Overview

Dataset statistics

Number of variables8
Number of observations385
Missing cells7
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.6 KiB
Average record size in memory65.3 B

Variable types

Numeric1
Categorical1
DateTime1
Text5

Dataset

Description충청남도 도내 일반 및 공공측량업체 289개소의 등록현황(업종, 업등록일, 상호, 대표자, 전화번호, 주소) 제공
Author충청남도
URLhttps://www.data.go.kr/data/15047452/fileData.do

Alerts

연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
사무소전화번호 has 7 (1.8%) missing valuesMissing
연번 has unique valuesUnique
업등록번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:45:56.073539
Analysis finished2024-03-14 20:45:57.713120
Duration1.64 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct385
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean193
Minimum1
Maximum385
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-03-15T05:45:57.862114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.2
Q197
median193
Q3289
95-th percentile365.8
Maximum385
Range384
Interquartile range (IQR)192

Descriptive statistics

Standard deviation111.28417
Coefficient of variation (CV)0.57660192
Kurtosis-1.2
Mean193
Median Absolute Deviation (MAD)96
Skewness0
Sum74305
Variance12384.167
MonotonicityStrictly increasing
2024-03-15T05:45:58.157930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
290 1
 
0.3%
264 1
 
0.3%
263 1
 
0.3%
262 1
 
0.3%
261 1
 
0.3%
260 1
 
0.3%
259 1
 
0.3%
258 1
 
0.3%
257 1
 
0.3%
Other values (375) 375
97.4%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
385 1
0.3%
384 1
0.3%
383 1
0.3%
382 1
0.3%
381 1
0.3%
380 1
0.3%
379 1
0.3%
378 1
0.3%
377 1
0.3%
376 1
0.3%

업종
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
일반측량
311 
공공측량
74 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반측량 311
80.8%
공공측량 74
 
19.2%

Length

2024-03-15T05:45:58.806834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:45:59.053484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반측량 311
80.8%
공공측량 74
 
19.2%

업등록일
Date

Distinct346
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum1976-03-19 00:00:00
Maximum2024-01-16 00:00:00
2024-03-15T05:45:59.247857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:45:59.660484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업등록번호
Text

UNIQUE 

Distinct385
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-03-15T05:46:01.100463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters3465
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

Unique385 ?
Unique (%)100.0%

Sample

1st row03-001528
2nd row03-001525
3rd row03-001519
4th row03-001516
5th row03-001505
ValueCountFrequency (%)
03-001528 1
 
0.3%
04-003731 1
 
0.3%
04-000246 1
 
0.3%
04-000294 1
 
0.3%
04-002429 1
 
0.3%
04-002428 1
 
0.3%
04-000161 1
 
0.3%
04-000214 1
 
0.3%
04-000181 1
 
0.3%
04-000253 1
 
0.3%
Other values (375) 375
97.4%
2024-03-15T05:46:02.972101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1407
40.6%
4 511
 
14.7%
- 385
 
11.1%
3 249
 
7.2%
1 203
 
5.9%
2 192
 
5.5%
5 142
 
4.1%
6 102
 
2.9%
9 97
 
2.8%
8 93
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3080
88.9%
Dash Punctuation 385
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1407
45.7%
4 511
 
16.6%
3 249
 
8.1%
1 203
 
6.6%
2 192
 
6.2%
5 142
 
4.6%
6 102
 
3.3%
9 97
 
3.1%
8 93
 
3.0%
7 84
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 385
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3465
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1407
40.6%
4 511
 
14.7%
- 385
 
11.1%
3 249
 
7.2%
1 203
 
5.9%
2 192
 
5.5%
5 142
 
4.1%
6 102
 
2.9%
9 97
 
2.8%
8 93
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3465
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1407
40.6%
4 511
 
14.7%
- 385
 
11.1%
3 249
 
7.2%
1 203
 
5.9%
2 192
 
5.5%
5 142
 
4.1%
6 102
 
2.9%
9 97
 
2.8%
8 93
 
2.7%

상호
Text

Distinct376
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-03-15T05:46:03.827982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length9.225974
Min length4

Characters and Unicode

Total characters3552
Distinct characters210
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique368 ?
Unique (%)95.6%

Sample

1st row주은이엔지 주식회사
2nd row주식회사 플랜이엔씨
3rd row주식회사 혜원
4th row주식회사 더수이앤씨
5th row(주)우정이엔씨
ValueCountFrequency (%)
주식회사 56
 
12.3%
중앙측량설계사무소 3
 
0.7%
유한회사 3
 
0.7%
토목설계 2
 
0.4%
메타지아이에스 2
 
0.4%
바른측량설계사무소 2
 
0.4%
주)명성엔지니어링 2
 
0.4%
주은이엔지 2
 
0.4%
대한측량설계공사 2
 
0.4%
한빛엔지니어링(주 2
 
0.4%
Other values (375) 378
83.3%
2024-03-15T05:46:04.932003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 239
 
6.7%
설 205
 
5.8%
측 200
 
5.6%
량 200
 
5.6%
계 200
 
5.6%
주 170
 
4.8%
지 115
 
3.2%
( 114
 
3.2%
) 114
 
3.2%
소 106
 
3.0%
Other values (200) 1889
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3232
91.0%
Open Punctuation 114
 
3.2%
Close Punctuation 114
 
3.2%
Space Separator 70
 
2.0%
Uppercase Letter 14
 
0.4%
Other Punctuation 6
 
0.2%
Other Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 239
 
7.4%
설 205
 
6.3%
측 200
 
6.2%
량 200
 
6.2%
계 200
 
6.2%
주 170
 
5.3%
지 115
 
3.6%
소 106
 
3.3%
무 103
 
3.2%
토 103
 
3.2%
Other values (189) 1591
49.2%
Uppercase Letter
ValueCountFrequency (%)
E 5
35.7%
N 4
28.6%
G 4
28.6%
C 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 4
66.7%
& 1
 
16.7%
· 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 114
100.0%
Space Separator
ValueCountFrequency (%)
70
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3234
91.0%
Common 304
 
8.6%
Latin 14
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 239
 
7.4%
설 205
 
6.3%
측 200
 
6.2%
량 200
 
6.2%
계 200
 
6.2%
주 170
 
5.3%
지 115
 
3.6%
소 106
 
3.3%
무 103
 
3.2%
토 103
 
3.2%
Other values (190) 1593
49.3%
Common
ValueCountFrequency (%)
( 114
37.5%
) 114
37.5%
70
23.0%
. 4
 
1.3%
& 1
 
0.3%
· 1
 
0.3%
Latin
ValueCountFrequency (%)
E 5
35.7%
N 4
28.6%
G 4
28.6%
C 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3232
91.0%
ASCII 317
 
8.9%
None 3
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 239
 
7.4%
설 205
 
6.3%
측 200
 
6.2%
량 200
 
6.2%
계 200
 
6.2%
주 170
 
5.3%
지 115
 
3.6%
소 106
 
3.3%
무 103
 
3.2%
토 103
 
3.2%
Other values (189) 1591
49.2%
ASCII
ValueCountFrequency (%)
( 114
36.0%
) 114
36.0%
70
22.1%
E 5
 
1.6%
. 4
 
1.3%
N 4
 
1.3%
G 4
 
1.3%
& 1
 
0.3%
C 1
 
0.3%
None
ValueCountFrequency (%)
㈜ 2
66.7%
· 1
33.3%

대표자명
Text

Distinct378
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-03-15T05:46:06.616794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9974026
Min length2

Characters and Unicode

Total characters1154
Distinct characters170
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique371 ?
Unique (%)96.4%

Sample

1st row송진영
2nd row천민승
3rd row이경구
4th row이수연
5th row한윤희
ValueCountFrequency (%)
송진영 2
 
0.5%
유수영 2
 
0.5%
이재우 2
 
0.5%
이형석 2
 
0.5%
조성희 2
 
0.5%
박상수 2
 
0.5%
김현수 2
 
0.5%
심진수 1
 
0.3%
최호식 1
 
0.3%
신경남 1
 
0.3%
Other values (368) 368
95.6%
2024-03-15T05:46:08.827531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 63
 
5.5%
이 60
 
5.2%
박 35
 
3.0%
영 34
 
2.9%
정 33
 
2.9%
수 28
 
2.4%
석 24
 
2.1%
현 23
 
2.0%
성 22
 
1.9%
종 22
 
1.9%
Other values (160) 810
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1153
99.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 63
 
5.5%
이 60
 
5.2%
박 35
 
3.0%
영 34
 
2.9%
정 33
 
2.9%
수 28
 
2.4%
석 24
 
2.1%
현 23
 
2.0%
성 22
 
1.9%
종 22
 
1.9%
Other values (159) 809
70.2%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1153
99.9%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 63
 
5.5%
이 60
 
5.2%
박 35
 
3.0%
영 34
 
2.9%
정 33
 
2.9%
수 28
 
2.4%
석 24
 
2.1%
현 23
 
2.0%
성 22
 
1.9%
종 22
 
1.9%
Other values (159) 809
70.2%
Common
ValueCountFrequency (%)
, 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1153
99.9%
ASCII 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 63
 
5.5%
이 60
 
5.2%
박 35
 
3.0%
영 34
 
2.9%
정 33
 
2.9%
수 28
 
2.4%
석 24
 
2.1%
현 23
 
2.0%
성 22
 
1.9%
종 22
 
1.9%
Other values (159) 809
70.2%
ASCII
ValueCountFrequency (%)
, 1
100.0%

사무소전화번호
Text

MISSING 

Distinct369
Distinct (%)97.6%
Missing7
Missing (%)1.8%
Memory size3.1 KiB
2024-03-15T05:46:09.990071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.039683
Min length11

Characters and Unicode

Total characters4551
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

Unique360 ?
Unique (%)95.2%

Sample

1st row041-332-1996
2nd row070-5030-5595
3rd row041-563-3315
4th row041-942-1187
5th row041-631-5700
ValueCountFrequency (%)
041-577-5211 2
 
0.5%
041-666-2807 2
 
0.5%
041-631-5700 2
 
0.5%
041-673-2011 2
 
0.5%
041-575-4797 2
 
0.5%
041-732-4874 2
 
0.5%
041-674-0166 2
 
0.5%
041-332-1996 2
 
0.5%
041-751-3887 2
 
0.5%
041-665-9811 1
 
0.3%
Other values (359) 359
95.0%
2024-03-15T05:46:11.671225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 756
16.6%
0 663
14.6%
4 601
13.2%
1 568
12.5%
5 430
9.4%
3 323
7.1%
6 285
 
6.3%
7 255
 
5.6%
2 247
 
5.4%
8 225
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3795
83.4%
Dash Punctuation 756
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 663
17.5%
4 601
15.8%
1 568
15.0%
5 430
11.3%
3 323
8.5%
6 285
7.5%
7 255
 
6.7%
2 247
 
6.5%
8 225
 
5.9%
9 198
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4551
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 756
16.6%
0 663
14.6%
4 601
13.2%
1 568
12.5%
5 430
9.4%
3 323
7.1%
6 285
 
6.3%
7 255
 
5.6%
2 247
 
5.4%
8 225
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 756
16.6%
0 663
14.6%
4 601
13.2%
1 568
12.5%
5 430
9.4%
3 323
7.1%
6 285
 
6.3%
7 255
 
5.6%
2 247
 
5.4%
8 225
 
4.9%

사무소도로명주소
Text

Distinct372
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-03-15T05:46:13.079478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length49
Mean length36.122078
Min length25

Characters and Unicode

Total characters13907
Distinct characters230
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique359 ?
Unique (%)93.2%

Sample

1st row충청남도 예산군 예산읍 예산로164번길 22, 102호 우)32440
2nd row충청남도 논산시 부창로 54-2 , 비동 (부창동) 우)32956
3rd row충청남도 천안시 동남구 청수14로 68 503호(청당동, 센터타워) 우)31198
4th row충청남도 청양군 청양읍 중앙로 66, 나동 101호 내 3호 우)33336
5th row충청남도 홍성군 홍성읍 대학길 25, 217호 우)32244
ValueCountFrequency (%)
충청남도 385
 
14.3%
천안시 79
 
2.9%
아산시 49
 
1.8%
47
 
1.7%
2층 46
 
1.7%
동남구 40
 
1.5%
당진시 39
 
1.5%
서북구 39
 
1.5%
온천동 38
 
1.4%
서산시 37
 
1.4%
Other values (726) 1889
70.3%
2024-03-15T05:46:14.915840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2811
20.2%
3 761
 
5.5%
1 738
 
5.3%
) 655
 
4.7%
2 523
 
3.8%
청 500
 
3.6%
남 436
 
3.1%
충 391
 
2.8%
우 390
 
2.8%
도 385
 
2.8%
Other values (220) 6317
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6219
44.7%
Decimal Number 3648
26.2%
Space Separator 2811
20.2%
Close Punctuation 655
 
4.7%
Open Punctuation 270
 
1.9%
Other Punctuation 220
 
1.6%
Dash Punctuation 78
 
0.6%
Uppercase Letter 3
 
< 0.1%
Letter Number 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 500
 
8.0%
남 436
 
7.0%
충 391
 
6.3%
우 390
 
6.3%
도 385
 
6.2%
동 362
 
5.8%
시 352
 
5.7%
로 287
 
4.6%
산 200
 
3.2%
천 177
 
2.8%
Other values (201) 2739
44.0%
Decimal Number
ValueCountFrequency (%)
3 761
20.9%
1 738
20.2%
2 523
14.3%
4 357
9.8%
0 286
 
7.8%
5 244
 
6.7%
7 219
 
6.0%
8 177
 
4.9%
6 177
 
4.9%
9 166
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
2811
100.0%
Close Punctuation
ValueCountFrequency (%)
) 655
100.0%
Open Punctuation
ValueCountFrequency (%)
( 270
100.0%
Other Punctuation
ValueCountFrequency (%)
, 220
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7683
55.2%
Hangul 6219
44.7%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 500
 
8.0%
남 436
 
7.0%
충 391
 
6.3%
우 390
 
6.3%
도 385
 
6.2%
동 362
 
5.8%
시 352
 
5.7%
로 287
 
4.6%
산 200
 
3.2%
천 177
 
2.8%
Other values (201) 2739
44.0%
Common
ValueCountFrequency (%)
2811
36.6%
3 761
 
9.9%
1 738
 
9.6%
) 655
 
8.5%
2 523
 
6.8%
4 357
 
4.6%
0 286
 
3.7%
( 270
 
3.5%
5 244
 
3.2%
, 220
 
2.9%
Other values (6) 818
 
10.6%
Latin
ValueCountFrequency (%)
A 2
40.0%
Ⅱ 2
40.0%
C 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7686
55.3%
Hangul 6219
44.7%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2811
36.6%
3 761
 
9.9%
1 738
 
9.6%
) 655
 
8.5%
2 523
 
6.8%
4 357
 
4.6%
0 286
 
3.7%
( 270
 
3.5%
5 244
 
3.2%
, 220
 
2.9%
Other values (8) 821
 
10.7%
Hangul
ValueCountFrequency (%)
청 500
 
8.0%
남 436
 
7.0%
충 391
 
6.3%
우 390
 
6.3%
도 385
 
6.2%
동 362
 
5.8%
시 352
 
5.7%
로 287
 
4.6%
산 200
 
3.2%
천 177
 
2.8%
Other values (201) 2739
44.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

Interactions

2024-03-15T05:45:56.736893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:46:15.116953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.999
업종0.9991.000
2024-03-15T05:46:15.341670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.966
업종0.9661.000

Missing values

2024-03-15T05:45:57.118932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:45:57.541871image/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

연번업종업등록일업등록번호상호대표자명사무소전화번호사무소도로명주소
01공공측량2024-01-1103-001528주은이엔지 주식회사송진영041-332-1996충청남도 예산군 예산읍 예산로164번길 22, 102호 우)32440
12공공측량2023-12-2803-001525주식회사 플랜이엔씨천민승070-5030-5595충청남도 논산시 부창로 54-2 , 비동 (부창동) 우)32956
23공공측량2023-11-1003-001519주식회사 혜원이경구041-563-3315충청남도 천안시 동남구 청수14로 68 503호(청당동, 센터타워) 우)31198
34공공측량2023-10-1703-001516주식회사 더수이앤씨이수연041-942-1187충청남도 청양군 청양읍 중앙로 66, 나동 101호 내 3호 우)33336
45공공측량2023-08-2303-001505(주)우정이엔씨한윤희041-631-5700충청남도 홍성군 홍성읍 대학길 25, 217호 우)32244
56공공측량2023-07-2503-001495주식회사 에스에이치엔지니어링이각희041-834-2017충청남도 예산군 예산읍 아리랑로 236 , 2층 우)32434
67공공측량2023-07-2103-001494(주)수엔지니어링김재숙041-576-9593충청남도 천안시 동남구 풍세로 769-33, 302호 (신방동) 우)31203
78공공측량2023-05-1803-001481백제엔지니어링(주)박경록041-563-9593충청남도 천안시 동남구 차돌고개2길 8 (다가동) 우)31154
89공공측량2023-04-1103-001475주식회사 다우박미영042-824-0608충청남도 천안시 서북구 검은들3길 46 8층 803-2(817)호(불당동, 미래시티빌딩) 우)31163
910공공측량2023-03-3103-001473주식회사 화우이엔씨전선문070-8866-8842충청남도 천안시 서북구 미라15길 23 상가동 307-208호(쌍용동, 대우타워종합상가) 우)31155
연번업종업등록일업등록번호상호대표자명사무소전화번호사무소도로명주소
375376일반측량1995-05-1904-000207(자)공주측량설계공사이진상041-856-7004충청남도 공주시 제민천1길 19 (봉황동) 우)32551
376377일반측량1994-08-2704-000204부여측량설계사김덕태041-832-8254충청남도 부여군 부여읍 사비로 17, 1동 201호 우)33168
377378일반측량2007-01-1204-000300서천토목측량설계사정진석041-953-0386충청남도 서천군 서천읍 군사길 52-2 우)33645
378379일반측량1996-07-0904-000212(주)삼우엔지니어링조석형041-542-7879충청남도 아산시 번영로93번길 38 (온천동) 우)31508
379380일반측량1976-03-1904-000187합자회사 대한측량사신봉근041-832-8000충청남도 부여군 부여읍 계백로 261 우)33153
380381일반측량1982-12-2904-000183보령측량설계사무소한은숙041-935-6664충청남도 보령시 보령남로 34 (명천동) 우)33474
381382일반측량1978-08-1704-000186(합)광만측량설계공사백종철041-569-9033충청남도 천안시 동남구 옛시청길 9-1 (대흥동) 우)31129
382383일반측량2012-05-0704-002325한국측량설계공사유민수041-549-1252충청남도 아산시 번영로69번길 20-9 (온천동) 우)31508
383384일반측량2002-08-2904-000859대훈측량설계공사문광열042-585-1491충청남도 계룡시 장안로 43, 308호 (금암동) 우)32826
384385일반측량2007-03-2104-000110태성측량설계공사장기영041-734-9978충청남도 논산시 시민로194번길 21-9 (내동) 우)32989