Datasets:
Tasks:
Text Classification
Sub-tasks:
intent-classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
License:
| import csv | |
| # This script transforms categorical labels to integer | |
| # Define the mapping | |
| mapping = { | |
| 'information': '0', | |
| 'cuisine': '1', | |
| 'directions': '2', | |
| 'reservations': '3', | |
| 'open_hours': '4', | |
| 'rating': '5' | |
| } | |
| # Open the input file in read mode and output file in write mode | |
| with open('train-intent-dataset-categorical.csv', 'r') as infile, open('output.csv', 'w', newline='') as outfile: | |
| # Create a CSV reader and writer | |
| reader = csv.reader(infile) | |
| writer = csv.writer(outfile) | |
| # Iterate over each row in the input CSV | |
| for row in reader: | |
| # If the first column value is in the mapping, replace it | |
| if row[0] in mapping: | |
| row[0] = mapping[row[0]] | |
| # Write the row to the output CSV | |
| writer.writerow(row) |