Overview

Dataset statistics

Number of variables7
Number of observations8411
Missing cells8411
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory460.1 KiB
Average record size in memory56.0 B

Variable types

Text5
Categorical1
DateTime1

Dataset

Description2022-08-01기준으로 영주시 관내 무선원격 디지털수도미터기가 설치된 데이터로 현재 원격검침 중인 수용가 현황입니다.
Author경상북도 영주시
URLhttps://www.data.go.kr/data/15103098/fileData.do

Alerts

기준일자 has constant value ""Constant
소재지지번주소 has 8226 (97.8%) missing valuesMissing
소재지도로명주소 has 185 (2.2%) missing valuesMissing
무선원격수집기 번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:45:12.211132
Analysis finished2023-12-12 10:45:13.402117
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수용가번호(관리번호)
Text

Distinct8397
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size65.8 KiB
2023-12-12T19:45:13.551388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters126165
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

Unique8383 ?
Unique (%)99.7%

Sample

1st row113-080-0660-00
2nd row111-010-0071-00
3rd row111-010-0074-00
4th row116-060-0550-00
5th row114-010-0080-00
ValueCountFrequency (%)
310-210-0800-00 2
 
< 0.1%
310-210-0780-00 2
 
< 0.1%
310-210-0640-00 2
 
< 0.1%
310-210-0700-00 2
 
< 0.1%
310-210-0830-00 2
 
< 0.1%
310-210-1250-00 2
 
< 0.1%
310-210-0760-00 2
 
< 0.1%
310-210-0900-00 2
 
< 0.1%
310-210-1080-00 2
 
< 0.1%
310-210-0950-00 2
 
< 0.1%
Other values (8387) 8391
99.8%
2023-12-12T19:45:13.919224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44495
35.3%
- 25233
20.0%
2 15482
 
12.3%
3 11487
 
9.1%
1 9572
 
7.6%
5 5314
 
4.2%
4 4124
 
3.3%
7 2971
 
2.4%
6 2794
 
2.2%
9 2680
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100932
80.0%
Dash Punctuation 25233
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44495
44.1%
2 15482
 
15.3%
3 11487
 
11.4%
1 9572
 
9.5%
5 5314
 
5.3%
4 4124
 
4.1%
7 2971
 
2.9%
6 2794
 
2.8%
9 2680
 
2.7%
8 2013
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 25233
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 126165
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44495
35.3%
- 25233
20.0%
2 15482
 
12.3%
3 11487
 
9.1%
1 9572
 
7.6%
5 5314
 
4.2%
4 4124
 
3.3%
7 2971
 
2.4%
6 2794
 
2.2%
9 2680
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44495
35.3%
- 25233
20.0%
2 15482
 
12.3%
3 11487
 
9.1%
1 9572
 
7.6%
5 5314
 
4.2%
4 4124
 
3.3%
7 2971
 
2.4%
6 2794
 
2.2%
9 2680
 
2.1%

구역
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size65.8 KiB
풍기읍
1636 
부석면
1121 
순흥면
988 
안정면
968 
문수면
738 
Other values (16)
2960 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
풍기읍 1636
19.5%
부석면 1121
13.3%
순흥면 988
11.7%
안정면 968
11.5%
문수면 738
8.8%
이산면 708
8.4%
장수면 611
 
7.3%
봉현면 606
 
7.2%
단산면 419
 
5.0%
조암동 174
 
2.1%
Other values (11) 442
 
5.3%

Length

2023-12-12T19:45:14.112328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
풍기읍 1636
19.5%
부석면 1121
13.3%
순흥면 988
11.7%
안정면 968
11.5%
문수면 738
8.8%
이산면 708
8.4%
장수면 611
 
7.3%
봉현면 606
 
7.2%
단산면 419
 
5.0%
조암동 174
 
2.1%
Other values (11) 442
 
5.3%

소재지지번주소
Text

MISSING 

Distinct175
Distinct (%)94.6%
Missing8226
Missing (%)97.8%
Memory size65.8 KiB
2023-12-12T19:45:14.622914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length33
Mean length22.945946
Min length19

Characters and Unicode

Total characters4245
Distinct characters114
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)91.9%

Sample

1st row경상북도 영주시 단산면 구구리 322-2
2nd row경상북도 영주시 단산면 단곡리 570-18
3rd row경상북도 영주시 단산면 사천리 469-6
4th row경상북도 영주시 단산면 사천리 399-1
5th row경상북도 영주시 단산면 옥대리 163-4
ValueCountFrequency (%)
경상북도 187
18.9%
영주시 185
18.7%
문수면 38
 
3.8%
이산면 31
 
3.1%
장수면 31
 
3.1%
부석면 29
 
2.9%
안정면 29
 
2.9%
순흥면 29
 
2.9%
풍기읍 28
 
2.8%
소천리 13
 
1.3%
Other values (235) 389
39.3%
2023-12-12T19:45:15.356937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
869
20.5%
면 209
 
4.9%
상 189
 
4.5%
경 187
 
4.4%
도 187
 
4.4%
북 187
 
4.4%
리 186
 
4.4%
영 185
 
4.4%
주 185
 
4.4%
시 185
 
4.4%
Other values (104) 1676
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2614
61.6%
Space Separator 869
 
20.5%
Decimal Number 660
 
15.5%
Dash Punctuation 98
 
2.3%
Other Punctuation 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 209
 
8.0%
상 189
 
7.2%
경 187
 
7.2%
도 187
 
7.2%
북 187
 
7.2%
리 186
 
7.1%
영 185
 
7.1%
주 185
 
7.1%
시 185
 
7.1%
수 69
 
2.6%
Other values (89) 845
32.3%
Decimal Number
ValueCountFrequency (%)
1 111
16.8%
2 95
14.4%
3 70
10.6%
4 70
10.6%
9 67
10.2%
5 64
9.7%
7 61
9.2%
6 50
7.6%
8 37
 
5.6%
0 35
 
5.3%
Space Separator
ValueCountFrequency (%)
869
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2614
61.6%
Common 1631
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 209
 
8.0%
상 189
 
7.2%
경 187
 
7.2%
도 187
 
7.2%
북 187
 
7.2%
리 186
 
7.1%
영 185
 
7.1%
주 185
 
7.1%
시 185
 
7.1%
수 69
 
2.6%
Other values (89) 845
32.3%
Common
ValueCountFrequency (%)
869
53.3%
1 111
 
6.8%
- 98
 
6.0%
2 95
 
5.8%
3 70
 
4.3%
4 70
 
4.3%
9 67
 
4.1%
5 64
 
3.9%
7 61
 
3.7%
6 50
 
3.1%
Other values (5) 76
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2614
61.6%
ASCII 1631
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
869
53.3%
1 111
 
6.8%
- 98
 
6.0%
2 95
 
5.8%
3 70
 
4.3%
4 70
 
4.3%
9 67
 
4.1%
5 64
 
3.9%
7 61
 
3.7%
6 50
 
3.1%
Other values (5) 76
 
4.7%
Hangul
ValueCountFrequency (%)
면 209
 
8.0%
상 189
 
7.2%
경 187
 
7.2%
도 187
 
7.2%
북 187
 
7.2%
리 186
 
7.1%
영 185
 
7.1%
주 185
 
7.1%
시 185
 
7.1%
수 69
 
2.6%
Other values (89) 845
32.3%

소재지도로명주소
Text

MISSING 

Distinct7717
Distinct (%)93.8%
Missing185
Missing (%)2.2%
Memory size65.8 KiB
2023-12-12T19:45:16.013396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length24.044615
Min length14

Characters and Unicode

Total characters197791
Distinct characters303
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

Unique7484 ?
Unique (%)91.0%

Sample

1st row경상북도 영주시 가흥로357번길 31
2nd row경상북도 영주시 대동로103번길 41-1
3rd row경상북도 영주시 대동로103번길 31-14
4th row경상북도 영주시 신재로 129
5th row경상북도 영주시 고현로 52-2
ValueCountFrequency (%)
경상북도 8226
20.0%
영주시 8217
20.0%
풍기읍 1631
 
4.0%
부석면 1107
 
2.7%
순흥면 996
 
2.4%
안정면 968
 
2.4%
문수면 705
 
1.7%
이산면 683
 
1.7%
봉현면 601
 
1.5%
장수면 591
 
1.4%
Other values (4162) 17352
42.2%
2023-12-12T19:45:16.589999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38566
19.5%
주 8953
 
4.5%
영 8540
 
4.3%
상 8471
 
4.3%
경 8233
 
4.2%
북 8226
 
4.2%
도 8226
 
4.2%
시 8220
 
4.2%
로 7895
 
4.0%
1 7737
 
3.9%
Other values (293) 84724
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 116424
58.9%
Space Separator 38566
 
19.5%
Decimal Number 38278
 
19.4%
Dash Punctuation 4176
 
2.1%
Other Punctuation 240
 
0.1%
Open Punctuation 46
 
< 0.1%
Close Punctuation 46
 
< 0.1%
Uppercase Letter 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 8953
 
7.7%
영 8540
 
7.3%
상 8471
 
7.3%
경 8233
 
7.1%
북 8226
 
7.1%
도 8226
 
7.1%
시 8220
 
7.1%
로 7895
 
6.8%
면 6109
 
5.2%
길 4920
 
4.2%
Other values (269) 38631
33.2%
Decimal Number
ValueCountFrequency (%)
1 7737
20.2%
2 4949
12.9%
3 4611
12.0%
5 3471
9.1%
4 3463
9.0%
6 3352
8.8%
7 3058
 
8.0%
0 2795
 
7.3%
9 2610
 
6.8%
8 2232
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 5
33.3%
C 3
20.0%
B 2
 
13.3%
E 2
 
13.3%
G 1
 
6.7%
L 1
 
6.7%
D 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 235
97.9%
. 4
 
1.7%
& 1
 
0.4%
Space Separator
ValueCountFrequency (%)
38566
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 116424
58.9%
Common 81352
41.1%
Latin 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 8953
 
7.7%
영 8540
 
7.3%
상 8471
 
7.3%
경 8233
 
7.1%
북 8226
 
7.1%
도 8226
 
7.1%
시 8220
 
7.1%
로 7895
 
6.8%
면 6109
 
5.2%
길 4920
 
4.2%
Other values (269) 38631
33.2%
Common
ValueCountFrequency (%)
38566
47.4%
1 7737
 
9.5%
2 4949
 
6.1%
3 4611
 
5.7%
- 4176
 
5.1%
5 3471
 
4.3%
4 3463
 
4.3%
6 3352
 
4.1%
7 3058
 
3.8%
0 2795
 
3.4%
Other values (7) 5174
 
6.4%
Latin
ValueCountFrequency (%)
A 5
33.3%
C 3
20.0%
B 2
 
13.3%
E 2
 
13.3%
G 1
 
6.7%
L 1
 
6.7%
D 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 116424
58.9%
ASCII 81367
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38566
47.4%
1 7737
 
9.5%
2 4949
 
6.1%
3 4611
 
5.7%
- 4176
 
5.1%
5 3471
 
4.3%
4 3463
 
4.3%
6 3352
 
4.1%
7 3058
 
3.8%
0 2795
 
3.4%
Other values (14) 5189
 
6.4%
Hangul
ValueCountFrequency (%)
주 8953
 
7.7%
영 8540
 
7.3%
상 8471
 
7.3%
경 8233
 
7.1%
북 8226
 
7.1%
도 8226
 
7.1%
시 8220
 
7.1%
로 7895
 
6.8%
면 6109
 
5.2%
길 4920
 
4.2%
Other values (269) 38631
33.2%

전자식 수도미터 번호
Text

Distinct8375
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size65.8 KiB
2023-12-12T19:45:16.965145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.8763524
Min length9

Characters and Unicode

Total characters83070
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8339 ?
Unique (%)99.1%

Sample

1st row21-E320072
2nd row21-E011513
3rd row21-E011514
4th row21-E250510
5th row22-E010466
ValueCountFrequency (%)
22-e010944 2
 
< 0.1%
22-e010384 2
 
< 0.1%
22-e011327 2
 
< 0.1%
22-e011285 2
 
< 0.1%
22-e011679 2
 
< 0.1%
22-e011980 2
 
< 0.1%
22-e010180 2
 
< 0.1%
21-e000542 2
 
< 0.1%
22-e011284 2
 
< 0.1%
22-e012170 2
 
< 0.1%
Other values (8365) 8391
99.8%
2023-12-12T19:45:17.571548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 17053
20.5%
0 15757
19.0%
1 15136
18.2%
- 8409
10.1%
E 7367
8.9%
5 2734
 
3.3%
8 2729
 
3.3%
4 2721
 
3.3%
9 2607
 
3.1%
3 2592
 
3.1%
Other values (3) 5965
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66250
79.8%
Uppercase Letter 8411
 
10.1%
Dash Punctuation 8409
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 17053
25.7%
0 15757
23.8%
1 15136
22.8%
5 2734
 
4.1%
8 2729
 
4.1%
4 2721
 
4.1%
9 2607
 
3.9%
3 2592
 
3.9%
7 2486
 
3.8%
6 2435
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
E 7367
87.6%
D 1044
 
12.4%
Dash Punctuation
ValueCountFrequency (%)
- 8409
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74659
89.9%
Latin 8411
 
10.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 17053
22.8%
0 15757
21.1%
1 15136
20.3%
- 8409
11.3%
5 2734
 
3.7%
8 2729
 
3.7%
4 2721
 
3.6%
9 2607
 
3.5%
3 2592
 
3.5%
7 2486
 
3.3%
Latin
ValueCountFrequency (%)
E 7367
87.6%
D 1044
 
12.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 17053
20.5%
0 15757
19.0%
1 15136
18.2%
- 8409
10.1%
E 7367
8.9%
5 2734
 
3.3%
8 2729
 
3.3%
4 2721
 
3.3%
9 2607
 
3.1%
3 2592
 
3.1%
Other values (3) 5965
 
7.2%

무선원격수집기 번호
Text

UNIQUE 

Distinct8411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size65.8 KiB
2023-12-12T19:45:18.009167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.1240043
Min length7

Characters and Unicode

Total characters59920
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8411 ?
Unique (%)100.0%

Sample

1st rowP082361
2nd rowP082390
3rd rowP082386
4th rowP086563
5th rowP087746
ValueCountFrequency (%)
p082361 1
 
< 0.1%
p086416 1
 
< 0.1%
p086418 1
 
< 0.1%
p087218 1
 
< 0.1%
p087216 1
 
< 0.1%
p087193 1
 
< 0.1%
p087219 1
 
< 0.1%
p087191 1
 
< 0.1%
p087212 1
 
< 0.1%
p087201 1
 
< 0.1%
Other values (8401) 8401
99.9%
2023-12-12T19:45:18.593850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12730
21.2%
7 7516
12.5%
P 6280
10.5%
8 5346
8.9%
2 4693
 
7.8%
1 4559
 
7.6%
6 4358
 
7.3%
4 3604
 
6.0%
5 3542
 
5.9%
3 3172
 
5.3%
Other values (3) 4120
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52552
87.7%
Uppercase Letter 7368
 
12.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12730
24.2%
7 7516
14.3%
8 5346
10.2%
2 4693
 
8.9%
1 4559
 
8.7%
6 4358
 
8.3%
4 3604
 
6.9%
5 3542
 
6.7%
3 3172
 
6.0%
9 3032
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
P 6280
85.2%
F 1008
 
13.7%
U 80
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 52552
87.7%
Latin 7368
 
12.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12730
24.2%
7 7516
14.3%
8 5346
10.2%
2 4693
 
8.9%
1 4559
 
8.7%
6 4358
 
8.3%
4 3604
 
6.9%
5 3542
 
6.7%
3 3172
 
6.0%
9 3032
 
5.8%
Latin
ValueCountFrequency (%)
P 6280
85.2%
F 1008
 
13.7%
U 80
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12730
21.2%
7 7516
12.5%
P 6280
10.5%
8 5346
8.9%
2 4693
 
7.8%
1 4559
 
7.6%
6 4358
 
7.3%
4 3604
 
6.0%
5 3542
 
5.9%
3 3172
 
5.3%
Other values (3) 4120
 
6.9%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.8 KiB
Minimum2022-08-01 00:00:00
Maximum2022-08-01 00:00:00
2023-12-12T19:45:18.729959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:18.822947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2023-12-12T19:45:13.001015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:45:13.175296image/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.
2023-12-12T19:45:13.318976image/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

수용가번호(관리번호)구역소재지지번주소소재지도로명주소전자식 수도미터 번호무선원격수집기 번호기준일자
0113-080-0660-00가흥동<NA>경상북도 영주시 가흥로357번길 3121-E320072P0823612022-08-01
1111-010-0071-00가흥동<NA>경상북도 영주시 대동로103번길 41-121-E011513P0823902022-08-01
2111-010-0074-00가흥동<NA>경상북도 영주시 대동로103번길 31-1421-E011514P0823862022-08-01
3116-060-0550-00가흥동<NA>경상북도 영주시 신재로 12921-E250510P0865632022-08-01
4114-010-0080-00가흥동<NA>경상북도 영주시 고현로 52-222-E010466P0877462022-08-01
5114-010-0070-00가흥동<NA>경상북도 영주시 고현로 5222-E010477P0877422022-08-01
6114-010-0030-00가흥동<NA>경상북도 영주시 고현로 4822-E010469P0878762022-08-01
7114-010-0050-00가흥동<NA>경상북도 영주시 고현로 3722-E010470P0878562022-08-01
8114-010-0040-00가흥동<NA>경상북도 영주시 고현로 48-122-E010462P0878512022-08-01
9116-060-0430-00가흥동<NA>경상북도 영주시 가흥공단로 19-6422-E010156P0896862022-08-01
수용가번호(관리번호)구역소재지지번주소소재지도로명주소전자식 수도미터 번호무선원격수집기 번호기준일자
8401390-251-0170-00부석면<NA>경상북도 영주시 부석면 소백로 3508번길 6021-D21079210210792022-08-01
8402390-251-0180-00부석면<NA>경상북도 영주시 부석면 소백로 3508번길 6321-D21080210210802022-08-01
8403390-251-0190-00부석면<NA>경상북도 영주시 부석면 소백로 3508번길 6521-D21081210210812022-08-01
8404390-251-0200-00부석면<NA>경상북도 영주시 부석면 소백로 3508번길 57-221-D21076210210762022-08-01
8405390-251-0210-00부석면경상북도 영주시 부석면 노곡리 312<NA>21-D21077210210772022-08-01
8406390-251-0220-00부석면<NA>경상북도 영주시 부석면 소백로 3508번길 57-321-D21078210210782022-08-01
8407390-251-0230-00부석면<NA>경상북도 영주시 부석면 소백로 3508번길 5121-D21075210210752022-08-01
8408390-251-0240-00부석면<NA>경상북도 영주시 부석면 소백로 3508번길 4721-D21073210210732022-08-01
8409390-251-0250-00부석면<NA>경상북도 영주시 부석면 소백로 3508번길 4821-D21074210210742022-08-01
8410390-251-0260-00부석면<NA>경상북도 영주시 부석면 소백로 3508번길 4121-D21072210210722022-08-01