Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells70093
Missing cells (%)27.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 MiB
Average record size in memory229.0 B

Variable types

Text7
Numeric9
Boolean4
DateTime2
Categorical1
Unsupported3

Dataset

Description한국기술교육대학교 일학습병행대학 학부 및 대학원생을 대상으로 실시되는 온라인교육(OKLMS)에서 학생들이 제출한 과제물(리포트) 정보입니다.
Author한국기술교육대학교
URLhttps://www.data.go.kr/data/15122469/fileData.do

Alerts

삭제여부 has constant value ""Constant
삭제여부_2 has constant value ""Constant
삭제여부_1 is highly imbalanced (51.1%)Imbalance
첨부파일아이디 has 3643 (36.4%) missing valuesMissing
제출내용 has 10000 (100.0%) missing valuesMissing
평가점수 has 6921 (69.2%) missing valuesMissing
제출제목 has 10000 (100.0%) missing valuesMissing
첨부파일아이디_1 has 9945 (99.5%) missing valuesMissing
삭제여부_2 has 9788 (97.9%) missing valuesMissing
피드백내용 has 10000 (100.0%) missing valuesMissing
과제제출아이디 has 9788 (97.9%) missing valuesMissing
분반 is highly skewed (γ1 = 22.39529552)Skewed
제출파일아이디 has unique valuesUnique
제출내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제출제목 is an unsupported type, check if it needs cleaning or further analysisUnsupported
피드백내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배점기준 has 2341 (23.4%) zerosZeros
등록종료시간 has 6741 (67.4%) zerosZeros
등록종료분 has 8135 (81.3%) zerosZeros
등록시작시간 has 7956 (79.6%) zerosZeros
등록시작분 has 9522 (95.2%) zerosZeros

Reproduction

Analysis started2024-04-20 21:21:06.955124
Analysis finished2024-04-20 21:21:08.349722
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

과제아이디
Text

Distinct2886
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T06:21:09.017649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters140000
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique622 ?
Unique (%)6.2%

Sample

1st rowREP_0000001300
2nd rowREP_0000003798
3rd rowREP_0000001414
4th rowREP_0000000958
5th rowREP_0000003821
ValueCountFrequency (%)
rep_0000001223 15
 
0.1%
rep_0000002109 15
 
0.1%
rep_0000000854 14
 
0.1%
rep_0000000962 13
 
0.1%
rep_0000002136 13
 
0.1%
rep_0000000907 13
 
0.1%
rep_0000003740 12
 
0.1%
rep_0000004521 12
 
0.1%
rep_0000002677 12
 
0.1%
rep_0000002581 12
 
0.1%
Other values (2876) 9869
98.7%
2024-04-21T06:21:10.192141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64249
45.9%
R 10000
 
7.1%
E 10000
 
7.1%
P 10000
 
7.1%
_ 10000
 
7.1%
1 5626
 
4.0%
3 5301
 
3.8%
2 5198
 
3.7%
4 4450
 
3.2%
5 3171
 
2.3%
Other values (4) 12005
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100000
71.4%
Uppercase Letter 30000
 
21.4%
Connector Punctuation 10000
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64249
64.2%
1 5626
 
5.6%
3 5301
 
5.3%
2 5198
 
5.2%
4 4450
 
4.5%
5 3171
 
3.2%
7 3059
 
3.1%
6 3024
 
3.0%
9 2965
 
3.0%
8 2957
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
R 10000
33.3%
E 10000
33.3%
P 10000
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 110000
78.6%
Latin 30000
 
21.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64249
58.4%
_ 10000
 
9.1%
1 5626
 
5.1%
3 5301
 
4.8%
2 5198
 
4.7%
4 4450
 
4.0%
5 3171
 
2.9%
7 3059
 
2.8%
6 3024
 
2.7%
9 2965
 
2.7%
Latin
ValueCountFrequency (%)
R 10000
33.3%
E 10000
33.3%
P 10000
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 140000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64249
45.9%
R 10000
 
7.1%
E 10000
 
7.1%
P 10000
 
7.1%
_ 10000
 
7.1%
1 5626
 
4.0%
3 5301
 
3.8%
2 5198
 
3.7%
4 4450
 
3.2%
5 3171
 
2.3%
Other values (4) 12005
 
8.6%

과제제목
Text

Distinct2231
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T06:21:11.089080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length86
Median length59
Mean length13.6035
Min length2

Characters and Unicode

Total characters136035
Distinct characters600
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique406 ?
Unique (%)4.1%

Sample

1st row1주차 과제
2nd row6주차 과제 문제
3rd row실습일지
4th rowW12-2
5th row부가경로설정
ValueCountFrequency (%)
과제 2743
 
9.2%
문제 727
 
2.4%
제출 393
 
1.3%
기말고사 379
 
1.3%
379
 
1.3%
및 376
 
1.3%
퀴즈 331
 
1.1%
2주차 311
 
1.0%
실습 264
 
0.9%
4주차 253
 
0.8%
Other values (2931) 23693
79.4%
2024-04-21T06:21:12.569210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21469
 
15.8%
제 8193
 
6.0%
과 5869
 
4.3%
차 3296
 
2.4%
주 3277
 
2.4%
1 3113
 
2.3%
기 2909
 
2.1%
2 1794
 
1.3%
_ 1558
 
1.1%
사 1455
 
1.1%
Other values (590) 83102
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85293
62.7%
Space Separator 21469
 
15.8%
Decimal Number 11021
 
8.1%
Lowercase Letter 5720
 
4.2%
Uppercase Letter 3858
 
2.8%
Open Punctuation 2153
 
1.6%
Close Punctuation 2147
 
1.6%
Other Punctuation 1689
 
1.2%
Connector Punctuation 1558
 
1.1%
Dash Punctuation 937
 
0.7%
Other values (4) 190
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 8193
 
9.6%
과 5869
 
6.9%
차 3296
 
3.9%
주 3277
 
3.8%
기 2909
 
3.4%
사 1455
 
1.7%
습 1423
 
1.7%
실 1376
 
1.6%
문 1243
 
1.5%
계 1130
 
1.3%
Other values (505) 55122
64.6%
Lowercase Letter
ValueCountFrequency (%)
e 904
15.8%
o 542
 
9.5%
t 411
 
7.2%
a 398
 
7.0%
r 393
 
6.9%
s 323
 
5.6%
i 309
 
5.4%
n 303
 
5.3%
d 256
 
4.5%
l 253
 
4.4%
Other values (16) 1628
28.5%
Uppercase Letter
ValueCountFrequency (%)
C 495
12.8%
W 377
9.8%
P 324
 
8.4%
S 296
 
7.7%
T 277
 
7.2%
A 253
 
6.6%
I 246
 
6.4%
D 230
 
6.0%
L 221
 
5.7%
M 198
 
5.1%
Other values (16) 941
24.4%
Decimal Number
ValueCountFrequency (%)
1 3113
28.2%
2 1794
16.3%
0 1319
12.0%
3 1285
11.7%
4 990
 
9.0%
5 811
 
7.4%
6 512
 
4.6%
7 428
 
3.9%
9 415
 
3.8%
8 354
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 910
53.9%
/ 473
28.0%
: 276
 
16.3%
? 17
 
1.0%
· 9
 
0.5%
' 4
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 84
50.0%
~ 49
29.2%
> 16
 
9.5%
< 14
 
8.3%
= 5
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 1136
52.8%
[ 1016
47.2%
【 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 1136
52.9%
] 1009
47.0%
} 2
 
0.1%
Space Separator
ValueCountFrequency (%)
21469
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1558
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 937
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 11
100.0%
Control
ValueCountFrequency (%)
8
100.0%
Other Symbol
ValueCountFrequency (%)
★ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85293
62.7%
Common 41164
30.3%
Latin 9578
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 8193
 
9.6%
과 5869
 
6.9%
차 3296
 
3.9%
주 3277
 
3.8%
기 2909
 
3.4%
사 1455
 
1.7%
습 1423
 
1.7%
실 1376
 
1.6%
문 1243
 
1.5%
계 1130
 
1.3%
Other values (505) 55122
64.6%
Latin
ValueCountFrequency (%)
e 904
 
9.4%
o 542
 
5.7%
C 495
 
5.2%
t 411
 
4.3%
a 398
 
4.2%
r 393
 
4.1%
W 377
 
3.9%
P 324
 
3.4%
s 323
 
3.4%
i 309
 
3.2%
Other values (42) 5102
53.3%
Common
ValueCountFrequency (%)
21469
52.2%
1 3113
 
7.6%
2 1794
 
4.4%
_ 1558
 
3.8%
0 1319
 
3.2%
3 1285
 
3.1%
( 1136
 
2.8%
) 1136
 
2.8%
[ 1016
 
2.5%
] 1009
 
2.5%
Other values (23) 6329
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85290
62.7%
ASCII 50718
37.3%
Punctuation 11
 
< 0.1%
None 10
 
< 0.1%
Misc Symbols 3
 
< 0.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21469
42.3%
1 3113
 
6.1%
2 1794
 
3.5%
_ 1558
 
3.1%
0 1319
 
2.6%
3 1285
 
2.5%
( 1136
 
2.2%
) 1136
 
2.2%
[ 1016
 
2.0%
] 1009
 
2.0%
Other values (71) 15883
31.3%
Hangul
ValueCountFrequency (%)
제 8193
 
9.6%
과 5869
 
6.9%
차 3296
 
3.9%
주 3277
 
3.8%
기 2909
 
3.4%
사 1455
 
1.7%
습 1423
 
1.7%
실 1376
 
1.6%
문 1243
 
1.5%
계 1130
 
1.3%
Other values (504) 55119
64.6%
Punctuation
ValueCountFrequency (%)
’ 11
100.0%
None
ValueCountFrequency (%)
· 9
90.0%
【 1
 
10.0%
Misc Symbols
ValueCountFrequency (%)
★ 3
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅐ 3
100.0%

첨부파일아이디
Text

MISSING 

Distinct1814
Distinct (%)28.5%
Missing3643
Missing (%)36.4%
Memory size156.2 KiB
2024-04-21T06:21:13.321706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters127140
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique402 ?
Unique (%)6.3%

Sample

1st row2021FILE000000215743
2nd row2017FILE000000005973
3rd row2021FILE000000172947
4th row2020FILE000000057692
5th row2020FILE000000058628
ValueCountFrequency (%)
2018file000000018470 14
 
0.2%
2018file000000021220 13
 
0.2%
2018file000000019746 13
 
0.2%
2018file000000013828 12
 
0.2%
2019file000000026788 12
 
0.2%
2018file000000021849 12
 
0.2%
2020file000000124059 12
 
0.2%
2019file000000025437 12
 
0.2%
2018file000000014750 11
 
0.2%
2020file000000051153 11
 
0.2%
Other values (1804) 6235
98.1%
2024-04-21T06:21:14.456627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 53032
41.7%
2 16131
 
12.7%
1 9076
 
7.1%
F 6357
 
5.0%
I 6357
 
5.0%
L 6357
 
5.0%
E 6357
 
5.0%
9 3800
 
3.0%
8 3631
 
2.9%
5 3489
 
2.7%
Other values (4) 12553
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101712
80.0%
Uppercase Letter 25428
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53032
52.1%
2 16131
 
15.9%
1 9076
 
8.9%
9 3800
 
3.7%
8 3631
 
3.6%
5 3489
 
3.4%
6 3310
 
3.3%
7 3263
 
3.2%
3 3160
 
3.1%
4 2820
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
F 6357
25.0%
I 6357
25.0%
L 6357
25.0%
E 6357
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 101712
80.0%
Latin 25428
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 53032
52.1%
2 16131
 
15.9%
1 9076
 
8.9%
9 3800
 
3.7%
8 3631
 
3.6%
5 3489
 
3.4%
6 3310
 
3.3%
7 3263
 
3.2%
3 3160
 
3.1%
4 2820
 
2.8%
Latin
ValueCountFrequency (%)
F 6357
25.0%
I 6357
25.0%
L 6357
25.0%
E 6357
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 53032
41.7%
2 16131
 
12.7%
1 9076
 
7.1%
F 6357
 
5.0%
I 6357
 
5.0%
L 6357
 
5.0%
E 6357
 
5.0%
9 3800
 
3.0%
8 3631
 
2.9%
5 3489
 
2.7%
Other values (4) 12553
 
9.9%

분반
Real number (ℝ)

SKEWED 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0658
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T06:21:14.812209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum18
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.53450812
Coefficient of variation (CV)0.50150884
Kurtosis612.55256
Mean1.0658
Median Absolute Deviation (MAD)0
Skewness22.395296
Sum10658
Variance0.28569893
MonotonicityNot monotonic
2024-04-21T06:21:15.071537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 9517
95.2%
2 464
 
4.6%
17 4
 
< 0.1%
7 3
 
< 0.1%
8 2
 
< 0.1%
15 2
 
< 0.1%
6 2
 
< 0.1%
16 1
 
< 0.1%
5 1
 
< 0.1%
13 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
ValueCountFrequency (%)
1 9517
95.2%
2 464
 
4.6%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 3
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
13 1
 
< 0.1%
15 2
 
< 0.1%
ValueCountFrequency (%)
18 1
 
< 0.1%
17 4
< 0.1%
16 1
 
< 0.1%
15 2
< 0.1%
13 1
 
< 0.1%
10 1
 
< 0.1%
8 2
< 0.1%
7 3
< 0.1%
6 2
< 0.1%
5 1
 
< 0.1%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2024-04-21T06:21:15.261591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

평가여부
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
6879 
False
3121 
ValueCountFrequency (%)
True 6879
68.8%
False 3121
31.2%
2024-04-21T06:21:15.425315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

배점기준
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)0.3%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean17.489892
Minimum0
Maximum1000
Zeros2341
Zeros (%)23.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T06:21:15.660801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q310
95-th percentile100
Maximum1000
Range1000
Interquartile range (IQR)9

Descriptive statistics

Standard deviation39.065858
Coefficient of variation (CV)2.2336249
Kurtosis239.77652
Mean17.489892
Median Absolute Deviation (MAD)5
Skewness10.598512
Sum174759
Variance1526.1412
MonotonicityNot monotonic
2024-04-21T06:21:15.880676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 2341
23.4%
5 1930
19.3%
10 1707
17.1%
100 1116
11.2%
2 897
 
9.0%
1 527
 
5.3%
30 465
 
4.7%
3 419
 
4.2%
20 134
 
1.3%
4 115
 
1.1%
Other values (17) 341
 
3.4%
ValueCountFrequency (%)
0 2341
23.4%
1 527
 
5.3%
2 897
 
9.0%
3 419
 
4.2%
4 115
 
1.1%
5 1930
19.3%
6 30
 
0.3%
7 15
 
0.1%
8 19
 
0.2%
9 7
 
0.1%
ValueCountFrequency (%)
1000 6
 
0.1%
209 2
 
< 0.1%
100 1116
11.2%
80 2
 
< 0.1%
63 3
 
< 0.1%
50 50
 
0.5%
45 5
 
0.1%
43 3
 
< 0.1%
40 89
 
0.9%
35 11
 
0.1%

교과목코드
Text

Distinct266
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T06:21:17.134323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters60000
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)0.1%

Sample

1st rowMAE210
2nd rowMAE441
3rd rowMAE810
4th rowMDE685
5th rowMDE880
ValueCountFrequency (%)
mae890 215
 
2.1%
mae800 205
 
2.1%
mde685 185
 
1.8%
mae840 178
 
1.8%
mae845 170
 
1.7%
mae501 166
 
1.7%
mde695 165
 
1.7%
sme210 155
 
1.6%
mae835 146
 
1.5%
mae460 142
 
1.4%
Other values (256) 8273
82.7%
2024-04-21T06:21:18.578189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 9317
15.5%
M 9316
15.5%
0 6709
11.2%
5 4322
7.2%
A 4256
7.1%
1 3856
 
6.4%
8 3394
 
5.7%
D 3337
 
5.6%
6 3130
 
5.2%
2 2698
 
4.5%
Other values (6) 9665
16.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32049
53.4%
Uppercase Letter 27951
46.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6709
20.9%
5 4322
13.5%
1 3856
12.0%
8 3394
10.6%
6 3130
9.8%
2 2698
8.4%
4 2628
 
8.2%
7 2250
 
7.0%
9 1883
 
5.9%
3 1179
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
E 9317
33.3%
M 9316
33.3%
A 4256
15.2%
D 3337
 
11.9%
S 1724
 
6.2%
T 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 32049
53.4%
Latin 27951
46.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6709
20.9%
5 4322
13.5%
1 3856
12.0%
8 3394
10.6%
6 3130
9.8%
2 2698
8.4%
4 2628
 
8.2%
7 2250
 
7.0%
9 1883
 
5.9%
3 1179
 
3.7%
Latin
ValueCountFrequency (%)
E 9317
33.3%
M 9316
33.3%
A 4256
15.2%
D 3337
 
11.9%
S 1724
 
6.2%
T 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 9317
15.5%
M 9316
15.5%
0 6709
11.2%
5 4322
7.2%
A 4256
7.1%
1 3856
 
6.4%
8 3394
 
5.7%
D 3337
 
5.6%
6 3130
 
5.2%
2 2698
 
4.5%
Other values (6) 9665
16.1%

제출종료일
Date

Distinct724
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-07-07 00:00:00
Maximum2023-06-28 00:00:00
2024-04-21T06:21:18.833797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:21:19.107061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

등록종료시간
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3296
Minimum0
Maximum23
Zeros6741
Zeros (%)67.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T06:21:19.339835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q316
95-th percentile23
Maximum23
Range23
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.4822231
Coefficient of variation (CV)1.4980762
Kurtosis-0.93508702
Mean6.3296
Median Absolute Deviation (MAD)0
Skewness0.94593783
Sum63296
Variance89.912555
MonotonicityNot monotonic
2024-04-21T06:21:19.548714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 6741
67.4%
23 1797
 
18.0%
12 189
 
1.9%
16 186
 
1.9%
15 161
 
1.6%
18 151
 
1.5%
19 128
 
1.3%
17 122
 
1.2%
11 101
 
1.0%
22 81
 
0.8%
Other values (8) 343
 
3.4%
ValueCountFrequency (%)
0 6741
67.4%
1 4
 
< 0.1%
8 49
 
0.5%
9 42
 
0.4%
10 62
 
0.6%
11 101
 
1.0%
12 189
 
1.9%
13 66
 
0.7%
14 78
 
0.8%
15 161
 
1.6%
ValueCountFrequency (%)
23 1797
18.0%
22 81
 
0.8%
21 5
 
0.1%
20 37
 
0.4%
19 128
 
1.3%
18 151
 
1.5%
17 122
 
1.2%
16 186
 
1.9%
15 161
 
1.6%
14 78
 
0.8%

등록종료분
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.137
Minimum0
Maximum50
Zeros8135
Zeros (%)81.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T06:21:19.757157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile50
Maximum50
Range50
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17.832864
Coefficient of variation (CV)2.1915772
Kurtosis1.4581714
Mean8.137
Median Absolute Deviation (MAD)0
Skewness1.8297616
Sum81370
Variance318.01103
MonotonicityNot monotonic
2024-04-21T06:21:19.977152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 8135
81.3%
50 1421
 
14.2%
10 125
 
1.2%
20 124
 
1.2%
30 121
 
1.2%
40 74
 
0.7%
ValueCountFrequency (%)
0 8135
81.3%
10 125
 
1.2%
20 124
 
1.2%
30 121
 
1.2%
40 74
 
0.7%
50 1421
 
14.2%
ValueCountFrequency (%)
50 1421
 
14.2%
40 74
 
0.7%
30 121
 
1.2%
20 124
 
1.2%
10 125
 
1.2%
0 8135
81.3%

제출시작일
Date

Distinct624
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-06-24 00:00:00
Maximum2023-03-25 00:00:00
2024-04-21T06:21:20.215712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:21:20.482728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

등록시작시간
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8238
Minimum0
Maximum23
Zeros7956
Zeros (%)79.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T06:21:20.727366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile17
Maximum23
Range23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.8852882
Coefficient of variation (CV)2.0841732
Kurtosis1.7997497
Mean2.8238
Median Absolute Deviation (MAD)0
Skewness1.8128703
Sum28238
Variance34.636617
MonotonicityNot monotonic
2024-04-21T06:21:20.974150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7956
79.6%
9 327
 
3.3%
16 244
 
2.4%
13 214
 
2.1%
14 204
 
2.0%
18 199
 
2.0%
15 176
 
1.8%
17 142
 
1.4%
11 126
 
1.3%
10 112
 
1.1%
Other values (12) 300
 
3.0%
ValueCountFrequency (%)
0 7956
79.6%
1 36
 
0.4%
2 4
 
< 0.1%
3 7
 
0.1%
5 3
 
< 0.1%
7 1
 
< 0.1%
8 16
 
0.2%
9 327
 
3.3%
10 112
 
1.1%
11 126
 
1.3%
ValueCountFrequency (%)
23 107
1.1%
22 5
 
0.1%
21 4
 
< 0.1%
20 8
 
0.1%
19 39
 
0.4%
18 199
2.0%
17 142
1.4%
16 244
2.4%
15 176
1.8%
14 204
2.0%

등록시작분
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.529
Minimum0
Maximum50
Zeros9522
Zeros (%)95.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T06:21:21.293091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum50
Range50
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.4119938
Coefficient of variation (CV)4.8476088
Kurtosis26.691524
Mean1.529
Median Absolute Deviation (MAD)0
Skewness5.1660004
Sum15290
Variance54.937653
MonotonicityNot monotonic
2024-04-21T06:21:21.667213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9522
95.2%
30 163
 
1.6%
50 117
 
1.2%
20 74
 
0.7%
10 63
 
0.6%
40 61
 
0.6%
ValueCountFrequency (%)
0 9522
95.2%
10 63
 
0.6%
20 74
 
0.7%
30 163
 
1.6%
40 61
 
0.6%
50 117
 
1.2%
ValueCountFrequency (%)
50 117
 
1.2%
40 61
 
0.6%
30 163
 
1.6%
20 74
 
0.7%
10 63
 
0.6%
0 9522
95.2%

학기
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
4386 
2
4118 
3
1096 
4
 
400

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 4386
43.9%
2 4118
41.2%
3 1096
 
11.0%
4 400
 
4.0%

Length

2024-04-21T06:21:22.171636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:21:22.382259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4386
43.9%
2 4118
41.2%
3 1096
 
11.0%
4 400
 
4.0%

주차
Real number (ℝ)

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5926
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T06:21:22.690340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q310
95-th percentile15
Maximum15
Range14
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.3150072
Coefficient of variation (CV)0.65452283
Kurtosis-0.97708743
Mean6.5926
Median Absolute Deviation (MAD)3
Skewness0.50357461
Sum65926
Variance18.619287
MonotonicityNot monotonic
2024-04-21T06:21:23.054121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4 1105
11.1%
2 1043
10.4%
3 1004
10.0%
5 989
9.9%
1 971
9.7%
15 628
 
6.3%
6 622
 
6.2%
12 507
 
5.1%
10 502
 
5.0%
7 499
 
5.0%
Other values (5) 2130
21.3%
ValueCountFrequency (%)
1 971
9.7%
2 1043
10.4%
3 1004
10.0%
4 1105
11.1%
5 989
9.9%
6 622
6.2%
7 499
5.0%
8 471
4.7%
9 469
4.7%
10 502
5.0%
ValueCountFrequency (%)
15 628
6.3%
14 268
2.7%
13 430
4.3%
12 507
5.1%
11 492
4.9%
10 502
5.0%
9 469
4.7%
8 471
4.7%
7 499
5.0%
6 622
6.2%

학년도
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.9909
Minimum2017
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T06:21:23.392239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2018
Q12019
median2020
Q32021
95-th percentile2022
Maximum2023
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3069001
Coefficient of variation (CV)0.00064698318
Kurtosis-0.52880367
Mean2019.9909
Median Absolute Deviation (MAD)1
Skewness-0.38461832
Sum20199909
Variance1.707988
MonotonicityNot monotonic
2024-04-21T06:21:23.733095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2020 2958
29.6%
2021 2804
28.0%
2019 1524
15.2%
2018 1268
12.7%
2022 1067
 
10.7%
2017 351
 
3.5%
2023 28
 
0.3%
ValueCountFrequency (%)
2017 351
 
3.5%
2018 1268
12.7%
2019 1524
15.2%
2020 2958
29.6%
2021 2804
28.0%
2022 1067
 
10.7%
2023 28
 
0.3%
ValueCountFrequency (%)
2023 28
 
0.3%
2022 1067
 
10.7%
2021 2804
28.0%
2020 2958
29.6%
2019 1524
15.2%
2018 1268
12.7%
2017 351
 
3.5%

제출파일아이디
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T06:21:24.468279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters200000
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row2019FILE000000031896
2nd row2021FILE000000219077
3rd row2019FILE000000039474
4th row2018FILE000000021314
5th row2021FILE000000217452
ValueCountFrequency (%)
2019file000000031896 1
 
< 0.1%
2018file000000013427 1
 
< 0.1%
2021file000000181645 1
 
< 0.1%
2017file000000006377 1
 
< 0.1%
2021file000000235401 1
 
< 0.1%
2021file000000216577 1
 
< 0.1%
2018file000000019532 1
 
< 0.1%
2020file000000068272 1
 
< 0.1%
2020file000000066194 1
 
< 0.1%
2022file000000276202 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-21T06:21:25.556725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 82932
41.5%
2 25809
 
12.9%
1 14112
 
7.1%
F 10000
 
5.0%
I 10000
 
5.0%
L 10000
 
5.0%
E 10000
 
5.0%
9 6459
 
3.2%
8 5987
 
3.0%
3 5296
 
2.6%
Other values (4) 19405
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160000
80.0%
Uppercase Letter 40000
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 82932
51.8%
2 25809
 
16.1%
1 14112
 
8.8%
9 6459
 
4.0%
8 5987
 
3.7%
3 5296
 
3.3%
6 5015
 
3.1%
5 4971
 
3.1%
7 4870
 
3.0%
4 4549
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
F 10000
25.0%
I 10000
25.0%
L 10000
25.0%
E 10000
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 160000
80.0%
Latin 40000
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 82932
51.8%
2 25809
 
16.1%
1 14112
 
8.8%
9 6459
 
4.0%
8 5987
 
3.7%
3 5296
 
3.3%
6 5015
 
3.1%
5 4971
 
3.1%
7 4870
 
3.0%
4 4549
 
2.8%
Latin
ValueCountFrequency (%)
F 10000
25.0%
I 10000
25.0%
L 10000
25.0%
E 10000
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 200000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 82932
41.5%
2 25809
 
12.9%
1 14112
 
7.1%
F 10000
 
5.0%
I 10000
 
5.0%
L 10000
 
5.0%
E 10000
 
5.0%
9 6459
 
3.2%
8 5987
 
3.0%
3 5296
 
2.6%
Other values (4) 19405
 
9.7%

제출내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

삭제여부_1
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
8935 
True
1065 
ValueCountFrequency (%)
False 8935
89.3%
True 1065
 
10.7%
2024-04-21T06:21:25.896402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

평가점수
Real number (ℝ)

MISSING 

Distinct91
Distinct (%)3.0%
Missing6921
Missing (%)69.2%
Infinite0
Infinite (%)0.0%
Mean27.897272
Minimum0
Maximum100
Zeros16
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T06:21:26.240660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median7.5
Q339.5
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)36.5

Descriptive statistics

Standard deviation38.473751
Coefficient of variation (CV)1.3791224
Kurtosis-0.4549164
Mean27.897272
Median Absolute Deviation (MAD)5.5
Skewness1.1870946
Sum85895.7
Variance1480.2295
MonotonicityNot monotonic
2024-04-21T06:21:26.682216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 536
 
5.4%
100.0 526
 
5.3%
5.0 505
 
5.1%
2.0 419
 
4.2%
1.0 212
 
2.1%
3.0 181
 
1.8%
90.0 70
 
0.7%
4.0 69
 
0.7%
9.0 53
 
0.5%
80.0 52
 
0.5%
Other values (81) 456
 
4.6%
(Missing) 6921
69.2%
ValueCountFrequency (%)
0.0 16
 
0.2%
0.1 2
 
< 0.1%
0.2 1
 
< 0.1%
0.3 2
 
< 0.1%
0.4 2
 
< 0.1%
0.5 17
 
0.2%
0.7 1
 
< 0.1%
0.8 3
 
< 0.1%
0.9 9
 
0.1%
1.0 212
2.1%
ValueCountFrequency (%)
100.0 526
5.3%
98.0 2
 
< 0.1%
97.0 2
 
< 0.1%
96.0 2
 
< 0.1%
95.0 21
 
0.2%
94.0 2
 
< 0.1%
93.0 1
 
< 0.1%
92.0 2
 
< 0.1%
90.0 70
 
0.7%
89.0 1
 
< 0.1%

제출제목
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

첨부파일아이디_1
Text

MISSING 

Distinct55
Distinct (%)100.0%
Missing9945
Missing (%)99.5%
Memory size156.2 KiB
2024-04-21T06:21:27.347597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters1100
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)100.0%

Sample

1st row2021FILE000000154260
2nd row2021FILE000000219210
3rd row2021FILE000000213731
4th row2021FILE000000154585
5th row2022FILE000000252405
ValueCountFrequency (%)
2021file000000154260 1
 
1.8%
2021file000000156909 1
 
1.8%
2021file000000154254 1
 
1.8%
2021file000000200682 1
 
1.8%
2022file000000252412 1
 
1.8%
2021file000000200675 1
 
1.8%
2021file000000213711 1
 
1.8%
2022file000000255123 1
 
1.8%
2021file000000200646 1
 
1.8%
2021file000000219261 1
 
1.8%
Other values (45) 45
81.8%
2024-04-21T06:21:28.432203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 413
37.5%
2 181
16.5%
1 111
 
10.1%
F 55
 
5.0%
I 55
 
5.0%
L 55
 
5.0%
E 55
 
5.0%
5 41
 
3.7%
4 28
 
2.5%
6 27
 
2.5%
Other values (4) 79
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 880
80.0%
Uppercase Letter 220
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 413
46.9%
2 181
20.6%
1 111
 
12.6%
5 41
 
4.7%
4 28
 
3.2%
6 27
 
3.1%
7 23
 
2.6%
9 23
 
2.6%
3 19
 
2.2%
8 14
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
F 55
25.0%
I 55
25.0%
L 55
25.0%
E 55
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 880
80.0%
Latin 220
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 413
46.9%
2 181
20.6%
1 111
 
12.6%
5 41
 
4.7%
4 28
 
3.2%
6 27
 
3.1%
7 23
 
2.6%
9 23
 
2.6%
3 19
 
2.2%
8 14
 
1.6%
Latin
ValueCountFrequency (%)
F 55
25.0%
I 55
25.0%
L 55
25.0%
E 55
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 413
37.5%
2 181
16.5%
1 111
 
10.1%
F 55
 
5.0%
I 55
 
5.0%
L 55
 
5.0%
E 55
 
5.0%
5 41
 
3.7%
4 28
 
2.5%
6 27
 
2.5%
Other values (4) 79
 
7.2%

삭제여부_2
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing9788
Missing (%)97.9%
Memory size97.7 KiB
False
 
212
(Missing)
9788 
ValueCountFrequency (%)
False 212
 
2.1%
(Missing) 9788
97.9%
2024-04-21T06:21:28.784937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

피드백내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

과제제출아이디
Text

MISSING 

Distinct212
Distinct (%)100.0%
Missing9788
Missing (%)97.9%
Memory size156.2 KiB
2024-04-21T06:21:29.612891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters2968
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique212 ?
Unique (%)100.0%

Sample

1st rowRES_0000066700
2nd rowRES_0000045237
3rd rowRES_0000048732
4th rowRES_0000069326
5th rowRES_0000043905
ValueCountFrequency (%)
res_0000044285 1
 
0.5%
res_0000045415 1
 
0.5%
res_0000055491 1
 
0.5%
res_0000070246 1
 
0.5%
res_0000046578 1
 
0.5%
res_0000052792 1
 
0.5%
res_0000060959 1
 
0.5%
res_0000056323 1
 
0.5%
res_0000057134 1
 
0.5%
res_0000053247 1
 
0.5%
Other values (202) 202
95.3%
2024-04-21T06:21:30.788179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1111
37.4%
R 212
 
7.1%
E 212
 
7.1%
S 212
 
7.1%
_ 212
 
7.1%
5 188
 
6.3%
4 157
 
5.3%
6 136
 
4.6%
2 111
 
3.7%
3 100
 
3.4%
Other values (4) 317
 
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2120
71.4%
Uppercase Letter 636
 
21.4%
Connector Punctuation 212
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1111
52.4%
5 188
 
8.9%
4 157
 
7.4%
6 136
 
6.4%
2 111
 
5.2%
3 100
 
4.7%
7 99
 
4.7%
9 84
 
4.0%
8 70
 
3.3%
1 64
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
R 212
33.3%
E 212
33.3%
S 212
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2332
78.6%
Latin 636
 
21.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1111
47.6%
_ 212
 
9.1%
5 188
 
8.1%
4 157
 
6.7%
6 136
 
5.8%
2 111
 
4.8%
3 100
 
4.3%
7 99
 
4.2%
9 84
 
3.6%
8 70
 
3.0%
Latin
ValueCountFrequency (%)
R 212
33.3%
E 212
33.3%
S 212
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1111
37.4%
R 212
 
7.1%
E 212
 
7.1%
S 212
 
7.1%
_ 212
 
7.1%
5 188
 
6.3%
4 157
 
5.3%
6 136
 
4.6%
2 111
 
3.7%
3 100
 
3.4%
Other values (4) 317
 
10.7%

Sample

과제아이디과제제목첨부파일아이디분반삭제여부평가여부배점기준교과목코드제출종료일등록종료시간등록종료분제출시작일등록시작시간등록시작분학기주차학년도제출파일아이디제출내용삭제여부_1평가점수제출제목첨부파일아이디_1삭제여부_2피드백내용과제제출아이디
19011REP_00000013001주차 과제<NA>1NY100MAE2102019-07-01002019-06-17003120192019FILE000000031896<NA>N100.0<NA><NA><NA><NA><NA>
50142REP_00000037986주차 과제 문제2021FILE0000002157431NY100MAE4412021-10-2323502021-10-16002620212021FILE000000219077<NA>Y<NA><NA><NA><NA><NA><NA>
1671REP_0000001414실습일지<NA>1NN0MAE8102019-11-02002019-11-02002920192019FILE000000039474<NA>Y<NA><NA><NA><NA><NA><NA>
22823REP_0000000958W12-2<NA>1NN0MDE6852018-12-08002018-11-240021220182018FILE000000021314<NA>N<NA><NA><NA><NA><NA><NA>
49809REP_0000003821부가경로설정<NA>1NY3MDE8802021-10-1619302021-10-161802620212021FILE000000217452<NA>Y<NA><NA><NA><NA><NA><NA>
9032REP_0000000401[2차_이론평가_과제물]2017FILE0000000059731NN0MAE6952017-12-08002017-10-14002620172017FILE000000006130<NA>N<NA><NA><NA><NA><NA><NA>
48907REP_0000003372일반열처리 종류2021FILE0000001729472NY10MDE7052021-06-042302021-05-220011220212021FILE000000177583<NA>N9.0<NA><NA><NA><NA><NA>
15022REP_0000001893대학수학과제4 입니다.2020FILE0000000576921NY4MAE1252020-04-26002020-04-21001420202020FILE000000058374<NA>N<NA><NA><NA><NA><NA><NA>
63701REP_0000004269상호작용7<NA>1NN0MDE8502022-06-30002022-04-02001720222022FILE000000281723<NA>N<NA><NA><NA><NA><NA><NA>
38262REP_0000002176과제 제출(3주차)<NA>1NY10MAE4152020-07-25002020-07-18003320202020FILE000000078391<NA>N<NA><NA><NA><NA><NA><NA>
과제아이디과제제목첨부파일아이디분반삭제여부평가여부배점기준교과목코드제출종료일등록종료시간등록종료분제출시작일등록시작시간등록시작분학기주차학년도제출파일아이디제출내용삭제여부_1평가점수제출제목첨부파일아이디_1삭제여부_2피드백내용과제제출아이디
52574REP_0000003884[NCS_센서선정하기_강의자료종합 + 과제제출03]2021FILE0000002210631NN0MAE8552021-12-10002021-10-29002820212021FILE000000227043<NA>N<NA><NA><NA><NA><NA><NA>
37361REP_0000002162[3]코어금형실습2020FILE0000000773581NY5MDE6702020-07-11002020-07-11003120202020FILE000000077439<NA>N<NA><NA><NA><NA><NA><NA>
38182REP_0000001762과제_품질경영_week_01_서비스유형2020FILE0000000514301NY1SME7352020-03-31002020-03-21001120202020FILE000000053251<NA>N1.0<NA><NA><NA><NA><NA>
6521REP_0000001009W06 : 중간고사<NA>1NN0MDE7502019-01-05002019-01-05004220182019FILE000000022750<NA>N<NA><NA><NA><NA><NA><NA>
44143REP_000000341514주차 과제입니다.<NA>1NY2MDE5032021-06-12002021-06-050011420212021FILE000000178467<NA>N<NA><NA><NA><NA><NA><NA>
51246REP_00000038718주차 과제 문제2021FILE0000002201041NY100MAE4602021-11-0723502021-10-30002820212021FILE000000223256<NA>N100.0<NA><NA><NA><NA><NA>
50395REP_0000003602부저 부품라이브러리 작성 프로젝트 파일<NA>2NY10MAE4152021-07-1715402021-07-17003520212021FILE000000198218<NA>N<NA><NA><NA><NA><NA><NA>
30289REP_0000002610드릴지그의 리드나사 모델링 과제<NA>1NY2MDE5032020-11-04002020-10-31002820202020FILE000000100190<NA>N<NA><NA><NA><NA><NA><NA>
45831REP_0000003378EVM 을 통한 EVA 측정 및 예측<NA>1NN02910282021-05-2217502021-05-22173011220212021FILE000000173155<NA>N<NA><NA><NA><NA><NA><NA>
11037REP_0000000924과제52018FILE0000000201702NN0MAE8052018-11-03002018-10-20002720182018FILE000000020462<NA>N<NA><NA><NA><NA><NA><NA>