diff -r cc2424a28d24 -r 63cf968627a3 day1/sslc1.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/day1/sslc1.py	Wed Oct 28 20:33:27 2009 +0530
@@ -0,0 +1,50 @@
+from pylab import *
+from scipy import *
+from scipy import stats
+
+scores = [[], [], [], [], []]
+ninety_percents = [{}, {}, {}, {}, {}]
+
+for record in open('sslc1.txt'):
+    record = record.strip()
+    fields = record.split(';')
+
+    region_code = fields[0].strip()
+   
+    for i, field in enumerate(fields[3:8]):
+        if region_code not in ninety_percents[i]:
+            ninety_percents[i][region_code] = 0
+        score_str = field.strip()
+        score = 0 if score_str == 'AA' else int(score_str)
+        scores[i].append(score)
+        if score > 90:
+            ninety_percents[i][region_code] += 1
+
+subj_total = []
+for subject in ninety_percents:
+    subj_total.append(sum(subject.values()))
+
+
+figure(1)
+pie(ninety_percents[3].values(), labels=ninety_percents[3].keys())
+title('Students scoring 90% and above in science by region')
+savefig('/tmp/science.png')
+
+figure(2)
+pie(subj_total, labels=['English', 'Hindi', 'Maths', 'Science', 'Social'])
+title('Students scoring more than 90% by subject(All regions combined).')
+savefig('/tmp/all_regions.png')
+
+math_scores = array(scores[2])
+# Mean score in Maths(All regions combined)
+print "Mean: ", mean(math_scores)
+
+# Median score in Maths(All regions combined)
+print "Median: ", median(math_scores)
+
+# Mode score in Maths(All regions combined)
+print "Mode: ", stats.mode(math_scores)
+
+# Standard deviation of scores in Maths(All regions combined)
+print "Standard Deviation: ", std(math_scores)
+