Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory869.1 KiB
Average record size in memory89.0 B

Variable types

Numeric1
DateTime4
Categorical2
Text3

Dataset

Description전국 구조활동내역에 대한 데이터로 신고자가 신고한 연월일과 신고시각, 소방대원이 출동한 연월일과 출동시각, 사고의 유형 및 세부유형 등에 관한 자료입니다.
Author소방청
URLhttps://www.data.go.kr/data/15062386/fileData.do

Alerts

번호 has unique valuesUnique

Reproduction

Analysis started2023-12-16 16:00:43.379472
Analysis finished2023-12-16 16:01:02.921347
Duration19.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47970.221
Minimum4
Maximum95291
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-16T16:01:03.327287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4488.7
Q124283.5
median47752.5
Q372179.75
95-th percentile90907.5
Maximum95291
Range95287
Interquartile range (IQR)47896.25

Descriptive statistics

Standard deviation27668.705
Coefficient of variation (CV)0.57678919
Kurtosis-1.2024418
Mean47970.221
Median Absolute Deviation (MAD)23938.5
Skewness-0.013418821
Sum4.7970221 × 108
Variance7.6555724 × 108
MonotonicityNot monotonic
2023-12-16T16:01:04.031564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71201 1
 
< 0.1%
94090 1
 
< 0.1%
35812 1
 
< 0.1%
1901 1
 
< 0.1%
4613 1
 
< 0.1%
41655 1
 
< 0.1%
40617 1
 
< 0.1%
53562 1
 
< 0.1%
81374 1
 
< 0.1%
65760 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
4 1
< 0.1%
22 1
< 0.1%
23 1
< 0.1%
26 1
< 0.1%
98 1
< 0.1%
100 1
< 0.1%
111 1
< 0.1%
121 1
< 0.1%
150 1
< 0.1%
152 1
< 0.1%
ValueCountFrequency (%)
95291 1
< 0.1%
95280 1
< 0.1%
95278 1
< 0.1%
95269 1
< 0.1%
95248 1
< 0.1%
95246 1
< 0.1%
95241 1
< 0.1%
95222 1
< 0.1%
95212 1
< 0.1%
95207 1
< 0.1%

신고년월일
Date

Distinct63
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-01 00:00:00
Maximum2021-03-04 00:00:00
2023-12-16T16:01:04.673079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:01:05.130226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신고시각
Date

Distinct1418
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-16 00:00:00
Maximum2023-12-16 23:59:00
2023-12-16T16:01:05.517540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:01:05.957195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

출동년월일
Date

Distinct63
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-01 00:00:00
Maximum2021-03-04 00:00:00
2023-12-16T16:01:06.415959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:01:06.910298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

출동시각
Date

Distinct1413
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-16 00:00:00
Maximum2023-12-16 23:59:00
2023-12-16T16:01:07.323449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:01:07.853518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발생장소_시
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
서울특별시
2660 
경기도
2146 
경상남도
664 
경상북도
595 
인천광역시
430 
Other values (12)
3505 

Length

Max length7
Median length5
Mean length4.2689
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 2660
26.6%
경기도 2146
21.5%
경상남도 664
 
6.6%
경상북도 595
 
5.9%
인천광역시 430
 
4.3%
전라북도 428
 
4.3%
충청남도 426
 
4.3%
전라남도 422
 
4.2%
강원도 391
 
3.9%
대구광역시 348
 
3.5%
Other values (7) 1490
14.9%

Length

2023-12-16T16:01:08.540863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 2660
26.6%
경기도 2146
21.5%
경상남도 664
 
6.6%
경상북도 595
 
5.9%
인천광역시 430
 
4.3%
전라북도 428
 
4.3%
충청남도 426
 
4.3%
전라남도 422
 
4.2%
강원도 391
 
3.9%
대구광역시 348
 
3.5%
Other values (7) 1490
14.9%

발생장소_구
Text

Distinct230
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-16T16:01:09.467314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.5276
Min length2

Characters and Unicode

Total characters35276
Distinct characters147
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row용인시 기흥구
2nd row의왕시
3rd row수성구
4th row강남구
5th row고양시 일산동구
ValueCountFrequency (%)
북구 211
 
1.9%
강남구 195
 
1.8%
서구 195
 
1.8%
남구 192
 
1.7%
중구 190
 
1.7%
강서구 172
 
1.5%
수원시 170
 
1.5%
용인시 160
 
1.4%
송파구 150
 
1.3%
노원구 148
 
1.3%
Other values (228) 9336
84.0%
2023-12-16T16:01:10.921858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 5658
 
16.0%
시 4530
 
12.8%
군 1448
 
4.1%
1241
 
3.5%
주 1215
 
3.4%
산 910
 
2.6%
서 832
 
2.4%
성 826
 
2.3%
양 825
 
2.3%
남 800
 
2.3%
Other values (137) 16991
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34035
96.5%
Space Separator 1241
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 5658
 
16.6%
시 4530
 
13.3%
군 1448
 
4.3%
주 1215
 
3.6%
산 910
 
2.7%
서 832
 
2.4%
성 826
 
2.4%
양 825
 
2.4%
남 800
 
2.4%
천 770
 
2.3%
Other values (136) 16221
47.7%
Space Separator
ValueCountFrequency (%)
1241
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34035
96.5%
Common 1241
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 5658
 
16.6%
시 4530
 
13.3%
군 1448
 
4.3%
주 1215
 
3.6%
산 910
 
2.7%
서 832
 
2.4%
성 826
 
2.4%
양 825
 
2.4%
남 800
 
2.4%
천 770
 
2.3%
Other values (136) 16221
47.7%
Common
ValueCountFrequency (%)
1241
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34035
96.5%
ASCII 1241
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 5658
 
16.6%
시 4530
 
13.3%
군 1448
 
4.3%
주 1215
 
3.6%
산 910
 
2.7%
서 832
 
2.4%
성 826
 
2.4%
양 825
 
2.4%
남 800
 
2.4%
천 770
 
2.3%
Other values (136) 16221
47.7%
ASCII
ValueCountFrequency (%)
1241
100.0%

발생장소_동
Text

Distinct2431
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-16T16:01:11.789846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0569
Min length2

Characters and Unicode

Total characters30569
Distinct characters337
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

Unique829 ?
Unique (%)8.3%

Sample

1st row중동
2nd row삼동
3rd row매호동
4th row개포동
5th row식사동
ValueCountFrequency (%)
신림동 79
 
0.8%
상계동 67
 
0.7%
화곡동 61
 
0.6%
봉천동 58
 
0.6%
역삼동 57
 
0.6%
신정동 54
 
0.5%
논현동 49
 
0.5%
서초동 46
 
0.5%
중동 45
 
0.4%
월계동 36
 
0.4%
Other values (2421) 9448
94.5%
2023-12-16T16:01:13.268793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 7341
24.0%
면 1731
 
5.7%
읍 1205
 
3.9%
산 592
 
1.9%
가 513
 
1.7%
신 493
 
1.6%
정 469
 
1.5%
천 442
 
1.4%
곡 367
 
1.2%
성 358
 
1.2%
Other values (327) 17058
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30241
98.9%
Decimal Number 328
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7341
24.3%
면 1731
 
5.7%
읍 1205
 
4.0%
산 592
 
2.0%
가 513
 
1.7%
신 493
 
1.6%
정 469
 
1.6%
천 442
 
1.5%
곡 367
 
1.2%
성 358
 
1.2%
Other values (319) 16730
55.3%
Decimal Number
ValueCountFrequency (%)
2 106
32.3%
1 94
28.7%
3 65
19.8%
4 28
 
8.5%
6 17
 
5.2%
5 9
 
2.7%
7 8
 
2.4%
8 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30241
98.9%
Common 328
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7341
24.3%
면 1731
 
5.7%
읍 1205
 
4.0%
산 592
 
2.0%
가 513
 
1.7%
신 493
 
1.6%
정 469
 
1.6%
천 442
 
1.5%
곡 367
 
1.2%
성 358
 
1.2%
Other values (319) 16730
55.3%
Common
ValueCountFrequency (%)
2 106
32.3%
1 94
28.7%
3 65
19.8%
4 28
 
8.5%
6 17
 
5.2%
5 9
 
2.7%
7 8
 
2.4%
8 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30241
98.9%
ASCII 328
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 7341
24.3%
면 1731
 
5.7%
읍 1205
 
4.0%
산 592
 
2.0%
가 513
 
1.7%
신 493
 
1.6%
정 469
 
1.6%
천 442
 
1.5%
곡 367
 
1.2%
성 358
 
1.2%
Other values (319) 16730
55.3%
ASCII
ValueCountFrequency (%)
2 106
32.3%
1 94
28.7%
3 65
19.8%
4 28
 
8.5%
6 17
 
5.2%
5 9
 
2.7%
7 8
 
2.4%
8 1
 
0.3%

사고원인
Categorical

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
화재
1941 
안전조치
1824 
교통
1100 
기타
1039 
동물포획
929 
Other values (17)
3167 

Length

Max length6
Median length5
Mean length3.2346
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화재
2nd row자연재난
3rd row동물포획
4th row기타
5th row안전조치

Common Values

ValueCountFrequency (%)
화재 1941
19.4%
안전조치 1824
18.2%
교통 1100
11.0%
기타 1039
10.4%
동물포획 929
9.3%
잠금장치개방 850
8.5%
자연재난 557
 
5.6%
승강기 359
 
3.6%
자살추정 336
 
3.4%
위치추적 253
 
2.5%
Other values (12) 812
8.1%

Length

2023-12-16T16:01:13.762026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화재 1941
19.0%
안전조치 1824
17.9%
교통 1100
10.8%
기타 1039
10.2%
동물포획 929
9.1%
잠금장치개방 850
8.3%
자연재난 557
 
5.5%
승강기 359
 
3.5%
자살추정 336
 
3.3%
위치추적 253
 
2.5%
Other values (13) 1027
10.1%

사고원인코드명_사고종별
Text

Distinct120
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-16T16:01:14.840532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length4.3823
Min length1

Characters and Unicode

Total characters43823
Distinct characters177
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.1%

Sample

1st row기타화재
2nd row고드름 제거
3rd row개
4th row기타
5th row소방시설 오작동
ValueCountFrequency (%)
기타 2792
20.4%
기타화재 1475
 
10.8%
안전조치 981
 
7.2%
소방시설 600
 
4.4%
오작동 600
 
4.4%
개 596
 
4.4%
개방 550
 
4.0%
차대차 533
 
3.9%
문 499
 
3.6%
실화 335
 
2.4%
Other values (120) 4733
34.6%
2023-12-16T16:01:16.238498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 4877
 
11.1%
타 4358
 
9.9%
3694
 
8.4%
화 1884
 
4.3%
차 1590
 
3.6%
재 1535
 
3.5%
방 1235
 
2.8%
개 1161
 
2.6%
치 1139
 
2.6%
전 1043
 
2.4%
Other values (167) 21307
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39816
90.9%
Space Separator 3694
 
8.4%
Other Punctuation 200
 
0.5%
Close Punctuation 52
 
0.1%
Open Punctuation 52
 
0.1%
Uppercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 4877
 
12.2%
타 4358
 
10.9%
화 1884
 
4.7%
차 1590
 
4.0%
재 1535
 
3.9%
방 1235
 
3.1%
개 1161
 
2.9%
치 1139
 
2.9%
전 1043
 
2.6%
조 1043
 
2.6%
Other values (159) 19951
50.1%
Uppercase Letter
ValueCountFrequency (%)
L 3
33.3%
G 3
33.3%
N 2
22.2%
P 1
 
11.1%
Space Separator
ValueCountFrequency (%)
3694
100.0%
Other Punctuation
ValueCountFrequency (%)
· 200
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39816
90.9%
Common 3998
 
9.1%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 4877
 
12.2%
타 4358
 
10.9%
화 1884
 
4.7%
차 1590
 
4.0%
재 1535
 
3.9%
방 1235
 
3.1%
개 1161
 
2.9%
치 1139
 
2.9%
전 1043
 
2.6%
조 1043
 
2.6%
Other values (159) 19951
50.1%
Common
ValueCountFrequency (%)
3694
92.4%
· 200
 
5.0%
) 52
 
1.3%
( 52
 
1.3%
Latin
ValueCountFrequency (%)
L 3
33.3%
G 3
33.3%
N 2
22.2%
P 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39816
90.9%
ASCII 3807
 
8.7%
None 200
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 4877
 
12.2%
타 4358
 
10.9%
화 1884
 
4.7%
차 1590
 
4.0%
재 1535
 
3.9%
방 1235
 
3.1%
개 1161
 
2.9%
치 1139
 
2.9%
전 1043
 
2.6%
조 1043
 
2.6%
Other values (159) 19951
50.1%
ASCII
ValueCountFrequency (%)
3694
97.0%
) 52
 
1.4%
( 52
 
1.4%
L 3
 
0.1%
G 3
 
0.1%
N 2
 
0.1%
P 1
 
< 0.1%
None
ValueCountFrequency (%)
· 200
100.0%

Interactions

2023-12-16T16:01:00.214340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T16:01:16.653555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호신고년월일출동년월일발생장소_시사고원인
번호1.0000.9980.9980.0980.251
신고년월일0.9981.0001.0000.1390.325
출동년월일0.9981.0001.0000.1390.325
발생장소_시0.0980.1390.1391.0000.338
사고원인0.2510.3250.3250.3381.000
2023-12-16T16:01:17.115666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발생장소_시사고원인
발생장소_시1.0000.107
사고원인0.1071.000
2023-12-16T16:01:17.462480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호발생장소_시사고원인
번호1.0000.0380.095
발생장소_시0.0381.0000.107
사고원인0.0950.1071.000

Missing values

2023-12-16T16:01:00.909714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T16:01:02.515976image/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

번호신고년월일신고시각출동년월일출동시각발생장소_시발생장소_구발생장소_동사고원인사고원인코드명_사고종별
71200712012021-02-1519:102021-02-1519:11경기도용인시 기흥구중동화재기타화재
17862178632021-01-1111:462021-01-1111:48경기도의왕시삼동자연재난고드름 제거
35704357052021-01-2010:402021-01-2010:42대구광역시수성구매호동동물포획개
40126401272021-01-2310:432021-01-2310:45서울특별시강남구개포동기타기타
19152191532021-01-1120:492021-01-1120:49경기도고양시 일산동구식사동안전조치소방시설 오작동
253125322021-01-0221:092021-01-0221:11서울특별시중랑구면목동안전조치소방시설 오작동
33258332592021-01-1815:532021-01-1815:54경기도구리시수택동기타기타
94728947292021-03-0410:372021-03-0410:40경기도화성시남양읍동물포획고양이
34336343372021-01-1910:572021-01-1911:00인천광역시미추홀구용현동자연재난도로결빙
72407724082021-02-1616:542021-02-1616:56강원도원주시행구동교통기타 교통
번호신고년월일신고시각출동년월일출동시각발생장소_시발생장소_구발생장소_동사고원인사고원인코드명_사고종별
87673876742021-02-2714:072021-02-2714:09서울특별시송파구잠실동안전조치기타 안전조치
84980849812021-02-2517:422021-02-2517:42경기도화성시마도면동물포획개
38082380832021-01-2120:372021-01-2120:37경상남도함양군함양읍안전조치소방시설 오작동
76336763372021-02-1913:192021-02-1913:20경상북도경산시대동수난시설물 침수
58468584692021-02-0602:342021-02-0602:37경기도동두천시지행동잠금장치개방신변확인
72311723122021-02-1615:332021-02-1615:34전라북도군산시대야면교통화물차
52580525812021-02-0113:422021-02-0113:42충청남도공주시교동기타기타
16517165182021-01-1020:262021-01-1020:27세종특별자치시세종특별자치시새롬동동물포획고양이
76603766042021-02-1916:182021-02-1916:19경기도연천군청산면교통차대차
47290472912021-01-2819:092021-01-2819:14충청남도천안시 동남구신부동자연재난강풍