Overview

Dataset statistics

Number of variables6
Number of observations79
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory50.7 B

Variable types

Categorical1
Text4
Numeric1

Dataset

Description본 제공자료는 상주시 산업(농공)단지 입주기업 현황 자료(2021.12.31.) 로서 단지명, 입주기업체명, 공장대표주소, 대표업종번호, 업종명, 회사전화번호 입니다
Author경상북도 상주시
URLhttps://www.data.go.kr/data/15098566/fileData.do

Reproduction

Analysis started2023-12-11 23:36:24.212160
Analysis finished2023-12-11 23:36:25.101938
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단지명
Categorical

Distinct9
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size764.0 B
상주외답농공단지
20 
상주함창농공단지
14 
상주함창제2농공단지
12 
상주공성농공단지
11 
상주화동농공단지
Other values (4)
16 

Length

Max length10
Median length8
Mean length8.5822785
Min length8

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
상주외답농공단지 20
25.3%
상주함창농공단지 14
17.7%
상주함창제2농공단지 12
15.2%
상주공성농공단지 11
13.9%
상주화동농공단지 6
 
7.6%
상주청리일반산업단지 5
 
6.3%
상주화서농공단지 5
 
6.3%
상주화서제2농공단지 5
 
6.3%
상주한방일반산업단지 1
 
1.3%

Length

2023-12-12T08:36:25.217254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:36:25.348866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상주외답농공단지 20
25.3%
상주함창농공단지 14
17.7%
상주함창제2농공단지 12
15.2%
상주공성농공단지 11
13.9%
상주화동농공단지 6
 
7.6%
상주청리일반산업단지 5
 
6.3%
상주화서농공단지 5
 
6.3%
상주화서제2농공단지 5
 
6.3%
상주한방일반산업단지 1
 
1.3%
Distinct76
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-12T08:36:25.601898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.6962025
Min length4

Characters and Unicode

Total characters608
Distinct characters148
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)92.4%

Sample

1st row(주)누리
2nd row(주)메쉬코리아
3rd row(주)비에스티/상주지점
4th row(주)성왕이앤에프
5th row(주)지오콘
ValueCountFrequency (%)
주식회사 11
 
11.5%
농업회사법인 3
 
3.1%
주)대평 2
 
2.1%
주)덕산지에스 2
 
2.1%
현대파이프(주 2
 
2.1%
주)비엘에프씨 1
 
1.0%
덕산콘크리트(주 1
 
1.0%
대흥수지 1
 
1.0%
주)턴투 1
 
1.0%
주)케이아이피씨엠 1
 
1.0%
Other values (71) 71
74.0%
2023-12-12T08:36:26.026398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
11.8%
( 57
 
9.4%
) 57
 
9.4%
18
 
3.0%
18
 
3.0%
15
 
2.5%
14
 
2.3%
12
 
2.0%
12
 
2.0%
10
 
1.6%
Other values (138) 323
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 472
77.6%
Open Punctuation 57
 
9.4%
Close Punctuation 57
 
9.4%
Space Separator 18
 
3.0%
Decimal Number 2
 
0.3%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
72
 
15.3%
18
 
3.8%
15
 
3.2%
14
 
3.0%
12
 
2.5%
12
 
2.5%
10
 
2.1%
9
 
1.9%
9
 
1.9%
9
 
1.9%
Other values (131) 292
61.9%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
/ 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 472
77.6%
Common 136
 
22.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
72
 
15.3%
18
 
3.8%
15
 
3.2%
14
 
3.0%
12
 
2.5%
12
 
2.5%
10
 
2.1%
9
 
1.9%
9
 
1.9%
9
 
1.9%
Other values (131) 292
61.9%
Common
ValueCountFrequency (%)
( 57
41.9%
) 57
41.9%
18
 
13.2%
1 1
 
0.7%
2 1
 
0.7%
. 1
 
0.7%
/ 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 472
77.6%
ASCII 136
 
22.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
72
 
15.3%
18
 
3.8%
15
 
3.2%
14
 
3.0%
12
 
2.5%
12
 
2.5%
10
 
2.1%
9
 
1.9%
9
 
1.9%
9
 
1.9%
Other values (131) 292
61.9%
ASCII
ValueCountFrequency (%)
( 57
41.9%
) 57
41.9%
18
 
13.2%
1 1
 
0.7%
2 1
 
0.7%
. 1
 
0.7%
/ 1
 
0.7%
Distinct69
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-12T08:36:26.269331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32
Mean length23.696203
Min length20

Characters and Unicode

Total characters1872
Distinct characters57
Distinct categories6 ?
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 (%)74.7%

Sample

1st row경상북도 상주시 공성면 평천공단길 7-14
2nd row경상북도 상주시 공성면 평천공단길 9-11
3rd row경상북도 상주시 공성면 평천공단길 29-14 (총 3 필지) 외 2필지
4th row경상북도 상주시 공성면 평천공단길 7-30
5th row경상북도 상주시 공성면 평천공단길 15
ValueCountFrequency (%)
경상북도 79
18.6%
상주시 79
18.6%
함창읍 26
 
6.1%
영동길 22
 
5.2%
헌신공단길 13
 
3.1%
헌신동 13
 
3.1%
평천공단길 11
 
2.6%
공성면 11
 
2.6%
화서면 10
 
2.4%
9
 
2.1%
Other values (83) 152
35.8%
2023-12-12T08:36:26.625100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
346
18.5%
161
 
8.6%
80
 
4.3%
79
 
4.2%
79
 
4.2%
79
 
4.2%
79
 
4.2%
59
 
3.2%
52
 
2.8%
- 49
 
2.6%
Other values (47) 809
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1165
62.2%
Space Separator 346
 
18.5%
Decimal Number 264
 
14.1%
Dash Punctuation 49
 
2.6%
Open Punctuation 24
 
1.3%
Close Punctuation 24
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
161
 
13.8%
80
 
6.9%
79
 
6.8%
79
 
6.8%
79
 
6.8%
79
 
6.8%
59
 
5.1%
52
 
4.5%
43
 
3.7%
33
 
2.8%
Other values (33) 421
36.1%
Decimal Number
ValueCountFrequency (%)
1 44
16.7%
2 42
15.9%
9 36
13.6%
8 27
10.2%
7 27
10.2%
3 24
9.1%
6 21
8.0%
4 21
8.0%
0 11
 
4.2%
5 11
 
4.2%
Space Separator
ValueCountFrequency (%)
346
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1165
62.2%
Common 707
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
161
 
13.8%
80
 
6.9%
79
 
6.8%
79
 
6.8%
79
 
6.8%
79
 
6.8%
59
 
5.1%
52
 
4.5%
43
 
3.7%
33
 
2.8%
Other values (33) 421
36.1%
Common
ValueCountFrequency (%)
346
48.9%
- 49
 
6.9%
1 44
 
6.2%
2 42
 
5.9%
9 36
 
5.1%
8 27
 
3.8%
7 27
 
3.8%
3 24
 
3.4%
( 24
 
3.4%
) 24
 
3.4%
Other values (4) 64
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1165
62.2%
ASCII 707
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
346
48.9%
- 49
 
6.9%
1 44
 
6.2%
2 42
 
5.9%
9 36
 
5.1%
8 27
 
3.8%
7 27
 
3.8%
3 24
 
3.4%
( 24
 
3.4%
) 24
 
3.4%
Other values (4) 64
 
9.1%
Hangul
ValueCountFrequency (%)
161
 
13.8%
80
 
6.9%
79
 
6.8%
79
 
6.8%
79
 
6.8%
79
 
6.8%
59
 
5.1%
52
 
4.5%
43
 
3.7%
33
 
2.8%
Other values (33) 421
36.1%

대표업종번호
Real number (ℝ)

Distinct52
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21838.519
Minimum10211
Maximum38321
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-12T08:36:26.745248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10211
5-th percentile10730.6
Q119019
median23322
Q325112
95-th percentile30689.2
Maximum38321
Range28110
Interquartile range (IQR)6093

Descriptive statistics

Standard deviation6533.6597
Coefficient of variation (CV)0.29918053
Kurtosis0.035798481
Mean21838.519
Median Absolute Deviation (MAD)2977
Skewness-0.1430106
Sum1725243
Variance42688709
MonotonicityNot monotonic
2023-12-12T08:36:26.877778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23325 12
 
15.2%
23322 3
 
3.8%
10749 3
 
3.8%
22211 3
 
3.8%
23324 2
 
2.5%
22251 2
 
2.5%
29210 2
 
2.5%
38321 2
 
2.5%
33301 2
 
2.5%
28422 2
 
2.5%
Other values (42) 46
58.2%
ValueCountFrequency (%)
10211 1
 
1.3%
10309 1
 
1.3%
10611 1
 
1.3%
10619 1
 
1.3%
10743 1
 
1.3%
10749 3
3.8%
10797 1
 
1.3%
10799 1
 
1.3%
10801 1
 
1.3%
10802 1
 
1.3%
ValueCountFrequency (%)
38321 2
2.5%
33301 2
2.5%
30399 1
1.3%
29299 1
1.3%
29210 2
2.5%
29131 1
1.3%
28519 1
1.3%
28422 2
2.5%
28123 2
2.5%
26326 1
1.3%
Distinct57
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-12T08:36:27.159148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length19.949367
Min length6

Characters and Unicode

Total characters1576
Distinct characters149
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)57.0%

Sample

1st row그 외 자동차용 신품 부품 제조업 외 3 종
2nd row금속선 가공제품 제조업 외 1 종
3rd row그 외 기타 고무제품 제조업
4th row목재 도구 및 주방용 나무제품 제조업
5th row플라스틱 필름 제조업 외 3 종
ValueCountFrequency (%)
제조업 70
 
13.8%
45
 
8.9%
40
 
7.9%
기타 36
 
7.1%
35
 
6.9%
콘크리트 26
 
5.1%
1 19
 
3.8%
구조용 15
 
3.0%
15
 
3.0%
제품 13
 
2.6%
Other values (117) 192
37.9%
2023-12-12T08:36:27.574344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
427
27.1%
103
 
6.5%
96
 
6.1%
85
 
5.4%
52
 
3.3%
45
 
2.9%
41
 
2.6%
38
 
2.4%
38
 
2.4%
37
 
2.3%
Other values (139) 614
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1096
69.5%
Space Separator 427
 
27.1%
Decimal Number 36
 
2.3%
Other Punctuation 17
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
103
 
9.4%
96
 
8.8%
85
 
7.8%
52
 
4.7%
45
 
4.1%
41
 
3.7%
38
 
3.5%
38
 
3.5%
37
 
3.4%
34
 
3.1%
Other values (132) 527
48.1%
Decimal Number
ValueCountFrequency (%)
1 21
58.3%
2 8
 
22.2%
3 5
 
13.9%
4 1
 
2.8%
8 1
 
2.8%
Space Separator
ValueCountFrequency (%)
427
100.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1096
69.5%
Common 480
30.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
103
 
9.4%
96
 
8.8%
85
 
7.8%
52
 
4.7%
45
 
4.1%
41
 
3.7%
38
 
3.5%
38
 
3.5%
37
 
3.4%
34
 
3.1%
Other values (132) 527
48.1%
Common
ValueCountFrequency (%)
427
89.0%
1 21
 
4.4%
, 17
 
3.5%
2 8
 
1.7%
3 5
 
1.0%
4 1
 
0.2%
8 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1095
69.5%
ASCII 480
30.5%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
427
89.0%
1 21
 
4.4%
, 17
 
3.5%
2 8
 
1.7%
3 5
 
1.0%
4 1
 
0.2%
8 1
 
0.2%
Hangul
ValueCountFrequency (%)
103
 
9.4%
96
 
8.8%
85
 
7.8%
52
 
4.7%
45
 
4.1%
41
 
3.7%
38
 
3.5%
38
 
3.5%
37
 
3.4%
34
 
3.1%
Other values (131) 526
48.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct71
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-12T08:36:27.818671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.987342
Min length11

Characters and Unicode

Total characters947
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

Unique63 ?
Unique (%)79.7%

Sample

1st row054-532-5696
2nd row054-533-8323
3rd row031-511-5451
4th row054-434-5701
5th row054-534-0901
ValueCountFrequency (%)
054-907-5788 2
 
2.5%
054-541-4801 2
 
2.5%
054-532-3887 2
 
2.5%
054-541-9001 2
 
2.5%
054-541-0419 2
 
2.5%
02-451-3415 2
 
2.5%
054-534-3614 2
 
2.5%
054-541-0486 2
 
2.5%
054-541-1080 1
 
1.3%
054-541-5112 1
 
1.3%
Other values (61) 61
77.2%
2023-12-12T08:36:28.186795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 176
18.6%
- 158
16.7%
4 144
15.2%
0 135
14.3%
3 89
9.4%
1 80
8.4%
2 41
 
4.3%
8 39
 
4.1%
7 33
 
3.5%
9 32
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 789
83.3%
Dash Punctuation 158
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 176
22.3%
4 144
18.3%
0 135
17.1%
3 89
11.3%
1 80
10.1%
2 41
 
5.2%
8 39
 
4.9%
7 33
 
4.2%
9 32
 
4.1%
6 20
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 947
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 176
18.6%
- 158
16.7%
4 144
15.2%
0 135
14.3%
3 89
9.4%
1 80
8.4%
2 41
 
4.3%
8 39
 
4.1%
7 33
 
3.5%
9 32
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 947
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 176
18.6%
- 158
16.7%
4 144
15.2%
0 135
14.3%
3 89
9.4%
1 80
8.4%
2 41
 
4.3%
8 39
 
4.1%
7 33
 
3.5%
9 32
 
3.4%

Interactions

2023-12-12T08:36:24.779490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:36:28.291341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지명회사명공장대표주소(도로명)대표업종번호업종명전화번호
단지명1.0000.8791.0000.3070.8240.985
회사명0.8791.0000.9721.0000.9970.999
공장대표주소(도로명)1.0000.9721.0000.9650.9440.992
대표업종번호0.3071.0000.9651.0001.0000.996
업종명0.8240.9970.9441.0001.0000.995
전화번호0.9850.9990.9920.9960.9951.000
2023-12-12T08:36:28.387116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대표업종번호단지명
대표업종번호1.0000.128
단지명0.1281.000

Missing values

2023-12-12T08:36:24.893277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:36:25.032063image/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

단지명회사명공장대표주소(도로명)대표업종번호업종명전화번호
0상주공성농공단지(주)누리경상북도 상주시 공성면 평천공단길 7-1430399그 외 자동차용 신품 부품 제조업 외 3 종054-532-5696
1상주공성농공단지(주)메쉬코리아경상북도 상주시 공성면 평천공단길 9-1125944금속선 가공제품 제조업 외 1 종054-533-8323
2상주공성농공단지(주)비에스티/상주지점경상북도 상주시 공성면 평천공단길 29-14 (총 3 필지) 외 2필지22199그 외 기타 고무제품 제조업031-511-5451
3상주공성농공단지(주)성왕이앤에프경상북도 상주시 공성면 평천공단길 7-3016291목재 도구 및 주방용 나무제품 제조업054-434-5701
4상주공성농공단지(주)지오콘경상북도 상주시 공성면 평천공단길 1522212플라스틱 필름 제조업 외 3 종054-534-0901
5상주공성농공단지(주)천지창조 농업회사법인경상북도 상주시 공성면 평천공단길 7-3010743장류 제조업054-373-4003
6상주공성농공단지(주)케이티앤에프경상북도 상주시 공성면 평천공단길 2310749기타 식품 첨가물 제조업 외 3 종054-534-4470
7상주공성농공단지(합)엠케어경상북도 상주시 공성면 평천공단길 3721300의료용품 및 기타 의약 관련제품 제조업 외 1 종054-534-9170
8상주공성농공단지주식회사 비지텍경상북도 상주시 공성면 평천공단길 7-3220312복합비료 및 기타 화학비료 제조업 외 1 종054-534-1999
9상주공성농공단지케이투와이(주)경상북도 상주시 공성면 평천공단길 29-1422199그 외 기타 고무제품 제조업054-532-3083
단지명회사명공장대표주소(도로명)대표업종번호업종명전화번호
69상주화서농공단지(주)대한폴리머경상북도 상주시 화서면 영남제일로 4287-3826326콘크리트관및조립구조재제조업054-534-8165
70상주화서농공단지(주)보은경상북도 상주시 화서면 영남제일로 4287-1417909그 외 기타 종이 및 판지 제품 제조업 외 1 종054-531-0340
71상주화서농공단지삼표피앤씨(주)경상북도 상주시 화서면 영남제일로 4287-1123325콘크리트 관 및 기타 구조용 콘크리트 제품 제조업054-534-2538
72상주화서농공단지와이제이팩경상북도 상주시 화서면 영남제일로 4287-1417211골판지 제조업031-945-4055
73상주화서농공단지중화레미콘(주)경상북도 상주시 화서면 영남제일로 4287-2423322레미콘 제조업054-531-2101
74상주화서제2농공단지(주)가산경상북도 상주시 화서면 상용리 713번지23325콘크리트 관 및 기타 구조용 콘크리트 제품 제조업070-4849-6465
75상주화서제2농공단지(주)올품 상주사료공장경상북도 상주시 화서면 상용리 702번지10801배합 사료 제조업 외 1 종054-533-9998
76상주화서제2농공단지세연테크경상북도 상주시 화서면 영남제일로 4287-6823325콘크리트 관 및 기타 구조용 콘크리트 제품 제조업02-451-3415
77상주화서제2농공단지제이제이피씨산업 주식회사경상북도 상주시 화서면 영남제일로 4287-6823325콘크리트 관 및 기타 구조용 콘크리트 제품 제조업02-451-3415
78상주화서제2농공단지주식회사 진성경상북도 상주시 화서면 상용리 713-1번지23325콘크리트 관 및 기타 구조용 콘크리트 제품 제조업054-500-8509