feat: unsplitting data into train and test set

.gitignore

@@ -1,3 +1,2 @@
 20news-19997.tar.gz
-20_newsgroups/
-20newsgroups.csv
+20_newsgroups/

20newsgroups.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:455f8305fed7bee443348db3c0e7d017a118ca73299527f8be3b0a05efb71209
+size 36689935

convert.py

@@ -10,10 +10,6 @@ import csv
 import os
 import re
 
-import pandas as pd
-
-from sklearn.model_selection import train_test_split
-
 
 DATASET_PATH = "20_newsgroups"
 OUTPUT_FILE = "20newsgroups.csv"
@@ -42,7 +38,6 @@ def run():
                 rows.append(doc)
 
     save_csv(rows)
-    split_csv_train_test(test_size=0.2, random_state=42)
 
 
 def read_document(class_name, doc_name):
@@ -69,16 +64,6 @@ def save_csv(rows, fname=OUTPUT_FILE):
             writer.writerow(row)
 
 
-def split_csv_train_test(**kwargs):
-    """
-    Split the data into training and testing sets.
-    """
-    df = pd.read_csv(OUTPUT_FILE)
-    train_df, test_df = train_test_split(df, **kwargs)
-    train_df.to_csv(TRAIN_OUTPUT_FILE, index=False)
-    test_df.to_csv(TEST_OUTPUT_FILE, index=False)
-
-
 def parse_document(doc):
     """
     Parses a document into a dictionary