def parse_file(datafile):

data = []

with open(datafile, "r") as f:

header = f.readline().split(",")

for line in f:

fields = line.split(",")

entry = {}

for i, value in enumerate(fields):

entry[header[i].strip()] = value.strip()

data.append(entry)

return data

import csv

def parse_csv(datafile):

data = []

with open(datafile, "r") as f:

r = csv.DictReader(f)

for line in r:

data.append(line)

return data

import xlrd

def parse_xls(datafile):

workbook = xlrd.open_workbook(datafile)

sheet = workbook.sheet_by_index(0)

data = [[sheet.cell_value(r, col) for col in range(sheet.ncols)] for r in range(1, sheet.nrows)]

cv = sheet.col_values(1, start_rowx=1, end_rowx=None)

maxval = max(cv)

minval = min(cv)

maxpos = cv.index(maxval) + 1

minpos = cv.index(minval) + 1

maxtime = sheet.cell_value(maxpos, 0)

realtime = xlrd.xldate_as_tuple(maxtime, 0)

mintime = sheet.cell_value(minpos, 0)

realmintime = xlrd.xldata_as_tuple(mintime, 0)

data = {

'maxtime': realtime,

'maxvalue': maxval,

'mintime':realmintime,

'minvalue': minval,

'avgcoast': sum(cv) / float(len(cv))

}

return data

data = parse_xls(datafile)

import pprint

pprint.pprint(data)