Overview

Dataset statistics

Number of variables20
Number of observations798
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory131.1 KiB
Average record size in memory168.2 B

Variable types

Text4
Categorical7
Numeric6
Boolean2
DateTime1

Dataset

Description대구광역시_강서소방서_소방용수시설
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15034538&dataSetDetailId=150345381cc26d07af31e&provdMethod=FILE

Alerts

시도명 has constant value ""Constant
사용가능여부 has constant value ""Constant
관할소방서명 has constant value ""Constant
관할소방서전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시군구코드 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
시군구명 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
위도 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 시군구명 and 2 other fieldsHigh correlation
설치연도 is highly overall correlated with 시군구명 and 2 other fieldsHigh correlation
출수압력 is highly overall correlated with 시설유형코드 and 1 other fieldsHigh correlation
시설유형코드 is highly overall correlated with 출수압력High correlation
안전센터명 is highly overall correlated with 경도 and 4 other fieldsHigh correlation
보호틀유무 is highly imbalanced (70.8%)Imbalance
시설번호 has unique valuesUnique

Reproduction

Analysis started2024-04-19 05:19:47.599989
Analysis finished2024-04-19 05:19:52.512518
Duration4.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설번호
Text

UNIQUE 

Distinct798
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-19T14:19:52.726759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.3471178
Min length6

Characters and Unicode

Total characters5863
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique798 ?
Unique (%)100.0%

Sample

1st row상8-1-1
2nd row상8-1-2
3rd row하8-1-3
4th row하8-1-4
5th row상8-1-5
ValueCountFrequency (%)
상8-1-1 1
 
0.1%
하8-3-145 1
 
0.1%
하8-3-147 1
 
0.1%
하8-3-148 1
 
0.1%
상8-3-150 1
 
0.1%
하8-3-151 1
 
0.1%
상8-3-152 1
 
0.1%
하8-3-153 1
 
0.1%
상8-3-154 1
 
0.1%
상8-3-155 1
 
0.1%
Other values (788) 788
98.7%
2024-04-19T14:19:53.141984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1596
27.2%
8 938
16.0%
1 665
11.3%
상 428
 
7.3%
2 385
 
6.6%
하 368
 
6.3%
3 360
 
6.1%
4 312
 
5.3%
5 238
 
4.1%
6 158
 
2.7%
Other values (4) 415
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3469
59.2%
Dash Punctuation 1596
27.2%
Other Letter 798
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 938
27.0%
1 665
19.2%
2 385
11.1%
3 360
 
10.4%
4 312
 
9.0%
5 238
 
6.9%
6 158
 
4.6%
7 155
 
4.5%
9 132
 
3.8%
0 126
 
3.6%
Other Letter
ValueCountFrequency (%)
상 428
53.6%
하 368
46.1%
저 2
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 1596
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5065
86.4%
Hangul 798
 
13.6%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1596
31.5%
8 938
18.5%
1 665
13.1%
2 385
 
7.6%
3 360
 
7.1%
4 312
 
6.2%
5 238
 
4.7%
6 158
 
3.1%
7 155
 
3.1%
9 132
 
2.6%
Hangul
ValueCountFrequency (%)
상 428
53.6%
하 368
46.1%
저 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5065
86.4%
Hangul 798
 
13.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1596
31.5%
8 938
18.5%
1 665
13.1%
2 385
 
7.6%
3 360
 
7.1%
4 312
 
6.2%
5 238
 
4.7%
6 158
 
3.1%
7 155
 
3.1%
9 132
 
2.6%
Hangul
ValueCountFrequency (%)
상 428
53.6%
하 368
46.1%
저 2
 
0.3%

시설유형코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
1
428 
2
368 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 428
53.6%
2 368
46.1%
4 2
 
0.3%

Length

2024-04-19T14:19:53.278377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:19:53.373237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 428
53.6%
2 368
46.1%
4 2
 
0.3%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
대구광역시
798 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 798
100.0%

Length

2024-04-19T14:19:53.468443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:19:53.555785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 798
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
달서구
651 
달성군
147 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row달서구
2nd row달성군
3rd row달서구
4th row달서구
5th row달서구

Common Values

ValueCountFrequency (%)
달서구 651
81.6%
달성군 147
 
18.4%

Length

2024-04-19T14:19:53.649573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:19:53.744824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
달서구 651
81.6%
달성군 147
 
18.4%

시군구코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
27290
651 
27710
147 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27290
2nd row27710
3rd row27290
4th row27290
5th row27290

Common Values

ValueCountFrequency (%)
27290 651
81.6%
27710 147
 
18.4%

Length

2024-04-19T14:19:53.851243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:19:53.985820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27290 651
81.6%
27710 147
 
18.4%

소재지도로명주소
Text

Distinct759
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-19T14:19:54.273584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length19.833333
Min length15

Characters and Unicode

Total characters15827
Distinct characters99
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique730 ?
Unique (%)91.5%

Sample

1st row대구광역시 달서구 달구벌대로 203길 3
2nd row대구광역시 달성군 다사읍 세천로10길 42
3rd row대구광역시 달서구 호산동로35북길 79
4th row대구광역시 달서구 호산동로36북길 54
5th row대구광역시 달서구 달서대로109안길 20
ValueCountFrequency (%)
대구광역시 798
23.2%
달서구 652
18.9%
달성군 149
 
4.3%
다사읍 98
 
2.8%
성서공단로 51
 
1.5%
하빈면 47
 
1.4%
달구벌대로 42
 
1.2%
성서로 39
 
1.1%
성서공단북로 37
 
1.1%
성서서로 27
 
0.8%
Other values (618) 1507
43.7%
2024-04-19T14:19:54.733535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2649
16.7%
구 1531
 
9.7%
서 1037
 
6.6%
대 946
 
6.0%
달 924
 
5.8%
역 816
 
5.2%
광 798
 
5.0%
시 798
 
5.0%
로 722
 
4.6%
1 510
 
3.2%
Other values (89) 5096
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10466
66.1%
Decimal Number 2661
 
16.8%
Space Separator 2649
 
16.7%
Dash Punctuation 50
 
0.3%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1531
14.6%
서 1037
9.9%
대 946
9.0%
달 924
8.8%
역 816
 
7.8%
광 798
 
7.6%
시 798
 
7.6%
로 722
 
6.9%
길 424
 
4.1%
성 423
 
4.0%
Other values (76) 2047
19.6%
Decimal Number
ValueCountFrequency (%)
1 510
19.2%
2 380
14.3%
3 370
13.9%
5 271
10.2%
4 231
8.7%
6 197
 
7.4%
7 184
 
6.9%
9 180
 
6.8%
0 180
 
6.8%
8 158
 
5.9%
Space Separator
ValueCountFrequency (%)
2649
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10466
66.1%
Common 5361
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1531
14.6%
서 1037
9.9%
대 946
9.0%
달 924
8.8%
역 816
 
7.8%
광 798
 
7.6%
시 798
 
7.6%
로 722
 
6.9%
길 424
 
4.1%
성 423
 
4.0%
Other values (76) 2047
19.6%
Common
ValueCountFrequency (%)
2649
49.4%
1 510
 
9.5%
2 380
 
7.1%
3 370
 
6.9%
5 271
 
5.1%
4 231
 
4.3%
6 197
 
3.7%
7 184
 
3.4%
9 180
 
3.4%
0 180
 
3.4%
Other values (3) 209
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10466
66.1%
ASCII 5361
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2649
49.4%
1 510
 
9.5%
2 380
 
7.1%
3 370
 
6.9%
5 271
 
5.1%
4 231
 
4.3%
6 197
 
3.7%
7 184
 
3.4%
9 180
 
3.4%
0 180
 
3.4%
Other values (3) 209
 
3.9%
Hangul
ValueCountFrequency (%)
구 1531
14.6%
서 1037
9.9%
대 946
9.0%
달 924
8.8%
역 816
 
7.8%
광 798
 
7.6%
시 798
 
7.6%
로 722
 
6.9%
길 424
 
4.1%
성 423
 
4.0%
Other values (76) 2047
19.6%

소재지지번주소
Text

Distinct758
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-19T14:19:54.961633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length19.236842
Min length15

Characters and Unicode

Total characters15351
Distinct characters64
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

Unique728 ?
Unique (%)91.2%

Sample

1st row대구광역시 달서구 호산동 984-4
2nd row대구광역시 달성군 다사읍 세천리 1606-6
3rd row대구광역시 달서구 호산동 371
4th row대구광역시 달서구 호산동 357-32
5th row대구광역시 달서구 호산동 386-19
ValueCountFrequency (%)
대구광역시 798
24.5%
달서구 651
20.0%
달성군 147
 
4.5%
감삼동 120
 
3.7%
갈산동 81
 
2.5%
호산동 69
 
2.1%
이곡동 64
 
2.0%
신당동 58
 
1.8%
장동 52
 
1.6%
대천동 48
 
1.5%
Other values (774) 1171
35.9%
2024-04-19T14:19:55.293015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2461
16.0%
구 1449
 
9.4%
대 850
 
5.5%
달 799
 
5.2%
광 798
 
5.2%
역 798
 
5.2%
시 798
 
5.2%
1 703
 
4.6%
서 669
 
4.4%
동 654
 
4.3%
Other values (54) 5372
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8947
58.3%
Decimal Number 3350
 
21.8%
Space Separator 2461
 
16.0%
Dash Punctuation 591
 
3.8%
Close Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1449
16.2%
대 850
9.5%
달 799
8.9%
광 798
8.9%
역 798
8.9%
시 798
8.9%
서 669
 
7.5%
동 654
 
7.3%
산 162
 
1.8%
리 147
 
1.6%
Other values (40) 1823
20.4%
Decimal Number
ValueCountFrequency (%)
1 703
21.0%
3 380
11.3%
0 375
11.2%
5 328
9.8%
2 311
9.3%
6 283
8.4%
7 273
 
8.1%
8 251
 
7.5%
4 226
 
6.7%
9 220
 
6.6%
Space Separator
ValueCountFrequency (%)
2461
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 591
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8947
58.3%
Common 6404
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1449
16.2%
대 850
9.5%
달 799
8.9%
광 798
8.9%
역 798
8.9%
시 798
8.9%
서 669
 
7.5%
동 654
 
7.3%
산 162
 
1.8%
리 147
 
1.6%
Other values (40) 1823
20.4%
Common
ValueCountFrequency (%)
2461
38.4%
1 703
 
11.0%
- 591
 
9.2%
3 380
 
5.9%
0 375
 
5.9%
5 328
 
5.1%
2 311
 
4.9%
6 283
 
4.4%
7 273
 
4.3%
8 251
 
3.9%
Other values (4) 448
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8947
58.3%
ASCII 6404
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2461
38.4%
1 703
 
11.0%
- 591
 
9.2%
3 380
 
5.9%
0 375
 
5.9%
5 328
 
5.1%
2 311
 
4.9%
6 283
 
4.4%
7 273
 
4.3%
8 251
 
3.9%
Other values (4) 448
 
7.0%
Hangul
ValueCountFrequency (%)
구 1449
16.2%
대 850
9.5%
달 799
8.9%
광 798
8.9%
역 798
8.9%
시 798
8.9%
서 669
 
7.5%
동 654
 
7.3%
산 162
 
1.8%
리 147
 
1.6%
Other values (40) 1823
20.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct762
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.850819
Minimum35.503568
Maximum35.93739
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-19T14:19:55.437899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.503568
5-th percentile35.825184
Q135.841569
median35.849772
Q335.857055
95-th percentile35.879744
Maximum35.93739
Range0.433822
Interquartile range (IQR)0.015485226

Descriptive statistics

Standard deviation0.021438191
Coefficient of variation (CV)0.0005979833
Kurtosis87.54144
Mean35.850819
Median Absolute Deviation (MAD)0.0077527661
Skewness-4.4690342
Sum28608.954
Variance0.00045959604
MonotonicityNot monotonic
2024-04-19T14:19:55.584613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8454788633 4
 
0.5%
35.8324986656 3
 
0.4%
35.8419243566 3
 
0.4%
35.8502225544 3
 
0.4%
35.8451549921 3
 
0.4%
35.8475665166 3
 
0.4%
35.8431298479 3
 
0.4%
35.8526210413 2
 
0.3%
35.8555296935 2
 
0.3%
35.8573446482 2
 
0.3%
Other values (752) 770
96.5%
ValueCountFrequency (%)
35.503568 1
0.1%
35.8164020542 1
0.1%
35.8173461186 1
0.1%
35.817421 1
0.1%
35.817715068 1
0.1%
35.817878 1
0.1%
35.8178890366 1
0.1%
35.8179174273 1
0.1%
35.8180427532 1
0.1%
35.8185894837 1
0.1%
ValueCountFrequency (%)
35.9373899952 1
0.1%
35.9356295639 1
0.1%
35.9355154481 1
0.1%
35.9322118896 1
0.1%
35.9311863102 1
0.1%
35.9310887778 1
0.1%
35.925536 1
0.1%
35.9189994078 1
0.1%
35.9134555269 1
0.1%
35.911161762 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct758
Distinct (%)95.1%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean128.49958
Minimum128.27561
Maximum128.54834
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-19T14:19:55.718098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.27561
5-th percentile128.44468
Q1128.48557
median128.50359
Q3128.51748
95-th percentile128.54082
Maximum128.54834
Range0.27273086
Interquartile range (IQR)0.031910187

Descriptive statistics

Standard deviation0.03043269
Coefficient of variation (CV)0.00023683105
Kurtosis5.0094991
Mean128.49958
Median Absolute Deviation (MAD)0.016008
Skewness-1.4902343
Sum102414.16
Variance0.00092614864
MonotonicityNot monotonic
2024-04-19T14:19:55.849816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.4798120093 4
 
0.5%
128.5077435968 4
 
0.5%
128.4901108819 4
 
0.5%
128.4900103537 3
 
0.4%
128.4908182592 3
 
0.4%
128.4736776784 3
 
0.4%
128.5061979917 3
 
0.4%
128.4939141922 2
 
0.3%
128.4718540243 2
 
0.3%
128.493402477 2
 
0.3%
Other values (748) 767
96.1%
ValueCountFrequency (%)
128.275609 1
0.1%
128.3922420673 1
0.1%
128.3929048198 1
0.1%
128.3930803708 1
0.1%
128.394428 1
0.1%
128.3958168009 1
0.1%
128.3975071362 1
0.1%
128.3981242749 1
0.1%
128.3981962669 1
0.1%
128.3995011667 1
0.1%
ValueCountFrequency (%)
128.5483398589 1
0.1%
128.5473925121 1
0.1%
128.5468857145 1
0.1%
128.546851 1
0.1%
128.5465012261 1
0.1%
128.5464173728 1
0.1%
128.5464042977 1
0.1%
128.545921 1
0.1%
128.5459099952 1
0.1%
128.5456141287 1
0.1%

상세위치
Text

Distinct795
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-19T14:19:56.097721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length34
Mean length12.482456
Min length4

Characters and Unicode

Total characters9961
Distinct characters563
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique792 ?
Unique (%)99.2%

Sample

1st row산호경로당앞
2nd row나무트레이드 앞
3rd row미헤어라인 북편
4th row재광빌라 앞
5th row건풍관 동편
ValueCountFrequency (%)
앞 237
 
11.2%
인도상 100
 
4.7%
정문 84
 
4.0%
도로상 72
 
3.4%
북편 62
 
2.9%
동편 57
 
2.7%
서편 45
 
2.1%
남편 42
 
2.0%
인도 28
 
1.3%
맞은편 17
 
0.8%
Other values (1083) 1380
65.0%
2024-04-19T14:19:56.502897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1333
 
13.4%
편 451
 
4.5%
앞 368
 
3.7%
도 287
 
2.9%
상 259
 
2.6%
서 221
 
2.2%
정 218
 
2.2%
동 202
 
2.0%
문 182
 
1.8%
인 180
 
1.8%
Other values (553) 6260
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7814
78.4%
Space Separator 1335
 
13.4%
Decimal Number 300
 
3.0%
Uppercase Letter 161
 
1.6%
Open Punctuation 117
 
1.2%
Close Punctuation 115
 
1.2%
Other Symbol 39
 
0.4%
Other Punctuation 35
 
0.4%
Lowercase Letter 30
 
0.3%
Dash Punctuation 11
 
0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
편 451
 
5.8%
앞 368
 
4.7%
도 287
 
3.7%
상 259
 
3.3%
서 221
 
2.8%
정 218
 
2.8%
동 202
 
2.6%
문 182
 
2.3%
인 180
 
2.3%
로 143
 
1.8%
Other values (490) 5303
67.9%
Uppercase Letter
ValueCountFrequency (%)
S 28
17.4%
G 12
 
7.5%
T 12
 
7.5%
C 11
 
6.8%
M 10
 
6.2%
A 9
 
5.6%
J 8
 
5.0%
E 8
 
5.0%
K 8
 
5.0%
P 8
 
5.0%
Other values (15) 47
29.2%
Decimal Number
ValueCountFrequency (%)
1 82
27.3%
2 60
20.0%
0 58
19.3%
5 28
 
9.3%
3 15
 
5.0%
7 14
 
4.7%
6 13
 
4.3%
4 12
 
4.0%
8 10
 
3.3%
9 8
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
m 20
66.7%
e 3
 
10.0%
p 1
 
3.3%
o 1
 
3.3%
i 1
 
3.3%
n 1
 
3.3%
t 1
 
3.3%
y 1
 
3.3%
k 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 16
45.7%
, 7
20.0%
/ 6
 
17.1%
＆ 2
 
5.7%
& 2
 
5.7%
* 1
 
2.9%
※ 1
 
2.9%
Space Separator
ValueCountFrequency (%)
1333
99.9%
　 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 115
98.3%
[ 2
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 113
98.3%
] 2
 
1.7%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
→ 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7852
78.8%
Common 1917
 
19.2%
Latin 191
 
1.9%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
편 451
 
5.7%
앞 368
 
4.7%
도 287
 
3.7%
상 259
 
3.3%
서 221
 
2.8%
정 218
 
2.8%
동 202
 
2.6%
문 182
 
2.3%
인 180
 
2.3%
로 143
 
1.8%
Other values (490) 5341
68.0%
Latin
ValueCountFrequency (%)
S 28
14.7%
m 20
 
10.5%
G 12
 
6.3%
T 12
 
6.3%
C 11
 
5.8%
M 10
 
5.2%
A 9
 
4.7%
J 8
 
4.2%
E 8
 
4.2%
K 8
 
4.2%
Other values (24) 65
34.0%
Common
ValueCountFrequency (%)
1333
69.5%
( 115
 
6.0%
) 113
 
5.9%
1 82
 
4.3%
2 60
 
3.1%
0 58
 
3.0%
5 28
 
1.5%
. 16
 
0.8%
3 15
 
0.8%
7 14
 
0.7%
Other values (18) 83
 
4.3%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7813
78.4%
ASCII 2100
 
21.1%
None 43
 
0.4%
Punctuation 3
 
< 0.1%
CJK 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1333
63.5%
( 115
 
5.5%
) 113
 
5.4%
1 82
 
3.9%
2 60
 
2.9%
0 58
 
2.8%
S 28
 
1.3%
5 28
 
1.3%
m 20
 
1.0%
. 16
 
0.8%
Other values (46) 247
 
11.8%
Hangul
ValueCountFrequency (%)
편 451
 
5.8%
앞 368
 
4.7%
도 287
 
3.7%
상 259
 
3.3%
서 221
 
2.8%
정 218
 
2.8%
동 202
 
2.6%
문 182
 
2.3%
인 180
 
2.3%
로 143
 
1.8%
Other values (489) 5302
67.9%
None
ValueCountFrequency (%)
㈜ 39
90.7%
＆ 2
 
4.7%
　 2
 
4.7%
CJK
ValueCountFrequency (%)
家 1
100.0%
Punctuation
ValueCountFrequency (%)
‘ 1
33.3%
’ 1
33.3%
※ 1
33.3%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

안전센터명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
성서안전센터
207 
죽전안전센터
189 
다사안전센터
176 
대천안전센터
146 
매곡안전센터
80 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성서안전센터 207
25.9%
죽전안전센터 189
23.7%
다사안전센터 176
22.1%
대천안전센터 146
18.3%
매곡안전센터 80
 
10.0%

Length

2024-04-19T14:19:56.634481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:19:56.758114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성서안전센터 207
25.9%
죽전안전센터 189
23.7%
다사안전센터 176
22.1%
대천안전센터 146
18.3%
매곡안전센터 80
 
10.0%

보호틀유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size930.0 B
False
757 
True
 
41
ValueCountFrequency (%)
False 757
94.9%
True 41
 
5.1%
2024-04-19T14:19:56.865030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

사용가능여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size930.0 B
True
798 
ValueCountFrequency (%)
True 798
100.0%
2024-04-19T14:19:56.949631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

설치연도
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1999.609
Minimum1979
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-19T14:19:57.052772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1979
5-th percentile1990
Q11994
median1998
Q32002
95-th percentile2016.15
Maximum2021
Range42
Interquartile range (IQR)8

Descriptive statistics

Standard deviation8.3782906
Coefficient of variation (CV)0.0041899644
Kurtosis0.009173362
Mean1999.609
Median Absolute Deviation (MAD)4
Skewness0.67784344
Sum1595688
Variance70.195753
MonotonicityNot monotonic
2024-04-19T14:19:57.177425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
1998 97
 
12.2%
1994 87
 
10.9%
1995 63
 
7.9%
1999 49
 
6.1%
2002 49
 
6.1%
1997 46
 
5.8%
1990 43
 
5.4%
1993 41
 
5.1%
2014 35
 
4.4%
1996 31
 
3.9%
Other values (32) 257
32.2%
ValueCountFrequency (%)
1979 3
 
0.4%
1980 3
 
0.4%
1982 1
 
0.1%
1983 1
 
0.1%
1984 9
1.1%
1985 3
 
0.4%
1986 8
1.0%
1987 2
 
0.3%
1988 3
 
0.4%
1989 5
0.6%
ValueCountFrequency (%)
2021 3
 
0.4%
2020 5
 
0.6%
2019 12
 
1.5%
2018 7
 
0.9%
2017 13
 
1.6%
2016 14
 
1.8%
2015 4
 
0.5%
2014 35
4.4%
2013 10
 
1.3%
2012 3
 
0.4%

배관깊이
Real number (ℝ)

Distinct35
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7169173
Minimum1
Maximum9.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-19T14:19:57.300522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1.5
Q32
95-th percentile3.415
Maximum9.9
Range8.9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0031329
Coefficient of variation (CV)0.58426394
Kurtosis17.067682
Mean1.7169173
Median Absolute Deviation (MAD)0.5
Skewness3.3920689
Sum1370.1
Variance1.0062756
MonotonicityNot monotonic
2024-04-19T14:19:57.416245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1.0 255
32.0%
1.5 249
31.2%
2.0 107
13.4%
3.0 39
 
4.9%
1.8 24
 
3.0%
1.6 20
 
2.5%
1.2 15
 
1.9%
2.1 13
 
1.6%
2.5 12
 
1.5%
5.0 9
 
1.1%
Other values (25) 55
 
6.9%
ValueCountFrequency (%)
1.0 255
32.0%
1.2 15
 
1.9%
1.3 5
 
0.6%
1.5 249
31.2%
1.6 20
 
2.5%
1.7 5
 
0.6%
1.8 24
 
3.0%
2.0 107
13.4%
2.1 13
 
1.6%
2.3 3
 
0.4%
ValueCountFrequency (%)
9.9 2
0.3%
8.6 1
 
0.1%
6.6 1
 
0.1%
6.5 1
 
0.1%
6.0 1
 
0.1%
5.9 1
 
0.1%
5.6 1
 
0.1%
5.5 3
0.4%
5.4 1
 
0.1%
5.3 1
 
0.1%

출수압력
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9438346
Minimum0
Maximum7.3
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-19T14:19:57.537127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.5
Q14.1
median4.7
Q36.1
95-th percentile6.5
Maximum7.3
Range7.3
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.0962501
Coefficient of variation (CV)0.22174085
Kurtosis-0.40045878
Mean4.9438346
Median Absolute Deviation (MAD)0.7
Skewness0.059417832
Sum3945.18
Variance1.2017642
MonotonicityNot monotonic
2024-04-19T14:19:57.669683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
4.0 78
 
9.8%
4.2 62
 
7.8%
4.1 59
 
7.4%
6.2 58
 
7.3%
5.0 58
 
7.3%
6.5 52
 
6.5%
5.1 38
 
4.8%
6.3 33
 
4.1%
6.1 33
 
4.1%
4.3 32
 
4.0%
Other values (37) 295
37.0%
ValueCountFrequency (%)
0.0 2
 
0.3%
3.0 4
 
0.5%
3.1 3
 
0.4%
3.2 7
 
0.9%
3.3 6
 
0.8%
3.4 2
 
0.3%
3.5 27
3.4%
3.6 18
2.3%
3.7 16
2.0%
3.8 20
2.5%
ValueCountFrequency (%)
7.3 1
 
0.1%
7.2 3
 
0.4%
7.1 4
 
0.5%
7.0 8
 
1.0%
6.9 1
 
0.1%
6.8 5
 
0.6%
6.6 3
 
0.4%
6.54 2
 
0.3%
6.5 52
6.5%
6.4 18
 
2.3%

배관지름
Real number (ℝ)

Distinct10
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154.52381
Minimum80
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-04-19T14:19:57.795003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80
5-th percentile80
Q1100
median100
Q3200
95-th percentile300
Maximum500
Range420
Interquartile range (IQR)100

Descriptive statistics

Standard deviation79.80504
Coefficient of variation (CV)0.51645789
Kurtosis3.5032094
Mean154.52381
Median Absolute Deviation (MAD)20
Skewness1.7808108
Sum123310
Variance6368.8445
MonotonicityNot monotonic
2024-04-19T14:19:57.907078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
100 350
43.9%
150 166
20.8%
200 117
 
14.7%
300 65
 
8.1%
80 52
 
6.5%
250 24
 
3.0%
400 8
 
1.0%
500 7
 
0.9%
450 5
 
0.6%
350 4
 
0.5%
ValueCountFrequency (%)
80 52
 
6.5%
100 350
43.9%
150 166
20.8%
200 117
 
14.7%
250 24
 
3.0%
300 65
 
8.1%
350 4
 
0.5%
400 8
 
1.0%
450 5
 
0.6%
500 7
 
0.9%
ValueCountFrequency (%)
500 7
 
0.9%
450 5
 
0.6%
400 8
 
1.0%
350 4
 
0.5%
300 65
 
8.1%
250 24
 
3.0%
200 117
 
14.7%
150 166
20.8%
100 350
43.9%
80 52
 
6.5%

관할소방서명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
강서소방서
798 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강서소방서 798
100.0%

Length

2024-04-19T14:19:58.009702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:19:58.100424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강서소방서 798
100.0%

관할소방서전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
053-601-4676
798 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row053-601-4676
2nd row053-601-4676
3rd row053-601-4676
4th row053-601-4676
5th row053-601-4676

Common Values

ValueCountFrequency (%)
053-601-4676 798
100.0%

Length

2024-04-19T14:19:58.195291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:19:58.280621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
053-601-4676 798
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
Minimum2021-08-31 00:00:00
Maximum2021-08-31 00:00:00
2024-04-19T14:19:58.355299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:58.439495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-19T14:19:51.318580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:48.582055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.131201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.689596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.239342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.752675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:51.408713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:48.679205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.220990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.779984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.323753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.837567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:51.495170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:48.771303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.308753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.872504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.408285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.943769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:51.581811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:48.861158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.397046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.968297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.490026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:51.031048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:51.662670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:48.951592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.489810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.050157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.576771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:51.116148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:51.753978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.050056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:49.592048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.152760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:50.668398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:19:51.219419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:19:58.537823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형코드시군구명시군구코드위도경도안전센터명보호틀유무설치연도배관깊이출수압력배관지름
시설유형코드1.0000.1630.1630.0630.5730.3800.1280.5940.1200.7900.363
시군구명0.1631.0001.0000.7890.9320.6750.1250.6830.3610.2720.032
시군구코드0.1631.0001.0000.7890.9320.6750.1250.6830.3610.2720.032
위도0.0630.7890.7891.0000.7860.4950.2070.3870.2580.3090.100
경도0.5730.9320.9320.7861.0000.8250.2660.6500.4250.5220.385
안전센터명0.3800.6750.6750.4950.8251.0000.1390.8450.4370.7080.535
보호틀유무0.1280.1250.1250.2070.2660.1391.0000.3380.1250.0560.000
설치연도0.5940.6830.6830.3870.6500.8450.3381.0000.2620.4380.373
배관깊이0.1200.3610.3610.2580.4250.4370.1250.2621.0000.1720.523
출수압력0.7900.2720.2720.3090.5220.7080.0560.4380.1721.0000.436
배관지름0.3630.0320.0320.1000.3850.5350.0000.3730.5230.4361.000
2024-04-19T14:19:58.662410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형코드보호틀유무안전센터명시군구코드시군구명
시설유형코드1.0000.2110.3110.2690.269
보호틀유무0.2111.0000.1700.0800.080
안전센터명0.3110.1701.0000.8060.806
시군구코드0.2690.0800.8061.0000.996
시군구명0.2690.0800.8060.9961.000
2024-04-19T14:19:59.078161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치연도배관깊이출수압력배관지름시설유형코드시군구명시군구코드안전센터명보호틀유무
위도1.000-0.2390.2090.156-0.385-0.1570.0590.5800.5800.4240.137
경도-0.2391.000-0.466-0.153-0.115-0.0110.2830.7670.7670.7230.188
설치연도0.209-0.4661.0000.055-0.1160.0960.4340.5300.5300.5070.223
배관깊이0.156-0.1530.0551.000-0.0260.2740.0520.3590.3590.2700.124
출수압력-0.385-0.115-0.116-0.0261.000-0.2230.7360.2900.2900.5570.060
배관지름-0.157-0.0110.0960.274-0.2231.0000.1710.0320.0320.3440.000
시설유형코드0.0590.2830.4340.0520.7360.1711.0000.2690.2690.3110.211
시군구명0.5800.7670.5300.3590.2900.0320.2691.0000.9960.8060.080
시군구코드0.5800.7670.5300.3590.2900.0320.2690.9961.0000.8060.080
안전센터명0.4240.7230.5070.2700.5570.3440.3110.8060.8061.0000.170
보호틀유무0.1370.1880.2230.1240.0600.0000.2110.0800.0800.1701.000

Missing values

2024-04-19T14:19:52.193266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:19:52.417817image/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

시설번호시설유형코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도상세위치안전센터명보호틀유무사용가능여부설치연도배관깊이출수압력배관지름관할소방서명관할소방서전화번호데이터기준일자
0상8-1-11대구광역시달서구27290대구광역시 달서구 달구벌대로 203길 3대구광역시 달서구 호산동 984-435.853551128.477962산호경로당앞다사안전센터NY20133.04.1150강서소방서053-601-46762021-08-31
1상8-1-21대구광역시달성군27710대구광역시 달성군 다사읍 세천로10길 42대구광역시 달성군 다사읍 세천리 1606-635.870394128.474796나무트레이드 앞다사안전센터NY20022.04.0100강서소방서053-601-46762021-08-31
2하8-1-32대구광역시달서구27290대구광역시 달서구 호산동로35북길 79대구광역시 달서구 호산동 37135.851912128.482312미헤어라인 북편다사안전센터NY19793.04.0200강서소방서053-601-46762021-08-31
3하8-1-42대구광역시달서구27290대구광역시 달서구 호산동로36북길 54대구광역시 달서구 호산동 357-3235.851446128.487581재광빌라 앞다사안전센터NY19881.54.1150강서소방서053-601-46762021-08-31
4상8-1-51대구광역시달서구27290대구광역시 달서구 달서대로109안길 20대구광역시 달서구 호산동 386-1935.849967128.488364건풍관 동편다사안전센터NY20013.04.0150강서소방서053-601-46762021-08-31
5하8-1-62대구광역시달서구27290대구광역시 달서구 호산동로36길 45대구광역시 달서구 호산동 357-4635.850825128.488342태평빌라트 동편다사안전센터NY20011.54.1150강서소방서053-601-46762021-08-31
6상8-1-71대구광역시달서구27290대구광역시 달서구 달서대로109안길 28대구광역시 달서구 호산동 386-1435.849959128.487407배드민턴용품 토털브랜드샾 앞다사안전센터NY20011.54.1300강서소방서053-601-46762021-08-31
7상8-1-81대구광역시달서구27290대구광역시 달서구 호산동로 166대구광역시 달서구 호산동 38635.849969128.485963선산곱창 앞다사안전센터NY20012.04.1300강서소방서053-601-46762021-08-31
8상8-1-91대구광역시달서구27290대구광역시 달서구 호산동로35 남길 33대구광역시 달서구 호산동 38835.849963128.484309커피아리 앞다사안전센터NY20013.04.0450강서소방서053-601-46762021-08-31
9상8-1-101대구광역시달서구27290대구광역시 달서구 달서대로109안길 74대구광역시 달서구 호산동 39035.849957128.482356CU편의점 앞다사안전센터NY20012.04.0450강서소방서053-601-46762021-08-31
시설번호시설유형코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도상세위치안전센터명보호틀유무사용가능여부설치연도배관깊이출수압력배관지름관할소방서명관할소방서전화번호데이터기준일자
788상8-5-711대구광역시달성군27710대구광역시 달성군 하빈남로 278대구광역시 달성군 봉촌리 22335.860906128.405257봉천교 동편매곡안전센터YY20191.54.0100강서소방서053-601-46762021-08-31
789상8-5-721대구광역시달성군27710대구광역시 달성군 다사읍 다사로104대구광역시 달성군 매곡리 455-235.869692128.457979동양농기 앞매곡안전센터NY20191.54.0100강서소방서053-601-46762021-08-31
790상8-5-731대구광역시달성군27710대구광역시 달성군 하빈면 하빈로94길31대구광역시 달성군 현내리 419-635.90428128.448379성신금속 남편매곡안전센터YY20191.54.0100강서소방서053-601-46762021-08-31
791상8-5-741대구광역시달성군27710대구광역시 달성군 하빈면 하빈로 90길 9대구광역시 달성군 현내리 49435.902885128.446568현내2리 마을회관 북편매곡안전센터YY20191.54.0100강서소방서053-601-46762021-08-31
792상8-5-751대구광역시달성군27710대구광역시 달성군 하빈면 하빈남로 354대구광역시 달성군 봉촌리 81235.861206128.397507태원철강 동편 사거리 전봇대 옆매곡안전센터NY20201.54.1100강서소방서053-601-46762021-08-31
793상8-5-761대구광역시달성군27710대구광역시 달성군 하빈면 하산2길 6대구광역시 달성군 하산리 66735.882158128.406979성안텍스타일 버스정류장 옆매곡안전센터NY20201.54.3150강서소방서053-601-46762021-08-31
794상8-5-771대구광역시달성군27710대구광역시 달성군 하빈면 하빈로 880대구광역시 달성군 하빈면 대평리 20235.93563128.467341올리브 헤어 남동편매곡안전센터NY20051.54.180강서소방서053-601-46762021-08-31
795상8-5-781대구광역시달성군27710대구광역시 달성군 하빈면 묘동길 91대구광역시 달성군 하빈면 묘리 906-335.898287128.421866성당공업 남동편매곡안전센터NY20211.54.1150강서소방서053-601-46762021-08-31
796상8-5-791대구광역시달성군27710대구광역시 달성군 하빈면 기곡길 224대구광역시 달성군 하빈면 기곡리 37-235.931186128.439992기곡 버스정류장 옆매곡안전센터NY20211.54.5100강서소방서053-601-46762021-08-31
797상8-5-801대구광역시달성군27710대구광역시 달성군 하빈면 하빈로 533대구광역시 달성군 하빈면 현내리 134-235.91089128.446845현내1리 경로당 앞 버스정류장매곡안전센터NY20211.54.3200강서소방서053-601-46762021-08-31