Overview

Dataset statistics

Number of variables8
Number of observations325
Missing cells127
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.8 KiB
Average record size in memory65.4 B

Variable types

Numeric1
Text4
Categorical3

Dataset

Description인천광역시 bizok 시 우수기업 선정 현황(기업명,대표자명,생산품목, 전화번호, 등록일 등)에 대한 데이터를 제공 합니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15049265/fileData.do

Alerts

지정기간끝 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
지정기간시작 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
번호 is highly overall correlated with 지정기간시작 and 2 other fieldsHigh correlation
구분 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
전화번호 has 127 (39.1%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:57:33.622327
Analysis finished2023-12-12 16:57:34.477369
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct325
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163
Minimum1
Maximum325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-13T01:57:34.545369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.2
Q182
median163
Q3244
95-th percentile308.8
Maximum325
Range324
Interquartile range (IQR)162

Descriptive statistics

Standard deviation93.963645
Coefficient of variation (CV)0.57646408
Kurtosis-1.2
Mean163
Median Absolute Deviation (MAD)81
Skewness0
Sum52975
Variance8829.1667
MonotonicityStrictly increasing
2023-12-13T01:57:34.707558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
205 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
217 1
 
0.3%
216 1
 
0.3%
Other values (315) 315
96.9%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
325 1
0.3%
324 1
0.3%
323 1
0.3%
322 1
0.3%
321 1
0.3%
320 1
0.3%
319 1
0.3%
318 1
0.3%
317 1
0.3%
316 1
0.3%

기업명
Text

Distinct299
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T01:57:34.949052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length7.2307692
Min length2

Characters and Unicode

Total characters2350
Distinct characters281
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique276 ?
Unique (%)84.9%

Sample

1st row(주)미라지식품
2nd row㈜나우로보틱스
3rd row㈜대신전기산업
4th row㈜디앤푸드
5th row㈜바낙스
ValueCountFrequency (%)
주식회사 6
 
1.8%
이솔정보통신(주 4
 
1.2%
주)현다이엔지 3
 
0.9%
씨피디그룹 2
 
0.6%
㈜이온폴리스 2
 
0.6%
주)아주화장품 2
 
0.6%
나이프코리아(주 2
 
0.6%
주)이노테크미디어 2
 
0.6%
주)뉴겐코스메틱 2
 
0.6%
주)두인 2
 
0.6%
Other values (291) 305
91.9%
2023-12-13T01:57:35.393076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 250
 
10.6%
( 238
 
10.1%
) 238
 
10.1%
이 103
 
4.4%
스 89
 
3.8%
㈜ 50
 
2.1%
에 40
 
1.7%
지 31
 
1.3%
리 30
 
1.3%
크 29
 
1.2%
Other values (271) 1252
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1792
76.3%
Open Punctuation 238
 
10.1%
Close Punctuation 238
 
10.1%
Other Symbol 50
 
2.1%
Uppercase Letter 22
 
0.9%
Space Separator 7
 
0.3%
Decimal Number 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 250
 
14.0%
이 103
 
5.7%
스 89
 
5.0%
에 40
 
2.2%
지 31
 
1.7%
리 30
 
1.7%
크 29
 
1.6%
코 28
 
1.6%
테 27
 
1.5%
아 26
 
1.5%
Other values (251) 1139
63.6%
Uppercase Letter
ValueCountFrequency (%)
M 4
18.2%
S 3
13.6%
L 2
9.1%
A 2
9.1%
C 2
9.1%
E 1
 
4.5%
G 1
 
4.5%
D 1
 
4.5%
R 1
 
4.5%
O 1
 
4.5%
Other values (4) 4
18.2%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 238
100.0%
Close Punctuation
ValueCountFrequency (%)
) 238
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 50
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1842
78.4%
Common 486
 
20.7%
Latin 22
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 250
 
13.6%
이 103
 
5.6%
스 89
 
4.8%
㈜ 50
 
2.7%
에 40
 
2.2%
지 31
 
1.7%
리 30
 
1.6%
크 29
 
1.6%
코 28
 
1.5%
테 27
 
1.5%
Other values (252) 1165
63.2%
Latin
ValueCountFrequency (%)
M 4
18.2%
S 3
13.6%
L 2
9.1%
A 2
9.1%
C 2
9.1%
E 1
 
4.5%
G 1
 
4.5%
D 1
 
4.5%
R 1
 
4.5%
O 1
 
4.5%
Other values (4) 4
18.2%
Common
ValueCountFrequency (%)
( 238
49.0%
) 238
49.0%
7
 
1.4%
2 2
 
0.4%
1 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1792
76.3%
ASCII 508
 
21.6%
None 50
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 250
 
14.0%
이 103
 
5.7%
스 89
 
5.0%
에 40
 
2.2%
지 31
 
1.7%
리 30
 
1.7%
크 29
 
1.6%
코 28
 
1.6%
테 27
 
1.5%
아 26
 
1.5%
Other values (251) 1139
63.6%
ASCII
ValueCountFrequency (%)
( 238
46.9%
) 238
46.9%
7
 
1.4%
M 4
 
0.8%
S 3
 
0.6%
L 2
 
0.4%
A 2
 
0.4%
C 2
 
0.4%
2 2
 
0.4%
E 1
 
0.2%
Other values (9) 9
 
1.8%
None
ValueCountFrequency (%)
㈜ 50
100.0%

대표자명
Text

Distinct284
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T01:57:35.738975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.3569231
Min length2

Characters and Unicode

Total characters1091
Distinct characters145
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

Unique254 ?
Unique (%)78.2%

Sample

1st row김준택,기정희
2nd row이종주
3rd row김진숙
4th row박성규
5th row장용수
ValueCountFrequency (%)
이정협 5
 
1.4%
심영수 4
 
1.2%
최순필 3
 
0.9%
황규진 3
 
0.9%
박성우 3
 
0.9%
김성훈 3
 
0.9%
이종주 3
 
0.9%
유경석 3
 
0.9%
이민구 2
 
0.6%
홍기수 2
 
0.6%
Other values (293) 315
91.0%
2023-12-13T01:57:36.213976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 61
 
5.6%
김 61
 
5.6%
박 33
 
3.0%
정 29
 
2.7%
성 27
 
2.5%
수 25
 
2.3%
석 25
 
2.3%
, 24
 
2.2%
22
 
2.0%
진 22
 
2.0%
Other values (135) 762
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1045
95.8%
Other Punctuation 24
 
2.2%
Space Separator 22
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 61
 
5.8%
김 61
 
5.8%
박 33
 
3.2%
정 29
 
2.8%
성 27
 
2.6%
수 25
 
2.4%
석 25
 
2.4%
진 22
 
2.1%
호 21
 
2.0%
영 21
 
2.0%
Other values (133) 720
68.9%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1045
95.8%
Common 46
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 61
 
5.8%
김 61
 
5.8%
박 33
 
3.2%
정 29
 
2.8%
성 27
 
2.6%
수 25
 
2.4%
석 25
 
2.4%
진 22
 
2.1%
호 21
 
2.0%
영 21
 
2.0%
Other values (133) 720
68.9%
Common
ValueCountFrequency (%)
, 24
52.2%
22
47.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1045
95.8%
ASCII 46
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 61
 
5.8%
김 61
 
5.8%
박 33
 
3.2%
정 29
 
2.8%
성 27
 
2.6%
수 25
 
2.4%
석 25
 
2.4%
진 22
 
2.1%
호 21
 
2.0%
영 21
 
2.0%
Other values (133) 720
68.9%
ASCII
ValueCountFrequency (%)
, 24
52.2%
22
47.8%

생산품목
Text

Distinct313
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T01:57:36.509355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length37
Mean length12.363077
Min length2

Characters and Unicode

Total characters4018
Distinct characters450
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique305 ?
Unique (%)93.8%

Sample

1st row추어탕
2nd row산업용로봇,자동화설비
3rd row자외선살균소독기
4th row호떡
5th row낚시장비
ValueCountFrequency (%)
51
 
5.9%
외 28
 
3.2%
및 18
 
2.1%
등 10
 
1.1%
부품 9
 
1.0%
플라스틱 7
 
0.8%
화장품 6
 
0.7%
자동차부품 5
 
0.6%
금형 5
 
0.6%
led 5
 
0.6%
Other values (632) 726
83.4%
2023-12-13T01:57:36.943808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
545
 
13.6%
기 154
 
3.8%
, 126
 
3.1%
스 92
 
2.3%
용 82
 
2.0%
품 57
 
1.4%
/ 57
 
1.4%
전 56
 
1.4%
이 51
 
1.3%
장 50
 
1.2%
Other values (440) 2748
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2935
73.0%
Space Separator 545
 
13.6%
Uppercase Letter 214
 
5.3%
Other Punctuation 191
 
4.8%
Lowercase Letter 52
 
1.3%
Decimal Number 29
 
0.7%
Close Punctuation 25
 
0.6%
Open Punctuation 25
 
0.6%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 154
 
5.2%
스 92
 
3.1%
용 82
 
2.8%
품 57
 
1.9%
전 56
 
1.9%
이 51
 
1.7%
장 50
 
1.7%
자 47
 
1.6%
동 42
 
1.4%
트 40
 
1.4%
Other values (386) 2264
77.1%
Uppercase Letter
ValueCountFrequency (%)
E 25
 
11.7%
D 20
 
9.3%
S 17
 
7.9%
L 15
 
7.0%
C 15
 
7.0%
T 14
 
6.5%
A 12
 
5.6%
P 11
 
5.1%
H 10
 
4.7%
R 9
 
4.2%
Other values (13) 66
30.8%
Lowercase Letter
ValueCountFrequency (%)
e 10
19.2%
l 7
13.5%
a 7
13.5%
t 6
11.5%
i 4
 
7.7%
n 3
 
5.8%
r 3
 
5.8%
o 2
 
3.8%
g 2
 
3.8%
f 2
 
3.8%
Other values (5) 6
11.5%
Decimal Number
ValueCountFrequency (%)
0 12
41.4%
2 6
20.7%
3 4
 
13.8%
1 3
 
10.3%
4 2
 
6.9%
5 1
 
3.4%
7 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 126
66.0%
/ 57
29.8%
& 5
 
2.6%
" 2
 
1.0%
' 1
 
0.5%
Space Separator
ValueCountFrequency (%)
545
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2935
73.0%
Common 817
 
20.3%
Latin 266
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 154
 
5.2%
스 92
 
3.1%
용 82
 
2.8%
품 57
 
1.9%
전 56
 
1.9%
이 51
 
1.7%
장 50
 
1.7%
자 47
 
1.6%
동 42
 
1.4%
트 40
 
1.4%
Other values (386) 2264
77.1%
Latin
ValueCountFrequency (%)
E 25
 
9.4%
D 20
 
7.5%
S 17
 
6.4%
L 15
 
5.6%
C 15
 
5.6%
T 14
 
5.3%
A 12
 
4.5%
P 11
 
4.1%
e 10
 
3.8%
H 10
 
3.8%
Other values (28) 117
44.0%
Common
ValueCountFrequency (%)
545
66.7%
, 126
 
15.4%
/ 57
 
7.0%
) 25
 
3.1%
( 25
 
3.1%
0 12
 
1.5%
2 6
 
0.7%
& 5
 
0.6%
3 4
 
0.5%
1 3
 
0.4%
Other values (6) 9
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2935
73.0%
ASCII 1083
 
27.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
545
50.3%
, 126
 
11.6%
/ 57
 
5.3%
) 25
 
2.3%
( 25
 
2.3%
E 25
 
2.3%
D 20
 
1.8%
S 17
 
1.6%
L 15
 
1.4%
C 15
 
1.4%
Other values (44) 213
 
19.7%
Hangul
ValueCountFrequency (%)
기 154
 
5.2%
스 92
 
3.1%
용 82
 
2.8%
품 57
 
1.9%
전 56
 
1.9%
이 51
 
1.7%
장 50
 
1.7%
자 47
 
1.6%
동 42
 
1.4%
트 40
 
1.4%
Other values (386) 2264
77.1%

전화번호
Text

MISSING 

Distinct182
Distinct (%)91.9%
Missing127
Missing (%)39.1%
Memory size2.7 KiB
2023-12-13T01:57:37.260586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.060606
Min length9

Characters and Unicode

Total characters2388
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

Unique167 ?
Unique (%)84.3%

Sample

1st row032-461-1294
2nd row032-719-7040
3rd row032-504-0304
4th row032-568-9996
5th row032-550-2030
ValueCountFrequency (%)
070-5101-2420 3
 
1.5%
032-822-8877 2
 
1.0%
032-719-7040 2
 
1.0%
032-715-7892 2
 
1.0%
032-812-0114 2
 
1.0%
032-814-0721 2
 
1.0%
032-246-3404 2
 
1.0%
02-1544-3706 2
 
1.0%
032-818-0217 2
 
1.0%
032-873-0051 2
 
1.0%
Other values (172) 177
89.4%
2023-12-13T01:57:37.713111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 395
16.5%
0 355
14.9%
2 320
13.4%
3 272
11.4%
1 201
8.4%
5 198
8.3%
7 166
7.0%
8 166
7.0%
6 128
 
5.4%
4 114
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1993
83.5%
Dash Punctuation 395
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 355
17.8%
2 320
16.1%
3 272
13.6%
1 201
10.1%
5 198
9.9%
7 166
8.3%
8 166
8.3%
6 128
 
6.4%
4 114
 
5.7%
9 73
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 395
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 395
16.5%
0 355
14.9%
2 320
13.4%
3 272
11.4%
1 201
8.4%
5 198
8.3%
7 166
7.0%
8 166
7.0%
6 128
 
5.4%
4 114
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 395
16.5%
0 355
14.9%
2 320
13.4%
3 272
11.4%
1 201
8.4%
5 198
8.3%
7 166
7.0%
8 166
7.0%
6 128
 
5.4%
4 114
 
4.8%

지정기간시작
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2019-11-06
101 
2020-11-24
92 
2020-08-21
40 
2022-09-08
26 
2020-07-01
24 
Other values (3)
42 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row2022-07-05
2nd row2022-07-05
3rd row2022-07-05
4th row2022-07-05
5th row2022-07-05

Common Values

ValueCountFrequency (%)
2019-11-06 101
31.1%
2020-11-24 92
28.3%
2020-08-21 40
 
12.3%
2022-09-08 26
 
8.0%
2020-07-01 24
 
7.4%
2022-07-05 23
 
7.1%
2021-07-23 18
 
5.5%
2021-07-01 1
 
0.3%

Length

2023-12-13T01:57:37.924314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:38.223582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-11-06 101
31.1%
2020-11-24 92
28.3%
2020-08-21 40
 
12.3%
2022-09-08 26
 
8.0%
2020-07-01 24
 
7.4%
2022-07-05 23
 
7.1%
2021-07-23 18
 
5.5%
2021-07-01 1
 
0.3%

지정기간끝
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2025-11-23
64 
2021-11-05
61 
2023-08-20
40 
2024-11-05
40 
2022-11-23
28 
Other values (5)
92 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row2024-07-04
2nd row2024-07-04
3rd row2024-07-04
4th row2024-07-04
5th row2024-07-04

Common Values

ValueCountFrequency (%)
2025-11-23 64
19.7%
2021-11-05 61
18.8%
2023-08-20 40
12.3%
2024-11-05 40
12.3%
2022-11-23 28
8.6%
2025-09-07 26
8.0%
2022-06-30 24
 
7.4%
2024-07-04 23
 
7.1%
2023-07-22 18
 
5.5%
2023-06-30 1
 
0.3%

Length

2023-12-13T01:57:38.457497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:38.615874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2025-11-23 64
19.7%
2021-11-05 61
18.8%
2023-08-20 40
12.3%
2024-11-05 40
12.3%
2022-11-23 28
8.6%
2025-09-07 26
8.0%
2022-06-30 24
 
7.4%
2024-07-04 23
 
7.1%
2023-07-22 18
 
5.5%
2023-06-30 1
 
0.3%

구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
비전기업
92 
유망중소기업
90 
일자리 창출 우수기업
43 
품질우수제품
40 
품질우수제품기업
26 
Other values (2)
34 

Length

Max length11
Median length9
Mean length6.5015385
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
비전기업 92
28.3%
유망중소기업 90
27.7%
일자리 창출 우수기업 43
13.2%
품질우수제품 40
12.3%
품질우수제품기업 26
 
8.0%
일자리창출우수기업 23
 
7.1%
중견사다리기업 11
 
3.4%

Length

2023-12-13T01:57:38.790434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:38.928768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비전기업 92
22.4%
유망중소기업 90
21.9%
일자리 43
10.5%
창출 43
10.5%
우수기업 43
10.5%
품질우수제품 40
9.7%
품질우수제품기업 26
 
6.3%
일자리창출우수기업 23
 
5.6%
중견사다리기업 11
 
2.7%

Interactions

2023-12-13T01:57:34.153183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:57:39.019601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지정기간시작지정기간끝구분
번호1.0000.9090.9640.887
지정기간시작0.9091.0001.0000.926
지정기간끝0.9641.0001.0000.938
구분0.8870.9260.9381.000
2023-12-13T01:57:39.116548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지정기간끝지정기간시작
구분1.0000.8360.813
지정기간끝0.8361.0000.997
지정기간시작0.8130.9971.000
2023-12-13T01:57:39.211844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지정기간시작지정기간끝구분
번호1.0000.7420.6740.719
지정기간시작0.7421.0000.9970.813
지정기간끝0.6740.9971.0000.836
구분0.7190.8130.8361.000

Missing values

2023-12-13T01:57:34.276395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:57:34.424496image/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

번호기업명대표자명생산품목전화번호지정기간시작지정기간끝구분
01(주)미라지식품김준택,기정희추어탕032-461-12942022-07-052024-07-04일자리창출우수기업
12㈜나우로보틱스이종주산업용로봇,자동화설비032-719-70402022-07-052024-07-04일자리창출우수기업
23㈜대신전기산업김진숙자외선살균소독기032-504-03042022-07-052024-07-04일자리창출우수기업
34㈜디앤푸드박성규호떡032-568-99962022-07-052024-07-04일자리창출우수기업
45㈜바낙스장용수낚시장비032-550-20302022-07-052024-07-04일자리창출우수기업
56㈜부영김영호정수기,청정기032-816-15912022-07-052024-07-04일자리창출우수기업
67㈜삼흥정밀김종렬가스스프링,댐퍼032-811-84002022-07-052024-07-04일자리창출우수기업
78㈜성일기공김성묵정밀커플링,서포트유닛032-719-34562022-07-052024-07-04일자리창출우수기업
89㈜제스텍박필석배전반,전기자동제어반032-505-80552022-07-052024-07-04일자리창출우수기업
910㈜진영심영수친환경데코시트032-562-19242022-07-052024-07-04일자리창출우수기업
번호기업명대표자명생산품목전화번호지정기간시작지정기간끝구분
315316(주)메드믹스임수정의료기기<NA>2019-11-062021-11-05유망중소기업
316317(주)오넥트박미설사무용가구<NA>2019-11-062021-11-05유망중소기업
317318(주)피케이엘앤에스박성우전자교탁, 전자칠판<NA>2019-11-062021-11-05유망중소기업
318319(주)세창케미컬김동원화학약품<NA>2019-11-062021-11-05유망중소기업
319320(주)현다이엔지김성훈자동제어 / 조명기구<NA>2019-11-062021-11-05유망중소기업
320321동인중공업(주)최성진유압브레이커 / 어태치먼트<NA>2019-11-062024-11-05중견사다리기업
321322(주)미트뱅크김영준소시지 / 양념육<NA>2019-11-062024-11-05중견사다리기업
322323(주)바낙스장용수낚시장비<NA>2019-11-062024-11-05중견사다리기업
323324(주)예림임업전용진목재문<NA>2019-11-062021-11-05중견사다리기업
324325신진화학(주)문창호자동차플라스틱부품<NA>2019-11-062021-11-05중견사다리기업