c92AwbplcmnV2lXNjDKVjEPUkeljfx+2NgzlBVhXxilaPWPrPJFIddZjAeEg8n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\nTkXneZC5hyseQQpGKFQyZAt7JLwJEokZas0i48GI6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UxlxaPUe712S//BjZKTPWxljHyrke5h8yHY0o5bfndu9xWRkCtNsVVkJZqs0y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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f97958aee80>"
+       "<matplotlib.figure.Figure at 0x10efd0668>"
       ]
      },
      "metadata": {},
@@ -221,7 +455,8 @@
     }
    ],
    "source": [
-    "gpd.GeoDataFrame(df).plot('hr90', linewidth=.1) #to prove we're in geopandas"
+    "gdf = gpd.GeoDataFrame(df)\n",
+    "gdf.plot('hr90', linewidth=.1) # to prove we're in geopandas"
    ]
   },
   {
@@ -234,12 +469,107 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<iframe srcdoc=\"<!DOCTYPE html>\n",
+       "<html>\n",
+       "  <head>\n",
+       "    <title>Carto</title>\n",
+       "    <meta name='viewport' content='initial-scale=1.0, user-scalable=no' />\n",
+       "    <meta http-equiv='content-type' content='text/html; charset=UTF-8' />\n",
+       "    <link rel='shortcut icon' href='http://cartodb.com/assets/favicon.ico' />\n",
+       "\n",
+       "    <style>\n",
+       "     html, body, #map {\n",
+       "       height: 100%;\n",
+       "       padding: 0;\n",
+       "       margin: 0;\n",
+       "     }\n",
+       "     #zoom-center {\n",
+       "       position: absolute;\n",
+       "       right: 0;\n",
+       "       top: 0;\n",
+       "       background-color: rgba(255, 255, 255, 0.7);\n",
+       "       width: 240px;\n",
+       "       z-index: 100;\n",
+       "       padding: 4px;\n",
+       "     }\n",
+       "    </style>\n",
+       "\n",
+       "    <link rel='stylesheet' href='https://cartodb-libs.global.ssl.fastly.net/cartodb.js/v3/3.15/themes/css/cartodb.css' />\n",
+       "  </head>\n",
+       "  <body>\n",
+       "    <div id='zoom-center'>\n",
+       "      zoom=<span id='zoom'>4</span>,\n",
+       "      lng=<span id='lon'>No data</span>, lat=<span id='lat'>No data</span></div>\n",
+       "    <div id='map'></div>\n",
+       "    <script src='https://cartodb-libs.global.ssl.fastly.net/cartodb.js/v3/3.15/cartodb.js'></script>\n",
+       "\n",
+       "    <script>\n",
+       "     const config  = {'user_name': 'eschbacher', 'maps_api_template': 'https://eschbacher.carto.com', 'sql_api_template': 'https://eschbacher.carto.com', 'tiler_protocol': 'https', 'tiler_domain': 'carto.com', 'tiler_port': '80', 'type': 'namedmap', 'named_map': {'name': 'cartoframes_ver20170406_layers1_time0_baseid1_labels0_zoom0', 'params': {'basemap_url': 'https://cartodb-basemaps-{s}.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png', 'cartocss_0': &quot;#layer[&#92;'mapnik::geometry_type&#92;'=1] {  marker-width: 10; marker-fill: ramp([hr90], cartocolor(Sunset), quantiles(7)); marker-fill-opacity: 1; marker-allow-overlap: true; marker-line-width: 0.5; marker-line-color: #000; marker-line-opacity: 1;} #layer[&#92;'mapnik::geometry_type&#92;'=2] {  line-width: 1.5; line-color: ramp([hr90], cartocolor(Sunset), quantiles(7));} #layer[&#92;'mapnik::geometry_type&#92;'=3] {  polygon-fill: ramp([hr90], cartocolor(Sunset), quantiles(7)); polygon-opacity: 0.9; polygon-gamma: 0.5; line-color: #FFF; line-width: 0.5; line-opacity: 0.25; line-comp-op: hard-light;} &quot;, 'sql_0': 'SELECT * FROM nat', 'west': -124.73142242431599, 'south': 24.955966949462901, 'east': -66.9698486328125, 'north': 49.371734619140597}}};\n",
+       "     const bounds  = [[49.371734619140597, -66.9698486328125], [24.955966949462901, -124.73142242431599]];\n",
+       "     const options = {'filter': ['http', 'mapnik', 'torque'], 'https': true};\n",
+       "\n",
+       "     const adjustLongitude = (lng) => (\n",
+       "       lng - ((Math.ceil((lng + 180) / 360) - 1) * 360)\n",
+       "     );\n",
+       "     const map = L.map('map', {\n",
+       "       zoom: 3,\n",
+       "       center: [0, 0],\n",
+       "     });\n",
+       "     const updateMapInfo = () => {\n",
+       "       $('#zoom').text(map.getZoom());\n",
+       "       $('#lat').text(map.getCenter().lat.toFixed(4));\n",
+       "       $('#lon').text(adjustLongitude(map.getCenter().lng).toFixed(4));\n",
+       "     };\n",
+       "\n",
+       "     cartodb.createLayer(map, config, options)\n",
+       "            .addTo(map)\n",
+       "            .done((layer) => {\n",
+       "              if (bounds.length) {\n",
+       "                map.fitBounds(bounds);\n",
+       "              }\n",
+       "              updateMapInfo();\n",
+       "              map.on('move', () => {\n",
+       "                updateMapInfo();\n",
+       "              });\n",
+       "            })\n",
+       "            .error((err) => {\n",
+       "              console.log('ERROR: ', err);\n",
+       "            });\n",
+       "    </script>\n",
+       "\n",
+       "  </body>\n",
+       "</html>\n",
+       "\" width=800 height=400>  Preview image: <img src=\"https://eschbacher.carto.com/api/v1/map/static/named/cartoframes_ver20170406_layers1_time0_baseid1_labels0_zoom0/800/400.png?config=%7B%22basemap_url%22%3A+%22https%3A%2F%2Fcartodb-basemaps-%7Bs%7D.global.ssl.fastly.net%2Fdark_all%2F%7Bz%7D%2F%7Bx%7D%2F%7By%7D.png%22%2C+%22cartocss_0%22%3A+%22%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D1%5D+%7B++marker-width%3A+10%3B+marker-fill%3A+ramp%28%5Bhr90%5D%2C+cartocolor%28Sunset%29%2C+quantiles%287%29%29%3B+marker-fill-opacity%3A+1%3B+marker-allow-overlap%3A+true%3B+marker-line-width%3A+0.5%3B+marker-line-color%3A+%23000%3B+marker-line-opacity%3A+1%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D2%5D+%7B++line-width%3A+1.5%3B+line-color%3A+ramp%28%5Bhr90%5D%2C+cartocolor%28Sunset%29%2C+quantiles%287%29%29%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D3%5D+%7B++polygon-fill%3A+ramp%28%5Bhr90%5D%2C+cartocolor%28Sunset%29%2C+quantiles%287%29%29%3B+polygon-opacity%3A+0.9%3B+polygon-gamma%3A+0.5%3B+line-color%3A+%23FFF%3B+line-width%3A+0.5%3B+line-opacity%3A+0.25%3B+line-comp-op%3A+hard-light%3B%7D+%22%2C+%22sql_0%22%3A+%22SELECT+%2A+FROM+nat%22%7D&anti_cache=0.03286307778211395\" /></iframe>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from cartoframes import Layer, styling\n",
+    "cxn.map(layers=Layer('nat', color={'column': 'hr90', 'scheme': styling.sunset(7)}))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "cxn.write(df, encode_geom=True, table_name='new_table', overwrite=True)"
+    "cxn.write(gdf,\n",
+    "          encode_geom=True,\n",
+    "          table_name='cartoframes_geopandas',\n",
+    "          overwrite=True)"
    ]
   },
   {
@@ -251,10 +581,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 10,
+   "metadata": {},
    "outputs": [],
    "source": [
     "gdf['geometry'] = gdf.geometry.apply(lambda x: x.buffer(2))\n",
@@ -263,21 +591,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [],
    "source": [
-    "cxn.write(gdf, encode_geom=True, table_name='buffered', overwrite=True)"
+    "cxn.write(gdf, encode_geom=True,\n",
+    "          table_name='cartoframes_geopandas_buffered',\n",
+    "          overwrite=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
-    "collapsed": false
+    "scrolled": false
    },
    "outputs": [
     {
@@ -288,26 +617,26 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>ma90</th>\n",
-       "      <th>south</th>\n",
-       "      <th>fp89</th>\n",
-       "      <th>dnl60</th>\n",
-       "      <th>mfil79</th>\n",
-       "      <th>rd90</th>\n",
-       "      <th>dv80</th>\n",
-       "      <th>hc60</th>\n",
-       "      <th>po70</th>\n",
-       "      <th>ps90</th>\n",
-       "      <th>...</th>\n",
-       "      <th>blk90</th>\n",
-       "      <th>rd60</th>\n",
+       "      <th>the_geom</th>\n",
+       "      <th>the_geom_webmercator</th>\n",
+       "      <th>name</th>\n",
+       "      <th>state_name</th>\n",
        "      <th>state_fips</th>\n",
-       "      <th>dv90</th>\n",
-       "      <th>fp69</th>\n",
-       "      <th>field_1</th>\n",
+       "      <th>cnty_fips</th>\n",
+       "      <th>fips</th>\n",
+       "      <th>stfips</th>\n",
+       "      <th>cofips</th>\n",
        "      <th>fipsno</th>\n",
+       "      <th>...</th>\n",
+       "      <th>blk90</th>\n",
+       "      <th>gi59</th>\n",
+       "      <th>gi69</th>\n",
+       "      <th>gi79</th>\n",
+       "      <th>gi89</th>\n",
+       "      <th>fh60</th>\n",
+       "      <th>fh70</th>\n",
+       "      <th>fh80</th>\n",
        "      <th>fh90</th>\n",
-       "      <th>pol80</th>\n",
        "      <th>geometry</th>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -337,175 +666,191 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1505</th>\n",
-       "      <td>38.2</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>15.828502</td>\n",
-       "      <td>4.226510</td>\n",
-       "      <td>9.695417</td>\n",
-       "      <td>0.377041</td>\n",
-       "      <td>5.412968</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>25721.0</td>\n",
-       "      <td>0.207842</td>\n",
+       "      <th>364</th>\n",
+       "      <td>0103000000010000004900000013d72ae150dd57c02a78...</td>\n",
+       "      <td>0106000020110F00000100000001030000000100000007...</td>\n",
+       "      <td>Murray</td>\n",
+       "      <td>Minnesota</td>\n",
+       "      <td>27</td>\n",
+       "      <td>101</td>\n",
+       "      <td>27101</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>101.0</td>\n",
+       "      <td>27101.0</td>\n",
        "      <td>...</td>\n",
-       "      <td>3.506459</td>\n",
-       "      <td>0.457671</td>\n",
-       "      <td>17.0</td>\n",
-       "      <td>8.403532</td>\n",
-       "      <td>19.3</td>\n",
-       "      <td>1504.0</td>\n",
-       "      <td>17165.0</td>\n",
-       "      <td>13.172442</td>\n",
-       "      <td>10.255833</td>\n",
-       "      <td>POLYGON ((-88.35277784856117 35.60879368035607...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.340082</td>\n",
+       "      <td>0.414127</td>\n",
+       "      <td>0.382432</td>\n",
+       "      <td>0.364256</td>\n",
+       "      <td>9.146341</td>\n",
+       "      <td>5.1</td>\n",
+       "      <td>5.566097</td>\n",
+       "      <td>4.782767</td>\n",
+       "      <td>POLYGON ((-95.45806149657828 46.19699053301913...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1720</th>\n",
-       "      <td>39.5</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>11.474435</td>\n",
-       "      <td>2.089815</td>\n",
-       "      <td>9.738908</td>\n",
-       "      <td>-0.342290</td>\n",
-       "      <td>4.069299</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>7117.0</td>\n",
-       "      <td>-1.178859</td>\n",
+       "      <th>1660</th>\n",
+       "      <td>01030000000100000047000000c828d722b9fb57c02ced...</td>\n",
+       "      <td>0106000020110F00000100000001030000000100000006...</td>\n",
+       "      <td>Chautauqua</td>\n",
+       "      <td>Kansas</td>\n",
+       "      <td>20</td>\n",
+       "      <td>019</td>\n",
+       "      <td>20019</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>20019.0</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.052733</td>\n",
-       "      <td>-0.358385</td>\n",
-       "      <td>40.0</td>\n",
-       "      <td>5.862884</td>\n",
-       "      <td>14.6</td>\n",
-       "      <td>1719.0</td>\n",
-       "      <td>40053.0</td>\n",
-       "      <td>7.134364</td>\n",
-       "      <td>8.782323</td>\n",
-       "      <td>POLYGON ((-98.09408038595517 34.59131608926712...</td>\n",
+       "      <td>0.521897</td>\n",
+       "      <td>0.368538</td>\n",
+       "      <td>0.437940</td>\n",
+       "      <td>0.401030</td>\n",
+       "      <td>0.395566</td>\n",
+       "      <td>9.501188</td>\n",
+       "      <td>6.8</td>\n",
+       "      <td>7.728495</td>\n",
+       "      <td>8.073541</td>\n",
+       "      <td>POLYGON ((-95.93317481052065 34.99958301471847...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2799</th>\n",
-       "      <td>36.7</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>9.645150</td>\n",
-       "      <td>3.555298</td>\n",
-       "      <td>9.842463</td>\n",
-       "      <td>-0.553942</td>\n",
-       "      <td>4.230542</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>24165.0</td>\n",
-       "      <td>0.554042</td>\n",
+       "      <th>115</th>\n",
+       "      <td>0103000000010000004c000000d1b43b8a3e8b58c02e9d...</td>\n",
+       "      <td>0106000020110F0000010000000103000000010000000A...</td>\n",
+       "      <td>Becker</td>\n",
+       "      <td>Minnesota</td>\n",
+       "      <td>27</td>\n",
+       "      <td>005</td>\n",
+       "      <td>27005</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>27005.0</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.854684</td>\n",
-       "      <td>-0.498175</td>\n",
-       "      <td>48.0</td>\n",
-       "      <td>7.072922</td>\n",
-       "      <td>13.0</td>\n",
-       "      <td>2798.0</td>\n",
-       "      <td>48091.0</td>\n",
-       "      <td>9.104427</td>\n",
-       "      <td>10.503587</td>\n",
-       "      <td>POLYGON ((-99.342072998125 27.87317430656412, ...</td>\n",
+       "      <td>0.071733</td>\n",
+       "      <td>0.328578</td>\n",
+       "      <td>0.390693</td>\n",
+       "      <td>0.374987</td>\n",
+       "      <td>0.375178</td>\n",
+       "      <td>12.385242</td>\n",
+       "      <td>7.2</td>\n",
+       "      <td>8.790072</td>\n",
+       "      <td>11.961039</td>\n",
+       "      <td>POLYGON ((-98.17569213705725 46.72406149358208...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>43.9</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>8.383961</td>\n",
-       "      <td>1.454312</td>\n",
-       "      <td>9.708567</td>\n",
-       "      <td>-0.737595</td>\n",
-       "      <td>3.135889</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4564.0</td>\n",
-       "      <td>-1.724842</td>\n",
+       "      <th>55</th>\n",
+       "      <td>0103000000010000004a000000c0248c918d9a58c08a4b...</td>\n",
+       "      <td>0106000020110F0000010000000103000000010000000A...</td>\n",
+       "      <td>Pennington</td>\n",
+       "      <td>Minnesota</td>\n",
+       "      <td>27</td>\n",
+       "      <td>113</td>\n",
+       "      <td>27113</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>27113.0</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.034495</td>\n",
-       "      <td>-0.173043</td>\n",
-       "      <td>38.0</td>\n",
-       "      <td>5.452946</td>\n",
-       "      <td>14.6</td>\n",
-       "      <td>13.0</td>\n",
-       "      <td>38023.0</td>\n",
-       "      <td>9.113001</td>\n",
-       "      <td>8.158802</td>\n",
-       "      <td>POLYGON ((-100.9549124845266 49.24699589679899...</td>\n",
+       "      <td>0.082669</td>\n",
+       "      <td>0.264746</td>\n",
+       "      <td>0.361857</td>\n",
+       "      <td>0.357659</td>\n",
+       "      <td>0.370818</td>\n",
+       "      <td>11.554969</td>\n",
+       "      <td>7.1</td>\n",
+       "      <td>10.775000</td>\n",
+       "      <td>10.980841</td>\n",
+       "      <td>POLYGON ((-98.41489065824408 47.46063804640205...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>68</th>\n",
-       "      <td>35.5</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>10.930828</td>\n",
-       "      <td>2.602347</td>\n",
-       "      <td>9.551587</td>\n",
-       "      <td>-0.652795</td>\n",
-       "      <td>2.569074</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>5388.0</td>\n",
-       "      <td>-1.070270</td>\n",
+       "      <th>62</th>\n",
+       "      <td>0103000000010000005b000000644f2b866ee75cc03ff8...</td>\n",
+       "      <td>0106000020110F00000100000001030000000100000035...</td>\n",
+       "      <td>Shoshone</td>\n",
+       "      <td>Idaho</td>\n",
+       "      <td>16</td>\n",
+       "      <td>079</td>\n",
+       "      <td>16079</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>16079.0</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>-0.089455</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>5.014409</td>\n",
-       "      <td>21.2</td>\n",
-       "      <td>67.0</td>\n",
-       "      <td>27125.0</td>\n",
-       "      <td>6.746371</td>\n",
-       "      <td>8.607217</td>\n",
-       "      <td>POLYGON ((-98.481259264152 48.00606406878377, ...</td>\n",
+       "      <td>0.114852</td>\n",
+       "      <td>0.185961</td>\n",
+       "      <td>0.296188</td>\n",
+       "      <td>0.328998</td>\n",
+       "      <td>0.364126</td>\n",
+       "      <td>7.810136</td>\n",
+       "      <td>5.4</td>\n",
+       "      <td>8.762984</td>\n",
+       "      <td>12.869565</td>\n",
+       "      <td>POLYGON ((-115.6161208556128 49.95441929622074...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 73 columns</p>\n",
+       "<p>5 rows × 72 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "            ma90  south       fp89     dnl60    mfil79      rd90      dv80  \\\n",
-       "cartodb_id                                                                   \n",
-       "1505        38.2    0.0  15.828502  4.226510  9.695417  0.377041  5.412968   \n",
-       "1720        39.5    1.0  11.474435  2.089815  9.738908 -0.342290  4.069299   \n",
-       "2799        36.7    1.0   9.645150  3.555298  9.842463 -0.553942  4.230542   \n",
-       "14          43.9    0.0   8.383961  1.454312  9.708567 -0.737595  3.135889   \n",
-       "68          35.5    0.0  10.930828  2.602347  9.551587 -0.652795  2.569074   \n",
+       "                                                     the_geom  \\\n",
+       "cartodb_id                                                      \n",
+       "364         0103000000010000004900000013d72ae150dd57c02a78...   \n",
+       "1660        01030000000100000047000000c828d722b9fb57c02ced...   \n",
+       "115         0103000000010000004c000000d1b43b8a3e8b58c02e9d...   \n",
+       "55          0103000000010000004a000000c0248c918d9a58c08a4b...   \n",
+       "62          0103000000010000005b000000644f2b866ee75cc03ff8...   \n",
        "\n",
-       "                hc60     po70      ps90  \\\n",
-       "cartodb_id                                \n",
-       "1505        1.000000  25721.0  0.207842   \n",
-       "1720        0.000000   7117.0 -1.178859   \n",
-       "2799        0.666667  24165.0  0.554042   \n",
-       "14          0.000000   4564.0 -1.724842   \n",
-       "68          0.000000   5388.0 -1.070270   \n",
+       "                                         the_geom_webmercator        name  \\\n",
+       "cartodb_id                                                                  \n",
+       "364         0106000020110F00000100000001030000000100000007...      Murray   \n",
+       "1660        0106000020110F00000100000001030000000100000006...  Chautauqua   \n",
+       "115         0106000020110F0000010000000103000000010000000A...      Becker   \n",
+       "55          0106000020110F0000010000000103000000010000000A...  Pennington   \n",
+       "62          0106000020110F00000100000001030000000100000035...    Shoshone   \n",
+       "\n",
+       "           state_name state_fips cnty_fips   fips  stfips  cofips   fipsno  \\\n",
+       "cartodb_id                                                                   \n",
+       "364         Minnesota         27       101  27101    27.0   101.0  27101.0   \n",
+       "1660           Kansas         20       019  20019    20.0    19.0  20019.0   \n",
+       "115         Minnesota         27       005  27005    27.0     5.0  27005.0   \n",
+       "55          Minnesota         27       113  27113    27.0   113.0  27113.0   \n",
+       "62              Idaho         16       079  16079    16.0    79.0  16079.0   \n",
        "\n",
        "                                  ...                             blk90  \\\n",
        "cartodb_id                        ...                                     \n",
-       "1505                              ...                          3.506459   \n",
-       "1720                              ...                          0.052733   \n",
-       "2799                              ...                          0.854684   \n",
-       "14                                ...                          0.034495   \n",
-       "68                                ...                          0.000000   \n",
+       "364                               ...                          0.000000   \n",
+       "1660                              ...                          0.521897   \n",
+       "115                               ...                          0.071733   \n",
+       "55                                ...                          0.082669   \n",
+       "62                                ...                          0.114852   \n",
        "\n",
-       "                rd60  state_fips      dv90  fp69  field_1   fipsno       fh90  \\\n",
-       "cartodb_id                                                                      \n",
-       "1505        0.457671        17.0  8.403532  19.3   1504.0  17165.0  13.172442   \n",
-       "1720       -0.358385        40.0  5.862884  14.6   1719.0  40053.0   7.134364   \n",
-       "2799       -0.498175        48.0  7.072922  13.0   2798.0  48091.0   9.104427   \n",
-       "14         -0.173043        38.0  5.452946  14.6     13.0  38023.0   9.113001   \n",
-       "68         -0.089455        27.0  5.014409  21.2     67.0  27125.0   6.746371   \n",
+       "                gi59      gi69      gi79      gi89       fh60  fh70  \\\n",
+       "cartodb_id                                                            \n",
+       "364         0.340082  0.414127  0.382432  0.364256   9.146341   5.1   \n",
+       "1660        0.368538  0.437940  0.401030  0.395566   9.501188   6.8   \n",
+       "115         0.328578  0.390693  0.374987  0.375178  12.385242   7.2   \n",
+       "55          0.264746  0.361857  0.357659  0.370818  11.554969   7.1   \n",
+       "62          0.185961  0.296188  0.328998  0.364126   7.810136   5.4   \n",
        "\n",
-       "                pol80                                           geometry  \n",
-       "cartodb_id                                                                \n",
-       "1505        10.255833  POLYGON ((-88.35277784856117 35.60879368035607...  \n",
-       "1720         8.782323  POLYGON ((-98.09408038595517 34.59131608926712...  \n",
-       "2799        10.503587  POLYGON ((-99.342072998125 27.87317430656412, ...  \n",
-       "14           8.158802  POLYGON ((-100.9549124845266 49.24699589679899...  \n",
-       "68           8.607217  POLYGON ((-98.481259264152 48.00606406878377, ...  \n",
+       "                 fh80       fh90  \\\n",
+       "cartodb_id                         \n",
+       "364          5.566097   4.782767   \n",
+       "1660         7.728495   8.073541   \n",
+       "115          8.790072  11.961039   \n",
+       "55          10.775000  10.980841   \n",
+       "62           8.762984  12.869565   \n",
        "\n",
-       "[5 rows x 73 columns]"
+       "                                                     geometry  \n",
+       "cartodb_id                                                     \n",
+       "364         POLYGON ((-95.45806149657828 46.19699053301913...  \n",
+       "1660        POLYGON ((-95.93317481052065 34.99958301471847...  \n",
+       "115         POLYGON ((-98.17569213705725 46.72406149358208...  \n",
+       "55          POLYGON ((-98.41489065824408 47.46063804640205...  \n",
+       "62          POLYGON ((-115.6161208556128 49.95441929622074...  \n",
+       "\n",
+       "[5 rows x 72 columns]"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -516,118 +861,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<iframe srcdoc=\"<!DOCTYPE html>\n",
-       "<html>\n",
-       "  <head>\n",
-       "    <title>Carto</title>\n",
-       "    <meta name='viewport' content='initial-scale=1.0, user-scalable=no' />\n",
-       "    <meta http-equiv='content-type' content='text/html; charset=UTF-8' />\n",
-       "    <link rel='shortcut icon' href='http://cartodb.com/assets/favicon.ico' />\n",
-       "\n",
-       "    <style>\n",
-       "     html, body, #map {\n",
-       "       height: 100%;\n",
-       "       padding: 0;\n",
-       "       margin: 0;\n",
-       "     }\n",
-       "     #zoom-center {\n",
-       "       position: absolute;\n",
-       "       right: 0;\n",
-       "       top: 0;\n",
-       "       background-color: rgba(255, 255, 255, 0.7);\n",
-       "       width: 240px;\n",
-       "       z-index: 100;\n",
-       "       padding: 4px;\n",
-       "     }\n",
-       "    </style>\n",
-       "\n",
-       "    <link rel='stylesheet' href='https://cartodb-libs.global.ssl.fastly.net/cartodb.js/v3/3.15/themes/css/cartodb.css' />\n",
-       "  </head>\n",
-       "  <body>\n",
-       "    <div id='zoom-center'>\n",
-       "      zoom=<span id='zoom'>4</span>,\n",
-       "      lng=<span id='lon'>No data</span>, lat=<span id='lat'>No data</span></div>\n",
-       "    <div id='map'></div>\n",
-       "    <script src='https://cartodb-libs.global.ssl.fastly.net/cartodb.js/v3/3.15/cartodb.js'></script>\n",
-       "\n",
-       "    <script>\n",
-       "     const config  = {'maps_api_template': 'https://lwolf-carto.carto.com', 'user_name': 'lwolf-carto', 'tiler_protocol': 'https', 'tiler_port': '80', 'sql_api_template': 'https://lwolf-carto.carto.com', 'named_map': {'name': 'cartoframes_ver20170406_layers1_time0_baseid1_labels0_zoom0', 'params': {'south': 22.9569580927926, 'sql_0': 'SELECT * FROM buffered', 'north': 51.370932923985499, 'cartocss_0': &quot;#layer[&#92;'mapnik::geometry_type&#92;'=1] {  marker-line-color: #000; marker-line-opacity: 1; marker-fill: ramp([gi69], cartocolor(Mint), quantiles(5)); marker-fill-opacity: 1; marker-line-width: 0.5; marker-width: 10; marker-allow-overlap: true;} #layer[&#92;'mapnik::geometry_type&#92;'=2] {  line-width: 1.5; line-color: ramp([gi69], cartocolor(Mint), quantiles(5));} #layer[&#92;'mapnik::geometry_type&#92;'=3] {  line-color: #FFF; polygon-gamma: 0.5; polygon-opacity: 0.9; line-opacity: 0.25; line-width: 0.5; line-comp-op: hard-light; polygon-fill: ramp([gi69], cartocolor(Mint), quantiles(5));} &quot;, 'west': -126.729647650788, 'basemap_url': 'https://cartodb-basemaps-{s}.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png', 'east': -64.969860407846895}}, 'type': 'namedmap', 'tiler_domain': 'carto.com'};\n",
-       "     const bounds  = [[51.370932923985499, -64.969860407846895], [22.9569580927926, -126.729647650788]];\n",
-       "     const options = {'https': true, 'filter': ['http', 'mapnik', 'torque']};\n",
-       "\n",
-       "     const adjustLongitude = (lng) => (\n",
-       "       lng - ((Math.ceil((lng + 180) / 360) - 1) * 360)\n",
-       "     );\n",
-       "     const map = L.map('map', {\n",
-       "       zoom: 3,\n",
-       "       center: [0, 0],\n",
-       "     });\n",
-       "     const updateMapInfo = () => {\n",
-       "       $('#zoom').text(map.getZoom());\n",
-       "       $('#lat').text(map.getCenter().lat.toFixed(4));\n",
-       "       $('#lon').text(adjustLongitude(map.getCenter().lng).toFixed(4));\n",
-       "     };\n",
-       "\n",
-       "     cartodb.createLayer(map, config, options)\n",
-       "            .addTo(map)\n",
-       "            .done((layer) => {\n",
-       "              if (bounds.length) {\n",
-       "                map.fitBounds(bounds);\n",
-       "              }\n",
-       "              updateMapInfo();\n",
-       "              map.on('move', () => {\n",
-       "                updateMapInfo();\n",
-       "              });\n",
-       "            })\n",
-       "            .error((err) => {\n",
-       "              console.log('ERROR: ', err);\n",
-       "            });\n",
-       "    </script>\n",
-       "\n",
-       "  </body>\n",
-       "</html>\n",
-       "\" width=800 height=400>  Preview image: <img src=\"https://lwolf-carto.carto.com/api/v1/map/static/named/cartoframes_ver20170406_layers1_time0_baseid1_labels0_zoom0/800/400.png?config=%7B%22cartocss_0%22%3A+%22%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D1%5D+%7B++marker-line-color%3A+%23000%3B+marker-line-opacity%3A+1%3B+marker-fill%3A+ramp%28%5Bgi69%5D%2C+cartocolor%28Mint%29%2C+quantiles%285%29%29%3B+marker-fill-opacity%3A+1%3B+marker-line-width%3A+0.5%3B+marker-width%3A+10%3B+marker-allow-overlap%3A+true%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D2%5D+%7B++line-width%3A+1.5%3B+line-color%3A+ramp%28%5Bgi69%5D%2C+cartocolor%28Mint%29%2C+quantiles%285%29%29%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D3%5D+%7B++line-color%3A+%23FFF%3B+polygon-gamma%3A+0.5%3B+polygon-opacity%3A+0.9%3B+line-opacity%3A+0.25%3B+line-width%3A+0.5%3B+line-comp-op%3A+hard-light%3B+polygon-fill%3A+ramp%28%5Bgi69%5D%2C+cartocolor%28Mint%29%2C+quantiles%285%29%29%3B%7D+%22%2C+%22basemap_url%22%3A+%22https%3A%2F%2Fcartodb-basemaps-%7Bs%7D.global.ssl.fastly.net%2Fdark_all%2F%7Bz%7D%2F%7Bx%7D%2F%7By%7D.png%22%2C+%22sql_0%22%3A+%22SELECT+%2A+FROM+buffered%22%7D&anti_cache=0.3092037769690339\" /></iframe>"
+       "<img src=\"https://eschbacher.carto.com/api/v1/map/static/named/cartoframes_ver20170406_layers1_time0_baseid0_labels0_zoom0/800/400.png?config=%7B%22basemap_url%22%3A+%22https%3A%2F%2Fcartodb-basemaps-%7Bs%7D.global.ssl.fastly.net%2Flight_all%2F%7Bz%7D%2F%7Bx%7D%2F%7By%7D.png%22%2C+%22cartocss_0%22%3A+%22%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D1%5D+%7B++marker-width%3A+10%3B+marker-fill%3A+ramp%28%5Bgi69%5D%2C+cartocolor%28Mint%29%2C+quantiles%285%29%29%3B+marker-fill-opacity%3A+1%3B+marker-allow-overlap%3A+true%3B+marker-line-width%3A+0.5%3B+marker-line-color%3A+%23FFF%3B+marker-line-opacity%3A+1%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D2%5D+%7B++line-width%3A+1.5%3B+line-color%3A+ramp%28%5Bgi69%5D%2C+cartocolor%28Mint%29%2C+quantiles%285%29%29%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D3%5D+%7B++polygon-fill%3A+ramp%28%5Bgi69%5D%2C+cartocolor%28Mint%29%2C+quantiles%285%29%29%3B+polygon-opacity%3A+0.9%3B+polygon-gamma%3A+0.5%3B+line-color%3A+%23FFF%3B+line-width%3A+0.5%3B+line-opacity%3A+0.25%3B+line-comp-op%3A+hard-light%3B%7D+%22%2C+%22sql_0%22%3A+%22SELECT+%2A+FROM+cartoframes_geopandas_buffered%22%7D&anti_cache=0.45856294708729795\" />"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "cxn.map(layers=[cf.BaseMap(), cf.Layer('buffered', \n",
-    "                                       color=dict(column='gi69'))],\n",
-    "        interactive=True)"
+    "cxn.map(layers=[cf.BaseMap('light'),\n",
+    "                cf.Layer('cartoframes_geopandas_buffered', \n",
+    "                         color='gi69')],\n",
+    "        interactive=False)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:py36]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-py36-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -639,7 +905,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,

From ba8c0241b74d75eee2a30589edb6f9227466dcaa Mon Sep 17 00:00:00 2001
From: Andy Eschbacher <andy.eschbacher@gmail.com>
Date: Fri, 19 May 2017 16:06:40 -0400
Subject: [PATCH 6/7] pep8 updates

---
 cartoframes/context.py | 23 ++++++++++++++---------
 1 file changed, 14 insertions(+), 9 deletions(-)

diff --git a/cartoframes/context.py b/cartoframes/context.py
index a20fe64ef..d9b6c5160 100644
--- a/cartoframes/context.py
+++ b/cartoframes/context.py
@@ -175,18 +175,22 @@ def write(self, df, table_name, temp_dir='/tmp', overwrite=False,
             None
         """
         if encode_geom:
+            # None if not a GeoDataFrame
             is_geopandas = getattr(df, '_geometry_column_name')
             if is_geopandas is None and geom_col is None:
                 geom_col = df.get('geometry')
                 if geom_col is None:
-                    raise KeyError('Geometries were requested to be encoded'
-                                   ' but no "geom_col" was not found in the' 
-                                   ' dataframe and no default geometry column was set.')
+                    raise KeyError('Geometries were requested to be encoded '
+                                   'but `{geom_col}` was not found in the '
+                                   'DataFrame and no default geometry column '
+                                   'was set.'.format(geom_col=geom_col))
             elif is_geopandas is not None and geom_col is not None:
-                warn('geometry column of the input dataframe does not '
-                     ' match the geometry column supplied! Using user-supplied column...'
-                     ' \n\tGeopandas geometry column: {}'
-                     ' \n\tSupplied geom_col: {}'.format(is_geopandas, geom_col))
+                warn('Geometry column of the input DataFrame does not '
+                     'match the geometry column supplied. Using user-supplied '
+                     'column...\n'
+                     '\tGeopandas geometry column: {}\n'
+                     '\tSupplied `geom_col`: {}'.format(is_geopandas,
+                                                        geom_col))
             elif is_geopandas is not None and geom_col is None:
                 geom_col = is_geopandas
             df['the_geom'] = df[geom_col].apply(_encode_geom)
@@ -215,7 +219,8 @@ def remove_tempfile():
             """removes temporary file"""
             os.remove(tempfile)
 
-        df.drop(geom_col,axis=1,errors='ignore').to_csv(tempfile)
+        # reset DataFrame before sending to CARTO
+        df.drop(geom_col, axis=1, errors='ignore').to_csv(tempfile)
 
         with open(tempfile, 'rb') as f:
             res = self._auth_send('api/v1/imports', 'POST',
@@ -769,7 +774,7 @@ def _debug_print(self, **kwargs):
 
 def _encode_geom(geom):
     """
-    Encode geometries into hex-encoded wkb 
+    Encode geometries into hex-encoded wkb
     """
     from shapely import wkb
     return ba.hexlify(wkb.dumps(geom)).decode()

From 9959766e5973a7fc5006eccc7dbfb6926fdc8c4f Mon Sep 17 00:00:00 2001
From: Andy Eschbacher <andy.eschbacher@gmail.com>
Date: Fri, 19 May 2017 16:14:45 -0400
Subject: [PATCH 7/7] small pep8 update

---
 cartoframes/context.py | 21 +++++++++++----------
 1 file changed, 11 insertions(+), 10 deletions(-)

diff --git a/cartoframes/context.py b/cartoframes/context.py
index d9b6c5160..c3ff23760 100644
--- a/cartoframes/context.py
+++ b/cartoframes/context.py
@@ -735,16 +735,17 @@ def _get_bounds(self, layers):
              if not layer.is_basemap])
 
         extent = self.query('''
-               SELECT
-                 ST_XMIN(ext) AS west,
-                 ST_YMIN(ext) AS south,
-                 ST_XMAX(ext) AS east,
-                 ST_YMAX(ext) AS north
-               FROM (
-                   SELECT st_extent(the_geom) AS ext
-                   FROM ({union_query}) AS wrap1
-               ) AS wrap2'''.format(union_query=union_query),
-                 decode_geom=False)
+                       SELECT
+                         ST_XMIN(ext) AS west,
+                         ST_YMIN(ext) AS south,
+                         ST_XMAX(ext) AS east,
+                         ST_YMAX(ext) AS north
+                       FROM (
+                           SELECT st_extent(the_geom) AS ext
+                           FROM ({union_query}) AS _wrap1
+                       ) AS _wrap2
+                            '''.format(union_query=union_query),
+                            decode_geom=False)
 
         west, south, east, north = extent.values[0]