Overview

Dataset statistics

Number of variables8
Number of observations38
Missing cells2
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory69.5 B

Variable types

Text3
Categorical2
Numeric2
DateTime1

Dataset

Description대구광역시 북구 관내 소재 소음진동배출시설 현황(업소명, 소재지도로명주소, 전화번호, 지역구분 등) 정보를 제공합니다.
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15006283/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도High correlation
지역구분 is highly overall correlated with 위도High correlation
위도 has 1 (2.6%) missing valuesMissing
경도 has 1 (2.6%) missing valuesMissing
업소명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:56:07.807711
Analysis finished2024-04-06 08:56:09.954428
Duration2.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-04-06T17:56:10.199620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.1315789
Min length4

Characters and Unicode

Total characters195
Distinct characters79
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

Unique38 ?
Unique (%)100.0%

Sample

1st row청안도금
2nd row주식회사 화랑
3rd row일성직물
4th row우성산업
5th row중원산업
ValueCountFrequency (%)
주식회사 3
 
7.3%
청안도금 1
 
2.4%
한국유체기술 1
 
2.4%
주)대창냉동 1
 
2.4%
금성광학 1
 
2.4%
금화사출 1
 
2.4%
전진산업사 1
 
2.4%
제이와이플라테크 1
 
2.4%
우방하이테크 1
 
2.4%
하나정밀 1
 
2.4%
Other values (29) 29
70.7%
2024-04-06T17:56:10.902073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 11
 
5.6%
산 10
 
5.1%
성 9
 
4.6%
주 7
 
3.6%
이 7
 
3.6%
정 6
 
3.1%
사 6
 
3.1%
일 5
 
2.6%
테 5
 
2.6%
크 5
 
2.6%
Other values (69) 124
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
93.3%
Close Punctuation 4
 
2.1%
Open Punctuation 4
 
2.1%
Space Separator 3
 
1.5%
Other Symbol 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 11
 
6.0%
산 10
 
5.5%
성 9
 
4.9%
주 7
 
3.8%
이 7
 
3.8%
정 6
 
3.3%
사 6
 
3.3%
일 5
 
2.7%
테 5
 
2.7%
크 5
 
2.7%
Other values (65) 111
61.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 184
94.4%
Common 11
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 11
 
6.0%
산 10
 
5.4%
성 9
 
4.9%
주 7
 
3.8%
이 7
 
3.8%
정 6
 
3.3%
사 6
 
3.3%
일 5
 
2.7%
테 5
 
2.7%
크 5
 
2.7%
Other values (66) 113
61.4%
Common
ValueCountFrequency (%)
) 4
36.4%
( 4
36.4%
3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
93.3%
ASCII 11
 
5.6%
None 2
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 11
 
6.0%
산 10
 
5.5%
성 9
 
4.9%
주 7
 
3.8%
이 7
 
3.8%
정 6
 
3.3%
사 6
 
3.3%
일 5
 
2.7%
테 5
 
2.7%
크 5
 
2.7%
Other values (65) 111
61.0%
ASCII
ValueCountFrequency (%)
) 4
36.4%
( 4
36.4%
3
27.3%
None
ValueCountFrequency (%)
㈜ 2
100.0%

소재지도로명주소
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-04-06T17:56:11.420811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length29
Mean length25.421053
Min length21

Characters and Unicode

Total characters966
Distinct characters51
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

Unique38 ?
Unique (%)100.0%

Sample

1st row대구광역시 북구 침산남로7길 40 (침산동)
2nd row대구광역시 북구 검단공단로21길 54-42 (산격동)
3rd row대구광역시 북구 유통단지로3길 20 (산격동)
4th row대구광역시 북구 노원로39길 5 (침산동)
5th row대구광역시 북구 검단공단로21길 7 (검단동)
ValueCountFrequency (%)
대구광역시 38
20.8%
북구 38
20.8%
산격동 10
 
5.5%
침산동 9
 
4.9%
연암로42길 4
 
2.2%
검단공단로21길 4
 
2.2%
검단동 4
 
2.2%
노원로42길 3
 
1.6%
노원로 2
 
1.1%
오봉로 2
 
1.1%
Other values (61) 69
37.7%
2024-04-06T17:56:12.181304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
 
15.0%
구 76
 
7.9%
북 44
 
4.6%
동 43
 
4.5%
( 40
 
4.1%
) 39
 
4.0%
로 39
 
4.0%
1 38
 
3.9%
대 38
 
3.9%
시 38
 
3.9%
Other values (41) 426
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 567
58.7%
Decimal Number 160
 
16.6%
Space Separator 145
 
15.0%
Open Punctuation 40
 
4.1%
Close Punctuation 39
 
4.0%
Dash Punctuation 15
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 76
13.4%
북 44
 
7.8%
동 43
 
7.6%
로 39
 
6.9%
대 38
 
6.7%
시 38
 
6.7%
역 38
 
6.7%
광 38
 
6.7%
길 31
 
5.5%
단 27
 
4.8%
Other values (27) 155
27.3%
Decimal Number
ValueCountFrequency (%)
1 38
23.8%
2 36
22.5%
4 22
13.8%
6 12
 
7.5%
3 12
 
7.5%
5 11
 
6.9%
0 11
 
6.9%
7 10
 
6.2%
9 5
 
3.1%
8 3
 
1.9%
Space Separator
ValueCountFrequency (%)
145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 567
58.7%
Common 399
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 76
13.4%
북 44
 
7.8%
동 43
 
7.6%
로 39
 
6.9%
대 38
 
6.7%
시 38
 
6.7%
역 38
 
6.7%
광 38
 
6.7%
길 31
 
5.5%
단 27
 
4.8%
Other values (27) 155
27.3%
Common
ValueCountFrequency (%)
145
36.3%
( 40
 
10.0%
) 39
 
9.8%
1 38
 
9.5%
2 36
 
9.0%
4 22
 
5.5%
- 15
 
3.8%
6 12
 
3.0%
3 12
 
3.0%
5 11
 
2.8%
Other values (4) 29
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 567
58.7%
ASCII 399
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
36.3%
( 40
 
10.0%
) 39
 
9.8%
1 38
 
9.5%
2 36
 
9.0%
4 22
 
5.5%
- 15
 
3.8%
6 12
 
3.0%
3 12
 
3.0%
5 11
 
2.8%
Other values (4) 29
 
7.3%
Hangul
ValueCountFrequency (%)
구 76
13.4%
북 44
 
7.8%
동 43
 
7.6%
로 39
 
6.9%
대 38
 
6.7%
시 38
 
6.7%
역 38
 
6.7%
광 38
 
6.7%
길 31
 
5.5%
단 27
 
4.8%
Other values (27) 155
27.3%

전화번호
Text

Distinct36
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-04-06T17:56:12.901688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters456
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

Unique35 ?
Unique (%)92.1%

Sample

1st row053-352-2041
2nd row053-382-7711
3rd row053-382-7880
4th row053-358-7714
5th row053-383-6464
ValueCountFrequency (%)
000-000-0000 3
 
7.9%
053-954-4600 1
 
2.6%
053-356-4422 1
 
2.6%
053-352-8721 1
 
2.6%
053-351-3555 1
 
2.6%
053-358-2468 1
 
2.6%
053-353-6931 1
 
2.6%
053-383-9147 1
 
2.6%
053-382-4353 1
 
2.6%
053-352-2041 1
 
2.6%
Other values (26) 26
68.4%
2024-04-06T17:56:13.610404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 89
19.5%
0 78
17.1%
- 76
16.7%
5 66
14.5%
8 35
 
7.7%
2 21
 
4.6%
1 20
 
4.4%
7 20
 
4.4%
4 19
 
4.2%
9 16
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 380
83.3%
Dash Punctuation 76
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 89
23.4%
0 78
20.5%
5 66
17.4%
8 35
 
9.2%
2 21
 
5.5%
1 20
 
5.3%
7 20
 
5.3%
4 19
 
5.0%
9 16
 
4.2%
6 16
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 456
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 89
19.5%
0 78
17.1%
- 76
16.7%
5 66
14.5%
8 35
 
7.7%
2 21
 
4.6%
1 20
 
4.4%
7 20
 
4.4%
4 19
 
4.2%
9 16
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 89
19.5%
0 78
17.1%
- 76
16.7%
5 66
14.5%
8 35
 
7.7%
2 21
 
4.6%
1 20
 
4.4%
7 20
 
4.4%
4 19
 
4.2%
9 16
 
3.5%

소음진동
Categorical

Distinct5
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size436.0 B
소음
20 
소음허가
13 
소음진동
3 
소음진동허가
 
1
소음진동신고
 
1

Length

Max length6
Median length2
Mean length3.0526316
Min length2

Unique

Unique2 ?
Unique (%)5.3%

Sample

1st row소음허가
2nd row소음
3rd row소음
4th row소음
5th row소음

Common Values

ValueCountFrequency (%)
소음 20
52.6%
소음허가 13
34.2%
소음진동 3
 
7.9%
소음진동허가 1
 
2.6%
소음진동신고 1
 
2.6%

Length

2024-04-06T17:56:13.874305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:56:14.158612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소음 20
52.6%
소음허가 13
34.2%
소음진동 3
 
7.9%
소음진동허가 1
 
2.6%
소음진동신고 1
 
2.6%

지역구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size436.0 B
준공업
22 
준주거
13 
2종주거
 
1
자연녹지
 
1
일반주거
 
1

Length

Max length4
Median length3
Mean length3.0789474
Min length3

Unique

Unique3 ?
Unique (%)7.9%

Sample

1st row2종주거
2nd row준공업
3rd row준공업
4th row준공업
5th row준공업

Common Values

ValueCountFrequency (%)
준공업 22
57.9%
준주거 13
34.2%
2종주거 1
 
2.6%
자연녹지 1
 
2.6%
일반주거 1
 
2.6%

Length

2024-04-06T17:56:14.410691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:56:14.619269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
준공업 22
57.9%
준주거 13
34.2%
2종주거 1
 
2.6%
자연녹지 1
 
2.6%
일반주거 1
 
2.6%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct37
Distinct (%)100.0%
Missing1
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean35.903157
Minimum35.887526
Maximum35.926152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-04-06T17:56:14.918418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.887526
5-th percentile35.890762
Q135.895262
median35.902825
Q335.911894
95-th percentile35.91453
Maximum35.926152
Range0.03862582
Interquartile range (IQR)0.01663171

Descriptive statistics

Standard deviation0.0090557882
Coefficient of variation (CV)0.00025222819
Kurtosis-0.50349729
Mean35.903157
Median Absolute Deviation (MAD)0.0081273
Skewness0.30759222
Sum1328.4168
Variance8.20073 × 10-5
MonotonicityNot monotonic
2024-04-06T17:56:15.240434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
35.89194635 1
 
2.6%
35.90382808 1
 
2.6%
35.89781001 1
 
2.6%
35.89060402 1
 
2.6%
35.895874 1
 
2.6%
35.89185 1
 
2.6%
35.9126204 1
 
2.6%
35.89423192 1
 
2.6%
35.89556817 1
 
2.6%
35.89526211 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
35.887526 1
2.6%
35.89060402 1
2.6%
35.890801 1
2.6%
35.89185 1
2.6%
35.89194635 1
2.6%
35.89293126 1
2.6%
35.89423192 1
2.6%
35.89469733 1
2.6%
35.89503808 1
2.6%
35.89526211 1
2.6%
ValueCountFrequency (%)
35.92615182 1
2.6%
35.91596279 1
2.6%
35.91417165 1
2.6%
35.91376993 1
2.6%
35.913707 1
2.6%
35.91288487 1
2.6%
35.9126204 1
2.6%
35.91213721 1
2.6%
35.912109 1
2.6%
35.91189382 1
2.6%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct37
Distinct (%)100.0%
Missing1
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean128.59386
Minimum128.57215
Maximum128.61318
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-04-06T17:56:15.641749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.57215
5-th percentile128.57523
Q1128.58033
median128.59823
Q3128.60599
95-th percentile128.61196
Maximum128.61318
Range0.0410269
Interquartile range (IQR)0.0256562

Descriptive statistics

Standard deviation0.01355985
Coefficient of variation (CV)0.0001054471
Kurtosis-1.6033148
Mean128.59386
Median Absolute Deviation (MAD)0.0131195
Skewness-0.078080038
Sum4757.9729
Variance0.00018386953
MonotonicityNot monotonic
2024-04-06T17:56:15.933386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
128.5788713 1
 
2.6%
128.6003725 1
 
2.6%
128.5907559 1
 
2.6%
128.5787396 1
 
2.6%
128.582921 1
 
2.6%
128.575384 1
 
2.6%
128.6084163 1
 
2.6%
128.5721531 1
 
2.6%
128.5828966 1
 
2.6%
128.5828168 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
128.5721531 1
2.6%
128.5746139 1
2.6%
128.575384 1
2.6%
128.577061 1
2.6%
128.577551 1
2.6%
128.5787396 1
2.6%
128.5788713 1
2.6%
128.579495 1
2.6%
128.5802984 1
2.6%
128.5803314 1
2.6%
ValueCountFrequency (%)
128.61318 1
2.6%
128.6127684 1
2.6%
128.6117633 1
2.6%
128.611348 1
2.6%
128.6104807 1
2.6%
128.6094984 1
2.6%
128.6084163 1
2.6%
128.607809 1
2.6%
128.6071549 1
2.6%
128.6059876 1
2.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum2024-03-22 00:00:00
Maximum2024-03-22 00:00:00
2024-04-06T17:56:16.273327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:56:16.484004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-06T17:56:08.961294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:56:08.440659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:56:09.181196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:56:08.699442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:56:16.655883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지도로명주소전화번호소음진동지역구분위도경도
업소명1.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0000.9690.9710.8760.962
소음진동1.0001.0000.9691.0000.7510.6020.594
지역구분1.0001.0000.9710.7511.0000.9160.437
위도1.0001.0000.8760.6020.9161.0000.864
경도1.0001.0000.9620.5940.4370.8641.000
2024-04-06T17:56:16.943962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소음진동지역구분
소음진동1.0000.369
지역구분0.3691.000
2024-04-06T17:56:17.142445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도소음진동지역구분
위도1.0000.9310.3690.770
경도0.9311.0000.3060.262
소음진동0.3690.3061.0000.369
지역구분0.7700.2620.3691.000

Missing values

2024-04-06T17:56:09.383529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:56:09.626499image/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.
2024-04-06T17:56:09.863984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업소명소재지도로명주소전화번호소음진동지역구분위도경도데이터기준일자
0청안도금대구광역시 북구 침산남로7길 40 (침산동)053-352-2041소음허가2종주거35.891946128.5788712024-03-22
1주식회사 화랑대구광역시 북구 검단공단로21길 54-42 (산격동)053-382-7711소음준공업35.911894128.6059512024-03-22
2일성직물대구광역시 북구 유통단지로3길 20 (산격동)053-382-7880소음준공업35.906588128.6036622024-03-22
3우성산업대구광역시 북구 노원로39길 5 (침산동)053-358-7714소음준공업35.900445128.5808612024-03-22
4중원산업대구광역시 북구 검단공단로21길 7 (검단동)053-383-6464소음준공업35.91377128.6127682024-03-22
5제일정공대구광역시 북구 노원로 39길 11 (침산동)053-351-0886소음준공업35.90079128.5802982024-03-22
6청기와산업대구광역시 북구 검단북로 2-13외 1필지((검단북로2길 16-12)(산격동)053-381-9787소음준공업35.912885128.6078092024-03-22
7(주)보광산업대구광역시 북구 유통단지로3길 40 (산격동)053-384-0882소음준공업35.90746128.6039672024-03-22
8신흥산업(주)대구광역시 북구 검단북로11길 11 (검단동)053-380-2149소음자연녹지35.915963128.6104812024-03-22
9한울광학대구광역시 북구 오봉로 36-6 (노원동1가)000-000-0000소음허가준주거35.890801128.5775512024-03-22
업소명소재지도로명주소전화번호소음진동지역구분위도경도데이터기준일자
28에이스코팅대구광역시 북구 연암로42길 42-4 (산격동)053-356-4422소음진동신고준공업35.903828128.6003722024-03-22
29태정테크대구광역시 북구 노원로42길 57-6 (침산동)053-358-1596소음허가준주거35.895262128.5828172024-03-22
30성진분체대구광역시 북구 검단북로2길 24(산격동)053-359-2926소음진동준공업35.912137128.6094982024-03-22
31㈜엔유씨전자대구광역시 북구 노원로 280 (침산동)053-665-5030소음준주거35.900375128.590212024-03-22
32명신정공대구광역시 북구 연암로42길 17-1(산격동)053-351-7539소음준공업35.903055128.5982292024-03-22
33성신정밀대구광역시 북구 연암로42길 24-4(노원동3가)000-000-0000소음준공업35.902825128.5991682024-03-22
34대성산업대구광역시 북구 검단공단로21길 3 (검단동)053-384-3579소음준공업<NA><NA>2024-03-22
35송학산업대구광역시 북구 검단공단로17길 6(검단동)053-383-9144소음준공업35.913707128.613182024-03-22
36(주)대창냉동대구광역시 북구 신천동로 960(산격동)053-383-9908소음준공업35.902446128.5941672024-03-22
37대호도장대구광역시 북구 오봉로 156(침산동)053-357-8017소음준공업35.901678128.5794952024-03-22