North,6.47,4.03

Yorkshire,6.13,3.76

Northeast,6.19,3.77

East Midlands,4.89,3.34

West Midlands,5.63,3.47

East Anglia,4.52,2.92

Southeast,5.89,3.20

Southwest,4.79,2.71

Wales,5.27,3.53

Scotland,6.08,4.51

global data

data=[i.split(',') for i in data.splitlines()]

column_names = data[0]

data_rows = data[1:]

df = pd.DataFrame(data_rows, columns = column_names)

df["Alcohol"]=df["Alcohol"].astype(float)

df["Tobacco"]=df["Tobacco"].astype(float)

print "Alcohol dataset stats:"

print "Mean = ",df['Alcohol'].mean()

print "Median =",df['Alcohol'].median()

print "Mode =", stats.mode(df["Alcohol"])

print "Range =",max(df['Alcohol']) - min(df['Alcohol'])

print "Variance =",df['Alcohol'].var()

print "Standard Deviation =",df['Alcohol'].std()

print "\n"

print "Tobacco dataset stats:"

print "Mean = ",df['Tobacco'].mean()

print "Median =",df['Tobacco'].median()

print "Mode =",stats.mode(df["Tobacco"])[0][0]

print "Range =",max(df['Tobacco']) - min(df['Tobacco'])

print "Variance =",df['Tobacco'].var()

global data

data=[i.split(',') for i in data.splitlines()]

column_names = data[0]

data_rows = data[1:]

df = pd.DataFrame(data_rows, columns = column_names)

df["Alcohol"]=df["Alcohol"].astype(float)

df["Tobacco"]=df["Tobacco"].astype(float)

print df['Alcohol'].mean()

print df['Alcohol'].median()

print stats.mode(df["Alcohol"])[0][0]

print '\n'

print df['Tobacco'].mean()

print df['Tobacco'].median()

print stats.mode(df["Tobacco"])[0][0]

print '\n'

print max(df['Alcohol']) - min(df['Alcohol'])

print df['Alcohol'].std()

print df['Alcohol'].var()

print '\n'

print max(df['Tobacco']) - min(df['Tobacco'])

print df['Tobacco'].std()

print df['Tobacco'].var()

print "\n"

##z-score of Utopian people

mean = 251

std = 20

x = 2.3*std+mean