# HG changeset patch # User Puneeth Chaganti # Date 1255602109 -19800 # Node ID b4a83ea1a5176341f86c0766206a800d43fbf3c4 # Parent 44c2f614e32171c39ee56fc8477d1a1842feed1e# Parent a4bbc14342f9a6733e1429171a55240405476057 Merged branch with Mainline. diff -r 44c2f614e321 -r b4a83ea1a517 day1/session3.tex --- a/day1/session3.tex Thu Oct 15 15:50:55 2009 +0530 +++ b/day1/session3.tex Thu Oct 15 15:51:49 2009 +0530 @@ -258,7 +258,8 @@ \begin{itemize} \item Average total marks scored in each region \item Subject wise average score of each region - \item ??Subject wise average score for all regions combined?? + \item \alert{??Subject wise average score for all regions combined??} + \item Find the subject wise standard deviation of scores for each region \end{itemize} \end{frame} @@ -354,31 +355,63 @@ \begin{frame}[fragile] \frametitle{Dictionary - Building parsed data \ldots} - \small + \begin{lstlisting} +marks = [] +for field in fields[3:8]: + score_str = field.strip() + score = 0 if score_str == 'AA' + or score_str == 'AAA' + or score_str == '' + else int(score_str) + marks.append(score) + +data[fields[0]]['marks'].append(marks) + \end{lstlisting} +\end{frame} + +\begin{frame}[fragile] + \frametitle{Dictionary - Building parsed data \ldots} \begin{lstlisting} -data[fields[0]]['marks'] = append( - data[fields[0]]['marks'], - [int(fields[3]), int(fields[4]), - int(fields[5]), int(fields[6]), - int(fields[7]) - ]) +total = 0 if score_str == 'AA' + or score_str == 'AAA' + or score_str == '' + else int(fields[8]) +data[fields[0]]['total'].append(total) -data[fields[0]]['total'].append(fields[8]) +pfw_key = fields[9] + or fields[10] + or 'F' +data[fields[0]][pfw_key] += 1 + \end{lstlisting} +\end{frame} -pfw_key = fields[9] or fields[10] or fields[11] +\begin{frame}[fragile] + \frametitle{Dictionary - Building parsed data \ldots} + \begin{lstlisting} +pfw_key = fields[9] + or fields[10] + or 'F' data[fields[0]][pfw_key] += 1 \end{lstlisting} \end{frame} \begin{frame}[fragile] \frametitle{Calculations} + \small \begin{lstlisting} -all_sub_avg = array([]) -for k, v in data: +for k in data: + data[k]['marks'] = array(data[k]['marks']) + data[k]['total'] = array(data[k]['total']) + data[k]['avg'] = average( data[k]['total']) - data[k]['sub_avg'] = average( - data[k]['marks'], axis=1) + marks = data[k]['marks'] + sub_avg = average(marks, axis=1) + sub_std = sqrt(sum(square( + sub_avg[:,newaxis] - marks), axis=0) / + len(marks)) + data[k]['sub_avg'] = sub_avg + data[k]['sub_std'] = sub_std \end{lstlisting} \end{frame} diff -r 44c2f614e321 -r b4a83ea1a517 day1/sslc1.txt --- a/day1/sslc1.txt Thu Oct 15 15:50:55 2009 +0530 +++ b/day1/sslc1.txt Thu Oct 15 15:51:49 2009 +0530 @@ -131341,7 +131341,7 @@ 15;144497;KARTHIKEYAN N;090;079; 88; 86; 81;424;P;; 15;144498;PRABHAKARAN C;091;087; 94; 95; 82;449;P;; 15;144499;MANIKANDAN J;088;073; 93; 90; 87;431;P;; -15;144500;VIJAYA KUMAR ;G;086;073; 92; 78; 74;403;P;; +15;144500;VIJAYA KUMAR G;086;073; 92; 78; 74;403;P;; 15;144501;SARAVANAN S;077;062; 73; 65; 67;344;P;; 15;144502;GOWTHAMA PANDIAN M;072;064; 64; 66; 69;335;P;; 15;144503;BABU R;088;076; 95; 75; 82;416;P;;