Overview

Dataset statistics

Number of variables3
Number of observations54
Missing cells2
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory26.4 B

Variable types

Text3

Dataset

Description인천광역시 부평구_기계가스설비공사업 현황 데이터는 부평구 내에 기계가스설비공사업체의 업체명, 도로명 주소, 전화번호 정보를 제공하고 있습니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15117920&srcSe=7661IVAWM27C61E190

Alerts

전화번호 has 2 (3.7%) missing valuesMissing
업체명 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-04-17 18:41:02.325736
Analysis finished2024-04-17 18:41:02.596319
Duration0.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2024-04-18T03:41:02.721292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.8148148
Min length4

Characters and Unicode

Total characters422
Distinct characters99
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

Unique54 ?
Unique (%)100.0%

Sample

1st row(주)가온이앤아이
2nd row(주)강현이엔씨
3rd row(주)금당
4th row(주)더존이엔씨
5th row(주)디에스이엔지
ValueCountFrequency (%)
주)가온이앤아이 1
 
1.9%
삼진건축설비 1
 
1.9%
현대엠지(주 1
 
1.9%
강원건축설비 1
 
1.9%
공간지에스(주 1
 
1.9%
기산수기 1
 
1.9%
대송이엔지(주 1
 
1.9%
대신이앤씨(주 1
 
1.9%
대흥엔지니어링주식회사 1
 
1.9%
동신설비공사 1
 
1.9%
Other values (44) 44
81.5%
2024-04-18T03:41:02.981855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 42
 
10.0%
( 38
 
9.0%
) 38
 
9.0%
이 25
 
5.9%
지 16
 
3.8%
엔 15
 
3.6%
에 14
 
3.3%
스 12
 
2.8%
설 8
 
1.9%
비 8
 
1.9%
Other values (89) 206
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 340
80.6%
Open Punctuation 38
 
9.0%
Close Punctuation 38
 
9.0%
Other Symbol 6
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 42
 
12.4%
이 25
 
7.4%
지 16
 
4.7%
엔 15
 
4.4%
에 14
 
4.1%
스 12
 
3.5%
설 8
 
2.4%
비 8
 
2.4%
아 7
 
2.1%
링 7
 
2.1%
Other values (86) 186
54.7%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 346
82.0%
Common 76
 
18.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 42
 
12.1%
이 25
 
7.2%
지 16
 
4.6%
엔 15
 
4.3%
에 14
 
4.0%
스 12
 
3.5%
설 8
 
2.3%
비 8
 
2.3%
아 7
 
2.0%
링 7
 
2.0%
Other values (87) 192
55.5%
Common
ValueCountFrequency (%)
( 38
50.0%
) 38
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 340
80.6%
ASCII 76
 
18.0%
None 6
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 42
 
12.4%
이 25
 
7.4%
지 16
 
4.7%
엔 15
 
4.4%
에 14
 
4.1%
스 12
 
3.5%
설 8
 
2.4%
비 8
 
2.4%
아 7
 
2.1%
링 7
 
2.1%
Other values (86) 186
54.7%
ASCII
ValueCountFrequency (%)
( 38
50.0%
) 38
50.0%
None
ValueCountFrequency (%)
㈜ 6
100.0%

도로명주소
Text

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2024-04-18T03:41:03.235791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length36
Mean length31.166667
Min length22

Characters and Unicode

Total characters1683
Distinct characters93
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 길주로 659 5층 507호 (삼산동)
2nd row인천광역시 부평구 길주로 623 101동 1505-2호 (삼산동)
3rd row인천광역시 부평구 경인로 959-1 301호 (부평동)
4th row인천광역시 부평구 새벌로 4 공장동2층 201-3호 (청천동)
5th row인천광역시 부평구 청천마차로 250 (청천동)
ValueCountFrequency (%)
인천광역시 54
 
15.9%
부평구 54
 
15.9%
청천동 20
 
5.9%
부평대로 13
 
3.8%
부평동 9
 
2.6%
283 8
 
2.4%
십정동 7
 
2.1%
삼산동 6
 
1.8%
경인로 4
 
1.2%
1층 4
 
1.2%
Other values (127) 161
47.4%
2024-04-18T03:41:03.590355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
286
 
17.0%
부 89
 
5.3%
평 85
 
5.1%
천 77
 
4.6%
동 65
 
3.9%
인 60
 
3.6%
구 56
 
3.3%
시 54
 
3.2%
( 54
 
3.2%
광 54
 
3.2%
Other values (83) 803
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 944
56.1%
Decimal Number 317
 
18.8%
Space Separator 286
 
17.0%
Open Punctuation 54
 
3.2%
Close Punctuation 54
 
3.2%
Other Punctuation 11
 
0.7%
Uppercase Letter 9
 
0.5%
Dash Punctuation 8
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 89
 
9.4%
평 85
 
9.0%
천 77
 
8.2%
동 65
 
6.9%
인 60
 
6.4%
구 56
 
5.9%
시 54
 
5.7%
광 54
 
5.7%
로 54
 
5.7%
역 54
 
5.7%
Other values (64) 296
31.4%
Decimal Number
ValueCountFrequency (%)
1 53
16.7%
2 51
16.1%
3 47
14.8%
0 40
12.6%
5 31
9.8%
4 22
6.9%
8 20
 
6.3%
6 19
 
6.0%
9 17
 
5.4%
7 17
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 5
55.6%
A 2
 
22.2%
C 2
 
22.2%
Other Punctuation
ValueCountFrequency (%)
, 8
72.7%
， 3
 
27.3%
Space Separator
ValueCountFrequency (%)
286
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 944
56.1%
Common 730
43.4%
Latin 9
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 89
 
9.4%
평 85
 
9.0%
천 77
 
8.2%
동 65
 
6.9%
인 60
 
6.4%
구 56
 
5.9%
시 54
 
5.7%
광 54
 
5.7%
로 54
 
5.7%
역 54
 
5.7%
Other values (64) 296
31.4%
Common
ValueCountFrequency (%)
286
39.2%
( 54
 
7.4%
) 54
 
7.4%
1 53
 
7.3%
2 51
 
7.0%
3 47
 
6.4%
0 40
 
5.5%
5 31
 
4.2%
4 22
 
3.0%
8 20
 
2.7%
Other values (6) 72
 
9.9%
Latin
ValueCountFrequency (%)
B 5
55.6%
A 2
 
22.2%
C 2
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 944
56.1%
ASCII 736
43.7%
None 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
286
38.9%
( 54
 
7.3%
) 54
 
7.3%
1 53
 
7.2%
2 51
 
6.9%
3 47
 
6.4%
0 40
 
5.4%
5 31
 
4.2%
4 22
 
3.0%
8 20
 
2.7%
Other values (8) 78
 
10.6%
Hangul
ValueCountFrequency (%)
부 89
 
9.4%
평 85
 
9.0%
천 77
 
8.2%
동 65
 
6.9%
인 60
 
6.4%
구 56
 
5.9%
시 54
 
5.7%
광 54
 
5.7%
로 54
 
5.7%
역 54
 
5.7%
Other values (64) 296
31.4%
None
ValueCountFrequency (%)
， 3
100.0%

전화번호
Text

MISSING 

Distinct52
Distinct (%)100.0%
Missing2
Missing (%)3.7%
Memory size564.0 B
2024-04-18T03:41:03.783163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.980769
Min length11

Characters and Unicode

Total characters623
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

Unique52 ?
Unique (%)100.0%

Sample

1st row032-517-1191
2nd row032-323-1616
3rd row032-330-3009
4th row032-441-1313
5th row032-513-8004
ValueCountFrequency (%)
032-504-2328 1
 
1.9%
032-501-7777 1
 
1.9%
032-715-5223 1
 
1.9%
032-887-7760 1
 
1.9%
032-218-3003 1
 
1.9%
032-515-8076 1
 
1.9%
032-544-6660 1
 
1.9%
032-502-3355 1
 
1.9%
032-519-9001 1
 
1.9%
032-512-0488 1
 
1.9%
Other values (42) 42
80.8%
2024-04-18T03:41:04.076219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 104
16.7%
0 102
16.4%
3 95
15.2%
2 88
14.1%
1 55
8.8%
5 50
8.0%
6 36
 
5.8%
7 33
 
5.3%
4 22
 
3.5%
8 21
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 519
83.3%
Dash Punctuation 104
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 102
19.7%
3 95
18.3%
2 88
17.0%
1 55
10.6%
5 50
9.6%
6 36
 
6.9%
7 33
 
6.4%
4 22
 
4.2%
8 21
 
4.0%
9 17
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 623
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 104
16.7%
0 102
16.4%
3 95
15.2%
2 88
14.1%
1 55
8.8%
5 50
8.0%
6 36
 
5.8%
7 33
 
5.3%
4 22
 
3.5%
8 21
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 623
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 104
16.7%
0 102
16.4%
3 95
15.2%
2 88
14.1%
1 55
8.8%
5 50
8.0%
6 36
 
5.8%
7 33
 
5.3%
4 22
 
3.5%
8 21
 
3.4%

Correlations

2024-04-18T03:41:04.157957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명도로명주소전화번호
업체명1.0001.0001.000
도로명주소1.0001.0001.000
전화번호1.0001.0001.000

Missing values

2024-04-18T03:41:02.517427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T03:41:02.574026image/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

업체명도로명주소전화번호
0(주)가온이앤아이인천광역시 부평구 길주로 659 5층 507호 (삼산동)032-517-1191
1(주)강현이엔씨인천광역시 부평구 길주로 623 101동 1505-2호 (삼산동)032-323-1616
2(주)금당인천광역시 부평구 경인로 959-1 301호 (부평동)032-330-3009
3(주)더존이엔씨인천광역시 부평구 새벌로 4 공장동2층 201-3호 (청천동)032-441-1313
4(주)디에스이엔지인천광역시 부평구 청천마차로 250 (청천동)032-513-8004
5(주)무영이엔지인천광역시 부평구 경인로 1015 2층 201호 (부개동)032-518-7211
6(주)바텍인천광역시 부평구 일신로8번길 29 사랑빌딩 4층 (일신동)032-502-8610
7(주)비와이엔지니어링인천광역시 부평구 부평대로 138 1210호 (부평동)<NA>
8(주)서광이엔지인천광역시 부평구 평천로 396 5층 501호,502호 (삼산동)032-502-5551
9(주)세원글로벌인천광역시 부평구 부평대로329번길 3 (청천동)032-330-6671
업체명도로명주소전화번호
44엠에이산업(주)인천광역시 부평구 일신로39번길 16-11 , 3층 (일신동)032-663-2326
45은성산기(주)인천광역시 부평구 부평대로 283 B동 B115호 (청천동)032-623-5281
46조광설비(주)인천광역시 부평구 영성서로 3， 1층 (삼산동)032-522-3088
47주식회사숨터인천광역시 부평구 백범로577번길 20 703호-3호 (십정동)02-578-0099
48킹스엔지니어링(주)인천광역시 부평구 부평대로 337 제7층 제745호 (청천동)032-361-9600
49플로우테크(주)인천광역시 부평구 부평대로 283 에이동 409호 (청천동, 부평우림라이온스밸리)032-715-7990
50하나방재설비(주)인천광역시 부평구 경인로 896 (부평동)032-501-6161
51하늘건설(주)인천광역시 부평구 경원대로1130번길 6， 203호 (십정동)032-514-9000
52현대엠지(주)인천광역시 부평구 가재울로 129 (십정동)032-571-1426
53형제설비인천광역시 부평구 신촌로 50 (부평동)<NA>