How to find a columns set for a primary key candidate in CSV file?

Question

I have a CSV file (not normalized, example, real file up to 100 columns):

   ID, CUST_NAME, CLIENT_NAME, PAYMENT_NUM, START_DATE, END_DATE
    1,     CUST1,         


        

Answer 1

pandas and itertools will give you what you're looking for.

import pandas
from itertools import chain, combinations

def key_options(items):
    return chain.from_iterable(combinations(items, r) for r in range(1, len(items)+1) )

df = pandas.read_csv('test.csv');

# iterate over all combos of headings, excluding ID for brevity
for candidate in key_options(list(df)[1:]):
    deduped = df.drop_duplicates(candidate)

    if len(deduped.index) == len(df.index):
        print ','.join(candidate)

This gives you the output:

PAYMENT_NUM, END_DATE
CUST_NAME, CLIENT_NAME, END_DATE
CUST_NAME, PAYMENT_NUM, END_DATE
CLIENT_NAME, PAYMENT_NUM, END_DATE
PAYMENT_NUM, START_DATE, END_DATE
CUST_NAME, CLIENT_NAME, PAYMENT_NUM, END_DATE
CUST_NAME, CLIENT_NAME, START_DATE, END_DATE
CUST_NAME, PAYMENT_NUM, START_DATE, END_DATE
CLIENT_NAME, PAYMENT_NUM, START_DATE, END_DATE
CUST_NAME, CLIENT_NAME, PAYMENT_NUM, START_DATE, END_DATE