Overview

Dataset statistics

Number of variables8
Number of observations394
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.8 KiB
Average record size in memory64.3 B

Variable types

Text5
Categorical3

Dataset

Description(주)한국가스기술공사 연구관리 시스템에 사용되는 기관표준용어 목록으로 용어명 물리명 도메인 인포타입 데이터타입 정의 등의 항목을 제공합니다
URLhttps://www.data.go.kr/data/15103152/fileData.do

Alerts

개인정보 유형 has constant value ""Constant
공개/비공개여부 has constant value ""Constant
용어명 has unique valuesUnique
물리명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:43:34.215187
Analysis finished2023-12-12 02:43:35.169954
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

용어명
Text

UNIQUE 

Distinct394
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T11:43:35.383969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length5.4060914
Min length2

Characters and Unicode

Total characters2130
Distinct characters232
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique394 ?
Unique (%)100.0%

Sample

1st row적용기관
2nd row성과활용보고서작성자이메일
3rd row실무담당자이메일
4th row연구책임자이메일
5th row이메일
ValueCountFrequency (%)
적용기관 1
 
0.3%
추진방식코드 1
 
0.3%
지식재산권상위구분코드 1
 
0.3%
지식재산권구분코드 1
 
0.3%
중복코드 1
 
0.3%
제작국가명코드 1
 
0.3%
전담기관코드 1
 
0.3%
저자구분코드 1
 
0.3%
위원구분코드 1
 
0.3%
심의결과코드 1
 
0.3%
Other values (384) 384
97.5%
2023-12-12T11:43:35.860856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 91
 
4.3%
드 65
 
3.1%
코 60
 
2.8%
구 52
 
2.4%
아 51
 
2.4%
기 50
 
2.3%
자 50
 
2.3%
디 50
 
2.3%
과 48
 
2.3%
명 43
 
2.0%
Other values (222) 1570
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2099
98.5%
Uppercase Letter 19
 
0.9%
Decimal Number 12
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 91
 
4.3%
드 65
 
3.1%
코 60
 
2.9%
구 52
 
2.5%
아 51
 
2.4%
기 50
 
2.4%
자 50
 
2.4%
디 50
 
2.4%
과 48
 
2.3%
명 43
 
2.0%
Other values (208) 1539
73.3%
Uppercase Letter
ValueCountFrequency (%)
I 4
21.1%
S 4
21.1%
L 2
10.5%
R 2
10.5%
U 2
10.5%
N 2
10.5%
P 1
 
5.3%
B 1
 
5.3%
C 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 3
25.0%
2 3
25.0%
3 2
16.7%
4 2
16.7%
5 2
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2099
98.5%
Latin 19
 
0.9%
Common 12
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 91
 
4.3%
드 65
 
3.1%
코 60
 
2.9%
구 52
 
2.5%
아 51
 
2.4%
기 50
 
2.4%
자 50
 
2.4%
디 50
 
2.4%
과 48
 
2.3%
명 43
 
2.0%
Other values (208) 1539
73.3%
Latin
ValueCountFrequency (%)
I 4
21.1%
S 4
21.1%
L 2
10.5%
R 2
10.5%
U 2
10.5%
N 2
10.5%
P 1
 
5.3%
B 1
 
5.3%
C 1
 
5.3%
Common
ValueCountFrequency (%)
1 3
25.0%
2 3
25.0%
3 2
16.7%
4 2
16.7%
5 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2099
98.5%
ASCII 31
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 91
 
4.3%
드 65
 
3.1%
코 60
 
2.9%
구 52
 
2.5%
아 51
 
2.4%
기 50
 
2.4%
자 50
 
2.4%
디 50
 
2.4%
과 48
 
2.3%
명 43
 
2.0%
Other values (208) 1539
73.3%
ASCII
ValueCountFrequency (%)
I 4
12.9%
S 4
12.9%
1 3
9.7%
2 3
9.7%
L 2
 
6.5%
R 2
 
6.5%
3 2
 
6.5%
U 2
 
6.5%
4 2
 
6.5%
N 2
 
6.5%
Other values (4) 5
16.1%

물리명
Text

UNIQUE 

Distinct394
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T11:43:36.158320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length9.5406091
Min length2

Characters and Unicode

Total characters3759
Distinct characters32
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

Unique394 ?
Unique (%)100.0%

Sample

1st rowAPPLC_INSTT
2nd rowRPR_WRTER_EMAIL
3rd rowPRCAFS_CHARGER_EMAIL
4th rowRSCH_RSPNBER_EMAIL
5th rowEMAIL
ValueCountFrequency (%)
applc_instt 1
 
0.3%
prtn_mthd_cd 1
 
0.3%
knw_prp_upr_se_cd 1
 
0.3%
knw_prp_se_cd 1
 
0.3%
dplct_cd 1
 
0.3%
maker_nation_cd 1
 
0.3%
wpsy_cd 1
 
0.3%
authr_se_cd 1
 
0.3%
mfcmm_se_cd 1
 
0.3%
dlbrt_rslt_cd 1
 
0.3%
Other values (384) 384
97.5%
2023-12-12T11:43:36.624559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 497
13.2%
R 344
 
9.2%
N 295
 
7.8%
T 283
 
7.5%
C 273
 
7.3%
E 265
 
7.0%
S 228
 
6.1%
D 197
 
5.2%
P 189
 
5.0%
M 165
 
4.4%
Other values (22) 1023
27.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3245
86.3%
Connector Punctuation 497
 
13.2%
Decimal Number 17
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 344
10.6%
N 295
 
9.1%
T 283
 
8.7%
C 273
 
8.4%
E 265
 
8.2%
S 228
 
7.0%
D 197
 
6.1%
P 189
 
5.8%
M 165
 
5.1%
A 148
 
4.6%
Other values (16) 858
26.4%
Decimal Number
ValueCountFrequency (%)
2 6
35.3%
3 4
23.5%
1 3
17.6%
4 2
 
11.8%
5 2
 
11.8%
Connector Punctuation
ValueCountFrequency (%)
_ 497
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3245
86.3%
Common 514
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 344
10.6%
N 295
 
9.1%
T 283
 
8.7%
C 273
 
8.4%
E 265
 
8.2%
S 228
 
7.0%
D 197
 
6.1%
P 189
 
5.8%
M 165
 
5.1%
A 148
 
4.6%
Other values (16) 858
26.4%
Common
ValueCountFrequency (%)
_ 497
96.7%
2 6
 
1.2%
3 4
 
0.8%
1 3
 
0.6%
4 2
 
0.4%
5 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3759
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 497
13.2%
R 344
 
9.2%
N 295
 
7.8%
T 283
 
7.5%
C 273
 
7.3%
E 265
 
7.0%
S 228
 
6.1%
D 197
 
5.2%
P 189
 
5.0%
M 165
 
4.4%
Other values (22) 1023
27.2%

도메인
Text

Distinct108
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T11:43:36.914884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length1.9974619
Min length1

Characters and Unicode

Total characters787
Distinct characters138
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)17.0%

Sample

1st row기관
2nd row이메일
3rd row이메일
4th row이메일
5th row이메일
ValueCountFrequency (%)
코드 50
 
12.7%
id 49
 
12.4%
명 37
 
9.4%
번호 28
 
7.1%
이름 16
 
4.1%
내용 12
 
3.0%
순번 12
 
3.0%
여부 10
 
2.5%
일 8
 
2.0%
유형 7
 
1.8%
Other values (98) 165
41.9%
2023-12-12T11:43:37.349307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
드 53
 
6.7%
코 52
 
6.6%
I 51
 
6.5%
D 49
 
6.2%
번 46
 
5.8%
명 45
 
5.7%
호 33
 
4.2%
일 27
 
3.4%
이 25
 
3.2%
름 16
 
2.0%
Other values (128) 390
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 681
86.5%
Uppercase Letter 105
 
13.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
드 53
 
7.8%
코 52
 
7.6%
번 46
 
6.8%
명 45
 
6.6%
호 33
 
4.8%
일 27
 
4.0%
이 25
 
3.7%
름 16
 
2.3%
용 14
 
2.1%
순 14
 
2.1%
Other values (121) 356
52.3%
Uppercase Letter
ValueCountFrequency (%)
I 51
48.6%
D 49
46.7%
P 2
 
1.9%
U 1
 
1.0%
R 1
 
1.0%
L 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 681
86.5%
Latin 105
 
13.3%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
드 53
 
7.8%
코 52
 
7.6%
번 46
 
6.8%
명 45
 
6.6%
호 33
 
4.8%
일 27
 
4.0%
이 25
 
3.7%
름 16
 
2.3%
용 14
 
2.1%
순 14
 
2.1%
Other values (121) 356
52.3%
Latin
ValueCountFrequency (%)
I 51
48.6%
D 49
46.7%
P 2
 
1.9%
U 1
 
1.0%
R 1
 
1.0%
L 1
 
1.0%
Common
ValueCountFrequency (%)
/ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 681
86.5%
ASCII 106
 
13.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
드 53
 
7.8%
코 52
 
7.6%
번 46
 
6.8%
명 45
 
6.6%
호 33
 
4.8%
일 27
 
4.0%
이 25
 
3.7%
름 16
 
2.3%
용 14
 
2.1%
순 14
 
2.1%
Other values (121) 356
52.3%
ASCII
ValueCountFrequency (%)
I 51
48.1%
D 49
46.2%
P 2
 
1.9%
/ 1
 
0.9%
U 1
 
0.9%
R 1
 
0.9%
L 1
 
0.9%

인포타입
Text

Distinct147
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T11:43:37.676433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.9822335
Min length4

Characters and Unicode

Total characters2751
Distinct characters154
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)23.6%

Sample

1st row기관_VC255
2nd row이메일_VC180
3rd row이메일_VC180
4th row이메일_VC180
5th row이메일_VC180
ValueCountFrequency (%)
코드_vc15 48
 
12.2%
id_vc20 40
 
10.2%
명_vc180 17
 
4.3%
번호_vc60 16
 
4.1%
순번_nm 12
 
3.0%
내용_vc4000 8
 
2.0%
일_vc8 8
 
2.0%
유형_vc15 7
 
1.8%
명_vc100 7
 
1.8%
이름_vc180 6
 
1.5%
Other values (137) 225
57.1%
2023-12-12T11:43:38.123053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 394
14.3%
C 323
 
11.7%
0 317
 
11.5%
V 313
 
11.4%
1 145
 
5.3%
5 93
 
3.4%
2 77
 
2.8%
M 67
 
2.4%
N 67
 
2.4%
8 63
 
2.3%
Other values (144) 892
32.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 893
32.5%
Decimal Number 781
28.4%
Other Letter 681
24.8%
Connector Punctuation 394
14.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
드 53
 
7.8%
코 52
 
7.6%
번 46
 
6.8%
명 45
 
6.6%
호 33
 
4.8%
일 27
 
4.0%
이 25
 
3.7%
름 16
 
2.3%
용 14
 
2.1%
순 14
 
2.1%
Other values (121) 356
52.3%
Uppercase Letter
ValueCountFrequency (%)
C 323
36.2%
V 313
35.1%
M 67
 
7.5%
N 67
 
7.5%
D 53
 
5.9%
I 51
 
5.7%
H 9
 
1.0%
T 4
 
0.4%
L 2
 
0.2%
P 2
 
0.2%
Other values (2) 2
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 317
40.6%
1 145
18.6%
5 93
 
11.9%
2 77
 
9.9%
8 63
 
8.1%
6 41
 
5.2%
4 38
 
4.9%
3 7
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
/ 1
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 394
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1177
42.8%
Latin 893
32.5%
Hangul 681
24.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
드 53
 
7.8%
코 52
 
7.6%
번 46
 
6.8%
명 45
 
6.6%
호 33
 
4.8%
일 27
 
4.0%
이 25
 
3.7%
름 16
 
2.3%
용 14
 
2.1%
순 14
 
2.1%
Other values (121) 356
52.3%
Latin
ValueCountFrequency (%)
C 323
36.2%
V 313
35.1%
M 67
 
7.5%
N 67
 
7.5%
D 53
 
5.9%
I 51
 
5.7%
H 9
 
1.0%
T 4
 
0.4%
L 2
 
0.2%
P 2
 
0.2%
Other values (2) 2
 
0.2%
Common
ValueCountFrequency (%)
_ 394
33.5%
0 317
26.9%
1 145
 
12.3%
5 93
 
7.9%
2 77
 
6.5%
8 63
 
5.4%
6 41
 
3.5%
4 38
 
3.2%
3 7
 
0.6%
. 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2070
75.2%
Hangul 681
 
24.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 394
19.0%
C 323
15.6%
0 317
15.3%
V 313
15.1%
1 145
 
7.0%
5 93
 
4.5%
2 77
 
3.7%
M 67
 
3.2%
N 67
 
3.2%
8 63
 
3.0%
Other values (13) 211
10.2%
Hangul
ValueCountFrequency (%)
드 53
 
7.8%
코 52
 
7.6%
번 46
 
6.8%
명 45
 
6.6%
호 33
 
4.8%
일 27
 
4.0%
이 25
 
3.7%
름 16
 
2.3%
용 14
 
2.1%
순 14
 
2.1%
Other values (121) 356
52.3%

데이터타입
Categorical

Distinct28
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
VARCHAR(15)
68 
NUMBER
66 
VARCHAR(20)
49 
VARCHAR(180)
40 
VARCHAR(4000)
34 
Other values (23)
137 

Length

Max length13
Median length12
Mean length10.347716
Min length4

Unique

Unique6 ?
Unique (%)1.5%

Sample

1st rowVARCHAR(255)
2nd rowVARCHAR(180)
3rd rowVARCHAR(180)
4th rowVARCHAR(180)
5th rowVARCHAR(180)

Common Values

ValueCountFrequency (%)
VARCHAR(15) 68
17.3%
NUMBER 66
16.8%
VARCHAR(20) 49
12.4%
VARCHAR(180) 40
10.2%
VARCHAR(4000) 34
8.6%
VARCHAR(60) 33
8.4%
VARCHAR(8) 23
 
5.8%
VARCHAR(100) 16
 
4.1%
VARCHAR(255) 9
 
2.3%
VARCHAR(600) 8
 
2.0%
Other values (18) 48
12.2%

Length

2023-12-12T11:43:38.258817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
varchar(15 68
17.3%
number 66
16.8%
varchar(20 49
12.4%
varchar(180 40
10.2%
varchar(4000 34
8.6%
varchar(60 33
8.4%
varchar(8 23
 
5.8%
varchar(100 16
 
4.1%
varchar(255 9
 
2.3%
varchar(600 8
 
2.0%
Other values (18) 48
12.2%

정의
Text

Distinct390
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T11:43:38.515385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length5.964467
Min length2

Characters and Unicode

Total characters2350
Distinct characters243
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique389 ?
Unique (%)98.7%

Sample

1st row적용기관
2nd row성과활용보고서 작성자 이메일
3rd row실무담당자 이메일
4th row연구책임자 이메일
5th row이메일
ValueCountFrequency (%)
코드 26
 
4.6%
아이디 21
 
3.7%
구분 10
 
1.8%
작성자 7
 
1.2%
명 7
 
1.2%
순번 7
 
1.2%
성과활용보고서 7
 
1.2%
실무담당자 7
 
1.2%
연구책임자 7
 
1.2%
과기인번호 5
 
0.9%
Other values (373) 458
81.5%
2023-12-12T11:43:38.949987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
168
 
7.1%
이 93
 
4.0%
드 65
 
2.8%
코 60
 
2.6%
구 52
 
2.2%
기 51
 
2.2%
자 51
 
2.2%
아 50
 
2.1%
디 49
 
2.1%
과 47
 
2.0%
Other values (233) 1664
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2140
91.1%
Space Separator 168
 
7.1%
Uppercase Letter 21
 
0.9%
Connector Punctuation 10
 
0.4%
Decimal Number 8
 
0.3%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 93
 
4.3%
드 65
 
3.0%
코 60
 
2.8%
구 52
 
2.4%
기 51
 
2.4%
자 51
 
2.4%
아 50
 
2.3%
디 49
 
2.3%
과 47
 
2.2%
번 46
 
2.1%
Other values (215) 1576
73.6%
Uppercase Letter
ValueCountFrequency (%)
I 5
23.8%
S 4
19.0%
L 2
 
9.5%
R 2
 
9.5%
N 2
 
9.5%
U 2
 
9.5%
C 1
 
4.8%
B 1
 
4.8%
P 1
 
4.8%
D 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
2 2
25.0%
5 1
 
12.5%
4 1
 
12.5%
3 1
 
12.5%
Space Separator
ValueCountFrequency (%)
168
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2140
91.1%
Common 189
 
8.0%
Latin 21
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 93
 
4.3%
드 65
 
3.0%
코 60
 
2.8%
구 52
 
2.4%
기 51
 
2.4%
자 51
 
2.4%
아 50
 
2.3%
디 49
 
2.3%
과 47
 
2.2%
번 46
 
2.1%
Other values (215) 1576
73.6%
Latin
ValueCountFrequency (%)
I 5
23.8%
S 4
19.0%
L 2
 
9.5%
R 2
 
9.5%
N 2
 
9.5%
U 2
 
9.5%
C 1
 
4.8%
B 1
 
4.8%
P 1
 
4.8%
D 1
 
4.8%
Common
ValueCountFrequency (%)
168
88.9%
_ 10
 
5.3%
/ 3
 
1.6%
1 3
 
1.6%
2 2
 
1.1%
5 1
 
0.5%
4 1
 
0.5%
3 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2140
91.1%
ASCII 210
 
8.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
168
80.0%
_ 10
 
4.8%
I 5
 
2.4%
S 4
 
1.9%
/ 3
 
1.4%
1 3
 
1.4%
L 2
 
1.0%
R 2
 
1.0%
2 2
 
1.0%
N 2
 
1.0%
Other values (8) 9
 
4.3%
Hangul
ValueCountFrequency (%)
이 93
 
4.3%
드 65
 
3.0%
코 60
 
2.8%
구 52
 
2.4%
기 51
 
2.4%
자 51
 
2.4%
아 50
 
2.3%
디 49
 
2.3%
과 47
 
2.2%
번 46
 
2.1%
Other values (215) 1576
73.6%

개인정보 유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
해당없음
394 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해당없음 394
100.0%

Length

2023-12-12T11:43:39.085881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:43:39.173041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 394
100.0%

공개/비공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
공개
394 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 394
100.0%

Length

2023-12-12T11:43:39.262944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:43:39.364673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 394
100.0%

Missing values

2023-12-12T11:43:35.007844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:43:35.128395image/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

용어명물리명도메인인포타입데이터타입정의개인정보 유형공개/비공개여부
0적용기관APPLC_INSTT기관기관_VC255VARCHAR(255)적용기관해당없음공개
1성과활용보고서작성자이메일RPR_WRTER_EMAIL이메일이메일_VC180VARCHAR(180)성과활용보고서 작성자 이메일해당없음공개
2실무담당자이메일PRCAFS_CHARGER_EMAIL이메일이메일_VC180VARCHAR(180)실무담당자 이메일해당없음공개
3연구책임자이메일RSCH_RSPNBER_EMAIL이메일이메일_VC180VARCHAR(180)연구책임자 이메일해당없음공개
4이메일EMAIL이메일이메일_VC180VARCHAR(180)이메일해당없음공개
5책임자이메일RSPNBER_EMAIL이메일이메일_VC180VARCHAR(180)책임자의 이메일해당없음공개
6참여율PRT_RT율율_NMNUMBER참여율해당없음공개
7실적참여율PARTCPTN_RT율율_NMNUMBER실적 참여율해당없음공개
8정부외출연금GVRN_ELSE_DNT_AMT금금_NMNUMBER정부 외 출연금해당없음공개
9정부출연금GVRN_DNT_AMT금금_NMNUMBER정부 출연금해당없음공개
용어명물리명도메인인포타입데이터타입정의개인정보 유형공개/비공개여부
384변경전BFCHG내용내용_VC1000VARCHAR(1000)변경되기 이전해당없음공개
385공문번호OFLDC_NO번호번호_VC100VARCHAR(100)공문의 문서번호해당없음공개
386계좌번호ACCOUNT_NUM번호번호_VC100VARCHAR(100)계좌번호해당없음공개
387계좌인덱스ACCOUNT_IDX번호번호_VC100VARCHAR(100)계좌등록의 순번해당없음공개
388카드인덱스CARD_IDX번호번호_VC100VARCHAR(100)카드등록 순번해당없음공개
389카드번호CARD_NUM번호번호_VC100VARCHAR(100)카드의 고유번호해당없음공개
390계획변경인덱스PLANCHG_IDX번호번호_VC100VARCHAR(100)계획변경인덱스해당없음공개
391평가점수EVL_SCORE점수점수_NM15.2NUMBER(15,2)평가점수해당없음공개
392이름NAME이름이름_VC10VARCHAR(10)이름해당없음공개
393연구개발성과의활용RDR_PRCUSE활용활용_VC60VARCHAR(60)연구개발 성과의 활용해당없음공개