""" Purpose: introductory take on examining a table of values
"""

# get access to web-based data support
import url # we cannot access web data without the url module

# set repository folder
DATASET_FOLDER = "http://www.cs.virginia.edu/~cs1112/datasets/csv/"
# you could go to this folder and download the datasets that we use in class here

# get name of the dataset
reply = input( "Enter name of dataset: " )
file_name = reply.strip() # get rid of any accidental unwanted whitespace

# specify link
link = DATASET_FOLDER + file_name
# when we're getting info from the class webpage, we will have folder+file to make our link

# get dataset
table = url.get_dataset( link )
# get_dataset() vs. get_contents() - if we want a big string, use get_contents()
# if you want a dataset/csv file, use get_datasets()
# typically it will be clear which function you should use from problem to problem
    # "read a dataset" -> get_dataset()
    # "read a page"    -> get_contents()
# url.py has a lot of functions, and it will parse a csv into a dataset
# since csv stands for comma-separated file, it will use split( "," ) to split on the commas
# these functions are very handy and you don't really need to know how they work

print( "table:", table )
# this will print as a big ugly list of lists, because that's all a dataset is to python

print()

# determine number of rows in table
nrows = len( table )
# since a dataset is a list of lists, the length is the number of row lists in the table
# this returns our number of lists in the megalist

# if all rows have the same number of columns, ncols = len( table[0] )


print( "the table has", nrows, "rows" )

print()

# print each row of the table along with its number of columns
for row in table : # row is our loop variable that takes on a different row in table each run
    # you should always be able to identify what type of data is stored in your loop variable
    # in this case, row will be a list every time, so we can use list methods
    ncols = len( row ) # length of a row is the length of the inner list we're looking at
    # this hands back the number of elements in the row
    print( "row", row, "has", ncols, "columns" )

print()

# print each row of the table using row indices
for r in range( 0, nrows ) :
    # r is now going to be an integer every run of the for loop
    row = table[ r ] # we use that integer to access a specific row
    # this allows us to keep track of the row number, which can be very useful

    # *row is going to be the same in both of these loops*

    print( "row", r, ":",  row )
    # if you're working on a problem and you're not able to do it by looping through the
    # list, try transitioning to this type of list and see if you can solve the problem

    # python probably turns our looping through lists, strings, etc. into looping through
    # ranges and working with indices