Creating a Unified Dictionary from a CSV File Consisting of Unique Key-Value Pairs
When handling CSV files, one common task is to create dictionaries where each row represents a unique key-value pair. While the 'csv.DictReader' class provides a convenient way to iterate through such files row-by-row, creating a unified dictionary requires a different approach.
The provided code attempts to construct a dictionary within the nested loop, leading to the 'ValueError' due to attempting to unpack multiple values with only two expected. To address this issue, the syntax should be slightly modified:
Python 3:
import csv with open('coors.csv', mode='r') as infile: reader = csv.reader(infile) with open('coors_new.csv', mode='w') as outfile: writer = csv.writer(outfile) mydict = {rows[0]: rows[1] for rows in reader}
Python 2:
import csv with open('coors.csv', mode='r') as infile: reader = csv.reader(infile) with open('coors_new.csv', mode='w') as outfile: writer = csv.writer(outfile) mydict = dict((rows[0], rows[1]) for rows in reader)
This revised syntax correctly iterates through the CSV file, extracting the key from the first column and the value from the second column for each row. The result is a single dictionary where the keys are unique and sourced from the first column, and the values are sourced from the second column. This approach consolidates all key-value pairs into a comprehensive dictionary.
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