Merged heads.
--- a/advanced-features-functions/script.rst Thu Nov 11 03:00:19 2010 +0530
+++ b/advanced-features-functions/script.rst Thu Nov 11 03:00:35 2010 +0530
@@ -19,6 +19,7 @@
.. Author : Puneeth
Internal Reviewer : Anoop Jacob Thomas<anoop@fossee.in>
External Reviewer :
+ Language Reviewer : Bhanukiran
Checklist OK? : <put date stamp here, if OK> [2010-10-05]
Script
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/getting-started-with-functions/questions.rst Thu Nov 11 03:00:35 2010 +0530
@@ -0,0 +1,112 @@
+Objective Questions
+-------------------
+
+.. A mininum of 8 questions here (along with answers)
+
+1. What will the function do?
+ ::
+
+ def what(x)
+ return x*x
+
+ 1. Returns the square of x
+ #. Returns x
+ #. Function doesn't have docstring
+ #. Error
+
+ Answer: Error
+
+2. What will the function do?
+ ::
+
+ def what(x):
+ return x*x
+
+ 1. Returns the square of x
+ #. Returns x
+ #. Function doesn't have docstring
+ #. Error
+
+ Answer: Returns the square of x
+
+3. How many arguments can be passed to a python function?
+
+ 1. None
+ #. One
+ #. Two
+ #. Any
+
+ Answer: Any
+
+4. How many values can a python function return?
+
+ 1. None
+ #. One
+ #. Two
+ #. Any
+
+ Answer: Any
+
+5. A python function can return only one value
+
+ 1. True
+ #. False
+
+ Answer: False
+
+6. What will be the output of the following code?
+ ::
+
+ def avg(a, b):
+ return (a + b) / 2
+
+ print avg(10,11)
+
+ 1. 10
+ #. 10.5
+ #. 11
+ #. 9.5
+
+ Answer: 10
+
+7. What will be the output of the following code?
+ ::
+
+ def avg(a, b):
+ return (a + b) / 2
+
+ print avg(10,11.0)
+
+ 1. 10
+ #. 10.5
+ #. 11
+ #. 9.5
+
+ Answer: 10.5
+
+8. What will be the output of the following code?
+ ::
+
+ def what(a, b):
+ return a + b / 2
+
+ print avg(10,11)
+
+ 1. 10
+ #. 10.5
+ #. 16
+ #. 15
+
+ Answer: 15
+
+
+Larger Questions
+----------------
+
+.. A minimum of 2 questions here (along with answers)
+
+1. Write a python function to check the numbers a, b c is a Pythagorean
+ triplet or not.
+
+2. Write a python function which will accept an n digit number and
+ which returns the reverse of the number.
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/getting-started-with-functions/quickref.tex Thu Nov 11 03:00:35 2010 +0530
@@ -0,0 +1,4 @@
+Defining a function:\\
+{\ex \lstinline| def name([arguments]):|}
+{\ex \lstinline| code|}
+{\ex \lstinline| [return values]|}
--- a/loops/questions.rst Thu Nov 11 03:00:19 2010 +0530
+++ b/loops/questions.rst Thu Nov 11 03:00:35 2010 +0530
@@ -16,7 +16,7 @@
#. all of the above
.. I was not sure of how to frame this question. Can someone fix it?
-
+..#[bhanu: it works for every `sequence` or an iterator for that matter right?]
Answer: all of the above
#. ``x = range(20)``. What is x?
@@ -85,7 +85,7 @@
Answer: Nothing is printed
-.. #[[Anoop: I think more questions on while loop has to be added as
+.. #[[Anoop: I think more questions on while loop have to be added as
for loop was already covered in another LO, these questions can be
kept, but it will good if we add few more on while loop]]
--- a/loops/script.rst Thu Nov 11 03:00:19 2010 +0530
+++ b/loops/script.rst Thu Nov 11 03:00:35 2010 +0530
@@ -19,6 +19,7 @@
.. Author : Puneeth
Internal Reviewer : Anoop Jacob Thomas<anoop@fossee.in>
External Reviewer :
+ Langauge Reviewer : Bhanukiran
Checklist OK? : <put date stamp here, if OK> [2010-10-05]
Script
--- a/manipulating-strings/script.rst Thu Nov 11 03:00:19 2010 +0530
+++ b/manipulating-strings/script.rst Thu Nov 11 03:00:35 2010 +0530
@@ -19,7 +19,8 @@
.. Author : Puneeth
Internal Reviewer : Amit
External Reviewer :
- Checklist OK? : <put date stamp here, if OK> [2010-10-05]
+ Language Reviewer : Bhanukiran
+ Checklist OK? : <08-11-2010, Anand, OK> [2010-10-05]
Script
------
@@ -90,8 +91,8 @@
s[1:-1]
-gives the a substring of s, without the first and the last
-characters.
+gives the substring of s, without the first and the last
+characters of s.
::
--- a/progress.org Thu Nov 11 03:00:19 2010 +0530
+++ b/progress.org Thu Nov 11 03:00:35 2010 +0530
@@ -46,7 +46,7 @@
| 7.5 LO: | sets | 2 | Nishanth | Punch (Done) | |
| 7.6 LO: | Assessment | 3 | Amit | | |
|---------+----------------------------------------+-------+----------+-----------------+-----------|
-| 8.1 LO: | getting started with functions | 3 | Anoop | | |
+| 8.1 LO: | getting started with functions | 3 | Anoop | Pending | |
| 8.2 LO: | advanced features of functions | 3 | Punch | Anoop (Done) | |
| 8.3 LO: | using python modules | 3 | Anoop | Punch (Done) | |
| 8.4 LO: | writing python scripts | 2 | Nishanth | | |
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/statistics/football.txt Thu Nov 11 03:00:35 2010 +0530
@@ -0,0 +1,8 @@
+Cristiano Ronaldo, 86 ,67
+latan Ibrahimovic, 34 , 65
+Lionel Messi , 45 , 41
+Samuel Eto’o , 23 , 24
+Kaka , 43 , 45
+Frank Lampard , 65 ,34
+
+
--- a/statistics/script.rst Thu Nov 11 03:00:19 2010 +0530
+++ b/statistics/script.rst Thu Nov 11 03:00:35 2010 +0530
@@ -13,6 +13,8 @@
.. Getting started with IPython
.. Loading Data from files
.. Getting started with Lists
+.. Accessing Pieces of Arrays
+
.. Author : Amit Sethi
Internal Reviewer : Puneeth
@@ -28,8 +30,12 @@
{{{ Show the slide containing the outline slide }}}
In this tutorial, we shall learn
- * Doing simple statistical operations in Python
- * Applying these to real world problems
+ * Doing statistical operations in Python
+ * Summing set of numbers
+ * Finding there mean
+ * Finding there Median
+ * Finding there Standard Deviation
+
.. #[punch: since loadtxt is anyway a pre-req, I would recommend you
@@ -45,88 +51,13 @@
.. smaller data-set or something. Using lists doesn't seem natural.]
-We will first start with the most necessary statistical operation i.e
-finding mean.
-
-We have a list of ages of a random group of people ::
-
- age_list = [4,45,23,34,34,38,65,42,32,7]
-
-One way of getting the mean could be getting sum of all the ages and
-dividing by the number of people in the group. ::
-
- sum_age_list = sum(age_list)
-
-sum function gives us the sum of the elements. Note that the
-``sum_age_list`` variable is an integer and the number of people or
-length of the list is also an integer. We will need to convert one of
-them to a float before carrying out the division. ::
-
- mean_using_sum = float(sum_age_list)/len(age_list)
-
-This obviously gives the mean age but there is a simpler way to do
-this in Python - using the mean function::
-
- mean(age_list)
-
-Mean can be used in more ways in case of 2 dimensional lists. Take a
-two dimensional list ::
-
- two_dimension=[[1,5,6,8],[1,3,4,5]]
-
-The mean function by default gives the mean of the flattened sequence.
-A Flattened sequence means a list obtained by concatenating all the
-smaller lists into a large long list. In this case, the list obtained
-by writing the two lists one after the other. ::
-
- mean(two_dimension)
- flattened_seq=[1,5,6,8,1,3,4,5]
- mean(flattened_seq)
-
-As you can see both the results are same. ``mean`` function can also
-give us the mean of each column, or the mean of corresponding elements
-in the smaller lists. ::
-
- mean(two_dimension, 0)
- array([ 1. , 4. , 5. , 6.5])
-
-we pass an extra argument 0 in that case.
-
-If we use an argument 1, we obtain the mean along the rows. ::
-
- mean(two_dimension, 1)
- array([ 5. , 3.25])
-
-We can see more option of mean using ::
-
- mean?
-
-Similarly we can calculate median and stanard deviation of a list
-using the functions median and std::
-
- median(age_list)
- std(age_list)
-
-Median and std can also be calculated for two dimensional arrays along
-columns and rows just like mean.
-
-For example ::
-
- median(two_dimension, 0)
- std(two_dimension, 1)
-
-This gives us the median along the colums and standard devition along
-the rows.
-
-Now lets apply this to a real world example
-
-We will a data file that is at the a path ``/home/fossee/sslc2.txt``.
-It contains record of students and their performance in one of the
-State Secondary Board Examination. It has 180, 000 lines of record. We
-are going to read it and process this data. We can see the content of
-file by double clicking on it. It might take some time to open since
-it is quite a large file. Please don't edit the data. This file has
-a particular structure.
+For this tutorial We will use data file that is at the a path
+``/home/fossee/sslc2.txt``. It contains record of students and their
+performance in one of the State Secondary Board Examination. It has
+180,000 lines of record. We are going to read it and process this
+data. We can see the content of file by double clicking on it. It
+might take some time to open since it is quite a large file. Please
+don't edit the data. This file has a particular structure.
We can do ::
@@ -134,6 +65,9 @@
to check the contents of the file.
+
+{{{ Show the data structure on a slide }}}
+
Each line in the file is a set of 11 fields separated
by semi-colons Consider a sample line from this file.
A;015163;JOSEPH RAJ S;083;042;47;00;72;244;;;
@@ -147,45 +81,97 @@
* Total marks 244
-Now lets try and find the mean of English marks of all students.
-
-For this we do. ::
+Lets try and load this data as an array and then run various function on
+it.
- L=loadtxt('/home/fossee/sslc2.txt',usecols=(3,),delimiter=';')
+To get the data as an array we do. ::
+
+ L=loadtxt('/home/amit/sslc2.txt',usecols=(3,4,5,6,7,),delimiter=';')
L
- mean(L)
+
loadtxt function loads data from an external file.Delimiter specifies
-the kind of character are the fields of data seperated by.
-usecols specifies the columns to be used so (3,). The 'comma' is added
-because usecols is a sequence.
+the kind of character are the fields of data seperated by. usecols
+specifies the columns to be used so (3,4,5,6,7) loads those
+colums. The 'comma' is added because usecols is a sequence.
-To get the median marks. ::
+As we can see L is an array. We can get the shape of this array using::
- median(L)
+ L.shape
+ (185667, 5)
+
+Lets start applying statistics operations on these. We will start with
+the most basic, summing. How do you find the sum of marks of all
+subjects for the first student.
+
+As we know from our knowledge of accessing pieces of arrays. To acess
+the first row we will do ::
-Standard deviation. ::
-
- std(L)
+ L[0,:]
+
+Now to sum this we can say ::
+ totalmarks=sum(L[0,:])
+ totalmarks
-Now lets try and and get the mean for all the subjects ::
+To get the mean we can do ::
+
+ totalmarks/len(L[0,:])
+
+or simply ::
+
+ mean(L[0,:])
- L=loadtxt('/home/fossee/sslc2.txt',usecols=(3,4,5,6,7),delimiter=';')
- mean(L,0)
- array([ 73.55452504, 53.79828941, 62.83342759, 50.69806158, 63.17056881])
+But we have such a large data set calculating one by one the mean of
+each student is impossible. Is there a way to reduce the work.
+
+For this we will look into the documentation of mean by doing::
-As we can see from the result mean(L,0). The resultant sequence
-is the mean marks of all students that gave the exam for the five subjects.
+ mean?
-and ::
-
+As we know L is a two dimensional array. We can calculate the mean
+across each of the axis of the array. The axis of rows is referred by
+number 0 and columns by 1. So to calculate mean accross all colums we
+will pass extra parameter 1 for the axis.::
+
mean(L,1)
-
-is the average accumalative marks of individual students. Clearly, mean(L,0)
-was a row wise calcultaion while mean(L,1) was a column wise calculation.
+L here is the two dimensional array.
+
+Similarly to calculate average marks scored by all the students for each
+subject can be calculated using ::
+
+ mean(L,0)
+
+Next lets now calculate the median of English marks for the all the students
+We can access English marks of all students using ::
+
+ L[:,0]
+
+To get the median we will do ::
+
+ median(L[:,0])
+For all the subjects we can use the same syntax as mean and calculate
+median across all rows using ::
+
+ median(L,0)
+
+
+Similarly to calculate standard deviation for English we can do::
+
+ std(L[:,0])
+
+and for all rows::
+
+ std(L,0)
+
+Following is an exercise that you must do.
+
+%% %% In the given file football.txt at path /home/fossee/football.txt , one column is player name,second is goals at home and third goals away.
+ 1.Find the total goals for each player
+ 2.Mean home and away goals
+ 3.Standard deviation of home and away goals
{{{ Show summary slide }}}
--- a/statistics/slides.org Thu Nov 11 03:00:19 2010 +0530
+++ b/statistics/slides.org Thu Nov 11 03:00:35 2010 +0530
@@ -2,32 +2,73 @@
#+LaTeX_CLASS_OPTIONS: [presentation]
#+BEAMER_FRAME_LEVEL: 1
-#+BEAMER_HEADER_EXTRA: \usetheme{Warsaw}\useoutertheme{infolines}\usecolortheme{default}\setbeamercovered{transparent}
+#+BEAMER_HEADER_EXTRA: \usetheme{Warsaw}\usecolortheme{default}\useoutertheme{infolines}\setbeamercovered{transparent}
#+COLUMNS: %45ITEM %10BEAMER_env(Env) %10BEAMER_envargs(Env Args) %4BEAMER_col(Col) %8BEAMER_extra(Extra)
#+PROPERTY: BEAMER_col_ALL 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 :ETC
-#+OPTIONS: H:5 num:t toc:nil \n:nil @:t ::t |:t ^:t -:t f:t *:t <:t
+
+#+LaTeX_CLASS: beamer
+#+LaTeX_CLASS_OPTIONS: [presentation]
+
+#+LaTeX_HEADER: \usepackage[english]{babel} \usepackage{ae,aecompl}
+#+LaTeX_HEADER: \usepackage{mathpazo,courier,euler} \usepackage[scaled=.95]{helvet}
+
+#+LaTeX_HEADER: \usepackage{listings}
+
+#+LaTeX_HEADER:\lstset{language=Python, basicstyle=\ttfamily\bfseries,
+#+LaTeX_HEADER: commentstyle=\color{red}\itshape, stringstyle=\color{darkgreen},
+#+LaTeX_HEADER: showstringspaces=false, keywordstyle=\color{blue}\bfseries}
#+TITLE: Statistics
#+AUTHOR: FOSSEE
-#+DATE: 2010-09-14 Tue
+#+DATE
#+EMAIL: info@fossee.in
-# \author[FOSSEE] {FOSSEE}
+#+DESCRIPTION:
+#+KEYWORDS:
+#+LANGUAGE: en
+#+OPTIONS: H:3 num:nil toc:nil \n:nil @:t ::t |:t ^:t -:t f:t *:t <:t
+#+OPTIONS: TeX:t LaTeX:nil skip:nil d:nil todo:nil pri:nil tags:not-in-toc
+
+
+* Outline
+ - Doing statistical operations in Python
+ - Summing set of numbers
+ - Finding there mean
+ - Finding there Median
+ - Finding there Standard Deviation
+
+* Data set
+ - A;015163;JOSEPH RAJ S;083;042;47;00;72;244;;;
-# \institute[IIT Bombay] {Department of Aerospace Engineering\\IIT Bombay}
-# \date{}
+ The following are the fields in any given line.
+ - Region Code which is 'A'
+ - Roll Number 015163
+ - Name JOSEPH RAJ S
+ - Marks of 5 subjects: -- English 083 --
+ Hindi 042 -- Maths 47 --
+ Science 35 -- Social 72
+ - Total marks 244
-* Tutorial Plan
-** Doing simple statistical operations in Python
-** Using loadtxt to solve statistics problem
+* Question
+ - In the given file football.txt at path /home/fossee/football.txt ,
+ one column is player name,second is goals at home
+ and third goals away.
+ - Find the total goals for each player
+ - Mean home and away goals
+ - Standard deviation of home and away goals
+
+* Solution
+#+begin_src python
+ L=loadtxt('/home/amit/football.txt',usecols=(1,2),
+ delimiter=',')
+ sum(L,1)
+ mean(L,0)
+ std(L,0)
+#+end_src python
* Summary
-** seq=[1,5,6,8,1,3,4,5]
-** sum(seq)
-** mean(seq)
-** median(seq)
-** std(seq)
+ - sum
+ - mean
+ - median
+ - std
-* Summary
-
-** loadtxt
--- a/statistics/slides.tex Thu Nov 11 03:00:19 2010 +0530
+++ b/statistics/slides.tex Thu Nov 11 03:00:35 2010 +0530
@@ -1,106 +1,122 @@
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-%Tutorial slides on Python.
-%
-% Author: FOSSEE
-% Copyright (c) 2009, FOSSEE, IIT Bombay
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-\documentclass[14pt,compress]{beamer}
-%\documentclass[draft]{beamer}
-%\documentclass[compress,handout]{beamer}
-%\usepackage{pgfpages}
-%\pgfpagesuselayout{2 on 1}[a4paper,border shrink=5mm]
-
-% Modified from: generic-ornate-15min-45min.de.tex
-\mode<presentation>
-{
- \usetheme{Warsaw}
- \useoutertheme{infolines}
- \setbeamercovered{transparent}
-}
-
-\usepackage[english]{babel}
+% Created 2010-11-11 Thu 01:35
+\documentclass[presentation]{beamer}
\usepackage[latin1]{inputenc}
-%\usepackage{times}
\usepackage[T1]{fontenc}
-
-\usepackage{ae,aecompl}
-\usepackage{mathpazo,courier,euler}
-\usepackage[scaled=.95]{helvet}
-
-\definecolor{darkgreen}{rgb}{0,0.5,0}
-
+\usepackage{fixltx2e}
+\usepackage{graphicx}
+\usepackage{longtable}
+\usepackage{float}
+\usepackage{wrapfig}
+\usepackage{soul}
+\usepackage{t1enc}
+\usepackage{textcomp}
+\usepackage{marvosym}
+\usepackage{wasysym}
+\usepackage{latexsym}
+\usepackage{amssymb}
+\usepackage{hyperref}
+\tolerance=1000
+\usepackage[english]{babel} \usepackage{ae,aecompl}
+\usepackage{mathpazo,courier,euler} \usepackage[scaled=.95]{helvet}
\usepackage{listings}
-\lstset{language=Python,
- basicstyle=\ttfamily\bfseries,
- commentstyle=\color{red}\itshape,
- stringstyle=\color{darkgreen},
- showstringspaces=false,
- keywordstyle=\color{blue}\bfseries}
+\lstset{language=Python, basicstyle=\ttfamily\bfseries,
+commentstyle=\color{red}\itshape, stringstyle=\color{darkgreen},
+showstringspaces=false, keywordstyle=\color{blue}\bfseries}
+\providecommand{\alert}[1]{\textbf{#1}}
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% Macros
-\setbeamercolor{emphbar}{bg=blue!20, fg=black}
-\newcommand{\emphbar}[1]
-{\begin{beamercolorbox}[rounded=true]{emphbar}
- {#1}
- \end{beamercolorbox}
-}
-\newcounter{time}
-\setcounter{time}{0}
-\newcommand{\inctime}[1]{\addtocounter{time}{#1}{\tiny \thetime\ m}}
+\title{Statistics}
+\author{FOSSEE}
+\date{11 November 2010}
-\newcommand{\typ}[1]{\lstinline{#1}}
-
-\newcommand{\kwrd}[1]{ \texttt{\textbf{\color{blue}{#1}}} }
-
-% Title page
-\title{Your Title Here}
-
-\author[FOSSEE] {FOSSEE}
-
-\institute[IIT Bombay] {Department of Aerospace Engineering\\IIT Bombay}
-\date{}
-
-% DOCUMENT STARTS
+\usetheme{Warsaw}\usecolortheme{default}\useoutertheme{infolines}\setbeamercovered{transparent}
\begin{document}
-\begin{frame}
- \maketitle
-\end{frame}
+\maketitle
-\begin{frame}[fragile]
- \frametitle{Outline}
- \begin{itemize}
- \item
- \end{itemize}
-\end{frame}
+
+
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-%% All other slides here. %%
-%% The same slides will be used in a classroom setting. %%
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+
-\begin{frame}[fragile]
- \frametitle{Summary}
- \begin{itemize}
- \item
- \end{itemize}
-\end{frame}
+
+
\begin{frame}
- \frametitle{Thank you!}
- \begin{block}{}
- \begin{center}
- This spoken tutorial has been produced by the
- \textcolor{blue}{FOSSEE} team, which is funded by the
- \end{center}
- \begin{center}
- \textcolor{blue}{National Mission on Education through \\
- Information \& Communication Technology \\
- MHRD, Govt. of India}.
- \end{center}
- \end{block}
+\frametitle{Outline}
+\label{sec-1}
+
+\begin{itemize}
+\item Doing statistical operations in Python
+
+\begin{itemize}
+\item Summing set of numbers
+\item Finding there mean
+\item Finding there Median
+\item Finding there Standard Deviation
+\end{itemize}
+
+\end{itemize}
+\end{frame}
+\begin{frame}
+\frametitle{Data set}
+\label{sec-2}
+
+\begin{itemize}
+\item A;015163;JOSEPH RAJ S;083;042;47;00;72;244;;;
+\end{itemize}
+
+
+ The following are the fields in any given line.
+\begin{itemize}
+\item Region Code which is `A'
+\item Roll Number 015163
+\item Name JOSEPH RAJ S
+\item Marks of 5 subjects: -- English 083 --
+ Hindi 042 -- Maths 47 --
+ Science 35 -- Social 72
+\item Total marks 244
+\end{itemize}
+\end{frame}
+\begin{frame}
+\frametitle{Question}
+\label{sec-3}
+
+\begin{itemize}
+\item In the given file football.txt at path /home/fossee/football.txt ,
+ one column is player name,second is goals at home
+ and third goals away.
+
+\begin{itemize}
+\item Find the total goals for each player
+\item Mean home and away goals
+\item Standard deviation of home and away goals
+\end{itemize}
+
+\end{itemize}
+\end{frame}
+\begin{frame}[fragile]
+\frametitle{Solution}
+\label{sec-4}
+
+\begin{verbatim}
+L=loadtxt('/home/amit/football.txt',usecols=(1,2),
+ delimiter=',')
+sum(L,1)
+mean(L,0)
+std(L,0)
+\end{verbatim}
+\end{frame}
+\begin{frame}
+\frametitle{Summary}
+\label{sec-5}
+
+\begin{itemize}
+\item sum
+\item mean
+\item median
+\item std
+\end{itemize}
\end{frame}
\end{document}