""" Purpose: dataset nuance introduction
"""

# get access to web-based data support
import url 

# set repository folder
DATASET_FOLDER = "http://www.cs.virginia.edu/~cs1112/datasets/csv/"

# set name of the dataset
file_name = "best-sellers.csv"

# specify link
link = DATASET_FOLDER + file_name

# get dataset
table = url.get_dataset( link )

# define and print dataset header
header = table[ 0 ]
print( "header:", header )

print()

# define and print dataset books
books = table[ 1 : ]
print( "books:", books )

print()


# determine and print index of names, sales, and date columns of dataset
sales_column = header.index( "Sales" )
name_column  = header.index( "Name" )
date_column  = header.index( "Date" )

print( "sales column:", sales_column )
print( "name  column:", name_column )
print( "date  column:", date_column )

print()

"""             <---- will move down to reveal more of the program

# determine total books solds among the best sellers of all time
total = 0
for book in books :
    sold = book[ sales_column ]
    total = total + sold

print( "total sold:", total )

print()

# build a list of the book publication dates

dates = []
for row in books :
    year = row[ date_column ]
    dates.append( year )

print( "dates:", dates )

print()

# determine earliest and latest publication date
earliest = min( dates )
latest   = max( dates )

print( "earliest:", earliest )
print( "latest  :", latest )

print()

# determine average publication date

date_total   = sum( dates )   # <--------------------- HUH?
nbr_of_dates = len( dates )   

average_date = date_total // nbr_of_dates

print( "average date:", average_date )

print()

# determine earliest and latest published books

# to do so need to first find their indices into dates list, those
#     indices correspond to the row indices into books list
row_earliest = dates.index( earliest )
row_latest   = dates.index( latest )

print( "row with earliest book:", row_earliest )
print( "row with latest book  :", row_latest )

print()

# use those indices to look at corresponding rows into books dataset
earliest_row = books[ row_earliest ]
latest_row   = books[ row_latest ]

# print those rows
print( "info on earliest:", earliest_row )
print( "info on latest:  ", latest_row )

print()

# print just the names of those books
name_column  = header.index( "Name" )

earliest_name = earliest_row[ name_column ]
latest_name   = latest_row[ name_column ]

print( "name of earliest:", earliest_name )
print( "name of latest:  ", latest_name )

"""