csvcolumn_to_scurve.py

#!/usr/bin/env python3

# This is a simple script that reads in a csv file, selects a column, and then
# forms an "s-curve" graph of that column.

importargparse
importcsv
importsys


defget_data(input_file, before_column, after_column):

defget_selected_csv_rows(input_file, before_column, after_column):
forrowincsv.DictReader(input_file):
before=float(row[before_column])
after=float(row[after_column])
ifbefore>0:
delta=after/before
else:
delta=1
yielddelta

deff(input_data):
result=list(enumerate(sorted(input_data)))
count=float(len(result) -1)
return [(x[0] /count, x[1]) forxinresult]

returnf(get_selected_csv_rows(input_file, before_column, after_column))


defmain():
p=argparse.ArgumentParser(description="""

 A script that reads in a csv file, splices out selected before/after
 column, and then outputs a new csv file with that data in s-curve form. An
 s-curve is a graph where one sorts the output %-change and graphs the %-n
 vs %-change.

 NOTE: We assume that the csv has a csv header that maps to the before and
 after column names passed in.
 """)

p.add_argument('input_file', type=argparse.FileType('r'))
p.add_argument('before_column_name', type=str)
p.add_argument('after_column_name', type=str)

args=p.parse_args()

data=get_data(args.input_file, args.before_column_name,
args.after_column_name)
w=csv.DictWriter(sys.stdout, fieldnames=['N/total', 'New/Old'])
w.writeheader()
fordindata:
w.writerow({'N/total': d[0], 'New/Old': d[1]})


if__name__=="__main__":
main()