Overview

Dataset statistics

Number of variables8
Number of observations60
Missing cells8
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory68.2 B

Variable types

Categorical3
Text3
Numeric2

Dataset

Description부산광역시 수영구 환경오염 배출시설 현황 데이터로 사업장명, 시도명, 시군구명, 업종, 주소, 전화번호 등 정보를 제공하고 있다.
Author부산광역시 수영구
URLhttps://www.data.go.kr/data/15026062/fileData.do

Alerts

구군명 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
업종 is highly overall correlated with 구군명 and 1 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 구군명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 구군명 and 1 other fieldsHigh correlation
구군명 is highly imbalanced (87.8%)Imbalance
데이터기준일자 is highly imbalanced (87.8%)Imbalance
업체명 has 1 (1.7%) missing valuesMissing
도로명주소 has 1 (1.7%) missing valuesMissing
전화번호 has 4 (6.7%) missing valuesMissing
위도 has 1 (1.7%) missing valuesMissing
경도 has 1 (1.7%) missing valuesMissing

Reproduction

Analysis started2023-12-11 22:50:50.426945
Analysis finished2023-12-11 22:50:51.312697
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구군명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
수영구
59 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0166667
Min length3

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
수영구 59
98.3%
<NA> 1
 
1.7%

Length

2023-12-12T07:50:51.365651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:50:51.450566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수영구 59
98.3%
na 1
 
1.7%

업체명
Text

MISSING 

Distinct59
Distinct (%)100.0%
Missing1
Missing (%)1.7%
Memory size612.0 B
2023-12-12T07:50:51.622617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length8.7457627
Min length3

Characters and Unicode

Total characters516
Distinct characters151
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)100.0%

Sample

1st row의법선우의료재단 비에이치에스한서병원
2nd row용화여객자동차㈜
3rd row오성여객㈜
4th row금륜산업㈜
5th row미광운수㈜
ValueCountFrequency (%)
입주자대표회의 2
 
2.4%
좋은강안병원 2
 
2.4%
부산점 2
 
2.4%
의료법인 2
 
2.4%
의법선우의료재단 1
 
1.2%
부산방송총국 1
 
1.2%
광안해수월드점 1
 
1.2%
㈜더스토리컴퍼니 1
 
1.2%
호메르스호텔㈜ 1
 
1.2%
암센터 1
 
1.2%
Other values (68) 68
82.9%
2023-12-12T07:50:51.943668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 25
 
4.8%
24
 
4.7%
스 17
 
3.3%
차 14
 
2.7%
산 13
 
2.5%
비 12
 
2.3%
의 10
 
1.9%
터 10
 
1.9%
주 9
 
1.7%
유 9
 
1.7%
Other values (141) 373
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 457
88.6%
Other Symbol 25
 
4.8%
Space Separator 24
 
4.7%
Uppercase Letter 6
 
1.2%
Decimal Number 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 17
 
3.7%
차 14
 
3.1%
산 13
 
2.8%
비 12
 
2.6%
의 10
 
2.2%
터 10
 
2.2%
주 9
 
2.0%
유 9
 
2.0%
모 9
 
2.0%
세 9
 
2.0%
Other values (131) 345
75.5%
Uppercase Letter
ValueCountFrequency (%)
J 2
33.3%
D 1
16.7%
S 1
16.7%
N 1
16.7%
E 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
2 1
25.0%
Other Symbol
ValueCountFrequency (%)
㈜ 25
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 482
93.4%
Common 28
 
5.4%
Latin 6
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 25
 
5.2%
스 17
 
3.5%
차 14
 
2.9%
산 13
 
2.7%
비 12
 
2.5%
의 10
 
2.1%
터 10
 
2.1%
주 9
 
1.9%
유 9
 
1.9%
모 9
 
1.9%
Other values (132) 354
73.4%
Latin
ValueCountFrequency (%)
J 2
33.3%
D 1
16.7%
S 1
16.7%
N 1
16.7%
E 1
16.7%
Common
ValueCountFrequency (%)
24
85.7%
1 2
 
7.1%
3 1
 
3.6%
2 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 457
88.6%
ASCII 34
 
6.6%
None 25
 
4.8%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 25
100.0%
ASCII
ValueCountFrequency (%)
24
70.6%
1 2
 
5.9%
J 2
 
5.9%
3 1
 
2.9%
D 1
 
2.9%
2 1
 
2.9%
S 1
 
2.9%
N 1
 
2.9%
E 1
 
2.9%
Hangul
ValueCountFrequency (%)
스 17
 
3.7%
차 14
 
3.1%
산 13
 
2.8%
비 12
 
2.6%
의 10
 
2.2%
터 10
 
2.2%
주 9
 
2.0%
유 9
 
2.0%
모 9
 
2.0%
세 9
 
2.0%
Other values (131) 345
75.5%

도로명주소
Text

MISSING 

Distinct58
Distinct (%)98.3%
Missing1
Missing (%)1.7%
Memory size612.0 B
2023-12-12T07:50:52.146555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length23.915254
Min length21

Characters and Unicode

Total characters1411
Distinct characters44
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

Unique57 ?
Unique (%)96.6%

Sample

1st row부산광역시 수영구 수영로 615 (광안동)
2nd row부산광역시 수영구 민락본동로19번길 51 (민락동)
3rd row부산광역시 수영구 민락본동로31번길 33 (민락동)
4th row부산광역시 수영구 구락로 28 (수영동)
5th row부산광역시 수영구 구락로 22 (수영동)
ValueCountFrequency (%)
부산광역시 59
20.5%
수영구 57
19.8%
광안동 21
 
7.3%
수영로 13
 
4.5%
망미동 12
 
4.2%
광남로 10
 
3.5%
민락동 9
 
3.1%
남천동 8
 
2.8%
구락로 4
 
1.4%
수영동 4
 
1.4%
Other values (76) 91
31.6%
2023-12-12T07:50:52.661831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229
16.2%
광 96
 
6.8%
수 88
 
6.2%
영 84
 
6.0%
동 62
 
4.4%
구 62
 
4.4%
산 59
 
4.2%
로 59
 
4.2%
부 59
 
4.2%
역 59
 
4.2%
Other values (34) 554
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 878
62.2%
Space Separator 229
 
16.2%
Decimal Number 185
 
13.1%
Open Punctuation 58
 
4.1%
Close Punctuation 58
 
4.1%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 96
10.9%
수 88
10.0%
영 84
9.6%
동 62
 
7.1%
구 62
 
7.1%
산 59
 
6.7%
로 59
 
6.7%
부 59
 
6.7%
역 59
 
6.7%
시 59
 
6.7%
Other values (20) 191
21.8%
Decimal Number
ValueCountFrequency (%)
1 37
20.0%
3 26
14.1%
2 23
12.4%
4 22
11.9%
7 19
10.3%
5 18
9.7%
0 13
 
7.0%
9 9
 
4.9%
8 9
 
4.9%
6 9
 
4.9%
Space Separator
ValueCountFrequency (%)
229
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 878
62.2%
Common 533
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 96
10.9%
수 88
10.0%
영 84
9.6%
동 62
 
7.1%
구 62
 
7.1%
산 59
 
6.7%
로 59
 
6.7%
부 59
 
6.7%
역 59
 
6.7%
시 59
 
6.7%
Other values (20) 191
21.8%
Common
ValueCountFrequency (%)
229
43.0%
( 58
 
10.9%
) 58
 
10.9%
1 37
 
6.9%
3 26
 
4.9%
2 23
 
4.3%
4 22
 
4.1%
7 19
 
3.6%
5 18
 
3.4%
0 13
 
2.4%
Other values (4) 30
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 878
62.2%
ASCII 533
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229
43.0%
( 58
 
10.9%
) 58
 
10.9%
1 37
 
6.9%
3 26
 
4.9%
2 23
 
4.3%
4 22
 
4.1%
7 19
 
3.6%
5 18
 
3.4%
0 13
 
2.4%
Other values (4) 30
 
5.6%
Hangul
ValueCountFrequency (%)
광 96
10.9%
수 88
10.0%
영 84
9.6%
동 62
 
7.1%
구 62
 
7.1%
산 59
 
6.7%
로 59
 
6.7%
부 59
 
6.7%
역 59
 
6.7%
시 59
 
6.7%
Other values (20) 191
21.8%

업종
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
세차
23 
운수및수선업
10 
자동차수리업
7 
병원
5 
부동산관리업
3 
Other values (12)
12 

Length

Max length12
Median length11
Mean length4.2333333
Min length2

Unique

Unique12 ?
Unique (%)20.0%

Sample

1st row병원
2nd row세차
3rd row세차
4th row운수및수선업
5th row운수및수선업

Common Values

ValueCountFrequency (%)
세차 23
38.3%
운수및수선업 10
16.7%
자동차수리업 7
 
11.7%
병원 5
 
8.3%
부동산관리업 3
 
5.0%
호텔업 1
 
1.7%
세탁업 1
 
1.7%
자동차 종합 수리업 1
 
1.7%
그외 기타 가구제조업 1
 
1.7%
간판 및 광고물 제조업 1
 
1.7%
Other values (7) 7
 
11.7%

Length

2023-12-12T07:50:52.773306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
세차 23
33.3%
운수및수선업 10
14.5%
자동차수리업 7
 
10.1%
병원 5
 
7.2%
부동산관리업 3
 
4.3%
및 2
 
2.9%
광고물 1
 
1.4%
욕탕업 1
 
1.4%
자동차세차업 1
 
1.4%
소매업 1
 
1.4%
Other values (15) 15
21.7%

전화번호
Text

MISSING 

Distinct56
Distinct (%)100.0%
Missing4
Missing (%)6.7%
Memory size612.0 B
2023-12-12T07:50:52.962263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.946429
Min length9

Characters and Unicode

Total characters669
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

Unique56 ?
Unique (%)100.0%

Sample

1st row051-756-0081
2nd row051-753-1138
3rd row051-753-2801
4th row051-752-6001
5th row051-752-5001
ValueCountFrequency (%)
051-753-1138 1
 
1.8%
051-753-2801 1
 
1.8%
051-753-0360 1
 
1.8%
051-754-0009 1
 
1.8%
051-755-4976 1
 
1.8%
051-753-8283 1
 
1.8%
051-751-0488 1
 
1.8%
051-625-2233 1
 
1.8%
051-327-7301 1
 
1.8%
051-757-9000 1
 
1.8%
Other values (46) 46
82.1%
2023-12-12T07:50:53.263090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 129
19.3%
- 111
16.6%
0 109
16.3%
1 89
13.3%
7 67
10.0%
2 40
 
6.0%
8 34
 
5.1%
6 26
 
3.9%
3 25
 
3.7%
9 25
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 558
83.4%
Dash Punctuation 111
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 129
23.1%
0 109
19.5%
1 89
15.9%
7 67
12.0%
2 40
 
7.2%
8 34
 
6.1%
6 26
 
4.7%
3 25
 
4.5%
9 25
 
4.5%
4 14
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 669
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 129
19.3%
- 111
16.6%
0 109
16.3%
1 89
13.3%
7 67
10.0%
2 40
 
6.0%
8 34
 
5.1%
6 26
 
3.9%
3 25
 
3.7%
9 25
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 129
19.3%
- 111
16.6%
0 109
16.3%
1 89
13.3%
7 67
10.0%
2 40
 
6.0%
8 34
 
5.1%
6 26
 
3.9%
3 25
 
3.7%
9 25
 
3.7%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct59
Distinct (%)100.0%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean35.161129
Minimum35.13852
Maximum35.184893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T07:50:53.378575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.13852
5-th percentile35.143721
Q135.153596
median35.159219
Q335.170286
95-th percentile35.179167
Maximum35.184893
Range0.04637259
Interquartile range (IQR)0.01668978

Descriptive statistics

Standard deviation0.011347486
Coefficient of variation (CV)0.00032272814
Kurtosis-0.68243599
Mean35.161129
Median Absolute Deviation (MAD)0.0093796
Skewness0.26122609
Sum2074.5066
Variance0.00012876543
MonotonicityNot monotonic
2023-12-12T07:50:53.487177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.16104695 1
 
1.7%
35.15759886 1
 
1.7%
35.15203452 1
 
1.7%
35.17746377 1
 
1.7%
35.18489255 1
 
1.7%
35.15692948 1
 
1.7%
35.14983892 1
 
1.7%
35.15376661 1
 
1.7%
35.16872455 1
 
1.7%
35.17393198 1
 
1.7%
Other values (49) 49
81.7%
ValueCountFrequency (%)
35.13851996 1
1.7%
35.14343383 1
1.7%
35.1434371 1
1.7%
35.14375211 1
1.7%
35.14450116 1
1.7%
35.14480577 1
1.7%
35.14866024 1
1.7%
35.14969018 1
1.7%
35.14977737 1
1.7%
35.14983892 1
1.7%
ValueCountFrequency (%)
35.18489255 1
1.7%
35.18398813 1
1.7%
35.18324591 1
1.7%
35.17871403 1
1.7%
35.17850374 1
1.7%
35.17746377 1
1.7%
35.17692698 1
1.7%
35.17445013 1
1.7%
35.17393198 1
1.7%
35.17355785 1
1.7%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct59
Distinct (%)100.0%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean129.11582
Minimum129.09693
Maximum129.13356
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T07:50:53.591065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.09693
5-th percentile129.1068
Q1129.11158
median129.11584
Q3129.11961
95-th percentile129.12701
Maximum129.13356
Range0.0366269
Interquartile range (IQR)0.0080354

Descriptive statistics

Standard deviation0.0070552132
Coefficient of variation (CV)5.4642517 × 10-5
Kurtosis0.78227014
Mean129.11582
Median Absolute Deviation (MAD)0.004003
Skewness-0.084119242
Sum7617.8332
Variance4.9776033 × 10-5
MonotonicityNot monotonic
2023-12-12T07:50:53.715734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.1128819 1
 
1.7%
129.1264027 1
 
1.7%
129.1162117 1
 
1.7%
129.1160181 1
 
1.7%
129.1158434 1
 
1.7%
129.1133738 1
 
1.7%
129.1113133 1
 
1.7%
129.1167694 1
 
1.7%
129.112429 1
 
1.7%
129.1195836 1
 
1.7%
Other values (49) 49
81.7%
ValueCountFrequency (%)
129.0969295 1
1.7%
129.0986104 1
1.7%
129.1008267 1
1.7%
129.1074595 1
1.7%
129.1075946 1
1.7%
129.108102 1
1.7%
129.1096433 1
1.7%
129.1097892 1
1.7%
129.1097929 1
1.7%
129.1098008 1
1.7%
ValueCountFrequency (%)
129.1335564 1
1.7%
129.1287745 1
1.7%
129.128505 1
1.7%
129.1268409 1
1.7%
129.1265075 1
1.7%
129.1264027 1
1.7%
129.1260699 1
1.7%
129.1260542 1
1.7%
129.1237207 1
1.7%
129.1209372 1
1.7%

데이터기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-01-25
59 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.9
Min length4

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st row2023-01-25
2nd row2023-01-25
3rd row2023-01-25
4th row2023-01-25
5th row2023-01-25

Common Values

ValueCountFrequency (%)
2023-01-25 59
98.3%
<NA> 1
 
1.7%

Length

2023-12-12T07:50:53.829206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:50:53.917268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-25 59
98.3%
na 1
 
1.7%

Interactions

2023-12-12T07:50:50.884957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:50:50.743953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:50:50.951488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:50:50.805954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:50:54.019607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명도로명주소업종전화번호위도경도
업체명1.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.000
업종1.0001.0001.0001.0000.5260.788
전화번호1.0001.0001.0001.0001.0001.000
위도1.0001.0000.5261.0001.0000.648
경도1.0001.0000.7881.0000.6481.000
2023-12-12T07:50:54.111151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구군명업종데이터기준일자
구군명1.0001.0001.000
업종1.0001.0001.000
데이터기준일자1.0001.0001.000
2023-12-12T07:50:54.199380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도구군명업종데이터기준일자
위도1.0000.2111.0000.2101.000
경도0.2111.0001.0000.4331.000
구군명1.0001.0001.0001.0001.000
업종0.2100.4331.0001.0001.000
데이터기준일자1.0001.0001.0001.0001.000

Missing values

2023-12-12T07:50:51.050300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:50:51.143403image/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.
2023-12-12T07:50:51.239400image/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

구군명업체명도로명주소업종전화번호위도경도데이터기준일자
0수영구의법선우의료재단 비에이치에스한서병원부산광역시 수영구 수영로 615 (광안동)병원051-756-008135.161047129.1128822023-01-25
1수영구용화여객자동차㈜부산광역시 수영구 민락본동로19번길 51 (민락동)세차051-753-113835.157599129.1264032023-01-25
2수영구오성여객㈜부산광역시 수영구 민락본동로31번길 33 (민락동)세차051-753-280135.158835129.1268412023-01-25
3수영구금륜산업㈜부산광역시 수영구 구락로 28 (수영동)운수및수선업051-752-600135.170891129.1205542023-01-25
4수영구미광운수㈜부산광역시 수영구 구락로 22 (수영동)운수및수선업051-752-500135.169789129.1199142023-01-25
5수영구미광택시㈜부산광역시 수영구 구락로 134 (망미동)세차051-755-511135.178714129.1163842023-01-25
6수영구광미산업사부산광역시 수영구 좌수영로83번길 12 (수영동)세탁업051-752-870035.172055129.1208192023-01-25
7수영구세일석유㈜ 광안리주유소부산광역시 수영구 광남로 83 (광안동)세차051-754-979935.14969129.1136622023-01-25
8수영구청송세차장부산광역시 수영구 망미번영로38번길 79 (광안동)세차051-759-270035.168618129.112612023-01-25
9수영구㈜세왕에너지부산광역시 수영구 광남로 176 (민락동)세차051-755-818835.156538129.1196412023-01-25
구군명업체명도로명주소업종전화번호위도경도데이터기준일자
50수영구주식회사 갓차부산광역시 수영구 감포로 11 (광안동)세차051-753-575835.159452129.1204482023-01-25
51수영구타워더모스트 관리사무소부산광역시 수영구 민락수변로17번길 36건물임대업?051-752-188835.154222129.126072023-01-25
52수영구수영구 국민체육센터부산광역시 수영구 수영로521번길 77 (광안동)교육서비스업051-711-234035.152938129.107462023-01-25
53수영구㈜코스트코 코리아 부산점부산광역시 수영구 구락로 137 (망미동)도매 및 소매업<NA>35.178504129.1152622023-01-25
54수영구마이오토링크㈜부산광역시 수영구 광남로 4-2 (남천동)운수및수선업1600-522235.143434129.1097932023-01-25
55수영구남천뉴비치아파트 입주자대표회의부산광역시 수영구 광안해변로15번길 68(남천동)부동산관리업051-622-372535.13852129.1099352023-01-25
56수영구망미삼성아파트부산광역시 망미로30번길 23(망미동)부동산관리업051-758-215735.16861129.1008272023-01-25
57수영구삼익비치타운 입주자대표회의부산광역시 수영구 광안해변로 100(남천동)부동산관리업051-622-597535.143752129.1153722023-01-25
58수영구광안리세차부산광역시 광안해변로307번길 50(민락동)자동차세차업<NA>35.159202129.1260542023-01-25
59<NA><NA><NA><NA><NA><NA><NA><NA>