Merge branch 'master' into timestamp_fix

.travis.yml

@@ -0,0 +1,9 @@
+language: python
+python:
+    - '3.5'
+    - '3.6'
+install:
+    - pip install .
+    - pip install -r requirements.txt
+script:
+    - make test

Makefile

@@ -0,0 +1,10 @@
+init:
+	pip install -r requirements.txt
+
+docs:
+	cd docs && make html
+
+test:
+	nosetests -v test/
+
+.PHONY: init docs test

README.rst

@@ -1,6 +1,9 @@
 CARTOFrames
 ===========
 
+.. image:: https://travis-ci.org/CartoDB/cartoframes.svg?branch=master
+    :target: https://travis-ci.org/CartoDB/cartoframes
+
 A Python package for integrating `CARTO <https://carto.com/>`__ maps and services into data science workflows.
 
 Python data analysis workflows often rely on the de facto standards `pandas <http://pandas.pydata.org/>`__ and `Jupyter notebooks <http://jupyter.org/>`__. Integrating CARTO into this workflow saves data scientists time and energy by not having to export datasets as files or retain multiple copies of the data. Instead, CARTOFrames give the ability to communicate reproducible analysis while providing the ability to gain from CARTO's services like hosted, dynamic or static maps and `Data Observatory <https://carto.com/data-observatory/>`__ augmentation.
@@ -10,7 +13,7 @@ Complete documentation: https://cartodb.github.io/cartoframes/
 Install Instructions
 --------------------
 
-`cartoframes` relies on `pandas <http://pandas.pydata.org/>`__ and a development version of the CARTO Python SDK (on branch `1.0.0 <https://github.com/CartoDB/carto-python/tree/1.0.0>`__). To install `cartoframes` on your machine, do the following:
+`cartoframes` relies on `pandas <http://pandas.pydata.org/>`__ and the `CARTO Python SDK <https://github.com/CartoDB/carto-python/>`__). To install `cartoframes` on your machine, do the following:
 
 .. code:: bash
 
@@ -35,23 +38,29 @@ Get table from CARTO, make changes in pandas, sync updates with CARTO:
 .. code:: python
 
     import cartoframes
-    cc = cartoframes.CartoContext('https://eschbacher.carto.com/', APIKEY)
+    # `base_url`s are of the form `http://{username}.carto.com/` for most users
+    cc = cartoframes.CartoContext(base_url='https://eschbacher.carto.com/',
+                                  api_key=APIKEY)
+
+    # read a table from your CARTO account to a DataFrame
     df = cc.read('brooklyn_poverty_census_tracts')
+
     # do fancy pandas operations (add/drop columns, change values, etc.)
     df['poverty_per_pop'] = df['poverty_count'] / df['total_population']
 
-    # updates carto table with all changes from this session
+    # updates CARTO table with all changes from this session
     cc.write(df, 'brooklyn_poverty_census_tracts', overwrite=True)
 
 
-Associate an existing pandas DataFrame with CARTO.
+Write an existing pandas DataFrame to CARTO.
 
 .. code:: python
 
     import pandas as pd
     import cartoframes
     df = pd.read_csv('acadia_biodiversity.csv')
-    cc = cartoframes.CartoContext(BASEURL, APIKEY)
+    cc = cartoframes.CartoContext(base_url=BASEURL,
+                                  api_key=APIKEY)
     cc.write(df, 'acadia_biodiversity')
 
 
@@ -63,7 +72,8 @@ The following will embed a CARTO map in a Jupyter notebook, allowing for custom
 .. code:: python
 
     from cartoframes import Layer, BaseMap, styling
-    cc = cartoframes.CartoContext(BASEURL, APIKEY)
+    cc = cartoframes.CartoContext(base_url=BASEURL,
+                                  api_key=APIKEY)
     cc.map(layers=[BaseMap('light'),
                    Layer('acadia_biodiversity',
                          color={'column': 'simpson_index',
@@ -95,6 +105,5 @@ Interact with CARTO's `Data Observatory <https://carto.com/docs/carto-engine/dat
                          {'numer_id': 'us.census.acs.B19013001'},
                          {'numer_id': 'us.census.acs.B17001002',
                           'normalization': 'predenominated'},]
-    df = cc.do_augment('transactions', data_obs_measures)
+    df = cc.data_augment('transactions', data_obs_measures)
     df.head()
-