Merge pull request #18 from sheelfshah/master

Grader for titanic created

titanic/grader_sheelfshah.py

@@ -0,0 +1,40 @@
+import pandas as pd
+import numpy as np
+
+INPUT_MESSAGE = "Enter the name (with .csv ending) of the csv file to be graded:"
+CSV_ERROR = "The provided file name is invalid"
+TITLE_ERROR = "The title of the columns should be 'PassengerId' and 'Survived', in this order"
+COL1_ERROR = "The PassengerId column must have values starting at 892 and ending at 1309"
+SHAPE_ERROR = "The shape of the file is incorrect, ensure that you have added titles"
+END_MESSAGE = "Please rerun the grader with the required changes"
+expected_op_file = "output.csv"
+
+
+def main():
+    file_name = input(INPUT_MESSAGE)
+    try:
+        df = pd.read_csv(file_name)
+        df_exp = pd.read_csv(expected_op_file)
+        if not df.shape == df_exp.shape:
+            print(SHAPE_ERROR)
+            print(END_MESSAGE)
+            return
+        if not np.array_equal(df.columns, df_exp.columns):
+            print(TITLE_ERROR)
+            print(END_MESSAGE)
+            return
+        if not np.array_equal(df["PassengerId"], df_exp["PassengerId"]):
+            print(COL1_ERROR)
+            print(END_MESSAGE)
+            return
+        correct = df_exp["Survived"] == df["Survived"]
+        accuracy = (100 * np.sum(correct)) / len(correct)
+        accuracy = round(accuracy, 3)
+        print("Your prediction has an accuracy of", accuracy, "%")
+    except:
+        print(CSV_ERROR)
+        print(END_MESSAGE)
+        return
+
+if __name__ == '__main__':
+    main()