Overview

Dataset statistics

Number of variables10
Number of observations125
Missing cells24
Missing cells (%)1.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.0 KiB
Average record size in memory82.1 B

Variable types

Numeric1
Text4
Categorical4
DateTime1

Dataset

Description인천광역시 bizok 시 우수기업 선정 현황(기업명,대표자명,생산품목, 전화번호, 등록일 등)에 대한 데이터를 제공 합니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15049265&srcSe=7661IVAWM27C61E190

Alerts

등록아이디 has constant value ""Constant
지정기간시작 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
지정기간끝 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
구분 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
번호 is highly overall correlated with 지정기간시작 and 2 other fieldsHigh correlation
전화번호 has 24 (19.2%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2024-01-28 09:14:55.667141
Analysis finished2024-01-28 09:14:56.350973
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct125
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63
Minimum1
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-28T18:14:56.408090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.2
Q132
median63
Q394
95-th percentile118.8
Maximum125
Range124
Interquartile range (IQR)62

Descriptive statistics

Standard deviation36.228442
Coefficient of variation (CV)0.57505463
Kurtosis-1.2
Mean63
Median Absolute Deviation (MAD)31
Skewness0
Sum7875
Variance1312.5
MonotonicityStrictly increasing
2024-01-28T18:14:56.518237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
80 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
Other values (115) 115
92.0%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%

기업명
Text

Distinct121
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T18:14:56.744221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.296
Min length2

Characters and Unicode

Total characters912
Distinct characters182
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)93.6%

Sample

1st row(주)신성피엔텍
2nd row케이와이피씨(주)
3rd row(주)핵광산업
4th row오병이어(주)
5th row(주)현다이엔지
ValueCountFrequency (%)
나이프코리아(주 2
 
1.6%
나이프플러스(주 2
 
1.6%
주)현다이엔지 2
 
1.6%
이솔정보통신(주 2
 
1.6%
주)신성피엔텍 1
 
0.8%
주)나노앤텍 1
 
0.8%
대덕기계 1
 
0.8%
화성 1
 
0.8%
가람환경기술(주 1
 
0.8%
우양기공(주 1
 
0.8%
Other values (111) 111
88.8%
2024-01-28T18:14:57.080452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 115
 
12.6%
( 113
 
12.4%
) 113
 
12.4%
이 37
 
4.1%
스 30
 
3.3%
에 14
 
1.5%
지 12
 
1.3%
아 11
 
1.2%
크 10
 
1.1%
신 10
 
1.1%
Other values (172) 447
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 678
74.3%
Open Punctuation 113
 
12.4%
Close Punctuation 113
 
12.4%
Uppercase Letter 8
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 115
 
17.0%
이 37
 
5.5%
스 30
 
4.4%
에 14
 
2.1%
지 12
 
1.8%
아 11
 
1.6%
크 10
 
1.5%
신 10
 
1.5%
기 10
 
1.5%
엔 10
 
1.5%
Other values (163) 419
61.8%
Uppercase Letter
ValueCountFrequency (%)
S 2
25.0%
L 1
12.5%
D 1
12.5%
M 1
12.5%
G 1
12.5%
C 1
12.5%
R 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 113
100.0%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 678
74.3%
Common 226
 
24.8%
Latin 8
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 115
 
17.0%
이 37
 
5.5%
스 30
 
4.4%
에 14
 
2.1%
지 12
 
1.8%
아 11
 
1.6%
크 10
 
1.5%
신 10
 
1.5%
기 10
 
1.5%
엔 10
 
1.5%
Other values (163) 419
61.8%
Latin
ValueCountFrequency (%)
S 2
25.0%
L 1
12.5%
D 1
12.5%
M 1
12.5%
G 1
12.5%
C 1
12.5%
R 1
12.5%
Common
ValueCountFrequency (%)
( 113
50.0%
) 113
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 678
74.3%
ASCII 234
 
25.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 115
 
17.0%
이 37
 
5.5%
스 30
 
4.4%
에 14
 
2.1%
지 12
 
1.8%
아 11
 
1.6%
크 10
 
1.5%
신 10
 
1.5%
기 10
 
1.5%
엔 10
 
1.5%
Other values (163) 419
61.8%
ASCII
ValueCountFrequency (%)
( 113
48.3%
) 113
48.3%
S 2
 
0.9%
L 1
 
0.4%
D 1
 
0.4%
M 1
 
0.4%
G 1
 
0.4%
C 1
 
0.4%
R 1
 
0.4%

대표자명
Text

Distinct120
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T18:14:57.354539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.32
Min length3

Characters and Unicode

Total characters415
Distinct characters114
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)92.8%

Sample

1st row하현정, 김경훈
2nd row강영구
3rd row정영섭
4th row한상만
5th row김성훈
ValueCountFrequency (%)
유경석 3
 
2.3%
이정협 2
 
1.5%
심영수 2
 
1.5%
김성훈 2
 
1.5%
한윤희 1
 
0.8%
서일석 1
 
0.8%
이성진 1
 
0.8%
이우봉 1
 
0.8%
반은상 1
 
0.8%
박주철 1
 
0.8%
Other values (118) 118
88.7%
2024-01-28T18:14:57.731756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 23
 
5.5%
김 22
 
5.3%
수 14
 
3.4%
경 11
 
2.7%
석 11
 
2.7%
영 11
 
2.7%
정 10
 
2.4%
진 10
 
2.4%
유 9
 
2.2%
박 9
 
2.2%
Other values (104) 285
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 399
96.1%
Other Punctuation 8
 
1.9%
Space Separator 8
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 23
 
5.8%
김 22
 
5.5%
수 14
 
3.5%
경 11
 
2.8%
석 11
 
2.8%
영 11
 
2.8%
정 10
 
2.5%
진 10
 
2.5%
유 9
 
2.3%
박 9
 
2.3%
Other values (102) 269
67.4%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 399
96.1%
Common 16
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 23
 
5.8%
김 22
 
5.5%
수 14
 
3.5%
경 11
 
2.8%
석 11
 
2.8%
영 11
 
2.8%
정 10
 
2.5%
진 10
 
2.5%
유 9
 
2.3%
박 9
 
2.3%
Other values (102) 269
67.4%
Common
ValueCountFrequency (%)
, 8
50.0%
8
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 399
96.1%
ASCII 16
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 23
 
5.8%
김 22
 
5.5%
수 14
 
3.5%
경 11
 
2.8%
석 11
 
2.8%
영 11
 
2.8%
정 10
 
2.5%
진 10
 
2.5%
유 9
 
2.3%
박 9
 
2.3%
Other values (102) 269
67.4%
ASCII
ValueCountFrequency (%)
, 8
50.0%
8
50.0%

생산품목
Text

Distinct124
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T18:14:57.946871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length21
Mean length11.424
Min length2

Characters and Unicode

Total characters1428
Distinct characters282
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)98.4%

Sample

1st row친환경복사용지
2nd row레미콘, 아스콘
3rd row방사선 차폐장치
4th row잉크충전기 재생토너
5th rowLED 투광등
ValueCountFrequency (%)
49
 
14.2%
외 19
 
5.5%
및 6
 
1.7%
플라스틱 6
 
1.7%
자동차 4
 
1.2%
부품 4
 
1.2%
led 3
 
0.9%
sheet 2
 
0.6%
용기 2
 
0.6%
의료기기 2
 
0.6%
Other values (238) 247
71.8%
2024-01-28T18:14:58.263497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
219
 
15.3%
기 54
 
3.8%
/ 52
 
3.6%
용 32
 
2.2%
스 27
 
1.9%
전 27
 
1.9%
품 25
 
1.8%
이 20
 
1.4%
자 20
 
1.4%
외 19
 
1.3%
Other values (272) 933
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1016
71.1%
Space Separator 219
 
15.3%
Uppercase Letter 91
 
6.4%
Other Punctuation 67
 
4.7%
Lowercase Letter 22
 
1.5%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%
Decimal Number 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 54
 
5.3%
용 32
 
3.1%
스 27
 
2.7%
전 27
 
2.7%
품 25
 
2.5%
이 20
 
2.0%
자 20
 
2.0%
외 19
 
1.9%
동 19
 
1.9%
장 18
 
1.8%
Other values (237) 755
74.3%
Uppercase Letter
ValueCountFrequency (%)
E 13
14.3%
D 10
11.0%
L 8
 
8.8%
S 7
 
7.7%
B 6
 
6.6%
C 6
 
6.6%
T 5
 
5.5%
O 5
 
5.5%
A 5
 
5.5%
U 4
 
4.4%
Other values (8) 22
24.2%
Lowercase Letter
ValueCountFrequency (%)
t 4
18.2%
l 4
18.2%
e 4
18.2%
a 3
13.6%
y 2
9.1%
g 1
 
4.5%
v 1
 
4.5%
f 1
 
4.5%
r 1
 
4.5%
u 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
/ 52
77.6%
, 14
 
20.9%
' 1
 
1.5%
Space Separator
ValueCountFrequency (%)
219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Decimal Number
ValueCountFrequency (%)
2 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1016
71.1%
Common 299
 
20.9%
Latin 113
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 54
 
5.3%
용 32
 
3.1%
스 27
 
2.7%
전 27
 
2.7%
품 25
 
2.5%
이 20
 
2.0%
자 20
 
2.0%
외 19
 
1.9%
동 19
 
1.9%
장 18
 
1.8%
Other values (237) 755
74.3%
Latin
ValueCountFrequency (%)
E 13
 
11.5%
D 10
 
8.8%
L 8
 
7.1%
S 7
 
6.2%
B 6
 
5.3%
C 6
 
5.3%
T 5
 
4.4%
O 5
 
4.4%
A 5
 
4.4%
U 4
 
3.5%
Other values (18) 44
38.9%
Common
ValueCountFrequency (%)
219
73.2%
/ 52
 
17.4%
, 14
 
4.7%
( 5
 
1.7%
) 5
 
1.7%
2 3
 
1.0%
' 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1016
71.1%
ASCII 412
28.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219
53.2%
/ 52
 
12.6%
, 14
 
3.4%
E 13
 
3.2%
D 10
 
2.4%
L 8
 
1.9%
S 7
 
1.7%
B 6
 
1.5%
C 6
 
1.5%
T 5
 
1.2%
Other values (25) 72
 
17.5%
Hangul
ValueCountFrequency (%)
기 54
 
5.3%
용 32
 
3.1%
스 27
 
2.7%
전 27
 
2.7%
품 25
 
2.5%
이 20
 
2.0%
자 20
 
2.0%
외 19
 
1.9%
동 19
 
1.9%
장 18
 
1.8%
Other values (237) 755
74.3%

전화번호
Text

MISSING 

Distinct101
Distinct (%)100.0%
Missing24
Missing (%)19.2%
Memory size1.1 KiB
2024-01-28T18:14:58.494011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.039604
Min length12

Characters and Unicode

Total characters1216
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)100.0%

Sample

1st row070-7776-0159
2nd row032-813-2345
3rd row032-578-6063
4th row032-562-9174
5th row032-581-6923
ValueCountFrequency (%)
032-678-4562 1
 
1.0%
070-4713-0670 1
 
1.0%
032-204-1900 1
 
1.0%
032-876-8743 1
 
1.0%
032-345-2611 1
 
1.0%
032-817-8030 1
 
1.0%
070-7585-5706 1
 
1.0%
032-812-9914 1
 
1.0%
032-815-8855 1
 
1.0%
032-548-5172 1
 
1.0%
Other values (91) 91
90.1%
2024-01-28T18:14:58.810158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 202
16.6%
0 184
15.1%
2 157
12.9%
3 146
12.0%
1 105
8.6%
5 104
8.6%
8 90
7.4%
6 74
 
6.1%
7 60
 
4.9%
4 52
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1014
83.4%
Dash Punctuation 202
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 184
18.1%
2 157
15.5%
3 146
14.4%
1 105
10.4%
5 104
10.3%
8 90
8.9%
6 74
7.3%
7 60
 
5.9%
4 52
 
5.1%
9 42
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1216
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 202
16.6%
0 184
15.1%
2 157
12.9%
3 146
12.0%
1 105
8.6%
5 104
8.6%
8 90
7.4%
6 74
 
6.1%
7 60
 
4.9%
4 52
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 202
16.6%
0 184
15.1%
2 157
12.9%
3 146
12.0%
1 105
8.6%
5 104
8.6%
8 90
7.4%
6 74
 
6.1%
7 60
 
4.9%
4 52
 
4.3%

지정기간시작
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2019-11-06
101 
2020-07-01
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-07-01
2nd row2020-07-01
3rd row2020-07-01
4th row2020-07-01
5th row2020-07-01

Common Values

ValueCountFrequency (%)
2019-11-06 101
80.8%
2020-07-01 24
 
19.2%

Length

2024-01-28T18:14:58.922187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:14:59.002357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-11-06 101
80.8%
2020-07-01 24
 
19.2%

지정기간끝
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2021-11-05
61 
2024-11-05
40 
2022-06-30
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-06-30
2nd row2022-06-30
3rd row2022-06-30
4th row2022-06-30
5th row2022-06-30

Common Values

ValueCountFrequency (%)
2021-11-05 61
48.8%
2024-11-05 40
32.0%
2022-06-30 24
 
19.2%

Length

2024-01-28T18:14:59.086051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:14:59.162091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-11-05 61
48.8%
2024-11-05 40
32.0%
2022-06-30 24
 
19.2%

구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
비전기업
56 
유망중소기업
40 
일자리 창출 우수기업
24 
중견사다리기업
 
5

Length

Max length11
Median length7
Mean length6.104
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일자리 창출 우수기업
2nd row일자리 창출 우수기업
3rd row일자리 창출 우수기업
4th row일자리 창출 우수기업
5th row일자리 창출 우수기업

Common Values

ValueCountFrequency (%)
비전기업 56
44.8%
유망중소기업 40
32.0%
일자리 창출 우수기업 24
19.2%
중견사다리기업 5
 
4.0%

Length

2024-01-28T18:14:59.252742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:14:59.343986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비전기업 56
32.4%
유망중소기업 40
23.1%
일자리 24
13.9%
창출 24
13.9%
우수기업 24
13.9%
중견사다리기업 5
 
2.9%

등록아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
dsyoo
125 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
dsyoo 125
100.0%

Length

2024-01-28T18:14:59.438929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:14:59.756019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
dsyoo 125
100.0%

등록일
Date

Distinct79
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2019-11-08 17:38:00
Maximum2020-07-02 13:23:00
2024-01-28T18:14:59.834976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:14:59.932359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-01-28T18:14:56.087489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:14:59.997757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지정기간시작지정기간끝구분등록일
번호1.0000.9990.9140.9260.998
지정기간시작0.9991.0001.0001.0001.000
지정기간끝0.9141.0001.0000.7091.000
구분0.9261.0000.7091.0001.000
등록일0.9981.0001.0001.0001.000
2024-01-28T18:15:00.084867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정기간시작지정기간끝구분
지정기간시작1.0000.9960.992
지정기간끝0.9961.0000.745
구분0.9920.7451.000
2024-01-28T18:15:00.159773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지정기간시작지정기간끝구분
번호1.0000.9420.8520.808
지정기간시작0.9421.0000.9960.992
지정기간끝0.8520.9961.0000.745
구분0.8080.9920.7451.000

Missing values

2024-01-28T18:14:56.182029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:14:56.309134image/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

번호기업명대표자명생산품목전화번호지정기간시작지정기간끝구분등록아이디등록일
01(주)신성피엔텍하현정, 김경훈친환경복사용지<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:23
12케이와이피씨(주)강영구레미콘, 아스콘<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:23
23(주)핵광산업정영섭방사선 차폐장치<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:22
34오병이어(주)한상만잉크충전기 재생토너<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:21
45(주)현다이엔지김성훈LED 투광등<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:21
56이솔정보통신(주)이정협인터렉티브 화이트보드<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:20
67(주)뉴겐코스메틱권락균이미용 재료<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:19
78(주)이노테크미디어윤두현실김미디어(S/W, H/W)<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:19
89대원인물(주)최도현공업용 인물 및 스프링<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:18
910삼영물류(주)이상근화물운송주선 외<NA>2020-07-012022-06-30일자리 창출 우수기업dsyoo2020-07-02 13:17
번호기업명대표자명생산품목전화번호지정기간시작지정기간끝구분등록아이디등록일
115116(주)메드믹스임수정의료기기032-720-58002019-11-062021-11-05유망중소기업dsyoo2019-11-08 17:51
116117(주)오넥트박미설사무용가구032-575-99002019-11-062021-11-05유망중소기업dsyoo2019-11-08 17:51
117118(주)피케이엘앤에스박성우전자교탁, 전자칠판032-552-35962019-11-062021-11-05유망중소기업dsyoo2019-11-08 17:50
118119(주)세창케미컬김동원화학약품032-581-50302019-11-062021-11-05유망중소기업dsyoo2019-11-08 17:50
119120(주)현다이엔지김성훈자동제어 / 조명기구032-815-48662019-11-062021-11-05유망중소기업dsyoo2019-11-08 17:47
120121동인중공업(주)최성진유압브레이커 / 어태치먼트032-821-69112019-11-062024-11-05중견사다리기업dsyoo2019-11-08 17:40
121122(주)미트뱅크김영준소시지 / 양념육032-561-52092019-11-062024-11-05중견사다리기업dsyoo2019-11-08 17:39
122123(주)바낙스장용수낚시장비032-550-20122019-11-062024-11-05중견사다리기업dsyoo2019-11-08 17:39
123124(주)예림임업전용진목재문032-858-21202019-11-062021-11-05중견사다리기업dsyoo2019-11-08 17:38
124125신진화학(주)문창호자동차플라스틱부품032-810-82002019-11-062021-11-05중견사다리기업dsyoo2019-11-08 17:38