Overview

Dataset statistics

Number of variables13
Number of observations2812
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory291.2 KiB
Average record size in memory106.0 B

Variable types

Categorical8
Text4
Numeric1

Dataset

Description대학특성화 종합정보(2019년도 이후 데이터 다운로드 가능)
Author교육부
URLhttps://www.data.go.kr/data/3038869/fileData.do

Alerts

조사년도 has constant value ""Constant
상태 has constant value ""Constant
학교종류 is highly overall correlated with 구분1High correlation
구분1 is highly overall correlated with 학교종류High correlation
학교종류 is highly imbalanced (83.0%)Imbalance
설립구분 is highly imbalanced (57.3%)Imbalance
구분1 is highly imbalanced (83.0%)Imbalance
학과특성 is highly imbalanced (97.4%)Imbalance

Reproduction

Analysis started2023-12-12 21:49:13.442480
Analysis finished2023-12-12 21:49:14.979136
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조사년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2018
2812 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 2812
100.0%

Length

2023-12-13T06:49:15.054233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:49:15.164068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 2812
100.0%

학교종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
대학교
2679 
사이버대학(대학)
 
70
교육대학
 
46
산업대학
 
17

Length

Max length9
Median length3
Mean length3.1717639
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대학교
2nd row대학교
3rd row대학교
4th row대학교
5th row대학교

Common Values

ValueCountFrequency (%)
대학교 2679
95.3%
사이버대학(대학) 70
 
2.5%
교육대학 46
 
1.6%
산업대학 17
 
0.6%

Length

2023-12-13T06:49:15.270604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:49:15.384754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대학교 2679
95.3%
사이버대학(대학 70
 
2.5%
교육대학 46
 
1.6%
산업대학 17
 
0.6%

설립구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
사립
2156 
국립
627 
국립대법인
 
21
공립
 
8

Length

Max length5
Median length2
Mean length2.022404
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사립
2nd row사립
3rd row사립
4th row사립
5th row사립

Common Values

ValueCountFrequency (%)
사립 2156
76.7%
국립 627
 
22.3%
국립대법인 21
 
0.7%
공립 8
 
0.3%

Length

2023-12-13T06:49:15.524974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:49:15.667140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 2156
76.7%
국립 627
 
22.3%
국립대법인 21
 
0.7%
공립 8
 
0.3%

지역
Categorical

Distinct16
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
서울
496 
경북
285 
충남
278 
부산
245 
경기
233 
Other values (11)
1275 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경남
2nd row경남
3rd row경남
4th row경남
5th row경기

Common Values

ValueCountFrequency (%)
서울 496
17.6%
경북 285
10.1%
충남 278
9.9%
부산 245
8.7%
경기 233
8.3%
충북 218
7.8%
강원 174
 
6.2%
대전 154
 
5.5%
전북 150
 
5.3%
경남 117
 
4.2%
Other values (6) 462
16.4%

Length

2023-12-13T06:49:15.808180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 496
17.6%
경북 285
10.1%
충남 278
9.9%
부산 245
8.7%
경기 233
8.3%
충북 218
7.8%
강원 174
 
6.2%
대전 154
 
5.5%
전북 150
 
5.3%
경남 117
 
4.2%
Other values (6) 462
16.4%

상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
기존
2812 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기존
2nd row기존
3rd row기존
4th row기존
5th row기존

Common Values

ValueCountFrequency (%)
기존 2812
100.0%

Length

2023-12-13T06:49:15.951640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:49:16.058507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기존 2812
100.0%

학교
Text

Distinct188
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2023-12-13T06:49:16.325604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length5
Mean length5.9914651
Min length5

Characters and Unicode

Total characters16848
Distinct characters155
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row가야대학교(김해)
2nd row가야대학교(김해)
3rd row가야대학교(김해)
4th row가야대학교(김해)
5th row가천대학교
ValueCountFrequency (%)
제2캠퍼스 93
 
3.1%
대구가톨릭대학교 72
 
2.4%
한림대학교 71
 
2.4%
목포대학교 66
 
2.2%
분교 65
 
2.2%
제주대학교 62
 
2.1%
계명대학교 62
 
2.1%
성균관대학교 55
 
1.8%
공주대학교 48
 
1.6%
동의대학교 47
 
1.6%
Other values (167) 2336
78.5%
2023-12-13T06:49:16.767291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 2974
17.7%
대 2972
17.6%
학 2838
16.8%
한 419
 
2.5%
국 306
 
1.8%
경 292
 
1.7%
주 284
 
1.7%
원 230
 
1.4%
동 207
 
1.2%
제 197
 
1.2%
Other values (145) 6129
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16215
96.2%
Space Separator 165
 
1.0%
Connector Punctuation 165
 
1.0%
Decimal Number 100
 
0.6%
Open Punctuation 69
 
0.4%
Close Punctuation 69
 
0.4%
Uppercase Letter 65
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 2974
18.3%
대 2972
18.3%
학 2838
17.5%
한 419
 
2.6%
국 306
 
1.9%
경 292
 
1.8%
주 284
 
1.8%
원 230
 
1.4%
동 207
 
1.3%
제 197
 
1.2%
Other values (133) 5496
33.9%
Uppercase Letter
ValueCountFrequency (%)
E 13
20.0%
I 13
20.0%
A 13
20.0%
C 13
20.0%
R 13
20.0%
Decimal Number
ValueCountFrequency (%)
2 93
93.0%
4 4
 
4.0%
3 3
 
3.0%
Space Separator
ValueCountFrequency (%)
165
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 165
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16215
96.2%
Common 568
 
3.4%
Latin 65
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 2974
18.3%
대 2972
18.3%
학 2838
17.5%
한 419
 
2.6%
국 306
 
1.9%
경 292
 
1.8%
주 284
 
1.8%
원 230
 
1.4%
동 207
 
1.3%
제 197
 
1.2%
Other values (133) 5496
33.9%
Common
ValueCountFrequency (%)
165
29.0%
_ 165
29.0%
2 93
16.4%
( 69
12.1%
) 69
12.1%
4 4
 
0.7%
3 3
 
0.5%
Latin
ValueCountFrequency (%)
E 13
20.0%
I 13
20.0%
A 13
20.0%
C 13
20.0%
R 13
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16215
96.2%
ASCII 633
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 2974
18.3%
대 2972
18.3%
학 2838
17.5%
한 419
 
2.6%
국 306
 
1.9%
경 292
 
1.8%
주 284
 
1.8%
원 230
 
1.4%
동 207
 
1.3%
제 197
 
1.2%
Other values (133) 5496
33.9%
ASCII
ValueCountFrequency (%)
165
26.1%
_ 165
26.1%
2 93
14.7%
( 69
10.9%
) 69
10.9%
E 13
 
2.1%
I 13
 
2.1%
A 13
 
2.1%
C 13
 
2.1%
R 13
 
2.1%
Other values (2) 7
 
1.1%

단과대학
Text

Distinct231
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2023-12-13T06:49:17.083524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length12
Mean length5.9139403
Min length4

Characters and Unicode

Total characters16630
Distinct characters205
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)1.1%

Sample

1st row단과대구분없음
2nd row단과대구분없음
3rd row단과대구분없음
4th row단과대구분없음
5th row바이오나노대학
ValueCountFrequency (%)
단과대구분없음 457
 
16.0%
공과대학 350
 
12.3%
사회과학대학 141
 
4.9%
자연과학대학 138
 
4.8%
사범대학 90
 
3.2%
인문대학 85
 
3.0%
경영대학 71
 
2.5%
예술대학 54
 
1.9%
과학기술대학 39
 
1.4%
문과대학 36
 
1.3%
Other values (225) 1390
48.8%
2023-12-13T06:49:17.512945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 3010
18.1%
대 2780
16.7%
과 1576
 
9.5%
공 531
 
3.2%
음 470
 
2.8%
단 457
 
2.7%
구 457
 
2.7%
분 457
 
2.7%
없 457
 
2.7%
사 291
 
1.7%
Other values (195) 6144
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16060
96.6%
Uppercase Letter 346
 
2.1%
Lowercase Letter 153
 
0.9%
Space Separator 39
 
0.2%
Decimal Number 24
 
0.1%
Other Punctuation 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 3010
18.7%
대 2780
17.3%
과 1576
 
9.8%
공 531
 
3.3%
음 470
 
2.9%
단 457
 
2.8%
구 457
 
2.8%
분 457
 
2.8%
없 457
 
2.8%
사 291
 
1.8%
Other values (165) 5574
34.7%
Uppercase Letter
ValueCountFrequency (%)
I 95
27.5%
T 85
24.6%
C 42
12.1%
H 40
11.6%
M 14
 
4.0%
R 10
 
2.9%
E 10
 
2.9%
P 10
 
2.9%
S 9
 
2.6%
B 8
 
2.3%
Other values (4) 23
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
s 35
22.9%
a 31
20.3%
n 31
20.3%
e 20
13.1%
l 20
13.1%
g 4
 
2.6%
o 4
 
2.6%
h 4
 
2.6%
t 4
 
2.6%
Decimal Number
ValueCountFrequency (%)
3 9
37.5%
2 9
37.5%
1 3
 
12.5%
4 3
 
12.5%
Space Separator
ValueCountFrequency (%)
39
100.0%
Other Punctuation
ValueCountFrequency (%)
& 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16060
96.6%
Latin 499
 
3.0%
Common 71
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 3010
18.7%
대 2780
17.3%
과 1576
 
9.8%
공 531
 
3.3%
음 470
 
2.9%
단 457
 
2.8%
구 457
 
2.8%
분 457
 
2.8%
없 457
 
2.8%
사 291
 
1.8%
Other values (165) 5574
34.7%
Latin
ValueCountFrequency (%)
I 95
19.0%
T 85
17.0%
C 42
8.4%
H 40
8.0%
s 35
 
7.0%
a 31
 
6.2%
n 31
 
6.2%
e 20
 
4.0%
l 20
 
4.0%
M 14
 
2.8%
Other values (13) 86
17.2%
Common
ValueCountFrequency (%)
39
54.9%
3 9
 
12.7%
2 9
 
12.7%
& 5
 
7.0%
1 3
 
4.2%
4 3
 
4.2%
- 3
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16025
96.4%
ASCII 570
 
3.4%
Compat Jamo 35
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 3010
18.8%
대 2780
17.3%
과 1576
 
9.8%
공 531
 
3.3%
음 470
 
2.9%
단 457
 
2.9%
구 457
 
2.9%
분 457
 
2.9%
없 457
 
2.9%
사 291
 
1.8%
Other values (164) 5539
34.6%
ASCII
ValueCountFrequency (%)
I 95
16.7%
T 85
14.9%
C 42
 
7.4%
H 40
 
7.0%
39
 
6.8%
s 35
 
6.1%
a 31
 
5.4%
n 31
 
5.4%
e 20
 
3.5%
l 20
 
3.5%
Other values (20) 132
23.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 35
100.0%

학과
Text

Distinct1501
Distinct (%)53.4%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2023-12-13T06:49:17.826146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length29
Mean length6.8513514
Min length3

Characters and Unicode

Total characters19266
Distinct characters372
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1120 ?
Unique (%)39.8%

Sample

1st row물리치료학과
2nd row간호학과
3rd row방사선학과
4th row작업치료학과
5th row나노물리학과
ValueCountFrequency (%)
간호학과 47
 
1.6%
사회복지학과 37
 
1.3%
컴퓨터공학과 33
 
1.1%
물리치료학과 31
 
1.1%
식품영양학과 28
 
1.0%
유아교육과 22
 
0.7%
경영학과 21
 
0.7%
작업치료학과 19
 
0.6%
전자공학과 19
 
0.6%
화학과 19
 
0.6%
Other values (1535) 2671
90.6%
2023-12-13T06:49:18.256234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 2623
 
13.6%
과 2108
 
10.9%
공 1287
 
6.7%
전 644
 
3.3%
부 489
 
2.5%
경 322
 
1.7%
영 306
 
1.6%
자 303
 
1.6%
어 285
 
1.5%
육 247
 
1.3%
Other values (362) 10652
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18633
96.7%
Space Separator 135
 
0.7%
Close Punctuation 115
 
0.6%
Open Punctuation 115
 
0.6%
Uppercase Letter 112
 
0.6%
Other Punctuation 70
 
0.4%
Lowercase Letter 57
 
0.3%
Decimal Number 22
 
0.1%
Math Symbol 6
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 2623
 
14.1%
과 2108
 
11.3%
공 1287
 
6.9%
전 644
 
3.5%
부 489
 
2.6%
경 322
 
1.7%
영 306
 
1.6%
자 303
 
1.6%
어 285
 
1.5%
육 247
 
1.3%
Other values (314) 10019
53.8%
Lowercase Letter
ValueCountFrequency (%)
a 7
12.3%
o 7
12.3%
e 6
10.5%
g 5
8.8%
n 5
8.8%
l 4
 
7.0%
c 3
 
5.3%
i 3
 
5.3%
s 3
 
5.3%
u 3
 
5.3%
Other values (8) 11
19.3%
Uppercase Letter
ValueCountFrequency (%)
T 43
38.4%
I 41
36.6%
C 9
 
8.0%
G 4
 
3.6%
S 3
 
2.7%
L 2
 
1.8%
D 1
 
0.9%
N 1
 
0.9%
O 1
 
0.9%
E 1
 
0.9%
Other values (6) 6
 
5.4%
Other Punctuation
ValueCountFrequency (%)
· 48
68.6%
, 8
 
11.4%
. 6
 
8.6%
& 5
 
7.1%
/ 3
 
4.3%
Decimal Number
ValueCountFrequency (%)
4 7
31.8%
2 7
31.8%
5 7
31.8%
6 1
 
4.5%
Space Separator
ValueCountFrequency (%)
135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 115
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18633
96.7%
Common 464
 
2.4%
Latin 169
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 2623
 
14.1%
과 2108
 
11.3%
공 1287
 
6.9%
전 644
 
3.5%
부 489
 
2.6%
경 322
 
1.7%
영 306
 
1.6%
자 303
 
1.6%
어 285
 
1.5%
육 247
 
1.3%
Other values (314) 10019
53.8%
Latin
ValueCountFrequency (%)
T 43
25.4%
I 41
24.3%
C 9
 
5.3%
a 7
 
4.1%
o 7
 
4.1%
e 6
 
3.6%
g 5
 
3.0%
n 5
 
3.0%
G 4
 
2.4%
l 4
 
2.4%
Other values (24) 38
22.5%
Common
ValueCountFrequency (%)
135
29.1%
) 115
24.8%
( 115
24.8%
· 48
 
10.3%
, 8
 
1.7%
4 7
 
1.5%
2 7
 
1.5%
5 7
 
1.5%
. 6
 
1.3%
+ 6
 
1.3%
Other values (4) 10
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18625
96.7%
ASCII 585
 
3.0%
None 48
 
0.2%
Compat Jamo 8
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 2623
 
14.1%
과 2108
 
11.3%
공 1287
 
6.9%
전 644
 
3.5%
부 489
 
2.6%
경 322
 
1.7%
영 306
 
1.6%
자 303
 
1.6%
어 285
 
1.5%
육 247
 
1.3%
Other values (313) 10011
53.8%
ASCII
ValueCountFrequency (%)
135
23.1%
) 115
19.7%
( 115
19.7%
T 43
 
7.4%
I 41
 
7.0%
C 9
 
1.5%
, 8
 
1.4%
a 7
 
1.2%
4 7
 
1.2%
o 7
 
1.2%
Other values (37) 98
16.8%
None
ValueCountFrequency (%)
· 48
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 8
100.0%

구분1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
주간
2705 
원격
 
70
야간
 
37

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주간
2nd row주간
3rd row주간
4th row주간
5th row주간

Common Values

ValueCountFrequency (%)
주간 2705
96.2%
원격 70
 
2.5%
야간 37
 
1.3%

Length

2023-12-13T06:49:18.620346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:49:18.712460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주간 2705
96.2%
원격 70
 
2.5%
야간 37
 
1.3%

학과특성
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
일반과정
2801 
학석사통합과정
 
6
계약학과
 
5

Length

Max length7
Median length4
Mean length4.0064011
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반과정
2nd row일반과정
3rd row일반과정
4th row일반과정
5th row일반과정

Common Values

ValueCountFrequency (%)
일반과정 2801
99.6%
학석사통합과정 6
 
0.2%
계약학과 5
 
0.2%

Length

2023-12-13T06:49:18.823877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:49:18.913191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반과정 2801
99.6%
학석사통합과정 6
 
0.2%
계약학과 5
 
0.2%

구분2
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
중점육성분야
2319 
예비육성분야
493 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중점육성분야
2nd row중점육성분야
3rd row중점육성분야
4th row중점육성분야
5th row중점육성분야

Common Values

ValueCountFrequency (%)
중점육성분야 2319
82.5%
예비육성분야 493
 
17.5%

Length

2023-12-13T06:49:19.004517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:49:19.087848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중점육성분야 2319
82.5%
예비육성분야 493
 
17.5%

학과특성화명
Text

Distinct1030
Distinct (%)36.6%
Missing1
Missing (%)< 0.1%
Memory size22.1 KiB
2023-12-13T06:49:19.294771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length50
Mean length14.525792
Min length2

Characters and Unicode

Total characters40832
Distinct characters510
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique574 ?
Unique (%)20.4%

Sample

1st row웰니스케어특화
2nd row웰니스케어특화
3rd row웰니스케어특화
4th row웰니스케어특화
5th row바이오
ValueCountFrequency (%)
양성 363
 
4.7%
사업단 217
 
2.8%
특성화 149
 
1.9%
인재 126
 
1.6%
분야 119
 
1.5%
및 107
 
1.4%
전문인력 84
 
1.1%
인재양성 71
 
0.9%
위한 68
 
0.9%
양성사업단 58
 
0.7%
Other values (1931) 6381
82.4%
2023-12-13T06:49:19.684818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4943
 
12.1%
성 1437
 
3.5%
인 1013
 
2.5%
양 980
 
2.4%
화 897
 
2.2%
업 894
 
2.2%
사 826
 
2.0%
문 652
 
1.6%
재 601
 
1.5%
학 546
 
1.3%
Other values (500) 28043
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30472
74.6%
Space Separator 4943
 
12.1%
Lowercase Letter 2215
 
5.4%
Uppercase Letter 1838
 
4.5%
Other Punctuation 567
 
1.4%
Open Punctuation 269
 
0.7%
Close Punctuation 269
 
0.7%
Decimal Number 132
 
0.3%
Dash Punctuation 96
 
0.2%
Connector Punctuation 18
 
< 0.1%
Other values (2) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 1437
 
4.7%
인 1013
 
3.3%
양 980
 
3.2%
화 897
 
2.9%
업 894
 
2.9%
사 826
 
2.7%
문 652
 
2.1%
재 601
 
2.0%
학 546
 
1.8%
합 515
 
1.7%
Other values (426) 22111
72.6%
Lowercase Letter
ValueCountFrequency (%)
e 305
13.8%
o 225
10.2%
i 204
9.2%
r 192
 
8.7%
a 189
 
8.5%
n 143
 
6.5%
t 142
 
6.4%
l 122
 
5.5%
c 100
 
4.5%
s 95
 
4.3%
Other values (15) 498
22.5%
Uppercase Letter
ValueCountFrequency (%)
T 332
18.1%
C 272
14.8%
I 263
14.3%
S 165
9.0%
E 116
 
6.3%
M 97
 
5.3%
B 81
 
4.4%
W 70
 
3.8%
A 68
 
3.7%
L 64
 
3.5%
Other values (14) 310
16.9%
Other Punctuation
ValueCountFrequency (%)
, 204
36.0%
/ 148
26.1%
· 124
21.9%
. 30
 
5.3%
: 24
 
4.2%
& 23
 
4.1%
' 12
 
2.1%
; 1
 
0.2%
! 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 30
22.7%
4 24
18.2%
0 24
18.2%
2 20
15.2%
6 15
11.4%
3 14
10.6%
7 5
 
3.8%
Open Punctuation
ValueCountFrequency (%)
( 268
99.6%
[ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 268
99.6%
] 1
 
0.4%
Space Separator
ValueCountFrequency (%)
4943
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 18
100.0%
Math Symbol
ValueCountFrequency (%)
+ 8
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30464
74.6%
Common 6302
 
15.4%
Latin 4058
 
9.9%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 1437
 
4.7%
인 1013
 
3.3%
양 980
 
3.2%
화 897
 
2.9%
업 894
 
2.9%
사 826
 
2.7%
문 652
 
2.1%
재 601
 
2.0%
학 546
 
1.8%
합 515
 
1.7%
Other values (419) 22103
72.6%
Latin
ValueCountFrequency (%)
T 332
 
8.2%
e 305
 
7.5%
C 272
 
6.7%
I 263
 
6.5%
o 225
 
5.5%
i 204
 
5.0%
r 192
 
4.7%
a 189
 
4.7%
S 165
 
4.1%
n 143
 
3.5%
Other values (40) 1768
43.6%
Common
ValueCountFrequency (%)
4943
78.4%
( 268
 
4.3%
) 268
 
4.3%
, 204
 
3.2%
/ 148
 
2.3%
· 124
 
2.0%
- 96
 
1.5%
1 30
 
0.5%
. 30
 
0.5%
4 24
 
0.4%
Other values (14) 167
 
2.6%
Han
ValueCountFrequency (%)
生 2
25.0%
新 1
12.5%
文 1
12.5%
人 1
12.5%
學 1
12.5%
實 1
12.5%
路 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30404
74.5%
ASCII 10231
 
25.1%
None 124
 
0.3%
Compat Jamo 60
 
0.1%
CJK 8
 
< 0.1%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4943
48.3%
T 332
 
3.2%
e 305
 
3.0%
C 272
 
2.7%
( 268
 
2.6%
) 268
 
2.6%
I 263
 
2.6%
o 225
 
2.2%
, 204
 
2.0%
i 204
 
2.0%
Other values (62) 2947
28.8%
Hangul
ValueCountFrequency (%)
성 1437
 
4.7%
인 1013
 
3.3%
양 980
 
3.2%
화 897
 
3.0%
업 894
 
2.9%
사 826
 
2.7%
문 652
 
2.1%
재 601
 
2.0%
학 546
 
1.8%
합 515
 
1.7%
Other values (418) 22043
72.5%
None
ValueCountFrequency (%)
· 124
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 60
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
100.0%
CJK
ValueCountFrequency (%)
生 2
25.0%
新 1
12.5%
文 1
12.5%
人 1
12.5%
學 1
12.5%
實 1
12.5%
路 1
12.5%

계획수립연도
Real number (ℝ)

Distinct21
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.1046
Minimum1995
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.8 KiB
2023-12-13T06:49:19.816118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1995
5-th percentile2011
Q12014
median2016
Q32017
95-th percentile2017
Maximum2017
Range22
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3546514
Coefficient of variation (CV)0.0011685009
Kurtosis15.55441
Mean2015.1046
Median Absolute Deviation (MAD)1
Skewness-3.0447305
Sum5666474
Variance5.5443834
MonotonicityNot monotonic
2023-12-13T06:49:19.919037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2017 928
33.0%
2014 666
23.7%
2016 576
20.5%
2015 327
 
11.6%
2011 91
 
3.2%
2012 82
 
2.9%
2013 66
 
2.3%
2009 18
 
0.6%
2003 13
 
0.5%
2007 12
 
0.4%
Other values (11) 33
 
1.2%
ValueCountFrequency (%)
1995 1
 
< 0.1%
1996 3
 
0.1%
1997 1
 
< 0.1%
1999 1
 
< 0.1%
2000 4
 
0.1%
2001 3
 
0.1%
2003 13
0.5%
2004 5
 
0.2%
2005 3
 
0.1%
2006 2
 
0.1%
ValueCountFrequency (%)
2017 928
33.0%
2016 576
20.5%
2015 327
 
11.6%
2014 666
23.7%
2013 66
 
2.3%
2012 82
 
2.9%
2011 91
 
3.2%
2010 8
 
0.3%
2009 18
 
0.6%
2008 2
 
0.1%

Interactions

2023-12-13T06:49:14.550168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:49:19.994057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학교종류설립구분지역구분1학과특성구분2계획수립연도
학교종류1.0000.3570.4430.6760.0000.1100.113
설립구분0.3571.0000.7530.0650.0570.1020.184
지역0.4430.7531.0000.3470.2240.2840.372
구분10.6760.0650.3471.0000.4090.0420.000
학과특성0.0000.0570.2240.4091.0000.0230.080
구분20.1100.1020.2840.0420.0231.0000.129
계획수립연도0.1130.1840.3720.0000.0800.1291.000
2023-12-13T06:49:20.112957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학과특성지역구분2학교종류구분1설립구분
학과특성1.0000.1240.0380.0000.1520.054
지역0.1241.0000.2220.2200.2010.448
구분20.0380.2221.0000.0730.0690.067
학교종류0.0000.2200.0731.0000.7070.145
구분10.1520.2010.0690.7071.0000.061
설립구분0.0540.4480.0670.1450.0611.000
2023-12-13T06:49:20.230114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계획수립연도학교종류설립구분지역구분1학과특성구분2
계획수립연도1.0000.0680.1070.1560.0000.0470.099
학교종류0.0681.0000.1450.2200.7070.0000.073
설립구분0.1070.1451.0000.4480.0610.0540.067
지역0.1560.2200.4481.0000.2010.1240.222
구분10.0000.7070.0610.2011.0000.1520.069
학과특성0.0470.0000.0540.1240.1521.0000.038
구분20.0990.0730.0670.2220.0690.0381.000

Missing values

2023-12-13T06:49:14.686889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:49:14.879303image/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.

Sample

조사년도학교종류설립구분지역상태학교단과대학학과구분1학과특성구분2학과특성화명계획수립연도
02018대학교사립경남기존가야대학교(김해)단과대구분없음물리치료학과주간일반과정중점육성분야웰니스케어특화2017
12018대학교사립경남기존가야대학교(김해)단과대구분없음간호학과주간일반과정중점육성분야웰니스케어특화2017
22018대학교사립경남기존가야대학교(김해)단과대구분없음방사선학과주간일반과정중점육성분야웰니스케어특화2017
32018대학교사립경남기존가야대학교(김해)단과대구분없음작업치료학과주간일반과정중점육성분야웰니스케어특화2017
42018대학교사립경기기존가천대학교바이오나노대학나노물리학과주간일반과정중점육성분야바이오2014
52018대학교사립경기기존가천대학교공과대학화공생명공학과주간일반과정예비육성분야청정에너지2014
62018대학교사립경기기존가천대학교약학대학약학과(2+4학제)주간일반과정중점육성분야바이오2014
72018대학교사립경기기존가천대학교바이오나노대학생명과학과주간일반과정중점육성분야바이오2014
82018대학교사립경기기존가천대학교공과대학도시계획학과주간일반과정예비육성분야도시재생2014
92018대학교사립경기기존가천대학교IT대학컴퓨터공학과주간일반과정중점육성분야소프트웨어2014
조사년도학교종류설립구분지역상태학교단과대학학과구분1학과특성구분2학과특성화명계획수립연도
28022018대학교사립서울기존홍익대학교공과대학신소재 화공시스템공학부주간일반과정예비육성분야웨어러블 전자기기 소재 및 소자 융합 디자인 공학 사업단2016
28032018대학교사립서울기존홍익대학교공과대학전자·전기공학부주간일반과정예비육성분야창의적 미래 IT 핵심인재 양성 사업단2016
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