Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells3973
Missing cells (%)2.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory129.0 B

Variable types

Numeric1
Categorical8
DateTime4
Text2

Dataset

Description세종소방본부에서 제공하는 2020년 구조활동 현황 정보로서 접수일시, 긴급구조 종별, 분류, 규모, 상황종료일시, 관할서명, 서센터명 등의 정보를 제공하는 데이터임 * 개인정보 비 식별화, 데이터 미집계 등을 사유로 일부 컬럼 NULL 값 존재
Author소방청
URLhttps://www.data.go.kr/data/15080967/fileData.do

Alerts

긴급구조 종별명 has constant value ""Constant
긴급구조 규모명 has constant value ""Constant
일련번호 is highly overall correlated with 관할서명High correlation
긴급구조 동명 is highly overall correlated with 관할서명 and 1 other fieldsHigh correlation
관할서명 is highly overall correlated with 일련번호 and 2 other fieldsHigh correlation
서센터명 is highly overall correlated with 긴급구조 동명 and 1 other fieldsHigh correlation
접수경로명 is highly imbalanced (58.5%)Imbalance
타시도신고여부 is highly imbalanced (94.8%)Imbalance
긴급구조 우편번호 has 179 (1.8%) missing valuesMissing
긴급구조 리명 has 3791 (37.9%) missing valuesMissing
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:26:14.900260
Analysis finished2023-12-12 17:26:19.329212
Duration4.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10556.722
Minimum3
Maximum21130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:26:19.405115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile1106.95
Q15274.25
median10552
Q315834.25
95-th percentile20063.15
Maximum21130
Range21127
Interquartile range (IQR)10560

Descriptive statistics

Standard deviation6107.1094
Coefficient of variation (CV)0.57850432
Kurtosis-1.206493
Mean10556.722
Median Absolute Deviation (MAD)5281
Skewness0.0062622423
Sum1.0556722 × 108
Variance37296785
MonotonicityNot monotonic
2023-12-13T02:26:19.549968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7220 1
 
< 0.1%
8981 1
 
< 0.1%
3725 1
 
< 0.1%
13293 1
 
< 0.1%
871 1
 
< 0.1%
11315 1
 
< 0.1%
9670 1
 
< 0.1%
6827 1
 
< 0.1%
564 1
 
< 0.1%
3294 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
17 1
< 0.1%
ValueCountFrequency (%)
21130 1
< 0.1%
21127 1
< 0.1%
21125 1
< 0.1%
21122 1
< 0.1%
21121 1
< 0.1%
21118 1
< 0.1%
21115 1
< 0.1%
21113 1
< 0.1%
21110 1
< 0.1%
21109 1
< 0.1%

접수경로명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
이동전화
6939 
기타
1418 
일반전화
952 
사후각지
 
365
IP전화
 
311
Other values (6)
 
15

Length

Max length6
Median length4
Mean length3.7175
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row이동전화
2nd row이동전화
3rd row기타
4th row일반전화
5th row이동전화

Common Values

ValueCountFrequency (%)
이동전화 6939
69.4%
기타 1418
 
14.2%
일반전화 952
 
9.5%
사후각지 365
 
3.6%
IP전화 311
 
3.1%
SMS신고 4
 
< 0.1%
공중전화 3
 
< 0.1%
MMS신고 3
 
< 0.1%
영상신고 2
 
< 0.1%
WEB신고 2
 
< 0.1%

Length

2023-12-13T02:26:19.712268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이동전화 6939
69.4%
기타 1418
 
14.2%
일반전화 952
 
9.5%
사후각지 365
 
3.6%
ip전화 311
 
3.1%
sms신고 4
 
< 0.1%
공중전화 3
 
< 0.1%
mms신고 3
 
< 0.1%
영상신고 2
 
< 0.1%
web신고 2
 
< 0.1%

접수일시
Date

Distinct2651
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2012-07-01 00:00:00
Maximum2020-12-31 00:00:00
2023-12-13T02:26:19.855461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:26:20.017161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

접수일시(상세)
Date

Distinct8841
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-13 00:00:18
Maximum2023-12-13 23:59:43
2023-12-13T02:26:20.155984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:26:20.314575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

타시도신고여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
아니오
9941 
예
 
59

Length

Max length3
Median length3
Mean length2.9882
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아니오 9941
99.4%
예 59
 
0.6%

Length

2023-12-13T02:26:20.493466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:26:20.716060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아니오 9941
99.4%
예 59
 
0.6%

긴급구조 우편번호
Text

MISSING 

Distinct324
Distinct (%)3.3%
Missing179
Missing (%)1.8%
Memory size156.2 KiB
2023-12-13T02:26:21.252324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3018023
Min length5

Characters and Unicode

Total characters52069
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)0.3%

Sample

1st row80175
2nd row80158
3rd row71128
4th row80085
5th row80006
ValueCountFrequency (%)
80006 442
 
4.5%
100-001 383
 
3.9%
100-002 359
 
3.7%
80039 343
 
3.5%
100-006 325
 
3.3%
100-005 312
 
3.2%
80012 258
 
2.6%
80167 240
 
2.4%
80185 201
 
2.0%
80013 199
 
2.0%
Other values (314) 6759
68.8%
2023-12-13T02:26:22.026298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19430
37.3%
8 9075
17.4%
1 8736
16.8%
7 3022
 
5.8%
6 2604
 
5.0%
2 1863
 
3.6%
5 1791
 
3.4%
3 1577
 
3.0%
- 1482
 
2.8%
9 1271
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50587
97.2%
Dash Punctuation 1482
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19430
38.4%
8 9075
17.9%
1 8736
17.3%
7 3022
 
6.0%
6 2604
 
5.1%
2 1863
 
3.7%
5 1791
 
3.5%
3 1577
 
3.1%
9 1271
 
2.5%
4 1218
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1482
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52069
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19430
37.3%
8 9075
17.4%
1 8736
16.8%
7 3022
 
5.8%
6 2604
 
5.0%
2 1863
 
3.6%
5 1791
 
3.4%
3 1577
 
3.0%
- 1482
 
2.8%
9 1271
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52069
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19430
37.3%
8 9075
17.4%
1 8736
16.8%
7 3022
 
5.8%
6 2604
 
5.0%
2 1863
 
3.6%
5 1791
 
3.4%
3 1577
 
3.0%
- 1482
 
2.8%
9 1271
 
2.4%

긴급구조 동명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
조치원읍
1681 
금남면
815 
장군면
732 
전의면
617 
부강면
 
546
Other values (20)
5609 

Length

Max length4
Median length3
Mean length3.1682
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row장군면
2nd row소정면
3rd row전의면
4th row연기면
5th row고운동

Common Values

ValueCountFrequency (%)
조치원읍 1681
16.8%
금남면 815
 
8.2%
장군면 732
 
7.3%
전의면 617
 
6.2%
부강면 546
 
5.5%
연서면 534
 
5.3%
연기면 468
 
4.7%
고운동 443
 
4.4%
어진동 433
 
4.3%
아름동 427
 
4.3%
Other values (15) 3304
33.0%

Length

2023-12-13T02:26:22.217165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조치원읍 1681
16.8%
금남면 815
 
8.2%
장군면 732
 
7.3%
전의면 617
 
6.2%
부강면 546
 
5.5%
연서면 534
 
5.3%
연기면 468
 
4.7%
고운동 443
 
4.4%
어진동 433
 
4.3%
아름동 427
 
4.3%
Other values (15) 3304
33.0%

긴급구조 리명
Text

MISSING 

Distinct120
Distinct (%)1.9%
Missing3791
Missing (%)37.9%
Memory size156.2 KiB
2023-12-13T02:26:22.616124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9205991
Min length2

Characters and Unicode

Total characters18134
Distinct characters110
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

Unique0 ?
Unique (%)0.0%

Sample

1st row대교리
2nd row고등리
3rd row동교리
4th row연기리
5th row죽림리
ValueCountFrequency (%)
신안리 303
 
4.9%
부강리 248
 
4.0%
서창리 247
 
4.0%
세종리 213
 
3.4%
용포리 179
 
2.9%
금암리 175
 
2.8%
침산리 170
 
2.7%
신흥리 159
 
2.6%
원리 134
 
2.2%
죽림리 134
 
2.2%
Other values (110) 4247
68.4%
2023-12-13T02:26:23.251844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 6228
34.3%
신 600
 
3.3%
암 549
 
3.0%
산 489
 
2.7%
안 414
 
2.3%
곡 405
 
2.2%
봉 396
 
2.2%
용 380
 
2.1%
부 291
 
1.6%
교 289
 
1.6%
Other values (100) 8093
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18134
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 6228
34.3%
신 600
 
3.3%
암 549
 
3.0%
산 489
 
2.7%
안 414
 
2.3%
곡 405
 
2.2%
봉 396
 
2.2%
용 380
 
2.1%
부 291
 
1.6%
교 289
 
1.6%
Other values (100) 8093
44.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18134
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 6228
34.3%
신 600
 
3.3%
암 549
 
3.0%
산 489
 
2.7%
안 414
 
2.3%
곡 405
 
2.2%
봉 396
 
2.2%
용 380
 
2.1%
부 291
 
1.6%
교 289
 
1.6%
Other values (100) 8093
44.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18134
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 6228
34.3%
신 600
 
3.3%
암 549
 
3.0%
산 489
 
2.7%
안 414
 
2.3%
곡 405
 
2.2%
봉 396
 
2.2%
용 380
 
2.1%
부 291
 
1.6%
교 289
 
1.6%
Other values (100) 8093
44.6%

긴급구조 종별명
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구조 10000
100.0%

Length

2023-12-13T02:26:23.488845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:26:23.634478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구조 10000
100.0%

긴급구조 분류명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
벌집제거
4045 
기타안전사고
1943 
동물구조
1784 
교통사고
764 
시건개방
658 
Other values (10)
806 

Length

Max length10
Median length4
Mean length4.4555
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row벌집제거
2nd row벌집제거
3rd row기타안전사고
4th row벌집제거
5th row기타안전사고

Common Values

ValueCountFrequency (%)
벌집제거 4045
40.5%
기타안전사고 1943
19.4%
동물구조 1784
17.8%
교통사고 764
 
7.6%
시건개방 658
 
6.6%
E/V사고 639
 
6.4%
산악사고 44
 
0.4%
기계사고 41
 
0.4%
추락사고 39
 
0.4%
수난사고 24
 
0.2%
Other values (5) 19
 
0.2%

Length

2023-12-13T02:26:23.790925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
벌집제거 4045
40.5%
기타안전사고 1943
19.4%
동물구조 1784
17.8%
교통사고 764
 
7.6%
시건개방 658
 
6.6%
e/v사고 639
 
6.4%
산악사고 44
 
0.4%
기계사고 41
 
0.4%
추락사고 39
 
0.4%
수난사고 24
 
0.2%
Other values (5) 19
 
0.2%

긴급구조 규모명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1차출동
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1차출동
2nd row1차출동
3rd row1차출동
4th row1차출동
5th row1차출동

Common Values

ValueCountFrequency (%)
1차출동 10000
100.0%

Length

2023-12-13T02:26:23.928229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:26:24.048405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1차출동 10000
100.0%

상황종료일시
Date

Distinct2635
Distinct (%)26.4%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum2012-07-05 00:00:00
Maximum2020-12-31 00:00:00
2023-12-13T02:26:24.197176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:26:24.390502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상황종료일시(상세)
Date

Distinct9229
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 23:59:05
2023-12-13T02:26:24.592906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:26:24.753776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관할서명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
조치원소방서
4571 
세종소방서
4414 
세종소방본부
932 
<NA>
 
83

Length

Max length6
Median length6
Mean length5.542
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row세종소방서
2nd row조치원소방서
3rd row조치원소방서
4th row세종소방서
5th row세종소방서

Common Values

ValueCountFrequency (%)
조치원소방서 4571
45.7%
세종소방서 4414
44.1%
세종소방본부 932
 
9.3%
<NA> 83
 
0.8%

Length

2023-12-13T02:26:24.897572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:26:25.034112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조치원소방서 4571
45.7%
세종소방서 4414
44.1%
세종소방본부 932
 
9.3%
na 83
 
0.8%

서센터명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
아름119안전센터
1959 
조치원119안전센터
1914 
한솔119안전센터
1442 
보람119안전센터
1111 
전의119안전센터
1033 
Other values (7)
2541 

Length

Max length10
Median length9
Mean length9.1733
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row아름119안전센터
2nd row전의119안전센터
3rd row전의119안전센터
4th row어진119안전센터
5th row아름119안전센터

Common Values

ValueCountFrequency (%)
아름119안전센터 1959
19.6%
조치원119안전센터 1914
19.1%
한솔119안전센터 1442
14.4%
보람119안전센터 1111
11.1%
전의119안전센터 1033
10.3%
부강119안전센터 801
8.0%
어진119안전센터 767
 
7.7%
연서119안전센터 467
 
4.7%
첫마을119안전센터 234
 
2.3%
조치원119구조대 122
 
1.2%
Other values (2) 150
 
1.5%

Length

2023-12-13T02:26:25.174408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아름119안전센터 1959
19.6%
조치원119안전센터 1914
19.1%
한솔119안전센터 1442
14.4%
보람119안전센터 1111
11.1%
전의119안전센터 1033
10.3%
부강119안전센터 801
8.0%
어진119안전센터 767
 
7.7%
연서119안전센터 467
 
4.7%
첫마을119안전센터 234
 
2.3%
조치원119구조대 122
 
1.2%
Other values (2) 150
 
1.5%

Interactions

2023-12-13T02:26:18.577815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:26:25.520029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호접수경로명타시도신고여부긴급구조 동명긴급구조 분류명관할서명서센터명
일련번호1.0000.2180.0740.3200.4720.7110.523
접수경로명0.2181.0000.1960.1610.2090.2060.230
타시도신고여부0.0740.1961.0000.0000.0490.0270.000
긴급구조 동명0.3200.1610.0001.0000.3190.8980.953
긴급구조 분류명0.4720.2090.0490.3191.0000.3270.329
관할서명0.7110.2060.0270.8980.3271.0000.840
서센터명0.5230.2300.0000.9530.3290.8401.000
2023-12-13T02:26:25.647001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
타시도신고여부긴급구조 동명접수경로명관할서명서센터명긴급구조 분류명
타시도신고여부1.0000.0000.1880.0440.0000.044
긴급구조 동명0.0001.0000.0570.6760.7540.103
접수경로명0.1880.0571.0000.1220.0700.082
관할서명0.0440.6760.1221.0000.7370.158
서센터명0.0000.7540.0700.7371.0000.133
긴급구조 분류명0.0440.1030.0820.1580.1331.000
2023-12-13T02:26:25.776443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호접수경로명타시도신고여부긴급구조 동명긴급구조 분류명관할서명서센터명
일련번호1.0000.0940.0570.1220.1960.5700.253
접수경로명0.0941.0000.1880.0570.0820.1220.070
타시도신고여부0.0570.1881.0000.0000.0440.0440.000
긴급구조 동명0.1220.0570.0001.0000.1030.6760.754
긴급구조 분류명0.1960.0820.0440.1031.0000.1580.133
관할서명0.5700.1220.0440.6760.1581.0000.737
서센터명0.2530.0700.0000.7540.1330.7371.000

Missing values

2023-12-13T02:26:18.771378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:26:19.011011image/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.
2023-12-13T02:26:19.207155image/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

일련번호접수경로명접수일시접수일시(상세)타시도신고여부긴급구조 우편번호긴급구조 동명긴급구조 리명긴급구조 종별명긴급구조 분류명긴급구조 규모명상황종료일시상황종료일시(상세)관할서명서센터명
72387220이동전화2016-08-1811:50:09아니오80175장군면대교리구조벌집제거1차출동2016-08-1812:20:09세종소방서아름119안전센터
66476629이동전화2016-08-0614:50:13아니오80158소정면고등리구조벌집제거1차출동2016-08-0617:50:55조치원소방서전의119안전센터
19001893기타2013-09-0513:35:00아니오71128전의면동교리구조기타안전사고1차출동2013-09-0514:27:28조치원소방서전의119안전센터
76297611일반전화2016-08-2909:43:36아니오80085연기면연기리구조벌집제거1차출동2016-08-2910:54:46세종소방서어진119안전센터
1335613355이동전화2018-08-1719:14:31아니오80006고운동<NA>구조기타안전사고1차출동2018-08-1719:31:06세종소방서아름119안전센터
1862418625이동전화2020-04-0318:36:52아니오80165조치원읍죽림리구조동물구조1차출동2020-04-0319:01:40조치원소방서조치원119안전센터
30593051이동전화2014-07-2010:11:18아니오80110금남면용포리구조기타안전사고1차출동2014-07-2010:29:22세종소방본부한솔119안전센터
33073299이동전화2014-08-3112:09:20아니오80127전동면심중리구조벌집제거1차출동2014-08-3114:59:39조치원소방서전의119안전센터
1671416715이동전화2019-08-0811:17:54아니오80006고운동<NA>구조벌집제거1차출동2019-08-0811:21:53세종소방서아름119안전센터
34613453이동전화2014-09-0410:15:34아니오80039한솔동<NA>구조벌집제거1차출동2014-09-0410:40:49세종소방본부한솔119안전센터
일련번호접수경로명접수일시접수일시(상세)타시도신고여부긴급구조 우편번호긴급구조 동명긴급구조 리명긴급구조 종별명긴급구조 분류명긴급구조 규모명상황종료일시상황종료일시(상세)관할서명서센터명
1025110252이동전화2017-08-2517:25:52아니오80062조치원읍서창리구조벌집제거1차출동2017-08-2518:19:00조치원소방서조치원119안전센터
33273319일반전화2014-08-2408:49:31아니오80123전동면석곡리구조벌집제거1차출동2014-08-2410:34:00조치원소방서전의119안전센터
17991794이동전화2013-08-2616:54:33아니오<NA>소정면소정리구조기타안전사고1차출동2013-08-2618:13:07조치원소방서전의119안전센터
68866868이동전화2016-07-2914:27:55아니오100-001도담동<NA>구조E/V사고1차출동2016-07-2914:39:14세종소방서어진119안전센터
27982791이동전화2014-07-0909:59:53아니오80131전의면관정리구조벌집제거1차출동2014-07-0911:07:50조치원소방서전의119안전센터
91949188이동전화2017-06-0201:16:13아니오80080연기면세종리구조동물구조1차출동2017-06-0214:24:16세종소방서아름119안전센터
85598546이동전화2017-01-0214:00:20아니오80167조치원읍신안리구조산악사고1차출동2017-01-0215:33:08조치원소방서조치원119안전센터
2041720418이동전화2020-09-0417:41:22아니오100-001도담동<NA>구조벌집제거1차출동2020-09-0418:28:19세종소방서어진119안전센터
1341613415이동전화2018-08-1300:01:45아니오100-002아름동<NA>구조동물구조1차출동2018-08-1301:13:52세종소방서아름119안전센터
2055920560기타2020-06-2403:13:11아니오100-006어진동<NA>구조기타안전사고1차출동2020-06-2405:41:38세종소방서어진119안전센터