Tatarian

SAT.csv

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+GPA,Math SAT Score
+3.4,705
+3.65,750
+2.9,610
+2.5,400
+3.07,570
+2.3,400
+2.75,550
+3.3,660
+3.4,680
+3,575
+3.7,770
+3.1,575
+3,600

exercise-9-q1

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+#!/usr/bin/env python2
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Nov  7 20:31:47 2018
+
+@author: atatarian
+"""
+
+import numpy
+import pandas
+from plotnine import *
+
+sat=pandas.read_csv("SAT.txt",sep="\t",header=0)
+sat.shape
+
+print (sat)
+
+a=ggplot(sat,aes(x="GPA",y="SAT-Score"))+theme_classic()+geom_point()+coord_cartesian()
+
+print a+xlab("GPA")+ylab("SAT-Score")+stat_smooth(method="lm")

exercise-9-q2

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+#!/usr/bin/env python2
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Nov  7 20:49:52 2018
+
+@author: atatarian
+"""
+
+import numpy
+import pandas
+from plotnine import *
+
+data=pandas.read_csv("data.txt",sep=",",header=0)
+data.shape
+
+
+#bar plot
+
+
+d=ggplot(data)+theme_classic()+xlab("region")+ylab("observations")
+
+print d+geom_bar(aes(x="factor(region)",y="observations"),stat="summary",fun_y=numpy.mean)
+
+#scatter plot
+
+a=ggplot(data,aes(x="region",y="observations"))+theme_classic()+geom_jitter()
+
+print a
+
+
+# The scatter plots tell different stories, most notably for the north and
+# south regions. While the means are similar, as shown by the bar plot, the
+# spreads, or distributions, of the data are different, as shown by the scatter
+# plot.

sat.txt

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+GPA	SAT-Score
+3.4	705
+3.65	750
+2.9	610
+2.5	400
+3.07	570
+2.3	400
+2.75	550
+3.3	660
+3.4	680
+3	575
+3.7	770
+3.1	575
+3	600