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,X좌표,Y좌표
Author서울종합방재센터 전산통신과
URLhttps://data.seoul.go.kr/dataList/OA-12734/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 X좌표High correlation
중앙점Y좌표 is highly overall correlated with Y좌표High correlation
X좌표 is highly overall correlated with 중앙점X좌표High correlation
Y좌표 is highly overall correlated with 중앙점Y좌표High correlation
순번 has unique valuesUnique
서소코드 has unique valuesUnique
중앙점X좌표 has unique valuesUnique
중앙점Y좌표 has unique valuesUnique
서소이름 has unique valuesUnique
X좌표 has unique valuesUnique
Y좌표 has unique valuesUnique
중앙점X좌표 has 1 (4.3%) zerosZeros
중앙점Y좌표 has 1 (4.3%) zerosZeros

Reproduction

Analysis started2023-12-11 06:10:30.605006
Analysis finished2023-12-11 06:10:33.919515
Duration3.31 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
2023-12-11T15:10:33.984321image/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
2023-12-11T15:10:34.102184image/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
2023-12-11T15:10:34.226714image/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
2023-12-11T15:10:34.365609image/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

2023-12-11T15:10:34.506858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:10:34.616066image/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
2023-12-11T15:10:34.733538image/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
2023-12-11T15:10:34.857333image/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
2023-12-11T15:10:34.978915image/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
2023-12-11T15:10:35.114525image/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
2023-12-11T15:10:35.351466image/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%
2023-12-11T15:10:35.794617image/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%

X좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean199224.98
Minimum184329.33
Maximum212941.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T15:10:35.966170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184329.33
5-th percentile187413.5
Q1193745.98
median199487.03
Q3204966.2
95-th percentile209938.79
Maximum212941.3
Range28611.972
Interquartile range (IQR)11220.217

Descriptive statistics

Standard deviation7608.8298
Coefficient of variation (CV)0.038192148
Kurtosis-0.70712349
Mean199224.98
Median Absolute Deviation (MAD)5967.657
Skewness-0.17210241
Sum4582174.5
Variance57894290
MonotonicityNot monotonic
2023-12-11T15:10:36.402807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
192393.04 1
 
4.3%
204477.715 1
 
4.3%
199487.029 1
 
4.3%
201299.277 1
 
4.3%
202805.836 1
 
4.3%
194316.925 1
 
4.3%
195074.546 1
 
4.3%
208297.55 1
 
4.3%
187284.923 1
 
4.3%
195029.548 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
184329.333 1
4.3%
187284.923 1
4.3%
188570.725 1
4.3%
191941.166 1
4.3%
192393.04 1
4.3%
193175.042 1
4.3%
194316.925 1
4.3%
195029.548 1
4.3%
195074.546 1
4.3%
198315.522 1
4.3%
ValueCountFrequency (%)
212941.305 1
4.3%
210121.155 1
4.3%
208297.55 1
4.3%
206807.137 1
4.3%
205874.547 1
4.3%
205454.686 1
4.3%
204477.715 1
4.3%
203344.759 1
4.3%
202805.836 1
4.3%
202052.468 1
4.3%

Y좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean450933.23
Minimum440666.05
Maximum462913.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T15:10:36.553052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440666.05
5-th percentile441838.49
Q1445924.98
median450935.42
Q3455298.96
95-th percentile461646.68
Maximum462913.04
Range22246.989
Interquartile range (IQR)9373.9755

Descriptive statistics

Standard deviation6480.1405
Coefficient of variation (CV)0.01437051
Kurtosis-0.81260538
Mean450933.23
Median Absolute Deviation (MAD)4568.06
Skewness0.19494325
Sum10371464
Variance41992221
MonotonicityNot monotonic
2023-12-11T15:10:36.704031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
446800.622 1
 
4.3%
453806.678 1
 
4.3%
450935.422 1
 
4.3%
460818.584 1
 
4.3%
462913.039 1
 
4.3%
453703.074 1
 
4.3%
444117.29 1
 
4.3%
455094.436 1
 
4.3%
447515.498 1
 
4.3%
440666.05 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
440666.05 1
4.3%
441826.441 1
4.3%
441946.916 1
4.3%
444060.674 1
4.3%
444117.29 1
4.3%
445049.345 1
4.3%
446800.622 1
4.3%
447515.498 1
4.3%
447956.789 1
4.3%
449851.375 1
4.3%
ValueCountFrequency (%)
462913.039 1
4.3%
461738.689 1
4.3%
460818.584 1
4.3%
457560.435 1
4.3%
456378.766 1
4.3%
455503.482 1
4.3%
455094.436 1
4.3%
453806.678 1
4.3%
453703.074 1
4.3%
451818.06 1
4.3%

Interactions

2023-12-11T15:10:33.222384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:30.845581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.288177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.714138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.207373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.693815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:33.312572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:30.920578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.360265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.799509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.286745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.784709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:33.390797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:30.992687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.428295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.881963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.366304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.875883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:33.474735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.076866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.497541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.961617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.439939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.969288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:33.556859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.148502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.569110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.037552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.514287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:33.060067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:33.642796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.221243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:31.640791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.132764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:32.601731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:10:33.140428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T15:10:36.828927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번서소코드방면코드중앙점X좌표중앙점Y좌표서소이름X좌표Y좌표
순번1.0000.9410.0000.0000.0001.0000.4850.591
서소코드0.9411.0000.0000.0000.0001.0000.2680.366
방면코드0.0000.0001.0000.3940.0001.0000.7210.331
중앙점X좌표0.0000.0000.3941.0001.0001.0000.9190.000
중앙점Y좌표0.0000.0000.0001.0001.0001.0000.0000.000
서소이름1.0001.0001.0001.0001.0001.0001.0001.000
X좌표0.4850.2680.7210.9190.0001.0001.0000.000
Y좌표0.5910.3660.3310.0000.0001.0000.0001.000
2023-12-11T15:10:36.955483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번서소코드중앙점X좌표중앙점Y좌표X좌표Y좌표방면코드
순번1.0000.708-0.129-0.1370.0040.0880.000
서소코드0.7081.000-0.184-0.261-0.044-0.0290.000
중앙점X좌표-0.129-0.1841.0000.2460.9210.0220.368
중앙점Y좌표-0.137-0.2610.2461.0000.1340.7920.000
X좌표0.004-0.0440.9210.1341.0000.1610.444
Y좌표0.088-0.0290.0220.7920.1611.0000.195
방면코드0.0000.0000.3680.0000.4440.1951.000

Missing values

2023-12-11T15:10:33.746376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T15:10:33.873537image/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

순번서소코드방면코드중앙점X좌표중앙점Y좌표서소이름X좌표Y좌표
01762363192393.0395446800.6215영등포소방서192393.04446800.622
12752362204477.7145453806.678동대문소방서204477.715453806.678
23742361198315.522447956.789용산소방서198315.522447956.789
34732362205454.686449851.3745광진소방서205454.686449851.375
45712361197056.96972455503.4815종로소방서198780.238455503.482
56782361193175.0415457560.4345은평소방서193175.042457560.435
67772362202052.4675456378.766성북소방서202052.468456378.766
78792364205874.54745444060.6735강남소방서205874.547444060.674
89802364203344.759441946.916서초소방서203344.759441946.916
910812363184329.3325451818.06강서소방서184329.333451818.06
순번서소코드방면코드중앙점X좌표중앙점Y좌표서소이름X좌표Y좌표
1314852363190632.75186441826.441구로소방서188570.725441826.441
1415882364210121.155445049.34545송파소방서210121.155445049.345
1516872363195029.548440666.05관악소방서195029.548440666.05
1617892363187284.9225447515.498양천소방서187284.923447515.498
1718902362208297.55455094.4355중랑소방서208297.55455094.436
1819912363195074.5455444117.2895동작소방서195074.546444117.29
1920922361194316.9245453703.0735서대문소방서194316.925453703.074
2021842362201572.0815461722.5795도봉소방서202805.836462913.039
21229323620.00.0강북소방서201299.277460818.584
2223722361199487.0285450935.422중부소방서199487.029450935.422