Overview

Dataset statistics

Number of variables5
Number of observations1050
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.2 KiB
Average record size in memory44.1 B

Variable types

Categorical1
Text1
Numeric3

Dataset

Description2010년부터 2013년까지의 소방서(관할소방서)별 화재건수를 제공하는 데이터로 사업소(관할사업소), 총 화재 건수,전기 화재건수,점유율을 제공합니다.
Author한국전기안전공사
URLhttps://www.data.go.kr/data/15043830/fileData.do

Alerts

총화재건수 is highly overall correlated with 전기화재건수High correlation
전기화재건수 is highly overall correlated with 총화재건수High correlation

Reproduction

Analysis started2023-12-12 21:44:20.425002
Analysis finished2023-12-12 21:44:21.882852
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
2011
263 
2010
263 
2013
262 
2012
262 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013
2nd row2013
3rd row2013
4th row2013
5th row2013

Common Values

ValueCountFrequency (%)
2011 263
25.0%
2010 263
25.0%
2013 262
25.0%
2012 262
25.0%

Length

2023-12-13T06:44:21.948708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:44:22.050625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2011 263
25.0%
2010 263
25.0%
2013 262
25.0%
2012 262
25.0%

사업소/관할소방서
Text

Distinct240
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
2023-12-13T06:44:22.307528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.4533333
Min length4

Characters and Unicode

Total characters5726
Distinct characters132
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 row서울지역본부
2nd row서울지역본부직할
3rd row마포소방서
4th row서대문소방서
5th row용산소방서
ValueCountFrequency (%)
동부소방서 24
 
2.3%
서부소방서 24
 
2.3%
중부소방서 24
 
2.3%
남부소방서 20
 
1.9%
북부소방서 16
 
1.5%
강서소방서 8
 
0.8%
서울지역본부 4
 
0.4%
포천소방서 4
 
0.4%
파주고양지사 4
 
0.4%
고양소방서 4
 
0.4%
Other values (230) 918
87.4%
2023-12-13T06:44:22.708190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 874
15.3%
소 754
 
13.2%
방 754
 
13.2%
부 368
 
6.4%
지 296
 
5.2%
사 200
 
3.5%
남 144
 
2.5%
산 124
 
2.2%
역 104
 
1.8%
주 104
 
1.8%
Other values (122) 2004
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5726
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 874
15.3%
소 754
 
13.2%
방 754
 
13.2%
부 368
 
6.4%
지 296
 
5.2%
사 200
 
3.5%
남 144
 
2.5%
산 124
 
2.2%
역 104
 
1.8%
주 104
 
1.8%
Other values (122) 2004
35.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5726
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 874
15.3%
소 754
 
13.2%
방 754
 
13.2%
부 368
 
6.4%
지 296
 
5.2%
사 200
 
3.5%
남 144
 
2.5%
산 124
 
2.2%
역 104
 
1.8%
주 104
 
1.8%
Other values (122) 2004
35.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5726
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 874
15.3%
소 754
 
13.2%
방 754
 
13.2%
부 368
 
6.4%
지 296
 
5.2%
사 200
 
3.5%
남 144
 
2.5%
산 124
 
2.2%
역 104
 
1.8%
주 104
 
1.8%
Other values (122) 2004
35.0%

총화재건수
Real number (ℝ)

HIGH CORRELATION 

Distinct515
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean477.88857
Minimum36
Maximum6866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2023-12-13T06:44:22.858757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile100
Q1166
median240.5
Q3394.75
95-th percentile1612.4
Maximum6866
Range6830
Interquartile range (IQR)228.75

Descriptive statistics

Standard deviation792.29744
Coefficient of variation (CV)1.6579125
Kurtosis25.567082
Mean477.88857
Median Absolute Deviation (MAD)97.5
Skewness4.6817299
Sum501783
Variance627735.23
MonotonicityNot monotonic
2023-12-13T06:44:22.990775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160 8
 
0.8%
139 8
 
0.8%
209 8
 
0.8%
166 8
 
0.8%
267 7
 
0.7%
211 7
 
0.7%
167 7
 
0.7%
232 7
 
0.7%
164 7
 
0.7%
157 7
 
0.7%
Other values (505) 976
93.0%
ValueCountFrequency (%)
36 1
 
0.1%
48 1
 
0.1%
49 1
 
0.1%
56 1
 
0.1%
65 1
 
0.1%
70 2
0.2%
71 1
 
0.1%
74 3
0.3%
77 2
0.2%
78 3
0.3%
ValueCountFrequency (%)
6866 1
0.1%
6588 1
0.1%
6445 1
0.1%
6186 1
0.1%
5641 1
0.1%
5529 1
0.1%
5526 1
0.1%
5417 1
0.1%
5321 1
0.1%
5282 1
0.1%

전기화재건수
Real number (ℝ)

HIGH CORRELATION 

Distinct246
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.80571
Minimum5
Maximum1560
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2023-12-13T06:44:23.119235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile16
Q133
median55
Q388
95-th percentile354.75
Maximum1560
Range1555
Interquartile range (IQR)55

Descriptive statistics

Standard deviation178.95622
Coefficient of variation (CV)1.7239534
Kurtosis30.578807
Mean103.80571
Median Absolute Deviation (MAD)25
Skewness5.006651
Sum108996
Variance32025.327
MonotonicityNot monotonic
2023-12-13T06:44:23.263896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 19
 
1.8%
36 18
 
1.7%
38 18
 
1.7%
30 17
 
1.6%
25 17
 
1.6%
22 17
 
1.6%
24 17
 
1.6%
61 17
 
1.6%
27 16
 
1.5%
26 15
 
1.4%
Other values (236) 879
83.7%
ValueCountFrequency (%)
5 1
 
0.1%
9 5
0.5%
10 2
 
0.2%
11 2
 
0.2%
12 8
0.8%
13 8
0.8%
14 10
1.0%
15 11
1.0%
16 8
0.8%
17 12
1.1%
ValueCountFrequency (%)
1560 1
0.1%
1558 1
0.1%
1518 1
0.1%
1490 1
0.1%
1473 1
0.1%
1446 1
0.1%
1426 1
0.1%
1415 1
0.1%
1152 1
0.1%
1071 1
0.1%

점유율
Real number (ℝ)

Distinct232
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.299619
Minimum6.8
Maximum38.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2023-12-13T06:44:23.402627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.8
5-th percentile13.3
Q117.7
median21
Q324.4
95-th percentile30.355
Maximum38.5
Range31.7
Interquartile range (IQR)6.7

Descriptive statistics

Standard deviation5.1817786
Coefficient of variation (CV)0.24328034
Kurtosis0.23093716
Mean21.299619
Median Absolute Deviation (MAD)3.3
Skewness0.31430366
Sum22364.6
Variance26.850829
MonotonicityNot monotonic
2023-12-13T06:44:23.572626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.7 19
 
1.8%
22.0 17
 
1.6%
22.5 14
 
1.3%
18.0 14
 
1.3%
22.8 13
 
1.2%
18.3 13
 
1.2%
17.7 13
 
1.2%
21.0 13
 
1.2%
20.5 13
 
1.2%
18.8 12
 
1.1%
Other values (222) 909
86.6%
ValueCountFrequency (%)
6.8 1
0.1%
7.2 1
0.1%
7.4 1
0.1%
8.1 1
0.1%
8.7 1
0.1%
8.8 1
0.1%
9.3 1
0.1%
9.4 2
0.2%
10.1 1
0.1%
10.2 1
0.1%
ValueCountFrequency (%)
38.5 2
0.2%
37.5 1
0.1%
37.1 2
0.2%
37.0 1
0.1%
36.9 2
0.2%
35.4 1
0.1%
34.7 1
0.1%
34.4 1
0.1%
34.3 1
0.1%
34.2 2
0.2%

Interactions

2023-12-13T06:44:21.243337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:20.631416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:20.949680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:21.330376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:20.748431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:21.060624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:21.419665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:20.853062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:21.151905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:44:23.682765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도총화재건수전기화재건수점유율
연도1.0000.0000.0000.111
총화재건수0.0001.0000.9160.132
전기화재건수0.0000.9161.0000.150
점유율0.1110.1320.1501.000
2023-12-13T06:44:23.844826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총화재건수전기화재건수점유율연도
총화재건수1.0000.9360.1100.000
전기화재건수0.9361.0000.4110.000
점유율0.1100.4111.0000.066
연도0.0000.0000.0661.000

Missing values

2023-12-13T06:44:21.776302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:44:21.852017image/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

연도사업소/관할소방서총화재건수전기화재건수점유율
02013서울지역본부5417142626.3
12013서울지역본부직할127233226.1
22013마포소방서2267131.4
32013서대문소방서2214419.9
42013용산소방서1703621.2
52013은평소방서2115124.2
62013종로소방서2546525.6
72013중부소방서1906534.2
82013서울동부지사113433630.1
92013강동소방서2258336.9
연도사업소/관할소방서총화재건수전기화재건수점유율
10402010합천소방서1152017.4
10412010밀양창녕지사3045217.4
10422010밀양소방서2103516.7
10432010창녕소방서941718.1
10442010제주지역본부68710715.3
10452010제주지역본부직할68710715.3
10462010동부소방서1662213.3
10472010서귀포소방서1341511.2
10482010서부소방서1332518.8
10492010제주소방서2544517.7