first commit

.gitattributes

@@ -53,3 +53,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+complete.csv filter=lfs diff=lfs merge=lfs -text
+test.csv filter=lfs diff=lfs merge=lfs -text
+train.csv filter=lfs diff=lfs merge=lfs -text

Makefile

@@ -0,0 +1,4 @@
+download:
+	wget https://archive.ics.uci.edu/static/public/462/drug+review+dataset+drugs+com.zip
+	unzip drug+review+dataset+drugs+com.zip
+	rm drug+review+dataset+drugs+com.zip

README.md

@@ -0,0 +1,17 @@
+---
+language:
+- en
+task_categories:
+- text-classification
+
+configs:
+- config_name: default
+  data_files:
+  - split: complete
+    path: "complete.csv"
+  - split: train
+    path: "train.csv"
+  - split: test
+    path: "test.csv"
+  default: true
+---

complete.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2817f31c2558813c95742c3f592797c670090184cc604faa74a0a22ae14f316e
+size 107763488

convert.py

@@ -0,0 +1,66 @@
+from datetime import datetime
+
+import pandas as pd
+
+from bs4 import BeautifulSoup
+
+
+def parse_review(html):
+    if html.startswith('"') and html.endswith('"'):
+        html = html[1:-1]
+
+    soup = BeautifulSoup(html, "lxml")
+    text = soup.get_text()
+    return text
+
+
+def parse_rating(rating_str):
+    rating = int(rating_str)
+    return rating
+
+
+def parse_date(date_str):
+    dt = datetime.strptime(date_str, "%B %d, %Y")
+
+    iso_format_date = dt.strftime("%Y-%m-%d")
+
+    return iso_format_date
+
+
+def read_file(file_path):
+    data = pd.read_csv(file_path, sep="\t")
+
+    rows = []
+
+    for _, row in data.iterrows():
+        obj = {
+            "id": row[0],
+            "drugName": row[1],
+            "condition": row[2],
+            "review": parse_review(row[3]),
+            "rating": parse_rating(row[4]),
+            "date": parse_date(row[5]),
+            "usefulCount": row[6],
+        }
+        rows.append(obj)
+
+    return rows
+
+
+def save(rows, file_path):
+    df = pd.DataFrame(rows)
+    df.to_csv(file_path, index=False)
+
+
+def run():
+    train_rows = read_file("drugsComTrain_raw.tsv")
+    test_rows = read_file("drugsComTest_raw.tsv")
+    all_rows = train_rows + test_rows
+
+    save(train_rows, "train.csv")
+    save(test_rows, "test.csv")
+    save(all_rows, "complete.csv")
+
+
+if __name__ == "__main__":
+    run()

test.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:be700a0c1da6967ca1db27a624d649010bb9d0c66e8cd3489268f8f89c740960
+size 26919224

train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:49c1ebdf38ee8443a0cb6ea79de630375e0609d4119e2d77ee4a35b20e299517
+size 80844317