Overview

Dataset statistics

Number of variables7
Number of observations1368
Missing cells1247
Missing cells (%)13.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory76.3 KiB
Average record size in memory57.1 B

Variable types

Text5
Categorical1
Numeric1

Dataset

Description2021년 2월 기준 ICTBAY 예고기술별 과제 정보입니다.
Author한국연구재단 정보통신기획평가원
URLhttps://www.data.go.kr/data/15077401/fileData.do

Alerts

과제별기술순번 is highly overall correlated with 수정자High correlation
수정자 is highly overall correlated with 과제별기술순번High correlation
수정자 is highly imbalanced (77.0%)Imbalance
수정일시 has 1247 (91.2%) missing valuesMissing
예고기술 has unique valuesUnique

Reproduction

Analysis started2024-04-20 17:32:13.608848
Analysis finished2024-04-20 17:32:15.112009
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

예고기술
Text

UNIQUE 

Distinct1368
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
2024-04-21T02:32:15.719746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters24624
Distinct characters36
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

Unique1368 ?
Unique (%)100.0%

Sample

1st row754XKHH0I0009A6000
2nd row754XKHHHA0009AR000
3rd row754XKHIUQ0009D5000
4th row754XKHIED0009BU000
5th row754XKHU1H0009RJ000
ValueCountFrequency (%)
754xkhh0i0009a6000 1
 
0.1%
75edvjvmq04vk6o000 1
 
0.1%
75edwpw8h04vlxz000 1
 
0.1%
75edxwspt04vnxv000 1
 
0.1%
75edwph0404vlvh000 1
 
0.1%
75edwp3wp04vlrm000 1
 
0.1%
75edw4wwm04vl76000 1
 
0.1%
75edw4p1g04vl58000 1
 
0.1%
75edwpg6k04vluz000 1
 
0.1%
75eco2u4m04vf3i000 1
 
0.1%
Other values (1358) 1358
99.3%
2024-04-21T02:32:16.889592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6380
25.9%
5 2242
 
9.1%
7 1759
 
7.1%
4 1041
 
4.2%
9 656
 
2.7%
L 647
 
2.6%
K 623
 
2.5%
E 576
 
2.3%
V 537
 
2.2%
J 537
 
2.2%
Other values (26) 9626
39.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13938
56.6%
Uppercase Letter 10686
43.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 647
 
6.1%
K 623
 
5.8%
E 576
 
5.4%
V 537
 
5.0%
J 537
 
5.0%
P 511
 
4.8%
X 488
 
4.6%
W 470
 
4.4%
H 469
 
4.4%
N 463
 
4.3%
Other values (16) 5365
50.2%
Decimal Number
ValueCountFrequency (%)
0 6380
45.8%
5 2242
 
16.1%
7 1759
 
12.6%
4 1041
 
7.5%
9 656
 
4.7%
1 501
 
3.6%
2 415
 
3.0%
6 387
 
2.8%
8 283
 
2.0%
3 274
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13938
56.6%
Latin 10686
43.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 647
 
6.1%
K 623
 
5.8%
E 576
 
5.4%
V 537
 
5.0%
J 537
 
5.0%
P 511
 
4.8%
X 488
 
4.6%
W 470
 
4.4%
H 469
 
4.4%
N 463
 
4.3%
Other values (16) 5365
50.2%
Common
ValueCountFrequency (%)
0 6380
45.8%
5 2242
 
16.1%
7 1759
 
12.6%
4 1041
 
7.5%
9 656
 
4.7%
1 501
 
3.6%
2 415
 
3.0%
6 387
 
2.8%
8 283
 
2.0%
3 274
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6380
25.9%
5 2242
 
9.1%
7 1759
 
7.1%
4 1041
 
4.2%
9 656
 
2.7%
L 647
 
2.6%
K 623
 
2.5%
E 576
 
2.3%
V 537
 
2.2%
J 537
 
2.2%
Other values (26) 9626
39.1%

생성자
Text

Distinct257
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
2024-04-21T02:32:17.809463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters24624
Distinct characters36
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

Unique133 ?
Unique (%)9.7%

Sample

1st row754U6G2N000005W004
2nd row754U6G2N000005W001
3rd row754U6G2N000005W003
4th row754U6G2N000005W005
5th row754U6G2N000005W003
ValueCountFrequency (%)
000000000000000uu0 591
43.2%
754u6g2n000005w004 41
 
3.0%
754u6g2n000005w005 41
 
3.0%
754u6g2n000005w001 36
 
2.6%
754u6g2n000005w003 34
 
2.5%
754u6g2n000005w002 32
 
2.3%
7557872y801uz5e000 25
 
1.8%
000000anonymousuu0 18
 
1.3%
759pd96wm04kge7000 17
 
1.2%
759pg8sl804kv61000 16
 
1.2%
Other values (247) 517
37.8%
2024-04-21T02:32:18.826139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13334
54.2%
U 1616
 
6.6%
5 1222
 
5.0%
7 960
 
3.9%
4 741
 
3.0%
9 498
 
2.0%
L 414
 
1.7%
2 412
 
1.7%
P 401
 
1.6%
N 388
 
1.6%
Other values (26) 4638
 
18.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17968
73.0%
Uppercase Letter 6656
 
27.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 1616
24.3%
L 414
 
6.2%
P 401
 
6.0%
N 388
 
5.8%
G 339
 
5.1%
W 322
 
4.8%
K 294
 
4.4%
E 265
 
4.0%
J 261
 
3.9%
V 186
 
2.8%
Other values (16) 2170
32.6%
Decimal Number
ValueCountFrequency (%)
0 13334
74.2%
5 1222
 
6.8%
7 960
 
5.3%
4 741
 
4.1%
9 498
 
2.8%
2 412
 
2.3%
6 333
 
1.9%
8 205
 
1.1%
1 155
 
0.9%
3 108
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 17968
73.0%
Latin 6656
 
27.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 1616
24.3%
L 414
 
6.2%
P 401
 
6.0%
N 388
 
5.8%
G 339
 
5.1%
W 322
 
4.8%
K 294
 
4.4%
E 265
 
4.0%
J 261
 
3.9%
V 186
 
2.8%
Other values (16) 2170
32.6%
Common
ValueCountFrequency (%)
0 13334
74.2%
5 1222
 
6.8%
7 960
 
5.3%
4 741
 
4.1%
9 498
 
2.8%
2 412
 
2.3%
6 333
 
1.9%
8 205
 
1.1%
1 155
 
0.9%
3 108
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13334
54.2%
U 1616
 
6.6%
5 1222
 
5.0%
7 960
 
3.9%
4 741
 
3.0%
9 498
 
2.0%
L 414
 
1.7%
2 412
 
1.7%
P 401
 
1.6%
N 388
 
1.6%
Other values (26) 4638
 
18.8%

생성일시
Text

Distinct1367
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
2024-04-21T02:32:19.699293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length21.307749
Min length21

Characters and Unicode

Total characters29149
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1366 ?
Unique (%)99.9%

Sample

1st row2015-03-27 오전 9:33:46
2nd row2015-03-27 오전 9:39:50
3rd row2015-03-27 오전 9:57:30
4th row2015-03-27 오전 9:51:41
5th row2015-03-27 오전 11:02:29
ValueCountFrequency (%)
오후 922
22.5%
오전 446
 
10.9%
2015-03-27 181
 
4.4%
2016-07-29 64
 
1.6%
2018-11-30 49
 
1.2%
2016-07-27 43
 
1.0%
2017-08-31 41
 
1.0%
2016-07-28 38
 
0.9%
2015-08-11 36
 
0.9%
2015-08-13 34
 
0.8%
Other values (1470) 2250
54.8%
2024-04-21T02:32:20.781918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3988
13.7%
1 3511
12.0%
2 3219
11.0%
- 2736
9.4%
2736
9.4%
: 2736
9.4%
3 1494
 
5.1%
오 1368
 
4.7%
5 1350
 
4.6%
7 1080
 
3.7%
Other values (6) 4931
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18205
62.5%
Dash Punctuation 2736
 
9.4%
Space Separator 2736
 
9.4%
Other Punctuation 2736
 
9.4%
Other Letter 2736
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3988
21.9%
1 3511
19.3%
2 3219
17.7%
3 1494
 
8.2%
5 1350
 
7.4%
7 1080
 
5.9%
4 1027
 
5.6%
8 1023
 
5.6%
9 764
 
4.2%
6 749
 
4.1%
Other Letter
ValueCountFrequency (%)
오 1368
50.0%
후 922
33.7%
전 446
 
16.3%
Dash Punctuation
ValueCountFrequency (%)
- 2736
100.0%
Space Separator
ValueCountFrequency (%)
2736
100.0%
Other Punctuation
ValueCountFrequency (%)
: 2736
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26413
90.6%
Hangul 2736
 
9.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3988
15.1%
1 3511
13.3%
2 3219
12.2%
- 2736
10.4%
2736
10.4%
: 2736
10.4%
3 1494
 
5.7%
5 1350
 
5.1%
7 1080
 
4.1%
4 1027
 
3.9%
Other values (3) 2536
9.6%
Hangul
ValueCountFrequency (%)
오 1368
50.0%
후 922
33.7%
전 446
 
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26413
90.6%
Hangul 2736
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3988
15.1%
1 3511
13.3%
2 3219
12.2%
- 2736
10.4%
2736
10.4%
: 2736
10.4%
3 1494
 
5.7%
5 1350
 
5.1%
7 1080
 
4.1%
4 1027
 
3.9%
Other values (3) 2536
9.6%
Hangul
ValueCountFrequency (%)
오 1368
50.0%
후 922
33.7%
전 446
 
16.3%

수정자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
<NA>
1247 
754U6G2N000005W003
 
34
754U6G2N000005W005
 
30
754U6G2N000005W002
 
22
754U6G2N000005W004
 
15
Other values (2)
 
20

Length

Max length18
Median length4
Mean length5.2383041
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row754U6G2N000005W004
2nd row754U6G2N000005W001
3rd row754U6G2N000005W003
4th row754U6G2N000005W005
5th row754U6G2N000005W003

Common Values

ValueCountFrequency (%)
<NA> 1247
91.2%
754U6G2N000005W003 34
 
2.5%
754U6G2N000005W005 30
 
2.2%
754U6G2N000005W002 22
 
1.6%
754U6G2N000005W004 15
 
1.1%
754U6G2N000005W001 13
 
1.0%
754U6G2N000005W000 7
 
0.5%

Length

2024-04-21T02:32:21.034130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:32:21.239909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1247
91.2%
754u6g2n000005w003 34
 
2.5%
754u6g2n000005w005 30
 
2.2%
754u6g2n000005w002 22
 
1.6%
754u6g2n000005w004 15
 
1.1%
754u6g2n000005w001 13
 
1.0%
754u6g2n000005w000 7
 
0.5%

수정일시
Text

MISSING 

Distinct121
Distinct (%)100.0%
Missing1247
Missing (%)91.2%
Memory size10.8 KiB
2024-04-21T02:32:22.292394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length21.008264
Min length21

Characters and Unicode

Total characters2542
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)100.0%

Sample

1st row2015-03-31 오후 3:51:38
2nd row2015-03-27 오전 9:49:22
3rd row2015-03-31 오전 9:13:55
4th row2015-03-31 오후 3:46:25
5th row2015-03-31 오후 5:32:38
ValueCountFrequency (%)
2015-03-31 105
28.9%
오후 104
28.7%
오전 17
 
4.7%
2015-04-01 7
 
1.9%
2015-03-27 6
 
1.7%
2015-03-30 3
 
0.8%
5:57:12 1
 
0.3%
5:02:56 1
 
0.3%
4:28:18 1
 
0.3%
9:26:30 1
 
0.3%
Other values (117) 117
32.2%
2024-04-21T02:32:23.578661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 317
12.5%
1 289
11.4%
3 289
11.4%
- 242
9.5%
242
9.5%
: 242
9.5%
5 238
9.4%
2 218
8.6%
오 121
 
4.8%
후 104
 
4.1%
Other values (6) 240
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1574
61.9%
Dash Punctuation 242
 
9.5%
Space Separator 242
 
9.5%
Other Punctuation 242
 
9.5%
Other Letter 242
 
9.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 317
20.1%
1 289
18.4%
3 289
18.4%
5 238
15.1%
2 218
13.9%
4 102
 
6.5%
6 36
 
2.3%
8 32
 
2.0%
9 29
 
1.8%
7 24
 
1.5%
Other Letter
ValueCountFrequency (%)
오 121
50.0%
후 104
43.0%
전 17
 
7.0%
Dash Punctuation
ValueCountFrequency (%)
- 242
100.0%
Space Separator
ValueCountFrequency (%)
242
100.0%
Other Punctuation
ValueCountFrequency (%)
: 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2300
90.5%
Hangul 242
 
9.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 317
13.8%
1 289
12.6%
3 289
12.6%
- 242
10.5%
242
10.5%
: 242
10.5%
5 238
10.3%
2 218
9.5%
4 102
 
4.4%
6 36
 
1.6%
Other values (3) 85
 
3.7%
Hangul
ValueCountFrequency (%)
오 121
50.0%
후 104
43.0%
전 17
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2300
90.5%
Hangul 242
 
9.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 317
13.8%
1 289
12.6%
3 289
12.6%
- 242
10.5%
242
10.5%
: 242
10.5%
5 238
10.3%
2 218
9.5%
4 102
 
4.4%
6 36
 
1.6%
Other values (3) 85
 
3.7%
Hangul
ValueCountFrequency (%)
오 121
50.0%
후 104
43.0%
전 17
 
7.0%

과제
Text

Distinct757
Distinct (%)55.3%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
2024-04-21T02:32:24.300685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters24624
Distinct characters36
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

Unique493 ?
Unique (%)36.0%

Sample

1st row754XJX9R700092D000
2nd row754XJWX470008VK000
3rd row754XJX1LK0008WD000
4th row754XJX5X700091J000
5th row754XJX27I0008WZ000
ValueCountFrequency (%)
75ne8j4wo05yabcpj0 18
 
1.3%
75ivwxmyy056b57pj0 13
 
1.0%
759ntbj2q04hk8t000 12
 
0.9%
75nb3es7z05uso1pj0 12
 
0.9%
7555l8yaa00wnvd000 11
 
0.8%
759ntbj2w04hkgq000 10
 
0.7%
754xjxdiu00095b000 9
 
0.7%
7555lucs000xflx000 9
 
0.7%
759ntbj2x04hkig000 9
 
0.7%
7555usqi301d7zb000 9
 
0.7%
Other values (747) 1256
91.8%
2024-04-21T02:32:25.435582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5020
20.4%
5 2431
 
9.9%
7 1677
 
6.8%
J 1231
 
5.0%
4 1029
 
4.2%
P 862
 
3.5%
U 739
 
3.0%
9 665
 
2.7%
T 661
 
2.7%
N 655
 
2.7%
Other values (26) 9654
39.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12981
52.7%
Uppercase Letter 11643
47.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
J 1231
 
10.6%
P 862
 
7.4%
U 739
 
6.3%
T 661
 
5.7%
N 655
 
5.6%
X 642
 
5.5%
B 564
 
4.8%
S 555
 
4.8%
E 500
 
4.3%
K 489
 
4.2%
Other values (16) 4745
40.8%
Decimal Number
ValueCountFrequency (%)
0 5020
38.7%
5 2431
18.7%
7 1677
 
12.9%
4 1029
 
7.9%
9 665
 
5.1%
1 535
 
4.1%
6 521
 
4.0%
2 432
 
3.3%
8 382
 
2.9%
3 289
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 12981
52.7%
Latin 11643
47.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
J 1231
 
10.6%
P 862
 
7.4%
U 739
 
6.3%
T 661
 
5.7%
N 655
 
5.6%
X 642
 
5.5%
B 564
 
4.8%
S 555
 
4.8%
E 500
 
4.3%
K 489
 
4.2%
Other values (16) 4745
40.8%
Common
ValueCountFrequency (%)
0 5020
38.7%
5 2431
18.7%
7 1677
 
12.9%
4 1029
 
7.9%
9 665
 
5.1%
1 535
 
4.1%
6 521
 
4.0%
2 432
 
3.3%
8 382
 
2.9%
3 289
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5020
20.4%
5 2431
 
9.9%
7 1677
 
6.8%
J 1231
 
5.0%
4 1029
 
4.2%
P 862
 
3.5%
U 739
 
3.0%
9 665
 
2.7%
T 661
 
2.7%
N 655
 
2.7%
Other values (26) 9654
39.2%

과제별기술순번
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7434211
Minimum1
Maximum195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.1 KiB
2024-04-21T02:32:25.653867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile7
Maximum195
Range194
Interquartile range (IQR)2

Descriptive statistics

Standard deviation10.179908
Coefficient of variation (CV)3.710662
Kurtosis312.60574
Mean2.7434211
Median Absolute Deviation (MAD)0
Skewness17.352278
Sum3753
Variance103.63053
MonotonicityNot monotonic
2024-04-21T02:32:25.879969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 740
54.1%
2 270
 
19.7%
3 142
 
10.4%
4 75
 
5.5%
5 41
 
3.0%
6 29
 
2.1%
7 18
 
1.3%
8 16
 
1.2%
9 11
 
0.8%
10 6
 
0.4%
Other values (12) 20
 
1.5%
ValueCountFrequency (%)
1 740
54.1%
2 270
 
19.7%
3 142
 
10.4%
4 75
 
5.5%
5 41
 
3.0%
6 29
 
2.1%
7 18
 
1.3%
8 16
 
1.2%
9 11
 
0.8%
10 6
 
0.4%
ValueCountFrequency (%)
195 1
0.1%
194 1
0.1%
179 1
0.1%
178 1
0.1%
18 1
0.1%
17 1
0.1%
16 1
0.1%
15 1
0.1%
14 1
0.1%
13 2
0.1%

Interactions

2024-04-21T02:32:14.009328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T02:32:26.040652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수정자과제별기술순번
수정자1.0000.819
과제별기술순번0.8191.000
2024-04-21T02:32:26.174326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과제별기술순번수정자
과제별기술순번1.0000.613
수정자0.6131.000

Missing values

2024-04-21T02:32:14.572498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T02:32:14.962302image/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

예고기술생성자생성일시수정자수정일시과제과제별기술순번
0754XKHH0I0009A6000754U6G2N000005W0042015-03-27 오전 9:33:46754U6G2N000005W0042015-03-31 오후 3:51:38754XJX9R700092D0001
1754XKHHHA0009AR000754U6G2N000005W0012015-03-27 오전 9:39:50754U6G2N000005W0012015-03-27 오전 9:49:22754XJWX470008VK0002
2754XKHIUQ0009D5000754U6G2N000005W0032015-03-27 오전 9:57:30754U6G2N000005W0032015-03-31 오전 9:13:55754XJX1LK0008WD0001
3754XKHIED0009BU000754U6G2N000005W0052015-03-27 오전 9:51:41754U6G2N000005W0052015-03-31 오후 3:46:25754XJX5X700091J0001
4754XKHU1H0009RJ000754U6G2N000005W0032015-03-27 오전 11:02:29754U6G2N000005W0032015-03-31 오후 5:32:38754XJX27I0008WZ0003
5754XKHIUZ0009DB000754U6G2N000005W0042015-03-27 오전 9:57:39754U6G2N000005W0042015-03-31 오후 3:54:21754XJX9R700092D0008
6754XKHMNE0009FT000754U6G2N000005W0042015-03-27 오전 10:06:50754U6G2N000005W0042015-03-31 오후 3:56:32754XJX9R700092D0002
7754XKHMYF0009G1000754U6G2N000005W0032015-03-27 오전 10:10:47754U6G2N000005W0032015-03-31 오전 9:21:08754XJX1LK0008WD0003
8754XKHMZW0009GA000754U6G2N000005W0052015-03-27 오전 10:11:00754U6G2N000005W0052015-03-31 오후 3:54:36754XJX9IP0009210001
9754XKHM860009EE000754U6G2N000005W0052015-03-27 오전 10:01:02754U6G2N000005W0052015-03-31 오후 3:51:31754XJX9IP0009210003
예고기술생성자생성일시수정자수정일시과제과제별기술순번
135875NFUC3KN060BLQ0007557872Y801UZ5E0002019-06-14 오전 11:20:23<NA><NA>75NB3ES7Z05USO1PJ03
135975NFUC53N060BN20007557872Y801UZ5E0002019-06-14 오전 11:40:03<NA><NA>75NB3ES7Z05USO1PJ04
136075NFUDT0K060C9700075J2ZTAGP05JU7N0002019-06-14 오후 7:16:52<NA><NA>75N7MDQP305POQTPJ03
136175NFUDTWS060C9U00075J464SPW05K1V20002019-06-14 오후 7:28:12<NA><NA>75N7UPT6W05QAAZPJ07
136275NFUDUSL060CAO000759PHF7IL04L1P80002019-06-14 오후 7:39:57<NA><NA>75N7MZ6AM05PSQXPJ01
136375NFUDZSO060CBX00075J2ZT56E05JU6V0002019-06-14 오후 8:04:40<NA><NA>75N7UPT6W05QAAZPJ08
136475NFUY7IF060ENB00075NFQU2JK05ZWZS0002019-06-15 오후 2:35:59<NA><NA>75N90ZL7S05QHQUPJ01
136575NFUY99T060ENR00075NFQU2JK05ZWZS0002019-06-15 오후 2:58:41<NA><NA>75N90ZL7S05QHQUPJ02
136675NFUYCZ0060EO700075NFQU2JK05ZWZS0002019-06-15 오후 3:06:36<NA><NA>75N90ZL7S05QHQUPJ03
136775NFUYDHX060EOH00075NFQU2JK05ZWZS0002019-06-15 오후 3:13:17<NA><NA>75N90ZL7S05QHQUPJ04