Overview

Dataset statistics

Number of variables9
Number of observations118
Missing cells41
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory75.1 B

Variable types

Numeric2
Text5
DateTime2

Dataset

Description2022년 11월 23일 기준의 보은군 전문건설업에 대한 데이터로 상호, 대표자, 업체등록일자, 주소 등의 항목을 제공합니다. ## LINK 미리보기 [![미리보기](http://curate.gimi9.com/linkview/www-data-go-kr-data-filedata-15054581?url=https%3A//www.boeun.go.kr/www/selectBbsNttView.do%3Fkey%3D772%26bbsNo%3D199%26nttNo%3D151785&version=d7)](https://www.data.go.kr/data/15054581/fileData.do)
Author충청북도 보은군
URLhttps://www.data.go.kr/data/15054581/fileData.do

Alerts

데이터기준일 has constant value ""Constant
사업자등록번호 has 41 (34.7%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:57:58.959233
Analysis finished2023-12-12 02:58:00.876365
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct118
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.5
Minimum1
Maximum118
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T11:58:01.027747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.85
Q130.25
median59.5
Q388.75
95-th percentile112.15
Maximum118
Range117
Interquartile range (IQR)58.5

Descriptive statistics

Standard deviation34.207699
Coefficient of variation (CV)0.57491931
Kurtosis-1.2
Mean59.5
Median Absolute Deviation (MAD)29.5
Skewness0
Sum7021
Variance1170.1667
MonotonicityStrictly increasing
2023-12-12T11:58:01.277883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
76 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
82 1
 
0.8%
81 1
 
0.8%
Other values (108) 108
91.5%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%
111 1
0.8%
110 1
0.8%
109 1
0.8%

상호
Text

UNIQUE 

Distinct118
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T11:58:01.707521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length7.279661
Min length4

Characters and Unicode

Total characters859
Distinct characters141
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)100.0%

Sample

1st row(유)금강개발
2nd row(주)가온건설
3rd row(주)고당
4th row(주)나인건설
5th row(주)남산이엔씨
ValueCountFrequency (%)
유)금강개발 1
 
0.8%
동양기업(주 1
 
0.8%
우일철물설비 1
 
0.8%
아주건설주식회사 1
 
0.8%
세종엔주식회사 1
 
0.8%
서진엔지니어링(주 1
 
0.8%
서광건설주식회사 1
 
0.8%
삼성가스 1
 
0.8%
부일건설(주 1
 
0.8%
보은에너지 1
 
0.8%
Other values (108) 108
91.5%
2023-12-12T11:58:02.359341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 83
 
9.7%
83
 
9.7%
) 83
 
9.7%
66
 
7.7%
64
 
7.5%
20
 
2.3%
16
 
1.9%
15
 
1.7%
15
 
1.7%
14
 
1.6%
Other values (131) 400
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 688
80.1%
Open Punctuation 83
 
9.7%
Close Punctuation 83
 
9.7%
Decimal Number 4
 
0.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
83
 
12.1%
66
 
9.6%
64
 
9.3%
20
 
2.9%
16
 
2.3%
15
 
2.2%
15
 
2.2%
14
 
2.0%
13
 
1.9%
12
 
1.7%
Other values (125) 370
53.8%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
1 1
25.0%
4 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 688
80.1%
Common 171
 
19.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
83
 
12.1%
66
 
9.6%
64
 
9.3%
20
 
2.9%
16
 
2.3%
15
 
2.2%
15
 
2.2%
14
 
2.0%
13
 
1.9%
12
 
1.7%
Other values (125) 370
53.8%
Common
ValueCountFrequency (%)
( 83
48.5%
) 83
48.5%
0 2
 
1.2%
/ 1
 
0.6%
1 1
 
0.6%
4 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 688
80.1%
ASCII 171
 
19.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 83
48.5%
) 83
48.5%
0 2
 
1.2%
/ 1
 
0.6%
1 1
 
0.6%
4 1
 
0.6%
Hangul
ValueCountFrequency (%)
83
 
12.1%
66
 
9.6%
64
 
9.3%
20
 
2.9%
16
 
2.3%
15
 
2.2%
15
 
2.2%
14
 
2.0%
13
 
1.9%
12
 
1.7%
Other values (125) 370
53.8%

대표자
Text

UNIQUE 

Distinct118
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T11:58:02.688528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length3
Mean length3.3559322
Min length2

Characters and Unicode

Total characters396
Distinct characters108
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

Unique118 ?
Unique (%)100.0%

Sample

1st row권운섭
2nd row김은미
3rd row노은영
4th row정호범
5th row음창진
ValueCountFrequency (%)
권운섭 1
 
0.8%
이영주+유성모 1
 
0.8%
이철우 1
 
0.8%
김민지 1
 
0.8%
이금선 1
 
0.8%
김준기 1
 
0.8%
김은희 1
 
0.8%
한유신 1
 
0.8%
박영수 1
 
0.8%
허복 1
 
0.8%
Other values (108) 108
91.5%
2023-12-12T11:58:03.158657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
10.6%
22
 
5.6%
19
 
4.8%
16
 
4.0%
+ 11
 
2.8%
8
 
2.0%
8
 
2.0%
7
 
1.8%
7
 
1.8%
7
 
1.8%
Other values (98) 249
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 385
97.2%
Math Symbol 11
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
42
 
10.9%
22
 
5.7%
19
 
4.9%
16
 
4.2%
8
 
2.1%
8
 
2.1%
7
 
1.8%
7
 
1.8%
7
 
1.8%
6
 
1.6%
Other values (97) 243
63.1%
Math Symbol
ValueCountFrequency (%)
+ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 385
97.2%
Common 11
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
42
 
10.9%
22
 
5.7%
19
 
4.9%
16
 
4.2%
8
 
2.1%
8
 
2.1%
7
 
1.8%
7
 
1.8%
7
 
1.8%
6
 
1.6%
Other values (97) 243
63.1%
Common
ValueCountFrequency (%)
+ 11
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 385
97.2%
ASCII 11
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
42
 
10.9%
22
 
5.7%
19
 
4.9%
16
 
4.2%
8
 
2.1%
8
 
2.1%
7
 
1.8%
7
 
1.8%
7
 
1.8%
6
 
1.6%
Other values (97) 243
63.1%
ASCII
ValueCountFrequency (%)
+ 11
100.0%
Distinct109
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1976-11-10 00:00:00
Maximum2022-08-26 00:00:00
2023-12-12T11:58:03.353592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:58:03.539969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct43
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28935.771
Minimum28900
Maximum28965
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T11:58:03.759030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28900
5-th percentile28902.85
Q128924
median28941.5
Q328948
95-th percentile28954
Maximum28965
Range65
Interquartile range (IQR)24

Descriptive statistics

Standard deviation15.649151
Coefficient of variation (CV)0.00054082369
Kurtosis-0.40002284
Mean28935.771
Median Absolute Deviation (MAD)9.5
Skewness-0.67204672
Sum3414421
Variance244.89591
MonotonicityNot monotonic
2023-12-12T11:58:03.962958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
28942 11
 
9.3%
28951 8
 
6.8%
28943 7
 
5.9%
28948 6
 
5.1%
28953 6
 
5.1%
28935 6
 
5.1%
28929 5
 
4.2%
28952 4
 
3.4%
28923 4
 
3.4%
28900 4
 
3.4%
Other values (33) 57
48.3%
ValueCountFrequency (%)
28900 4
3.4%
28902 2
1.7%
28903 1
 
0.8%
28905 1
 
0.8%
28908 1
 
0.8%
28910 1
 
0.8%
28911 1
 
0.8%
28912 1
 
0.8%
28914 1
 
0.8%
28916 3
2.5%
ValueCountFrequency (%)
28965 1
 
0.8%
28961 1
 
0.8%
28957 1
 
0.8%
28956 1
 
0.8%
28954 3
 
2.5%
28953 6
5.1%
28952 4
3.4%
28951 8
6.8%
28950 1
 
0.8%
28949 2
 
1.7%
Distinct106
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T11:58:04.465135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length21.644068
Min length17

Characters and Unicode

Total characters2554
Distinct characters97
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)81.4%

Sample

1st row충청북도 보은군 보은읍 장신3길 9
2nd row충청북도 보은군 탄부면 숫돌길 70
3rd row충청북도 보은군 회인면 회인로 21
4th row충청북도 보은군 보은읍 보은로 144
5th row충청북도 보은군 보은읍 삼산로3길 7-1
ValueCountFrequency (%)
보은군 118
19.4%
충청북도 114
18.7%
보은읍 79
 
13.0%
보은로 16
 
2.6%
보청대로 12
 
2.0%
삼승면 9
 
1.5%
남부로 8
 
1.3%
2층 7
 
1.1%
교사삼산길 7
 
1.1%
수한면 7
 
1.1%
Other values (145) 232
38.1%
2023-12-12T11:58:05.205274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
491
19.2%
229
 
9.0%
220
 
8.6%
126
 
4.9%
125
 
4.9%
118
 
4.6%
118
 
4.6%
114
 
4.5%
1 92
 
3.6%
86
 
3.4%
Other values (87) 835
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1633
63.9%
Space Separator 491
 
19.2%
Decimal Number 393
 
15.4%
Dash Punctuation 35
 
1.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
229
14.0%
220
13.5%
126
 
7.7%
125
 
7.7%
118
 
7.2%
118
 
7.2%
114
 
7.0%
86
 
5.3%
79
 
4.8%
44
 
2.7%
Other values (73) 374
22.9%
Decimal Number
ValueCountFrequency (%)
1 92
23.4%
2 58
14.8%
4 40
10.2%
3 38
9.7%
8 31
 
7.9%
6 31
 
7.9%
0 31
 
7.9%
9 27
 
6.9%
7 23
 
5.9%
5 22
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
491
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1633
63.9%
Common 921
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
229
14.0%
220
13.5%
126
 
7.7%
125
 
7.7%
118
 
7.2%
118
 
7.2%
114
 
7.0%
86
 
5.3%
79
 
4.8%
44
 
2.7%
Other values (73) 374
22.9%
Common
ValueCountFrequency (%)
491
53.3%
1 92
 
10.0%
2 58
 
6.3%
4 40
 
4.3%
3 38
 
4.1%
- 35
 
3.8%
8 31
 
3.4%
6 31
 
3.4%
0 31
 
3.4%
9 27
 
2.9%
Other values (4) 47
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1633
63.9%
ASCII 920
36.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
491
53.4%
1 92
 
10.0%
2 58
 
6.3%
4 40
 
4.3%
3 38
 
4.1%
- 35
 
3.8%
8 31
 
3.4%
6 31
 
3.4%
0 31
 
3.4%
9 27
 
2.9%
Other values (3) 46
 
5.0%
Hangul
ValueCountFrequency (%)
229
14.0%
220
13.5%
126
 
7.7%
125
 
7.7%
118
 
7.2%
118
 
7.2%
114
 
7.0%
86
 
5.3%
79
 
4.8%
44
 
2.7%
Other values (73) 374
22.9%
None
ValueCountFrequency (%)
1
100.0%
Distinct109
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T11:58:05.503549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.008475
Min length11

Characters and Unicode

Total characters1417
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

Unique100 ?
Unique (%)84.7%

Sample

1st row043-543-3182
2nd row043-542-8655
3rd row043-543-8798
4th row043-542-0030
5th row070-8625-2700
ValueCountFrequency (%)
00-000-0000 2
 
1.7%
043-542-0938 2
 
1.7%
043-543-0575 2
 
1.7%
043-543-9662 2
 
1.7%
043-542-5998 2
 
1.7%
043-543-6100 2
 
1.7%
043-542-0030 2
 
1.7%
043-542-9995 2
 
1.7%
043-543-8321 2
 
1.7%
043-543-0484 1
 
0.8%
Other values (99) 99
83.9%
2023-12-12T11:58:06.031218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 255
18.0%
- 236
16.7%
0 216
15.2%
3 202
14.3%
5 144
10.2%
2 98
 
6.9%
8 67
 
4.7%
1 62
 
4.4%
9 50
 
3.5%
7 44
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1181
83.3%
Dash Punctuation 236
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 255
21.6%
0 216
18.3%
3 202
17.1%
5 144
12.2%
2 98
 
8.3%
8 67
 
5.7%
1 62
 
5.2%
9 50
 
4.2%
7 44
 
3.7%
6 43
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 236
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1417
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 255
18.0%
- 236
16.7%
0 216
15.2%
3 202
14.3%
5 144
10.2%
2 98
 
6.9%
8 67
 
4.7%
1 62
 
4.4%
9 50
 
3.5%
7 44
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 255
18.0%
- 236
16.7%
0 216
15.2%
3 202
14.3%
5 144
10.2%
2 98
 
6.9%
8 67
 
4.7%
1 62
 
4.4%
9 50
 
3.5%
7 44
 
3.1%

사업자등록번호
Text

MISSING 

Distinct77
Distinct (%)100.0%
Missing41
Missing (%)34.7%
Memory size1.1 KiB
2023-12-12T11:58:06.412263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters924
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

Unique77 ?
Unique (%)100.0%

Sample

1st row317-81-25397
2nd row825-87-00021
3rd row888-88-02314
4th row119-86-62546
5th row302-81-08606
ValueCountFrequency (%)
302-81-18050 1
 
1.3%
192-88-02149 1
 
1.3%
302-81-11945 1
 
1.3%
302-10-27544 1
 
1.3%
315-02-96042 1
 
1.3%
307-88-01155 1
 
1.3%
275-86-01795 1
 
1.3%
302-09-44436 1
 
1.3%
302-02-74756 1
 
1.3%
301-81-38747 1
 
1.3%
Other values (67) 67
87.0%
2023-12-12T11:58:06.941595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 154
16.7%
1 127
13.7%
0 118
12.8%
8 105
11.4%
3 100
10.8%
2 95
10.3%
5 50
 
5.4%
4 47
 
5.1%
7 47
 
5.1%
9 41
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 770
83.3%
Dash Punctuation 154
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 127
16.5%
0 118
15.3%
8 105
13.6%
3 100
13.0%
2 95
12.3%
5 50
 
6.5%
4 47
 
6.1%
7 47
 
6.1%
9 41
 
5.3%
6 40
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 154
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 924
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 154
16.7%
1 127
13.7%
0 118
12.8%
8 105
11.4%
3 100
10.8%
2 95
10.3%
5 50
 
5.4%
4 47
 
5.1%
7 47
 
5.1%
9 41
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 924
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 154
16.7%
1 127
13.7%
0 118
12.8%
8 105
11.4%
3 100
10.8%
2 95
10.3%
5 50
 
5.4%
4 47
 
5.1%
7 47
 
5.1%
9 41
 
4.4%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2022-11-23 00:00:00
Maximum2022-11-23 00:00:00
2023-12-12T11:58:07.134402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:58:07.283782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T11:58:00.132292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:57:59.407087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:58:00.289168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:57:59.551682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:58:07.382806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호(도로명주소)사업자등록번호
연번1.0000.1611.000
우편번호(도로명주소)0.1611.0001.000
사업자등록번호1.0001.0001.000
2023-12-12T11:58:07.478247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호(도로명주소)
연번1.000-0.074
우편번호(도로명주소)-0.0741.000

Missing values

2023-12-12T11:58:00.549860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:58:00.781541image/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

연번상호대표자업체등록일자우편번호(도로명주소)영업소재지(도로명주소)전화번호사업자등록번호데이터기준일
01(유)금강개발권운섭1996-11-0528952충청북도 보은군 보은읍 장신3길 9043-543-3182<NA>2022-11-23
12(주)가온건설김은미2011-09-2928912충청북도 보은군 탄부면 숫돌길 70043-542-8655317-81-253972022-11-23
23(주)고당노은영2015-04-2228929충청북도 보은군 회인면 회인로 21043-543-8798825-87-000212022-11-23
34(주)나인건설정호범2004-03-2928942충청북도 보은군 보은읍 보은로 144043-542-0030<NA>2022-11-23
45(주)남산이엔씨음창진2022-01-0528949충청북도 보은군 보은읍 삼산로3길 7-1070-8625-2700888-88-023142022-11-23
56(주)대명콘스텍신영태2012-11-1328923충청북도 보은군 삼승면 남부로 380002-831-1560119-86-625462022-11-23
67(주)대성개발안순하1998-10-2328953충청북도 보은군 보은읍 보은로 69 사무소043-543-3183302-81-086062022-11-23
78(주)대화건설문영자2002-09-1328924충청북도 보은군 삼승면 원남로 109-1043-542-9995312-81-575402022-11-23
89(주)동하건설박선우2021-12-1328954충청북도 보은군 보은읍 보은로 10043-544-1888779-87-025372022-11-23
910(주)디에이치산업홍일한2017-02-1728952충청북도 보은군 보은읍 장신로 13031-881-4674126-86-656482022-11-23
연번상호대표자업체등록일자우편번호(도로명주소)영업소재지(도로명주소)전화번호사업자등록번호데이터기준일
108109푸른에너지/샛골가스김종식2009-08-1328924충청북도 보은군 삼승면 남부로 3715043-542-6491301-23-720232022-11-23
109110하나건축설비박창미2015-06-1028942충청북도 보은군 보은읍 동광길 22043-543-1638302-04-444832022-11-23
110111한림건설주식회사김주경2022-03-1428937충청북도 보은군 보은읍 뱃들3길 6 201호043-543-6100230-88-023442022-11-23
111112한양건설(주)김영춘2004-11-2328946충청북도 보은군 보은읍 장신3길 21043-544-6868<NA>2022-11-23
112113현광건설(주)한철환2002-03-0928951충청북도 보은군 보은읍 삼산남로 44043-544-5400<NA>2022-11-23
113114현대가스김송기1998-07-2728920충청북도 보은군 수한면 안내보은로 1197-22043-544-6575302-02-334922022-11-23
114115현대종합가스김진홍2017-01-2028938충청북도 보은군 보은읍 보청대로 1670043-543-8844598-22-004552022-11-23
115116형제설비정용길2000-03-3128950충북 보은군 보은읍 동편길 34043-543-8399<NA>2022-11-23
116117화신이앤지(주)권운태2011-03-1128946충청북도 보은군 보은읍 작은장신길 7-18 1층043-544-5657302-81-221942022-11-23
117118회인가스이범철2013-06-0328928충청북도 보은군 회인면 애곡로1길 68-1200-000-0000302-10-337452022-11-23