Overview

Dataset statistics

Number of variables4
Number of observations109
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory34.2 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description충청남도 홍성군 지역내 산업단지 입주기업 현황으로 단지명으로 분류를 하여 ,회사명, 업종분류를 하여 업종별로도 사업의 분류를 할수있게 기재되어있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=438&beforeMenuCd=DOM_000000201001001000&publicdatapk=15028983

Alerts

연번 is highly overall correlated with 단지명High correlation
단지명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:43:57.351085
Analysis finished2024-01-09 22:43:57.752399
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55
Minimum1
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:43:57.821765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.4
Q128
median55
Q382
95-th percentile103.6
Maximum109
Range108
Interquartile range (IQR)54

Descriptive statistics

Standard deviation31.609598
Coefficient of variation (CV)0.57471996
Kurtosis-1.2
Mean55
Median Absolute Deviation (MAD)27
Skewness0
Sum5995
Variance999.16667
MonotonicityStrictly increasing
2024-01-10T07:43:57.945754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%

단지명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1004.0 B
결성전문농공단지
30 
갈산전문농공단지
16 
구항농공단지
16 
광천농공단지
14 
광천김특화농공단지
9 
Other values (4)
24 

Length

Max length10
Median length8
Mean length7.6422018
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
결성전문농공단지 30
27.5%
갈산전문농공단지 16
14.7%
구항농공단지 16
14.7%
광천농공단지 14
12.8%
광천김특화농공단지 9
 
8.3%
내포도시첨단산업단지 8
 
7.3%
은하전문농공단지 8
 
7.3%
홍성일반산업단지 6
 
5.5%
은하농공단지 2
 
1.8%

Length

2024-01-10T07:43:58.058615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:43:58.167367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
결성전문농공단지 30
27.5%
갈산전문농공단지 16
14.7%
구항농공단지 16
14.7%
광천농공단지 14
12.8%
광천김특화농공단지 9
 
8.3%
내포도시첨단산업단지 8
 
7.3%
은하전문농공단지 8
 
7.3%
홍성일반산업단지 6
 
5.5%
은하농공단지 2
 
1.8%

회사명
Text

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2024-01-10T07:43:58.364259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.3027523
Min length3

Characters and Unicode

Total characters796
Distinct characters177
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)98.2%

Sample

1st row㈜경남금속
2nd row㈜수천중공업
3rd row㈜우심시스템
4th row일진전기㈜
5th row㈜벽산
ValueCountFrequency (%)
주식회사 8
 
6.3%
주)동신포리마 4
 
3.1%
원강금속(주 3
 
2.4%
2공장 3
 
2.4%
주)참그로 2
 
1.6%
㈜한진오토모티브 2
 
1.6%
제2공장 2
 
1.6%
광천조양식품 1
 
0.8%
신한쎌틱(주 1
 
0.8%
주)블루월드 1
 
0.8%
Other values (100) 100
78.7%
2024-01-10T07:43:58.681569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 69
 
8.7%
( 59
 
7.4%
) 59
 
7.4%
이 23
 
2.9%
㈜ 22
 
2.8%
18
 
2.3%
업 14
 
1.8%
산 14
 
1.8%
식 13
 
1.6%
스 12
 
1.5%
Other values (167) 493
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 629
79.0%
Open Punctuation 59
 
7.4%
Close Punctuation 59
 
7.4%
Other Symbol 22
 
2.8%
Space Separator 18
 
2.3%
Decimal Number 8
 
1.0%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 69
 
11.0%
이 23
 
3.7%
업 14
 
2.2%
산 14
 
2.2%
식 13
 
2.1%
스 12
 
1.9%
에 12
 
1.9%
공 12
 
1.9%
크 10
 
1.6%
사 10
 
1.6%
Other values (159) 440
70.0%
Decimal Number
ValueCountFrequency (%)
2 6
75.0%
4 1
 
12.5%
3 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 22
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 651
81.8%
Common 145
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 69
 
10.6%
이 23
 
3.5%
㈜ 22
 
3.4%
업 14
 
2.2%
산 14
 
2.2%
식 13
 
2.0%
스 12
 
1.8%
에 12
 
1.8%
공 12
 
1.8%
크 10
 
1.5%
Other values (160) 450
69.1%
Common
ValueCountFrequency (%)
( 59
40.7%
) 59
40.7%
18
 
12.4%
2 6
 
4.1%
4 1
 
0.7%
3 1
 
0.7%
- 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 629
79.0%
ASCII 145
 
18.2%
None 22
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 69
 
11.0%
이 23
 
3.7%
업 14
 
2.2%
산 14
 
2.2%
식 13
 
2.1%
스 12
 
1.9%
에 12
 
1.9%
공 12
 
1.9%
크 10
 
1.6%
사 10
 
1.6%
Other values (159) 440
70.0%
ASCII
ValueCountFrequency (%)
( 59
40.7%
) 59
40.7%
18
 
12.4%
2 6
 
4.1%
4 1
 
0.7%
3 1
 
0.7%
- 1
 
0.7%
None
ValueCountFrequency (%)
㈜ 22
100.0%

업종명
Text

Distinct74
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2024-01-10T07:43:58.974811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length18.183486
Min length7

Characters and Unicode

Total characters1982
Distinct characters167
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

Unique59 ?
Unique (%)54.1%

Sample

1st row알루미늄 제련, 정련 및 합금 제조업
2nd row금속 조립구조재 제조업
3rd row컴퓨터 프린터 제조업
4th row변압기 제조업 외 2 종
5th row폴리스티렌 발포 성형제품 제조업
ValueCountFrequency (%)
제조업 93
 
14.9%
외 75
 
12.0%
및 46
 
7.4%
그 32
 
5.1%
기타 25
 
4.0%
부품 23
 
3.7%
신품 16
 
2.6%
자동차용 15
 
2.4%
자동차 10
 
1.6%
3종 9
 
1.4%
Other values (143) 279
44.8%
2024-01-10T07:43:59.379305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
514
25.9%
제 126
 
6.4%
업 115
 
5.8%
조 108
 
5.4%
외 80
 
4.0%
품 67
 
3.4%
기 49
 
2.5%
종 47
 
2.4%
및 46
 
2.3%
동 36
 
1.8%
Other values (157) 794
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1414
71.3%
Space Separator 514
 
25.9%
Decimal Number 48
 
2.4%
Other Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 126
 
8.9%
업 115
 
8.1%
조 108
 
7.6%
외 80
 
5.7%
품 67
 
4.7%
기 49
 
3.5%
종 47
 
3.3%
및 46
 
3.3%
동 36
 
2.5%
용 36
 
2.5%
Other values (146) 704
49.8%
Decimal Number
ValueCountFrequency (%)
1 15
31.2%
3 12
25.0%
2 9
18.8%
5 4
 
8.3%
4 3
 
6.2%
7 2
 
4.2%
6 1
 
2.1%
9 1
 
2.1%
8 1
 
2.1%
Space Separator
ValueCountFrequency (%)
514
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1414
71.3%
Common 568
28.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 126
 
8.9%
업 115
 
8.1%
조 108
 
7.6%
외 80
 
5.7%
품 67
 
4.7%
기 49
 
3.5%
종 47
 
3.3%
및 46
 
3.3%
동 36
 
2.5%
용 36
 
2.5%
Other values (146) 704
49.8%
Common
ValueCountFrequency (%)
514
90.5%
1 15
 
2.6%
3 12
 
2.1%
2 9
 
1.6%
, 6
 
1.1%
5 4
 
0.7%
4 3
 
0.5%
7 2
 
0.4%
6 1
 
0.2%
9 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1414
71.3%
ASCII 568
28.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
514
90.5%
1 15
 
2.6%
3 12
 
2.1%
2 9
 
1.6%
, 6
 
1.1%
5 4
 
0.7%
4 3
 
0.5%
7 2
 
0.4%
6 1
 
0.2%
9 1
 
0.2%
Hangul
ValueCountFrequency (%)
제 126
 
8.9%
업 115
 
8.1%
조 108
 
7.6%
외 80
 
5.7%
품 67
 
4.7%
기 49
 
3.5%
종 47
 
3.3%
및 46
 
3.3%
동 36
 
2.5%
용 36
 
2.5%
Other values (146) 704
49.8%

Interactions

2024-01-10T07:43:57.556866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:43:59.730028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단지명업종명
연번1.0000.9060.958
단지명0.9061.0000.996
업종명0.9580.9961.000
2024-01-10T07:43:59.800347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단지명
연번1.0000.712
단지명0.7121.000

Missing values

2024-01-10T07:43:57.649017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:43:57.724336image/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

연번단지명회사명업종명
01홍성일반산업단지㈜경남금속알루미늄 제련, 정련 및 합금 제조업
12홍성일반산업단지㈜수천중공업금속 조립구조재 제조업
23홍성일반산업단지㈜우심시스템컴퓨터 프린터 제조업
34홍성일반산업단지일진전기㈜변압기 제조업 외 2 종
45홍성일반산업단지㈜벽산폴리스티렌 발포 성형제품 제조업
56홍성일반산업단지성호티에스㈜육상 금속 골조 구조재 제조업
67내포도시첨단산업단지한양로보틱스㈜산업용 로봇제조업
78내포도시첨단산업단지㈜동양테크윈유무선 통신기기 제조업
89내포도시첨단산업단지㈜은성전장전동기 및 발전기 제조업 외3종
910내포도시첨단산업단지㈜유니에어공조산업용 냉장 및 냉동 장비 제조업 외3종
연번단지명회사명업종명
99100은하전문농공단지주식회사 글로벌 유니콘차체 및 특장차 제조업 외 7 종
100101광천김특화농공단지(주)김노리수산식물 가공 및 저장 처리업
101102광천김특화농공단지(주)솔뫼에프엔씨수산식물 가공 및 저장 처리업
102103광천김특화농공단지(주)해저식품수산식물 가공 및 저장 처리업
103104광천김특화농공단지광천농업협동조합수산식물 가공 및 저장 처리업
104105광천김특화농공단지광천조양식품수산식물 가공 및 저장 처리업
105106광천김특화농공단지서해수산푸드(주)수산동물 건조 및 염장품 제조업 외 1 종
106107광천김특화농공단지영어조합법인 최강식품수산식물 가공 및 저장 처리업
107108광천김특화농공단지천일식품(주)면류, 마카로니 및 유사식품 제조업
108109광천김특화농공단지주식회사 해저김수산식물 가공 및 저장 처리업