Readme.rst improvements

1 files changed, 2 insertions, 42 deletions

diff --git a/README.rst b/README.rst
index f974248..5afe600 100644
--- a/README.rst
+++ b/README.rst
@@ -22,20 +22,13 @@ Output formats supported:
 - TSV (Sets)
 - CSV (Sets)
 
-Import formats supported:
-
-- JSON (Sets + Books)
-- YAML (Sets + Books)
-- TSV (Sets)
-- CSV (Sets)
-
-Note that tablib *purposefully* excludes XML support. It always will.
+Note that tablib *purposefully* excludes XML support. It always will. (Note: This is a joke. Pull requests are welcome.)
 
 Overview
 --------
 
 `tablib.Dataset()`
-	A Dataset is a table of tabular data. It may or may not have a header row. They can be build and maniuplated as raw Python datatypes (Lists of tuples|dictonaries). Datasets can be imported from JSON, YAML, and CSV; they can be exported to Excel (XLS), JSON, YAML, and CSV.
+	A Dataset is a table of tabular data. It may or may not have a header row. They can be build and manipulated as raw Python datatypes (Lists of tuples|dictionaries). Datasets can be imported from JSON, YAML, and CSV; they can be exported to Excel (XLS), JSON, YAML, and CSV.
 	
 `tablib.Databook()`
 	A Databook is a set of Datasets. The most common form of a Databook is an Excel file with multiple spreadsheets. Databooks can be imported from JSON and YAML; they can be exported to Excel (XLS), JSON, and YAML.
@@ -128,39 +121,6 @@ EXCEL!
 
 It's that easy.
 
-Imports!
---------
-
-JSON
-++++
-
-::
-
-	>>> data.json = '[{"last_name": "Adams","age": 90,"first_name": "John"}]'
-	>>> print data[0]
-	('John', 'Adams', 90)
-
-
-YAML
-++++
-::
-
-	>>> data.yaml = '- {age: 90, first_name: John, last_name: Adams}'
-	>>> print data[0]
-	('John', 'Adams', 90)
-
-CSV
-+++
-::
-
-	>>> data.csv = 'age, first_name, last_name\n90, John, Adams'
-	>>> print data[0]
-	('John', 'Adams', 90)
-	
-	>>> print data.yaml
-	- {age: 90, first_name: John, last_name: Adams}
-	
-
 
 Installation
 ------------