Overview

Dataset statistics

Number of variables14
Number of observations5160
Missing cells9754
Missing cells (%)13.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory619.9 KiB
Average record size in memory123.0 B

Variable types

Numeric7
Text2
Categorical5

Dataset

Description경남도립거창대학의 기본과목 공공데이터입니다. 과목코드별 과목명(한글 및 영문), 학점, 이론시간, 실습시간, 개설연도 등의 데이터를 포함하고 있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15097837

Alerts

패스여부 is highly overall correlated with 학점 and 2 other fieldsHigh correlation
대체과목3 is highly overall correlated with 과목코드 and 7 other fieldsHigh correlation
개설학기 is highly overall correlated with 폐기년도 and 2 other fieldsHigh correlation
폐기년도 is highly overall correlated with 학점 and 3 other fieldsHigh correlation
폐기학기 is highly overall correlated with 실습시간 and 2 other fieldsHigh correlation
과목코드 is highly overall correlated with 대체과목1 and 2 other fieldsHigh correlation
학점 is highly overall correlated with 폐기년도 and 2 other fieldsHigh correlation
이론시간 is highly overall correlated with 실습시간High correlation
실습시간 is highly overall correlated with 이론시간 and 2 other fieldsHigh correlation
개설연도 is highly overall correlated with 폐기년도 and 2 other fieldsHigh correlation
대체과목1 is highly overall correlated with 과목코드 and 3 other fieldsHigh correlation
대체과목2 is highly overall correlated with 과목코드 and 3 other fieldsHigh correlation
폐기년도 is highly imbalanced (94.9%)Imbalance
폐기학기 is highly imbalanced (99.3%)Imbalance
패스여부 is highly imbalanced (79.3%)Imbalance
대체과목3 is highly imbalanced (99.4%)Imbalance
대체과목1 has 4647 (90.1%) missing valuesMissing
대체과목2 has 5103 (98.9%) missing valuesMissing
과목코드 has unique valuesUnique
이론시간 has 1170 (22.7%) zerosZeros
실습시간 has 2535 (49.1%) zerosZeros

Reproduction

Analysis started2023-12-11 00:29:41.813807
Analysis finished2023-12-11 00:29:48.754032
Duration6.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

과목코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct5160
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean138938.63
Minimum11001
Maximum714002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.5 KiB
2023-12-11T09:29:48.843859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11001
5-th percentile14036.95
Q153035.75
median84028.5
Q3151002.25
95-th percentile534051.1
Maximum714002
Range703001
Interquartile range (IQR)97966.5

Descriptive statistics

Standard deviation149124.23
Coefficient of variation (CV)1.07331
Kurtosis2.7088161
Mean138938.63
Median Absolute Deviation (MAD)48985
Skewness1.9123275
Sum7.1692334 × 108
Variance2.2238035 × 1010
MonotonicityNot monotonic
2023-12-11T09:29:49.027795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74010 1
 
< 0.1%
224189 1
 
< 0.1%
224150 1
 
< 0.1%
224148 1
 
< 0.1%
224142 1
 
< 0.1%
224140 1
 
< 0.1%
224137 1
 
< 0.1%
224133 1
 
< 0.1%
224131 1
 
< 0.1%
223020 1
 
< 0.1%
Other values (5150) 5150
99.8%
ValueCountFrequency (%)
11001 1
< 0.1%
11002 1
< 0.1%
11003 1
< 0.1%
11004 1
< 0.1%
11005 1
< 0.1%
11006 1
< 0.1%
11007 1
< 0.1%
11008 1
< 0.1%
11009 1
< 0.1%
11010 1
< 0.1%
ValueCountFrequency (%)
714002 1
< 0.1%
714001 1
< 0.1%
713001 1
< 0.1%
711004 1
< 0.1%
711003 1
< 0.1%
711002 1
< 0.1%
711001 1
< 0.1%
584069 1
< 0.1%
584068 1
< 0.1%
584067 1
< 0.1%

과목명한글
Text

Distinct3065
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Memory size40.4 KiB
2023-12-11T09:29:49.351529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length6.7255814
Min length2

Characters and Unicode

Total characters34704
Distinct characters463
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2163 ?
Unique (%)41.9%

Sample

1st row현장실습
2nd row피부관리이론및실습Ⅲ
3rd row사진학Ⅱ
4th row사진학Ⅰ
5th row헤어디자인실습
ValueCountFrequency (%)
및 85
 
1.4%
ⅱ 67
 
1.1%
ⅰ 67
 
1.1%
cad 50
 
0.8%
linc 47
 
0.8%
현장실습 40
 
0.7%
실습 36
 
0.6%
현장실습ⅰ 29
 
0.5%
직업윤리 24
 
0.4%
현장실습ⅱ 22
 
0.4%
Other values (3027) 5478
92.1%
2023-12-11T09:29:49.862743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
실 1269
 
3.7%
습 854
 
2.5%
학 847
 
2.4%
805
 
2.3%
기 696
 
2.0%
Ⅰ 647
 
1.9%
Ⅱ 587
 
1.7%
어 558
 
1.6%
인 556
 
1.6%
리 554
 
1.6%
Other values (453) 27331
78.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28433
81.9%
Uppercase Letter 2361
 
6.8%
Letter Number 1451
 
4.2%
Space Separator 805
 
2.3%
Lowercase Letter 695
 
2.0%
Open Punctuation 335
 
1.0%
Close Punctuation 335
 
1.0%
Decimal Number 160
 
0.5%
Dash Punctuation 96
 
0.3%
Other Punctuation 29
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 1269
 
4.5%
습 854
 
3.0%
학 847
 
3.0%
기 696
 
2.4%
어 558
 
2.0%
인 556
 
2.0%
리 554
 
1.9%
자 499
 
1.8%
계 466
 
1.6%
사 435
 
1.5%
Other values (382) 21699
76.3%
Uppercase Letter
ValueCountFrequency (%)
C 383
16.2%
I 349
14.8%
A 224
9.5%
D 204
 
8.6%
L 128
 
5.4%
N 121
 
5.1%
R 121
 
5.1%
T 118
 
5.0%
P 103
 
4.4%
B 98
 
4.2%
Other values (15) 512
21.7%
Lowercase Letter
ValueCountFrequency (%)
e 122
17.6%
n 66
9.5%
r 64
 
9.2%
i 63
 
9.1%
t 44
 
6.3%
o 41
 
5.9%
s 36
 
5.2%
g 35
 
5.0%
l 31
 
4.5%
a 30
 
4.3%
Other values (13) 163
23.5%
Decimal Number
ValueCountFrequency (%)
3 63
39.4%
1 42
26.2%
2 29
18.1%
4 12
 
7.5%
9 8
 
5.0%
8 4
 
2.5%
5 2
 
1.2%
Letter Number
ValueCountFrequency (%)
Ⅰ 647
44.6%
Ⅱ 587
40.5%
Ⅲ 151
 
10.4%
Ⅳ 36
 
2.5%
Ⅴ 26
 
1.8%
Ⅵ 4
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 14
48.3%
. 9
31.0%
# 3
 
10.3%
& 2
 
6.9%
· 1
 
3.4%
Space Separator
ValueCountFrequency (%)
805
100.0%
Open Punctuation
ValueCountFrequency (%)
( 335
100.0%
Close Punctuation
ValueCountFrequency (%)
) 335
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28433
81.9%
Latin 4507
 
13.0%
Common 1764
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 1269
 
4.5%
습 854
 
3.0%
학 847
 
3.0%
기 696
 
2.4%
어 558
 
2.0%
인 556
 
2.0%
리 554
 
1.9%
자 499
 
1.8%
계 466
 
1.6%
사 435
 
1.5%
Other values (382) 21699
76.3%
Latin
ValueCountFrequency (%)
Ⅰ 647
14.4%
Ⅱ 587
 
13.0%
C 383
 
8.5%
I 349
 
7.7%
A 224
 
5.0%
D 204
 
4.5%
Ⅲ 151
 
3.4%
L 128
 
2.8%
e 122
 
2.7%
N 121
 
2.7%
Other values (44) 1591
35.3%
Common
ValueCountFrequency (%)
805
45.6%
( 335
19.0%
) 335
19.0%
- 96
 
5.4%
3 63
 
3.6%
1 42
 
2.4%
2 29
 
1.6%
/ 14
 
0.8%
4 12
 
0.7%
. 9
 
0.5%
Other values (7) 24
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28433
81.9%
ASCII 4819
 
13.9%
Number Forms 1451
 
4.2%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
실 1269
 
4.5%
습 854
 
3.0%
학 847
 
3.0%
기 696
 
2.4%
어 558
 
2.0%
인 556
 
2.0%
리 554
 
1.9%
자 499
 
1.8%
계 466
 
1.6%
사 435
 
1.5%
Other values (382) 21699
76.3%
ASCII
ValueCountFrequency (%)
805
16.7%
C 383
 
7.9%
I 349
 
7.2%
( 335
 
7.0%
) 335
 
7.0%
A 224
 
4.6%
D 204
 
4.2%
L 128
 
2.7%
e 122
 
2.5%
N 121
 
2.5%
Other values (54) 1813
37.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 647
44.6%
Ⅱ 587
40.5%
Ⅲ 151
 
10.4%
Ⅳ 36
 
2.5%
Ⅴ 26
 
1.8%
Ⅵ 4
 
0.3%
None
ValueCountFrequency (%)
· 1
100.0%

과목명영문
Text

Distinct3345
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Memory size40.4 KiB
2023-12-11T09:29:50.169899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40
Mean length22.689922
Min length2

Characters and Unicode

Total characters117080
Distinct characters82
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2476 ?
Unique (%)48.0%

Sample

1st rowJob Training
2nd rowTheory and Practice for CosmeticⅢ
3rd rowPhotographic PracticeⅡ
4th rowPhotographic PracticeⅠ
5th rowHair Design Practice
ValueCountFrequency (%)
practice 580
 
3.7%
of 461
 
3.0%
and 414
 
2.7%
design 387
 
2.5%
331
 
2.1%
ⅱ 314
 
2.0%
computer 255
 
1.6%
english 246
 
1.6%
ⅰ 238
 
1.5%
nursing 207
 
1.3%
Other values (1590) 12042
77.8%
2023-12-11T09:29:50.613047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10624
 
9.1%
i 10453
 
8.9%
e 9321
 
8.0%
n 8947
 
7.6%
a 7718
 
6.6%
t 7495
 
6.4%
r 7227
 
6.2%
o 6093
 
5.2%
c 6025
 
5.1%
s 4331
 
3.7%
Other values (72) 38846
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 91131
77.8%
Uppercase Letter 12896
 
11.0%
Space Separator 10624
 
9.1%
Letter Number 1270
 
1.1%
Other Punctuation 400
 
0.3%
Dash Punctuation 227
 
0.2%
Close Punctuation 179
 
0.2%
Open Punctuation 179
 
0.2%
Decimal Number 159
 
0.1%
Connector Punctuation 7
 
< 0.1%
Other values (3) 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 10453
11.5%
e 9321
10.2%
n 8947
9.8%
a 7718
 
8.5%
t 7495
 
8.2%
r 7227
 
7.9%
o 6093
 
6.7%
c 6025
 
6.6%
s 4331
 
4.8%
l 3960
 
4.3%
Other values (16) 19561
21.5%
Uppercase Letter
ValueCountFrequency (%)
P 1620
12.6%
C 1535
11.9%
E 1186
9.2%
A 1072
 
8.3%
I 1006
 
7.8%
D 970
 
7.5%
S 819
 
6.4%
M 702
 
5.4%
T 664
 
5.1%
N 423
 
3.3%
Other values (15) 2899
22.5%
Other Punctuation
ValueCountFrequency (%)
& 341
85.2%
' 26
 
6.5%
/ 15
 
3.8%
. 10
 
2.5%
? 4
 
1.0%
# 3
 
0.8%
？ 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
3 65
40.9%
1 40
25.2%
2 28
17.6%
4 12
 
7.5%
9 8
 
5.0%
8 4
 
2.5%
5 2
 
1.3%
Letter Number
ValueCountFrequency (%)
Ⅰ 534
42.0%
Ⅱ 524
41.3%
Ⅲ 144
 
11.3%
Ⅳ 36
 
2.8%
Ⅴ 27
 
2.1%
Ⅵ 5
 
0.4%
Other Letter
ValueCountFrequency (%)
수 1
25.0%
리 1
25.0%
능 1
25.0%
력 1
25.0%
Space Separator
ValueCountFrequency (%)
10624
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 227
100.0%
Close Punctuation
ValueCountFrequency (%)
) 179
100.0%
Open Punctuation
ValueCountFrequency (%)
( 179
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Other Symbol
ValueCountFrequency (%)
® 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 105297
89.9%
Common 11779
 
10.1%
Hangul 4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 10453
 
9.9%
e 9321
 
8.9%
n 8947
 
8.5%
a 7718
 
7.3%
t 7495
 
7.1%
r 7227
 
6.9%
o 6093
 
5.8%
c 6025
 
5.7%
s 4331
 
4.1%
l 3960
 
3.8%
Other values (47) 33727
32.0%
Common
ValueCountFrequency (%)
10624
90.2%
& 341
 
2.9%
- 227
 
1.9%
) 179
 
1.5%
( 179
 
1.5%
3 65
 
0.6%
1 40
 
0.3%
2 28
 
0.2%
' 26
 
0.2%
/ 15
 
0.1%
Other values (11) 55
 
0.5%
Hangul
ValueCountFrequency (%)
수 1
25.0%
리 1
25.0%
능 1
25.0%
력 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115803
98.9%
Number Forms 1270
 
1.1%
Hangul 4
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10624
 
9.2%
i 10453
 
9.0%
e 9321
 
8.0%
n 8947
 
7.7%
a 7718
 
6.7%
t 7495
 
6.5%
r 7227
 
6.2%
o 6093
 
5.3%
c 6025
 
5.2%
s 4331
 
3.7%
Other values (60) 37569
32.4%
Number Forms
ValueCountFrequency (%)
Ⅰ 534
42.0%
Ⅱ 524
41.3%
Ⅲ 144
 
11.3%
Ⅳ 36
 
2.8%
Ⅴ 27
 
2.1%
Ⅵ 5
 
0.4%
None
ValueCountFrequency (%)
® 2
66.7%
？ 1
33.3%
Hangul
ValueCountFrequency (%)
수 1
25.0%
리 1
25.0%
능 1
25.0%
력 1
25.0%

학점
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4693798
Minimum0
Maximum43
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size45.5 KiB
2023-12-11T09:29:50.738627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q12
median2
Q33
95-th percentile3
Maximum43
Range43
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.50731
Coefficient of variation (CV)0.61040021
Kurtosis168.60239
Mean2.4693798
Median Absolute Deviation (MAD)0
Skewness10.518646
Sum12742
Variance2.2719833
MonotonicityNot monotonic
2023-12-11T09:29:50.871640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 3006
58.3%
3 1786
34.6%
1 234
 
4.5%
5 51
 
1.0%
4 28
 
0.5%
9 22
 
0.4%
18 15
 
0.3%
19 6
 
0.1%
20 5
 
0.1%
43 1
 
< 0.1%
Other values (6) 6
 
0.1%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 234
 
4.5%
2 3006
58.3%
3 1786
34.6%
4 28
 
0.5%
5 51
 
1.0%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 22
 
0.4%
ValueCountFrequency (%)
43 1
 
< 0.1%
20 5
 
0.1%
19 6
 
0.1%
18 15
0.3%
15 1
 
< 0.1%
10 1
 
< 0.1%
9 22
0.4%
8 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%

이론시간
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4368217
Minimum0
Maximum6
Zeros1170
Zeros (%)22.7%
Negative0
Negative (%)0.0%
Memory size45.5 KiB
2023-12-11T09:29:50.971079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q32
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.98184764
Coefficient of variation (CV)0.68334689
Kurtosis-0.89913959
Mean1.4368217
Median Absolute Deviation (MAD)1
Skewness-0.092510504
Sum7414
Variance0.96402479
MonotonicityNot monotonic
2023-12-11T09:29:51.061398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 2120
41.1%
1 1227
23.8%
0 1170
22.7%
3 627
 
12.2%
4 15
 
0.3%
6 1
 
< 0.1%
ValueCountFrequency (%)
0 1170
22.7%
1 1227
23.8%
2 2120
41.1%
3 627
 
12.2%
4 15
 
0.3%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
4 15
 
0.3%
3 627
 
12.2%
2 2120
41.1%
1 1227
23.8%
0 1170
22.7%

실습시간
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2300388
Minimum0
Maximum40
Zeros2535
Zeros (%)49.1%
Negative0
Negative (%)0.0%
Memory size45.5 KiB
2023-12-11T09:29:51.166643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum40
Range40
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8744228
Coefficient of variation (CV)1.5238729
Kurtosis117.44266
Mean1.2300388
Median Absolute Deviation (MAD)1
Skewness7.1898441
Sum6347
Variance3.5134607
MonotonicityNot monotonic
2023-12-11T09:29:51.264111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 2535
49.1%
2 1641
31.8%
1 369
 
7.2%
3 321
 
6.2%
4 185
 
3.6%
6 57
 
1.1%
10 34
 
0.7%
18 6
 
0.1%
8 3
 
0.1%
40 3
 
0.1%
Other values (3) 6
 
0.1%
ValueCountFrequency (%)
0 2535
49.1%
1 369
 
7.2%
2 1641
31.8%
3 321
 
6.2%
4 185
 
3.6%
5 3
 
0.1%
6 57
 
1.1%
8 3
 
0.1%
10 34
 
0.7%
12 2
 
< 0.1%
ValueCountFrequency (%)
40 3
 
0.1%
20 1
 
< 0.1%
18 6
 
0.1%
12 2
 
< 0.1%
10 34
 
0.7%
8 3
 
0.1%
6 57
 
1.1%
5 3
 
0.1%
4 185
3.6%
3 321
6.2%

개설연도
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)0.5%
Missing4
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2010.3206
Minimum1996
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.5 KiB
2023-12-11T09:29:51.389518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1996
5-th percentile1998
Q12003
median2011
Q32017
95-th percentile2022
Maximum2023
Range27
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.0499297
Coefficient of variation (CV)0.0040043015
Kurtosis-1.2419988
Mean2010.3206
Median Absolute Deviation (MAD)7
Skewness-0.16879802
Sum10365213
Variance64.801368
MonotonicityNot monotonic
2023-12-11T09:29:51.524955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1998 313
 
6.1%
2020 254
 
4.9%
2012 248
 
4.8%
2004 248
 
4.8%
2013 236
 
4.6%
2000 233
 
4.5%
2019 233
 
4.5%
2021 232
 
4.5%
1997 222
 
4.3%
2017 216
 
4.2%
Other values (18) 2721
52.7%
ValueCountFrequency (%)
1996 14
 
0.3%
1997 222
4.3%
1998 313
6.1%
1999 178
3.4%
2000 233
4.5%
2001 101
 
2.0%
2002 93
 
1.8%
2003 167
3.2%
2004 248
4.8%
2005 83
 
1.6%
ValueCountFrequency (%)
2023 142
2.8%
2022 202
3.9%
2021 232
4.5%
2020 254
4.9%
2019 233
4.5%
2018 211
4.1%
2017 216
4.2%
2016 158
3.1%
2015 215
4.2%
2014 215
4.2%

개설학기
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.4 KiB
1
2709 
2
2436 
3
 
10
<NA>
 
5

Length

Max length4
Median length1
Mean length1.002907
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 2709
52.5%
2 2436
47.2%
3 10
 
0.2%
<NA> 5
 
0.1%

Length

2023-12-11T09:29:51.645576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:51.739053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2709
52.5%
2 2436
47.2%
3 10
 
0.2%
na 5
 
0.1%

폐기년도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.4 KiB
<NA>
5109 
0
 
50
2018
 
1

Length

Max length4
Median length4
Mean length3.9709302
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5109
99.0%
0 50
 
1.0%
2018 1
 
< 0.1%

Length

2023-12-11T09:29:51.844799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:51.933510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5109
99.0%
0 50
 
1.0%
2018 1
 
< 0.1%

폐기학기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.4 KiB
<NA>
5155 
0
 
4
2
 
1

Length

Max length4
Median length4
Mean length3.997093
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5155
99.9%
0 4
 
0.1%
2 1
 
< 0.1%

Length

2023-12-11T09:29:52.032659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:52.124541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5155
99.9%
0 4
 
0.1%
2 1
 
< 0.1%

패스여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.4 KiB
9
4992 
P
 
168

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowP
2nd row9
3rd row9
4th row9
5th row9

Common Values

ValueCountFrequency (%)
9 4992
96.7%
P 168
 
3.3%

Length

2023-12-11T09:29:52.226665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:52.317408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9 4992
96.7%
p 168
 
3.3%

대체과목1
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct407
Distinct (%)79.3%
Missing4647
Missing (%)90.1%
Infinite0
Infinite (%)0.0%
Mean89263.865
Minimum11029
Maximum311010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.5 KiB
2023-12-11T09:29:52.418452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11029
5-th percentile14103
Q151038
median74197
Q3124036
95-th percentile224153
Maximum311010
Range299981
Interquartile range (IQR)72998

Descriptive statistics

Standard deviation57428.761
Coefficient of variation (CV)0.64335956
Kurtosis0.59095135
Mean89263.865
Median Absolute Deviation (MAD)39843
Skewness0.87678955
Sum45792363
Variance3.2980626 × 109
MonotonicityNot monotonic
2023-12-11T09:29:52.551944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
133020 4
 
0.1%
14109 4
 
0.1%
94150 3
 
0.1%
124045 3
 
0.1%
224165 3
 
0.1%
51039 3
 
0.1%
14124 3
 
0.1%
44228 3
 
0.1%
54167 3
 
0.1%
94151 3
 
0.1%
Other values (397) 481
 
9.3%
(Missing) 4647
90.1%
ValueCountFrequency (%)
11029 1
 
< 0.1%
11034 1
 
< 0.1%
11035 1
 
< 0.1%
11036 1
 
< 0.1%
11039 2
< 0.1%
11042 1
 
< 0.1%
14003 1
 
< 0.1%
14016 3
0.1%
14031 1
 
< 0.1%
14039 1
 
< 0.1%
ValueCountFrequency (%)
311010 1
< 0.1%
224191 1
< 0.1%
224183 1
< 0.1%
224181 1
< 0.1%
224179 1
< 0.1%
224178 1
< 0.1%
224172 1
< 0.1%
224170 1
< 0.1%
224169 1
< 0.1%
224168 2
< 0.1%

대체과목2
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct51
Distinct (%)89.5%
Missing5103
Missing (%)98.9%
Infinite0
Infinite (%)0.0%
Mean80950.86
Minimum11012
Maximum311010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.5 KiB
2023-12-11T09:29:52.684947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11012
5-th percentile11038.4
Q114132
median74166
Q3114078
95-th percentile221655.6
Maximum311010
Range299998
Interquartile range (IQR)99946

Descriptive statistics

Standard deviation66162.989
Coefficient of variation (CV)0.81732287
Kurtosis1.5402079
Mean80950.86
Median Absolute Deviation (MAD)59893
Skewness1.0728438
Sum4614199
Variance4.3775411 × 109
MonotonicityNot monotonic
2023-12-11T09:29:52.828383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14095 2
 
< 0.1%
14154 2
 
< 0.1%
14035 2
 
< 0.1%
114077 2
 
< 0.1%
14131 2
 
< 0.1%
54226 2
 
< 0.1%
14132 1
 
< 0.1%
124058 1
 
< 0.1%
114059 1
 
< 0.1%
221028 1
 
< 0.1%
Other values (41) 41
 
0.8%
(Missing) 5103
98.9%
ValueCountFrequency (%)
11012 1
< 0.1%
11030 1
< 0.1%
11032 1
< 0.1%
11040 1
< 0.1%
14016 1
< 0.1%
14029 1
< 0.1%
14035 2
< 0.1%
14095 2
< 0.1%
14105 1
< 0.1%
14130 1
< 0.1%
ValueCountFrequency (%)
311010 1
< 0.1%
224168 1
< 0.1%
224166 1
< 0.1%
221028 1
< 0.1%
144096 1
< 0.1%
144092 1
< 0.1%
144031 1
< 0.1%
144013 1
< 0.1%
141001 1
< 0.1%
134059 1
< 0.1%

대체과목3
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.4 KiB
<NA>
5155 
14105
 
2
134025
 
1
11038
 
1
11034
 
1

Length

Max length6
Median length4
Mean length4.0011628
Min length4

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5155
99.9%
14105 2
 
< 0.1%
134025 1
 
< 0.1%
11038 1
 
< 0.1%
11034 1
 
< 0.1%

Length

2023-12-11T09:29:52.988165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:29:53.092653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5155
99.9%
14105 2
 
< 0.1%
134025 1
 
< 0.1%
11038 1
 
< 0.1%
11034 1
 
< 0.1%

Interactions

2023-12-11T09:29:47.617992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:42.866997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.492526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:44.114075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:44.908181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:45.736798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:46.547983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:47.732655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:42.947492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.577894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:44.220018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:45.038458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:45.861704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:46.667364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:47.825720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.024505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.653600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:44.355706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:45.148309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:45.982235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:46.792476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:47.909689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.114794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.735838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:44.450165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:45.265779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:46.103626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:47.192717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:48.011418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.228500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.824462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:44.577544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:45.398109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:46.224945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:47.295432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:48.100725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.333095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.910485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:44.679155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:45.526772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:46.352707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:47.398727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:48.173859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:43.416036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:44.018663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:44.784628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:45.631207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:46.448787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:29:47.528461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:29:53.420713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과목코드학점이론시간실습시간개설연도개설학기폐기년도폐기학기패스여부대체과목1대체과목2대체과목3
과목코드1.0000.0000.3320.0710.4350.0970.0000.0000.0450.7850.8751.000
학점0.0001.0000.3330.4980.1180.1971.0000.0000.8290.000NaNNaN
이론시간0.3320.3331.0000.3400.2350.0790.0510.0000.4610.2850.2380.416
실습시간0.0710.4980.3401.0000.1140.0670.000NaN0.4550.118NaNNaN
개설연도0.4350.1180.2350.1141.0000.205NaNNaN0.1270.2470.2841.000
개설학기0.0970.1970.0790.0670.2051.000NaNNaN0.0800.0340.000NaN
폐기년도0.0001.0000.0510.000NaNNaN1.0000.0000.350NaNNaNNaN
폐기학기0.0000.0000.000NaNNaNNaN0.0001.0000.000NaNNaNNaN
패스여부0.0450.8290.4610.4550.1270.0800.3500.0001.0000.020NaNNaN
대체과목10.7850.0000.2850.1180.2470.034NaNNaN0.0201.0000.9571.000
대체과목20.875NaN0.238NaN0.2840.000NaNNaNNaN0.9571.0001.000
대체과목31.000NaN0.416NaN1.000NaNNaNNaNNaN1.0001.0001.000
2023-12-11T09:29:53.558682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
패스여부대체과목3개설학기폐기년도폐기학기
패스여부1.0001.0000.1330.2270.000
대체과목31.0001.0001.000NaNNaN
개설학기0.1331.0001.0001.0001.000
폐기년도0.227NaN1.0001.0000.000
폐기학기0.000NaN1.0000.0001.000
2023-12-11T09:29:53.658292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과목코드학점이론시간실습시간개설연도대체과목1대체과목2개설학기폐기년도폐기학기패스여부대체과목3
과목코드1.0000.0290.053-0.0630.0870.9690.9050.0420.0000.0000.0450.577
학점0.0291.0000.2680.162-0.0000.1540.2340.0830.9900.0000.6331.000
이론시간0.0530.2681.000-0.633-0.1660.0040.1020.0320.0450.0000.3320.000
실습시간-0.0630.162-0.6331.0000.0800.061-0.0030.0710.0001.0000.4931.000
개설연도0.087-0.000-0.1660.0801.0000.063-0.2050.1241.0001.0000.0980.577
대체과목10.9690.1540.0040.0610.0631.0000.8960.0331.0000.0000.0200.707
대체과목20.9050.2340.102-0.003-0.2050.8961.0000.0000.0000.0001.0000.577
개설학기0.0420.0830.0320.0710.1240.0330.0001.0001.0001.0000.1331.000
폐기년도0.0000.9900.0450.0001.0001.0000.0001.0001.0000.0000.2270.000
폐기학기0.0000.0000.0001.0001.0000.0000.0001.0000.0001.0000.0000.000
패스여부0.0450.6330.3320.4930.0980.0201.0000.1330.2270.0001.0001.000
대체과목30.5771.0000.0001.0000.5770.7070.5771.0000.0000.0001.0001.000

Missing values

2023-12-11T09:29:48.316714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:29:48.493692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T09:29:48.659621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

과목코드과목명한글과목명영문학점이론시간실습시간개설연도개설학기폐기년도폐기학기패스여부대체과목1대체과목2대체과목3
074010현장실습Job Training20019982<NA><NA>P<NA><NA><NA>
174011피부관리이론및실습ⅢTheory and Practice for CosmeticⅢ32219971<NA><NA>9<NA><NA><NA>
274012사진학ⅡPhotographic PracticeⅡ21219981<NA><NA>9<NA><NA><NA>
374013사진학ⅠPhotographic PracticeⅠ20019982<NA><NA>9<NA><NA><NA>
474014헤어디자인실습Hair Design Practice21219982<NA><NA>9<NA><NA><NA>
574015염색과탈색Hair Tint and Bleach32219971<NA><NA>9<NA><NA><NA>
674016메니큐어및페디큐어ⅡManicure and PadycureⅡ21219982<NA><NA>9<NA><NA><NA>
774017경락요법Meridian Point Therapy21219981<NA><NA>9<NA><NA><NA>
874018발관리Foot Treatment22019982<NA><NA>9<NA><NA><NA>
974019색채학Coloring33019981<NA><NA>9<NA><NA><NA>
과목코드과목명한글과목명영문학점이론시간실습시간개설연도개설학기폐기년도폐기학기패스여부대체과목1대체과목2대체과목3
5150311057의사소통영어(T-3)Communication English(T-3)22020211<NA><NA>9<NA><NA><NA>
5151311060의사소통영어(R-3)Communication English(R-3)22020211<NA><NA>9<NA><NA><NA>
5152311062의사소통영어(H-1)Communication English(H-1)22020211<NA><NA>9<NA><NA><NA>
5153311065종교의이해understanding of religion22020211<NA><NA>9<NA><NA><NA>
5154311077의사소통영어(B)Communication English22020221<NA><NA>9<NA><NA><NA>
5155311080의사소통영어(E)Communication English22020221<NA><NA>9<NA><NA><NA>
5156311086문제해결및정보능력(A)Problem-solving and information skills22020222<NA><NA>9<NA><NA><NA>
5157311089문제해결및정보능력(D)Problem-solving and information skills22020222<NA><NA>9<NA><NA><NA>
5158711003미술치료(학점교류)art therapy22020211<NA><NA>9<NA><NA><NA>
5159111031대인관계능력interpersonal skills22020172<NA><NA>9<NA><NA><NA>