Overview

Dataset statistics

Number of variables29
Number of observations10000
Missing cells20343
Missing cells (%)7.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 MiB
Average record size in memory254.0 B

Variable types

Categorical12
Numeric11
Text5
Boolean1

Dataset

Description2019년 기준부터 2021년까지 울산광역시 안전사고의 재난일시, 재난장소, 재난대상물, 관할 소방서·센터 정보 데이터
Author울산광역시
URLhttps://www.data.go.kr/data/15109140/fileData.do

Alerts

재난시명 has constant value ""Constant
지하 여부 has constant value ""Constant
접수경로명 is highly imbalanced (55.1%)Imbalance
화학사고여부 is highly imbalanced (99.7%)Imbalance
주용도명 is highly imbalanced (70.7%)Imbalance
건물구조식 is highly imbalanced (70.7%)Imbalance
건물구조조 is highly imbalanced (72.2%)Imbalance
건물구조즙 is highly imbalanced (74.2%)Imbalance
재난리명 has 7523 (75.2%) missing valuesMissing
도로명 has 2553 (25.5%) missing valuesMissing
읍면동순번 has 2473 (24.7%) missing valuesMissing
대상물명 has 7794 (77.9%) missing valuesMissing
신고시 has 439 (4.4%) zerosZeros
신고분 has 188 (1.9%) zerosZeros
상황종료시 has 434 (4.3%) zerosZeros
상황종료분 has 189 (1.9%) zerosZeros
지상층수 has 7812 (78.1%) zerosZeros
지하층수 has 8846 (88.5%) zerosZeros

Reproduction

Analysis started2024-03-14 18:51:55.673388
Analysis finished2024-03-14 18:51:57.921559
Duration2.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접수경로명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
이동전화
6479 
기타
1801 
사후각지
775 
일반전화
766 
IP전화
 
118
Other values (6)
 
61

Length

Max length6
Median length4
Mean length3.6484
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이동전화 6479
64.8%
기타 1801
 
18.0%
사후각지 775
 
7.8%
일반전화 766
 
7.7%
IP전화 118
 
1.2%
모바일앱신고 32
 
0.3%
SMS신고 11
 
0.1%
MMS신고 9
 
0.1%
공중전화 5
 
0.1%
WEB신고 2
 
< 0.1%

Length

2024-03-15T03:51:58.148585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이동전화 6479
64.8%
기타 1801
 
18.0%
사후각지 775
 
7.8%
일반전화 766
 
7.7%
ip전화 118
 
1.2%
모바일앱신고 32
 
0.3%
sms신고 11
 
0.1%
mms신고 9
 
0.1%
공중전화 5
 
< 0.1%
web신고 2
 
< 0.1%

신고연도
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020
3517 
2019
3426 
2021
3057 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2020
3rd row2019
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 3517
35.2%
2019 3426
34.3%
2021 3057
30.6%

Length

2024-03-15T03:51:58.557287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:51:58.814152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 3517
35.2%
2019 3426
34.3%
2021 3057
30.6%

신고월
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8461
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:51:59.109708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2013184
Coefficient of variation (CV)0.46761199
Kurtosis-0.93532869
Mean6.8461
Median Absolute Deviation (MAD)2
Skewness-0.23450408
Sum68461
Variance10.24844
MonotonicityNot monotonic
2024-03-15T03:51:59.475040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
9 1204
12.0%
7 1191
11.9%
8 1110
11.1%
6 898
9.0%
10 848
8.5%
5 756
7.6%
11 741
7.4%
1 714
7.1%
12 692
6.9%
4 656
6.6%
Other values (2) 1190
11.9%
ValueCountFrequency (%)
1 714
7.1%
2 603
6.0%
3 587
5.9%
4 656
6.6%
5 756
7.6%
6 898
9.0%
7 1191
11.9%
8 1110
11.1%
9 1204
12.0%
10 848
8.5%
ValueCountFrequency (%)
12 692
6.9%
11 741
7.4%
10 848
8.5%
9 1204
12.0%
8 1110
11.1%
7 1191
11.9%
6 898
9.0%
5 756
7.6%
4 656
6.6%
3 587
5.9%

신고일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.7308
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:51:59.718514image/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 deviation8.8501844
Coefficient of variation (CV)0.56260231
Kurtosis-1.214107
Mean15.7308
Median Absolute Deviation (MAD)8
Skewness-0.019004804
Sum157308
Variance78.325764
MonotonicityNot monotonic
2024-03-15T03:52:00.141694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
3 396
 
4.0%
22 396
 
4.0%
2 369
 
3.7%
27 354
 
3.5%
19 352
 
3.5%
21 346
 
3.5%
4 344
 
3.4%
20 342
 
3.4%
23 338
 
3.4%
11 337
 
3.4%
Other values (21) 6426
64.3%
ValueCountFrequency (%)
1 302
3.0%
2 369
3.7%
3 396
4.0%
4 344
3.4%
5 327
3.3%
6 320
3.2%
7 321
3.2%
8 302
3.0%
9 286
2.9%
10 317
3.2%
ValueCountFrequency (%)
31 179
1.8%
30 314
3.1%
29 276
2.8%
28 333
3.3%
27 354
3.5%
26 330
3.3%
25 299
3.0%
24 330
3.3%
23 338
3.4%
22 396
4.0%

신고시
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.4521
Minimum0
Maximum23
Zeros439
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:52:00.462944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median13
Q318
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.9083629
Coefficient of variation (CV)0.55479501
Kurtosis-1.1193612
Mean12.4521
Median Absolute Deviation (MAD)6
Skewness-0.22301383
Sum124521
Variance47.725478
MonotonicityNot monotonic
2024-03-15T03:52:00.687344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
18 544
 
5.4%
22 542
 
5.4%
21 507
 
5.1%
20 483
 
4.8%
17 481
 
4.8%
19 468
 
4.7%
16 466
 
4.7%
15 447
 
4.5%
23 440
 
4.4%
0 439
 
4.4%
Other values (14) 5183
51.8%
ValueCountFrequency (%)
0 439
4.4%
1 372
3.7%
2 339
3.4%
3 338
3.4%
4 272
2.7%
5 239
2.4%
6 305
3.0%
7 374
3.7%
8 421
4.2%
9 424
4.2%
ValueCountFrequency (%)
23 440
4.4%
22 542
5.4%
21 507
5.1%
20 483
4.8%
19 468
4.7%
18 544
5.4%
17 481
4.8%
16 466
4.7%
15 447
4.5%
14 424
4.2%

신고분
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.342
Minimum0
Maximum59
Zeros188
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:52:00.980518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q114
median29
Q345
95-th percentile56
Maximum59
Range59
Interquartile range (IQR)31

Descriptive statistics

Standard deviation17.314139
Coefficient of variation (CV)0.5900804
Kurtosis-1.2046106
Mean29.342
Median Absolute Deviation (MAD)15
Skewness-0.003058727
Sum293420
Variance299.77941
MonotonicityNot monotonic
2024-03-15T03:52:01.428260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21 197
 
2.0%
47 191
 
1.9%
33 188
 
1.9%
0 188
 
1.9%
5 187
 
1.9%
16 185
 
1.8%
43 182
 
1.8%
18 182
 
1.8%
37 182
 
1.8%
50 181
 
1.8%
Other values (50) 8137
81.4%
ValueCountFrequency (%)
0 188
1.9%
1 175
1.8%
2 172
1.7%
3 155
1.6%
4 175
1.8%
5 187
1.9%
6 132
1.3%
7 178
1.8%
8 178
1.8%
9 163
1.6%
ValueCountFrequency (%)
59 128
1.3%
58 173
1.7%
57 159
1.6%
56 158
1.6%
55 168
1.7%
54 170
1.7%
53 174
1.7%
52 154
1.5%
51 174
1.7%
50 181
1.8%

재난시명
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울산광역시 10000
100.0%

Length

2024-03-15T03:52:01.691475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:52:01.847389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산광역시 10000
100.0%

재난구명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남구
2908 
울주군
2477 
북구
1710 
중구
1563 
동구
1342 

Length

Max length3
Median length2
Mean length2.2477
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중구
2nd row남구
3rd row남구
4th row동구
5th row남구

Common Values

ValueCountFrequency (%)
남구 2908
29.1%
울주군 2477
24.8%
북구 1710
17.1%
중구 1563
15.6%
동구 1342
13.4%

Length

2024-03-15T03:52:02.257709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:52:02.613884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남구 2908
29.1%
울주군 2477
24.8%
북구 1710
17.1%
중구 1563
15.6%
동구 1342
13.4%

재난동명
Text

Distinct85
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T03:52:03.704443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9238
Min length2

Characters and Unicode

Total characters29238
Distinct characters87
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row태화동
2nd row신정동
3rd row달동
4th row방어동
5th row달동
ValueCountFrequency (%)
신정동 787
 
7.9%
방어동 536
 
5.4%
달동 505
 
5.1%
삼산동 456
 
4.6%
온산읍 431
 
4.3%
범서읍 389
 
3.9%
무거동 338
 
3.4%
언양읍 304
 
3.0%
온양읍 275
 
2.8%
야음동 265
 
2.6%
Other values (75) 5714
57.1%
2024-03-15T03:52:05.268213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 7711
26.4%
읍 1642
 
5.6%
산 1487
 
5.1%
정 1293
 
4.4%
신 927
 
3.2%
면 835
 
2.9%
서 795
 
2.7%
삼 755
 
2.6%
온 706
 
2.4%
양 629
 
2.2%
Other values (77) 12458
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29238
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7711
26.4%
읍 1642
 
5.6%
산 1487
 
5.1%
정 1293
 
4.4%
신 927
 
3.2%
면 835
 
2.9%
서 795
 
2.7%
삼 755
 
2.6%
온 706
 
2.4%
양 629
 
2.2%
Other values (77) 12458
42.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29238
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7711
26.4%
읍 1642
 
5.6%
산 1487
 
5.1%
정 1293
 
4.4%
신 927
 
3.2%
면 835
 
2.9%
서 795
 
2.7%
삼 755
 
2.6%
온 706
 
2.4%
양 629
 
2.2%
Other values (77) 12458
42.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29238
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 7711
26.4%
읍 1642
 
5.6%
산 1487
 
5.1%
정 1293
 
4.4%
신 927
 
3.2%
면 835
 
2.9%
서 795
 
2.7%
삼 755
 
2.6%
온 706
 
2.4%
양 629
 
2.2%
Other values (77) 12458
42.6%

재난리명
Text

MISSING 

Distinct111
Distinct (%)4.5%
Missing7523
Missing (%)75.2%
Memory size156.2 KiB
2024-03-15T03:52:06.910100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.9955591
Min length2

Characters and Unicode

Total characters7420
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

Unique5 ?
Unique (%)0.2%

Sample

1st row곡천리
2nd row방기리
3rd row교동리
4th row신화리
5th row교동리
ValueCountFrequency (%)
덕신리 235
 
9.5%
구영리 159
 
6.4%
교동리 116
 
4.7%
천상리 98
 
4.0%
대안리 97
 
3.9%
신화리 91
 
3.7%
굴화리 69
 
2.8%
진하리 67
 
2.7%
상남리 58
 
2.3%
운화리 56
 
2.3%
Other values (101) 1431
57.8%
2024-03-15T03:52:09.160186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 2477
33.4%
신 358
 
4.8%
천 293
 
3.9%
화 276
 
3.7%
덕 266
 
3.6%
동 209
 
2.8%
상 177
 
2.4%
구 171
 
2.3%
대 169
 
2.3%
영 159
 
2.1%
Other values (100) 2865
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7420
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 2477
33.4%
신 358
 
4.8%
천 293
 
3.9%
화 276
 
3.7%
덕 266
 
3.6%
동 209
 
2.8%
상 177
 
2.4%
구 171
 
2.3%
대 169
 
2.3%
영 159
 
2.1%
Other values (100) 2865
38.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7420
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 2477
33.4%
신 358
 
4.8%
천 293
 
3.9%
화 276
 
3.7%
덕 266
 
3.6%
동 209
 
2.8%
상 177
 
2.4%
구 171
 
2.3%
대 169
 
2.3%
영 159
 
2.1%
Other values (100) 2865
38.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7420
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 2477
33.4%
신 358
 
4.8%
천 293
 
3.9%
화 276
 
3.7%
덕 266
 
3.6%
동 209
 
2.8%
상 177
 
2.4%
구 171
 
2.3%
대 169
 
2.3%
영 159
 
2.1%
Other values (100) 2865
38.6%

상황종료연도
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020
3516 
2019
3426 
2021
3058 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2020
3rd row2019
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 3516
35.2%
2019 3426
34.3%
2021 3058
30.6%

Length

2024-03-15T03:52:09.556708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:52:09.733285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 3516
35.2%
2019 3426
34.3%
2021 3058
30.6%

상황종료월
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8457
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:52:09.923928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2014866
Coefficient of variation (CV)0.46766388
Kurtosis-0.93537777
Mean6.8457
Median Absolute Deviation (MAD)2
Skewness-0.23432617
Sum68457
Variance10.249516
MonotonicityNot monotonic
2024-03-15T03:52:10.117928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
9 1204
12.0%
7 1191
11.9%
8 1109
11.1%
6 898
9.0%
10 848
8.5%
5 756
7.6%
11 741
7.4%
1 715
7.1%
12 692
6.9%
4 658
6.6%
Other values (2) 1188
11.9%
ValueCountFrequency (%)
1 715
7.1%
2 602
6.0%
3 586
5.9%
4 658
6.6%
5 756
7.6%
6 898
9.0%
7 1191
11.9%
8 1109
11.1%
9 1204
12.0%
10 848
8.5%
ValueCountFrequency (%)
12 692
6.9%
11 741
7.4%
10 848
8.5%
9 1204
12.0%
8 1109
11.1%
7 1191
11.9%
6 898
9.0%
5 756
7.6%
4 658
6.6%
3 586
5.9%

상황종료일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.733
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:52:10.452218image/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 deviation8.8472673
Coefficient of variation (CV)0.56233822
Kurtosis-1.2147174
Mean15.733
Median Absolute Deviation (MAD)8
Skewness-0.019050073
Sum157330
Variance78.274138
MonotonicityNot monotonic
2024-03-15T03:52:10.854384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
3 396
 
4.0%
22 387
 
3.9%
2 367
 
3.7%
19 355
 
3.5%
27 353
 
3.5%
4 350
 
3.5%
20 348
 
3.5%
11 345
 
3.5%
21 342
 
3.4%
24 339
 
3.4%
Other values (21) 6418
64.2%
ValueCountFrequency (%)
1 299
3.0%
2 367
3.7%
3 396
4.0%
4 350
3.5%
5 322
3.2%
6 326
3.3%
7 321
3.2%
8 300
3.0%
9 281
2.8%
10 316
3.2%
ValueCountFrequency (%)
31 175
1.8%
30 318
3.2%
29 275
2.8%
28 334
3.3%
27 353
3.5%
26 331
3.3%
25 296
3.0%
24 339
3.4%
23 339
3.4%
22 387
3.9%

상황종료시
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5152
Minimum0
Maximum23
Zeros434
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:52:11.230364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median13
Q319
95-th percentile23
Maximum23
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.0011907
Coefficient of variation (CV)0.559415
Kurtosis-1.1387752
Mean12.5152
Median Absolute Deviation (MAD)6
Skewness-0.23089123
Sum125152
Variance49.016671
MonotonicityNot monotonic
2024-03-15T03:52:11.704513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
23 532
 
5.3%
22 531
 
5.3%
19 514
 
5.1%
18 508
 
5.1%
21 492
 
4.9%
17 481
 
4.8%
20 480
 
4.8%
16 461
 
4.6%
15 442
 
4.4%
11 437
 
4.4%
Other values (14) 5122
51.2%
ValueCountFrequency (%)
0 434
4.3%
1 404
4.0%
2 370
3.7%
3 306
3.1%
4 310
3.1%
5 256
2.6%
6 274
2.7%
7 332
3.3%
8 393
3.9%
9 421
4.2%
ValueCountFrequency (%)
23 532
5.3%
22 531
5.3%
21 492
4.9%
20 480
4.8%
19 514
5.1%
18 508
5.1%
17 481
4.8%
16 461
4.6%
15 442
4.4%
14 414
4.1%

상황종료분
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.6115
Minimum0
Maximum59
Zeros189
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:52:12.030624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q115
median30
Q345
95-th percentile57
Maximum59
Range59
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.262983
Coefficient of variation (CV)0.58298238
Kurtosis-1.1757665
Mean29.6115
Median Absolute Deviation (MAD)15
Skewness-0.002642321
Sum296115
Variance298.01057
MonotonicityNot monotonic
2024-03-15T03:52:12.310046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 205
 
2.1%
26 194
 
1.9%
27 192
 
1.9%
0 189
 
1.9%
49 188
 
1.9%
12 188
 
1.9%
59 184
 
1.8%
16 183
 
1.8%
35 182
 
1.8%
14 182
 
1.8%
Other values (50) 8113
81.1%
ValueCountFrequency (%)
0 189
1.9%
1 144
1.4%
2 165
1.7%
3 170
1.7%
4 161
1.6%
5 157
1.6%
6 176
1.8%
7 155
1.6%
8 136
1.4%
9 164
1.6%
ValueCountFrequency (%)
59 184
1.8%
58 170
1.7%
57 177
1.8%
56 161
1.6%
55 158
1.6%
54 172
1.7%
53 168
1.7%
52 163
1.6%
51 140
1.4%
50 162
1.6%

관할서명
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남부소방서
2909 
중부소방서
2584 
북부소방서
1705 
동부소방서
1342 
온산소방서
1263 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중부소방서
2nd row남부소방서
3rd row남부소방서
4th row동부소방서
5th row남부소방서

Common Values

ValueCountFrequency (%)
남부소방서 2909
29.1%
중부소방서 2584
25.8%
북부소방서 1705
17.1%
동부소방서 1342
13.4%
온산소방서 1263
12.6%
울주소방서 197
 
2.0%

Length

2024-03-15T03:52:12.774338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:52:13.261013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남부소방서 2909
29.1%
중부소방서 2584
25.8%
북부소방서 1705
17.1%
동부소방서 1342
13.4%
온산소방서 1263
12.6%
울주소방서 197
 
2.0%

관할센터명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
신정119안전센터
734 
언양119안전센터
727 
삼산119안전센터
704 
매곡119안전센터
 
593
화암119안전센터
 
588
Other values (21)
6654 

Length

Max length10
Median length9
Mean length9.0167
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row태화119안전센터
2nd row옥동119안전센터
3rd row신정119안전센터
4th row화암119안전센터
5th row신정119안전센터

Common Values

ValueCountFrequency (%)
신정119안전센터 734
 
7.3%
언양119안전센터 727
 
7.3%
삼산119안전센터 704
 
7.0%
매곡119안전센터 593
 
5.9%
화암119안전센터 588
 
5.9%
유곡119안전센터 525
 
5.2%
성남119안전센터 468
 
4.7%
범서119안전센터 458
 
4.6%
온산119안전센터 447
 
4.5%
옥동119안전센터 425
 
4.2%
Other values (16) 4331
43.3%

Length

2024-03-15T03:52:13.497358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신정119안전센터 734
 
7.3%
언양119안전센터 727
 
7.3%
삼산119안전센터 704
 
7.0%
매곡119안전센터 593
 
5.9%
화암119안전센터 588
 
5.9%
유곡119안전센터 525
 
5.2%
성남119안전센터 468
 
4.7%
범서119안전센터 458
 
4.6%
온산119안전센터 447
 
4.5%
옥동119안전센터 425
 
4.2%
Other values (16) 4331
43.3%

도로명
Text

MISSING 

Distinct1821
Distinct (%)24.5%
Missing2553
Missing (%)25.5%
Memory size156.2 KiB
2024-03-15T03:52:14.407548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.6344837
Min length3

Characters and Unicode

Total characters34513
Distinct characters295
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

Unique739 ?
Unique (%)9.9%

Sample

1st row명정10길
2nd row두왕로272번길
3rd row삼산로
4th row동진4길
5th row은월로
ValueCountFrequency (%)
방어진순환도로 153
 
2.1%
삼산로 125
 
1.7%
번영로 82
 
1.1%
삼산중로 66
 
0.9%
중앙로 59
 
0.8%
화합로 59
 
0.8%
염포로 57
 
0.8%
돋질로 56
 
0.8%
종가로 55
 
0.7%
수암로 54
 
0.7%
Other values (1811) 6681
89.7%
2024-03-15T03:52:15.604564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 4467
 
12.9%
로 4259
 
12.3%
1 1573
 
4.6%
번 1512
 
4.4%
산 1054
 
3.1%
2 850
 
2.5%
4 705
 
2.0%
3 671
 
1.9%
진 557
 
1.6%
중 531
 
1.5%
Other values (285) 18334
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28365
82.2%
Decimal Number 6148
 
17.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 4467
 
15.7%
로 4259
 
15.0%
번 1512
 
5.3%
산 1054
 
3.7%
진 557
 
2.0%
중 531
 
1.9%
화 472
 
1.7%
삼 457
 
1.6%
신 424
 
1.5%
동 405
 
1.4%
Other values (275) 14227
50.2%
Decimal Number
ValueCountFrequency (%)
1 1573
25.6%
2 850
13.8%
4 705
11.5%
3 671
10.9%
5 508
 
8.3%
7 474
 
7.7%
6 393
 
6.4%
8 366
 
6.0%
0 341
 
5.5%
9 267
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28365
82.2%
Common 6148
 
17.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 4467
 
15.7%
로 4259
 
15.0%
번 1512
 
5.3%
산 1054
 
3.7%
진 557
 
2.0%
중 531
 
1.9%
화 472
 
1.7%
삼 457
 
1.6%
신 424
 
1.5%
동 405
 
1.4%
Other values (275) 14227
50.2%
Common
ValueCountFrequency (%)
1 1573
25.6%
2 850
13.8%
4 705
11.5%
3 671
10.9%
5 508
 
8.3%
7 474
 
7.7%
6 393
 
6.4%
8 366
 
6.0%
0 341
 
5.5%
9 267
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28365
82.2%
ASCII 6148
 
17.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 4467
 
15.7%
로 4259
 
15.0%
번 1512
 
5.3%
산 1054
 
3.7%
진 557
 
2.0%
중 531
 
1.9%
화 472
 
1.7%
삼 457
 
1.6%
신 424
 
1.5%
동 405
 
1.4%
Other values (275) 14227
50.2%
ASCII
ValueCountFrequency (%)
1 1573
25.6%
2 850
13.8%
4 705
11.5%
3 671
10.9%
5 508
 
8.3%
7 474
 
7.7%
6 393
 
6.4%
8 366
 
6.0%
0 341
 
5.5%
9 267
 
4.3%

읍면동순번
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)0.2%
Missing2473
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean1.4013551
Minimum0
Maximum11
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:52:16.122680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.98125578
Coefficient of variation (CV)0.70021921
Kurtosis21.064038
Mean1.4013551
Median Absolute Deviation (MAD)0
Skewness3.9476627
Sum10548
Variance0.9628629
MonotonicityNot monotonic
2024-03-15T03:52:16.506885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 5785
57.9%
2 1100
 
11.0%
3 331
 
3.3%
4 171
 
1.7%
7 44
 
0.4%
5 44
 
0.4%
6 24
 
0.2%
9 10
 
0.1%
10 7
 
0.1%
0 5
 
0.1%
Other values (2) 6
 
0.1%
(Missing) 2473
24.7%
ValueCountFrequency (%)
0 5
 
0.1%
1 5785
57.9%
2 1100
 
11.0%
3 331
 
3.3%
4 171
 
1.7%
5 44
 
0.4%
6 24
 
0.2%
7 44
 
0.4%
8 4
 
< 0.1%
9 10
 
0.1%
ValueCountFrequency (%)
11 2
 
< 0.1%
10 7
 
0.1%
9 10
 
0.1%
8 4
 
< 0.1%
7 44
 
0.4%
6 24
 
0.2%
5 44
 
0.4%
4 171
 
1.7%
3 331
 
3.3%
2 1100
11.0%

지하 여부
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-03-15T03:52:16.939079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:52:17.259179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

화학사고여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9998 
True
 
2
ValueCountFrequency (%)
False 9998
> 99.9%
True 2
 
< 0.1%
2024-03-15T03:52:17.499741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

출동대센터정보
Text

Distinct489
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T03:52:18.549120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length9
Mean length11.1618
Min length5

Characters and Unicode

Total characters111618
Distinct characters77
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)2.7%

Sample

1st row태화119안전센터
2nd row옥동119안전센터
3rd row신정119안전센터
4th row화암119안전센터
5th row남부구조대, 신정119안전센터
ValueCountFrequency (%)
신정119안전센터 861
 
6.8%
삼산119안전센터 706
 
5.6%
언양119안전센터 657
 
5.2%
성남119안전센터 572
 
4.5%
병영119안전센터 572
 
4.5%
매곡119안전센터 554
 
4.4%
화암119안전센터 494
 
3.9%
남부구조대 467
 
3.7%
범서119안전센터 445
 
3.5%
옥동119안전센터 436
 
3.5%
Other values (39) 6813
54.2%
2024-03-15T03:52:20.235410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21794
19.5%
9 10897
 
9.8%
전 10700
 
9.6%
안 10268
 
9.2%
센 10245
 
9.2%
터 10245
 
9.2%
2577
 
2.3%
, 2577
 
2.3%
대 2289
 
2.1%
구 1669
 
1.5%
Other values (67) 28357
25.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73747
66.1%
Decimal Number 32691
29.3%
Space Separator 2577
 
2.3%
Other Punctuation 2577
 
2.3%
Open Punctuation 13
 
< 0.1%
Close Punctuation 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 10700
14.5%
안 10268
13.9%
센 10245
13.9%
터 10245
13.9%
대 2289
 
3.1%
구 1669
 
2.3%
조 1657
 
2.2%
정 1638
 
2.2%
화 1514
 
2.1%
산 1399
 
1.9%
Other values (61) 22123
30.0%
Decimal Number
ValueCountFrequency (%)
1 21794
66.7%
9 10897
33.3%
Space Separator
ValueCountFrequency (%)
2577
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2577
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73747
66.1%
Common 37871
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 10700
14.5%
안 10268
13.9%
센 10245
13.9%
터 10245
13.9%
대 2289
 
3.1%
구 1669
 
2.3%
조 1657
 
2.2%
정 1638
 
2.2%
화 1514
 
2.1%
산 1399
 
1.9%
Other values (61) 22123
30.0%
Common
ValueCountFrequency (%)
1 21794
57.5%
9 10897
28.8%
2577
 
6.8%
, 2577
 
6.8%
( 13
 
< 0.1%
) 13
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73747
66.1%
ASCII 37871
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21794
57.5%
9 10897
28.8%
2577
 
6.8%
, 2577
 
6.8%
( 13
 
< 0.1%
) 13
 
< 0.1%
Hangul
ValueCountFrequency (%)
전 10700
14.5%
안 10268
13.9%
센 10245
13.9%
터 10245
13.9%
대 2289
 
3.1%
구 1669
 
2.3%
조 1657
 
2.2%
정 1638
 
2.2%
화 1514
 
2.1%
산 1399
 
1.9%
Other values (61) 22123
30.0%

대상물명
Text

MISSING 

Distinct1451
Distinct (%)65.8%
Missing7794
Missing (%)77.9%
Memory size156.2 KiB
2024-03-15T03:52:21.610938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length6.5829556
Min length1

Characters and Unicode

Total characters14522
Distinct characters615
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1179 ?
Unique (%)53.4%

Sample

1st row원플러스마트 동구점
2nd row차양시설
3rd row주상빌딩
4th row성남프라자
5th row전하동 에스오션타워
ValueCountFrequency (%)
동명칭없음 145
 
5.7%
1동 50
 
2.0%
건물 39
 
1.5%
a동 36
 
1.4%
101동 23
 
0.9%
2동 19
 
0.7%
주건축물제1동 19
 
0.7%
102동 18
 
0.7%
범서소방파출소 18
 
0.7%
가동 16
 
0.6%
Other values (1581) 2161
84.9%
2024-03-15T03:52:23.222890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 785
 
5.4%
1 439
 
3.0%
338
 
2.3%
빌 317
 
2.2%
( 305
 
2.1%
) 300
 
2.1%
딩 202
 
1.4%
건 195
 
1.3%
물 187
 
1.3%
장 181
 
1.2%
Other values (605) 11273
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12159
83.7%
Decimal Number 976
 
6.7%
Space Separator 338
 
2.3%
Open Punctuation 305
 
2.1%
Close Punctuation 300
 
2.1%
Uppercase Letter 275
 
1.9%
Other Punctuation 85
 
0.6%
Dash Punctuation 58
 
0.4%
Lowercase Letter 23
 
0.2%
Final Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 785
 
6.5%
빌 317
 
2.6%
딩 202
 
1.7%
건 195
 
1.6%
물 187
 
1.5%
장 181
 
1.5%
음 174
 
1.4%
스 165
 
1.4%
이 165
 
1.4%
명 165
 
1.4%
Other values (545) 9623
79.1%
Uppercase Letter
ValueCountFrequency (%)
A 72
26.2%
B 36
13.1%
C 23
 
8.4%
S 15
 
5.5%
K 15
 
5.5%
O 15
 
5.5%
T 13
 
4.7%
M 11
 
4.0%
N 10
 
3.6%
P 10
 
3.6%
Other values (14) 55
20.0%
Lowercase Letter
ValueCountFrequency (%)
o 4
17.4%
e 3
13.0%
s 2
8.7%
i 2
8.7%
l 2
8.7%
p 2
8.7%
g 1
 
4.3%
a 1
 
4.3%
u 1
 
4.3%
n 1
 
4.3%
Other values (4) 4
17.4%
Decimal Number
ValueCountFrequency (%)
1 439
45.0%
0 126
 
12.9%
2 120
 
12.3%
9 84
 
8.6%
3 45
 
4.6%
4 44
 
4.5%
6 40
 
4.1%
5 40
 
4.1%
7 20
 
2.0%
8 18
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 44
51.8%
, 29
34.1%
" 6
 
7.1%
: 3
 
3.5%
' 2
 
2.4%
/ 1
 
1.2%
Space Separator
ValueCountFrequency (%)
338
100.0%
Open Punctuation
ValueCountFrequency (%)
( 305
100.0%
Close Punctuation
ValueCountFrequency (%)
) 300
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Final Punctuation
ValueCountFrequency (%)
” 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12159
83.7%
Common 2065
 
14.2%
Latin 298
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 785
 
6.5%
빌 317
 
2.6%
딩 202
 
1.7%
건 195
 
1.6%
물 187
 
1.5%
장 181
 
1.5%
음 174
 
1.4%
스 165
 
1.4%
이 165
 
1.4%
명 165
 
1.4%
Other values (545) 9623
79.1%
Latin
ValueCountFrequency (%)
A 72
24.2%
B 36
12.1%
C 23
 
7.7%
S 15
 
5.0%
K 15
 
5.0%
O 15
 
5.0%
T 13
 
4.4%
M 11
 
3.7%
N 10
 
3.4%
P 10
 
3.4%
Other values (28) 78
26.2%
Common
ValueCountFrequency (%)
1 439
21.3%
338
16.4%
( 305
14.8%
) 300
14.5%
0 126
 
6.1%
2 120
 
5.8%
9 84
 
4.1%
- 58
 
2.8%
3 45
 
2.2%
4 44
 
2.1%
Other values (12) 206
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12159
83.7%
ASCII 2361
 
16.3%
Punctuation 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 785
 
6.5%
빌 317
 
2.6%
딩 202
 
1.7%
건 195
 
1.6%
물 187
 
1.5%
장 181
 
1.5%
음 174
 
1.4%
스 165
 
1.4%
이 165
 
1.4%
명 165
 
1.4%
Other values (545) 9623
79.1%
ASCII
ValueCountFrequency (%)
1 439
18.6%
338
14.3%
( 305
12.9%
) 300
12.7%
0 126
 
5.3%
2 120
 
5.1%
9 84
 
3.6%
A 72
 
3.0%
- 58
 
2.5%
3 45
 
1.9%
Other values (49) 474
20.1%
Punctuation
ValueCountFrequency (%)
” 2
100.0%

주용도명
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7794 
근린생활
879 
복합건축물
 
345
공동주택(아파트/기숙사)
 
311
업무시설
 
192
Other values (23)
 
479

Length

Max length13
Median length4
Mean length4.3854
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7794
77.9%
근린생활 879
 
8.8%
복합건축물 345
 
3.5%
공동주택(아파트/기숙사) 311
 
3.1%
업무시설 192
 
1.9%
교육연구시설 71
 
0.7%
위락시설 58
 
0.6%
숙박시설 57
 
0.6%
공장 55
 
0.5%
노유자시설 52
 
0.5%
Other values (18) 186
 
1.9%

Length

2024-03-15T03:52:23.611586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7794
77.3%
근린생활 879
 
8.7%
복합건축물 345
 
3.4%
공동주택(아파트/기숙사 311
 
3.1%
업무시설 192
 
1.9%
교육연구시설 71
 
0.7%
위락시설 58
 
0.6%
숙박시설 57
 
0.6%
공장 55
 
0.5%
노유자시설 52
 
0.5%
Other values (21) 273
 
2.7%

건물구조식
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7918 
양식(옥)
1971 
조립식
 
47
기타 식
 
36
기타
 
17
Other values (2)
 
11

Length

Max length5
Median length4
Mean length4.1893
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7918
79.2%
양식(옥) 1971
 
19.7%
조립식 47
 
0.5%
기타 식 36
 
0.4%
기타 17
 
0.2%
한식(옥) 7
 
0.1%
절충식 4
 
< 0.1%

Length

2024-03-15T03:52:23.830498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:52:24.034386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7918
78.9%
양식(옥 1971
 
19.6%
기타 53
 
0.5%
조립식 47
 
0.5%
식 36
 
0.4%
한식(옥 7
 
0.1%
절충식 4
 
< 0.1%

건물구조조
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7794 
철근콘크리트조
1494 
철골철근콘크리트조
 
351
철골조
 
201
벽돌조
 
47
Other values (11)
 
113

Length

Max length11
Median length4
Mean length4.5897
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7794
77.9%
철근콘크리트조 1494
 
14.9%
철골철근콘크리트조 351
 
3.5%
철골조 201
 
2.0%
벽돌조 47
 
0.5%
철조 39
 
0.4%
기타 21
 
0.2%
기타 조 19
 
0.2%
목조 11
 
0.1%
샌드위치패널조 7
 
0.1%
Other values (6) 16
 
0.2%

Length

2024-03-15T03:52:24.296437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7794
77.8%
철근콘크리트조 1494
 
14.9%
철골철근콘크리트조 351
 
3.5%
철골조 201
 
2.0%
벽돌조 47
 
0.5%
기타 40
 
0.4%
철조 39
 
0.4%
조 19
 
0.2%
목조 11
 
0.1%
샌드위치패널조 7
 
0.1%
Other values (6) 16
 
0.2%

건물구조즙
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7795 
슬라브가
1843 
기타 즙
 
113
철근콘크리트조
 
75
기타(건물구조즙코드)
 
51
Other values (10)
 
123

Length

Max length11
Median length4
Mean length4.0637
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7795
78.0%
슬라브가 1843
 
18.4%
기타 즙 113
 
1.1%
철근콘크리트조 75
 
0.8%
기타(건물구조즙코드) 51
 
0.5%
샌드위치패널 32
 
0.3%
기타 30
 
0.3%
칼라피복철판 18
 
0.2%
시멘트기와 11
 
0.1%
스레트가 10
 
0.1%
Other values (5) 22
 
0.2%

Length

2024-03-15T03:52:24.676447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7795
77.1%
슬라브가 1843
 
18.2%
기타 143
 
1.4%
즙 113
 
1.1%
철근콘크리트조 75
 
0.7%
기타(건물구조즙코드 51
 
0.5%
샌드위치패널 32
 
0.3%
칼라피복철판 18
 
0.2%
시멘트기와 11
 
0.1%
스레트가 10
 
0.1%
Other values (5) 22
 
0.2%

지상층수
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2383
Minimum0
Maximum48
Zeros7812
Zeros (%)78.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:52:25.037146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7
Maximum48
Range48
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.4222923
Coefficient of variation (CV)2.7637021
Kurtosis40.341981
Mean1.2383
Median Absolute Deviation (MAD)0
Skewness5.1407102
Sum12383
Variance11.712084
MonotonicityNot monotonic
2024-03-15T03:52:25.467535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 7812
78.1%
3 436
 
4.4%
4 424
 
4.2%
2 272
 
2.7%
5 252
 
2.5%
1 168
 
1.7%
6 112
 
1.1%
7 81
 
0.8%
15 73
 
0.7%
8 69
 
0.7%
Other values (24) 301
 
3.0%
ValueCountFrequency (%)
0 7812
78.1%
1 168
 
1.7%
2 272
 
2.7%
3 436
 
4.4%
4 424
 
4.2%
5 252
 
2.5%
6 112
 
1.1%
7 81
 
0.8%
8 69
 
0.7%
9 51
 
0.5%
ValueCountFrequency (%)
48 5
 
0.1%
43 2
 
< 0.1%
40 2
 
< 0.1%
36 2
 
< 0.1%
33 2
 
< 0.1%
30 2
 
< 0.1%
29 2
 
< 0.1%
28 1
 
< 0.1%
25 15
0.1%
24 2
 
< 0.1%

지하층수
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1446
Minimum0
Maximum7
Zeros8846
Zeros (%)88.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:52:25.811276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.47698385
Coefficient of variation (CV)3.2986435
Kurtosis51.179114
Mean0.1446
Median Absolute Deviation (MAD)0
Skewness5.6494027
Sum1446
Variance0.22751359
MonotonicityNot monotonic
2024-03-15T03:52:26.093081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 8846
88.5%
1 969
 
9.7%
2 140
 
1.4%
3 19
 
0.2%
6 10
 
0.1%
4 8
 
0.1%
5 4
 
< 0.1%
7 4
 
< 0.1%
ValueCountFrequency (%)
0 8846
88.5%
1 969
 
9.7%
2 140
 
1.4%
3 19
 
0.2%
4 8
 
0.1%
5 4
 
< 0.1%
6 10
 
0.1%
7 4
 
< 0.1%
ValueCountFrequency (%)
7 4
 
< 0.1%
6 10
 
0.1%
5 4
 
< 0.1%
4 8
 
0.1%
3 19
 
0.2%
2 140
 
1.4%
1 969
 
9.7%
0 8846
88.5%

Sample

접수경로명신고연도신고월신고일신고시신고분재난시명재난구명재난동명재난리명상황종료연도상황종료월상황종료일상황종료시상황종료분관할서명관할센터명도로명읍면동순번지하 여부화학사고여부출동대센터정보대상물명주용도명건물구조식건물구조조건물구조즙지상층수지하층수
3749이동전화201910171835울산광역시중구태화동<NA>201910171844중부소방서태화119안전센터명정10길10N태화119안전센터<NA><NA><NA><NA><NA>00
7917기타202010201844울산광역시남구신정동<NA>202010201914남부소방서옥동119안전센터두왕로272번길10N옥동119안전센터<NA><NA><NA><NA><NA>00
941이동전화20194152329울산광역시남구달동<NA>20194152352남부소방서신정119안전센터삼산로20N신정119안전센터<NA><NA><NA><NA><NA>00
5277이동전화20204142328울산광역시동구방어동<NA>2020415015동부소방서화암119안전센터동진4길10N화암119안전센터<NA><NA><NA><NA><NA>00
8143이동전화20201151142울산광역시남구달동<NA>2020115129남부소방서신정119안전센터<NA><NA>0N남부구조대, 신정119안전센터<NA><NA><NA><NA><NA>00
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