Overview

Dataset statistics

Number of variables8
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory76.7 B

Variable types

Numeric6
Categorical1
Text1

Dataset

Description순번,서소코드,방면코드,중앙점X좌표,중앙점Y좌표,서소이름,위도,경도
Author서울종합방재센터 전산통신과
URLhttps://data.seoul.go.kr/dataList/OA-12735/S/1/datasetView.do

Alerts

순번 is highly overall correlated with 서소코드High correlation
서소코드 is highly overall correlated with 순번High correlation
중앙점X좌표 is highly overall correlated with 경도High correlation
중앙점Y좌표 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 중앙점Y좌표High correlation
경도 is highly overall correlated with 중앙점X좌표High correlation
순번 has unique valuesUnique
서소코드 has unique valuesUnique
중앙점X좌표 has unique valuesUnique
중앙점Y좌표 has unique valuesUnique
서소이름 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
중앙점X좌표 has 1 (4.3%) zerosZeros
중앙점Y좌표 has 1 (4.3%) zerosZeros

Reproduction

Analysis started2023-12-11 09:06:18.719192
Analysis finished2023-12-11 09:06:22.976042
Duration4.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T18:06:23.054121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2023-12-11T18:06:23.215578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

서소코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82236
Minimum71236
Maximum93236
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T18:06:23.347222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum71236
5-th percentile72336
Q176736
median82236
Q387736
95-th percentile92136
Maximum93236
Range22000
Interquartile range (IQR)11000

Descriptive statistics

Standard deviation6782.33
Coefficient of variation (CV)0.082473977
Kurtosis-1.2
Mean82236
Median Absolute Deviation (MAD)6000
Skewness0
Sum1891428
Variance46000000
MonotonicityNot monotonic
2023-12-11T18:06:23.486304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
76236 1
 
4.3%
75236 1
 
4.3%
72236 1
 
4.3%
93236 1
 
4.3%
84236 1
 
4.3%
92236 1
 
4.3%
91236 1
 
4.3%
90236 1
 
4.3%
89236 1
 
4.3%
87236 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
71236 1
4.3%
72236 1
4.3%
73236 1
4.3%
74236 1
4.3%
75236 1
4.3%
76236 1
4.3%
77236 1
4.3%
78236 1
4.3%
79236 1
4.3%
80236 1
4.3%
ValueCountFrequency (%)
93236 1
4.3%
92236 1
4.3%
91236 1
4.3%
90236 1
4.3%
89236 1
4.3%
88236 1
4.3%
87236 1
4.3%
86236 1
4.3%
85236 1
4.3%
84236 1
4.3%

방면코드
Categorical

Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
2
7 
3
6 
1
6 
4
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 7
30.4%
3 6
26.1%
1 6
26.1%
4 4
17.4%

Length

2023-12-11T18:06:23.640241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:23.783127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7
30.4%
3 6
26.1%
1 6
26.1%
4 4
17.4%

중앙점X좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190433.92
Minimum0
Maximum212941.3
Zeros1
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T18:06:23.916263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile184624.89
Q1192784.04
median198315.52
Q3204966.2
95-th percentile209938.79
Maximum212941.3
Range212941.3
Interquartile range (IQR)12182.16

Descriptive statistics

Standard deviation42179.252
Coefficient of variation (CV)0.22149022
Kurtosis21.380719
Mean190433.92
Median Absolute Deviation (MAD)6162.1925
Skewness-4.5513909
Sum4379980.2
Variance1.7790893 × 109
MonotonicityNot monotonic
2023-12-11T18:06:24.083046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
192393.0395 1
 
4.3%
204477.7145 1
 
4.3%
199487.0285 1
 
4.3%
0.0 1
 
4.3%
201572.0815 1
 
4.3%
194316.9245 1
 
4.3%
195074.5455 1
 
4.3%
208297.55 1
 
4.3%
187284.9225 1
 
4.3%
195029.548 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
0.0 1
4.3%
184329.3325 1
4.3%
187284.9225 1
4.3%
190632.75186 1
4.3%
191941.166 1
4.3%
192393.0395 1
4.3%
193175.0415 1
4.3%
194316.9245 1
4.3%
195029.548 1
4.3%
195074.5455 1
4.3%
ValueCountFrequency (%)
212941.3045 1
4.3%
210121.155 1
4.3%
208297.55 1
4.3%
206807.137 1
4.3%
205874.54745 1
4.3%
205454.686 1
4.3%
204477.7145 1
4.3%
203344.759 1
4.3%
202052.4675 1
4.3%
201572.0815 1
4.3%

중앙점Y좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean430845.88
Minimum0
Maximum461738.69
Zeros1
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T18:06:24.234172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile440782.09
Q1444583.32
median449980.71
Q3454450.56
95-th percentile461306.36
Maximum461738.69
Range461738.69
Interquartile range (IQR)9867.2393

Descriptive statistics

Standard deviation94112.902
Coefficient of variation (CV)0.21843751
Kurtosis22.78647
Mean430845.88
Median Absolute Deviation (MAD)5113.7265
Skewness-4.7637359
Sum9909455.2
Variance8.8572383 × 109
MonotonicityNot monotonic
2023-12-11T18:06:24.406205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
446800.6215 1
 
4.3%
453806.678 1
 
4.3%
450935.422 1
 
4.3%
0.0 1
 
4.3%
461722.5795 1
 
4.3%
453703.0735 1
 
4.3%
444117.2895 1
 
4.3%
455094.4355 1
 
4.3%
447515.498 1
 
4.3%
440666.05 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
0.0 1
4.3%
440666.05 1
4.3%
441826.441 1
4.3%
441946.916 1
4.3%
444060.6735 1
4.3%
444117.2895 1
4.3%
445049.34545 1
4.3%
446800.6215 1
4.3%
447515.498 1
4.3%
447956.789 1
4.3%
ValueCountFrequency (%)
461738.689 1
4.3%
461722.5795 1
4.3%
457560.4345 1
4.3%
456378.766 1
4.3%
455503.4815 1
4.3%
455094.4355 1
4.3%
453806.678 1
4.3%
453703.0735 1
4.3%
451818.06 1
4.3%
451421.9075 1
4.3%

서소이름
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T18:06:24.656041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.1304348
Min length5

Characters and Unicode

Total characters118
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row영등포소방서
2nd row동대문소방서
3rd row용산소방서
4th row광진소방서
5th row종로소방서
ValueCountFrequency (%)
영등포소방서 1
 
4.3%
노원소방서 1
 
4.3%
강북소방서 1
 
4.3%
도봉소방서 1
 
4.3%
서대문소방서 1
 
4.3%
동작소방서 1
 
4.3%
중랑소방서 1
 
4.3%
양천소방서 1
 
4.3%
관악소방서 1
 
4.3%
송파소방서 1
 
4.3%
Other values (13) 13
56.5%
2023-12-11T18:06:25.049326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 26
22.0%
소 23
19.5%
방 23
19.5%
강 4
 
3.4%
동 3
 
2.5%
포 2
 
1.7%
대 2
 
1.7%
문 2
 
1.7%
북 2
 
1.7%
중 2
 
1.7%
Other values (28) 29
24.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 26
22.0%
소 23
19.5%
방 23
19.5%
강 4
 
3.4%
동 3
 
2.5%
포 2
 
1.7%
대 2
 
1.7%
문 2
 
1.7%
북 2
 
1.7%
중 2
 
1.7%
Other values (28) 29
24.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 26
22.0%
소 23
19.5%
방 23
19.5%
강 4
 
3.4%
동 3
 
2.5%
포 2
 
1.7%
대 2
 
1.7%
문 2
 
1.7%
북 2
 
1.7%
중 2
 
1.7%
Other values (28) 29
24.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 26
22.0%
소 23
19.5%
방 23
19.5%
강 4
 
3.4%
동 3
 
2.5%
포 2
 
1.7%
대 2
 
1.7%
문 2
 
1.7%
북 2
 
1.7%
중 2
 
1.7%
Other values (28) 29
24.6%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.557893
Minimum37.4654
Maximum37.665859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T18:06:25.235367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.4654
5-th percentile37.475938
Q137.512747
median37.557945
Q337.597238
95-th percentile37.654433
Maximum37.665859
Range0.2004587
Interquartile range (IQR)0.0844907

Descriptive statistics

Standard deviation0.05839285
Coefficient of variation (CV)0.0015547425
Kurtosis-0.81274072
Mean37.557893
Median Absolute Deviation (MAD)0.0411552
Skewness0.195643
Sum863.83153
Variance0.003409725
MonotonicityNot monotonic
2023-12-11T18:06:25.381576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
37.5206414 1
 
4.3%
37.5837941 1
 
4.3%
37.5579449 1
 
4.3%
37.6469903 1
 
4.3%
37.6658587 1
 
4.3%
37.5828688 1
 
4.3%
37.4965073 1
 
4.3%
37.5953753 1
 
4.3%
37.5270363 1
 
4.3%
37.4654 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
37.4654 1
4.3%
37.4758251 1
4.3%
37.4769532 1
4.3%
37.4959815 1
4.3%
37.4965073 1
4.3%
37.5048526 1
4.3%
37.5206414 1
4.3%
37.5270363 1
4.3%
37.5311061 1
4.3%
37.5481447 1
4.3%
ValueCountFrequency (%)
37.6658587 1
4.3%
37.6552597 1
4.3%
37.6469903 1
4.3%
37.6176107 1
4.3%
37.6069889 1
4.3%
37.5991001 1
4.3%
37.5953753 1
4.3%
37.5837941 1
4.3%
37.5828688 1
4.3%
37.5657621 1
4.3%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99124
Minimum126.82266
Maximum127.14644
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T18:06:25.540011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.82266
5-th percentile126.8576
Q1126.92919
median126.9942
Q3127.05621
95-th percentile127.11242
Maximum127.14644
Range0.3237843
Interquartile range (IQR)0.12702025

Descriptive statistics

Standard deviation0.086097969
Coefficient of variation (CV)0.00067798354
Kurtosis-0.70728214
Mean126.99124
Median Absolute Deviation (MAD)0.0675376
Skewness-0.17208943
Sum2920.7985
Variance0.0074128602
MonotonicityNot monotonic
2023-12-11T18:06:25.676568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
126.9139239 1
 
4.3%
127.0506879 1
 
4.3%
126.9941953 1
 
4.3%
127.0147136 1
 
4.3%
127.0317954 1
 
4.3%
126.9356676 1
 
4.3%
126.9443079 1
 
4.3%
127.093966 1
 
4.3%
126.8561354 1
 
4.3%
126.9438067 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
126.8226558 1
4.3%
126.8561354 1
4.3%
126.8707748 1
4.3%
126.9087792 1
4.3%
126.9139239 1
4.3%
126.9227127 1
4.3%
126.9356676 1
4.3%
126.9438067 1
4.3%
126.9443079 1
4.3%
126.9809422 1
4.3%
ValueCountFrequency (%)
127.1464401 1
4.3%
127.1144708 1
4.3%
127.093966 1
4.3%
127.0771199 1
4.3%
127.0664088 1
4.3%
127.0617329 1
4.3%
127.0506879 1
4.3%
127.0378001 1
4.3%
127.0317954 1
4.3%
127.0232435 1
4.3%

Interactions

2023-12-11T18:06:22.049191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:18.983922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.514516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.032196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.705883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:21.290616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:22.150481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.057719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.594985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.151780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.798880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:21.416258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:22.257823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.141523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.676911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.263827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.877185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:21.524145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:22.357487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.230200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.755424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.404403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.963101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:21.632325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:22.477414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.330088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.833186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.479955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:21.062833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:21.765073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:22.608934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.425202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:19.924637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:20.599221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:21.178354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:21.907140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:06:25.818910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번서소코드방면코드중앙점X좌표중앙점Y좌표서소이름위도경도
순번1.0000.9410.0000.0000.0001.0000.5860.610
서소코드0.9411.0000.0000.0000.0001.0000.3790.157
방면코드0.0000.0001.0000.3940.0001.0000.4090.747
중앙점X좌표0.0000.0000.3941.0001.0001.0000.0000.772
중앙점Y좌표0.0000.0000.0001.0001.0001.0000.0000.000
서소이름1.0001.0001.0001.0001.0001.0001.0001.000
위도0.5860.3790.4090.0000.0001.0001.0000.000
경도0.6100.1570.7470.7720.0001.0000.0001.000
2023-12-11T18:06:26.255283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번서소코드중앙점X좌표중앙점Y좌표위도경도방면코드
순번1.0000.708-0.129-0.1370.0880.0040.000
서소코드0.7081.000-0.184-0.261-0.029-0.0440.000
중앙점X좌표-0.129-0.1841.0000.2460.0220.9210.368
중앙점Y좌표-0.137-0.2610.2461.0000.7920.1340.000
위도0.088-0.0290.0220.7921.0000.1610.195
경도0.004-0.0440.9210.1340.1611.0000.444
방면코드0.0000.0000.3680.0000.1950.4441.000

Missing values

2023-12-11T18:06:22.766551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:06:22.918838image/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

순번서소코드방면코드중앙점X좌표중앙점Y좌표서소이름위도경도
01762363192393.0395446800.6215영등포소방서37.520641126.913924
12752362204477.7145453806.678동대문소방서37.583794127.050688
23742361198315.522447956.789용산소방서37.531106126.980942
34732362205454.686449851.3745광진소방서37.548145127.061733
45712361197056.96972455503.4815종로소방서37.5991126.986175
56782361193175.0415457560.4345은평소방서37.617611126.922713
67772362202052.4675456378.766성북소방서37.606989127.023244
78792364205874.54745444060.6735강남소방서37.495981127.066409
89802364203344.759441946.916서초소방서37.476953127.0378
910812363184329.3325451818.06강서소방서37.565762126.822656
순번서소코드방면코드중앙점X좌표중앙점Y좌표서소이름위도경도
1314852363190632.75186441826.441구로소방서37.475825126.870775
1415882364210121.155445049.34545송파소방서37.504853127.114471
1516872363195029.548440666.05관악소방서37.4654126.943807
1617892363187284.9225447515.498양천소방서37.527036126.856135
1718902362208297.55455094.4355중랑소방서37.595375127.093966
1819912363195074.5455444117.2895동작소방서37.496507126.944308
1920922361194316.9245453703.0735서대문소방서37.582869126.935668
2021842362201572.0815461722.5795도봉소방서37.665859127.031795
21229323620.00.0강북소방서37.64699127.014714
2223722361199487.0285450935.422중부소방서37.557945126.994195