Overview

Dataset statistics

Number of variables25
Number of observations10000
Missing cells5863
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 MiB
Average record size in memory218.0 B

Variable types

Numeric8
Categorical12
Text5

Dataset

Description2022년 전국에서 발생한 화재통계이며 화재유형, 최초착화물, 발화요인, 발화장소, 화재건수, 인명 및 재산피해 현황이 포함된 자료임
Author소방청
URLhttps://www.data.go.kr/data/15124781/fileData.do

Alerts

화재발생(년) has constant value ""Constant
사망 is highly imbalanced (97.2%)Imbalance
차량장소 is highly imbalanced (72.3%)Imbalance
발화관련기기소분류 has 5863 (58.6%) missing valuesMissing
인명피해(명)소계 is highly skewed (γ1 = 49.51201907)Skewed
부상 is highly skewed (γ1 = 48.80961151)Skewed
재산피해소계 is highly skewed (γ1 = 57.7685011)Skewed
연번 has unique valuesUnique
화재발생(시) has 294 (2.9%) zerosZeros
화재발생(분) has 209 (2.1%) zerosZeros
인명피해(명)소계 has 9561 (95.6%) zerosZeros
부상 has 9611 (96.1%) zerosZeros
재산피해소계 has 851 (8.5%) zerosZeros

Reproduction

Analysis started2023-12-12 21:20:58.543057
Analysis finished2023-12-12 21:20:59.582997
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20035.501
Minimum1
Maximum40112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:20:59.665673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2067.85
Q19983.75
median20181.5
Q329928.75
95-th percentile38068.2
Maximum40112
Range40111
Interquartile range (IQR)19945

Descriptive statistics

Standard deviation11546.979
Coefficient of variation (CV)0.57632596
Kurtosis-1.1911782
Mean20035.501
Median Absolute Deviation (MAD)9933
Skewness-0.00361643
Sum2.0035501 × 108
Variance1.3333273 × 108
MonotonicityNot monotonic
2023-12-13T06:21:00.116310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15290 1
 
< 0.1%
19852 1
 
< 0.1%
24823 1
 
< 0.1%
16316 1
 
< 0.1%
283 1
 
< 0.1%
16855 1
 
< 0.1%
11914 1
 
< 0.1%
7114 1
 
< 0.1%
21210 1
 
< 0.1%
2358 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
11 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
17 1
< 0.1%
28 1
< 0.1%
30 1
< 0.1%
ValueCountFrequency (%)
40112 1
< 0.1%
40110 1
< 0.1%
40109 1
< 0.1%
40106 1
< 0.1%
40105 1
< 0.1%
40102 1
< 0.1%
40098 1
< 0.1%
40094 1
< 0.1%
40093 1
< 0.1%
40090 1
< 0.1%

시도
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
2220 
서울특별시
1345 
경상남도
883 
경상북도
806 
전라남도
720 
Other values (12)
4026 

Length

Max length7
Median length5
Mean length4.3084
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상북도
2nd row경기도
3rd row충청남도
4th row경상북도
5th row울산광역시

Common Values

ValueCountFrequency (%)
경기도 2220
22.2%
서울특별시 1345
13.5%
경상남도 883
 
8.8%
경상북도 806
 
8.1%
전라남도 720
 
7.2%
부산광역시 586
 
5.9%
전라북도 529
 
5.3%
충청남도 523
 
5.2%
강원특별자치도 476
 
4.8%
충청북도 385
 
3.9%
Other values (7) 1527
15.3%

Length

2023-12-13T06:21:00.288261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 2220
22.2%
서울특별시 1345
13.5%
경상남도 883
 
8.8%
경상북도 806
 
8.1%
전라남도 720
 
7.2%
부산광역시 586
 
5.9%
전라북도 529
 
5.3%
충청남도 523
 
5.2%
강원특별자치도 476
 
4.8%
충청북도 385
 
3.9%
Other values (7) 1527
15.3%

시군구
Text

Distinct228
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:21:00.633363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.3349
Min length2

Characters and Unicode

Total characters33349
Distinct characters143
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 row의성군
2nd row고양시덕양구
3rd row예산군
4th row의성군
5th row남구
ValueCountFrequency (%)
서구 203
 
2.0%
화성시 193
 
1.9%
중구 170
 
1.7%
북구 158
 
1.5%
동구 157
 
1.5%
남구 154
 
1.5%
창원시 153
 
1.5%
강서구 152
 
1.5%
평택시 121
 
1.2%
김해시 115
 
1.1%
Other values (220) 8688
84.6%
2023-12-13T06:21:01.108154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 4853
 
14.6%
구 4333
 
13.0%
군 2278
 
6.8%
주 1320
 
4.0%
산 958
 
2.9%
성 931
 
2.8%
천 916
 
2.7%
양 826
 
2.5%
남 786
 
2.4%
서 751
 
2.3%
Other values (133) 15397
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33085
99.2%
Space Separator 264
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4853
 
14.7%
구 4333
 
13.1%
군 2278
 
6.9%
주 1320
 
4.0%
산 958
 
2.9%
성 931
 
2.8%
천 916
 
2.8%
양 826
 
2.5%
남 786
 
2.4%
서 751
 
2.3%
Other values (132) 15133
45.7%
Space Separator
ValueCountFrequency (%)
264
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33085
99.2%
Common 264
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4853
 
14.7%
구 4333
 
13.1%
군 2278
 
6.9%
주 1320
 
4.0%
산 958
 
2.9%
성 931
 
2.8%
천 916
 
2.8%
양 826
 
2.5%
남 786
 
2.4%
서 751
 
2.3%
Other values (132) 15133
45.7%
Common
ValueCountFrequency (%)
264
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33085
99.2%
ASCII 264
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 4853
 
14.7%
구 4333
 
13.1%
군 2278
 
6.9%
주 1320
 
4.0%
산 958
 
2.9%
성 931
 
2.8%
천 916
 
2.8%
양 826
 
2.5%
남 786
 
2.4%
서 751
 
2.3%
Other values (132) 15133
45.7%
ASCII
ValueCountFrequency (%)
264
100.0%

읍면동
Text

Distinct2622
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:21:01.471204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0417
Min length2

Characters and Unicode

Total characters30417
Distinct characters349
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

Unique791 ?
Unique (%)7.9%

Sample

1st row비안면
2nd row내유동
3rd row예산읍
4th row단밀면
5th row선암동
ValueCountFrequency (%)
신림동 41
 
0.4%
남면 36
 
0.4%
신정동 36
 
0.4%
대곶면 36
 
0.4%
정왕동 36
 
0.4%
중동 35
 
0.4%
봉천동 31
 
0.3%
논현동 31
 
0.3%
상동 29
 
0.3%
구로동 27
 
0.3%
Other values (2612) 9662
96.6%
2023-12-13T06:21:01.956884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 5872
 
19.3%
면 3024
 
9.9%
읍 1437
 
4.7%
산 711
 
2.3%
대 452
 
1.5%
가 450
 
1.5%
천 426
 
1.4%
신 426
 
1.4%
성 410
 
1.3%
정 398
 
1.3%
Other values (339) 16811
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30131
99.1%
Decimal Number 286
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5872
 
19.5%
면 3024
 
10.0%
읍 1437
 
4.8%
산 711
 
2.4%
대 452
 
1.5%
가 450
 
1.5%
천 426
 
1.4%
신 426
 
1.4%
성 410
 
1.4%
정 398
 
1.3%
Other values (331) 16525
54.8%
Decimal Number
ValueCountFrequency (%)
2 101
35.3%
1 82
28.7%
3 46
16.1%
6 18
 
6.3%
4 17
 
5.9%
7 12
 
4.2%
5 9
 
3.1%
8 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30131
99.1%
Common 286
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5872
 
19.5%
면 3024
 
10.0%
읍 1437
 
4.8%
산 711
 
2.4%
대 452
 
1.5%
가 450
 
1.5%
천 426
 
1.4%
신 426
 
1.4%
성 410
 
1.4%
정 398
 
1.3%
Other values (331) 16525
54.8%
Common
ValueCountFrequency (%)
2 101
35.3%
1 82
28.7%
3 46
16.1%
6 18
 
6.3%
4 17
 
5.9%
7 12
 
4.2%
5 9
 
3.1%
8 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30131
99.1%
ASCII 286
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 5872
 
19.5%
면 3024
 
10.0%
읍 1437
 
4.8%
산 711
 
2.4%
대 452
 
1.5%
가 450
 
1.5%
천 426
 
1.4%
신 426
 
1.4%
성 410
 
1.4%
정 398
 
1.3%
Other values (331) 16525
54.8%
ASCII
ValueCountFrequency (%)
2 101
35.3%
1 82
28.7%
3 46
16.1%
6 18
 
6.3%
4 17
 
5.9%
7 12
 
4.2%
5 9
 
3.1%
8 1
 
0.3%

화재발생(년)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 10000
100.0%

Length

2023-12-13T06:21:02.093396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:21:02.176933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

화재발생(월)
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1687
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:21:02.271012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5580762
Coefficient of variation (CV)0.57679514
Kurtosis-1.2416996
Mean6.1687
Median Absolute Deviation (MAD)3
Skewness0.15679195
Sum61687
Variance12.659906
MonotonicityNot monotonic
2023-12-13T06:21:02.380592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 1051
10.5%
5 1011
10.1%
2 982
9.8%
12 911
9.1%
4 900
9.0%
3 855
8.6%
10 741
7.4%
11 730
7.3%
6 726
7.3%
8 709
7.1%
Other values (2) 1384
13.8%
ValueCountFrequency (%)
1 1051
10.5%
2 982
9.8%
3 855
8.6%
4 900
9.0%
5 1011
10.1%
6 726
7.3%
7 702
7.0%
8 709
7.1%
9 682
6.8%
10 741
7.4%
ValueCountFrequency (%)
12 911
9.1%
11 730
7.3%
10 741
7.4%
9 682
6.8%
8 709
7.1%
7 702
7.0%
6 726
7.3%
5 1011
10.1%
4 900
9.0%
3 855
8.6%

화재발생(일)
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.6127
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:21:02.499391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.9063478
Coefficient of variation (CV)0.57045532
Kurtosis-1.2337349
Mean15.6127
Median Absolute Deviation (MAD)8
Skewness0.020748269
Sum156127
Variance79.323031
MonotonicityNot monotonic
2023-12-13T06:21:02.640866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
24 374
 
3.7%
7 368
 
3.7%
28 361
 
3.6%
2 361
 
3.6%
6 359
 
3.6%
20 356
 
3.6%
18 354
 
3.5%
4 348
 
3.5%
5 346
 
3.5%
8 339
 
3.4%
Other values (21) 6434
64.3%
ValueCountFrequency (%)
1 328
3.3%
2 361
3.6%
3 338
3.4%
4 348
3.5%
5 346
3.5%
6 359
3.6%
7 368
3.7%
8 339
3.4%
9 302
3.0%
10 331
3.3%
ValueCountFrequency (%)
31 205
2.1%
30 287
2.9%
29 292
2.9%
28 361
3.6%
27 329
3.3%
26 326
3.3%
25 306
3.1%
24 374
3.7%
23 323
3.2%
22 314
3.1%

화재발생(시)
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.9422
Minimum0
Maximum23
Zeros294
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:21:02.776180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median13
Q318
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.0335976
Coefficient of variation (CV)0.46619567
Kurtosis-0.61161782
Mean12.9422
Median Absolute Deviation (MAD)4
Skewness-0.3739995
Sum129422
Variance36.4043
MonotonicityNot monotonic
2023-12-13T06:21:02.891964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
14 664
 
6.6%
13 659
 
6.6%
16 619
 
6.2%
12 618
 
6.2%
15 593
 
5.9%
17 568
 
5.7%
10 555
 
5.5%
11 554
 
5.5%
18 550
 
5.5%
19 470
 
4.7%
Other values (14) 4150
41.5%
ValueCountFrequency (%)
0 294
2.9%
1 239
2.4%
2 235
2.4%
3 213
2.1%
4 181
1.8%
5 222
2.2%
6 242
2.4%
7 263
2.6%
8 343
3.4%
9 409
4.1%
ValueCountFrequency (%)
23 336
3.4%
22 364
3.6%
21 398
4.0%
20 411
4.1%
19 470
4.7%
18 550
5.5%
17 568
5.7%
16 619
6.2%
15 593
5.9%
14 664
6.6%

화재발생(분)
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.3537
Minimum0
Maximum59
Zeros209
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:21:03.016309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q114
median30
Q344
95-th percentile56
Maximum59
Range59
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.389515
Coefficient of variation (CV)0.59241306
Kurtosis-1.2093318
Mean29.3537
Median Absolute Deviation (MAD)15
Skewness-0.0069255731
Sum293537
Variance302.39524
MonotonicityNot monotonic
2023-12-13T06:21:03.157138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 209
 
2.1%
54 194
 
1.9%
30 190
 
1.9%
37 189
 
1.9%
21 189
 
1.9%
14 187
 
1.9%
47 184
 
1.8%
43 184
 
1.8%
26 183
 
1.8%
5 182
 
1.8%
Other values (50) 8109
81.1%
ValueCountFrequency (%)
0 209
2.1%
1 154
1.5%
2 178
1.8%
3 176
1.8%
4 153
1.5%
5 182
1.8%
6 167
1.7%
7 163
1.6%
8 179
1.8%
9 151
1.5%
ValueCountFrequency (%)
59 156
1.6%
58 165
1.7%
57 148
1.5%
56 158
1.6%
55 173
1.7%
54 194
1.9%
53 160
1.6%
52 164
1.6%
51 164
1.6%
50 157
1.6%

요일
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
토
1523 
금
1474 
수
1459 
목
1427 
월
1409 
Other values (2)
2708 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일
2nd row목
3rd row토
4th row월
5th row목

Common Values

ValueCountFrequency (%)
토 1523
15.2%
금 1474
14.7%
수 1459
14.6%
목 1427
14.3%
월 1409
14.1%
화 1356
13.6%
일 1352
13.5%

Length

2023-12-13T06:21:03.341783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:21:03.453773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토 1523
15.2%
금 1474
14.7%
수 1459
14.6%
목 1427
14.3%
월 1409
14.1%
화 1356
13.6%
일 1352
13.5%

인명피해(명)소계
Real number (ℝ)

SKEWED  ZEROS 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0671
Minimum0
Maximum48
Zeros9561
Zeros (%)95.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:21:03.563683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum48
Range48
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.62468921
Coefficient of variation (CV)9.3098243
Kurtosis3543.7181
Mean0.0671
Median Absolute Deviation (MAD)0
Skewness49.512019
Sum671
Variance0.39023661
MonotonicityNot monotonic
2023-12-13T06:21:03.680273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 9561
95.6%
1 344
 
3.4%
2 63
 
0.6%
3 14
 
0.1%
4 6
 
0.1%
5 4
 
< 0.1%
6 2
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
13 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
0 9561
95.6%
1 344
 
3.4%
2 63
 
0.6%
3 14
 
0.1%
4 6
 
0.1%
5 4
 
< 0.1%
6 2
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
48 1
 
< 0.1%
16 1
 
< 0.1%
13 1
 
< 0.1%
10 1
 
< 0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
5 4
 
< 0.1%
4 6
 
0.1%
3 14
 
0.1%
2 63
0.6%

사망
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9930 
1
 
62
2
 
6
7
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9930
99.3%
1 62
 
0.6%
2 6
 
0.1%
7 1
 
< 0.1%
5 1
 
< 0.1%

Length

2023-12-13T06:21:03.808562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:21:03.908875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9930
99.3%
1 62
 
0.6%
2 6
 
0.1%
7 1
 
< 0.1%
5 1
 
< 0.1%

부상
Real number (ℝ)

SKEWED  ZEROS 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0585
Minimum0
Maximum43
Zeros9611
Zeros (%)96.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:21:04.005630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum43
Range43
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.56401202
Coefficient of variation (CV)9.6412311
Kurtosis3449.8475
Mean0.0585
Median Absolute Deviation (MAD)0
Skewness48.809612
Sum585
Variance0.31810956
MonotonicityNot monotonic
2023-12-13T06:21:04.093367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 9611
96.1%
1 310
 
3.1%
2 49
 
0.5%
3 15
 
0.1%
4 6
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
13 1
 
< 0.1%
7 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
0 9611
96.1%
1 310
 
3.1%
2 49
 
0.5%
3 15
 
0.1%
4 6
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
43 1
 
< 0.1%
15 1
 
< 0.1%
13 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
4 6
 
0.1%
3 15
 
0.1%
2 49
0.5%

재산피해소계
Real number (ℝ)

SKEWED  ZEROS 

Distinct4189
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23228.677
Minimum0
Maximum31767193
Zeros851
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:21:04.216638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1110
median583.5
Q33759.25
95-th percentile39552.9
Maximum31767193
Range31767193
Interquartile range (IQR)3649.25

Descriptive statistics

Standard deviation413856.74
Coefficient of variation (CV)17.81663
Kurtosis3986.5711
Mean23228.677
Median Absolute Deviation (MAD)578.5
Skewness57.768501
Sum2.3228677 × 108
Variance1.712774 × 1011
MonotonicityNot monotonic
2023-12-13T06:21:04.355451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 851
 
8.5%
110 94
 
0.9%
11 82
 
0.8%
55 74
 
0.7%
330 71
 
0.7%
220 59
 
0.6%
550 56
 
0.6%
1100 50
 
0.5%
1 44
 
0.4%
33 41
 
0.4%
Other values (4179) 8578
85.8%
ValueCountFrequency (%)
0 851
8.5%
1 44
 
0.4%
2 15
 
0.1%
3 14
 
0.1%
4 17
 
0.2%
5 32
 
0.3%
6 20
 
0.2%
7 10
 
0.1%
8 19
 
0.2%
9 25
 
0.2%
ValueCountFrequency (%)
31767193 1
< 0.1%
19527987 1
< 0.1%
8585291 1
< 0.1%
6234786 1
< 0.1%
4915811 1
< 0.1%
4751542 1
< 0.1%
4707978 1
< 0.1%
3872300 1
< 0.1%
3816120 1
< 0.1%
3511252 1
< 0.1%

화재유형
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
건축,구조물
6330 
기타(쓰레기 화재등)
1911 
자동차,철도차량
1188 
임야
 
524
선박,항공기
 
41

Length

Max length11
Median length6
Mean length6.9859
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건축,구조물
2nd row건축,구조물
3rd row임야
4th row건축,구조물
5th row자동차,철도차량

Common Values

ValueCountFrequency (%)
건축,구조물 6330
63.3%
기타(쓰레기 화재등) 1911
 
19.1%
자동차,철도차량 1188
 
11.9%
임야 524
 
5.2%
선박,항공기 41
 
0.4%
위험물,가스제조소등 6
 
0.1%

Length

2023-12-13T06:21:04.495942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:21:04.603149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축,구조물 6330
53.1%
기타(쓰레기 1911
 
16.0%
화재등 1911
 
16.0%
자동차,철도차량 1188
 
10.0%
임야 524
 
4.4%
선박,항공기 41
 
0.3%
위험물,가스제조소등 6
 
0.1%

발화요인대분류
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부주의
4925 
전기적 요인
2518 
기계적 요인
967 
미상
919 
화학적 요인
 
190
Other values (7)
 
481

Length

Max length8
Median length7
Mean length4.0424
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부주의 4925
49.2%
전기적 요인 2518
25.2%
기계적 요인 967
 
9.7%
미상 919
 
9.2%
화학적 요인 190
 
1.9%
기타 107
 
1.1%
교통사고 106
 
1.1%
방화 96
 
1.0%
방화의심 67
 
0.7%
자연적인 요인 37
 
0.4%
Other values (2) 68
 
0.7%

Length

2023-12-13T06:21:04.737498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부주의 4925
35.9%
요인 3712
27.1%
전기적 2518
18.4%
기계적 967
 
7.1%
미상 919
 
6.7%
화학적 190
 
1.4%
기타 107
 
0.8%
교통사고 106
 
0.8%
방화 96
 
0.7%
방화의심 67
 
0.5%
Other values (3) 105
 
0.8%

발화요인소분류
Categorical

Distinct49
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
담배꽁초
1585 
미상
919 
미확인단락
854 
불씨,불꽃,화원방치
723 
음식물 조리중
622 
Other values (44)
5297 

Length

Max length21
Median length12
Mean length6.8849
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가연물 근접방치
2nd row기타(부주의)
3rd row논,임야태우기
4th row불씨,불꽃,화원방치
5th row가연물 근접방치

Common Values

ValueCountFrequency (%)
담배꽁초 1585
15.8%
미상 919
 
9.2%
미확인단락 854
 
8.5%
불씨,불꽃,화원방치 723
 
7.2%
음식물 조리중 622
 
6.2%
과열, 과부하 617
 
6.2%
쓰레기 소각 595
 
5.9%
절연열화에 의한 단락 473
 
4.7%
기기(전기, 기계 등) 사용.설치부주의 363
 
3.6%
트래킹에 의한 단락 316
 
3.2%
Other values (39) 2933
29.3%

Length

2023-12-13T06:21:04.851261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
담배꽁초 1585
 
9.8%
의한 1167
 
7.2%
단락 1167
 
7.2%
미상 919
 
5.7%
미확인단락 854
 
5.3%
불씨,불꽃,화원방치 723
 
4.5%
음식물 622
 
3.8%
조리중 622
 
3.8%
과열 617
 
3.8%
과부하 617
 
3.8%
Other values (58) 7329
45.2%

최초착화물대분류
Categorical

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
종이,목재,건초등
2276 
전기,전자
2253 
쓰레기류
1215 
합성수지
1031 
미상
753 
Other values (8)
2472 

Length

Max length15
Median length7
Mean length5.5984
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종이,목재,건초등
2nd row합성수지
3rd row종이,목재,건초등
4th row기타
5th row쓰레기류

Common Values

ValueCountFrequency (%)
종이,목재,건초등 2276
22.8%
전기,전자 2253
22.5%
쓰레기류 1215
12.2%
합성수지 1031
10.3%
미상 753
 
7.5%
기타 740
 
7.4%
식품 560
 
5.6%
자동차,철도차량,선박,항공기 535
 
5.3%
침구,직물류 284
 
2.8%
위험물등 179
 
1.8%
Other values (3) 174
 
1.7%

Length

2023-12-13T06:21:04.981571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종이,목재,건초등 2276
22.8%
전기,전자 2253
22.5%
쓰레기류 1215
12.2%
합성수지 1031
10.3%
미상 753
 
7.5%
기타 740
 
7.4%
식품 560
 
5.6%
자동차,철도차량,선박,항공기 535
 
5.3%
침구,직물류 284
 
2.8%
위험물등 179
 
1.8%
Other values (3) 174
 
1.7%

최초착화물소분류
Text

Distinct83
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:21:05.221961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length5.6321
Min length2

Characters and Unicode

Total characters56321
Distinct characters165
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

Unique5 ?
Unique (%)< 0.1%

Sample

1st row나무
2nd row아크릴수지
3rd row건초
4th row기타
5th row쓰레기
ValueCountFrequency (%)
전선피복 1330
 
9.1%
쓰레기 1009
 
6.9%
기타 922
 
6.3%
미상 753
 
5.1%
플라스틱 737
 
5.0%
pvc 737
 
5.0%
비닐 737
 
5.0%
장판 737
 
5.0%
종이 595
 
4.1%
풀 555
 
3.8%
Other values (92) 6565
44.7%
2023-12-13T06:21:05.648739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 4923
 
8.7%
기 4681
 
8.3%
4677
 
8.3%
전 2618
 
4.6%
타 1849
 
3.3%
선 1618
 
2.9%
피 1330
 
2.4%
복 1330
 
2.4%
판 1250
 
2.2%
스 1237
 
2.2%
Other values (155) 30808
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42433
75.3%
Other Punctuation 4923
 
8.7%
Space Separator 4677
 
8.3%
Uppercase Letter 2211
 
3.9%
Close Punctuation 1023
 
1.8%
Open Punctuation 1023
 
1.8%
Decimal Number 31
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 4681
 
11.0%
전 2618
 
6.2%
타 1849
 
4.4%
선 1618
 
3.8%
피 1330
 
3.1%
복 1330
 
3.1%
판 1250
 
2.9%
스 1237
 
2.9%
이 1142
 
2.7%
레 1055
 
2.5%
Other values (144) 24323
57.3%
Decimal Number
ValueCountFrequency (%)
4 26
83.9%
1 3
 
9.7%
3 1
 
3.2%
2 1
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
P 737
33.3%
C 737
33.3%
V 737
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4923
100.0%
Space Separator
ValueCountFrequency (%)
4677
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1023
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1023
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42433
75.3%
Common 11677
 
20.7%
Latin 2211
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 4681
 
11.0%
전 2618
 
6.2%
타 1849
 
4.4%
선 1618
 
3.8%
피 1330
 
3.1%
복 1330
 
3.1%
판 1250
 
2.9%
스 1237
 
2.9%
이 1142
 
2.7%
레 1055
 
2.5%
Other values (144) 24323
57.3%
Common
ValueCountFrequency (%)
, 4923
42.2%
4677
40.1%
) 1023
 
8.8%
( 1023
 
8.8%
4 26
 
0.2%
1 3
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
Latin
ValueCountFrequency (%)
P 737
33.3%
C 737
33.3%
V 737
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42433
75.3%
ASCII 13888
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 4923
35.4%
4677
33.7%
) 1023
 
7.4%
( 1023
 
7.4%
P 737
 
5.3%
C 737
 
5.3%
V 737
 
5.3%
4 26
 
0.2%
1 3
 
< 0.1%
3 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
기 4681
 
11.0%
전 2618
 
6.2%
타 1849
 
4.4%
선 1618
 
3.8%
피 1330
 
3.1%
복 1330
 
3.1%
판 1250
 
2.9%
스 1237
 
2.9%
이 1142
 
2.7%
레 1055
 
2.5%
Other values (144) 24323
57.3%

발화관련기기대분류
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5863 
주방기기
670 
차량, 선박부품
651 
계절용 기기
631 
배선/배선기구
 
556
Other values (12)
1629 

Length

Max length8
Median length4
Mean length4.4944
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row산업장비
3rd row<NA>
4th row기타
5th row차량, 선박부품

Common Values

ValueCountFrequency (%)
<NA> 5863
58.6%
주방기기 670
 
6.7%
차량, 선박부품 651
 
6.5%
계절용 기기 631
 
6.3%
배선/배선기구 556
 
5.6%
산업장비 443
 
4.4%
기타 321
 
3.2%
전기설비 316
 
3.2%
생활기기 182
 
1.8%
미상 144
 
1.4%
Other values (7) 223
 
2.2%

Length

2023-12-13T06:21:05.799215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5863
51.5%
주방기기 670
 
5.9%
차량 651
 
5.7%
선박부품 651
 
5.7%
계절용 631
 
5.5%
기기 631
 
5.5%
배선/배선기구 556
 
4.9%
산업장비 443
 
3.9%
기타 321
 
2.8%
전기설비 316
 
2.8%
Other values (10) 655
 
5.8%

발화관련기기소분류
Text

MISSING 

Distinct151
Distinct (%)3.6%
Missing5863
Missing (%)58.6%
Memory size156.2 KiB
2023-12-13T06:21:06.063143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length5.8694706
Min length2

Characters and Unicode

Total characters24282
Distinct characters234
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.5%

Sample

1st row기타(산업장비)
2nd row기타
3rd row엔진본체
4th row화목보일러
5th row용접절단기(토치)
ValueCountFrequency (%)
기타 321
 
6.9%
가스렌지 273
 
5.9%
기타(차량,선박부품 167
 
3.6%
미상 144
 
3.1%
전선 138
 
3.0%
배선 134
 
2.9%
용접절단기(토치 124
 
2.7%
배전반/분전반 116
 
2.5%
기타(산업장비 109
 
2.3%
엔진본체 106
 
2.3%
Other values (154) 3018
64.9%
2023-12-13T06:21:06.459006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 2928
 
12.1%
전 1104
 
4.5%
타 1009
 
4.2%
선 952
 
3.9%
/ 873
 
3.6%
) 820
 
3.4%
( 820
 
3.4%
배 711
 
2.9%
용 559
 
2.3%
513
 
2.1%
Other values (224) 13993
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20831
85.8%
Other Punctuation 1133
 
4.7%
Close Punctuation 820
 
3.4%
Open Punctuation 820
 
3.4%
Space Separator 513
 
2.1%
Uppercase Letter 165
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 2928
 
14.1%
전 1104
 
5.3%
타 1009
 
4.8%
선 952
 
4.6%
배 711
 
3.4%
용 559
 
2.7%
장 488
 
2.3%
스 480
 
2.3%
가 408
 
2.0%
치 400
 
1.9%
Other values (209) 11792
56.6%
Uppercase Letter
ValueCountFrequency (%)
L 49
29.7%
D 47
28.5%
E 47
28.5%
P 6
 
3.6%
S 4
 
2.4%
U 4
 
2.4%
G 2
 
1.2%
R 2
 
1.2%
V 2
 
1.2%
A 2
 
1.2%
Other Punctuation
ValueCountFrequency (%)
/ 873
77.1%
, 260
 
22.9%
Close Punctuation
ValueCountFrequency (%)
) 820
100.0%
Open Punctuation
ValueCountFrequency (%)
( 820
100.0%
Space Separator
ValueCountFrequency (%)
513
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20831
85.8%
Common 3286
 
13.5%
Latin 165
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 2928
 
14.1%
전 1104
 
5.3%
타 1009
 
4.8%
선 952
 
4.6%
배 711
 
3.4%
용 559
 
2.7%
장 488
 
2.3%
스 480
 
2.3%
가 408
 
2.0%
치 400
 
1.9%
Other values (209) 11792
56.6%
Latin
ValueCountFrequency (%)
L 49
29.7%
D 47
28.5%
E 47
28.5%
P 6
 
3.6%
S 4
 
2.4%
U 4
 
2.4%
G 2
 
1.2%
R 2
 
1.2%
V 2
 
1.2%
A 2
 
1.2%
Common
ValueCountFrequency (%)
/ 873
26.6%
) 820
25.0%
( 820
25.0%
513
15.6%
, 260
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20831
85.8%
ASCII 3451
 
14.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 2928
 
14.1%
전 1104
 
5.3%
타 1009
 
4.8%
선 952
 
4.6%
배 711
 
3.4%
용 559
 
2.7%
장 488
 
2.3%
스 480
 
2.3%
가 408
 
2.0%
치 400
 
1.9%
Other values (209) 11792
56.6%
ASCII
ValueCountFrequency (%)
/ 873
25.3%
) 820
23.8%
( 820
23.8%
513
14.9%
, 260
 
7.5%
L 49
 
1.4%
D 47
 
1.4%
E 47
 
1.4%
P 6
 
0.2%
S 4
 
0.1%
Other values (5) 12
 
0.3%

장소대분류
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주거
2575 
기타
1911 
산업시설
1319 
자동차,철도차량
1188 
생활서비스
891 
Other values (10)
2116 

Length

Max length9
Median length2
Mean length3.8864
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주거
2nd row산업시설
3rd row임야
4th row주거
5th row자동차,철도차량

Common Values

ValueCountFrequency (%)
주거 2575
25.8%
기타 1911
19.1%
산업시설 1319
13.2%
자동차,철도차량 1188
11.9%
생활서비스 891
 
8.9%
판매,업무시설 711
 
7.1%
임야 524
 
5.2%
기타서비스 520
 
5.2%
의료,복지시설 90
 
0.9%
교육시설 80
 
0.8%
Other values (5) 191
 
1.9%

Length

2023-12-13T06:21:06.681049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주거 2575
25.8%
기타 1911
19.1%
산업시설 1319
13.2%
자동차,철도차량 1188
11.9%
생활서비스 891
 
8.9%
판매,업무시설 711
 
7.1%
임야 524
 
5.2%
기타서비스 520
 
5.2%
의료,복지시설 90
 
0.9%
교육시설 80
 
0.8%
Other values (5) 191
 
1.9%

장소중분류
Categorical

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
야외
1834 
단독주택
1343 
공동주택
1116 
자동차
1084 
음식점
639 
Other values (40)
3984 

Length

Max length7
Median length6
Mean length3.4244
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row단독주택
2nd row공장시설
3rd row들불
4th row단독주택
5th row자동차

Common Values

ValueCountFrequency (%)
야외 1834
18.3%
단독주택 1343
13.4%
공동주택 1116
11.2%
자동차 1084
10.8%
음식점 639
 
6.4%
공장시설 576
 
5.8%
기타건축물 520
 
5.2%
창고시설 371
 
3.7%
들불 324
 
3.2%
일반업무 291
 
2.9%
Other values (35) 1902
19.0%

Length

2023-12-13T06:21:06.794782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
야외 1834
18.3%
단독주택 1343
13.4%
공동주택 1116
11.2%
자동차 1084
10.8%
음식점 639
 
6.4%
공장시설 576
 
5.8%
기타건축물 520
 
5.2%
창고시설 371
 
3.7%
들불 324
 
3.2%
일반업무 291
 
2.9%
Other values (35) 1902
19.0%

장소소분류
Text

Distinct254
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:21:07.101439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length16
Mean length4.8554
Min length1

Characters and Unicode

Total characters48554
Distinct characters285
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)0.5%

Sample

1st row단독주택
2nd row식료품공업
3rd row들판
4th row단독주택
5th row화물자동차
ValueCountFrequency (%)
기타 1350
 
10.3%
단독주택 941
 
7.2%
기타야외 896
 
6.9%
쓰레기 682
 
5.2%
아파트 652
 
5.0%
승용자동차 531
 
4.1%
건축물 503
 
3.9%
화물자동차 389
 
3.0%
창고 349
 
2.7%
다가구주택 308
 
2.4%
Other values (279) 6452
49.4%
2023-12-13T06:21:07.701883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 3523
 
7.3%
3053
 
6.3%
타 2287
 
4.7%
주 2027
 
4.2%
택 1878
 
3.9%
물 1240
 
2.6%
동 1178
 
2.4%
차 1066
 
2.2%
자 1058
 
2.2%
야 989
 
2.0%
Other values (275) 30255
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44357
91.4%
Space Separator 3053
 
6.3%
Other Punctuation 622
 
1.3%
Close Punctuation 252
 
0.5%
Open Punctuation 252
 
0.5%
Uppercase Letter 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 3523
 
7.9%
타 2287
 
5.2%
주 2027
 
4.6%
택 1878
 
4.2%
물 1240
 
2.8%
동 1178
 
2.7%
차 1066
 
2.4%
자 1058
 
2.4%
야 989
 
2.2%
단 974
 
2.2%
Other values (266) 28137
63.4%
Uppercase Letter
ValueCountFrequency (%)
S 6
33.3%
A 6
33.3%
C 3
16.7%
P 3
16.7%
Other Punctuation
ValueCountFrequency (%)
, 616
99.0%
/ 6
 
1.0%
Space Separator
ValueCountFrequency (%)
3053
100.0%
Close Punctuation
ValueCountFrequency (%)
) 252
100.0%
Open Punctuation
ValueCountFrequency (%)
( 252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44357
91.4%
Common 4179
 
8.6%
Latin 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 3523
 
7.9%
타 2287
 
5.2%
주 2027
 
4.6%
택 1878
 
4.2%
물 1240
 
2.8%
동 1178
 
2.7%
차 1066
 
2.4%
자 1058
 
2.4%
야 989
 
2.2%
단 974
 
2.2%
Other values (266) 28137
63.4%
Common
ValueCountFrequency (%)
3053
73.1%
, 616
 
14.7%
) 252
 
6.0%
( 252
 
6.0%
/ 6
 
0.1%
Latin
ValueCountFrequency (%)
S 6
33.3%
A 6
33.3%
C 3
16.7%
P 3
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44357
91.4%
ASCII 4197
 
8.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 3523
 
7.9%
타 2287
 
5.2%
주 2027
 
4.6%
택 1878
 
4.2%
물 1240
 
2.8%
동 1178
 
2.7%
차 1066
 
2.4%
자 1058
 
2.4%
야 989
 
2.2%
단 974
 
2.2%
Other values (266) 28137
63.4%
ASCII
ValueCountFrequency (%)
3053
72.7%
, 616
 
14.7%
) 252
 
6.0%
( 252
 
6.0%
S 6
 
0.1%
/ 6
 
0.1%
A 6
 
0.1%
C 3
 
0.1%
P 3
 
0.1%

차량장소
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8812 
일반도로
 
509
주차장
 
219
고속도로
 
215
공지
 
154
Other values (2)
 
91

Length

Max length5
Median length4
Mean length3.9549
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8812
88.1%
일반도로 509
 
5.1%
주차장 219
 
2.2%
고속도로 215
 
2.1%
공지 154
 
1.5%
기타 도로 86
 
0.9%
터널 5
 
0.1%

Length

2023-12-13T06:21:07.894369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:21:08.049187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8812
87.4%
일반도로 509
 
5.0%
주차장 219
 
2.2%
고속도로 215
 
2.1%
공지 154
 
1.5%
기타 86
 
0.9%
도로 86
 
0.9%
터널 5
 
< 0.1%

Sample

연번시도시군구읍면동화재발생(년)화재발생(월)화재발생(일)화재발생(시)화재발생(분)요일인명피해(명)소계사망부상재산피해소계화재유형발화요인대분류발화요인소분류최초착화물대분류최초착화물소분류발화관련기기대분류발화관련기기소분류장소대분류장소중분류장소소분류차량장소
1528915290경상북도의성군비안면2022511034일0001343건축,구조물부주의가연물 근접방치종이,목재,건초등나무<NA><NA>주거단독주택단독주택<NA>
2095120952경기도고양시덕양구내유동20226161210목00081485건축,구조물부주의기타(부주의)합성수지아크릴수지산업장비기타(산업장비)산업시설공장시설식료품공업<NA>
57225723충청남도예산군예산읍20222121551토000553임야부주의논,임야태우기종이,목재,건초등건초<NA><NA>임야들불들판<NA>
3180831809경상북도의성군단밀면202210171837월00015741건축,구조물부주의불씨,불꽃,화원방치기타기타기타기타주거단독주택단독주택<NA>
1503415035울산광역시남구선암동20224281221목000660자동차,철도차량부주의가연물 근접방치쓰레기류쓰레기차량, 선박부품엔진본체자동차,철도차량자동차화물자동차일반도로
2423624237대구광역시북구노곡동2022723158토00022자동차,철도차량부주의담배꽁초쓰레기류기타 쓰레기<NA><NA>자동차,철도차량자동차화물자동차일반도로
3760537606충청남도당진시송악읍20221211108일000570건축,구조물부주의가연물 근접방치종이,목재,건초등종이계절용 기기화목보일러주거단독주택단독주택<NA>
25982599광주광역시광산구신창동20221201518목10135건축,구조물부주의용접, 절단, 연마합성수지기타(합성수지)산업장비용접절단기(토치)판매,업무시설판매시설기타 판매시설<NA>
1176811769경상남도거창군거창읍20224319일0003075건축,구조물기계적 요인과열, 과부하합성수지플라스틱, PVC, 비닐, 장판기타기타생활서비스음식점횟집<NA>
3239032391경기도양평군서종면202210221829토000429건축,구조물부주의용접, 절단, 연마합성수지플라스틱, PVC, 비닐, 장판<NA><NA>주거단독주택단독주택<NA>
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