Overview

Dataset statistics

Number of variables8
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory67.6 B

Variable types

Numeric2
Categorical2
Text3
DateTime1

Dataset

Description인천광역시 서구 비상급수시설 현황 (시설종류, 용도, 시설명칭, 소재지(도로명), 소재지(지번), 급수능력(일일생산능력(톤) 등) 에 관하여 데이터를 제공합니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15089430&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 시설종류 and 1 other fieldsHigh correlation
시설종류 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
용도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
시설종류 is highly imbalanced (68.1%)Imbalance
연번 has unique valuesUnique
소재지(지번) has unique valuesUnique

Reproduction

Analysis started2024-01-28 07:03:48.592589
Analysis finished2024-01-28 07:03:49.432924
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.5
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-01-28T16:03:49.489064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.15
Q121.75
median42.5
Q363.25
95-th percentile79.85
Maximum84
Range83
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation24.392622
Coefficient of variation (CV)0.57394404
Kurtosis-1.2
Mean42.5
Median Absolute Deviation (MAD)21
Skewness0
Sum3570
Variance595
MonotonicityStrictly increasing
2024-01-28T16:03:49.589586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
55 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
Other values (74) 74
88.1%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%

시설종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
공공용
76 
정부지원
 
7
지자체
 
1

Length

Max length4
Median length3
Mean length3.0833333
Min length3

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st row정부지원
2nd row지자체
3rd row정부지원
4th row정부지원
5th row정부지원

Common Values

ValueCountFrequency (%)
공공용 76
90.5%
정부지원 7
 
8.3%
지자체 1
 
1.2%

Length

2024-01-28T16:03:49.699621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T16:03:49.782192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 76
90.5%
정부지원 7
 
8.3%
지자체 1
 
1.2%

용도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
생활용수
65 
음용수
19 

Length

Max length4
Median length4
Mean length3.7738095
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활용수 65
77.4%
음용수 19
 
22.6%

Length

2024-01-28T16:03:49.864873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T16:03:49.943264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활용수 65
77.4%
음용수 19
 
22.6%

시설명칭
Text

Distinct83
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-01-28T16:03:50.158872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length5.6904762
Min length3

Characters and Unicode

Total characters478
Distinct characters185
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)97.6%

Sample

1st row대인고등학교
2nd row석남체육공원
3rd row가좌초등학교
4th row가좌울공원
5th row가좌체육공원
ValueCountFrequency (%)
㈜ 2
 
2.2%
신태진 2
 
2.2%
경제정책과(오류동 1
 
1.1%
수정교회 1
 
1.1%
검단식품 1
 
1.1%
검단농협주유소 1
 
1.1%
마전주유소 1
 
1.1%
이우영 1
 
1.1%
조영철 1
 
1.1%
영어마을 1
 
1.1%
Other values (77) 77
86.5%
2024-01-28T16:03:50.485747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 12
 
2.5%
가 12
 
2.5%
마 11
 
2.3%
공 11
 
2.3%
신 10
 
2.1%
사 10
 
2.1%
) 8
 
1.7%
8
 
1.7%
( 8
 
1.7%
소 8
 
1.7%
Other values (175) 380
79.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 431
90.2%
Decimal Number 15
 
3.1%
Close Punctuation 8
 
1.7%
Space Separator 8
 
1.7%
Open Punctuation 8
 
1.7%
Dash Punctuation 4
 
0.8%
Other Symbol 2
 
0.4%
Lowercase Letter 1
 
0.2%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 12
 
2.8%
가 12
 
2.8%
마 11
 
2.6%
공 11
 
2.6%
신 10
 
2.3%
사 10
 
2.3%
소 8
 
1.9%
우 7
 
1.6%
동 7
 
1.6%
교 7
 
1.6%
Other values (161) 336
78.0%
Decimal Number
ValueCountFrequency (%)
9 3
20.0%
3 3
20.0%
1 3
20.0%
5 2
13.3%
2 2
13.3%
8 1
 
6.7%
4 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
w 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 433
90.6%
Common 43
 
9.0%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 12
 
2.8%
가 12
 
2.8%
마 11
 
2.5%
공 11
 
2.5%
신 10
 
2.3%
사 10
 
2.3%
소 8
 
1.8%
우 7
 
1.6%
동 7
 
1.6%
교 7
 
1.6%
Other values (162) 338
78.1%
Common
ValueCountFrequency (%)
) 8
18.6%
8
18.6%
( 8
18.6%
- 4
9.3%
9 3
 
7.0%
3 3
 
7.0%
1 3
 
7.0%
5 2
 
4.7%
2 2
 
4.7%
8 1
 
2.3%
Latin
ValueCountFrequency (%)
w 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 431
90.2%
ASCII 45
 
9.4%
None 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 12
 
2.8%
가 12
 
2.8%
마 11
 
2.6%
공 11
 
2.6%
신 10
 
2.3%
사 10
 
2.3%
소 8
 
1.9%
우 7
 
1.6%
동 7
 
1.6%
교 7
 
1.6%
Other values (161) 336
78.0%
ASCII
ValueCountFrequency (%)
) 8
17.8%
8
17.8%
( 8
17.8%
- 4
8.9%
9 3
 
6.7%
3 3
 
6.7%
1 3
 
6.7%
5 2
 
4.4%
2 2
 
4.4%
8 1
 
2.2%
Other values (3) 3
 
6.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

소재지(도로명)
Text

Distinct82
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-01-28T16:03:50.711265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length22.511905
Min length15

Characters and Unicode

Total characters1891
Distinct characters92
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

Unique80 ?
Unique (%)95.2%

Sample

1st row인천광역시 서구 서곶로 446(공촌동)
2nd row인천광역시 서구 가정로 294번길 20(석남동)
3rd row인천광역시 서구 장고개로 309번길5(가좌동)
4th row인천광역시 서구 고래울로35(가좌동)
5th row인천광역시 서구 고래룰로 12(가좌동)
ValueCountFrequency (%)
인천광역시 84
21.3%
서구 84
21.3%
가좌동 14
 
3.6%
석남동 8
 
2.0%
원적로 8
 
2.0%
봉수대로 7
 
1.8%
신현동 6
 
1.5%
서곶로 6
 
1.5%
공촌동 3
 
0.8%
1 3
 
0.8%
Other values (142) 171
43.4%
2024-01-28T16:03:51.239681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
325
 
17.2%
서 100
 
5.3%
천 85
 
4.5%
시 85
 
4.5%
구 84
 
4.4%
인 84
 
4.4%
역 84
 
4.4%
광 84
 
4.4%
로 77
 
4.1%
동 64
 
3.4%
Other values (82) 819
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1118
59.1%
Space Separator 325
 
17.2%
Decimal Number 314
 
16.6%
Close Punctuation 57
 
3.0%
Open Punctuation 57
 
3.0%
Dash Punctuation 20
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 100
 
8.9%
천 85
 
7.6%
시 85
 
7.6%
구 84
 
7.5%
인 84
 
7.5%
역 84
 
7.5%
광 84
 
7.5%
로 77
 
6.9%
동 64
 
5.7%
번 37
 
3.3%
Other values (68) 334
29.9%
Decimal Number
ValueCountFrequency (%)
1 62
19.7%
3 47
15.0%
2 41
13.1%
5 34
10.8%
6 31
9.9%
7 26
8.3%
9 23
 
7.3%
0 21
 
6.7%
4 17
 
5.4%
8 12
 
3.8%
Space Separator
ValueCountFrequency (%)
325
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1118
59.1%
Common 773
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 100
 
8.9%
천 85
 
7.6%
시 85
 
7.6%
구 84
 
7.5%
인 84
 
7.5%
역 84
 
7.5%
광 84
 
7.5%
로 77
 
6.9%
동 64
 
5.7%
번 37
 
3.3%
Other values (68) 334
29.9%
Common
ValueCountFrequency (%)
325
42.0%
1 62
 
8.0%
) 57
 
7.4%
( 57
 
7.4%
3 47
 
6.1%
2 41
 
5.3%
5 34
 
4.4%
6 31
 
4.0%
7 26
 
3.4%
9 23
 
3.0%
Other values (4) 70
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1118
59.1%
ASCII 773
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
325
42.0%
1 62
 
8.0%
) 57
 
7.4%
( 57
 
7.4%
3 47
 
6.1%
2 41
 
5.3%
5 34
 
4.4%
6 31
 
4.0%
7 26
 
3.4%
9 23
 
3.0%
Other values (4) 70
 
9.1%
Hangul
ValueCountFrequency (%)
서 100
 
8.9%
천 85
 
7.6%
시 85
 
7.6%
구 84
 
7.5%
인 84
 
7.5%
역 84
 
7.5%
광 84
 
7.5%
로 77
 
6.9%
동 64
 
5.7%
번 37
 
3.3%
Other values (68) 334
29.9%

소재지(지번)
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-01-28T16:03:51.486161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.095238
Min length15

Characters and Unicode

Total characters1520
Distinct characters60
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

Unique84 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 공촌동47-3
2nd row인천광역시 서구 석남1동 483번지
3rd row인천광역시 서구 가좌2동 30-87
4th row인천광역시 서구 가좌4동 354
5th row인천광역시 서구 가좌4동 339번지
ValueCountFrequency (%)
인천광역시 84
24.9%
서구 84
24.9%
가좌3동 10
 
3.0%
석남동 9
 
2.7%
가좌동 8
 
2.4%
신현동 6
 
1.8%
가정동 6
 
1.8%
공촌동 5
 
1.5%
석남1동 5
 
1.5%
심곡동 3
 
0.9%
Other values (104) 118
34.9%
2024-01-28T16:03:51.843983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
254
16.7%
서 86
 
5.7%
천 85
 
5.6%
시 85
 
5.6%
동 85
 
5.6%
인 84
 
5.5%
광 84
 
5.5%
역 84
 
5.5%
구 84
 
5.5%
- 61
 
4.0%
Other values (50) 528
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 874
57.5%
Decimal Number 327
 
21.5%
Space Separator 254
 
16.7%
Dash Punctuation 61
 
4.0%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 86
9.8%
천 85
9.7%
시 85
9.7%
동 85
9.7%
인 84
9.6%
광 84
9.6%
역 84
9.6%
구 84
9.6%
가 29
 
3.3%
좌 23
 
2.6%
Other values (36) 145
16.6%
Decimal Number
ValueCountFrequency (%)
1 59
18.0%
2 50
15.3%
3 49
15.0%
5 40
12.2%
4 26
8.0%
7 25
7.6%
8 22
 
6.7%
6 21
 
6.4%
9 19
 
5.8%
0 16
 
4.9%
Space Separator
ValueCountFrequency (%)
254
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 874
57.5%
Common 646
42.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 86
9.8%
천 85
9.7%
시 85
9.7%
동 85
9.7%
인 84
9.6%
광 84
9.6%
역 84
9.6%
구 84
9.6%
가 29
 
3.3%
좌 23
 
2.6%
Other values (36) 145
16.6%
Common
ValueCountFrequency (%)
254
39.3%
- 61
 
9.4%
1 59
 
9.1%
2 50
 
7.7%
3 49
 
7.6%
5 40
 
6.2%
4 26
 
4.0%
7 25
 
3.9%
8 22
 
3.4%
6 21
 
3.3%
Other values (4) 39
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 874
57.5%
ASCII 646
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
254
39.3%
- 61
 
9.4%
1 59
 
9.1%
2 50
 
7.7%
3 49
 
7.6%
5 40
 
6.2%
4 26
 
4.0%
7 25
 
3.9%
8 22
 
3.4%
6 21
 
3.3%
Other values (4) 39
 
6.0%
Hangul
ValueCountFrequency (%)
서 86
9.8%
천 85
9.7%
시 85
9.7%
동 85
9.7%
인 84
9.6%
광 84
9.6%
역 84
9.6%
구 84
9.6%
가 29
 
3.3%
좌 23
 
2.6%
Other values (36) 145
16.6%

급수용량(일일공급능력(톤))
Real number (ℝ)

Distinct31
Distinct (%)36.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.809524
Minimum20
Maximum630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-01-28T16:03:51.946149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q150
median72
Q390
95-th percentile192.5
Maximum630
Range610
Interquartile range (IQR)40

Descriptive statistics

Standard deviation81.473993
Coefficient of variation (CV)0.94947494
Kurtosis24.930175
Mean85.809524
Median Absolute Deviation (MAD)22
Skewness4.3534628
Sum7208
Variance6638.0115
MonotonicityNot monotonic
2024-01-28T16:03:52.048794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
80 9
 
10.7%
20 7
 
8.3%
100 7
 
8.3%
60 7
 
8.3%
50 6
 
7.1%
150 5
 
6.0%
86 5
 
6.0%
25 4
 
4.8%
70 4
 
4.8%
72 4
 
4.8%
Other values (21) 26
31.0%
ValueCountFrequency (%)
20 7
8.3%
25 4
4.8%
30 3
3.6%
35 1
 
1.2%
40 1
 
1.2%
45 1
 
1.2%
50 6
7.1%
51 1
 
1.2%
52 1
 
1.2%
57 1
 
1.2%
ValueCountFrequency (%)
630 1
 
1.2%
350 1
 
1.2%
271 1
 
1.2%
270 1
 
1.2%
200 1
 
1.2%
150 5
6.0%
115 1
 
1.2%
100 7
8.3%
98 1
 
1.2%
96 1
 
1.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
Minimum2022-08-01 00:00:00
Maximum2022-08-01 00:00:00
2024-01-28T16:03:52.124993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:03:52.188636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T16:03:49.142028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:03:49.020678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:03:49.205884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:03:49.076112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T16:03:52.243731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설종류용도시설명칭소재지(도로명)소재지(지번)급수용량(일일공급능력(톤))
연번1.0000.7410.6840.9390.9731.0000.467
시설종류0.7411.0000.3691.0001.0001.0000.608
용도0.6840.3691.0001.0001.0001.0000.451
시설명칭0.9391.0001.0001.0001.0001.0000.000
소재지(도로명)0.9731.0001.0001.0001.0001.0000.000
소재지(지번)1.0001.0001.0001.0001.0001.0001.000
급수용량(일일공급능력(톤))0.4670.6080.4510.0000.0001.0001.000
2024-01-28T16:03:52.322241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도시설종류
용도1.0000.583
시설종류0.5831.000
2024-01-28T16:03:52.384150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번급수용량(일일공급능력(톤))시설종류용도
연번1.000-0.3800.5820.505
급수용량(일일공급능력(톤))-0.3801.0000.3030.316
시설종류0.5820.3031.0000.583
용도0.5050.3160.5831.000

Missing values

2024-01-28T16:03:49.299270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T16:03:49.392336image/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

연번시설종류용도시설명칭소재지(도로명)소재지(지번)급수용량(일일공급능력(톤))데이터기준일자
01정부지원음용수대인고등학교인천광역시 서구 서곶로 446(공촌동)인천광역시 서구 공촌동47-31502022-08-01
12지자체음용수석남체육공원인천광역시 서구 가정로 294번길 20(석남동)인천광역시 서구 석남1동 483번지512022-08-01
23정부지원음용수가좌초등학교인천광역시 서구 장고개로 309번길5(가좌동)인천광역시 서구 가좌2동 30-871502022-08-01
34정부지원음용수가좌울공원인천광역시 서구 고래울로35(가좌동)인천광역시 서구 가좌4동 3541502022-08-01
45정부지원음용수가좌체육공원인천광역시 서구 고래룰로 12(가좌동)인천광역시 서구 가좌4동 339번지2702022-08-01
56정부지원음용수갈마공원인천광역시 서구 승학로272번길 13(심곡동)인천광역시 서구 심곡동 238-51002022-08-01
67정부지원음용수신촌공원인천광역시 서구 건지로153번길 25-13인천광역시 서구 석남1동 521-1번지1002022-08-01
78정부지원음용수가좌근린공원인천광역시 서구 장고개로 287번길25(가좌동)인천광역시 서구 가좌2동 220 외3필지1002022-08-01
89공공용생활용수㈜ 신태진인천광역시 서구 도요지로 37 (경서동)인천광역시 서구 경서동 438-226302022-08-01
910공공용생활용수㈜ 신태진인천광역시 서구 도요지로 37 (경서동)인천광역시 서구 경서동 438-212712022-08-01
연번시설종류용도시설명칭소재지(도로명)소재지(지번)급수용량(일일공급능력(톤))데이터기준일자
7475공공용생활용수두밀촌낚시터인천광역시 서구 두밀로 91인천광역시 서구 대곡동 260-1572022-08-01
7576공공용생활용수배창호인천광역시 서구 도곡로 298인천광역시 서구 대곡동 26652022-08-01
7677공공용생활용수용오자동차공업사인천광역시 서구 길주로 87인천광역시 서구 석남동 511-3602022-08-01
7778공공용생활용수신우테크인천광역시 서구 길주로136번길 31인천광역시 서구 석남동 555-35502022-08-01
7879공공용생활용수경제정책과(공촌동89-2)인천광역시 서구 경명대로 725-77(공촌동)인천광역시 서구 공촌동 89-2802022-08-01
7980공공용생활용수청라스파렉스인천광역시 서구 청라커낼로260번길 15인천광역시 서구 청라동 158-23502022-08-01
8081공공용생활용수경제정책과(검암동9-1)인천광역시 서구 검암동 9-1인천광역시 서구 검암동 9-1802022-08-01
8182공공용생활용수선인장이야기인천광역시 서구 서곶로 156인천광역시 서구 가정동 5-5502022-08-01
8283공공용생활용수신도조경인천광역시 서구 서곶로 150인천광역시 서구 가정동 5-148602022-08-01
8384공공용생활용수경제정책과(오류동 395-35)인천광역시 서구 원당대로117번길 70-9인천광역시 서구 오류동 395-35802022-08-01