Overview

Dataset statistics

Number of variables9
Number of observations75
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory75.8 B

Variable types

Numeric2
Categorical2
Text4
DateTime1

Dataset

Description금산군 농공단지 내 입주업체현황(기업명, 주소, 전화번호, 공장등록일시 등)에 대한 내역입니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=396&beforeMenuCd=DOM_000000201001001000&publicdatapk=15028982

Alerts

데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 산업단지명High correlation
종업원수 is highly overall correlated with 산업단지명High correlation
산업단지명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
종업원수 has 1 (1.3%) missing valuesMissing
순번 has unique valuesUnique
회사명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:25:39.883268
Analysis finished2024-01-09 21:25:40.913606
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38
Minimum1
Maximum75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-01-10T06:25:40.968297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.7
Q119.5
median38
Q356.5
95-th percentile71.3
Maximum75
Range74
Interquartile range (IQR)37

Descriptive statistics

Standard deviation21.794495
Coefficient of variation (CV)0.57353933
Kurtosis-1.2
Mean38
Median Absolute Deviation (MAD)19
Skewness0
Sum2850
Variance475
MonotonicityStrictly increasing
2024-01-10T06:25:41.072469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
49 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
50 1
 
1.3%
48 1
 
1.3%
Other values (65) 65
86.7%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%
67 1
1.3%
66 1
1.3%

산업단지명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
추부농공단지
32 
금성농공단지
22 
복수농공단지
14 
인삼약초특화농공단지
금산일반산업단지
 
1

Length

Max length10
Median length6
Mean length6.3466667
Min length6

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row금산일반산업단지
2nd row금성농공단지
3rd row금성농공단지
4th row금성농공단지
5th row금성농공단지

Common Values

ValueCountFrequency (%)
추부농공단지 32
42.7%
금성농공단지 22
29.3%
복수농공단지 14
18.7%
인삼약초특화농공단지 6
 
8.0%
금산일반산업단지 1
 
1.3%

Length

2024-01-10T06:25:41.182207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:25:41.274341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
추부농공단지 32
42.7%
금성농공단지 22
29.3%
복수농공단지 14
18.7%
인삼약초특화농공단지 6
 
8.0%
금산일반산업단지 1
 
1.3%

회사명
Text

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-01-10T06:25:41.469221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.1466667
Min length3

Characters and Unicode

Total characters461
Distinct characters153
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

Unique75 ?
Unique (%)100.0%

Sample

1st row한국타이어㈜ 금산공장
2nd row태형산업㈜
3rd row한국생약영농조합법인
4th row㈜한영계기
5th row㈜부광케미컬
ValueCountFrequency (%)
농업회사법인 2
 
2.4%
한국타이어㈜ 1
 
1.2%
주)b 1
 
1.2%
주)이엑스쏠라 1
 
1.2%
주)미래기전 1
 
1.2%
주)더드림솔루션 1
 
1.2%
주)에스코알티에스 1
 
1.2%
진테크 1
 
1.2%
c 1
 
1.2%
d 1
 
1.2%
Other values (71) 71
86.6%
2024-01-10T06:25:41.773338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
8.0%
23
 
5.0%
21
 
4.6%
) 19
 
4.1%
18
 
3.9%
11
 
2.4%
11
 
2.4%
9
 
2.0%
9
 
2.0%
8
 
1.7%
Other values (143) 295
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 382
82.9%
Other Symbol 37
 
8.0%
Close Punctuation 19
 
4.1%
Uppercase Letter 9
 
2.0%
Space Separator 7
 
1.5%
Open Punctuation 6
 
1.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
23
 
6.0%
21
 
5.5%
18
 
4.7%
11
 
2.9%
11
 
2.9%
9
 
2.4%
9
 
2.4%
8
 
2.1%
8
 
2.1%
7
 
1.8%
Other values (130) 257
67.3%
Uppercase Letter
ValueCountFrequency (%)
D 2
22.2%
J 1
11.1%
S 1
11.1%
C 1
11.1%
B 1
11.1%
P 1
11.1%
E 1
11.1%
I 1
11.1%
Other Symbol
ValueCountFrequency (%)
37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 419
90.9%
Common 33
 
7.2%
Latin 9
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
37
 
8.8%
23
 
5.5%
21
 
5.0%
18
 
4.3%
11
 
2.6%
11
 
2.6%
9
 
2.1%
9
 
2.1%
8
 
1.9%
8
 
1.9%
Other values (131) 264
63.0%
Latin
ValueCountFrequency (%)
D 2
22.2%
J 1
11.1%
S 1
11.1%
C 1
11.1%
B 1
11.1%
P 1
11.1%
E 1
11.1%
I 1
11.1%
Common
ValueCountFrequency (%)
) 19
57.6%
7
 
21.2%
( 6
 
18.2%
& 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 382
82.9%
ASCII 42
 
9.1%
None 37
 
8.0%

Most frequent character per block

None
ValueCountFrequency (%)
37
100.0%
Hangul
ValueCountFrequency (%)
23
 
6.0%
21
 
5.5%
18
 
4.7%
11
 
2.9%
11
 
2.9%
9
 
2.4%
9
 
2.4%
8
 
2.1%
8
 
2.1%
7
 
1.8%
Other values (130) 257
67.3%
ASCII
ValueCountFrequency (%)
) 19
45.2%
7
 
16.7%
( 6
 
14.3%
D 2
 
4.8%
J 1
 
2.4%
S 1
 
2.4%
C 1
 
2.4%
B 1
 
2.4%
P 1
 
2.4%
E 1
 
2.4%
Other values (2) 2
 
4.8%
Distinct71
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
Minimum1988-08-15 00:00:00
Maximum2022-08-22 00:00:00
2024-01-10T06:25:41.886346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:25:42.003756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct74
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-01-10T06:25:42.482463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.973333
Min length9

Characters and Unicode

Total characters898
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

Unique73 ?
Unique (%)97.3%

Sample

1st row041-750-5101
2nd row041-754-6672
3rd row041-751-4400
4th row041-751-1051
5th row041-751-3205
ValueCountFrequency (%)
041-752-1029 2
 
2.7%
070-4038-7187 1
 
1.3%
041-752-0399 1
 
1.3%
041-751-4803 1
 
1.3%
041-754-0501 1
 
1.3%
041-751-6262 1
 
1.3%
041-752-1022 1
 
1.3%
041-751-1470 1
 
1.3%
041-751-9599 1
 
1.3%
041-754-7041 1
 
1.3%
Other values (64) 64
85.3%
2024-01-10T06:25:42.794518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 148
16.5%
0 140
15.6%
1 130
14.5%
4 114
12.7%
7 106
11.8%
5 101
11.2%
2 49
 
5.5%
3 35
 
3.9%
9 29
 
3.2%
8 26
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 750
83.5%
Dash Punctuation 148
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 140
18.7%
1 130
17.3%
4 114
15.2%
7 106
14.1%
5 101
13.5%
2 49
 
6.5%
3 35
 
4.7%
9 29
 
3.9%
8 26
 
3.5%
6 20
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 148
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 898
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 148
16.5%
0 140
15.6%
1 130
14.5%
4 114
12.7%
7 106
11.8%
5 101
11.2%
2 49
 
5.5%
3 35
 
3.9%
9 29
 
3.2%
8 26
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 898
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 148
16.5%
0 140
15.6%
1 130
14.5%
4 114
12.7%
7 106
11.8%
5 101
11.2%
2 49
 
5.5%
3 35
 
3.9%
9 29
 
3.2%
8 26
 
2.9%

종업원수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38
Distinct (%)51.4%
Missing1
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean58.391892
Minimum1
Maximum2978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-01-10T06:25:42.905456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q324.75
95-th percentile47.05
Maximum2978
Range2977
Interquartile range (IQR)16.75

Descriptive statistics

Standard deviation344.41234
Coefficient of variation (CV)5.8982904
Kurtosis73.673242
Mean58.391892
Median Absolute Deviation (MAD)8.5
Skewness8.5744516
Sum4321
Variance118619.86
MonotonicityNot monotonic
2024-01-10T06:25:43.009195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
13 5
 
6.7%
2 4
 
5.3%
3 4
 
5.3%
24 4
 
5.3%
7 3
 
4.0%
9 3
 
4.0%
10 3
 
4.0%
25 3
 
4.0%
18 3
 
4.0%
35 2
 
2.7%
Other values (28) 40
53.3%
ValueCountFrequency (%)
1 2
2.7%
2 4
5.3%
3 4
5.3%
4 2
2.7%
5 1
 
1.3%
6 2
2.7%
7 3
4.0%
8 2
2.7%
9 3
4.0%
10 3
4.0%
ValueCountFrequency (%)
2978 1
1.3%
102 1
1.3%
66 1
1.3%
49 1
1.3%
46 1
1.3%
39 1
1.3%
36 1
1.3%
35 2
2.7%
34 1
1.3%
30 2
2.7%
Distinct71
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-01-10T06:25:43.195086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.866667
Min length18

Characters and Unicode

Total characters1640
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)92.0%

Sample

1st row충청남도 금산군 제원면 금강로 1
2nd row충청남도 금산군 금성면 금성공단로 68
3rd row충청남도 금산군 금성면 금성공단로 5-8
4th row충청남도 금산군 금성면 금성공단로 49
5th row충청남도 금산군 금성면 금성공단로 66
ValueCountFrequency (%)
금산군 75
20.0%
충청남도 74
19.7%
추부면 32
 
8.5%
신평공단1로 32
 
8.5%
금성면 22
 
5.9%
금성공단로 22
 
5.9%
복수면 14
 
3.7%
복수공단길 14
 
3.7%
부리면 6
 
1.6%
13 4
 
1.1%
Other values (67) 80
21.3%
2024-01-10T06:25:43.486692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
301
18.4%
120
 
7.3%
75
 
4.6%
75
 
4.6%
75
 
4.6%
75
 
4.6%
75
 
4.6%
74
 
4.5%
74
 
4.5%
74
 
4.5%
Other values (29) 622
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1133
69.1%
Space Separator 301
 
18.4%
Decimal Number 200
 
12.2%
Dash Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
120
 
10.6%
75
 
6.6%
75
 
6.6%
75
 
6.6%
75
 
6.6%
75
 
6.6%
74
 
6.5%
74
 
6.5%
74
 
6.5%
74
 
6.5%
Other values (17) 342
30.2%
Decimal Number
ValueCountFrequency (%)
1 72
36.0%
2 22
 
11.0%
4 20
 
10.0%
6 18
 
9.0%
0 17
 
8.5%
5 14
 
7.0%
9 12
 
6.0%
3 12
 
6.0%
7 8
 
4.0%
8 5
 
2.5%
Space Separator
ValueCountFrequency (%)
301
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1133
69.1%
Common 507
30.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
120
 
10.6%
75
 
6.6%
75
 
6.6%
75
 
6.6%
75
 
6.6%
75
 
6.6%
74
 
6.5%
74
 
6.5%
74
 
6.5%
74
 
6.5%
Other values (17) 342
30.2%
Common
ValueCountFrequency (%)
301
59.4%
1 72
 
14.2%
2 22
 
4.3%
4 20
 
3.9%
6 18
 
3.6%
0 17
 
3.4%
5 14
 
2.8%
9 12
 
2.4%
3 12
 
2.4%
7 8
 
1.6%
Other values (2) 11
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1133
69.1%
ASCII 507
30.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
301
59.4%
1 72
 
14.2%
2 22
 
4.3%
4 20
 
3.9%
6 18
 
3.6%
0 17
 
3.4%
5 14
 
2.8%
9 12
 
2.4%
3 12
 
2.4%
7 8
 
1.6%
Other values (2) 11
 
2.2%
Hangul
ValueCountFrequency (%)
120
 
10.6%
75
 
6.6%
75
 
6.6%
75
 
6.6%
75
 
6.6%
75
 
6.6%
74
 
6.5%
74
 
6.5%
74
 
6.5%
74
 
6.5%
Other values (17) 342
30.2%
Distinct71
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-01-10T06:25:43.699411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length11
Mean length6.6
Min length2

Characters and Unicode

Total characters495
Distinct characters170
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

Unique68 ?
Unique (%)90.7%

Sample

1st row타이어
2nd row전기절연커버
3rd row홍삼액
4th row수도계량기, 보호통
5th row플라스틱 성형용기
ValueCountFrequency (%)
건강기능식품 3
 
2.7%
3
 
2.7%
폴리올 2
 
1.8%
보행형관리기 2
 
1.8%
2
 
1.8%
방송장비 2
 
1.8%
부직포 2
 
1.8%
홍삼액 2
 
1.8%
젤리류 2
 
1.8%
농기계 2
 
1.8%
Other values (90) 91
80.5%
2024-01-10T06:25:44.031961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
7.7%
25
 
5.1%
, 19
 
3.8%
16
 
3.2%
12
 
2.4%
11
 
2.2%
10
 
2.0%
9
 
1.8%
9
 
1.8%
9
 
1.8%
Other values (160) 337
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 430
86.9%
Space Separator 38
 
7.7%
Other Punctuation 19
 
3.8%
Uppercase Letter 6
 
1.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
5.8%
16
 
3.7%
12
 
2.8%
11
 
2.6%
10
 
2.3%
9
 
2.1%
9
 
2.1%
9
 
2.1%
8
 
1.9%
7
 
1.6%
Other values (151) 314
73.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
V 1
16.7%
T 1
16.7%
E 1
16.7%
P 1
16.7%
Space Separator
ValueCountFrequency (%)
38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 430
86.9%
Common 59
 
11.9%
Latin 6
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
25
 
5.8%
16
 
3.7%
12
 
2.8%
11
 
2.6%
10
 
2.3%
9
 
2.1%
9
 
2.1%
9
 
2.1%
8
 
1.9%
7
 
1.6%
Other values (151) 314
73.0%
Latin
ValueCountFrequency (%)
C 2
33.3%
V 1
16.7%
T 1
16.7%
E 1
16.7%
P 1
16.7%
Common
ValueCountFrequency (%)
38
64.4%
, 19
32.2%
) 1
 
1.7%
( 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 430
86.9%
ASCII 65
 
13.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
58.5%
, 19
29.2%
C 2
 
3.1%
V 1
 
1.5%
T 1
 
1.5%
) 1
 
1.5%
( 1
 
1.5%
E 1
 
1.5%
P 1
 
1.5%
Hangul
ValueCountFrequency (%)
25
 
5.8%
16
 
3.7%
12
 
2.8%
11
 
2.6%
10
 
2.3%
9
 
2.1%
9
 
2.1%
9
 
2.1%
8
 
1.9%
7
 
1.6%
Other values (151) 314
73.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
2022-09-01
75 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-01
2nd row2022-09-01
3rd row2022-09-01
4th row2022-09-01
5th row2022-09-01

Common Values

ValueCountFrequency (%)
2022-09-01 75
100.0%

Length

2024-01-10T06:25:44.145357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:25:44.226620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-01 75
100.0%

Interactions

2024-01-10T06:25:40.611031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:25:40.476349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:25:40.682741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:25:40.542965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:25:44.278214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번산업단지명회사명설립일자전화번호종업원수공장대표주소생산품
순번1.0000.9791.0000.7400.9370.0000.9350.877
산업단지명0.9791.0001.0000.8251.0001.0001.0000.611
회사명1.0001.0001.0001.0001.0001.0001.0001.000
설립일자0.7400.8251.0001.0001.0001.0000.9850.988
전화번호0.9371.0001.0001.0001.0001.0000.9940.994
종업원수0.0001.0001.0001.0001.0001.0001.0001.000
공장대표주소0.9351.0001.0000.9850.9941.0001.0000.989
생산품0.8770.6111.0000.9880.9941.0000.9891.000
2024-01-10T06:25:44.365170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종업원수산업단지명
순번1.0000.0560.765
종업원수0.0561.0000.979
산업단지명0.7650.9791.000

Missing values

2024-01-10T06:25:40.771285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:25:40.870862image/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

순번산업단지명회사명설립일자전화번호종업원수공장대표주소생산품데이터기준일자
01금산일반산업단지한국타이어㈜ 금산공장1995-02-16041-750-51012978충청남도 금산군 제원면 금강로 1타이어2022-09-01
12금성농공단지태형산업㈜1997-11-26041-754-667213충청남도 금산군 금성면 금성공단로 68전기절연커버2022-09-01
23금성농공단지한국생약영농조합법인2003-07-29041-751-44007충청남도 금산군 금성면 금성공단로 5-8홍삼액2022-09-01
34금성농공단지㈜한영계기1989-07-01041-751-10519충청남도 금산군 금성면 금성공단로 49수도계량기, 보호통2022-09-01
45금성농공단지㈜부광케미컬1996-05-01041-751-320523충청남도 금산군 금성면 금성공단로 66플라스틱 성형용기2022-09-01
56금성농공단지㈜한국농기계2022-01-02041-751-040110충청남도 금산군 금성면 금성공단로 5-10보행형관리기, 농기계2022-09-01
67금성농공단지구안산업㈜1997-03-18041-754-62579충청남도 금산군 금성면 금성공단로 23인삼차, 홍삼액2022-09-01
78금성농공단지㈜그린퓨어제지1997-05-201544-09598충청남도 금산군 금성면 금성공단로 90위생용 종이제품2022-09-01
89금성농공단지㈜이에스에프씨티1994-06-01041-754-789125충청남도 금산군 금성면 금성공단로 31표면처리재2022-09-01
910금성농공단지안성공업㈜1993-03-23041-752-96077충청남도 금산군 금성면 금성공단로 52플러그핀2022-09-01
순번산업단지명회사명설립일자전화번호종업원수공장대표주소생산품데이터기준일자
6566추부농공단지주)한일에스피2011-10-17041-754-072026충청남도 금산군 추부면 신평공단1로 21분무기, 노즐2022-09-01
6667추부농공단지주)세양2014-10-06041-754-835518충청남도 금산군 추부면 신평공단1로 20계란선별기2022-09-01
6768추부농공단지에스디(주2015-01-06041-752-68643충청남도 금산군 추부면 신평공단1로 109자동차부품 금속단자2022-09-01
6869추부농공단지지오엔에너지2019-01-28042-628-067516충청남도 금산군 추부면 신평공단1로 67전동기 및 발전기2022-09-01
6970인삼약초특화농공단지㈜명품코리아2015-05-20041-754-082117충청남도 금산군 부리면 인삼약초공단1로 27CCTV, 방송장비2022-09-01
7071인삼약초특화농공단지농업회사법인 금산흑삼㈜2015-08-25041-754-089329충청남도 금산군 부리면 인삼약초공단로 15흑삼2022-09-01
7172인삼약초특화농공단지농업회사법인 ㈜주안푸드2017-10-19041-752-175013충청남도 금산군 부리면 인삼약초공단1길 17도시락2022-09-01
7273인삼약초특화농공단지경방신약㈜2019-09-16041-751-565066충청남도 금산군 부리면 인삼약초공단로 27건강기능식품2022-09-01
7374인삼약초특화농공단지㈜다우에프에스2015-12-01041-751-061035충청남도 금산군 부리면 인삼약초공단로 6제과, 제빵 및 젤리류2022-09-01
7475인삼약초특화농공단지㈜다우엠에스2017-04-17041-751-552723충청남도 금산군 부리면 인삼약초공단로 16젤리류2022-09-01