Finding Min and Max of list generated from CSV file Python

Question

I am trying to find the MIN and MAX values for each row of a CSV file and append them to the next position in the list, positions 5 and 6. I have managed to calculate the average, append this to the forth position and output this in highest to lowest however, I am struggling to work out how to find the MAX and MIN values of each row so I can do the same - highest to lowest. The original CSV is formatted: Fred,56,78,99 with each user on a new line.

Any help would be appreciate.

import csv
import operator

sample  = open("sampleData.txt", "r")

csv1 = csv.reader(sample, delimiter = ',')

sort = sorted(csv1,key=operator.itemgetter(0))

for i in range( 0, len(sort)):
    sort[i].append((int(sort[i][1]) + int(sort[i][2]) + int(sort[i][3])) / int(len(sort[i])-1))   
sort = list(reversed(sorted(sort,key=operator.itemgetter(4))))
for i in range( 0, len( sort ) ):
print(sort[i][0], round(sort[i][4]))

Answer 1

import csv

sample  = open("sampleData.txt", "r")
csv1 = csv.reader(sample, delimiter = ',')

sorted_list = []

for line in csv1:
    print '-- ORIG:', line
    tmp = sorted( [int(i) for i in line[1:]], reverse=True )  # eg: [99,78,56]
    stat_list = [round(sum(tmp)/float(len(tmp)), 2), min(tmp), max(tmp)]
    sorted_list.append( [line[0]] + tmp + stat_list )

for s in sorted_list: print '** NEW: ', s # has ['Fred',99,78,56,78.0,57,99]

You can use/modify the quick & dirty solution above. Note:

1. The result is a list of lists with digits converted to integers.
2. The float() is needed for computing average - just doing it on the denominator is enough for the whole result to be a float.
3. List comprehensions are great shortcuts and efficient for avoiding for loops.
4. The numpy module has builtin mean() function (among many others) that are useful and fast, especially for large arrays.

OUTPUT (space added)

• ORIG: ['Fred', '57', '78', '99']
• ORIG: ['Wilma', '96', '4', '105']

• ORIG: ['Bar', '23', '88', '65']

• NEW: ['Fred', 99, 78, 57, 78.0, 57, 99]

• NEW: ['Wilma', 105, 96, 4, 68.33, 4, 105]
• NEW: ['Bar', 88, 65, 23, 58.67, 23, 88]