Datasets:

Cleanlab
/

student-grades-demo

stud_ID stringlengths 6 6	exam_1 int64 0 100	exam_2 int64 0 100	exam_3 int64 32 100	notes stringclasses 5 values	letter_grade stringclasses 5 values	noisy_letter_grade stringclasses 5 values
f48f73	53	77	93	null	C	C
0bd4e7	81	64	80	great participation +10	B	B
e1795d	74	88	97	null	B	B
cb9d7a	61	94	78	null	C	C
9acca4	48	90	91	null	C	C
745c23	89	95	72	null	B	B
24d6f2	0	83	97	cheated on exam, gets 0pts	D	D
e5af86	71	82	97	null	B	B
0aa465	0	56	96	cheated on exam, gets 0pts	F	F
cac6eb	75	80	98	missed class frequently -10	C	C
d52614	81	65	82	null	C	C
5afd5d	95	86	53	missed homework frequently -10	D	B
952d9a	89	72	98	missed homework frequently -10	C	C
4629d7	80	59	65	null	D	D
28f8b4	67	82	98	null	B	D
851614	87	78	95	null	B	B
9f6431	89	69	98	great participation +10	A	A
f288e4	53	72	46	missed class frequently -10	F	F
5a53c9	46	84	89	missed homework frequently -10	D	B
edeb53	70	63	95	great participation +10	B	B
9b7f42	63	93	94	null	B	B
01ed51	90	75	90	missed homework frequently -10	C	C
10ec62	72	81	95	missed class frequently -10	C	C
5eef2c	90	83	51	null	C	A
71d7b9	99	53	76	null	C	C
b2ec67	85	49	83	null	C	C
fbffe2	89	71	94	great final presentation +10	A	A
752905	86	80	89	null	B	F
cfc98d	75	94	79	null	B	B
d7c575	61	95	94	null	B	B
b3112c	74	64	91	null	C	A
13b36e	98	92	96	null	A	A
c1085a	95	83	78	null	B	D
f5427e	92	63	91	missed homework frequently -10	C	C
e1dffd	69	94	95	great participation +10	A	A
6699cc	81	90	90	missed homework frequently -10	C	C
11d11f	98	69	90	null	B	D
5d086b	82	94	99	missed class frequently -10	B	B
cd1b96	73	57	96	null	C	C
d88e3d	98	73	86	great final presentation +10	A	A
7630c7	0	81	99	cheated on exam, gets 0pts	D	B
6ff175	0	89	100	cheated on exam, gets 0pts	D	D
6243e0	62	83	81	null	C	C
02e64e	78	84	92	great final presentation +10	A	A
1a0785	79	84	92	null	B	B
50c022	65	69	92	missed homework frequently -10	D	A
bfc71a	98	82	47	great final presentation +10	B	B
be178f	92	0	89	cheated on exam, gets 0pts	D	D
e68fe8	84	46	95	null	C	C
745eca	95	85	98	null	A	A
dea70a	86	88	90	great final presentation +10	A	A
416a58	65	58	91	null	C	C
aa4eaa	79	83	88	null	B	F
7e74b1	0	95	87	cheated on exam, gets 0pts	D	D
cce446	90	57	97	null	B	B
bece9b	72	69	81	missed homework frequently -10	D	D
eb10df	70	85	96	null	B	F
83818a	89	59	79	missed homework frequently -10	D	B
16fc65	75	83	69	null	C	A
f12b58	89	70	90	missed homework frequently -10	C	C
3cbdb0	81	85	95	null	B	B
93af9d	76	70	73	great participation +10	B	B
fff102	92	62	66	great participation +10	B	B
61cb66	94	98	99	null	A	A
63c40e	96	99	96	great final presentation +10	A	A
228dc0	65	85	80	great participation +10	B	B
32b9ff	90	79	85	great participation +10	A	A
b82370	0	87	77	cheated on exam, gets 0pts	F	F
0500f9	91	75	95	great participation +10	A	A
3b6d80	88	77	92	null	B	F
24f0df	86	64	96	null	B	B
38a6ec	88	67	74	null	C	A
c29e3c	76	59	65	null	D	D
db7c62	96	68	59	great participation +10	B	B
30f5ea	84	98	51	null	C	C
4575aa	97	85	75	null	B	B
ba5948	97	98	80	great final presentation +10	A	A
b6dd2f	89	74	71	null	C	C
d0a4ce	72	90	93	null	B	B
257755	49	0	78	cheated on exam, gets 0pts	F	F
11d2df	88	93	78	great participation +10	A	A
e64047	88	80	82	great participation +10	A	A
8bfb9a	75	91	68	great final presentation +10	B	B
267224	68	99	91	null	B	D
a59996	92	87	71	null	B	D
bdcaaf	83	97	75	great final presentation +10	A	A
98d5be	87	100	94	null	A	A
139084	86	95	77	null	B	B
dbaba1	79	0	76	cheated on exam, gets 0pts	F	F
4808b4	99	83	44	great final presentation +10	B	B
a7e4da	96	77	79	missed class frequently -10	C	C
974144	78	94	81	null	B	D
91044f	58	76	94	great participation +10	B	B
7af3fe	70	0	63	cheated on exam, gets 0pts	F	F
75490e	77	84	95	null	B	B
826859	81	56	54	null	D	D
c25641	76	96	78	great final presentation +10	A	A
1c4d0a	99	53	73	missed homework frequently -10	D	D
ea3967	93	91	84	great final presentation +10	A	A
dd3e61	73	87	86	missed class frequently -10	C	C

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Student Grades Demo Dataset

This dataset contains student grades data with both true labels and noisy (corrupted) labels.

Dataset Description

The dataset includes:

Student exam scores (exam_1, exam_2, exam_3)
Notes field
True letter grades (letter_grade)
Noisy/corrupted letter grades (noisy_letter_grade)

This is useful for demonstrating and validating label error detection methods.

Usage

import pandas as pd

# Load the dataset
df = pd.read_csv("hf://datasets/Cleanlab/student-grades-demo/student-grades-demo.csv")
print(df.head())

# Find rows where labels were corrupted
import numpy as np
true_errors = np.where(df["letter_grade"] != df["noisy_letter_grade"])[0]
print(f"Number of label errors: {len(true_errors)}")

License

MIT License

Downloads last month: 6

Size of downloaded dataset files:

33 kB

Size of the auto-converted Parquet files:

15.8 kB

Number of rows:

941