add export script

A lot more information is available in the original dataset

export-script.py

@@ -0,0 +1,32 @@
+import pandas as pd
+from bs4 import BeautifulSoup
+
+with open("sorted_data/books/positive.review") as file:
+    soup_pos = BeautifulSoup(file, "lxml")
+
+texts_pos=[]
+for review in soup_pos.find_all("review"):
+    texts_pos.append(review.review_text.text)
+
+books_pos = pd.DataFrame({"text":texts_pos, "label":1})
+books_pos.text = books_pos.text.replace("^\n", "", regex=True)
+
+from sklearn.model_selection import train_test_split
+books_pos_train, books_pos_test = train_test_split(books_pos, train_size=800, random_state=41)
+
+# Not OK to sart with, OK after open+save in Sublime
+# (encoding situation)
+with open("sorted_data/books/negative.review") as file:
+    soup_neg = BeautifulSoup(file, "lxml")
+
+texts_neg=[]
+for review in soup_neg.find_all("review"):
+    texts_neg.append(review.review_text.text)
+
+books_neg = pd.DataFrame({"text":texts_neg, "label":0})
+books_neg.text = books_neg.text.replace("^\n", "", regex=True)
+
+books_neg_train, books_neg_test = train_test_split(books_neg, train_size=800)
+
+pd.concat([books_pos_train, books_neg_train]).to_csv("sorted_data/books/train.csv", index=False)
+pd.concat([books_pos_test,  books_neg_test ]).to_csv("sorted_data/books/test.csv", index=False)