Overview

Dataset statistics

Number of variables12
Number of observations93
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.2 KiB
Average record size in memory101.4 B

Variable types

Categorical7
Text2
Numeric3

Dataset

Description공간정보의 구축 및 관리 등에 관한 법률 제44조에 따른 측량업 등록정보 인천시 관내 지적측량업, 공공측량업, 일반측량업 현황
URLhttps://www.data.go.kr/data/15075111/fileData.do

Alerts

등록기관 has constant value ""Constant
시도_시군구 has constant value ""Constant
영업여부 has constant value ""Constant
본점_지점 has constant value ""Constant
기술자 수 is highly overall correlated with 장비 수 and 2 other fieldsHigh correlation
장비 수 is highly overall correlated with 기술자 수 and 1 other fieldsHigh correlation
업종 is highly overall correlated with 기술자 수 and 2 other fieldsHigh correlation
개인_법인 is highly overall correlated with 기술자 수 and 1 other fieldsHigh correlation
대표자 수 is highly imbalanced (61.5%)Imbalance
등록번호 has unique valuesUnique
임원 수 has 60 (64.5%) zerosZeros

Reproduction

Analysis started2023-12-12 06:17:19.282178
Analysis finished2023-12-12 06:17:21.395455
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록기관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
지자체
93 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지자체 93
100.0%

Length

2023-12-12T15:17:21.461770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:17:21.548410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지자체 93
100.0%

시도_시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
인천광역시
93 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 93
100.0%

Length

2023-12-12T15:17:21.642181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:17:21.735209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 93
100.0%

업종
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
일반측량
56 
공공측량
26 
지적측량
11 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지적측량
2nd row일반측량
3rd row일반측량
4th row일반측량
5th row공공측량

Common Values

ValueCountFrequency (%)
일반측량 56
60.2%
공공측량 26
28.0%
지적측량 11
 
11.8%

Length

2023-12-12T15:17:21.843702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:17:21.945885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반측량 56
60.2%
공공측량 26
28.0%
지적측량 11
 
11.8%

등록번호
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-12T15:17:22.263344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters837
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

Unique93 ?
Unique (%)100.0%

Sample

1st row02-000427
2nd row04-005383
3rd row04-005370
4th row04-005354
5th row03-001477
ValueCountFrequency (%)
02-000427 1
 
1.1%
03-000863 1
 
1.1%
03-000035 1
 
1.1%
04-001579 1
 
1.1%
02-000034 1
 
1.1%
02-000030 1
 
1.1%
03-000383 1
 
1.1%
02-000120 1
 
1.1%
04-002323 1
 
1.1%
04-000089 1
 
1.1%
Other values (83) 83
89.2%
2023-12-12T15:17:22.760633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 382
45.6%
4 95
 
11.4%
- 93
 
11.1%
3 72
 
8.6%
2 39
 
4.7%
1 33
 
3.9%
9 29
 
3.5%
5 28
 
3.3%
8 25
 
3.0%
7 23
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 744
88.9%
Dash Punctuation 93
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 382
51.3%
4 95
 
12.8%
3 72
 
9.7%
2 39
 
5.2%
1 33
 
4.4%
9 29
 
3.9%
5 28
 
3.8%
8 25
 
3.4%
7 23
 
3.1%
6 18
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 837
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 382
45.6%
4 95
 
11.4%
- 93
 
11.1%
3 72
 
8.6%
2 39
 
4.7%
1 33
 
3.9%
9 29
 
3.5%
5 28
 
3.3%
8 25
 
3.0%
7 23
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 382
45.6%
4 95
 
11.4%
- 93
 
11.1%
3 72
 
8.6%
2 39
 
4.7%
1 33
 
3.9%
9 29
 
3.5%
5 28
 
3.3%
8 25
 
3.0%
7 23
 
2.7%

측량업체명
Text

Distinct84
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-12T15:17:23.053890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length9
Min length4

Characters and Unicode

Total characters837
Distinct characters146
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)81.7%

Sample

1st row웅창토지개발 주식회사
2nd row웅창토지개발 주식회사
3rd row유씨아이테크 주식회사
4th row임측량토목설계사무소
5th row주식회사 동서이엔지
ValueCountFrequency (%)
주식회사 13
 
12.0%
주식회사삼조이앤씨 3
 
2.8%
한라이엔씨 2
 
1.9%
세종측량설계기술단 2
 
1.9%
웅창토지개발 2
 
1.9%
지오서베이주식회사 2
 
1.9%
신진지아이티 2
 
1.9%
주식회사경원지적엔지니어링 2
 
1.9%
명지공간개발(주 2
 
1.9%
주)극동산업개발 1
 
0.9%
Other values (77) 77
71.3%
2023-12-12T15:17:23.513378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 54
 
6.5%
사 48
 
5.7%
지 41
 
4.9%
) 33
 
3.9%
( 33
 
3.9%
설 31
 
3.7%
계 28
 
3.3%
측 27
 
3.2%
량 26
 
3.1%
엔 25
 
3.0%
Other values (136) 491
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 750
89.6%
Close Punctuation 33
 
3.9%
Open Punctuation 33
 
3.9%
Space Separator 15
 
1.8%
Uppercase Letter 5
 
0.6%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 54
 
7.2%
사 48
 
6.4%
지 41
 
5.5%
설 31
 
4.1%
계 28
 
3.7%
측 27
 
3.6%
량 26
 
3.5%
엔 25
 
3.3%
이 23
 
3.1%
니 22
 
2.9%
Other values (127) 425
56.7%
Uppercase Letter
ValueCountFrequency (%)
E 1
20.0%
N 1
20.0%
G 1
20.0%
B 1
20.0%
H 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 751
89.7%
Common 81
 
9.7%
Latin 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 54
 
7.2%
사 48
 
6.4%
지 41
 
5.5%
설 31
 
4.1%
계 28
 
3.7%
측 27
 
3.6%
량 26
 
3.5%
엔 25
 
3.3%
이 23
 
3.1%
니 22
 
2.9%
Other values (128) 426
56.7%
Latin
ValueCountFrequency (%)
E 1
20.0%
N 1
20.0%
G 1
20.0%
B 1
20.0%
H 1
20.0%
Common
ValueCountFrequency (%)
) 33
40.7%
( 33
40.7%
15
18.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 750
89.6%
ASCII 86
 
10.3%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 54
 
7.2%
사 48
 
6.4%
지 41
 
5.5%
설 31
 
4.1%
계 28
 
3.7%
측 27
 
3.6%
량 26
 
3.5%
엔 25
 
3.3%
이 23
 
3.1%
니 22
 
2.9%
Other values (127) 425
56.7%
ASCII
ValueCountFrequency (%)
) 33
38.4%
( 33
38.4%
15
17.4%
E 1
 
1.2%
N 1
 
1.2%
G 1
 
1.2%
B 1
 
1.2%
H 1
 
1.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

영업여부
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
영업
93 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 93
100.0%

Length

2023-12-12T15:17:23.683093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:17:23.770121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 93
100.0%

개인_법인
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
법인
54 
개인
39 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row법인
2nd row법인
3rd row개인
4th row개인
5th row법인

Common Values

ValueCountFrequency (%)
법인 54
58.1%
개인 39
41.9%

Length

2023-12-12T15:17:23.871605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:17:24.031750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 54
58.1%
개인 39
41.9%

본점_지점
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
본점
93 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
본점 93
100.0%

Length

2023-12-12T15:17:24.194493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:17:24.308167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 93
100.0%

대표자 수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
1
86 
2
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 86
92.5%
2 7
 
7.5%

Length

2023-12-12T15:17:24.397676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:17:24.517483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 86
92.5%
2 7
 
7.5%

임원 수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.92473118
Minimum0
Maximum13
Zeros60
Zeros (%)64.5%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-12T15:17:24.625110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3.4
Maximum13
Range13
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7584366
Coefficient of variation (CV)1.9015651
Kurtosis23.388146
Mean0.92473118
Median Absolute Deviation (MAD)0
Skewness3.9170413
Sum86
Variance3.0920991
MonotonicityNot monotonic
2023-12-12T15:17:24.737294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 60
64.5%
2 13
 
14.0%
3 8
 
8.6%
1 7
 
7.5%
4 4
 
4.3%
13 1
 
1.1%
ValueCountFrequency (%)
0 60
64.5%
1 7
 
7.5%
2 13
 
14.0%
3 8
 
8.6%
4 4
 
4.3%
13 1
 
1.1%
ValueCountFrequency (%)
13 1
 
1.1%
4 4
 
4.3%
3 8
 
8.6%
2 13
 
14.0%
1 7
 
7.5%
0 60
64.5%

기술자 수
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0215054
Minimum2
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-12T15:17:24.863733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median2
Q36
95-th percentile11.4
Maximum15
Range13
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.0359387
Coefficient of variation (CV)0.75492593
Kurtosis2.6262642
Mean4.0215054
Median Absolute Deviation (MAD)0
Skewness1.6749982
Sum374
Variance9.2169238
MonotonicityNot monotonic
2023-12-12T15:17:25.007276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 56
60.2%
6 22
 
23.7%
5 3
 
3.2%
12 3
 
3.2%
7 2
 
2.2%
8 1
 
1.1%
11 1
 
1.1%
14 1
 
1.1%
10 1
 
1.1%
15 1
 
1.1%
Other values (2) 2
 
2.2%
ValueCountFrequency (%)
2 56
60.2%
3 1
 
1.1%
4 1
 
1.1%
5 3
 
3.2%
6 22
 
23.7%
7 2
 
2.2%
8 1
 
1.1%
10 1
 
1.1%
11 1
 
1.1%
12 3
 
3.2%
ValueCountFrequency (%)
15 1
 
1.1%
14 1
 
1.1%
12 3
 
3.2%
11 1
 
1.1%
10 1
 
1.1%
8 1
 
1.1%
7 2
 
2.2%
6 22
23.7%
5 3
 
3.2%
4 1
 
1.1%

장비 수
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.311828
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-12T15:17:25.141029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median2
Q33
95-th percentile12
Maximum21
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.6534037
Coefficient of variation (CV)1.1031381
Kurtosis10.468823
Mean3.311828
Median Absolute Deviation (MAD)0
Skewness3.2925482
Sum308
Variance13.347359
MonotonicityNot monotonic
2023-12-12T15:17:25.272683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 68
73.1%
3 11
 
11.8%
4 3
 
3.2%
12 3
 
3.2%
5 2
 
2.2%
1 1
 
1.1%
15 1
 
1.1%
10 1
 
1.1%
16 1
 
1.1%
18 1
 
1.1%
ValueCountFrequency (%)
1 1
 
1.1%
2 68
73.1%
3 11
 
11.8%
4 3
 
3.2%
5 2
 
2.2%
10 1
 
1.1%
12 3
 
3.2%
15 1
 
1.1%
16 1
 
1.1%
18 1
 
1.1%
ValueCountFrequency (%)
21 1
 
1.1%
18 1
 
1.1%
16 1
 
1.1%
15 1
 
1.1%
12 3
 
3.2%
10 1
 
1.1%
5 2
 
2.2%
4 3
 
3.2%
3 11
 
11.8%
2 68
73.1%

Interactions

2023-12-12T15:17:20.449149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:19.746341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:20.118111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:20.549075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:19.871944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:20.235533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:20.656737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:19.991537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:20.330588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:17:25.394510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종등록번호측량업체명개인_법인대표자 수임원 수기술자 수장비 수
업종1.0001.0000.0000.4060.0000.2160.8950.733
등록번호1.0001.0001.0001.0001.0001.0001.0001.000
측량업체명0.0001.0001.0001.0001.0001.0000.0000.000
개인_법인0.4061.0001.0001.0000.0910.3670.7660.202
대표자 수0.0001.0001.0000.0911.0000.2970.0000.000
임원 수0.2161.0001.0000.3670.2971.0000.2770.000
기술자 수0.8951.0000.0000.7660.0000.2771.0000.941
장비 수0.7331.0000.0000.2020.0000.0000.9411.000
2023-12-12T15:17:25.543521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개인_법인업종대표자 수
개인_법인1.0000.6350.057
업종0.6351.0000.000
대표자 수0.0570.0001.000
2023-12-12T15:17:25.661382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
임원 수기술자 수장비 수업종개인_법인대표자 수
임원 수1.0000.4050.1710.1620.4400.356
기술자 수0.4051.0000.5550.8510.5700.000
장비 수0.1710.5551.0000.5780.2040.000
업종0.1620.8510.5781.0000.6350.000
개인_법인0.4400.5700.2040.6351.0000.057
대표자 수0.3560.0000.0000.0000.0571.000

Missing values

2023-12-12T15:17:20.826758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:17:21.325542image/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

등록기관시도_시군구업종등록번호측량업체명영업여부개인_법인본점_지점대표자 수임원 수기술자 수장비 수
0지자체인천광역시지적측량02-000427웅창토지개발 주식회사영업법인본점1062
1지자체인천광역시일반측량04-005383웅창토지개발 주식회사영업법인본점1022
2지자체인천광역시일반측량04-005370유씨아이테크 주식회사영업개인본점1022
3지자체인천광역시일반측량04-005354임측량토목설계사무소영업개인본점2022
4지자체인천광역시공공측량03-001477주식회사 동서이엔지영업법인본점1162
5지자체인천광역시일반측량04-005316(주)성우엔지니어링종합건축사사무소영업법인본점1022
6지자체인천광역시공공측량03-001456(주)아이맵영업법인본점1024
7지자체인천광역시일반측량04-005221비성하이테크(주)영업법인본점1022
8지자체인천광역시일반측량04-005172세움ENG영업개인본점1022
9지자체인천광역시일반측량04-005111(주)스마트항만영업법인본점1022
등록기관시도_시군구업종등록번호측량업체명영업여부개인_법인본점_지점대표자 수임원 수기술자 수장비 수
83지자체인천광역시일반측량04-000099강화측량설계공사영업개인본점1022
84지자체인천광역시일반측량04-000100한양측량토목설계공사영업개인본점1022
85지자체인천광역시일반측량04-000105미래엔지니어링영업개인본점1042
86지자체인천광역시일반측량04-000830광명측량설계공사영업개인본점1022
87지자체인천광역시일반측량04-000834토지엔지니어링영업개인본점1022
88지자체인천광역시공공측량03-000030(주)고산엔지니어링영업법인본점1063
89지자체인천광역시지적측량02-000032지오서베이주식회사영업법인본점12612
90지자체인천광역시공공측량03-000425(주)서해기술단영업법인본점11362
91지자체인천광역시일반측량04-000900주식회사경원지적엔지니어링영업법인본점1222
92지자체인천광역시일반측량04-000842명지공간개발(주)영업법인본점1022