7 files changed, 91 insertions, 25 deletions
diff --git a/doc/source/user/absolute_beginners.rst b/doc/source/user/absolute_beginners.rst
index 021f49bcb..ad2cd2d80 100644
--- a/doc/source/user/absolute_beginners.rst
+++ b/doc/source/user/absolute_beginners.rst
@@ -1576,6 +1576,10 @@ If you created this array "a" ::
   ...               [ 0.76989341,  0.81299683, -0.95068423, 0.11769564],
   ...               [ 0.20484034,  0.34784527,  1.96979195, 0.51992837]])
 
+.. for doctests
+   The continuous integration truncates dataframe display without this setting.
+   >>> pd.set_option('max_columns', 10)
+
 You could create a Pandas dataframe ::
 
   >>> df = pd.DataFrame(a)
diff --git a/doc/source/user/explanations_index.rst b/doc/source/user/explanations_index.rst
new file mode 100644
index 000000000..f515e36b1
--- /dev/null
+++ b/doc/source/user/explanations_index.rst
@@ -0,0 +1,14 @@
+.. _explanations:
+
+################
+Explanations
+################
+
+These documents are intended to explain in detail the concepts and techniques
+used in NumPy. For the reference documentation of the functions and classes
+contained in the package, see the :ref:`API reference <reference>`.
+
+.. toctree::
+   :maxdepth: 1
+
+   basics.broadcasting
diff --git a/doc/source/user/howtos_index.rst b/doc/source/user/howtos_index.rst
new file mode 100644
index 000000000..c052286b9
--- /dev/null
+++ b/doc/source/user/howtos_index.rst
@@ -0,0 +1,14 @@
+.. _howtos:
+
+################
+NumPy How Tos
+################
+
+These documents are intended as recipes to common tasks using NumPy. For
+detailed reference documentation of the functions and classes contained in
+the package, see the :ref:`API reference <reference>`.
+
+.. toctree::
+   :maxdepth: 1
+
+   ionumpy
diff --git a/doc/source/user/index.rst b/doc/source/user/index.rst
deleted file mode 100644
index d506a5a98..000000000
--- a/doc/source/user/index.rst
+++ /dev/null
@@ -1,23 +0,0 @@
-.. _user:
-
-################
-NumPy User Guide
-################
-
-This guide is intended as an introductory overview of NumPy and
-explains how to install and make use of the most important features of
-NumPy. For detailed reference documentation of the functions and
-classes contained in the package, see the :ref:`reference`.
-
-.. toctree::
-   :maxdepth: 1
-
-   setting-up
-   quickstart
-   absolute_beginners
-   basics
-   misc
-   numpy-for-matlab-users
-   tutorial-svd
-   building
-   c-info
diff --git a/doc/source/user/ionumpy.rst b/doc/source/user/ionumpy.rst
new file mode 100644
index 000000000..a31720322
--- /dev/null
+++ b/doc/source/user/ionumpy.rst
@@ -0,0 +1,20 @@
+================================================
+How to read and write data using NumPy
+================================================
+
+.. currentmodule:: numpy
+
+.. testsetup::
+
+   import numpy as np
+   np.random.seed(1)
+
+**Objectives**
+
+- Writing NumPy arrays to files
+- Reading NumPy arrays from files
+- Dealing with encoding and dtype issues
+
+**Content**
+
+To be completed.
diff --git a/doc/source/user/quickstart.rst b/doc/source/user/quickstart.rst
index 05a247f8a..bea07debf 100644
--- a/doc/source/user/quickstart.rst
+++ b/doc/source/user/quickstart.rst
@@ -21,6 +21,24 @@ If you wish to work the examples in this tutorial, you must also have
 some software installed on your computer. Please see
 https://scipy.org/install.html for instructions.
 
+**Learner profile**
+
+This tutorial is intended as a quick overview of 
+algebra and arrays in NumPy and want to understand how n-dimensional
+(:math:`n>=2`) arrays are represented and can be manipulated. In particular, if
+you don't know how to apply common functions to n-dimensional arrays (without
+using for-loops), or if you want to understand axis and shape properties for
+n-dimensional arrays, this tutorial might be of help.
+
+**Learning Objectives**
+
+After this tutorial, you should be able to:
+
+- Understand the difference between one-, two- and n-dimensional arrays in
+  NumPy;
+- Understand how to apply some linear algebra operations to n-dimensional
+  arrays without using for-loops;
+- Understand axis and shape properties for n-dimensional arrays.
 
 .. _quickstart.the-basics:
 
@@ -129,8 +147,8 @@ rather than providing a single sequence as an argument.
 
     >>> a = np.array(1,2,3,4)    # WRONG
     Traceback (most recent call last):
-    ...
-    ValueError: only 2 non-keyword arguments accepted
+      ...
+    TypeError: array() takes from 1 to 2 positional arguments but 4 were given
     >>> a = np.array([1,2,3,4])  # RIGHT
 
 ``array`` transforms sequences of sequences into two-dimensional arrays,
diff --git a/doc/source/user/tutorials_index.rst b/doc/source/user/tutorials_index.rst
new file mode 100644
index 000000000..c5e859fad
--- /dev/null
+++ b/doc/source/user/tutorials_index.rst
@@ -0,0 +1,19 @@
+.. _tutorials:
+
+################
+NumPy Tutorials
+################
+
+These documents are intended as an introductory overview of NumPy and its 
+features. For detailed reference documentation of the functions and
+classes contained in the package, see the :ref:`API reference <reference>`.
+
+.. toctree::
+   :maxdepth: 1
+
+   basics
+   misc
+   numpy-for-matlab-users
+   tutorial-svd
+   building
+   c-info