Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells4254
Missing cells (%)4.3%
Duplicate rows898
Duplicate rows (%)9.0%
Total size in memory878.9 KiB
Average record size in memory90.0 B

Variable types

Categorical6
Text2
Numeric1
Boolean1

Dataset

Description경기도의 구급활동 현황입니다. 출동소방서명, 신고시각, 접수경로, 현장거리, 환자연령 등의 정보를 제공합니다. ※ Sheet탭에서는 최신 1개년 데이터를 확인하실 수 있으며, 전체 데이터는 File탭에서 내려받을 수 있는 파일의 형태로 제공됩니다.
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=SE00GA6F273B8PIJ9N8412495661&infSeq=1

Alerts

집계년도 has constant value ""Constant
Dataset has 898 (9.0%) duplicate rowsDuplicates
시군명 is highly overall correlated with 출동소방서High correlation
출동소방서 is highly overall correlated with 시군명High correlation
외국인유무 is highly overall correlated with 국적High correlation
국적 is highly overall correlated with 외국인유무High correlation
외국인유무 is highly imbalanced (88.6%)Imbalance
국적 is highly imbalanced (96.9%)Imbalance
환자연령대 has 2727 (27.3%) missing valuesMissing
구급처종명 has 1527 (15.3%) missing valuesMissing
환자연령대 has 239 (2.4%) zerosZeros

Reproduction

Analysis started2024-03-12 23:27:00.810387
Analysis finished2024-03-12 23:27:01.898960
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 10000
100.0%

Length

2024-03-13T08:27:01.946254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:02.013063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10000
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
안산시
793 
수원시
751 
고양시
683 
성남시
664 
용인시
 
600
Other values (26)
6509 

Length

Max length4
Median length3
Mean length3.0934
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동두천시
2nd row가평군
3rd row남양주시
4th row수원시
5th row안성시

Common Values

ValueCountFrequency (%)
안산시 793
 
7.9%
수원시 751
 
7.5%
고양시 683
 
6.8%
성남시 664
 
6.6%
용인시 600
 
6.0%
부천시 533
 
5.3%
화성시 531
 
5.3%
남양주시 458
 
4.6%
평택시 408
 
4.1%
의정부시 336
 
3.4%
Other values (21) 4243
42.4%

Length

2024-03-13T08:27:02.081112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안산시 793
 
7.9%
수원시 751
 
7.5%
고양시 683
 
6.8%
성남시 664
 
6.6%
용인시 600
 
6.0%
부천시 533
 
5.3%
화성시 531
 
5.3%
남양주시 458
 
4.6%
평택시 408
 
4.1%
의정부시 336
 
3.4%
Other values (21) 4243
42.4%

출동소방서
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
안산소방서
793 
용인소방서
 
600
부천소방서
 
533
화성소방서
 
531
남양주소방서
 
458
Other values (30)
7085 

Length

Max length7
Median length5
Mean length5.1758
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동두천소방서
2nd row가평소방서
3rd row남양주소방서
4th row수원소방서
5th row안성소방서

Common Values

ValueCountFrequency (%)
안산소방서 793
 
7.9%
용인소방서 600
 
6.0%
부천소방서 533
 
5.3%
화성소방서 531
 
5.3%
남양주소방서 458
 
4.6%
수원남부소방서 412
 
4.1%
성남소방서 371
 
3.7%
일산소방서 365
 
3.6%
수원소방서 339
 
3.4%
의정부소방서 336
 
3.4%
Other values (25) 5262
52.6%

Length

2024-03-13T08:27:02.175795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안산소방서 793
 
7.9%
용인소방서 600
 
6.0%
부천소방서 533
 
5.3%
화성소방서 531
 
5.3%
남양주소방서 458
 
4.6%
수원남부소방서 412
 
4.1%
성남소방서 371
 
3.7%
일산소방서 365
 
3.6%
수원소방서 339
 
3.4%
의정부소방서 336
 
3.4%
Other values (25) 5262
52.6%

출동안전센터
Text

Distinct205
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:27:02.363543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.2678
Min length5

Characters and Unicode

Total characters82678
Distinct characters154
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row소요119안전센터
2nd row북면119지역대
3rd row화도119안전센터
4th row영통119안전센터
5th row119구조대
ValueCountFrequency (%)
119구조대 562
 
5.6%
상록수출동대 409
 
4.1%
오전출동대 213
 
2.1%
금정출동대 186
 
1.9%
흥선119안전센터 157
 
1.6%
매산119안전센터 139
 
1.4%
정자119안전센터 136
 
1.4%
신장119안전센터 133
 
1.3%
신흥119안전센터 118
 
1.2%
119구급대 112
 
1.1%
Other values (195) 7835
78.3%
2024-03-13T08:27:02.660883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17280
20.9%
9 8640
10.5%
전 7683
 
9.3%
안 7592
 
9.2%
터 7342
 
8.9%
센 7342
 
8.9%
대 2931
 
3.5%
지 1338
 
1.6%
동 1263
 
1.5%
역 1206
 
1.5%
Other values (144) 20061
24.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56758
68.6%
Decimal Number 25920
31.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 7683
13.5%
안 7592
13.4%
터 7342
12.9%
센 7342
12.9%
대 2931
 
5.2%
지 1338
 
2.4%
동 1263
 
2.2%
역 1206
 
2.1%
구 897
 
1.6%
수 850
 
1.5%
Other values (142) 18314
32.3%
Decimal Number
ValueCountFrequency (%)
1 17280
66.7%
9 8640
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56758
68.6%
Common 25920
31.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 7683
13.5%
안 7592
13.4%
터 7342
12.9%
센 7342
12.9%
대 2931
 
5.2%
지 1338
 
2.4%
동 1263
 
2.2%
역 1206
 
2.1%
구 897
 
1.6%
수 850
 
1.5%
Other values (142) 18314
32.3%
Common
ValueCountFrequency (%)
1 17280
66.7%
9 8640
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56758
68.6%
ASCII 25920
31.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17280
66.7%
9 8640
33.3%
Hangul
ValueCountFrequency (%)
전 7683
13.5%
안 7592
13.4%
터 7342
12.9%
센 7342
12.9%
대 2931
 
5.2%
지 1338
 
2.4%
동 1263
 
2.2%
역 1206
 
2.1%
구 897
 
1.6%
수 850
 
1.5%
Other values (142) 18314
32.3%

환자연령대
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.2%
Missing2727
Missing (%)27.3%
Infinite0
Infinite (%)0.0%
Mean50.79197
Minimum0
Maximum100
Zeros239
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:27:02.761031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q130
median50
Q370
95-th percentile80
Maximum100
Range100
Interquartile range (IQR)40

Descriptive statistics

Standard deviation22.610316
Coefficient of variation (CV)0.44515532
Kurtosis-0.65000598
Mean50.79197
Median Absolute Deviation (MAD)20
Skewness-0.36547637
Sum369410
Variance511.22638
MonotonicityNot monotonic
2024-03-13T08:27:02.841409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
60 1209
12.1%
50 1179
11.8%
70 1056
 
10.6%
80 930
 
9.3%
40 854
 
8.5%
20 669
 
6.7%
30 642
 
6.4%
10 273
 
2.7%
0 239
 
2.4%
90 213
 
2.1%
(Missing) 2727
27.3%
ValueCountFrequency (%)
0 239
 
2.4%
10 273
 
2.7%
20 669
6.7%
30 642
6.4%
40 854
8.5%
50 1179
11.8%
60 1209
12.1%
70 1056
10.6%
80 930
9.3%
90 213
 
2.1%
ValueCountFrequency (%)
100 9
 
0.1%
90 213
 
2.1%
80 930
9.3%
70 1056
10.6%
60 1209
12.1%
50 1179
11.8%
40 854
8.5%
30 642
6.4%
20 669
6.7%
10 273
 
2.7%

환자성별
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
4050 
여
3311 
<NA>
2638 
미상
 
1

Length

Max length4
Median length1
Mean length1.7915
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row남
2nd row<NA>
3rd row여
4th row여
5th row여

Common Values

ValueCountFrequency (%)
남 4050
40.5%
여 3311
33.1%
<NA> 2638
26.4%
미상 1
 
< 0.1%

Length

2024-03-13T08:27:02.938279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:27:03.016468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 4050
40.5%
여 3311
33.1%
na 2638
26.4%
미상 1
 
< 0.1%

외국인유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9848 
True
 
152
ValueCountFrequency (%)
False 9848
98.5%
True 152
 
1.5%
2024-03-13T08:27:03.082362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

국적
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9849 
중국
 
64
우즈베키스탄
 
9
베트남
 
7
러시아
 
6
Other values (38)
 
65

Length

Max length7
Median length4
Mean length3.9834
Min length2

Unique

Unique24 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9849
98.5%
중국 64
 
0.6%
우즈베키스탄 9
 
0.1%
베트남 7
 
0.1%
러시아 6
 
0.1%
태국 5
 
0.1%
미국 4
 
< 0.1%
네팔 4
 
< 0.1%
미얀마 4
 
< 0.1%
중국인 3
 
< 0.1%
Other values (33) 45
 
0.4%

Length

2024-03-13T08:27:03.157616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9849
98.5%
중국 64
 
0.6%
우즈베키스탄 9
 
0.1%
베트남 7
 
0.1%
러시아 6
 
0.1%
태국 5
 
< 0.1%
미국 4
 
< 0.1%
네팔 4
 
< 0.1%
미얀마 4
 
< 0.1%
중국인 3
 
< 0.1%
Other values (33) 45
 
0.4%

구급처종명
Text

MISSING 

Distinct185
Distinct (%)2.2%
Missing1527
Missing (%)15.3%
Memory size156.2 KiB
2024-03-13T08:27:03.265924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length1
Mean length2.5497463
Min length1

Characters and Unicode

Total characters21604
Distinct characters225
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)1.8%

Sample

1st row집
2nd row바다/강/산/논밭
3rd row집
4th row집
5th row집
ValueCountFrequency (%)
집 5385
63.1%
도로 980
 
11.5%
도로외교통지역 546
 
6.4%
상업시설 417
 
4.9%
집단거주시설 272
 
3.2%
의료관련시설 211
 
2.5%
공장/산업/건설시설 201
 
2.4%
바다/강/산/논밭 95
 
1.1%
오락/문화시설 56
 
0.7%
운동시설 30
 
0.4%
Other values (196) 338
 
4.0%
2024-03-13T08:27:03.506221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
집 5664
26.2%
도 1543
 
7.1%
로 1536
 
7.1%
설 1437
 
6.7%
시 1247
 
5.8%
/ 791
 
3.7%
업 636
 
2.9%
교 609
 
2.8%
지 589
 
2.7%
역 559
 
2.6%
Other values (215) 6993
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20251
93.7%
Other Punctuation 791
 
3.7%
Close Punctuation 237
 
1.1%
Open Punctuation 237
 
1.1%
Space Separator 61
 
0.3%
Decimal Number 20
 
0.1%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
집 5664
28.0%
도 1543
 
7.6%
로 1536
 
7.6%
설 1437
 
7.1%
시 1247
 
6.2%
업 636
 
3.1%
교 609
 
3.0%
지 589
 
2.9%
역 559
 
2.8%
외 555
 
2.7%
Other values (201) 5876
29.0%
Decimal Number
ValueCountFrequency (%)
1 11
55.0%
2 4
 
20.0%
3 2
 
10.0%
9 2
 
10.0%
7 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
L 2
28.6%
G 2
28.6%
M 1
14.3%
T 1
14.3%
A 1
14.3%
Other Punctuation
ValueCountFrequency (%)
/ 791
100.0%
Close Punctuation
ValueCountFrequency (%)
) 237
100.0%
Open Punctuation
ValueCountFrequency (%)
( 237
100.0%
Space Separator
ValueCountFrequency (%)
61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20251
93.7%
Common 1346
 
6.2%
Latin 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
집 5664
28.0%
도 1543
 
7.6%
로 1536
 
7.6%
설 1437
 
7.1%
시 1247
 
6.2%
업 636
 
3.1%
교 609
 
3.0%
지 589
 
2.9%
역 559
 
2.8%
외 555
 
2.7%
Other values (201) 5876
29.0%
Common
ValueCountFrequency (%)
/ 791
58.8%
) 237
 
17.6%
( 237
 
17.6%
61
 
4.5%
1 11
 
0.8%
2 4
 
0.3%
3 2
 
0.1%
9 2
 
0.1%
7 1
 
0.1%
Latin
ValueCountFrequency (%)
L 2
28.6%
G 2
28.6%
M 1
14.3%
T 1
14.3%
A 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20251
93.7%
ASCII 1353
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
집 5664
28.0%
도 1543
 
7.6%
로 1536
 
7.6%
설 1437
 
7.1%
시 1247
 
6.2%
업 636
 
3.1%
교 609
 
3.0%
지 589
 
2.9%
역 559
 
2.8%
외 555
 
2.7%
Other values (201) 5876
29.0%
ASCII
ValueCountFrequency (%)
/ 791
58.5%
) 237
 
17.5%
( 237
 
17.5%
61
 
4.5%
1 11
 
0.8%
2 4
 
0.3%
L 2
 
0.1%
3 2
 
0.1%
9 2
 
0.1%
G 2
 
0.1%
Other values (4) 4
 
0.3%

환자증상1
Categorical

Distinct44
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3538 
기타통증
1256 
기타
975 
복통
755 
요통
411 
Other values (39)
3065 

Length

Max length6
Median length4
Mean length3.3164
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row어지러움
2nd row<NA>
3rd row<NA>
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
<NA> 3538
35.4%
기타통증 1256
 
12.6%
기타 975
 
9.8%
복통 755
 
7.5%
요통 411
 
4.1%
두통 340
 
3.4%
어지러움 330
 
3.3%
심정지 283
 
2.8%
의식장애 274
 
2.7%
호흡곤란 242
 
2.4%
Other values (34) 1596
16.0%

Length

2024-03-13T08:27:03.624584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3538
35.0%
기타통증 1256
 
12.4%
기타 975
 
9.6%
복통 755
 
7.5%
요통 411
 
4.1%
두통 340
 
3.4%
어지러움 330
 
3.3%
심정지 283
 
2.8%
의식장애 274
 
2.7%
호흡곤란 242
 
2.4%
Other values (35) 1714
16.9%

Interactions

2024-03-13T08:27:01.519533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:27:03.710874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명출동소방서환자연령대환자성별외국인유무국적환자증상1
시군명1.0001.0000.1310.0490.0850.8580.197
출동소방서1.0001.0000.1400.0790.0890.8720.190
환자연령대0.1310.1401.0000.1870.1280.4970.397
환자성별0.0490.0790.1871.0000.0000.3650.184
외국인유무0.0850.0890.1280.0001.0000.9010.069
국적0.8580.8720.4970.3650.9011.0000.000
환자증상10.1970.1900.3970.1840.0690.0001.000
2024-03-13T08:27:03.791579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
외국인유무환자증상1시군명국적환자성별출동소방서
외국인유무1.0000.0580.0720.6620.0000.075
환자증상10.0581.0000.0420.0000.1530.039
시군명0.0720.0421.0000.3210.0241.000
국적0.6620.0000.3211.0000.2460.332
환자성별0.0000.1530.0240.2461.0000.039
출동소방서0.0750.0391.0000.3320.0391.000
2024-03-13T08:27:03.868589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자연령대시군명출동소방서환자성별외국인유무국적환자증상1
환자연령대1.0000.0440.0470.1080.1080.0000.136
시군명0.0441.0001.0000.0240.0720.3210.042
출동소방서0.0471.0001.0000.0390.0750.3320.039
환자성별0.1080.0240.0391.0000.0000.2460.153
외국인유무0.1080.0720.0750.0001.0000.6620.058
국적0.0000.3210.3320.2460.6621.0000.000
환자증상10.1360.0420.0390.1530.0580.0001.000

Missing values

2024-03-13T08:27:01.618885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:27:01.741674image/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.
2024-03-13T08:27:01.838449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

집계년도시군명출동소방서출동안전센터환자연령대환자성별외국인유무국적구급처종명환자증상1
835952021동두천시동두천소방서소요119안전센터60남N<NA>집어지러움
115802021가평군가평소방서북면119지역대<NA><NA>N<NA>바다/강/산/논밭<NA>
171962021남양주시남양주소방서화도119안전센터30여N<NA>집<NA>
165062021수원시수원소방서영통119안전센터0여N<NA>집기타
820512021안성시안성소방서119구조대0여N<NA>집기타
103582021남양주시남양주소방서수동지역대<NA><NA>N<NA>집<NA>
975572021안산시안산소방서선부119안전센터<NA><NA>N<NA>집<NA>
856592021양주시양주소방서옥정119안전센터40남N<NA>집기타통증
585722021수원시수원남부소방서남부119안전센터20남N<NA>집두통
285302021성남시성남소방서상대원119안전센터70여N<NA>집기타
집계년도시군명출동소방서출동안전센터환자연령대환자성별외국인유무국적구급처종명환자증상1
815872021성남시성남소방서태평119안전센터80남N<NA>집기타
42282021의왕시의왕소방서오전출동대<NA><NA>N<NA><NA><NA>
973282021수원시수원남부소방서남부119안전센터40남N<NA>집복통
40092021화성시화성소방서송산119지역대70남N<NA>집염좌
113832021양평군양평소방서양동119지역대<NA><NA>N<NA><NA><NA>
617802021광명시광명소방서광명119안전센터70남N<NA>집호흡곤란
353272021성남시성남소방서신흥119안전센터60남N<NA>상업시설호흡곤란
984762021광주시광주소방서송정119안전센터<NA><NA>N<NA><NA><NA>
281142021시흥시시흥소방서은행119안전센터50남N<NA><NA><NA>
341432021성남시성남소방서수진119안전센터30남N<NA>도로기타

Duplicate rows

Most frequently occurring

집계년도시군명출동소방서출동안전센터환자연령대환자성별외국인유무국적구급처종명환자증상1# duplicates
5022021안산시안산소방서상록수출동대<NA><NA>N<NA><NA><NA>44
5812021양평군양평소방서양서119지역대<NA><NA>N<NA><NA><NA>40
3682021수원시수원남부소방서매산119안전센터<NA><NA>N<NA><NA><NA>36
6932021의왕시의왕소방서오전출동대<NA><NA>N<NA><NA><NA>30
4322021시흥시시흥소방서은행119안전센터<NA><NA>N<NA><NA><NA>26
5002021안산시안산소방서상록수출동대<NA><NA>N<NA>집<NA>24
2042021남양주시남양주소방서수동지역대<NA><NA>N<NA><NA><NA>23
1182021광주시광주소방서퇴촌지역대<NA><NA>N<NA><NA><NA>20
8542021화성시화성소방서119구조대<NA><NA>N<NA><NA><NA>20
3002021성남시분당소방서서현119안전센터<NA><NA>N<NA><NA><NA>19