Overview

Dataset statistics

Number of variables8
Number of observations52
Missing cells5
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory67.5 B

Variable types

Categorical1
Text5
DateTime1
Numeric1

Dataset

Description충청남도 청양군에 소재하고 있는 산업단지 입주기업에 대한 기업명, 단지명, 업종, 전화번호, 설립일자, 종업원수, 생산품 현황입니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=430&beforeMenuCd=DOM_000000201001001000&publicdatapk=15029933

Alerts

종업원수 has 1 (1.9%) missing valuesMissing
전화번호 has 4 (7.7%) missing valuesMissing
기업명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:42:30.431289
Analysis finished2024-01-09 21:42:31.245090
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

산업단지명
Categorical

Distinct6
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
청양화성농공단지
16 
청양운곡농공단지
11 
청양비봉농공단지
10 
청양운곡2농공단지
9 
청양학당농공단지
3 

Length

Max length10
Median length8
Mean length8.2884615
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row청양학당농공단지
2nd row청양학당농공단지
3rd row청양학당농공단지
4th row청양운곡농공단지
5th row청양운곡농공단지

Common Values

ValueCountFrequency (%)
청양화성농공단지 16
30.8%
청양운곡농공단지 11
21.2%
청양비봉농공단지 10
19.2%
청양운곡2농공단지 9
17.3%
청양학당농공단지 3
 
5.8%
청양정산특별농공단지 3
 
5.8%

Length

2024-01-10T06:42:31.301690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:42:31.387457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청양화성농공단지 16
30.8%
청양운곡농공단지 11
21.2%
청양비봉농공단지 10
19.2%
청양운곡2농공단지 9
17.3%
청양학당농공단지 3
 
5.8%
청양정산특별농공단지 3
 
5.8%

기업명
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-01-10T06:42:31.576379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.4230769
Min length3

Characters and Unicode

Total characters334
Distinct characters127
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row에스엠인더스트리㈜
2nd row락희스틸㈜
3rd row(주)남영산업 제2공장
4th row농업회사법인 ㈜동일
5th row비전무역
ValueCountFrequency (%)
애경케미칼㈜ 2
 
3.3%
주)남영산업 2
 
3.3%
㈜우양 2
 
3.3%
성광산업㈜ 1
 
1.7%
고려특장㈜ 1
 
1.7%
다이어트캠프 1
 
1.7%
선광엘티아이㈜ 1
 
1.7%
㈜하은산업 1
 
1.7%
㈜하은산업2 1
 
1.7%
디에스그린에너지㈜ 1
 
1.7%
Other values (47) 47
78.3%
2024-01-10T06:42:31.877373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 41
 
12.3%
업 14
 
4.2%
산 12
 
3.6%
이 8
 
2.4%
8
 
2.4%
양 8
 
2.4%
에 7
 
2.1%
장 6
 
1.8%
스 6
 
1.8%
청 6
 
1.8%
Other values (117) 218
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 270
80.8%
Other Symbol 41
 
12.3%
Space Separator 8
 
2.4%
Open Punctuation 5
 
1.5%
Close Punctuation 5
 
1.5%
Decimal Number 5
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 14
 
5.2%
산 12
 
4.4%
이 8
 
3.0%
양 8
 
3.0%
에 7
 
2.6%
장 6
 
2.2%
스 6
 
2.2%
청 6
 
2.2%
공 6
 
2.2%
너 5
 
1.9%
Other values (111) 192
71.1%
Decimal Number
ValueCountFrequency (%)
2 4
80.0%
1 1
 
20.0%
Other Symbol
ValueCountFrequency (%)
㈜ 41
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 311
93.1%
Common 23
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 41
 
13.2%
업 14
 
4.5%
산 12
 
3.9%
이 8
 
2.6%
양 8
 
2.6%
에 7
 
2.3%
장 6
 
1.9%
스 6
 
1.9%
청 6
 
1.9%
공 6
 
1.9%
Other values (112) 197
63.3%
Common
ValueCountFrequency (%)
8
34.8%
( 5
21.7%
) 5
21.7%
2 4
17.4%
1 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 270
80.8%
None 41
 
12.3%
ASCII 23
 
6.9%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 41
100.0%
Hangul
ValueCountFrequency (%)
업 14
 
5.2%
산 12
 
4.4%
이 8
 
3.0%
양 8
 
3.0%
에 7
 
2.6%
장 6
 
2.2%
스 6
 
2.2%
청 6
 
2.2%
공 6
 
2.2%
너 5
 
1.9%
Other values (111) 192
71.1%
ASCII
ValueCountFrequency (%)
8
34.8%
( 5
21.7%
) 5
21.7%
2 4
17.4%
1 1
 
4.3%

도로명주소
Text

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-01-10T06:42:32.059084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length13.711538
Min length10

Characters and Unicode

Total characters713
Distinct characters42
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

Unique50 ?
Unique (%)96.2%

Sample

1st row청양읍 충절로 1259-130
2nd row청양읍 충절로 1259-92
3rd row청양읍 충절로 1259-132
4th row운곡면 청신로 567-103
5th row운곡면 청신로 567-31
ValueCountFrequency (%)
운곡면 20
 
12.8%
화성면 16
 
10.3%
금계동길 12
 
7.7%
비봉면 10
 
6.4%
작은한술길 10
 
6.4%
신대길 9
 
5.8%
청신로 9
 
5.8%
청양읍 3
 
1.9%
충의로 3
 
1.9%
정산면 3
 
1.9%
Other values (53) 61
39.1%
2024-01-10T06:42:32.333899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
 
15.1%
면 49
 
6.9%
- 44
 
6.2%
1 36
 
5.0%
4 32
 
4.5%
2 31
 
4.3%
길 31
 
4.3%
3 23
 
3.2%
5 22
 
3.1%
운 22
 
3.1%
Other values (32) 315
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 348
48.8%
Decimal Number 213
29.9%
Space Separator 108
 
15.1%
Dash Punctuation 44
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 49
 
14.1%
길 31
 
8.9%
운 22
 
6.3%
곡 22
 
6.3%
로 18
 
5.2%
신 18
 
5.2%
성 16
 
4.6%
화 16
 
4.6%
계 15
 
4.3%
청 13
 
3.7%
Other values (20) 128
36.8%
Decimal Number
ValueCountFrequency (%)
1 36
16.9%
4 32
15.0%
2 31
14.6%
3 23
10.8%
5 22
10.3%
7 17
8.0%
6 17
8.0%
8 15
7.0%
0 10
 
4.7%
9 10
 
4.7%
Space Separator
ValueCountFrequency (%)
108
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 365
51.2%
Hangul 348
48.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 49
 
14.1%
길 31
 
8.9%
운 22
 
6.3%
곡 22
 
6.3%
로 18
 
5.2%
신 18
 
5.2%
성 16
 
4.6%
화 16
 
4.6%
계 15
 
4.3%
청 13
 
3.7%
Other values (20) 128
36.8%
Common
ValueCountFrequency (%)
108
29.6%
- 44
12.1%
1 36
 
9.9%
4 32
 
8.8%
2 31
 
8.5%
3 23
 
6.3%
5 22
 
6.0%
7 17
 
4.7%
6 17
 
4.7%
8 15
 
4.1%
Other values (2) 20
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 365
51.2%
Hangul 348
48.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
108
29.6%
- 44
12.1%
1 36
 
9.9%
4 32
 
8.8%
2 31
 
8.5%
3 23
 
6.3%
5 22
 
6.0%
7 17
 
4.7%
6 17
 
4.7%
8 15
 
4.1%
Other values (2) 20
 
5.5%
Hangul
ValueCountFrequency (%)
면 49
 
14.1%
길 31
 
8.9%
운 22
 
6.3%
곡 22
 
6.3%
로 18
 
5.2%
신 18
 
5.2%
성 16
 
4.6%
화 16
 
4.6%
계 15
 
4.3%
청 13
 
3.7%
Other values (20) 128
36.8%

설립일자
Date

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
Minimum1989-02-28 00:00:00
Maximum2021-09-07 00:00:00
2024-01-10T06:42:32.442021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:42:32.548697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종업원수
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)58.8%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean29.27451
Minimum1
Maximum314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-10T06:42:32.641189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median12
Q321.5
95-th percentile122.5
Maximum314
Range313
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation53.078462
Coefficient of variation (CV)1.813129
Kurtosis16.69556
Mean29.27451
Median Absolute Deviation (MAD)7
Skewness3.7315659
Sum1493
Variance2817.3231
MonotonicityNot monotonic
2024-01-10T06:42:32.731401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
8 5
 
9.6%
1 5
 
9.6%
18 3
 
5.8%
13 3
 
5.8%
4 3
 
5.8%
7 2
 
3.8%
6 2
 
3.8%
3 2
 
3.8%
9 2
 
3.8%
19 2
 
3.8%
Other values (20) 22
42.3%
ValueCountFrequency (%)
1 5
9.6%
2 1
 
1.9%
3 2
 
3.8%
4 3
5.8%
5 1
 
1.9%
6 2
 
3.8%
7 2
 
3.8%
8 5
9.6%
9 2
 
3.8%
11 1
 
1.9%
ValueCountFrequency (%)
314 1
1.9%
149 1
1.9%
128 1
1.9%
117 1
1.9%
114 1
1.9%
71 1
1.9%
69 1
1.9%
55 1
1.9%
29 2
3.8%
25 1
1.9%

전화번호
Text

MISSING 

Distinct43
Distinct (%)89.6%
Missing4
Missing (%)7.7%
Memory size548.0 B
2024-01-10T06:42:32.905823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.979167
Min length11

Characters and Unicode

Total characters575
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

Unique39 ?
Unique (%)81.2%

Sample

1st row041-940-5700
2nd row041-943-8560
3rd row041-944-0089
4th row02-967-1777
5th row041-942-1475
ValueCountFrequency (%)
041-942-8523 3
 
6.2%
041-944-0089 2
 
4.2%
041-942-2911 2
 
4.2%
041-940-6300 2
 
4.2%
041-942-7124 1
 
2.1%
041-943-4488 1
 
2.1%
041-942-3253 1
 
2.1%
041-943-4533 1
 
2.1%
041-943-7948 1
 
2.1%
041-944-2268 1
 
2.1%
Other values (33) 33
68.8%
2024-01-10T06:42:33.197848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 106
18.4%
- 96
16.7%
0 83
14.4%
1 64
11.1%
9 64
11.1%
2 39
 
6.8%
3 39
 
6.8%
8 26
 
4.5%
7 26
 
4.5%
6 18
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 479
83.3%
Dash Punctuation 96
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 106
22.1%
0 83
17.3%
1 64
13.4%
9 64
13.4%
2 39
 
8.1%
3 39
 
8.1%
8 26
 
5.4%
7 26
 
5.4%
6 18
 
3.8%
5 14
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 575
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 106
18.4%
- 96
16.7%
0 83
14.4%
1 64
11.1%
9 64
11.1%
2 39
 
6.8%
3 39
 
6.8%
8 26
 
4.5%
7 26
 
4.5%
6 18
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 575
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 106
18.4%
- 96
16.7%
0 83
14.4%
1 64
11.1%
9 64
11.1%
2 39
 
6.8%
3 39
 
6.8%
8 26
 
4.5%
7 26
 
4.5%
6 18
 
3.1%

업종
Text

Distinct36
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-01-10T06:42:33.398339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length126
Median length20
Mean length18.192308
Min length6

Characters and Unicode

Total characters946
Distinct characters105
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

Unique28 ?
Unique (%)53.8%

Sample

1st row합성수지 및 기타 플라스틱 물질 제조업
2nd row육상금속골조 구조재제조업
3rd row금속선 가공제품 제조업
4th row기타 과실,채소 가공 및저장 처리업
5th row기타 과실,채소 가공 및저장 처리업
ValueCountFrequency (%)
제조업 35
 
15.8%
및 28
 
12.7%
기타 20
 
9.0%
콘크리트 7
 
3.2%
제품 7
 
3.2%
가공 6
 
2.7%
구조용 6
 
2.7%
및저장 5
 
2.3%
콘크리트관 5
 
2.3%
과실,채소 5
 
2.3%
Other values (70) 97
43.9%
2024-01-10T06:42:33.699647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
282
29.8%
제 63
 
6.7%
업 58
 
6.1%
조 56
 
5.9%
및 33
 
3.5%
기 31
 
3.3%
품 22
 
2.3%
리 20
 
2.1%
타 20
 
2.1%
용 15
 
1.6%
Other values (95) 346
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 653
69.0%
Space Separator 282
29.8%
Other Punctuation 11
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 63
 
9.6%
업 58
 
8.9%
조 56
 
8.6%
및 33
 
5.1%
기 31
 
4.7%
품 22
 
3.4%
리 20
 
3.1%
타 20
 
3.1%
용 15
 
2.3%
트 13
 
2.0%
Other values (93) 322
49.3%
Space Separator
ValueCountFrequency (%)
282
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 653
69.0%
Common 293
31.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 63
 
9.6%
업 58
 
8.9%
조 56
 
8.6%
및 33
 
5.1%
기 31
 
4.7%
품 22
 
3.4%
리 20
 
3.1%
타 20
 
3.1%
용 15
 
2.3%
트 13
 
2.0%
Other values (93) 322
49.3%
Common
ValueCountFrequency (%)
282
96.2%
, 11
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 653
69.0%
ASCII 293
31.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
282
96.2%
, 11
 
3.8%
Hangul
ValueCountFrequency (%)
제 63
 
9.6%
업 58
 
8.9%
조 56
 
8.6%
및 33
 
5.1%
기 31
 
4.7%
품 22
 
3.4%
리 20
 
3.1%
타 20
 
3.1%
용 15
 
2.3%
트 13
 
2.0%
Other values (93) 322
49.3%

생산품
Text

Distinct42
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-01-10T06:42:33.875036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length4.8846154
Min length2

Characters and Unicode

Total characters254
Distinct characters110
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

Unique35 ?
Unique (%)67.3%

Sample

1st row플라스틱컴파운드, 자동차부품
2nd row철근가공
3rd row용접철망
4th row마늘, 생강, 양파
5th row고춧가루
ValueCountFrequency (%)
콘크리트관 4
 
6.6%
펠렛 3
 
4.9%
관 2
 
3.3%
플라스틱관 2
 
3.3%
등 2
 
3.3%
냉동식품 2
 
3.3%
콘크리트 2
 
3.3%
용접철망 2
 
3.3%
유제품 2
 
3.3%
특장차 1
 
1.6%
Other values (39) 39
63.9%
2024-01-10T06:42:34.156831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
3.5%
관 8
 
3.1%
품 8
 
3.1%
크 8
 
3.1%
기 7
 
2.8%
제 7
 
2.8%
콘 6
 
2.4%
리 6
 
2.4%
트 6
 
2.4%
용 6
 
2.4%
Other values (100) 183
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
93.7%
Space Separator 9
 
3.5%
Other Punctuation 5
 
2.0%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 8
 
3.4%
품 8
 
3.4%
크 8
 
3.4%
기 7
 
2.9%
제 7
 
2.9%
콘 6
 
2.5%
리 6
 
2.5%
트 6
 
2.5%
용 6
 
2.5%
동 5
 
2.1%
Other values (96) 171
71.8%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 238
93.7%
Common 16
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 8
 
3.4%
품 8
 
3.4%
크 8
 
3.4%
기 7
 
2.9%
제 7
 
2.9%
콘 6
 
2.5%
리 6
 
2.5%
트 6
 
2.5%
용 6
 
2.5%
동 5
 
2.1%
Other values (96) 171
71.8%
Common
ValueCountFrequency (%)
9
56.2%
, 5
31.2%
( 1
 
6.2%
) 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 238
93.7%
ASCII 16
 
6.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
56.2%
, 5
31.2%
( 1
 
6.2%
) 1
 
6.2%
Hangul
ValueCountFrequency (%)
관 8
 
3.4%
품 8
 
3.4%
크 8
 
3.4%
기 7
 
2.9%
제 7
 
2.9%
콘 6
 
2.5%
리 6
 
2.5%
트 6
 
2.5%
용 6
 
2.5%
동 5
 
2.1%
Other values (96) 171
71.8%

Interactions

2024-01-10T06:42:30.952992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:42:34.234452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산업단지명기업명도로명주소설립일자종업원수전화번호업종생산품
산업단지명1.0001.0001.0000.9530.7270.9620.9070.946
기업명1.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0000.9971.0001.0001.0001.000
설립일자0.9531.0000.9971.0001.0000.9940.9980.990
종업원수0.7271.0001.0001.0001.0000.0000.0000.814
전화번호0.9621.0001.0000.9940.0001.0000.9950.992
업종0.9071.0001.0000.9980.0000.9951.0000.997
생산품0.9461.0001.0000.9900.8140.9920.9971.000
2024-01-10T06:42:34.318062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원수산업단지명
종업원수1.0000.337
산업단지명0.3371.000

Missing values

2024-01-10T06:42:31.046086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:42:31.139395image/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.
2024-01-10T06:42:31.210852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

산업단지명기업명도로명주소설립일자종업원수전화번호업종생산품
0청양학당농공단지에스엠인더스트리㈜청양읍 충절로 1259-1302008-07-04117041-940-5700합성수지 및 기타 플라스틱 물질 제조업플라스틱컴파운드, 자동차부품
1청양학당농공단지락희스틸㈜청양읍 충절로 1259-922008-04-3013041-943-8560육상금속골조 구조재제조업철근가공
2청양학당농공단지(주)남영산업 제2공장청양읍 충절로 1259-1322020-08-0612041-944-0089금속선 가공제품 제조업용접철망
3청양운곡농공단지농업회사법인 ㈜동일운곡면 청신로 567-1032020-11-04802-967-1777기타 과실,채소 가공 및저장 처리업마늘, 생강, 양파
4청양운곡농공단지비전무역운곡면 청신로 567-312017-09-198041-942-1475기타 과실,채소 가공 및저장 처리업고춧가루
5청양운곡농공단지(주)남영산업운곡면 청신로 567-502007-09-1219041-944-0089금속선 가공제품 제조업용접철망
6청양운곡농공단지뉴그린웰㈜운곡면 청신로 567-492001-11-154041-943-8925복합비료 및 기타 화학비료 제조업유기질비료
7청양운곡농공단지㈜삼정운곡면 청신로 567-622015-10-262041-943-0026라이터,연소물 및 흡연용품 제조업고형연료
8청양운곡농공단지예영㈜운곡면 중묵운곡로 398-232015-02-098070-8267-0162그 외 기타 의료용 기기제조업산업용마스크
9청양운곡농공단지우리화학㈜운곡면 중묵운곡로 398-372003-06-304041-943-6065플라스틱 필름 제조업플라스틱관
산업단지명기업명도로명주소설립일자종업원수전화번호업종생산품
42청양비봉농공단지㈜한울비봉면 작은한술길 421993-09-09128041-943-6681김치류 제조업김치류
43청양비봉농공단지우일산업㈜비봉면 작은한술길 48-71995-12-1525041-942-9889동물성 유지 제조업유지,단미사료
44청양비봉농공단지㈜진에너텍비봉면 작은한술길 48-392012-01-2729041-942-7234라이터,연소물 및 흡연용품 제조업펠렛
45청양비봉농공단지케이씨그린에너지비봉면 작은한술길 48-442020-06-0518041-943-0097라이터,연소물 및 흡연용품 제조업펠렛
46청양비봉농공단지대양테크비봉면 작은한술길 48-212018-12-081<NA>산업용 건조기 및 장비 제조업산업용 건조기
47청양비봉농공단지주식회사 서해중공업비봉면 작은한술길 48-302019-02-273041-943-8708금속 절삭기계 제조업공작기계
48청양비봉농공단지㈜수이노베이션비봉면 작은한술길 48-272020-01-1614041-942-0114라이터,연소물 및 흡연용품 제조업펠렛
49청양비봉농공단지㈜대경에너텍비봉면 작은한술길 48-162003-05-075041-943-9082절삭가공 및 유사처리업플라스틱관
50청양비봉농공단지㈜으뜸농산비봉면 작은한술길 48-222003-07-18114041-943-7887김치류 제조업단무지
51청양비봉농공단지㈜충청비봉면 작은한술길 48-382004-10-307041-943-3922콘크리트관 및 기타 구조용 콘크리트 제품 제조업콘크리트관