[dev-scripts] Add csv_to_scurve.py to convert csv documents into an scurve csv file ready for graphing.

I am upstreaming this for two reasons:

1. Traditionally I have done this by hand in a spreadsheet program. I would
rather just have a program fix it up for me.
2. Multiple people have asked me about how to produce this sort of graph and I
would just like to document it via a script.

I hope it is useful to others. You use the script by invoking it as:

./csvcolumn_to_scurve <input_file> <before_column> <after_column> [output_file]

utils/dev-scripts/csvcolumn_to_scurve.py

@@ -0,0 +1,55 @@
+#!/usr/bin/env python
+
+# This is a simple script that reads in a csv file, selects a column, and then
+# forms an "s-curve" graph of that column.
+
+import argparse
+import csv
+import sys
+
+
+def get_data(input_file, before_column, after_column):
+
+    def get_selected_csv_rows(input_file, before_column, after_column):
+        for row in csv.DictReader(input_file):
+            before = float(row[before_column])
+            after = float(row[after_column])
+            delta = after / before
+            yield delta
+
+    def f(input_data):
+        result = list(enumerate(sorted(input_data)))
+        count = float(len(result) - 1)
+        return [(x[0] / count, x[1]) for x in result]
+
+    return f(get_selected_csv_rows(input_file, before_column, after_column))
+
+
+def main():
+    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()
+    for d in data:
+        w.writerow({'N/total': d[0], 'New/Old': d[1]})
+
+
+if __name__ == "__main__":
+    main()