#!/usr/bin/env python
# coding: utf-8

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import pandas as pd

names = ['Bob','Jessica','Mary','John','Mel', 'Sam', 'Courtney', 'Jackie']
grades = [76,95,77,77,99,80,32,50]
hoursstudy = [11,5,5,3,0,3,2,1]

GradeList = zip(names,grades,hoursstudy)
df = pd.DataFrame(data = GradeList, columns=['Names', 'Grades','StudyHours'])
df


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print 'count:', df['Grades'].count()  # computes the number of values 

print 'mean:', df['Grades'].mean()   # computes the arithmetic average of the values 

print 'standard deviation:', df['Grades'].std()    # computes the standard deviation of the values 

print 'min:', df['Grades'].min()    # computes the minimum of the values 
print 'max:', df['Grades'].max()    # computes the maximum of the values 

print '1st quartile:', df['Grades'].quantile(.25)  # computes the first quartile of the values 
print '2nd quartile:', df['Grades'].quantile(.5)   # computes the second quartile of the values 
print '3rd quartile:', df['Grades'].quantile(.75)  # computes the third quartile of the values 


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# computes the arithmetic average of the values in a column
# mean = dividing the sum of all values by the number of values
print 'mean:', df['Grades'].mean()

# finds the median of the values in a column
# median = the middle value if they are sorted in order
print 'median:', df['Grades'].median()

# finds the mode of the values in a column
# mode = the most common single value
print 'mode:', df['Grades'].mode()


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# computes the variance of the values in a column
print 'variance:', df['Grades'].var()


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df.mean()

