diff --git a/data_science/export_csv_reports.py b/data_science/export_csv_reports.py
new file mode 100644
index 0000000..116658c
--- /dev/null
+++ b/data_science/export_csv_reports.py
@@ -0,0 +1,50 @@
+#!/usr/bin/env python
+"""
+    Export data in a CSV spreadsheet.
+
+    Marina von Steinkirch - 2017
+
+    Need to have argparse installed:
+    $ pip install argparse
+"""
+
+import sys
+import argparse
+from pandas import DataFrame
+
+
+def read_data(data):
+    lines = data.readlines()
+
+    feature, precision, recall, f1 = [], [], [], []
+    for line in lines:
+        line_clean = line.strip().split(",")
+        feature.append(line_clean[0])
+        precision.append(line_clean[1])
+        recall.append(line_clean[4])
+        f1.append(line_clean[6])
+    return feature, precision, recall, f1
+
+
+def save_to_spreadsheet(resultfile, data):
+    try:
+        df = DataFrame({'Feature': data[0], 'Precision': data[1], 'Recall': data[2], 'f1-score': data[3]})
+        df.to_csv(resultfile, index=False)
+        print("Spreadsheet saved at {0}".format(resultfile))
+    except:
+        print("Error: {0}".format(sys.exc_info()[0]))
+
+
+def menu():
+    parser = argparse.ArgumentParser(description='Copy data results into a spreadsheet.')
+    parser.add_argument('-s', dest='input', type=argparse.FileType('r'), required=True, help="File with the results.")
+    parser.add_argument('-d', dest='output', required=True, help="The name of the file to save the spreadsheet.")
+    args = parser.parse_args()
+    args.input, args.output
+    return args.input, args.output
+
+
+if __name__ == "__main__":
+    datafile, resultfile = menu()
+    data = read_data(datafile)
+    save_to_spreadsheet(resultfile, data)