Overview

Dataset statistics

Number of variables19
Number of observations137
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.5 KiB
Average record size in memory153.0 B

Variable types

Text4
Categorical15

Dataset

Description한국나노기술원에서 제공하는 나노소자팹 장비별 적용 가능한 기판 정보입니다.(장비명, 적용가능한 기판 종류, 사이즈, 기판유형, 기판 두께 등) * 장비 상세 정보 : 한국나노기술원_나노소자팹서비스 및 연구공정장비 정보(https://www.data.go.kr/data/15037530/fileData.do)에서 확인 가능합니다.
URLhttps://www.data.go.kr/data/15088740/fileData.do

Alerts

기판두께(Normal) has constant value ""Constant
담당자 is highly overall correlated with 기판종류(III-V) and 8 other fieldsHigh correlation
기판종류(Si) is highly overall correlated with 기판종류(Glass)High correlation
기판종류(III-V) is highly overall correlated with 담당자High correlation
기판종류(Glass) is highly overall correlated with 담당자 and 1 other fieldsHigh correlation
기판종류(Flex) is highly overall correlated with 담당자High correlation
기판크기(2인치) is highly overall correlated with 담당자 and 1 other fieldsHigh correlation
기판크기(4인치) is highly overall correlated with 담당자 and 2 other fieldsHigh correlation
기판크기(6인치) is highly overall correlated with 담당자 and 1 other fieldsHigh correlation
기판크기(12인치) is highly overall correlated with 담당자High correlation
기판유형(플랫) is highly overall correlated with 담당자High correlation
기판유형(노치) is highly overall correlated with 담당자High correlation
기판종류(Si) is highly imbalanced (54.7%)Imbalance
기판크기(12인치) is highly imbalanced (78.9%)Imbalance
기판유형(플랫) is highly imbalanced (59.5%)Imbalance
장비코드 has unique valuesUnique
장비명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:29:12.238113
Analysis finished2023-12-12 06:29:14.346176
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

장비코드
Text

UNIQUE 

Distinct137
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T15:29:14.678091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters959
Distinct characters30
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

Unique137 ?
Unique (%)100.0%

Sample

1st rowFL-EL10
2nd rowFL-EL20
3rd rowFL-NI10
4th rowFL-ST10
5th rowFL-ST20
ValueCountFrequency (%)
fl-el10 1
 
0.7%
ff-ie30 1
 
0.7%
fe-mc60 1
 
0.7%
fe-mc50 1
 
0.7%
fe-mc40 1
 
0.7%
fe-mc30 1
 
0.7%
fe-mc20 1
 
0.7%
fe-mc10 1
 
0.7%
fe-sr10 1
 
0.7%
fe-xd10 1
 
0.7%
Other values (127) 127
92.7%
2023-12-12T15:29:15.284259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
F 164
17.1%
- 137
14.3%
0 137
14.3%
1 79
 
8.2%
L 48
 
5.0%
C 44
 
4.6%
R 41
 
4.3%
E 38
 
4.0%
S 37
 
3.9%
B 30
 
3.1%
Other values (20) 204
21.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 548
57.1%
Decimal Number 274
28.6%
Dash Punctuation 137
 
14.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 164
29.9%
L 48
 
8.8%
C 44
 
8.0%
R 41
 
7.5%
E 38
 
6.9%
S 37
 
6.8%
B 30
 
5.5%
M 29
 
5.3%
P 25
 
4.6%
I 19
 
3.5%
Other values (11) 73
13.3%
Decimal Number
ValueCountFrequency (%)
0 137
50.0%
1 79
28.8%
2 28
 
10.2%
3 14
 
5.1%
4 7
 
2.6%
6 4
 
1.5%
5 3
 
1.1%
7 2
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 548
57.1%
Common 411
42.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 164
29.9%
L 48
 
8.8%
C 44
 
8.0%
R 41
 
7.5%
E 38
 
6.9%
S 37
 
6.8%
B 30
 
5.5%
M 29
 
5.3%
P 25
 
4.6%
I 19
 
3.5%
Other values (11) 73
13.3%
Common
ValueCountFrequency (%)
- 137
33.3%
0 137
33.3%
1 79
19.2%
2 28
 
6.8%
3 14
 
3.4%
4 7
 
1.7%
6 4
 
1.0%
5 3
 
0.7%
7 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 959
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F 164
17.1%
- 137
14.3%
0 137
14.3%
1 79
 
8.2%
L 48
 
5.0%
C 44
 
4.6%
R 41
 
4.3%
E 38
 
4.0%
S 37
 
3.9%
B 30
 
3.1%
Other values (20) 204
21.3%

장비명
Text

UNIQUE 

Distinct137
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T15:29:15.713518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length25
Mean length17.985401
Min length3

Characters and Unicode

Total characters2464
Distinct characters82
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)100.0%

Sample

1st rowE-beam lithography I (9300)
2nd rowE-beam lithography II (6000)
3rd rowNano Imprint
4th rowKrF Stepper
5th rowl-line Stepper
ValueCountFrequency (%)
i 18
 
4.6%
ii 18
 
4.6%
iii 12
 
3.1%
산업화 11
 
2.8%
machine 10
 
2.6%
etcher 9
 
2.3%
r&d 8
 
2.1%
e-beam 7
 
1.8%
mocvd 7
 
1.8%
system 7
 
1.8%
Other values (167) 281
72.4%
2023-12-12T15:29:16.241129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
 
10.4%
e 182
 
7.4%
t 125
 
5.1%
I 124
 
5.0%
a 123
 
5.0%
n 112
 
4.5%
i 112
 
4.5%
r 105
 
4.3%
c 87
 
3.5%
o 82
 
3.3%
Other values (72) 1156
46.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1334
54.1%
Uppercase Letter 561
22.8%
Space Separator 256
 
10.4%
Close Punctuation 71
 
2.9%
Open Punctuation 71
 
2.9%
Decimal Number 51
 
2.1%
Other Letter 46
 
1.9%
Dash Punctuation 38
 
1.5%
Other Punctuation 33
 
1.3%
Letter Number 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 182
13.6%
t 125
9.4%
a 123
9.2%
n 112
 
8.4%
i 112
 
8.4%
r 105
 
7.9%
c 87
 
6.5%
o 82
 
6.1%
s 56
 
4.2%
h 53
 
4.0%
Other values (14) 297
22.3%
Uppercase Letter
ValueCountFrequency (%)
I 124
22.1%
D 53
9.4%
M 48
 
8.6%
C 43
 
7.7%
S 35
 
6.2%
P 32
 
5.7%
A 32
 
5.7%
E 31
 
5.5%
R 26
 
4.6%
V 23
 
4.1%
Other values (13) 114
20.3%
Other Letter
ValueCountFrequency (%)
화 12
26.1%
업 12
26.1%
산 12
26.1%
시 1
 
2.2%
스 1
 
2.2%
측 1
 
2.2%
항 1
 
2.2%
저 1
 
2.2%
면 1
 
2.2%
정 1
 
2.2%
Other values (3) 3
 
6.5%
Decimal Number
ValueCountFrequency (%)
0 15
29.4%
8 8
15.7%
6 7
13.7%
4 5
 
9.8%
2 4
 
7.8%
3 4
 
7.8%
5 3
 
5.9%
1 2
 
3.9%
9 2
 
3.9%
7 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
& 21
63.6%
/ 5
 
15.2%
, 3
 
9.1%
: 2
 
6.1%
. 2
 
6.1%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
33.3%
Ⅵ 1
33.3%
Ⅱ 1
33.3%
Space Separator
ValueCountFrequency (%)
256
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1898
77.0%
Common 520
 
21.1%
Hangul 46
 
1.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 182
 
9.6%
t 125
 
6.6%
I 124
 
6.5%
a 123
 
6.5%
n 112
 
5.9%
i 112
 
5.9%
r 105
 
5.5%
c 87
 
4.6%
o 82
 
4.3%
s 56
 
3.0%
Other values (40) 790
41.6%
Common
ValueCountFrequency (%)
256
49.2%
) 71
 
13.7%
( 71
 
13.7%
- 38
 
7.3%
& 21
 
4.0%
0 15
 
2.9%
8 8
 
1.5%
6 7
 
1.3%
/ 5
 
1.0%
4 5
 
1.0%
Other values (9) 23
 
4.4%
Hangul
ValueCountFrequency (%)
화 12
26.1%
업 12
26.1%
산 12
26.1%
시 1
 
2.2%
스 1
 
2.2%
측 1
 
2.2%
항 1
 
2.2%
저 1
 
2.2%
면 1
 
2.2%
정 1
 
2.2%
Other values (3) 3
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2415
98.0%
Hangul 46
 
1.9%
Number Forms 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
 
10.6%
e 182
 
7.5%
t 125
 
5.2%
I 124
 
5.1%
a 123
 
5.1%
n 112
 
4.6%
i 112
 
4.6%
r 105
 
4.3%
c 87
 
3.6%
o 82
 
3.4%
Other values (56) 1107
45.8%
Hangul
ValueCountFrequency (%)
화 12
26.1%
업 12
26.1%
산 12
26.1%
시 1
 
2.2%
스 1
 
2.2%
측 1
 
2.2%
항 1
 
2.2%
저 1
 
2.2%
면 1
 
2.2%
정 1
 
2.2%
Other values (3) 3
 
6.5%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
33.3%
Ⅵ 1
33.3%
Ⅱ 1
33.3%

제작사
Text

Distinct74
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T15:29:16.547354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length6.2189781
Min length3

Characters and Unicode

Total characters852
Distinct characters85
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

Unique47 ?
Unique (%)34.3%

Sample

1st rowJEOL
2nd rowJEOL
3rd rowObducat
4th rowASML
5th rowNIKON
ValueCountFrequency (%)
아티스 12
 
7.5%
aixtron 6
 
3.8%
svs 5
 
3.1%
ulvac 5
 
3.1%
hitachi 5
 
3.1%
gatan 4
 
2.5%
unaxis 4
 
2.5%
jeol 4
 
2.5%
tech 4
 
2.5%
thermofisher 3
 
1.9%
Other values (78) 107
67.3%
2023-12-12T15:29:17.012444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 46
 
5.4%
t 43
 
5.0%
e 42
 
4.9%
A 36
 
4.2%
i 35
 
4.1%
a 35
 
4.1%
r 33
 
3.9%
c 32
 
3.8%
E 29
 
3.4%
o 28
 
3.3%
Other values (75) 493
57.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 383
45.0%
Uppercase Letter 356
41.8%
Other Letter 86
 
10.1%
Space Separator 24
 
2.8%
Other Punctuation 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 13
15.1%
스 13
15.1%
티 12
14.0%
성 4
 
4.7%
밍 3
 
3.5%
포 3
 
3.5%
원 3
 
3.5%
텍 3
 
3.5%
노 2
 
2.3%
이 2
 
2.3%
Other values (26) 28
32.6%
Uppercase Letter
ValueCountFrequency (%)
S 46
12.9%
A 36
 
10.1%
E 29
 
8.1%
T 25
 
7.0%
C 24
 
6.7%
L 21
 
5.9%
N 20
 
5.6%
O 18
 
5.1%
U 17
 
4.8%
M 17
 
4.8%
Other values (14) 103
28.9%
Lowercase Letter
ValueCountFrequency (%)
t 43
11.2%
e 42
11.0%
i 35
9.1%
a 35
9.1%
r 33
8.6%
c 32
8.4%
o 28
7.3%
h 26
6.8%
n 24
 
6.3%
s 24
 
6.3%
Other values (11) 61
15.9%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 739
86.7%
Hangul 86
 
10.1%
Common 27
 
3.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 46
 
6.2%
t 43
 
5.8%
e 42
 
5.7%
A 36
 
4.9%
i 35
 
4.7%
a 35
 
4.7%
r 33
 
4.5%
c 32
 
4.3%
E 29
 
3.9%
o 28
 
3.8%
Other values (35) 380
51.4%
Hangul
ValueCountFrequency (%)
아 13
15.1%
스 13
15.1%
티 12
14.0%
성 4
 
4.7%
밍 3
 
3.5%
포 3
 
3.5%
원 3
 
3.5%
텍 3
 
3.5%
노 2
 
2.3%
이 2
 
2.3%
Other values (26) 28
32.6%
Common
ValueCountFrequency (%)
24
88.9%
. 1
 
3.7%
- 1
 
3.7%
, 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 766
89.9%
Hangul 86
 
10.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 46
 
6.0%
t 43
 
5.6%
e 42
 
5.5%
A 36
 
4.7%
i 35
 
4.6%
a 35
 
4.6%
r 33
 
4.3%
c 32
 
4.2%
E 29
 
3.8%
o 28
 
3.7%
Other values (39) 407
53.1%
Hangul
ValueCountFrequency (%)
아 13
15.1%
스 13
15.1%
티 12
14.0%
성 4
 
4.7%
밍 3
 
3.5%
포 3
 
3.5%
원 3
 
3.5%
텍 3
 
3.5%
노 2
 
2.3%
이 2
 
2.3%
Other values (26) 28
32.6%

모델명
Text

Distinct109
Distinct (%)80.1%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
2023-12-12T15:29:17.292336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length8.5514706
Min length1

Characters and Unicode

Total characters1163
Distinct characters65
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)70.6%

Sample

1st rowJBX9300FS
2nd rowJBX6000FS/E
3rd rowEitre-8
4th rowPAS5500-300C
5th rowNSR2205-i9c
ValueCountFrequency (%)
12
 
6.6%
co-125d-ns 3
 
1.7%
icp 3
 
1.7%
multipex 3
 
1.7%
vlsaline(oerlikon 3
 
1.7%
series 3
 
1.7%
msx1000 3
 
1.7%
uee 3
 
1.7%
swp-c3d 2
 
1.1%
aix200/4 2
 
1.1%
Other values (132) 144
79.6%
2023-12-12T15:29:17.776523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 142
 
12.2%
- 76
 
6.5%
S 68
 
5.8%
48
 
4.1%
1 46
 
4.0%
E 43
 
3.7%
2 40
 
3.4%
5 38
 
3.3%
M 34
 
2.9%
P 34
 
2.9%
Other values (55) 594
51.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 478
41.1%
Decimal Number 343
29.5%
Lowercase Letter 195
16.8%
Dash Punctuation 76
 
6.5%
Space Separator 48
 
4.1%
Other Punctuation 8
 
0.7%
Open Punctuation 7
 
0.6%
Close Punctuation 7
 
0.6%
Math Symbol 1
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 68
14.2%
E 43
 
9.0%
M 34
 
7.1%
P 34
 
7.1%
A 33
 
6.9%
C 31
 
6.5%
I 26
 
5.4%
L 25
 
5.2%
D 21
 
4.4%
N 19
 
4.0%
Other values (16) 144
30.1%
Lowercase Letter
ValueCountFrequency (%)
e 28
14.4%
i 27
13.8%
r 18
9.2%
a 14
 
7.2%
t 14
 
7.2%
o 13
 
6.7%
l 13
 
6.7%
u 11
 
5.6%
s 11
 
5.6%
c 9
 
4.6%
Other values (10) 37
19.0%
Decimal Number
ValueCountFrequency (%)
0 142
41.4%
1 46
 
13.4%
2 40
 
11.7%
5 38
 
11.1%
3 23
 
6.7%
6 15
 
4.4%
8 14
 
4.1%
4 12
 
3.5%
9 10
 
2.9%
7 3
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/ 5
62.5%
? 1
 
12.5%
& 1
 
12.5%
, 1
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 673
57.9%
Common 490
42.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 68
 
10.1%
E 43
 
6.4%
M 34
 
5.1%
P 34
 
5.1%
A 33
 
4.9%
C 31
 
4.6%
e 28
 
4.2%
i 27
 
4.0%
I 26
 
3.9%
L 25
 
3.7%
Other values (36) 324
48.1%
Common
ValueCountFrequency (%)
0 142
29.0%
- 76
15.5%
48
 
9.8%
1 46
 
9.4%
2 40
 
8.2%
5 38
 
7.8%
3 23
 
4.7%
6 15
 
3.1%
8 14
 
2.9%
4 12
 
2.4%
Other values (9) 36
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 142
 
12.2%
- 76
 
6.5%
S 68
 
5.8%
48
 
4.1%
1 46
 
4.0%
E 43
 
3.7%
2 40
 
3.4%
5 38
 
3.3%
M 34
 
2.9%
P 34
 
2.9%
Other values (55) 594
51.1%

담당자
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
이지선
10 
이용수
10 
강대훈
 
9
장민철
 
8
강세민
 
7
Other values (26)
93 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique6 ?
Unique (%)4.4%

Sample

1st row김영재
2nd row김영재
3rd row김영재
4th row황선용
5th row장민철

Common Values

ValueCountFrequency (%)
이지선 10
 
7.3%
이용수 10
 
7.3%
강대훈 9
 
6.6%
장민철 8
 
5.8%
강세민 7
 
5.1%
고유민 7
 
5.1%
송근만 7
 
5.1%
이병오 6
 
4.4%
허종곤 5
 
3.6%
김현웅 5
 
3.6%
Other values (21) 63
46.0%

Length

2023-12-12T15:29:17.951451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이지선 10
 
7.3%
이용수 10
 
7.3%
강대훈 9
 
6.6%
장민철 8
 
5.8%
강세민 7
 
5.1%
고유민 7
 
5.1%
송근만 7
 
5.1%
이병오 6
 
4.4%
김영재 5
 
3.6%
조명주 5
 
3.6%
Other values (21) 63
46.0%

기판종류(Si)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
124 
X
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
O 124
90.5%
X 13
 
9.5%

Length

2023-12-12T15:29:18.120028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:18.240675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 124
90.5%
x 13
 
9.5%

기판종류(III-V)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
104 
△
22 
X
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th row△
5th rowO

Common Values

ValueCountFrequency (%)
O 104
75.9%
△ 22
 
16.1%
X 11
 
8.0%

Length

2023-12-12T15:29:18.363899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:18.464530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 104
75.9%
△ 22
 
16.1%
x 11
 
8.0%

기판종류(Glass)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
99 
X
27 
△
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th rowO
5th row△

Common Values

ValueCountFrequency (%)
O 99
72.3%
X 27
 
19.7%
△ 11
 
8.0%

Length

2023-12-12T15:29:18.568688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:18.665776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 99
72.3%
x 27
 
19.7%
△ 11
 
8.0%

기판종류(Flex)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
X
64 
△
43 
O
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row△
2nd row△
3rd rowO
4th rowX
5th row△

Common Values

ValueCountFrequency (%)
X 64
46.7%
△ 43
31.4%
O 30
21.9%

Length

2023-12-12T15:29:18.776911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:18.877972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 64
46.7%
△ 43
31.4%
o 30
21.9%

기판크기(조각)
Categorical

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
89 
X
40 
△
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th rowX
5th rowX

Common Values

ValueCountFrequency (%)
O 89
65.0%
X 40
29.2%
△ 8
 
5.8%

Length

2023-12-12T15:29:18.988941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:19.093100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 89
65.0%
x 40
29.2%
△ 8
 
5.8%

기판크기(2인치)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
100 
X
34 
△
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th rowX
5th row△

Common Values

ValueCountFrequency (%)
O 100
73.0%
X 34
 
24.8%
△ 3
 
2.2%

Length

2023-12-12T15:29:19.192792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:19.286777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 100
73.0%
x 34
 
24.8%
△ 3
 
2.2%

기판크기(4인치)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
95 
X
36 
△
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th row△
5th row△

Common Values

ValueCountFrequency (%)
O 95
69.3%
X 36
 
26.3%
△ 6
 
4.4%

Length

2023-12-12T15:29:19.396538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:19.485882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 95
69.3%
x 36
 
26.3%
△ 6
 
4.4%

기판크기(6인치)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
100 
X
35 
△
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th row△
5th rowO

Common Values

ValueCountFrequency (%)
O 100
73.0%
X 35
 
25.5%
△ 2
 
1.5%

Length

2023-12-12T15:29:19.602459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:19.702726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 100
73.0%
x 35
 
25.5%
△ 2
 
1.5%

기판크기(8인치)
Categorical

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
X
73 
O
57 
△
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th rowO
5th row△

Common Values

ValueCountFrequency (%)
X 73
53.3%
O 57
41.6%
△ 7
 
5.1%

Length

2023-12-12T15:29:19.799538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:19.893831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 73
53.3%
o 57
41.6%
△ 7
 
5.1%

기판크기(12인치)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
X
130 
O
 
5
△
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
X 130
94.9%
O 5
 
3.6%
△ 2
 
1.5%

Length

2023-12-12T15:29:20.031177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:20.163142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 130
94.9%
o 5
 
3.6%
△ 2
 
1.5%

기판유형(플랫)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
117 
X
19 
△
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
O 117
85.4%
X 19
 
13.9%
△ 1
 
0.7%

Length

2023-12-12T15:29:20.283829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:20.733311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 117
85.4%
x 19
 
13.9%
△ 1
 
0.7%

기판유형(노치)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
101 
X
29 
△
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th rowO
5th rowX

Common Values

ValueCountFrequency (%)
O 101
73.7%
X 29
 
21.2%
△ 7
 
5.1%

Length

2023-12-12T15:29:20.863374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:20.989077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 101
73.7%
x 29
 
21.2%
△ 7
 
5.1%

기판두께(Normal)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
O
137 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
O 137
100.0%

Length

2023-12-12T15:29:21.146278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:21.278273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 137
100.0%

기판두께(Special)
Categorical

Distinct5
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
△
77 
X
44 
O
8 
1T
 
7
2T
 
1

Length

Max length2
Median length1
Mean length1.0583942
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st rowO
2nd rowO
3rd rowO
4th row1T
5th row1T

Common Values

ValueCountFrequency (%)
△ 77
56.2%
X 44
32.1%
O 8
 
5.8%
1T 7
 
5.1%
2T 1
 
0.7%

Length

2023-12-12T15:29:21.432524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:29:21.585103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
△ 77
56.2%
x 44
32.1%
o 8
 
5.8%
1t 7
 
5.1%
2t 1
 
0.7%

Correlations

2023-12-12T15:29:21.687688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제작사담당자기판종류(Si)기판종류(III-V)기판종류(Glass)기판종류(Flex)기판크기(조각)기판크기(2인치)기판크기(4인치)기판크기(6인치)기판크기(8인치)기판크기(12인치)기판유형(플랫)기판유형(노치)기판두께(Special)
제작사1.0000.9810.9640.9340.9650.9550.8680.9600.9320.9550.7240.5160.3920.9270.958
담당자0.9811.0000.6160.7800.8150.8710.7560.8750.8480.7820.5180.8850.9700.8760.798
기판종류(Si)0.9640.6161.0000.1090.3230.1310.0410.0000.0000.1060.1010.0000.0000.1830.218
기판종류(III-V)0.9340.7800.1091.0000.6160.4290.5910.2590.0800.4810.4630.0000.2500.3410.000
기판종류(Glass)0.9650.8150.3230.6161.0000.6410.3800.7180.6740.4000.0000.4660.0000.5590.211
기판종류(Flex)0.9550.8710.1310.4290.6411.0000.6730.4470.5330.5360.6530.0000.6540.5820.382
기판크기(조각)0.8680.7560.0410.5910.3800.6731.0000.8080.6290.2560.3060.4540.1780.7850.322
기판크기(2인치)0.9600.8750.0000.2590.7180.4470.8081.0000.9300.5850.3150.6860.5350.7110.346
기판크기(4인치)0.9320.8480.0000.0800.6740.5330.6290.9301.0000.8390.4550.6290.7690.7830.470
기판크기(6인치)0.9550.7820.1060.4810.4000.5360.2560.5850.8391.0000.4380.0000.7090.6630.379
기판크기(8인치)0.7240.5180.1010.4630.0000.6530.3060.3150.4550.4381.0000.5180.4630.5990.270
기판크기(12인치)0.5160.8850.0000.0000.4660.0000.4540.6860.6290.0000.5181.0000.0000.4870.361
기판유형(플랫)0.3920.9700.0000.2500.0000.6540.1780.5350.7690.7090.4630.0001.0000.8260.473
기판유형(노치)0.9270.8760.1830.3410.5590.5820.7850.7110.7830.6630.5990.4870.8261.0000.335
기판두께(Special)0.9580.7980.2180.0000.2110.3820.3220.3460.4700.3790.2700.3610.4730.3351.000
2023-12-12T15:29:21.884517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기판종류(III-V)기판크기(8인치)기판유형(노치)기판종류(Flex)기판두께(Special)기판크기(2인치)기판크기(4인치)기판크기(6인치)기판유형(플랫)기판종류(Glass)담당자기판크기(조각)기판종류(Si)기판크기(12인치)
기판종류(III-V)1.0000.1810.1180.1620.0000.0840.0210.1910.0800.2840.5040.2650.1790.000
기판크기(8인치)0.1811.0000.2710.3140.2090.1070.1760.1670.1810.0000.2700.1030.1660.214
기판유형(노치)0.1180.2711.0000.2580.2660.3670.4450.3230.4980.2410.6250.4470.3000.195
기판종류(Flex)0.1620.3140.2581.0000.3110.1720.2240.2260.3150.3040.6180.3320.2150.000
기판두께(Special)0.0000.2090.2660.3111.0000.2770.3990.3070.4030.1600.4710.2540.2630.290
기판크기(2인치)0.0840.1070.3670.1720.2771.0000.6770.2600.2250.3740.6240.4750.0000.344
기판크기(4인치)0.0210.1760.4450.2240.3990.6771.0000.5160.4280.3330.5860.2940.0000.294
기판크기(6인치)0.1910.1670.3230.2260.3070.2600.5161.0000.3650.1470.5060.0820.1740.000
기판유형(플랫)0.0800.1810.4980.3150.4030.2250.4280.3651.0000.0000.8000.0540.0000.000
기판종류(Glass)0.2840.0000.2410.3040.1600.3740.3330.1470.0001.0000.5440.1360.5160.183
담당자0.5040.2700.6250.6180.4710.6240.5860.5060.8000.5441.0000.4770.4690.639
기판크기(조각)0.2650.1030.4470.3320.2540.4750.2940.0820.0540.1360.4771.0000.0670.175
기판종류(Si)0.1790.1660.3000.2150.2630.0000.0000.1740.0000.5160.4690.0671.0000.000
기판크기(12인치)0.0000.2140.1950.0000.2900.3440.2940.0000.0000.1830.6390.1750.0001.000
2023-12-12T15:29:22.066473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
담당자기판종류(Si)기판종류(III-V)기판종류(Glass)기판종류(Flex)기판크기(조각)기판크기(2인치)기판크기(4인치)기판크기(6인치)기판크기(8인치)기판크기(12인치)기판유형(플랫)기판유형(노치)기판두께(Special)
담당자1.0000.4690.5040.5440.6180.4770.6240.5860.5060.2700.6390.8000.6250.471
기판종류(Si)0.4691.0000.1790.5160.2150.0670.0000.0000.1740.1660.0000.0000.3000.263
기판종류(III-V)0.5040.1791.0000.2840.1620.2650.0840.0210.1910.1810.0000.0800.1180.000
기판종류(Glass)0.5440.5160.2841.0000.3040.1360.3740.3330.1470.0000.1830.0000.2410.160
기판종류(Flex)0.6180.2150.1620.3041.0000.3320.1720.2240.2260.3140.0000.3150.2580.311
기판크기(조각)0.4770.0670.2650.1360.3321.0000.4750.2940.0820.1030.1750.0540.4470.254
기판크기(2인치)0.6240.0000.0840.3740.1720.4751.0000.6770.2600.1070.3440.2250.3670.277
기판크기(4인치)0.5860.0000.0210.3330.2240.2940.6771.0000.5160.1760.2940.4280.4450.399
기판크기(6인치)0.5060.1740.1910.1470.2260.0820.2600.5161.0000.1670.0000.3650.3230.307
기판크기(8인치)0.2700.1660.1810.0000.3140.1030.1070.1760.1671.0000.2140.1810.2710.209
기판크기(12인치)0.6390.0000.0000.1830.0000.1750.3440.2940.0000.2141.0000.0000.1950.290
기판유형(플랫)0.8000.0000.0800.0000.3150.0540.2250.4280.3650.1810.0001.0000.4980.403
기판유형(노치)0.6250.3000.1180.2410.2580.4470.3670.4450.3230.2710.1950.4981.0000.266
기판두께(Special)0.4710.2630.0000.1600.3110.2540.2770.3990.3070.2090.2900.4030.2661.000

Missing values

2023-12-12T15:29:13.891717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:29:14.217553image/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

장비코드장비명제작사모델명담당자기판종류(Si)기판종류(III-V)기판종류(Glass)기판종류(Flex)기판크기(조각)기판크기(2인치)기판크기(4인치)기판크기(6인치)기판크기(8인치)기판크기(12인치)기판유형(플랫)기판유형(노치)기판두께(Normal)기판두께(Special)
0FL-EL10E-beam lithography I (9300)JEOLJBX9300FS김영재OOO△OOOOOXOOOO
1FL-EL20E-beam lithography II (6000)JEOLJBX6000FS/E김영재OOO△OOOOOXOOOO
2FL-NI10Nano ImprintObducatEitre-8김영재OOOOOOOOOXOOOO
3FL-ST10KrF StepperASMLPAS5500-300C황선용O△OXXX△△OXOOO1T
4FL-ST20l-line StepperNIKONNSR2205-i9c장민철OO△△X△△O△XOXO1T
5FL-CA10Automated Mask Aligner ISUSS MicrotecMA150e강대훈O△OXXXOOXXOOOX
6FL-CA40Automated Mask Aligner IISUSS MicrotecMA150e강대훈O△OXXOXXXXOOOX
7FL-CA30Contact Aligner I (Manual)EVGroupEVG620강대훈OOO△OOOO△XOOOX
8FL-CA50Contact Aligner III (Manual, 8inch)솔하이텍SHA-80SA강세민OOO△XXXXOXOOOX
9FL-CA60Automated Mask Aligner III (8 inch)우시오UX-3200SC장민철OOO△XXXXOXOOOX
장비코드장비명제작사모델명담당자기판종류(Si)기판종류(III-V)기판종류(Glass)기판종류(Flex)기판크기(조각)기판크기(2인치)기판크기(4인치)기판크기(6인치)기판크기(8인치)기판크기(12인치)기판유형(플랫)기판유형(노치)기판두께(Normal)기판두께(Special)
127FC-MT10MicrotomeLeicaMT990조명주XXXOOXXXXXXXOX
128FC-XP10XPSThermoFisherNEXSA최영수OOOOOXXXXXXXO△
129FS-DC10DC measurement systemFormFactor, KeysightTESLA200, B1505A박덕수OOO△OOOOOXOOO△
130FS-FI10FIB ⅢThermoFisherHelios 5 UX곽상희OOOOOOOOOXOOOX
131FS-AL10ALD-MetalsNCDLucida M300PL-M정해용OO△△△△△OOOO△O△
132FS-AL20ALD-InsulatorsNCDLucida M300PL-O정해용OO△△△△△OOOO△O△
133FS-WS10Wet Station (HF/Acid)썬패치테크노SUN-L19-11황선용O△OXXXX△OXOOO△
134FS-BC10Wafer backside cleaner이노맥스ASTRO2013AWB1NN황선용OXXXXXXXOXOOOX
135FS-SR104 point probe (면저항 측정 시스템)AIMAFP-300김재무OOOXOOOOOOOOO△
136FS-EM10Automatic EllipsometerAIMAE-86심재필O△△XXX△OO△OOO△