Overview

Dataset statistics

Number of variables6
Number of observations148
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory51.9 B

Variable types

Text3
Numeric3

Dataset

Description홈페이지 메뉴 생성 및 관리에 사용되는 데이터로 메뉴명, 프로그램파일명, 메뉴번호, 상위메뉴번호,\t메뉴순서, 메뉴설명 항목을 제공합니다.
Author한국공예디자인문화진흥원
URLhttps://www.data.go.kr/data/15072632/fileData.do

Alerts

메뉴번호 is highly overall correlated with 상위메뉴번호High correlation
상위메뉴번호 is highly overall correlated with 메뉴번호High correlation
메뉴번호 has unique valuesUnique
상위메뉴번호 has 16 (10.8%) zerosZeros

Reproduction

Analysis started2023-12-12 11:26:17.660820
Analysis finished2023-12-12 11:26:20.360378
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

메뉴명
Text

Distinct138
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T20:26:20.782353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length6.6554054
Min length2

Characters and Unicode

Total characters985
Distinct characters202
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)86.5%

Sample

1st rowroot
2nd row권한관리
3rd row관리자관리
4th row관리자로그관리
5th row권한관리
ValueCountFrequency (%)
관리 26
 
12.5%
개인정보 5
 
2.4%
kcdf 4
 
1.9%
뉴스레터 4
 
1.9%
4
 
1.9%
수집·이용 4
 
1.9%
동의 4
 
1.9%
정기간행물 3
 
1.4%
신청 3
 
1.4%
사업공모 3
 
1.4%
Other values (123) 148
71.2%
2023-12-12T20:26:21.577998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 70
 
7.1%
리 66
 
6.7%
62
 
6.3%
사 29
 
2.9%
이 27
 
2.7%
공 26
 
2.6%
정 25
 
2.5%
개 23
 
2.3%
보 20
 
2.0%
용 19
 
1.9%
Other values (192) 618
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 823
83.6%
Space Separator 62
 
6.3%
Lowercase Letter 44
 
4.5%
Uppercase Letter 26
 
2.6%
Decimal Number 9
 
0.9%
Other Punctuation 7
 
0.7%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%
Dash Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 70
 
8.5%
리 66
 
8.0%
사 29
 
3.5%
이 27
 
3.3%
공 26
 
3.2%
정 25
 
3.0%
개 23
 
2.8%
보 20
 
2.4%
용 19
 
2.3%
자 17
 
2.1%
Other values (160) 501
60.9%
Lowercase Letter
ValueCountFrequency (%)
n 8
18.2%
s 6
13.6%
o 5
11.4%
i 5
11.4%
t 4
9.1%
e 4
9.1%
r 3
 
6.8%
u 3
 
6.8%
g 2
 
4.5%
b 1
 
2.3%
Other values (3) 3
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
C 5
19.2%
F 4
15.4%
D 4
15.4%
K 4
15.4%
I 4
15.4%
P 2
 
7.7%
M 1
 
3.8%
A 1
 
3.8%
B 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
4 3
33.3%
2 3
33.3%
8 2
22.2%
6 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
· 5
71.4%
& 2
 
28.6%
Space Separator
ValueCountFrequency (%)
62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 823
83.6%
Common 92
 
9.3%
Latin 70
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 70
 
8.5%
리 66
 
8.0%
사 29
 
3.5%
이 27
 
3.3%
공 26
 
3.2%
정 25
 
3.0%
개 23
 
2.8%
보 20
 
2.4%
용 19
 
2.3%
자 17
 
2.1%
Other values (160) 501
60.9%
Latin
ValueCountFrequency (%)
n 8
 
11.4%
s 6
 
8.6%
o 5
 
7.1%
i 5
 
7.1%
C 5
 
7.1%
F 4
 
5.7%
D 4
 
5.7%
t 4
 
5.7%
e 4
 
5.7%
K 4
 
5.7%
Other values (12) 21
30.0%
Common
ValueCountFrequency (%)
62
67.4%
· 5
 
5.4%
) 5
 
5.4%
( 5
 
5.4%
- 4
 
4.3%
4 3
 
3.3%
2 3
 
3.3%
& 2
 
2.2%
8 2
 
2.2%
6 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 823
83.6%
ASCII 157
 
15.9%
None 5
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 70
 
8.5%
리 66
 
8.0%
사 29
 
3.5%
이 27
 
3.3%
공 26
 
3.2%
정 25
 
3.0%
개 23
 
2.8%
보 20
 
2.4%
용 19
 
2.3%
자 17
 
2.1%
Other values (160) 501
60.9%
ASCII
ValueCountFrequency (%)
62
39.5%
n 8
 
5.1%
s 6
 
3.8%
o 5
 
3.2%
i 5
 
3.2%
) 5
 
3.2%
C 5
 
3.2%
( 5
 
3.2%
F 4
 
2.5%
D 4
 
2.5%
Other values (21) 48
30.6%
None
ValueCountFrequency (%)
· 5
100.0%

프로그램파일명
Text

Distinct116
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T20:26:21.955913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length12.77027
Min length2

Characters and Unicode

Total characters1890
Distinct characters56
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)77.7%

Sample

1st rowdir
2nd rowdir
3rd rowEgovUserManage
4th rowSelectLoginLogList
5th rowEgovAuthorManage
ValueCountFrequency (%)
dir 33
 
22.3%
bbsmstr_000000000181 1
 
0.7%
group 1
 
0.7%
directions 1
 
0.7%
ci 1
 
0.7%
mission 1
 
0.7%
establish 1
 
0.7%
intro 1
 
0.7%
bizintro04 1
 
0.7%
bizintro03 1
 
0.7%
Other values (106) 106
71.6%
2023-12-12T20:26:22.600041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 270
 
14.3%
e 132
 
7.0%
i 113
 
6.0%
r 100
 
5.3%
t 93
 
4.9%
o 86
 
4.6%
n 84
 
4.4%
s 81
 
4.3%
a 72
 
3.8%
_ 66
 
3.5%
Other values (46) 793
42.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1118
59.2%
Uppercase Letter 363
 
19.2%
Decimal Number 343
 
18.1%
Connector Punctuation 66
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 132
11.8%
i 113
10.1%
r 100
8.9%
t 93
 
8.3%
o 86
 
7.7%
n 84
 
7.5%
s 81
 
7.2%
a 72
 
6.4%
g 55
 
4.9%
d 54
 
4.8%
Other values (16) 248
22.2%
Uppercase Letter
ValueCountFrequency (%)
M 60
16.5%
B 54
14.9%
S 53
14.6%
L 32
8.8%
E 28
7.7%
T 28
7.7%
R 27
7.4%
C 17
 
4.7%
I 16
 
4.4%
A 16
 
4.4%
Other values (9) 32
8.8%
Decimal Number
ValueCountFrequency (%)
0 270
78.7%
1 25
 
7.3%
2 14
 
4.1%
8 9
 
2.6%
4 8
 
2.3%
3 7
 
2.0%
9 4
 
1.2%
6 3
 
0.9%
5 2
 
0.6%
7 1
 
0.3%
Connector Punctuation
ValueCountFrequency (%)
_ 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1481
78.4%
Common 409
 
21.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 132
 
8.9%
i 113
 
7.6%
r 100
 
6.8%
t 93
 
6.3%
o 86
 
5.8%
n 84
 
5.7%
s 81
 
5.5%
a 72
 
4.9%
M 60
 
4.1%
g 55
 
3.7%
Other values (35) 605
40.9%
Common
ValueCountFrequency (%)
0 270
66.0%
_ 66
 
16.1%
1 25
 
6.1%
2 14
 
3.4%
8 9
 
2.2%
4 8
 
2.0%
3 7
 
1.7%
9 4
 
1.0%
6 3
 
0.7%
5 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 270
 
14.3%
e 132
 
7.0%
i 113
 
6.0%
r 100
 
5.3%
t 93
 
4.9%
o 86
 
4.6%
n 84
 
4.4%
s 81
 
4.3%
a 72
 
3.8%
_ 66
 
3.5%
Other values (46) 793
42.0%

메뉴번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct148
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6925026.6
Minimum0
Maximum31110000
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T20:26:22.821984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1740000
Q13237500
median9075000.5
Q39440250
95-th percentile9775850
Maximum31110000
Range31110000
Interquartile range (IQR)6202750

Descriptive statistics

Standard deviation4278750.3
Coefficient of variation (CV)0.61786771
Kurtosis11.919958
Mean6925026.6
Median Absolute Deviation (MAD)824997
Skewness2.1828694
Sum1.0249039 × 109
Variance1.8307704 × 1013
MonotonicityStrictly increasing
2023-12-12T20:26:23.035746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
0.7%
9230000 1
 
0.7%
9300000 1
 
0.7%
9310000 1
 
0.7%
9320000 1
 
0.7%
9330000 1
 
0.7%
9340000 1
 
0.7%
9360000 1
 
0.7%
9400000 1
 
0.7%
9410000 1
 
0.7%
Other values (138) 138
93.2%
ValueCountFrequency (%)
0 1
0.7%
1000000 1
0.7%
1100000 1
0.7%
1200000 1
0.7%
1300000 1
0.7%
1400000 1
0.7%
1500000 1
0.7%
1600000 1
0.7%
2000000 1
0.7%
2200000 1
0.7%
ValueCountFrequency (%)
31110000 1
0.7%
31100000 1
0.7%
9850000 1
0.7%
9840000 1
0.7%
9830000 1
0.7%
9820000 1
0.7%
9810000 1
0.7%
9800000 1
0.7%
9731000 1
0.7%
9730000 1
0.7%

상위메뉴번호
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5736959.5
Minimum0
Maximum9800000
Zeros16
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T20:26:23.303697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000000
median8000000
Q39400000
95-th percentile9700000
Maximum9800000
Range9800000
Interquartile range (IQR)6400000

Descriptive statistics

Standard deviation3681715.9
Coefficient of variation (CV)0.64175387
Kurtosis-1.6631231
Mean5736959.5
Median Absolute Deviation (MAD)1800000
Skewness-0.21121147
Sum8.4907 × 108
Variance1.3555032 × 1013
MonotonicityNot monotonic
2023-12-12T20:26:23.571183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 16
 
10.8%
3100000 11
 
7.4%
3000000 9
 
6.1%
3200000 9
 
6.1%
9100000 8
 
5.4%
1000000 6
 
4.1%
2200000 6
 
4.1%
9600000 6
 
4.1%
9510000 6
 
4.1%
9300000 5
 
3.4%
Other values (21) 66
44.6%
ValueCountFrequency (%)
0 16
10.8%
1000000 6
 
4.1%
2000000 4
 
2.7%
2200000 6
 
4.1%
2300000 3
 
2.0%
3000000 9
6.1%
3100000 11
7.4%
3200000 9
6.1%
3300000 4
 
2.7%
3900000 2
 
1.4%
ValueCountFrequency (%)
9800000 5
3.4%
9730000 1
 
0.7%
9720000 1
 
0.7%
9700000 3
2.0%
9600000 6
4.1%
9510000 6
4.1%
9500000 5
3.4%
9440000 4
2.7%
9420000 4
2.7%
9400000 4
2.7%

메뉴순서
Real number (ℝ)

Distinct16
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.027027
Minimum1
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T20:26:23.782466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile10
Maximum16
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.0325803
Coefficient of variation (CV)0.75305686
Kurtosis2.7943541
Mean4.027027
Median Absolute Deviation (MAD)2
Skewness1.5672315
Sum596
Variance9.1965435
MonotonicityNot monotonic
2023-12-12T20:26:23.981719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 29
19.6%
2 27
18.2%
3 22
14.9%
4 21
14.2%
5 16
10.8%
6 10
 
6.8%
8 5
 
3.4%
7 5
 
3.4%
9 4
 
2.7%
11 2
 
1.4%
Other values (6) 7
 
4.7%
ValueCountFrequency (%)
1 29
19.6%
2 27
18.2%
3 22
14.9%
4 21
14.2%
5 16
10.8%
6 10
 
6.8%
7 5
 
3.4%
8 5
 
3.4%
9 4
 
2.7%
10 2
 
1.4%
ValueCountFrequency (%)
16 1
 
0.7%
15 1
 
0.7%
14 1
 
0.7%
13 1
 
0.7%
12 1
 
0.7%
11 2
 
1.4%
10 2
 
1.4%
9 4
2.7%
8 5
3.4%
7 5
3.4%

메뉴설명
Text

Distinct132
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T20:26:24.481145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length5.7567568
Min length2

Characters and Unicode

Total characters852
Distinct characters188
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)82.4%

Sample

1st rowroot
2nd row권한관리
3rd row관리자관리
4th row새매뉴
5th row권한관리
ValueCountFrequency (%)
관리 23
 
12.2%
새매뉴 8
 
4.3%
영어 4
 
2.1%
사업공모 3
 
1.6%
뉴스레터 3
 
1.6%
기관소개 3
 
1.6%
채용공고 3
 
1.6%
이용문의 2
 
1.1%
설문조사 2
 
1.1%
연구보고서 2
 
1.1%
Other values (115) 135
71.8%
2023-12-12T20:26:25.250703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 71
 
8.3%
리 64
 
7.5%
42
 
4.9%
사 29
 
3.4%
공 24
 
2.8%
개 21
 
2.5%
뉴 19
 
2.2%
문 18
 
2.1%
이 18
 
2.1%
소 16
 
1.9%
Other values (178) 530
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 785
92.1%
Space Separator 42
 
4.9%
Decimal Number 9
 
1.1%
Uppercase Letter 6
 
0.7%
Lowercase Letter 4
 
0.5%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 71
 
9.0%
리 64
 
8.2%
사 29
 
3.7%
공 24
 
3.1%
개 21
 
2.7%
뉴 19
 
2.4%
문 18
 
2.3%
이 18
 
2.3%
소 16
 
2.0%
보 15
 
1.9%
Other values (161) 490
62.4%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
K 1
16.7%
D 1
16.7%
F 1
16.7%
I 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 3
33.3%
4 3
33.3%
8 2
22.2%
3 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
t 1
25.0%
r 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 785
92.1%
Common 57
 
6.7%
Latin 10
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 71
 
9.0%
리 64
 
8.2%
사 29
 
3.7%
공 24
 
3.1%
개 21
 
2.7%
뉴 19
 
2.4%
문 18
 
2.3%
이 18
 
2.3%
소 16
 
2.0%
보 15
 
1.9%
Other values (161) 490
62.4%
Common
ValueCountFrequency (%)
42
73.7%
2 3
 
5.3%
4 3
 
5.3%
) 2
 
3.5%
( 2
 
3.5%
8 2
 
3.5%
3 1
 
1.8%
& 1
 
1.8%
· 1
 
1.8%
Latin
ValueCountFrequency (%)
C 2
20.0%
o 2
20.0%
t 1
10.0%
K 1
10.0%
r 1
10.0%
D 1
10.0%
F 1
10.0%
I 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 785
92.1%
ASCII 66
 
7.7%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 71
 
9.0%
리 64
 
8.2%
사 29
 
3.7%
공 24
 
3.1%
개 21
 
2.7%
뉴 19
 
2.4%
문 18
 
2.3%
이 18
 
2.3%
소 16
 
2.0%
보 15
 
1.9%
Other values (161) 490
62.4%
ASCII
ValueCountFrequency (%)
42
63.6%
2 3
 
4.5%
4 3
 
4.5%
C 2
 
3.0%
o 2
 
3.0%
) 2
 
3.0%
( 2
 
3.0%
8 2
 
3.0%
t 1
 
1.5%
K 1
 
1.5%
Other values (6) 6
 
9.1%
None
ValueCountFrequency (%)
· 1
100.0%

Interactions

2023-12-12T20:26:19.493264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:26:18.190587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:26:18.871892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:26:19.676070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:26:18.412433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:26:19.111947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:26:19.859513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:26:18.627015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:26:19.316051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:26:25.450179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
메뉴번호상위메뉴번호메뉴순서
메뉴번호1.0000.8020.677
상위메뉴번호0.8021.0000.308
메뉴순서0.6770.3081.000
2023-12-12T20:26:25.619380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
메뉴번호상위메뉴번호메뉴순서
메뉴번호1.0000.742-0.086
상위메뉴번호0.7421.000-0.349
메뉴순서-0.086-0.3491.000

Missing values

2023-12-12T20:26:20.089533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:26:20.278997image/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

메뉴명프로그램파일명메뉴번호상위메뉴번호메뉴순서메뉴설명
0rootdir005root
1권한관리dir100000009권한관리
2관리자관리EgovUserManage110000010000001관리자관리
3관리자로그관리SelectLoginLogList120000010000005새매뉴
4권한관리EgovAuthorManage130000010000002권한관리
5관리자별권한관리EgovAuthorRoleManage140000010000003관리자별권한관리
6롤관리EgovRoleManage150000010000004롤관리
7사이트IP관리selectLoginGroupPolicyList160000010000006새매뉴
8사이트관리dir2000000012사이트관리
9매뉴관리dir220000020000002매뉴관리
메뉴명프로그램파일명메뉴번호상위메뉴번호메뉴순서메뉴설명
138introductiondir973000097000003영어 기관소개
139engIntroengIntro973100097300001영어 인사말
140개인정보 수집이용동의dir9800000011새매뉴
141이용문의 - 개인정보 수집·이용 동의useqna_agree981000098000001새매뉴
142뉴스레터 구독 신청 - 개인정보 수집·이용 동의newsletter_agree982000098000002새매뉴
143정기간행물 신청 - 개인정보 수집·이용 동의period_agree983000098000003새매뉴
144대관 신청 - 개인정보 수집·이용 동의reserve_agree984000098000004새매뉴
145전시관 정보exhibition_hall_info985000098000005전시관 정보
146유관사이트 관리popupzoneList_0731100000310000010상단관련사이트관리
147운영사이트 배너 관리popupzoneList_0831110000310000011유관기관관리