Overview

Dataset statistics

Number of variables29
Number of observations10000
Missing cells66079
Missing cells (%)22.8%
Duplicate rows199
Duplicate rows (%)2.0%
Total size in memory2.4 MiB
Average record size in memory253.0 B

Variable types

Text8
Categorical8
Numeric11
Boolean1
DateTime1

Dataset

Description지진해일 발생시 긴급대피소 현황 정보(대피소명, 주소, 수용가능인원, 위.경도 등) 제공 「지진ㆍ화산재해대책법」, 「지진해일 대비 주민대피계획 수립 지침」에 따라 지진해일 발생 시 지진해일 대피지구 내의 주민 등이 대피가 가능한 안전한 장소로 지정된 지역별 위치 정보
Author행정안전부
URLhttps://www.data.go.kr/data/15025449/standard.do

Alerts

Dataset has 199 (2.0%) duplicate rowsDuplicates
지진해일대피소구분 is highly imbalanced (50.9%)Imbalance
지진해일대피소운영상태 is highly imbalanced (83.1%)Imbalance
부대편의시설 is highly imbalanced (88.6%)Imbalance
내진적용여부 is highly imbalanced (54.9%)Imbalance
내진설계등급 is highly imbalanced (87.5%)Imbalance
지진대피안내표지판수 is highly imbalanced (55.7%)Imbalance
긴급대피장소안내표지판수 is highly imbalanced (71.9%)Imbalance
소재지도로명주소 has 1146 (11.5%) missing valuesMissing
소재지지번주소 has 4653 (46.5%) missing valuesMissing
위도 has 759 (7.6%) missing valuesMissing
경도 has 757 (7.6%) missing valuesMissing
주민대피지구내가구수 has 9274 (92.7%) missing valuesMissing
주민대피지구내거주인수 has 9363 (93.6%) missing valuesMissing
주민대피지구내재해약자수 has 9489 (94.9%) missing valuesMissing
해안선이격거리 has 9128 (91.3%) missing valuesMissing
해발높이 has 9071 (90.7%) missing valuesMissing
지진대피로안내표지판수 has 9084 (90.8%) missing valuesMissing
관리기관전화번호 has 3355 (33.6%) missing valuesMissing
수용가능면적 is highly skewed (γ1 = 36.60500216)Skewed
주민대피지구내가구수 has 238 (2.4%) zerosZeros
주민대피지구내거주인수 has 163 (1.6%) zerosZeros
주민대피지구내재해약자수 has 211 (2.1%) zerosZeros
지진대피로안내표지판수 has 568 (5.7%) zerosZeros

Reproduction

Analysis started2023-12-12 11:48:40.792920
Analysis finished2023-12-12 11:48:43.436576
Duration2.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct8754
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:48:43.739306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length26
Mean length8.4236
Min length2

Characters and Unicode

Total characters84236
Distinct characters618
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7949 ?
Unique (%)79.5%

Sample

1st row부개서초등학교
2nd row성지초등학교 운동장
3rd row인헌고등학교 운동장
4th row소월길 어린이공원
5th row백석초등학교
ValueCountFrequency (%)
운동장 3184
 
20.7%
마을회관 244
 
1.6%
주변 197
 
1.3%
197
 
1.3%
공터 128
 
0.8%
주차장 109
 
0.7%
강당 97
 
0.6%
어린이공원 70
 
0.5%
야산 41
 
0.3%
체육관 39
 
0.3%
Other values (8432) 11110
72.1%
2023-12-12T20:48:44.361810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6528
 
7.7%
6412
 
7.6%
5449
 
6.5%
4911
 
5.8%
4818
 
5.7%
4729
 
5.6%
4084
 
4.8%
4040
 
4.8%
1934
 
2.3%
1886
 
2.2%
Other values (608) 39445
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77035
91.5%
Space Separator 5449
 
6.5%
Decimal Number 829
 
1.0%
Close Punctuation 395
 
0.5%
Open Punctuation 389
 
0.5%
Other Punctuation 59
 
0.1%
Uppercase Letter 40
 
< 0.1%
Dash Punctuation 34
 
< 0.1%
Math Symbol 4
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6528
 
8.5%
6412
 
8.3%
4911
 
6.4%
4818
 
6.3%
4729
 
6.1%
4084
 
5.3%
4040
 
5.2%
1934
 
2.5%
1886
 
2.4%
1653
 
2.1%
Other values (573) 36040
46.8%
Uppercase Letter
ValueCountFrequency (%)
C 9
22.5%
M 8
20.0%
B 4
10.0%
I 4
10.0%
A 3
 
7.5%
G 3
 
7.5%
H 2
 
5.0%
L 2
 
5.0%
P 2
 
5.0%
S 1
 
2.5%
Other values (2) 2
 
5.0%
Decimal Number
ValueCountFrequency (%)
1 282
34.0%
2 234
28.2%
3 85
 
10.3%
5 52
 
6.3%
4 49
 
5.9%
7 29
 
3.5%
6 28
 
3.4%
0 24
 
2.9%
8 24
 
2.9%
9 22
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 28
47.5%
. 20
33.9%
/ 4
 
6.8%
· 4
 
6.8%
& 2
 
3.4%
: 1
 
1.7%
Math Symbol
ValueCountFrequency (%)
> 2
50.0%
< 2
50.0%
Space Separator
ValueCountFrequency (%)
5449
100.0%
Close Punctuation
ValueCountFrequency (%)
) 395
100.0%
Open Punctuation
ValueCountFrequency (%)
( 389
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77034
91.5%
Common 7159
 
8.5%
Latin 42
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6528
 
8.5%
6412
 
8.3%
4911
 
6.4%
4818
 
6.3%
4729
 
6.1%
4084
 
5.3%
4040
 
5.2%
1934
 
2.5%
1886
 
2.4%
1653
 
2.1%
Other values (572) 36039
46.8%
Common
ValueCountFrequency (%)
5449
76.1%
) 395
 
5.5%
( 389
 
5.4%
1 282
 
3.9%
2 234
 
3.3%
3 85
 
1.2%
5 52
 
0.7%
4 49
 
0.7%
- 34
 
0.5%
7 29
 
0.4%
Other values (12) 161
 
2.2%
Latin
ValueCountFrequency (%)
C 9
21.4%
M 8
19.0%
B 4
9.5%
I 4
9.5%
A 3
 
7.1%
G 3
 
7.1%
H 2
 
4.8%
L 2
 
4.8%
P 2
 
4.8%
2
 
4.8%
Other values (3) 3
 
7.1%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77034
91.5%
ASCII 7195
 
8.5%
None 4
 
< 0.1%
Number Forms 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6528
 
8.5%
6412
 
8.3%
4911
 
6.4%
4818
 
6.3%
4729
 
6.1%
4084
 
5.3%
4040
 
5.2%
1934
 
2.5%
1886
 
2.4%
1653
 
2.1%
Other values (572) 36039
46.8%
ASCII
ValueCountFrequency (%)
5449
75.7%
) 395
 
5.5%
( 389
 
5.4%
1 282
 
3.9%
2 234
 
3.3%
3 85
 
1.2%
5 52
 
0.7%
4 49
 
0.7%
- 34
 
0.5%
7 29
 
0.4%
Other values (23) 197
 
2.7%
None
ValueCountFrequency (%)
· 4
100.0%
Number Forms
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

지진해일대피소구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
지진대피소
8930 
지진해일대피소
1070 

Length

Max length7
Median length5
Mean length5.214
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지진대피소 8930
89.3%
지진해일대피소 1070
 
10.7%

Length

2023-12-12T20:48:44.544895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:48:44.678026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지진대피소 8930
89.3%
지진해일대피소 1070
 
10.7%
Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
옥외대피장소
5987 
옥외대피소
2324 
실내구호소
733 
실내대피소
 
457
지진해일 긴급대피장소
 
456

Length

Max length11
Median length6
Mean length5.8938
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row실내대피소
2nd row옥외대피소
3rd row옥외대피장소
4th row옥외대피장소
5th row옥외대피장소

Common Values

ValueCountFrequency (%)
옥외대피장소 5987
59.9%
옥외대피소 2324
 
23.2%
실내구호소 733
 
7.3%
실내대피소 457
 
4.6%
지진해일 긴급대피장소 456
 
4.6%
지진해일긴급대피장소 43
 
0.4%

Length

2023-12-12T20:48:44.821820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:48:44.976176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옥외대피장소 5987
57.3%
옥외대피소 2324
 
22.2%
실내구호소 733
 
7.0%
실내대피소 457
 
4.4%
지진해일 456
 
4.4%
긴급대피장소 456
 
4.4%
지진해일긴급대피장소 43
 
0.4%
Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
운동장
3455 
학교
2892 
공원
1506 
기타
1497 
공터
359 
Other values (8)
 
291

Length

Max length17
Median length2
Mean length2.4325
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row학교
2nd row학교
3rd row운동장
4th row공원
5th row학교

Common Values

ValueCountFrequency (%)
운동장 3455
34.5%
학교 2892
28.9%
공원 1506
15.1%
기타 1497
15.0%
공터 359
 
3.6%
체육관 126
 
1.3%
학교운동장 111
 
1.1%
기타(야영장, 공터, 쉼터 등) 18
 
0.2%
민간건축물 13
 
0.1%
공공건축물 12
 
0.1%
Other values (3) 11
 
0.1%

Length

2023-12-12T20:48:45.159984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
운동장 3455
34.4%
학교 2892
28.8%
공원 1506
15.0%
기타 1497
14.9%
공터 377
 
3.7%
체육관 126
 
1.3%
학교운동장 111
 
1.1%
기타(야영장 18
 
0.2%
쉼터 18
 
0.2%
18
 
0.2%
Other values (5) 36
 
0.4%
Distinct7824
Distinct (%)88.4%
Missing1146
Missing (%)11.5%
Memory size156.2 KiB
2023-12-12T20:48:45.649559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length32
Mean length20.927152
Min length8

Characters and Unicode

Total characters185289
Distinct characters495
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7068 ?
Unique (%)79.8%

Sample

1st row인천광역시 부평구 부일로 39(부개동)
2nd row인천광역시 계양구 아나지로247번길 8 (작전동)
3rd row서울특별시 관악구 인헌9길 74
4th row서울특별시 용산구 이태원동 463
5th row충청남도 논산시 연산면 선비로 726
ValueCountFrequency (%)
서울특별시 1517
 
3.7%
경상북도 1449
 
3.5%
경기도 1184
 
2.9%
북구 685
 
1.7%
대구광역시 644
 
1.6%
전라북도 623
 
1.5%
포항시 524
 
1.3%
인천광역시 505
 
1.2%
경상남도 438
 
1.1%
충청남도 418
 
1.0%
Other values (10509) 32914
80.5%
2023-12-12T20:48:46.388916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32055
 
17.3%
7286
 
3.9%
6304
 
3.4%
1 6139
 
3.3%
5786
 
3.1%
5516
 
3.0%
2 4231
 
2.3%
3989
 
2.2%
3899
 
2.1%
3624
 
2.0%
Other values (485) 106460
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117419
63.4%
Space Separator 32055
 
17.3%
Decimal Number 29640
 
16.0%
Open Punctuation 2141
 
1.2%
Close Punctuation 2140
 
1.2%
Dash Punctuation 1772
 
1.0%
Other Punctuation 119
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7286
 
6.2%
6304
 
5.4%
5786
 
4.9%
5516
 
4.7%
3989
 
3.4%
3899
 
3.3%
3624
 
3.1%
3389
 
2.9%
2913
 
2.5%
2659
 
2.3%
Other values (468) 72054
61.4%
Decimal Number
ValueCountFrequency (%)
1 6139
20.7%
2 4231
14.3%
3 3405
11.5%
5 2763
9.3%
4 2675
9.0%
6 2369
 
8.0%
7 2257
 
7.6%
0 2088
 
7.0%
9 1872
 
6.3%
8 1841
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 117
98.3%
. 2
 
1.7%
Space Separator
ValueCountFrequency (%)
32055
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2140
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1772
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117419
63.4%
Common 67870
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7286
 
6.2%
6304
 
5.4%
5786
 
4.9%
5516
 
4.7%
3989
 
3.4%
3899
 
3.3%
3624
 
3.1%
3389
 
2.9%
2913
 
2.5%
2659
 
2.3%
Other values (468) 72054
61.4%
Common
ValueCountFrequency (%)
32055
47.2%
1 6139
 
9.0%
2 4231
 
6.2%
3 3405
 
5.0%
5 2763
 
4.1%
4 2675
 
3.9%
6 2369
 
3.5%
7 2257
 
3.3%
( 2141
 
3.2%
) 2140
 
3.2%
Other values (7) 7695
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117419
63.4%
ASCII 67870
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32055
47.2%
1 6139
 
9.0%
2 4231
 
6.2%
3 3405
 
5.0%
5 2763
 
4.1%
4 2675
 
3.9%
6 2369
 
3.5%
7 2257
 
3.3%
( 2141
 
3.2%
) 2140
 
3.2%
Other values (7) 7695
 
11.3%
Hangul
ValueCountFrequency (%)
7286
 
6.2%
6304
 
5.4%
5786
 
4.9%
5516
 
4.7%
3989
 
3.4%
3899
 
3.3%
3624
 
3.1%
3389
 
2.9%
2913
 
2.5%
2659
 
2.3%
Other values (468) 72054
61.4%

소재지지번주소
Text

MISSING 

Distinct4582
Distinct (%)85.7%
Missing4653
Missing (%)46.5%
Memory size156.2 KiB
2023-12-12T20:48:46.860161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length19.493548
Min length13

Characters and Unicode

Total characters104232
Distinct characters336
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4086 ?
Unique (%)76.4%

Sample

1st row전라남도 곡성군 석곡면 석곡리 8-1
2nd row전라북도 고창군 성송면 하고리 672
3rd row전라북도 익산시 신동 156-4
4th row전라북도 군산시 나운동 155-4
5th row경기도 과천시 문원동 187-1
ValueCountFrequency (%)
경기도 743
 
3.1%
서울특별시 732
 
3.1%
경상북도 704
 
2.9%
전라북도 578
 
2.4%
대구광역시 519
 
2.2%
경상남도 356
 
1.5%
북구 300
 
1.3%
울산광역시 288
 
1.2%
노원구 284
 
1.2%
인천광역시 272
 
1.1%
Other values (5988) 19201
80.1%
2023-12-12T20:48:47.514952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18634
 
17.9%
4029
 
3.9%
1 3997
 
3.8%
3768
 
3.6%
3377
 
3.2%
3127
 
3.0%
- 3020
 
2.9%
2 2521
 
2.4%
2166
 
2.1%
3 2003
 
1.9%
Other values (326) 57590
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63094
60.5%
Decimal Number 19371
 
18.6%
Space Separator 18634
 
17.9%
Dash Punctuation 3020
 
2.9%
Close Punctuation 55
 
0.1%
Open Punctuation 54
 
0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4029
 
6.4%
3768
 
6.0%
3377
 
5.4%
3127
 
5.0%
2166
 
3.4%
1931
 
3.1%
1925
 
3.1%
1882
 
3.0%
1764
 
2.8%
1710
 
2.7%
Other values (310) 37415
59.3%
Decimal Number
ValueCountFrequency (%)
1 3997
20.6%
2 2521
13.0%
3 2003
10.3%
4 1882
9.7%
5 1867
9.6%
6 1596
 
8.2%
7 1473
 
7.6%
0 1433
 
7.4%
8 1391
 
7.2%
9 1208
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
, 1
 
25.0%
Space Separator
ValueCountFrequency (%)
18634
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3020
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63094
60.5%
Common 41138
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4029
 
6.4%
3768
 
6.0%
3377
 
5.4%
3127
 
5.0%
2166
 
3.4%
1931
 
3.1%
1925
 
3.1%
1882
 
3.0%
1764
 
2.8%
1710
 
2.7%
Other values (310) 37415
59.3%
Common
ValueCountFrequency (%)
18634
45.3%
1 3997
 
9.7%
- 3020
 
7.3%
2 2521
 
6.1%
3 2003
 
4.9%
4 1882
 
4.6%
5 1867
 
4.5%
6 1596
 
3.9%
7 1473
 
3.6%
0 1433
 
3.5%
Other values (6) 2712
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63094
60.5%
ASCII 41138
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18634
45.3%
1 3997
 
9.7%
- 3020
 
7.3%
2 2521
 
6.1%
3 2003
 
4.9%
4 1882
 
4.6%
5 1867
 
4.5%
6 1596
 
3.9%
7 1473
 
3.6%
0 1433
 
3.5%
Other values (6) 2712
 
6.6%
Hangul
ValueCountFrequency (%)
4029
 
6.4%
3768
 
6.0%
3377
 
5.4%
3127
 
5.0%
2166
 
3.4%
1931
 
3.1%
1925
 
3.1%
1882
 
3.0%
1764
 
2.8%
1710
 
2.7%
Other values (310) 37415
59.3%

위도
Real number (ℝ)

MISSING 

Distinct8253
Distinct (%)89.3%
Missing759
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean36.513093
Minimum33.301196
Maximum38.500797
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:47.743083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.301196
5-th percentile35.089615
Q135.828944
median36.427286
Q337.485664
95-th percentile37.695458
Maximum38.500797
Range5.1996008
Interquartile range (IQR)1.65672

Descriptive statistics

Standard deviation0.95185694
Coefficient of variation (CV)0.026068921
Kurtosis-0.73115323
Mean36.513093
Median Absolute Deviation (MAD)0.89115044
Skewness-0.28358004
Sum337417.5
Variance0.90603164
MonotonicityNot monotonic
2023-12-12T20:48:47.951203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.63753475 8
 
0.1%
37.62979181 8
 
0.1%
37.66128875 8
 
0.1%
37.67375516 6
 
0.1%
37.4739590696 5
 
0.1%
35.885859 5
 
0.1%
35.59252417 4
 
< 0.1%
35.55174377 4
 
< 0.1%
37.62850733 4
 
< 0.1%
37.67228886 4
 
< 0.1%
Other values (8243) 9185
91.8%
(Missing) 759
 
7.6%
ValueCountFrequency (%)
33.3011961816 1
< 0.1%
33.3491937 1
< 0.1%
33.4096907577 1
< 0.1%
33.4568876 1
< 0.1%
33.4594743254 1
< 0.1%
33.46298979 1
< 0.1%
33.4642974707 1
< 0.1%
33.46512638 1
< 0.1%
33.4710621 1
< 0.1%
33.47237484 1
< 0.1%
ValueCountFrequency (%)
38.500797 1
< 0.1%
38.4969627401 1
< 0.1%
38.495403099 1
< 0.1%
38.4884951158 1
< 0.1%
38.4854849917 1
< 0.1%
38.4709937131 1
< 0.1%
38.4511779136 1
< 0.1%
38.4471455577 1
< 0.1%
38.4396817912 1
< 0.1%
38.4243999615 1
< 0.1%

경도
Real number (ℝ)

MISSING 

Distinct8263
Distinct (%)89.4%
Missing757
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean127.79262
Minimum124.61906
Maximum130.90735
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:48.152703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.61906
5-th percentile126.64532
Q1126.93006
median127.42916
Q3128.64412
95-th percentile129.42475
Maximum130.90735
Range6.288297
Interquartile range (IQR)1.7140616

Descriptive statistics

Standard deviation1.0184265
Coefficient of variation (CV)0.0079693689
Kurtosis-1.0726379
Mean127.79262
Median Absolute Deviation (MAD)0.70551628
Skewness0.3232985
Sum1181187.2
Variance1.0371926
MonotonicityNot monotonic
2023-12-12T20:48:48.338618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0527686 8
 
0.1%
127.0639634 8
 
0.1%
127.080798 8
 
0.1%
127.054967 6
 
0.1%
128.717274 5
 
0.1%
129.445724 5
 
0.1%
126.6519998581 5
 
0.1%
128.5183057 4
 
< 0.1%
127.0690832 4
 
< 0.1%
127.0780777 4
 
< 0.1%
Other values (8253) 9186
91.9%
(Missing) 757
 
7.6%
ValueCountFrequency (%)
124.6190553103 1
< 0.1%
124.6445936636 1
< 0.1%
124.650637287 1
< 0.1%
124.6529366749 1
< 0.1%
124.6628398839 1
< 0.1%
124.6628460683 1
< 0.1%
124.6638037411 1
< 0.1%
124.6685297681 1
< 0.1%
124.6733262881 1
< 0.1%
124.6750688807 1
< 0.1%
ValueCountFrequency (%)
130.907352288 1
< 0.1%
130.906256 1
< 0.1%
130.9014516 1
< 0.1%
130.8734365 2
< 0.1%
130.8701618 1
< 0.1%
130.854711 1
< 0.1%
130.8347969 1
< 0.1%
130.8205636 1
< 0.1%
130.800633 1
< 0.1%
130.79758 1
< 0.1%

수용가능면적
Real number (ℝ)

SKEWED 

Distinct5152
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6815.926
Minimum0
Maximum2025534
Zeros72
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:48.540676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile200
Q11321
median3193
Q36212.75
95-th percentile17135.9
Maximum2025534
Range2025534
Interquartile range (IQR)4891.75

Descriptive statistics

Standard deviation30845.586
Coefficient of variation (CV)4.5255165
Kurtosis2014.095
Mean6815.926
Median Absolute Deviation (MAD)2195.5
Skewness36.605002
Sum68159260
Variance9.5145015 × 108
MonotonicityNot monotonic
2023-12-12T20:48:48.766956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200.0 220
 
2.2%
3000.0 112
 
1.1%
330.0 88
 
0.9%
1500.0 76
 
0.8%
990.0 76
 
0.8%
0.0 72
 
0.7%
660.0 68
 
0.7%
1000.0 62
 
0.6%
3500.0 53
 
0.5%
1650.0 51
 
0.5%
Other values (5142) 9122
91.2%
ValueCountFrequency (%)
0.0 72
0.7%
14.021 1
 
< 0.1%
24.0 1
 
< 0.1%
29.25 1
 
< 0.1%
33.0 1
 
< 0.1%
37.8 1
 
< 0.1%
39.6 1
 
< 0.1%
41.0 1
 
< 0.1%
42.0 1
 
< 0.1%
43.0 1
 
< 0.1%
ValueCountFrequency (%)
2025534.0 1
< 0.1%
910009.0 1
< 0.1%
817515.0 1
< 0.1%
635170.0 1
< 0.1%
565295.0 1
< 0.1%
536255.0 1
< 0.1%
447631.0 1
< 0.1%
426400.0 1
< 0.1%
424851.0 1
< 0.1%
378440.0 1
< 0.1%

최대수용인원수
Real number (ℝ)

Distinct4301
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3981.4875
Minimum0
Maximum516848
Zeros78
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:48.994990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile77
Q1440
median1543.5
Q34023.25
95-th percentile12473.45
Maximum516848
Range516848
Interquartile range (IQR)3583.25

Descriptive statistics

Standard deviation12893.099
Coefficient of variation (CV)3.2382619
Kurtosis502.56021
Mean3981.4875
Median Absolute Deviation (MAD)1301.5
Skewness18.391681
Sum39814875
Variance1.6623201 × 108
MonotonicityNot monotonic
2023-12-12T20:48:49.191080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
242.0 209
 
2.1%
100.0 199
 
2.0%
200.0 170
 
1.7%
300.0 162
 
1.6%
500.0 155
 
1.6%
1000.0 79
 
0.8%
0.0 78
 
0.8%
400.0 78
 
0.8%
50.0 74
 
0.7%
150.0 61
 
0.6%
Other values (4291) 8735
87.4%
ValueCountFrequency (%)
0.0 78
0.8%
2.0 1
 
< 0.1%
3.0 1
 
< 0.1%
10.0 2
 
< 0.1%
11.0 1
 
< 0.1%
12.0 2
 
< 0.1%
13.0 3
 
< 0.1%
14.0 1
 
< 0.1%
15.0 6
 
0.1%
16.0 1
 
< 0.1%
ValueCountFrequency (%)
516848.0 1
< 0.1%
394409.0 1
< 0.1%
345407.0 1
< 0.1%
321442.0 1
< 0.1%
282285.0 1
< 0.1%
243893.0 1
< 0.1%
242424.0 1
< 0.1%
218181.0 1
< 0.1%
177640.0 1
< 0.1%
175730.0 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
9750 
False
 
250
ValueCountFrequency (%)
True 9750
97.5%
False 250
 
2.5%
2023-12-12T20:48:49.336038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct5199
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:48:49.629222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.952
Min length9

Characters and Unicode

Total characters119520
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4335 ?
Unique (%)43.4%

Sample

1st row032-502-5306
2nd row032-546-3551
3rd row070-4361-1372
4th row02-2199-7605
5th row041-734-2434
ValueCountFrequency (%)
054-270-2597 338
 
3.4%
000-0000-0000 182
 
1.8%
054-760-2034 140
 
1.4%
031-324-3308 138
 
1.4%
031-228-2933 114
 
1.1%
02-2600-6471 109
 
1.1%
053-662-3165 98
 
1.0%
055-392-2842 88
 
0.9%
054-270-8282 83
 
0.8%
032-560-4700 80
 
0.8%
Other values (5189) 8630
86.3%
2023-12-12T20:48:50.153857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20705
17.3%
- 19984
16.7%
2 12682
10.6%
3 12539
10.5%
5 10911
9.1%
4 9146
7.7%
6 8360
7.0%
1 7242
 
6.1%
7 6784
 
5.7%
8 5942
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99536
83.3%
Dash Punctuation 19984
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20705
20.8%
2 12682
12.7%
3 12539
12.6%
5 10911
11.0%
4 9146
9.2%
6 8360
8.4%
1 7242
 
7.3%
7 6784
 
6.8%
8 5942
 
6.0%
9 5225
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 19984
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119520
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20705
17.3%
- 19984
16.7%
2 12682
10.6%
3 12539
10.5%
5 10911
9.1%
4 9146
7.7%
6 8360
7.0%
1 7242
 
6.1%
7 6784
 
5.7%
8 5942
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119520
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20705
17.3%
- 19984
16.7%
2 12682
10.6%
3 12539
10.5%
5 10911
9.1%
4 9146
7.7%
6 8360
7.0%
1 7242
 
6.1%
7 6784
 
5.7%
8 5942
 
5.0%

부대편의시설
Categorical

IMBALANCE 

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9360 
없음
 
209
별도지구지정사항없음
 
50
조명+화장실+전기
 
38
실내대피소
 
38
Other values (30)
 
305

Length

Max length22
Median length4
Mean length4.1111
Min length1

Unique

Unique11 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9360
93.6%
없음 209
 
2.1%
별도지구지정사항없음 50
 
0.5%
조명+화장실+전기 38
 
0.4%
실내대피소 38
 
0.4%
조명+화장실 33
 
0.3%
Y 32
 
0.3%
화장실+전기 31
 
0.3%
- 27
 
0.3%
급식시설, 화장실 26
 
0.3%
Other values (25) 156
 
1.6%

Length

2023-12-12T20:48:50.361023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9360
92.4%
없음 209
 
2.1%
화장실 78
 
0.8%
별도지구지정사항없음 50
 
0.5%
실내대피소 38
 
0.4%
조명+화장실+전기 38
 
0.4%
급식시설 37
 
0.4%
조명+화장실 33
 
0.3%
y 32
 
0.3%
화장실+전기 31
 
0.3%
Other values (30) 223
 
2.2%
Distinct1218
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:48:50.906059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length8.8349
Min length1

Characters and Unicode

Total characters88349
Distinct characters300
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique621 ?
Unique (%)6.2%

Sample

1st row별도 지구지정사항 없음
2nd row별도 지구지정사항 없음
3rd row인헌동
4th row별도 지구지정사항 없음
5th row연산지구
ValueCountFrequency (%)
없음 5758
27.2%
별도 5216
24.7%
지구지정사항 4935
23.3%
별도지구지정사항없음 460
 
2.2%
별도지구지정사항 176
 
0.8%
지구지정사항없음 176
 
0.8%
지정지구 128
 
0.6%
주민대피소 124
 
0.6%
대구광역시동구 98
 
0.5%
충청북도 91
 
0.4%
Other values (1252) 3975
18.8%
2023-12-12T20:48:51.661569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13816
15.6%
11137
12.6%
8194
9.3%
6673
7.6%
6548
7.4%
6270
7.1%
6262
7.1%
5999
6.8%
5968
6.8%
5910
6.7%
Other values (290) 11572
13.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76315
86.4%
Space Separator 11137
 
12.6%
Decimal Number 672
 
0.8%
Dash Punctuation 107
 
0.1%
Uppercase Letter 55
 
0.1%
Other Punctuation 25
 
< 0.1%
Open Punctuation 19
 
< 0.1%
Close Punctuation 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13816
18.1%
8194
10.7%
6673
8.7%
6548
8.6%
6270
8.2%
6262
8.2%
5999
7.9%
5968
7.8%
5910
7.7%
609
 
0.8%
Other values (274) 10066
13.2%
Decimal Number
ValueCountFrequency (%)
2 213
31.7%
1 210
31.2%
3 100
14.9%
4 53
 
7.9%
5 37
 
5.5%
6 19
 
2.8%
7 18
 
2.7%
9 9
 
1.3%
8 8
 
1.2%
0 5
 
0.7%
Space Separator
ValueCountFrequency (%)
11137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 107
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 55
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76315
86.4%
Common 11979
 
13.6%
Latin 55
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13816
18.1%
8194
10.7%
6673
8.7%
6548
8.6%
6270
8.2%
6262
8.2%
5999
7.9%
5968
7.8%
5910
7.7%
609
 
0.8%
Other values (274) 10066
13.2%
Common
ValueCountFrequency (%)
11137
93.0%
2 213
 
1.8%
1 210
 
1.8%
- 107
 
0.9%
3 100
 
0.8%
4 53
 
0.4%
5 37
 
0.3%
, 25
 
0.2%
( 19
 
0.2%
6 19
 
0.2%
Other values (5) 59
 
0.5%
Latin
ValueCountFrequency (%)
N 55
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76315
86.4%
ASCII 12034
 
13.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
13816
18.1%
8194
10.7%
6673
8.7%
6548
8.6%
6270
8.2%
6262
8.2%
5999
7.9%
5968
7.8%
5910
7.7%
609
 
0.8%
Other values (274) 10066
13.2%
ASCII
ValueCountFrequency (%)
11137
92.5%
2 213
 
1.8%
1 210
 
1.7%
- 107
 
0.9%
3 100
 
0.8%
N 55
 
0.5%
4 53
 
0.4%
5 37
 
0.3%
, 25
 
0.2%
( 19
 
0.2%
Other values (6) 78
 
0.6%

주민대피지구내가구수
Real number (ℝ)

MISSING  ZEROS 

Distinct149
Distinct (%)20.5%
Missing9274
Missing (%)92.7%
Infinite0
Infinite (%)0.0%
Mean18541.935
Minimum0
Maximum397295
Zeros238
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:51.891395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median956.5
Q34729
95-th percentile20367
Maximum397295
Range397295
Interquartile range (IQR)4729

Descriptive statistics

Standard deviation74778.938
Coefficient of variation (CV)4.032963
Kurtosis21.70319
Mean18541.935
Median Absolute Deviation (MAD)956.5
Skewness4.8418153
Sum13461445
Variance5.5918896 × 109
MonotonicityNot monotonic
2023-12-12T20:48:52.072580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 238
 
2.4%
20367 84
 
0.8%
9317 39
 
0.4%
397295 27
 
0.3%
3 18
 
0.2%
1673 15
 
0.1%
1618 13
 
0.1%
1298 11
 
0.1%
10324 10
 
0.1%
1602 9
 
0.1%
Other values (139) 262
 
2.6%
(Missing) 9274
92.7%
ValueCountFrequency (%)
0 238
2.4%
1 2
 
< 0.1%
2 1
 
< 0.1%
3 18
 
0.2%
4 4
 
< 0.1%
9 7
 
0.1%
10 2
 
< 0.1%
12 2
 
< 0.1%
17 1
 
< 0.1%
20 2
 
< 0.1%
ValueCountFrequency (%)
397295 27
 
0.3%
20367 84
0.8%
17076 2
 
< 0.1%
16673 1
 
< 0.1%
10324 10
 
0.1%
10185 1
 
< 0.1%
10160 1
 
< 0.1%
9317 39
0.4%
9274 1
 
< 0.1%
8571 3
 
< 0.1%

주민대피지구내거주인수
Real number (ℝ)

MISSING  ZEROS 

Distinct142
Distinct (%)22.3%
Missing9363
Missing (%)93.6%
Infinite0
Infinite (%)0.0%
Mean46017.378
Minimum0
Maximum964400
Zeros163
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:52.251935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2628
Q311798
95-th percentile25201.2
Maximum964400
Range964400
Interquartile range (IQR)11798

Descriptive statistics

Standard deviation193502.25
Coefficient of variation (CV)4.204982
Kurtosis18.732739
Mean46017.378
Median Absolute Deviation (MAD)2628
Skewness4.5431537
Sum29313070
Variance3.744312 × 1010
MonotonicityNot monotonic
2023-12-12T20:48:52.721584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 163
 
1.6%
11798 84
 
0.8%
21943 39
 
0.4%
964400 27
 
0.3%
50 18
 
0.2%
3080 15
 
0.1%
2916 13
 
0.1%
2347 11
 
0.1%
25155 10
 
0.1%
2980 9
 
0.1%
Other values (132) 248
 
2.5%
(Missing) 9363
93.6%
ValueCountFrequency (%)
0 163
1.6%
1 1
 
< 0.1%
2 2
 
< 0.1%
3 1
 
< 0.1%
13 1
 
< 0.1%
14 2
 
< 0.1%
15 2
 
< 0.1%
16 1
 
< 0.1%
17 2
 
< 0.1%
20 2
 
< 0.1%
ValueCountFrequency (%)
964400 27
0.3%
40650 1
 
< 0.1%
40051 2
 
< 0.1%
26038 1
 
< 0.1%
25386 1
 
< 0.1%
25155 10
 
0.1%
21943 39
0.4%
21374 1
 
< 0.1%
19830 3
 
< 0.1%
17089 1
 
< 0.1%

주민대피지구내재해약자수
Real number (ℝ)

MISSING  ZEROS 

Distinct60
Distinct (%)11.7%
Missing9489
Missing (%)94.9%
Infinite0
Infinite (%)0.0%
Mean2420.5205
Minimum0
Maximum14509
Zeros211
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:52.918937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q32806
95-th percentile11184
Maximum14509
Range14509
Interquartile range (IQR)2806

Descriptive statistics

Standard deviation4434.4048
Coefficient of variation (CV)1.8320046
Kurtosis0.6815652
Mean2420.5205
Median Absolute Deviation (MAD)2
Skewness1.5627653
Sum1236886
Variance19663946
MonotonicityNot monotonic
2023-12-12T20:48:53.111891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 211
 
2.1%
11184 84
 
0.8%
1 41
 
0.4%
3000 27
 
0.3%
40 14
 
0.1%
50 11
 
0.1%
14509 10
 
0.1%
4 8
 
0.1%
3 7
 
0.1%
2 5
 
0.1%
Other values (50) 93
 
0.9%
(Missing) 9489
94.9%
ValueCountFrequency (%)
0 211
2.1%
1 41
 
0.4%
2 5
 
0.1%
3 7
 
0.1%
4 8
 
0.1%
5 4
 
< 0.1%
6 3
 
< 0.1%
7 3
 
< 0.1%
11 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
14509 10
 
0.1%
11184 84
0.8%
4262 3
 
< 0.1%
3566 1
 
< 0.1%
3000 27
 
0.3%
2867 3
 
< 0.1%
2745 3
 
< 0.1%
2550 2
 
< 0.1%
2232 3
 
< 0.1%
2112 1
 
< 0.1%

내진적용여부
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
미적용
8156 
적용
1810 
부분적용
 
34

Length

Max length4
Median length3
Mean length2.8224
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미적용 8156
81.6%
적용 1810
 
18.1%
부분적용 34
 
0.3%

Length

2023-12-12T20:48:53.307593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:48:53.449928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미적용 8156
81.6%
적용 1810
 
18.1%
부분적용 34
 
0.3%

내진설계등급
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9635 
1등급
 
311
2등급
 
52
특등급
 
2

Length

Max length4
Median length4
Mean length3.9635
Min length3

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> 9635
96.4%
1등급 311
 
3.1%
2등급 52
 
0.5%
특등급 2
 
< 0.1%

Length

2023-12-12T20:48:53.592797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:48:53.720038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9635
96.4%
1등급 311
 
3.1%
2등급 52
 
0.5%
특등급 2
 
< 0.1%

해안선이격거리
Real number (ℝ)

MISSING 

Distinct190
Distinct (%)21.8%
Missing9128
Missing (%)91.3%
Infinite0
Infinite (%)0.0%
Mean1183.0635
Minimum0
Maximum30000
Zeros38
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:53.871994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.87
Q1100
median250
Q3446.25
95-th percentile1113.5
Maximum30000
Range30000
Interquartile range (IQR)346.25

Descriptive statistics

Standard deviation5061.3604
Coefficient of variation (CV)4.2781814
Kurtosis28.575055
Mean1183.0635
Median Absolute Deviation (MAD)150
Skewness5.5156611
Sum1031631.4
Variance25617369
MonotonicityNot monotonic
2023-12-12T20:48:54.092261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 135
 
1.4%
300.0 47
 
0.5%
200.0 44
 
0.4%
0.0 38
 
0.4%
600.0 34
 
0.3%
250.0 30
 
0.3%
150.0 28
 
0.3%
30000.0 26
 
0.3%
500.0 22
 
0.2%
350.0 18
 
0.2%
Other values (180) 450
 
4.5%
(Missing) 9128
91.3%
ValueCountFrequency (%)
0.0 38
0.4%
2.6 1
 
< 0.1%
2.7 2
 
< 0.1%
2.9 1
 
< 0.1%
3.1 1
 
< 0.1%
4.1 1
 
< 0.1%
5.5 1
 
< 0.1%
5.8 1
 
< 0.1%
6.1 1
 
< 0.1%
7.1 1
 
< 0.1%
ValueCountFrequency (%)
30000.0 26
0.3%
2000.0 1
 
< 0.1%
1800.0 1
 
< 0.1%
1750.0 1
 
< 0.1%
1700.0 1
 
< 0.1%
1560.0 1
 
< 0.1%
1500.0 2
 
< 0.1%
1400.0 1
 
< 0.1%
1230.0 1
 
< 0.1%
1200.0 3
 
< 0.1%

해발높이
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)10.9%
Missing9071
Missing (%)90.7%
Infinite0
Infinite (%)0.0%
Mean20.858052
Minimum0
Maximum340
Zeros64
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:54.282821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median18
Q327
95-th percentile43
Maximum340
Range340
Interquartile range (IQR)17

Descriptive statistics

Standard deviation20.908284
Coefficient of variation (CV)1.0024083
Kurtosis122.14441
Mean20.858052
Median Absolute Deviation (MAD)8
Skewness8.7709219
Sum19377.13
Variance437.15633
MonotonicityNot monotonic
2023-12-12T20:48:54.503346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 105
 
1.1%
0.0 64
 
0.6%
30.0 56
 
0.6%
15.0 53
 
0.5%
20.0 52
 
0.5%
18.0 38
 
0.4%
17.0 34
 
0.3%
7.62 33
 
0.3%
11.0 30
 
0.3%
12.0 29
 
0.3%
Other values (91) 435
 
4.3%
(Missing) 9071
90.7%
ValueCountFrequency (%)
0.0 64
0.6%
3.0 1
 
< 0.1%
5.0 4
 
< 0.1%
6.0 11
 
0.1%
7.0 5
 
0.1%
7.62 33
 
0.3%
8.0 5
 
0.1%
8.8 2
 
< 0.1%
9.0 9
 
0.1%
10.0 105
1.1%
ValueCountFrequency (%)
340.0 2
< 0.1%
198.0 1
< 0.1%
122.0 1
< 0.1%
120.0 1
< 0.1%
83.0 1
< 0.1%
79.0 1
< 0.1%
76.0 2
< 0.1%
69.0 1
< 0.1%
63.0 1
< 0.1%
61.0 2
< 0.1%

지진대피안내표지판수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6603 
1
3016 
0
 
263
2
 
73
3
 
34

Length

Max length4
Median length4
Mean length2.9809
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6603
66.0%
1 3016
30.2%
0 263
 
2.6%
2 73
 
0.7%
3 34
 
0.3%
4 11
 
0.1%

Length

2023-12-12T20:48:54.709979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:48:54.872398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6603
66.0%
1 3016
30.2%
0 263
 
2.6%
2 73
 
0.7%
3 34
 
0.3%
4 11
 
0.1%
Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8754 
1
 
597
0
 
532
2
 
74
3
 
34

Length

Max length4
Median length4
Mean length3.6262
Min length1

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> 8754
87.5%
1 597
 
6.0%
0 532
 
5.3%
2 74
 
0.7%
3 34
 
0.3%
4 9
 
0.1%

Length

2023-12-12T20:48:55.034475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:48:55.180610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8754
87.5%
1 597
 
6.0%
0 532
 
5.3%
2 74
 
0.7%
3 34
 
0.3%
4 9
 
0.1%

지진대피로안내표지판수
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)3.5%
Missing9084
Missing (%)90.8%
Infinite0
Infinite (%)0.0%
Mean2.3930131
Minimum0
Maximum108
Zeros568
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:55.322632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile15
Maximum108
Range108
Interquartile range (IQR)1

Descriptive statistics

Standard deviation7.5340042
Coefficient of variation (CV)3.1483339
Kurtosis64.307545
Mean2.3930131
Median Absolute Deviation (MAD)0
Skewness6.6633866
Sum2192
Variance56.761219
MonotonicityNot monotonic
2023-12-12T20:48:55.472688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 568
 
5.7%
1 182
 
1.8%
3 23
 
0.2%
2 21
 
0.2%
6 15
 
0.1%
4 14
 
0.1%
5 10
 
0.1%
15 8
 
0.1%
8 7
 
0.1%
33 6
 
0.1%
Other values (22) 62
 
0.6%
(Missing) 9084
90.8%
ValueCountFrequency (%)
0 568
5.7%
1 182
 
1.8%
2 21
 
0.2%
3 23
 
0.2%
4 14
 
0.1%
5 10
 
0.1%
6 15
 
0.1%
7 2
 
< 0.1%
8 7
 
0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
108 1
 
< 0.1%
78 1
 
< 0.1%
65 1
 
< 0.1%
50 1
 
< 0.1%
47 1
 
< 0.1%
45 1
 
< 0.1%
40 1
 
< 0.1%
33 6
0.1%
27 6
0.1%
26 1
 
< 0.1%
Distinct963
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:48:55.836765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length30
Mean length8.2403
Min length2

Characters and Unicode

Total characters82403
Distinct characters286
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

Unique671 ?
Unique (%)6.7%

Sample

1st row인천광역시교육청 인천광역시북부교육지원청
2nd row인천광역시 계양구청
3rd row서울특별시 관악구청
4th row서울특별시 용산구청
5th row충청남도 논산시청
ValueCountFrequency (%)
경기도 824
 
4.7%
서울특별시 779
 
4.5%
경상북도 759
 
4.3%
전라북도 585
 
3.4%
대구광역시 447
 
2.6%
인천광역시 423
 
2.4%
포항시 418
 
2.4%
북구청 379
 
2.2%
충청남도 335
 
1.9%
울산광역시 291
 
1.7%
Other values (981) 12214
70.0%
2023-12-12T20:48:56.440167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7965
 
9.7%
7454
 
9.0%
6275
 
7.6%
4204
 
5.1%
3786
 
4.6%
2272
 
2.8%
2270
 
2.8%
2134
 
2.6%
2117
 
2.6%
2032
 
2.5%
Other values (276) 41894
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74905
90.9%
Space Separator 7454
 
9.0%
Decimal Number 29
 
< 0.1%
Other Punctuation 13
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7965
 
10.6%
6275
 
8.4%
4204
 
5.6%
3786
 
5.1%
2272
 
3.0%
2270
 
3.0%
2134
 
2.8%
2117
 
2.8%
2032
 
2.7%
1869
 
2.5%
Other values (265) 39981
53.4%
Decimal Number
ValueCountFrequency (%)
1 13
44.8%
2 9
31.0%
3 3
 
10.3%
4 3
 
10.3%
9 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 10
76.9%
, 2
 
15.4%
/ 1
 
7.7%
Space Separator
ValueCountFrequency (%)
7454
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74905
90.9%
Common 7498
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7965
 
10.6%
6275
 
8.4%
4204
 
5.6%
3786
 
5.1%
2272
 
3.0%
2270
 
3.0%
2134
 
2.8%
2117
 
2.8%
2032
 
2.7%
1869
 
2.5%
Other values (265) 39981
53.4%
Common
ValueCountFrequency (%)
7454
99.4%
1 13
 
0.2%
. 10
 
0.1%
2 9
 
0.1%
3 3
 
< 0.1%
4 3
 
< 0.1%
, 2
 
< 0.1%
( 1
 
< 0.1%
) 1
 
< 0.1%
/ 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74905
90.9%
ASCII 7498
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
7965
 
10.6%
6275
 
8.4%
4204
 
5.6%
3786
 
5.1%
2272
 
3.0%
2270
 
3.0%
2134
 
2.8%
2117
 
2.8%
2032
 
2.7%
1869
 
2.5%
Other values (265) 39981
53.4%
ASCII
ValueCountFrequency (%)
7454
99.4%
1 13
 
0.2%
. 10
 
0.1%
2 9
 
0.1%
3 3
 
< 0.1%
4 3
 
< 0.1%
, 2
 
< 0.1%
( 1
 
< 0.1%
) 1
 
< 0.1%
/ 1
 
< 0.1%
Distinct976
Distinct (%)14.7%
Missing3355
Missing (%)33.6%
Memory size156.2 KiB
2023-12-12T20:48:56.773717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.02453
Min length11

Characters and Unicode

Total characters79903
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique724 ?
Unique (%)10.9%

Sample

1st row032-502-5306
2nd row041-746-6348
3rd row061-362-7035
4th row032-503-9603
5th row000-0000-0000
ValueCountFrequency (%)
02-2116-4185 284
 
4.3%
053-667-3442 267
 
4.0%
054-760-2034 140
 
2.1%
063-454-3863 139
 
2.1%
031-324-3308 138
 
2.1%
063-0859-5507 128
 
1.9%
031-228-2933 114
 
1.7%
02-2600-6293 109
 
1.6%
02-2620-3336 100
 
1.5%
053-662-3165 98
 
1.5%
Other values (966) 5128
77.2%
2023-12-12T20:48:57.298347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 13290
16.6%
0 12540
15.7%
3 9498
11.9%
2 8823
11.0%
4 6999
8.8%
5 6322
7.9%
6 6241
7.8%
1 5253
 
6.6%
8 4419
 
5.5%
7 3550
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66613
83.4%
Dash Punctuation 13290
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12540
18.8%
3 9498
14.3%
2 8823
13.2%
4 6999
10.5%
5 6322
9.5%
6 6241
9.4%
1 5253
7.9%
8 4419
 
6.6%
7 3550
 
5.3%
9 2968
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 13290
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79903
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 13290
16.6%
0 12540
15.7%
3 9498
11.9%
2 8823
11.0%
4 6999
8.8%
5 6322
7.9%
6 6241
7.8%
1 5253
 
6.6%
8 4419
 
5.5%
7 3550
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79903
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 13290
16.6%
0 12540
15.7%
3 9498
11.9%
2 8823
11.0%
4 6999
8.8%
5 6322
7.9%
6 6241
7.8%
1 5253
 
6.6%
8 4419
 
5.5%
7 3550
 
4.4%
Distinct160
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-10 00:00:00
Maximum2020-11-25 00:00:00
2023-12-12T20:48:57.485370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:57.675120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

Distinct188
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4146561.9
Minimum1741000
Maximum6510000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:48:57.832024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1741000
5-th percentile3000000
Q13420000
median4060000
Q35020000
95-th percentile5710000
Maximum6510000
Range4769000
Interquartile range (IQR)1600000

Descriptive statistics

Standard deviation1029841
Coefficient of variation (CV)0.24836022
Kurtosis-0.22335348
Mean4146561.9
Median Absolute Deviation (MAD)780000
Skewness-0.067306835
Sum4.1465619 × 1010
Variance1.0605726 × 1012
MonotonicityNot monotonic
2023-12-12T20:48:58.015405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1741000 456
 
4.6%
5020000 441
 
4.4%
3100000 284
 
2.8%
3470000 267
 
2.7%
6310000 172
 
1.7%
3220000 150
 
1.5%
5050000 140
 
1.4%
3460000 139
 
1.4%
4670000 139
 
1.4%
4050000 138
 
1.4%
Other values (178) 7674
76.7%
ValueCountFrequency (%)
1741000 456
4.6%
3000000 65
 
0.7%
3010000 37
 
0.4%
3020000 42
 
0.4%
3030000 54
 
0.5%
3040000 51
 
0.5%
3050000 42
 
0.4%
3060000 29
 
0.3%
3070000 80
 
0.8%
3100000 284
2.8%
ValueCountFrequency (%)
6510000 76
0.8%
6310000 172
1.7%
6300000 122
1.2%
5710000 132
1.3%
5700000 24
 
0.2%
5680000 30
 
0.3%
5670000 95
0.9%
5600000 38
 
0.4%
5590000 72
0.7%
5580000 8
 
0.1%
Distinct188
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:48:58.397396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.9402
Min length5

Characters and Unicode

Total characters79402
Distinct characters127
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 row인천광역시 부평구
2nd row인천광역시 계양구
3rd row서울특별시 관악구
4th row서울특별시 용산구
5th row충청남도 논산시
ValueCountFrequency (%)
서울특별시 1673
 
8.7%
경기도 1364
 
7.1%
경상북도 1317
 
6.8%
대구광역시 761
 
4.0%
전라북도 713
 
3.7%
인천광역시 573
 
3.0%
경상남도 517
 
2.7%
충청북도 473
 
2.5%
행정안전부 456
 
2.4%
충청남도 450
 
2.3%
Other values (173) 10953
56.9%
2023-12-12T20:48:58.992958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9250
 
11.6%
7826
 
9.9%
5578
 
7.0%
4440
 
5.6%
3418
 
4.3%
2892
 
3.6%
2701
 
3.4%
2435
 
3.1%
2318
 
2.9%
2068
 
2.6%
Other values (117) 36476
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70152
88.4%
Space Separator 9250
 
11.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7826
 
11.2%
5578
 
8.0%
4440
 
6.3%
3418
 
4.9%
2892
 
4.1%
2701
 
3.9%
2435
 
3.5%
2318
 
3.3%
2068
 
2.9%
2019
 
2.9%
Other values (116) 34457
49.1%
Space Separator
ValueCountFrequency (%)
9250
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70152
88.4%
Common 9250
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7826
 
11.2%
5578
 
8.0%
4440
 
6.3%
3418
 
4.9%
2892
 
4.1%
2701
 
3.9%
2435
 
3.5%
2318
 
3.3%
2068
 
2.9%
2019
 
2.9%
Other values (116) 34457
49.1%
Common
ValueCountFrequency (%)
9250
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70152
88.4%
ASCII 9250
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9250
100.0%
Hangul
ValueCountFrequency (%)
7826
 
11.2%
5578
 
8.0%
4440
 
6.3%
3418
 
4.9%
2892
 
4.1%
2701
 
3.9%
2435
 
3.5%
2318
 
3.3%
2068
 
2.9%
2019
 
2.9%
Other values (116) 34457
49.1%

Sample

지진해일대피소명지진해일대피소구분지진해일대피소유형지진해일대피소유형구분소재지도로명주소소재지지번주소위도경도수용가능면적최대수용인원수지진해일대피소운영상태지진해일대피소전화번호부대편의시설주민대피지구명주민대피지구내가구수주민대피지구내거주인수주민대피지구내재해약자수내진적용여부내진설계등급해안선이격거리해발높이지진대피안내표지판수긴급대피장소안내표지판수지진대피로안내표지판수관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
7183부개서초등학교지진대피소실내대피소학교인천광역시 부평구 부일로 39(부개동)<NA>37.489903126.735186914.02095.0Y032-502-5306<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>인천광역시교육청 인천광역시북부교육지원청032-502-53062020-02-203540000인천광역시 부평구
6947성지초등학교 운동장지진대피소옥외대피소학교인천광역시 계양구 아나지로247번길 8 (작전동)<NA>37.526492126.7200683387.04106.0Y032-546-3551<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>인천광역시 계양구청<NA>2020-04-293550000인천광역시 계양구
7821인헌고등학교 운동장지진대피소옥외대피장소운동장서울특별시 관악구 인헌9길 74<NA>37.472309126.9704851946.0589.0Y070-4361-1372<NA>인헌동<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>서울특별시 관악구청<NA>2020-06-013200000서울특별시 관악구
5114소월길 어린이공원지진대피소옥외대피장소공원서울특별시 용산구 이태원동 463<NA><NA><NA>570.0691.0Y02-2199-7605<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>서울특별시 용산구청<NA>2020-07-073020000서울특별시 용산구
10350백석초등학교지진대피소옥외대피장소학교충청남도 논산시 연산면 선비로 726<NA>36.247347127.179571440.0200.0Y041-734-2434<NA>연산지구<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>충청남도 논산시청041-746-63482020-05-074540000충청남도 논산시
9748석곡초등학교지진대피소옥외대피소학교전라남도 곡성군 석곡면 석곡로 91전라남도 곡성군 석곡면 석곡리 8-135.134895127.2529831881.0400.0Y061-362-7035<NA>석곡면<NA><NA><NA>미적용<NA><NA><NA>100전라남도교육청 전라남도곡성교육지원청 석곡초등학교061-362-70352019-06-274860000전라남도 곡성군
9997문곡4리 마을회관지진대피소실내대피소기타강원도 영월군 북면 원동재로 6-31<NA><NA><NA>107.032.0Y033-370-2985<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>문곡4리 마을회관<NA>2018-08-294270000강원도 영월군
7556일신초등학교 운동장지진대피소옥외대피소운동장인천광역시 부평구 항동로75번길 36(일신동)<NA>37.483857126.7423923660.04436.0Y032-503-9603<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>인천광역시교육청 북부교육지원청032-503-96032020-02-203540000인천광역시 부평구
10670영암3리 마을회관 주변지진대피소옥외대피장소기타경상북도 포항시 남구 장기면 영암길 91<NA>35.911646129.523943200.0242.0Y054-270-2597<NA>영암지구<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>포항시<NA>2020-07-095020000경상북도 포항시
4695양사마을광장지진대피소옥외대피장소기타전라북도 고창군 성송면 하고리 672전라북도 고창군 성송면 하고리 67235.363977126.608291176.053.0Y000-0000-0000<NA>성송면11261938<NA>적용1등급<NA><NA><NA><NA><NA>전라북도 고창군청000-0000-00002020-07-074780000전라북도 고창군
지진해일대피소명지진해일대피소구분지진해일대피소유형지진해일대피소유형구분소재지도로명주소소재지지번주소위도경도수용가능면적최대수용인원수지진해일대피소운영상태지진해일대피소전화번호부대편의시설주민대피지구명주민대피지구내가구수주민대피지구내거주인수주민대피지구내재해약자수내진적용여부내진설계등급해안선이격거리해발높이지진대피안내표지판수긴급대피장소안내표지판수지진대피로안내표지판수관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
8712마산리 버스승강장 앞 공터지진해일대피소지진해일 긴급대피장소공터경상북도 포항시 남구 동해면 마산리 247-2경상북도 포항시 남구 동해면 마산리 247-236.015477129.4868966.020.0Y054-270-8282<NA>흥환지구<NA><NA><NA>미적용<NA>200.032.0<NA><NA><NA>포항시054-270-82822019-06-301741000행정안전부
6382서울로봇고등학교지진해일대피소실내대피소학교서울특별시 강남구 광평로 20길 63<NA>37.48073127.0845782079.0800.0Y02-3423-5766<NA>별도 지구지정사항 없음<NA><NA><NA>적용<NA><NA><NA><NA><NA><NA>서울특별시 강남구청<NA>2020-03-033220000서울특별시 강남구
3924완월초등학교운동장지진대피소옥외대피장소운동장경상남도 창원시 마산합포구 고운로 201 (완월동)<NA>35.200309128.5631593940.04650.0Y055-243-5030<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>마산합포구 안전건설과<NA>2020-07-145670000경상남도 창원시
6967학마을공원지진대피소옥외대피소공원인천광역시 계양구 용종로 115 (병방동)<NA>37.544111126.7420314644.05629.0Y032-450-5662<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>인천광역시 계양구청<NA>2020-04-293550000인천광역시 계양구
7775내발산초등학교운동장지진대피소옥외대피소학교서울특별시 강서구 강서로46길 23서울특별시 강서구 내발산동 70737.550881126.8381630.00.0N02-2600-6471<NA>별도지구지정사항없음<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>서울특별시 강서구청02-2600-62932020-06-033150000서울특별시 강서구
2471수정초등학교 운동장 지진대피소지진대피소옥외대피장소학교부산광역시 동구 진성로 29(수정동)부산광역시 동구 수정동 464-235.131265129.0467295382.01631.0Y051-468-5478Y부산광역시 동구 수정동3501적용<NA>600.030.0111부산광역시 동구 안전도시국 안전도시과051-440-46452020-09-233270000부산광역시 동구
7256부곡초등학교운동장지진대피소옥외대피장소운동장부산광역시 금정구 기찰로22번길 15<NA>35.234113129.09325214362.04352.0Y051-580-4805<NA>금정구<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>금정구청<NA>2020-06-173350000부산광역시 금정구
2452신반중학교 운동장지진대피소옥외대피장소운동장경상남도 의령군 부림면 한지28길 18-12경상남도 의령군 부림면 신반리 148-635.463137128.3200944800.05818.0Y055-574-6431화장실 및 급식소의령군<NA><NA>120미적용<NA>30000.00.011<NA>의령군청055-570-34142020-09-185390000경상남도 의령군
2004오동초등학교지진대피소옥외대피장소학교경기도 의정부시 용민로 151경기도 의정부시 민락동 735-637.743004127.090594222.04222.0Y031-852-1071<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>경기도 의정부교육지원청031-820-01862020-10-053820000경기도 의정부시
1925경기관광고등학교지진대피소옥외대피장소운동장경기도 여주시 대신면여양로 1416<NA>37.375484127.5893982640.0800.0Y031-882-2250<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA><NA><NA><NA>경기관광고등학교031-882-22502020-07-175700000경기도 여주시

Duplicate rows

Most frequently occurring

지진해일대피소명지진해일대피소구분지진해일대피소유형지진해일대피소유형구분소재지도로명주소소재지지번주소위도경도수용가능면적최대수용인원수지진해일대피소운영상태지진해일대피소전화번호부대편의시설주민대피지구명주민대피지구내가구수주민대피지구내거주인수주민대피지구내재해약자수내진적용여부내진설계등급해안선이격거리해발높이지진대피안내표지판수긴급대피장소안내표지판수지진대피로안내표지판수관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명# duplicates
0갈울근린공원지진대피소옥외대피장소공원서울시 노원구 상계동 644서울특별시 노원구 상계동 644<NA><NA>3200.03879.0Y02-2116-3944<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4
9계상초등학교지진대피소옥외대피장소학교서울특별시 노원구 한글비석로41가길 24서울특별시 노원구 상계동 447-137.662197127.0686774270.05176.0Y02-2116-2837<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4
10공릉중학교지진대피소옥외대피장소학교서울특별시 노원구 노원로1길 42서울특별시 노원구 공릉동 25037.622227127.0836014590.05564.0Y02-971-5212<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4
12공연초등학교지진대피소옥외대피장소학교서울특별시 노원구 동일로192가길 16서울특별시 노원구 공릉동 371-1037.627549127.0745083800.04606.0Y02-973-9500<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4
13광운전자공업고등학교지진대피소옥외대피장소학교서울특별시 노원구 광운로1길 24서울특별시 노원구 월계동 50037.619241127.0565449540.011564.0Y02-918-7763<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4
18노원고등학교지진대피소옥외대피장소학교서울특별시 노원구 노원로 586서울특별시 노원구 상계동 66437.661801127.054022930.03552.0Y02-937-0038<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4
20노원초등학교지진대피소옥외대피장소학교서울특별시 노원구 동일로230나길 32서울특별시 노원구 상계동 101437.673595127.0584544010.04861.0Y02-939-1894<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4
21노일중학교지진대피소옥외대피장소학교서울특별시 노원구 동일로231길 24서울특별시 노원구 상계동 104437.672289127.0538914580.05552.0Y02-3391-0094<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4
23녹천중학교지진대피소옥외대피장소학교서울특별시 노원구 월계로 372서울특별시 노원구 월계동 321-737.629248127.0596654670.05661.0Y02-978-4591<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4
24녹천초등학교지진대피소옥외대피장소학교서울특별시 노원구 마들로3길 34서울특별시 노원구 월계동 322-237.628507127.0631172740.03321.0Y02-977-0670<NA>별도 지구지정사항 없음<NA><NA><NA>미적용<NA><NA><NA>1<NA><NA>노원구청02-2116-41852020-07-103100000서울특별시 노원구4