Overview

Dataset statistics

Number of variables10
Number of observations94
Missing cells57
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory82.4 B

Variable types

Text3
Categorical3
Numeric1
DateTime3

Dataset

Description서울특별시 송파구 의 비상급수시설 데이터입니다. 서울특별시 송파구의 민방위 대피, 급수시설 현황 데이터 등을 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15005453/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
준공일자 has 57 (60.6%) missing valuesMissing
비상시설관리번호 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:58:23.122849
Analysis finished2023-12-12 17:58:24.254808
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

비상시설관리번호
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-13T02:58:24.631579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters940
Distinct characters11
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

Unique94 ?
Unique (%)100.0%

Sample

1st rowE197700001
2nd rowE198000002
3rd rowE198200001
4th rowE198500007
5th rowE198700001
ValueCountFrequency (%)
e197700001 1
 
1.1%
e201100016 1
 
1.1%
e201300001 1
 
1.1%
e201200003 1
 
1.1%
e201200001 1
 
1.1%
e201100023 1
 
1.1%
e201100021 1
 
1.1%
e201100020 1
 
1.1%
e201100019 1
 
1.1%
e201100018 1
 
1.1%
Other values (84) 84
89.4%
2023-12-13T02:58:25.208752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 453
48.2%
1 136
 
14.5%
2 95
 
10.1%
E 94
 
10.0%
9 64
 
6.8%
8 21
 
2.2%
3 21
 
2.2%
7 17
 
1.8%
4 17
 
1.8%
5 12
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 846
90.0%
Uppercase Letter 94
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 453
53.5%
1 136
 
16.1%
2 95
 
11.2%
9 64
 
7.6%
8 21
 
2.5%
3 21
 
2.5%
7 17
 
2.0%
4 17
 
2.0%
5 12
 
1.4%
6 10
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
E 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 846
90.0%
Latin 94
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 453
53.5%
1 136
 
16.1%
2 95
 
11.2%
9 64
 
7.6%
8 21
 
2.5%
3 21
 
2.5%
7 17
 
2.0%
4 17
 
2.0%
5 12
 
1.4%
6 10
 
1.2%
Latin
ValueCountFrequency (%)
E 94
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 453
48.2%
1 136
 
14.5%
2 95
 
10.1%
E 94
 
10.0%
9 64
 
6.8%
8 21
 
2.2%
3 21
 
2.2%
7 17
 
1.8%
4 17
 
1.8%
5 12
 
1.3%

읍면동
Categorical

Distinct24
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Memory size884.0 B
가락1동
8 
오륜동
8 
석촌동
8 
거여2동
7 
가락본동
 
5
Other values (19)
58 

Length

Max length4
Median length4
Mean length3.6595745
Min length3

Unique

Unique2 ?
Unique (%)2.1%

Sample

1st row잠실3동
2nd row잠실3동
3rd row마천1동
4th row가락2동
5th row풍납2동

Common Values

ValueCountFrequency (%)
가락1동 8
 
8.5%
오륜동 8
 
8.5%
석촌동 8
 
8.5%
거여2동 7
 
7.4%
가락본동 5
 
5.3%
위례동 5
 
5.3%
풍납2동 5
 
5.3%
잠실4동 5
 
5.3%
잠실6동 4
 
4.3%
방이2동 4
 
4.3%
Other values (14) 35
37.2%

Length

2023-12-13T02:58:25.428200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가락1동 8
 
8.5%
석촌동 8
 
8.5%
오륜동 8
 
8.5%
거여2동 7
 
7.4%
가락본동 5
 
5.3%
위례동 5
 
5.3%
풍납2동 5
 
5.3%
잠실4동 5
 
5.3%
잠실6동 4
 
4.3%
방이2동 4
 
4.3%
Other values (14) 35
37.2%

시설명
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-13T02:58:25.690012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length8.9148936
Min length3

Characters and Unicode

Total characters838
Distinct characters211
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st rowYMCA 송파지회
2nd row영동일고교 내
3rd row구룡사우나
4th row가락프라자아파트
5th row석정사우나
ValueCountFrequency (%)
헬리오시티 6
 
4.4%
송파 6
 
4.4%
올림픽 2
 
1.5%
대각선 2
 
1.5%
제1체육관 2
 
1.5%
옆 2
 
1.5%
지하3층 2
 
1.5%
영동일고교 1
 
0.7%
내 1
 
0.7%
올림픽한증막 1
 
0.7%
Other values (110) 110
81.5%
2023-12-13T02:58:26.161735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41
 
4.9%
) 37
 
4.4%
( 37
 
4.4%
파 24
 
2.9%
우 20
 
2.4%
1 19
 
2.3%
사 19
 
2.3%
나 18
 
2.1%
리 15
 
1.8%
주 13
 
1.6%
Other values (201) 595
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 659
78.6%
Decimal Number 49
 
5.8%
Space Separator 41
 
4.9%
Close Punctuation 37
 
4.4%
Open Punctuation 37
 
4.4%
Uppercase Letter 7
 
0.8%
Dash Punctuation 4
 
0.5%
Other Punctuation 2
 
0.2%
Lowercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 24
 
3.6%
우 20
 
3.0%
사 19
 
2.9%
나 18
 
2.7%
리 15
 
2.3%
주 13
 
2.0%
호 13
 
2.0%
가 12
 
1.8%
크 11
 
1.7%
공 11
 
1.7%
Other values (180) 503
76.3%
Decimal Number
ValueCountFrequency (%)
1 19
38.8%
2 13
26.5%
3 5
 
10.2%
0 4
 
8.2%
4 3
 
6.1%
6 2
 
4.1%
8 1
 
2.0%
5 1
 
2.0%
9 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
C 2
28.6%
B 1
14.3%
M 1
14.3%
Y 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
: 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 659
78.6%
Common 170
 
20.3%
Latin 9
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 24
 
3.6%
우 20
 
3.0%
사 19
 
2.9%
나 18
 
2.7%
리 15
 
2.3%
주 13
 
2.0%
호 13
 
2.0%
가 12
 
1.8%
크 11
 
1.7%
공 11
 
1.7%
Other values (180) 503
76.3%
Common
ValueCountFrequency (%)
41
24.1%
) 37
21.8%
( 37
21.8%
1 19
11.2%
2 13
 
7.6%
3 5
 
2.9%
- 4
 
2.4%
0 4
 
2.4%
4 3
 
1.8%
: 2
 
1.2%
Other values (4) 5
 
2.9%
Latin
ValueCountFrequency (%)
A 2
22.2%
C 2
22.2%
B 1
11.1%
M 1
11.1%
k 1
11.1%
s 1
11.1%
Y 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 659
78.6%
ASCII 179
 
21.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41
22.9%
) 37
20.7%
( 37
20.7%
1 19
10.6%
2 13
 
7.3%
3 5
 
2.8%
- 4
 
2.2%
0 4
 
2.2%
4 3
 
1.7%
: 2
 
1.1%
Other values (11) 14
 
7.8%
Hangul
ValueCountFrequency (%)
파 24
 
3.6%
우 20
 
3.0%
사 19
 
2.9%
나 18
 
2.7%
리 15
 
2.3%
주 13
 
2.0%
호 13
 
2.0%
가 12
 
1.8%
크 11
 
1.7%
공 11
 
1.7%
Other values (180) 503
76.3%

시설구분
Categorical

Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
민간시설
68 
공공시설
14 
자치단체자체시설
9 
정부지원시설
 
3

Length

Max length8
Median length4
Mean length4.4468085
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row민간시설
2nd row정부지원시설
3rd row민간시설
4th row민간시설
5th row민간시설

Common Values

ValueCountFrequency (%)
민간시설 68
72.3%
공공시설 14
 
14.9%
자치단체자체시설 9
 
9.6%
정부지원시설 3
 
3.2%

Length

2023-12-13T02:58:26.326875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:58:26.786774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간시설 68
72.3%
공공시설 14
 
14.9%
자치단체자체시설 9
 
9.6%
정부지원시설 3
 
3.2%

시설도로명주소
Text

Distinct79
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-13T02:58:27.135784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length27.319149
Min length17

Characters and Unicode

Total characters2568
Distinct characters131
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

Unique74 ?
Unique (%)78.7%

Sample

1st row서울특별시 송파구 올림픽로 211 (잠실동, 서울Y.M.C.A송파지회)
2nd row서울특별시 송파구 석촌호수로 93 (잠실동, 영동일고등학교)
3rd row서울특별시 송파구 성내천로 265 (마천동, 구룡목욕탕)
4th row서울특별시 송파구 동남로18길 44 (가락동, 프라자아파트)
5th row서울특별시 송파구 토성로 58 (풍납동, 도원빌딩)
ValueCountFrequency (%)
서울특별시 94
18.5%
송파구 94
18.5%
가락동 15
 
3.0%
방이동 15
 
3.0%
거여동 14
 
2.8%
올림픽로 11
 
2.2%
신천동 9
 
1.8%
송파대로 8
 
1.6%
잠실동 8
 
1.6%
석촌동 8
 
1.6%
Other values (153) 232
45.7%
2023-12-13T02:58:27.717557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
414
 
16.1%
파 115
 
4.5%
송 109
 
4.2%
동 103
 
4.0%
시 100
 
3.9%
서 95
 
3.7%
구 95
 
3.7%
울 95
 
3.7%
특 94
 
3.7%
별 94
 
3.7%
Other values (121) 1254
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1608
62.6%
Space Separator 414
 
16.1%
Decimal Number 316
 
12.3%
Open Punctuation 84
 
3.3%
Close Punctuation 84
 
3.3%
Other Punctuation 44
 
1.7%
Dash Punctuation 14
 
0.5%
Uppercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 115
 
7.2%
송 109
 
6.8%
동 103
 
6.4%
시 100
 
6.2%
서 95
 
5.9%
구 95
 
5.9%
울 95
 
5.9%
특 94
 
5.8%
별 94
 
5.8%
로 83
 
5.2%
Other values (101) 625
38.9%
Decimal Number
ValueCountFrequency (%)
1 51
16.1%
2 50
15.8%
4 47
14.9%
3 44
13.9%
5 32
10.1%
0 25
7.9%
9 22
7.0%
6 21
6.6%
7 12
 
3.8%
8 12
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
Y 1
25.0%
M 1
25.0%
C 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 41
93.2%
. 3
 
6.8%
Space Separator
ValueCountFrequency (%)
414
100.0%
Open Punctuation
ValueCountFrequency (%)
( 84
100.0%
Close Punctuation
ValueCountFrequency (%)
) 84
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1608
62.6%
Common 956
37.2%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 115
 
7.2%
송 109
 
6.8%
동 103
 
6.4%
시 100
 
6.2%
서 95
 
5.9%
구 95
 
5.9%
울 95
 
5.9%
특 94
 
5.8%
별 94
 
5.8%
로 83
 
5.2%
Other values (101) 625
38.9%
Common
ValueCountFrequency (%)
414
43.3%
( 84
 
8.8%
) 84
 
8.8%
1 51
 
5.3%
2 50
 
5.2%
4 47
 
4.9%
3 44
 
4.6%
, 41
 
4.3%
5 32
 
3.3%
0 25
 
2.6%
Other values (6) 84
 
8.8%
Latin
ValueCountFrequency (%)
A 1
25.0%
Y 1
25.0%
M 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1608
62.6%
ASCII 960
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
414
43.1%
( 84
 
8.8%
) 84
 
8.8%
1 51
 
5.3%
2 50
 
5.2%
4 47
 
4.9%
3 44
 
4.6%
, 41
 
4.3%
5 32
 
3.3%
0 25
 
2.6%
Other values (10) 88
 
9.2%
Hangul
ValueCountFrequency (%)
파 115
 
7.2%
송 109
 
6.8%
동 103
 
6.4%
시 100
 
6.2%
서 95
 
5.9%
구 95
 
5.9%
울 95
 
5.9%
특 94
 
5.8%
별 94
 
5.8%
로 83
 
5.2%
Other values (101) 625
38.9%

규모
Real number (ℝ)

Distinct42
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.60638
Minimum23
Maximum1450
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-13T02:58:27.888282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile35
Q160
median80
Q3100
95-th percentile253.5
Maximum1450
Range1427
Interquartile range (IQR)40

Descriptive statistics

Standard deviation155.6858
Coefficient of variation (CV)1.3825664
Kurtosis59.660606
Mean112.60638
Median Absolute Deviation (MAD)20
Skewness7.1067184
Sum10585
Variance24238.069
MonotonicityNot monotonic
2023-12-13T02:58:28.062577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
60 13
 
13.8%
80 8
 
8.5%
90 6
 
6.4%
70 4
 
4.3%
130 4
 
4.3%
40 4
 
4.3%
100 4
 
4.3%
94 3
 
3.2%
50 3
 
3.2%
75 3
 
3.2%
Other values (32) 42
44.7%
ValueCountFrequency (%)
23 1
 
1.1%
25 1
 
1.1%
30 2
2.1%
35 2
2.1%
40 4
4.3%
41 1
 
1.1%
43 1
 
1.1%
45 2
2.1%
50 3
3.2%
55 1
 
1.1%
ValueCountFrequency (%)
1450 1
1.1%
432 1
1.1%
320 1
1.1%
290 1
1.1%
260 1
1.1%
250 2
2.1%
216 2
2.1%
200 1
1.1%
185 1
1.1%
180 1
1.1%

수질등급
Categorical

Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
<NA>
55 
3등급
20 
2등급
14 
1등급
 
5

Length

Max length4
Median length4
Mean length3.5851064
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2등급
2nd row<NA>
3rd row3등급
4th row2등급
5th row3등급

Common Values

ValueCountFrequency (%)
<NA> 55
58.5%
3등급 20
 
21.3%
2등급 14
 
14.9%
1등급 5
 
5.3%

Length

2023-12-13T02:58:28.240206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:58:28.397272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
58.5%
3등급 20
 
21.3%
2등급 14
 
14.9%
1등급 5
 
5.3%

준공일자
Date

MISSING 

Distinct34
Distinct (%)91.9%
Missing57
Missing (%)60.6%
Memory size884.0 B
Minimum1980-01-01 00:00:00
Maximum2011-01-27 00:00:00
2023-12-13T02:58:28.561876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:58:28.729175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

지정일자
Date

Distinct52
Distinct (%)55.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
Minimum1980-01-01 00:00:00
Maximum2019-12-27 00:00:00
2023-12-13T02:58:28.912436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:58:29.129175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
Minimum2023-06-30 00:00:00
Maximum2023-06-30 00:00:00
2023-12-13T02:58:29.291999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:58:29.426590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:58:23.849550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:58:29.529322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비상시설관리번호읍면동시설명시설구분시설도로명주소규모수질등급준공일자지정일자
비상시설관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
읍면동1.0001.0001.0000.8470.9990.0000.7840.9600.975
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.000
시설구분1.0000.8471.0001.0001.0000.7250.0500.0000.921
시설도로명주소1.0000.9991.0001.0001.0000.9520.8290.8390.999
규모1.0000.0001.0000.7250.9521.0000.0001.0000.000
수질등급1.0000.7841.0000.0500.8290.0001.0001.0001.000
준공일자1.0000.9601.0000.0000.8391.0001.0001.0000.996
지정일자1.0000.9751.0000.9210.9990.0001.0000.9961.000
2023-12-13T02:58:29.683707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동수질등급시설구분
읍면동1.0000.4380.499
수질등급0.4381.0000.073
시설구분0.4990.0731.000
2023-12-13T02:58:29.794120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모읍면동시설구분수질등급
규모1.0000.0000.3640.000
읍면동0.0001.0000.4990.438
시설구분0.3640.4991.0000.073
수질등급0.0000.4380.0731.000

Missing values

2023-12-13T02:58:24.000846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:58:24.192127image/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

비상시설관리번호읍면동시설명시설구분시설도로명주소규모수질등급준공일자지정일자데이터기준일자
0E197700001잠실3동YMCA 송파지회민간시설서울특별시 송파구 올림픽로 211 (잠실동, 서울Y.M.C.A송파지회)702등급<NA>1985-01-012023-06-30
1E198000002잠실3동영동일고교 내정부지원시설서울특별시 송파구 석촌호수로 93 (잠실동, 영동일고등학교)432<NA>1980-01-011980-01-012023-06-30
2E198200001마천1동구룡사우나민간시설서울특별시 송파구 성내천로 265 (마천동, 구룡목욕탕)943등급1999-01-011982-09-252023-06-30
3E198500007가락2동가락프라자아파트민간시설서울특별시 송파구 동남로18길 44 (가락동, 프라자아파트)502등급<NA>1985-08-012023-06-30
4E198700001풍납2동석정사우나민간시설서울특별시 송파구 토성로 58 (풍납동, 도원빌딩)883등급<NA>1987-12-012023-06-30
5E198900003잠실6동장미C상가민간시설서울특별시 송파구 올림픽로35길 104 (신천동, 장미아파트)403등급1989-02-011989-02-012023-06-30
6E199100002잠실6동대한제당민간시설서울특별시 송파구 올림픽로 299 (신천동, 대한제당)623등급1991-09-141991-10-012023-06-30
7E199100004방이2동수정사우나민간시설서울특별시 송파구 오금로19길 7-1 (방이동)603등급<NA>1991-01-012023-06-30
8E199100005오금동혜성빌딩민간시설서울특별시 송파구 동남로 286 (오금동)603등급<NA>1991-12-012023-06-30
9E199100007문정1동디에스크린(주)민간시설서울특별시 송파구 동남로6길 29-23 (문정동)1002등급<NA>1991-04-012023-06-30
비상시설관리번호읍면동시설명시설구분시설도로명주소규모수질등급준공일자지정일자데이터기준일자
84E201900003가락1동송파 헬리오시티 3호정(가락1동 주민센터 뒤)자치단체자체시설서울특별시 송파구 송파대로 345 (가락동, 헬리오시티)170<NA><NA>2019-02-112023-06-30
85E201900004가락1동송파 헬리오시티 4호정(책박물관 좌측 대각선)자치단체자체시설서울특별시 송파구 송파대로 345 (가락동, 헬리오시티)170<NA><NA>2019-02-112023-06-30
86E201900005가락1동송파 헬리오시티 5호정(책박물관 우측 대각선)자치단체자체시설서울특별시 송파구 송파대로 345 (가락동, 헬리오시티)216<NA><NA>2019-02-112023-06-30
87E201900006가락1동송파 헬리오시티 6호정(102동 아래)자치단체자체시설서울특별시 송파구 송파대로 345 (가락동, 헬리오시티)216<NA><NA>2019-02-112023-06-30
88E201900007위례동진흥기업(주)민간시설서울특별시 송파구 거마로 54-0 (거여동)75<NA><NA>2019-04-172023-06-30
89E201900008거여2동롯데건설(주)(1)민간시설서울특별시 송파구 거마로 54-0 (거여동)45<NA><NA>2019-04-172023-06-30
90E201900009거여2동롯데건설(주)(2)민간시설서울특별시 송파구 거마로 54-0 (거여동)45<NA><NA>2019-04-172023-06-30
91E201900010거여2동롯데건설(주)(3)민간시설서울특별시 송파구 거마로 54-0 (거여동)70<NA><NA>2019-04-172023-06-30
92E201900011거여2동롯데건설(주)(4)민간시설서울특별시 송파구 거마로 54-0 (거여동)70<NA><NA>2019-04-172023-06-30
93E201900012삼전동석촌탕민간시설서울특별시 송파구 백제고분로31길 38, 석촌목욕탕(삼전동)90<NA><NA>2019-12-272023-06-30