Overview

Dataset statistics

Number of variables7
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory60.7 B

Variable types

Numeric3
Text3
Categorical1

Dataset

Description울산광역시 중구에 설치된 그늘막 설치현황 정보 입니다. 설치 장소 , 도로명주소, 위치, 경도 등의 데이터 목록을 포함하고 있습니다.
Author울산광역시 중구
URLhttps://www.data.go.kr/data/15038509/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:16:01.901639
Analysis finished2023-12-12 10:16:04.127773
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.5
Minimum1
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T19:16:04.234889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.85
Q120.25
median39.5
Q358.75
95-th percentile74.15
Maximum78
Range77
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation22.660538
Coefficient of variation (CV)0.57368452
Kurtosis-1.2
Mean39.5
Median Absolute Deviation (MAD)19.5
Skewness0
Sum3081
Variance513.5
MonotonicityStrictly increasing
2023-12-12T19:16:04.422645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
51 1
 
1.3%
58 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
50 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%

설치위치
Text

Distinct72
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T19:16:04.746686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length10.692308
Min length5

Characters and Unicode

Total characters834
Distinct characters192
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)85.9%

Sample

1st row학성공원사거리
2nd row학성공원사거리 주광인테리어 앞
3rd row복산성당 교통섬
4th row복산육거리 횡단보도
5th row반구사거리 교통섬
ValueCountFrequency (%)
앞 40
 
20.1%
내 10
 
5.0%
일원 9
 
4.5%
교통섬 5
 
2.5%
후문 4
 
2.0%
함월노인복지관 4
 
2.0%
맞은편 4
 
2.0%
횡단보도 4
 
2.0%
교차로 3
 
1.5%
입구 3
 
1.5%
Other values (96) 113
56.8%
2023-12-12T19:16:05.235556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
14.5%
앞 40
 
4.8%
사 22
 
2.6%
리 22
 
2.6%
거 20
 
2.4%
교 15
 
1.8%
( 15
 
1.8%
) 15
 
1.8%
원 13
 
1.6%
영 12
 
1.4%
Other values (182) 539
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 654
78.4%
Space Separator 121
 
14.5%
Decimal Number 20
 
2.4%
Open Punctuation 15
 
1.8%
Close Punctuation 15
 
1.8%
Uppercase Letter 8
 
1.0%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 40
 
6.1%
사 22
 
3.4%
리 22
 
3.4%
거 20
 
3.1%
교 15
 
2.3%
원 13
 
2.0%
영 12
 
1.8%
이 12
 
1.8%
산 12
 
1.8%
일 11
 
1.7%
Other values (165) 475
72.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
25.0%
F 1
12.5%
B 1
12.5%
T 1
12.5%
P 1
12.5%
A 1
12.5%
K 1
12.5%
Decimal Number
ValueCountFrequency (%)
1 7
35.0%
2 4
20.0%
0 4
20.0%
3 3
15.0%
6 1
 
5.0%
5 1
 
5.0%
Space Separator
ValueCountFrequency (%)
121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 654
78.4%
Common 172
 
20.6%
Latin 8
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 40
 
6.1%
사 22
 
3.4%
리 22
 
3.4%
거 20
 
3.1%
교 15
 
2.3%
원 13
 
2.0%
영 12
 
1.8%
이 12
 
1.8%
산 12
 
1.8%
일 11
 
1.7%
Other values (165) 475
72.6%
Common
ValueCountFrequency (%)
121
70.3%
( 15
 
8.7%
) 15
 
8.7%
1 7
 
4.1%
2 4
 
2.3%
0 4
 
2.3%
3 3
 
1.7%
6 1
 
0.6%
5 1
 
0.6%
? 1
 
0.6%
Latin
ValueCountFrequency (%)
C 2
25.0%
F 1
12.5%
B 1
12.5%
T 1
12.5%
P 1
12.5%
A 1
12.5%
K 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 654
78.4%
ASCII 180
 
21.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
67.2%
( 15
 
8.3%
) 15
 
8.3%
1 7
 
3.9%
2 4
 
2.2%
0 4
 
2.2%
3 3
 
1.7%
C 2
 
1.1%
6 1
 
0.6%
F 1
 
0.6%
Other values (7) 7
 
3.9%
Hangul
ValueCountFrequency (%)
앞 40
 
6.1%
사 22
 
3.4%
리 22
 
3.4%
거 20
 
3.1%
교 15
 
2.3%
원 13
 
2.0%
영 12
 
1.8%
이 12
 
1.8%
산 12
 
1.8%
일 11
 
1.7%
Other values (165) 475
72.6%

도로명 주소
Text

Distinct48
Distinct (%)61.5%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T19:16:05.480365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length19.858974
Min length1

Characters and Unicode

Total characters1549
Distinct characters114
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)51.3%

Sample

1st row
2nd row울산광역시 중구 학성로 239 (학성동)
3rd row
4th row
5th row울산광역시 중구 화합로 363 (반구동)
ValueCountFrequency (%)
울산광역시 58
18.4%
중구 58
18.4%
번영로 14
 
4.4%
남외동 10
 
3.2%
종가로 9
 
2.8%
반구동 8
 
2.5%
태화동 7
 
2.2%
서동 6
 
1.9%
유곡동 6
 
1.9%
종가3길 5
 
1.6%
Other values (90) 135
42.7%
2023-12-12T19:16:05.832622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
395
25.5%
구 68
 
4.4%
산 65
 
4.2%
시 61
 
3.9%
동 59
 
3.8%
( 58
 
3.7%
광 58
 
3.7%
역 58
 
3.7%
중 58
 
3.7%
울 58
 
3.7%
Other values (104) 611
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 851
54.9%
Space Separator 395
25.5%
Decimal Number 167
 
10.8%
Open Punctuation 58
 
3.7%
Close Punctuation 58
 
3.7%
Other Punctuation 11
 
0.7%
Uppercase Letter 8
 
0.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 68
 
8.0%
산 65
 
7.6%
시 61
 
7.2%
동 59
 
6.9%
광 58
 
6.8%
역 58
 
6.8%
중 58
 
6.8%
울 58
 
6.8%
로 44
 
5.2%
화 15
 
1.8%
Other values (82) 307
36.1%
Decimal Number
ValueCountFrequency (%)
3 30
18.0%
5 22
13.2%
2 19
11.4%
1 18
10.8%
4 18
10.8%
7 16
9.6%
8 13
7.8%
6 12
 
7.2%
0 11
 
6.6%
9 8
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
K 2
25.0%
C 2
25.0%
I 1
12.5%
P 1
12.5%
A 1
12.5%
R 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
' 1
 
9.1%
Space Separator
ValueCountFrequency (%)
395
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 851
54.9%
Common 690
44.5%
Latin 8
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 68
 
8.0%
산 65
 
7.6%
시 61
 
7.2%
동 59
 
6.9%
광 58
 
6.8%
역 58
 
6.8%
중 58
 
6.8%
울 58
 
6.8%
로 44
 
5.2%
화 15
 
1.8%
Other values (82) 307
36.1%
Common
ValueCountFrequency (%)
395
57.2%
( 58
 
8.4%
) 58
 
8.4%
3 30
 
4.3%
5 22
 
3.2%
2 19
 
2.8%
1 18
 
2.6%
4 18
 
2.6%
7 16
 
2.3%
8 13
 
1.9%
Other values (6) 43
 
6.2%
Latin
ValueCountFrequency (%)
K 2
25.0%
C 2
25.0%
I 1
12.5%
P 1
12.5%
A 1
12.5%
R 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 851
54.9%
ASCII 698
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
395
56.6%
( 58
 
8.3%
) 58
 
8.3%
3 30
 
4.3%
5 22
 
3.2%
2 19
 
2.7%
1 18
 
2.6%
4 18
 
2.6%
7 16
 
2.3%
8 13
 
1.9%
Other values (12) 51
 
7.3%
Hangul
ValueCountFrequency (%)
구 68
 
8.0%
산 65
 
7.6%
시 61
 
7.2%
동 59
 
6.9%
광 58
 
6.8%
역 58
 
6.8%
중 58
 
6.8%
울 58
 
6.8%
로 44
 
5.2%
화 15
 
1.8%
Other values (82) 307
36.1%

지번 주소
Text

Distinct68
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T19:16:06.065407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length18.538462
Min length16

Characters and Unicode

Total characters1446
Distinct characters41
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)78.2%

Sample

1st row울산광역시 중구 학성동 196-1
2nd row울산광역시 중구 학성동 60-1
3rd row울산광역시 중구 학성동 422-1
4th row울산광역시 중구 학성동 461-9
5th row울산광역시 중구 반구동 265-10
ValueCountFrequency (%)
울산광역시 78
24.9%
중구 78
24.9%
태화동 12
 
3.8%
남외동 11
 
3.5%
반구동 9
 
2.9%
유곡동 9
 
2.9%
서동 6
 
1.9%
장현동 5
 
1.6%
복산동 5
 
1.6%
우정동 4
 
1.3%
Other values (75) 96
30.7%
2023-12-12T19:16:06.457799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
313
21.6%
구 87
 
6.0%
산 86
 
5.9%
울 78
 
5.4%
광 78
 
5.4%
역 78
 
5.4%
시 78
 
5.4%
중 78
 
5.4%
동 78
 
5.4%
1 61
 
4.2%
Other values (31) 431
29.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 775
53.6%
Space Separator 313
21.6%
Decimal Number 299
 
20.7%
Dash Punctuation 59
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 87
11.2%
산 86
11.1%
울 78
10.1%
광 78
10.1%
역 78
10.1%
시 78
10.1%
중 78
10.1%
동 78
10.1%
남 14
 
1.8%
태 12
 
1.5%
Other values (19) 108
13.9%
Decimal Number
ValueCountFrequency (%)
1 61
20.4%
2 55
18.4%
6 38
12.7%
4 31
10.4%
0 24
 
8.0%
7 20
 
6.7%
5 20
 
6.7%
3 18
 
6.0%
8 17
 
5.7%
9 15
 
5.0%
Space Separator
ValueCountFrequency (%)
313
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 775
53.6%
Common 671
46.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 87
11.2%
산 86
11.1%
울 78
10.1%
광 78
10.1%
역 78
10.1%
시 78
10.1%
중 78
10.1%
동 78
10.1%
남 14
 
1.8%
태 12
 
1.5%
Other values (19) 108
13.9%
Common
ValueCountFrequency (%)
313
46.6%
1 61
 
9.1%
- 59
 
8.8%
2 55
 
8.2%
6 38
 
5.7%
4 31
 
4.6%
0 24
 
3.6%
7 20
 
3.0%
5 20
 
3.0%
3 18
 
2.7%
Other values (2) 32
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 775
53.6%
ASCII 671
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
313
46.6%
1 61
 
9.1%
- 59
 
8.8%
2 55
 
8.2%
6 38
 
5.7%
4 31
 
4.6%
0 24
 
3.6%
7 20
 
3.0%
5 20
 
3.0%
3 18
 
2.7%
Other values (2) 32
 
4.8%
Hangul
ValueCountFrequency (%)
구 87
11.2%
산 86
11.1%
울 78
10.1%
광 78
10.1%
역 78
10.1%
시 78
10.1%
중 78
10.1%
동 78
10.1%
남 14
 
1.8%
태 12
 
1.5%
Other values (19) 108
13.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.564115
Minimum35.552015
Maximum35.58907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T19:16:06.635548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.552015
5-th percentile35.552674
Q135.556426
median35.561215
Q335.568518
95-th percentile35.585341
Maximum35.58907
Range0.0370551
Interquartile range (IQR)0.012092775

Descriptive statistics

Standard deviation0.010155123
Coefficient of variation (CV)0.00028554409
Kurtosis0.28733871
Mean35.564115
Median Absolute Deviation (MAD)0.00537605
Skewness1.0953887
Sum2774.0009
Variance0.00010312652
MonotonicityNot monotonic
2023-12-12T19:16:06.803910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.55255 2
 
2.6%
35.55597 1
 
1.3%
35.5794281 1
 
1.3%
35.5685 1
 
1.3%
35.5683586 1
 
1.3%
35.5688342 1
 
1.3%
35.5692913 1
 
1.3%
35.5694499 1
 
1.3%
35.5681415 1
 
1.3%
35.55368 1
 
1.3%
Other values (67) 67
85.9%
ValueCountFrequency (%)
35.5520149 1
1.3%
35.5522382 1
1.3%
35.55255 2
2.6%
35.5526959 1
1.3%
35.5529161 1
1.3%
35.5529233 1
1.3%
35.5533859 1
1.3%
35.55348 1
1.3%
35.55368 1
1.3%
35.5539688 1
1.3%
ValueCountFrequency (%)
35.58907 1
1.3%
35.5885816 1
1.3%
35.587354 1
1.3%
35.5864755 1
1.3%
35.5851413 1
1.3%
35.5850975 1
1.3%
35.5846851 1
1.3%
35.5846103 1
1.3%
35.581519 1
1.3%
35.5808475 1
1.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.3239
Minimum129.27616
Maximum129.3493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T19:16:06.979580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.27616
5-th percentile129.28662
Q1129.30519
median129.33067
Q3129.34312
95-th percentile129.34613
Maximum129.3493
Range0.0731373
Interquartile range (IQR)0.03793905

Descriptive statistics

Standard deviation0.021081129
Coefficient of variation (CV)0.00016301031
Kurtosis-0.93390444
Mean129.3239
Median Absolute Deviation (MAD)0.0141248
Skewness-0.61902304
Sum10087.264
Variance0.00044441402
MonotonicityNot monotonic
2023-12-12T19:16:07.161729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.33013 2
 
2.6%
129.33727 1
 
1.3%
129.2783669 1
 
1.3%
129.3447876 1
 
1.3%
129.3438899 1
 
1.3%
129.3458991 1
 
1.3%
129.3457369 1
 
1.3%
129.3461388 1
 
1.3%
129.3432502 1
 
1.3%
129.28578 1
 
1.3%
Other values (67) 67
85.9%
ValueCountFrequency (%)
129.2761627 1
1.3%
129.2764618 1
1.3%
129.2783669 1
1.3%
129.28578 1
1.3%
129.2867681 1
1.3%
129.2930375 1
1.3%
129.2959026 1
1.3%
129.2965438 1
1.3%
129.2965484 1
1.3%
129.2965685 1
1.3%
ValueCountFrequency (%)
129.3493 1
1.3%
129.3484087 1
1.3%
129.3464619 1
1.3%
129.3461388 1
1.3%
129.34613 1
1.3%
129.3458991 1
1.3%
129.3457369 1
1.3%
129.34548 1
1.3%
129.3450216 1
1.3%
129.3448265 1
1.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-09-06
78 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-06
2nd row2023-09-06
3rd row2023-09-06
4th row2023-09-06
5th row2023-09-06

Common Values

ValueCountFrequency (%)
2023-09-06 78
100.0%

Length

2023-12-12T19:16:07.372346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:16:07.521235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-06 78
100.0%

Interactions

2023-12-12T19:16:03.419178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:16:02.647032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:16:03.020119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:16:03.579645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:16:02.750468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:16:03.144477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:16:03.724546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:16:02.883437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:16:03.285485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:16:07.626857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치위치도로명 주소지번 주소위도경도
연번1.0000.9770.8500.9830.6830.855
설치위치0.9771.0000.9990.9991.0000.854
도로명 주소0.8500.9991.0001.0000.9250.735
지번 주소0.9830.9991.0001.0001.0000.952
위도0.6831.0000.9251.0001.0000.501
경도0.8550.8540.7350.9520.5011.000
2023-12-12T19:16:07.770639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.5930.225
위도0.5931.0000.503
경도0.2250.5031.000

Missing values

2023-12-12T19:16:03.913347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:16:04.062635image/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

연번설치위치도로명 주소지번 주소위도경도데이터기준일자
01학성공원사거리울산광역시 중구 학성동 196-135.55597129.337272023-09-06
12학성공원사거리 주광인테리어 앞울산광역시 중구 학성로 239 (학성동)울산광역시 중구 학성동 60-135.556408129.3373272023-09-06
23복산성당 교통섬울산광역시 중구 학성동 422-135.558694129.3281682023-09-06
34복산육거리 횡단보도울산광역시 중구 학성동 461-935.55915129.327732023-09-06
45반구사거리 교통섬울산광역시 중구 화합로 363 (반구동)울산광역시 중구 반구동 265-1035.558301129.3410062023-09-06
56반구사거리 교통섬(스포츠재활센터 앞)울산광역시 중구 화합로 358 (반구동)울산광역시 중구 반구동 447-2235.558089129.3416452023-09-06
67반구시장(김밥천국) 앞울산광역시 중구 염포로 20 (반구동)울산광역시 중구 반구동 449-135.559288129.3438482023-09-06
78구철길사거리 교통섬울산광역시 중구 화합로 371 (반구동)울산광역시 중구 반구동 262-3035.55892129.3404892023-09-06
89반구어린이집 내울산광역시 중구 반구정4길 66 (반구동)울산광역시 중구 반구동 452-135.558693129.3450222023-09-06
910울산전업사 앞울산광역시 중구 화합로 353 (반구동)울산광역시 중구 반구동 446-335.55778129.340822023-09-06
연번설치위치도로명 주소지번 주소위도경도데이터기준일자
6869101동 종가로 상 횡단보도 앞울산광역시 중구 종가로 730 (장현동, 에일린의 뜰 2차 아파트)울산광역시 중구 장현동 17835.587354129.3434352023-09-06
6970KCC APT 201동 앞울산광역시 중구 종가로 668-10 (서동, 우정혁신도시 KCC스위첸)울산광역시 중구 서동 61335.58084129.339342023-09-06
7071우정 골드클래스울산광역시 중구 종가로 730 (장현동, 에일린의 뜰 2차 아파트)울산광역시 중구 장현동 19135.58907129.345482023-09-06
7172골드클래스 교차로 일원울산광역시 중구 종가17길 52 (서동)울산광역시 중구 서동 612-135.581519129.3400732023-09-06
7273황방산 입구울산광역시 중구 장현동 25135.585098129.3424572023-09-06
7374에일린의 뜰 2차 정문 일원울산광역시 중구 종가로 730 (장현동, 에일린의 뜰 2차 아파트)울산광역시 중구 장현동 19135.586475129.3431842023-09-06
7475외솔중 후문울산광역시 중구 종가로 710 (서동)울산광역시 중구 서동 62235.58461129.3435242023-09-06
7576복산사거리(삼성디지털플라자 앞)울산광역시 중구 번영로 483 (약사동)울산광역시 중구 약사동 666-2835.564428129.3359592023-09-06
7677약사동 래미안 단지 정문 앞울산광역시 중구 약사동 707-135.568979129.3358792023-09-06
7778학성여고 앞울산광역시 중구 약사동 707-435.566431129.3341812023-09-06