# HG changeset patch
# User Puneeth Chaganti <punchagan@gmail.com>
# Date 1288084833 -19800
# Node ID 4c09238600e05c787f626868bcb9c16c53dfc28d
# Parent  e13e3452c599b2b92c8294fe9a061c595ac57868
Reviewed other types of plots.

diff -r e13e3452c599 -r 4c09238600e0 other-type-of-plots/script.rst
--- a/other-type-of-plots/script.rst	Tue Oct 26 11:13:32 2010 +0530
+++ b/other-type-of-plots/script.rst	Tue Oct 26 14:50:33 2010 +0530
@@ -22,6 +22,7 @@
    External Reviewer   :
    Checklist OK?       : <put date stamp here, if OK> [2010-10-05]
 
+.. #[Puneeth: Quickref missing]
 
 ===================
 Other type of plots
@@ -31,12 +32,21 @@
 
 Hello and welcome to the tutorial other type of plots.
 
+.. #[Puneeth: this sentence doesn't read well]
+
 {{{ show the outline slide }}}
 
+.. #[Puneeth: motivate looking at other plots. Why are we looking at
+.. them? Tell that we have only looked at one type of plot all the
+.. while, etc.]
+
 In this tutorial we will cover scatter plot, pie chart, bar chart and
-loglog plot. We will also see few other plots and also introduce you to
+log-log plot. We will also see few other plots and also introduce you to
 the matplotlib help.
 
+.. #[Puneeth: cover, see and introduce you. be consistent. does, the
+.. "We" include the viewer or not?]
+
 Let us start with scatter plot. 
 
 {{{ switch to the next slide, scatter plot }}}
@@ -47,8 +57,7 @@
 position on the vertical axis. This kind of plot is also called a
 scatter chart, scatter diagram and scatter graph.
 
-Before we proceed further get your IPython interpreter running with
-the ``-pylab`` option. Start your IPython interpreter as
+Before we proceed further, start your IPython interpreter
 ::
 
     ipython -pylab
@@ -59,9 +68,9 @@
 {{{ switch to the next slide having the problem statement of first
 exercise }}}
 
-Now, let us plot a scatter plot showing the percentage profit of company A
-from the year 2000-2010. The data for the same is available in the
-file ``company-a-data.txt``. 
+Now, let us plot a scatter plot showing the percentage profit of
+company A from the year 2000-2010. The data for the same is available
+in the file ``company-a-data.txt``.
 
 {{{ open the file company-a-data.txt and show the content }}}
 
@@ -78,6 +87,9 @@
     year,profit =
     loadtxt('/home/fossee/other-plot/company-a-data.txt',dtype=type(int()))
 
+.. #[Puneeth: make a remark about dtype, that has not been covered in
+.. the loadtxt tutorial.]
+
 {{{ switch to next slide, ``scatter`` function }}}
 
 Now in-order to generate the scatter graph we will use the function 
@@ -104,6 +116,9 @@
 
 Now let us move on to pie chart.
 
+.. #[Puneeth: instead of just saying that, say that let's plot a pie
+.. chart for the same data. continuity, will be good.]
+
 {{{ switch to the slide which says about pie chart }}}
 
 A pie chart or a circle graph is a circular chart divided into
@@ -116,6 +131,8 @@
 the same data from file ``company-a-data.txt``. So let us reuse the
 data we have loaded from the file previously.
 
+.. #[Puneeth, this part can be move above.]
+
 {{{ switch to next slide, ``pie()`` function }}}
 
 We can plot the pie chart using the function ``pie()``.
@@ -192,7 +209,7 @@
 Plot a `log-log` chart of y=5*x\ :sup:`3` for x from 1-20.
 
 Before we actually plot let us calculate the points needed for
-that. And it could be done as,
+that. 
 ::
 
     x = linspace(1,20,100)
diff -r e13e3452c599 -r 4c09238600e0 progress.org
--- a/progress.org	Tue Oct 26 11:13:32 2010 +0530
+++ b/progress.org	Tue Oct 26 14:50:33 2010 +0530
@@ -3,14 +3,14 @@
 | 1.2 LO: | getting started with =ipython=         |     2 | Punch    | Pending                               |           |
 | 1.3 LO: | using the =plot= command interactively |     2 | Amit     |                                       |           |
 | 1.4 LO: | embellishing a plot                    |     2 | Nishanth | Anoop (Done)                          |           |
-| 1.5 LO: | saving plots                           |     2 | Anoop    |                                       |           |
+| 1.5 LO: | saving plots                           |     2 | Anoop    | Punch (Done)                          |           |
 | 1.6 LO: | multiple plots                         |     3 | Madhu    | Nishanth (Done)                       |           |
 | 1.7 LO: | additional features of IPython         |     2 | Nishanth | Amit (Pending)                        |           |
 | 1.8 LO: | module level assessment                |     3 | Madhu    |                                       |           |
 |---------+----------------------------------------+-------+----------+---------------------------------------+-----------|
 | 2.2 LO: | loading data from files                |     3 | Punch    | Nishanth (Done)                       |           |
 | 2.3 LO: | plotting the data                      |     3 | Amit     |                                       |           |
-| 2.4 LO: | other types of plots                   |     3 | Anoop    | Pending                               |           |
+| 2.4 LO: | other types of plots                   |     3 | Anoop    | Punch (Done)                          |           |
 | 2.5 LO: | module level assessment                |     3 | Nishanth |                                       |           |
 |---------+----------------------------------------+-------+----------+---------------------------------------+-----------|
 | 3.1 LO: | getting started with lists             |     2 | Amit     |                                       |           |