Overview

Dataset statistics

Number of variables31
Number of observations583
Missing cells525
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory142.5 KiB
Average record size in memory250.2 B

Variable types

Text6
Categorical22
Numeric2
DateTime1

Dataset

Description경상남도 급경사지 붕괴위험지구 지정현황에 대한 데이터로, 위치, 관리기관, 재해위험도, 붕괴위험지역 지정고시일 등에 관한 정보들을 제공합니다.
Author경상남도
URLhttps://www.data.go.kr/data/15108460/fileData.do

Alerts

위치_시도 has constant value ""Constant
용도_기타상세 is highly imbalanced (68.3%)Imbalance
분류_유형 is highly imbalanced (54.6%)Imbalance
관리기관 세부현황 is highly imbalanced (59.0%)Imbalance
관리기관_소유자나 점유자 혹은 관계인 is highly imbalanced (51.3%)Imbalance
관리기관_공공 또는 민간 is highly imbalanced (89.5%)Imbalance
붕괴위험지역_상시계측현황 is highly imbalanced (88.0%)Imbalance
붕괴위험지역_주민대피 관리기준 제정여부 is highly imbalanced (54.4%)Imbalance
붕괴위험지역_지정해제일 is highly imbalanced (77.3%)Imbalance
기타_과거사고 발생현황 is highly imbalanced (87.3%)Imbalance
기타_비고 is highly imbalanced (94.4%)Imbalance
위치_읍면 has 37 (6.3%) missing valuesMissing
제원_평균경사_도 has 14 (2.4%) missing valuesMissing
붕괴위험지역_지정고시일 has 469 (80.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 02:48:22.991126
Analysis finished2023-12-12 02:48:23.882146
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지구명
Text

Distinct537
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-12T11:48:24.194181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length10
Mean length5.941681
Min length2

Characters and Unicode

Total characters3464
Distinct characters161
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

Unique526 ?
Unique (%)90.2%

Sample

1st row관덕
2nd row덕포구집
3rd row한산죽전
4th row비진
5th row서피랑
ValueCountFrequency (%)
경전선 127
 
13.9%
경전 119
 
13.0%
지구 29
 
3.2%
영남 16
 
1.8%
경부선 14
 
1.5%
삼정 12
 
1.3%
중산 8
 
0.9%
진해선 8
 
0.9%
황점지구 7
 
0.8%
송계지구 6
 
0.7%
Other values (547) 566
62.1%
2023-12-12T11:48:24.711182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 356
 
10.3%
전 338
 
9.8%
330
 
9.5%
2 204
 
5.9%
선 195
 
5.6%
3 184
 
5.3%
4 173
 
5.0%
1 156
 
4.5%
지 112
 
3.2%
0 110
 
3.2%
Other values (151) 1306
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1775
51.2%
Decimal Number 1239
35.8%
Space Separator 330
 
9.5%
Dash Punctuation 88
 
2.5%
Close Punctuation 16
 
0.5%
Open Punctuation 16
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 356
20.1%
전 338
19.0%
선 195
 
11.0%
지 112
 
6.3%
구 106
 
6.0%
산 47
 
2.6%
부 37
 
2.1%
수 23
 
1.3%
신 20
 
1.1%
남 20
 
1.1%
Other values (137) 521
29.4%
Decimal Number
ValueCountFrequency (%)
2 204
16.5%
3 184
14.9%
4 173
14.0%
1 156
12.6%
0 110
8.9%
6 94
7.6%
8 92
7.4%
5 89
7.2%
7 77
 
6.2%
9 60
 
4.8%
Space Separator
ValueCountFrequency (%)
330
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1775
51.2%
Common 1689
48.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 356
20.1%
전 338
19.0%
선 195
 
11.0%
지 112
 
6.3%
구 106
 
6.0%
산 47
 
2.6%
부 37
 
2.1%
수 23
 
1.3%
신 20
 
1.1%
남 20
 
1.1%
Other values (137) 521
29.4%
Common
ValueCountFrequency (%)
330
19.5%
2 204
12.1%
3 184
10.9%
4 173
10.2%
1 156
9.2%
0 110
 
6.5%
6 94
 
5.6%
8 92
 
5.4%
5 89
 
5.3%
- 88
 
5.2%
Other values (4) 169
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1775
51.2%
ASCII 1689
48.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 356
20.1%
전 338
19.0%
선 195
 
11.0%
지 112
 
6.3%
구 106
 
6.0%
산 47
 
2.6%
부 37
 
2.1%
수 23
 
1.3%
신 20
 
1.1%
남 20
 
1.1%
Other values (137) 521
29.4%
ASCII
ValueCountFrequency (%)
330
19.5%
2 204
12.1%
3 184
10.9%
4 173
10.2%
1 156
9.2%
0 110
 
6.5%
6 94
 
5.6%
8 92
 
5.4%
5 89
 
5.3%
- 88
 
5.2%
Other values (4) 169
10.0%

위치_시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
경남도
583 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경남도 583
100.0%

Length

2023-12-12T11:48:24.855942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:24.961140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경남도 583
100.0%

위치_시군구
Categorical

Distinct17
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
진주시
165 
하동군
85 
함안군
57 
함양군
45 
합천군
37 
Other values (12)
194 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진주시 165
28.3%
하동군 85
14.6%
함안군 57
 
9.8%
함양군 45
 
7.7%
합천군 37
 
6.3%
사천시 36
 
6.2%
창원시 29
 
5.0%
남해군 28
 
4.8%
거창군 19
 
3.3%
양산시 17
 
2.9%
Other values (7) 65
 
11.1%

Length

2023-12-12T11:48:25.087692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진주시 165
28.3%
하동군 85
14.6%
함안군 57
 
9.8%
함양군 45
 
7.7%
합천군 37
 
6.3%
사천시 36
 
6.2%
창원시 29
 
5.0%
남해군 28
 
4.8%
거창군 19
 
3.3%
양산시 17
 
2.9%
Other values (7) 65
 
11.1%

위치_읍면
Text

MISSING 

Distinct94
Distinct (%)17.2%
Missing37
Missing (%)6.3%
Memory size4.7 KiB
2023-12-12T11:48:25.347737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.2234432
Min length2

Characters and Unicode

Total characters1760
Distinct characters95
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)6.8%

Sample

1st row도산면
2nd row광도면
3rd row한산면
4th row한산면
5th row용현면
ValueCountFrequency (%)
내동면 52
 
9.3%
문산읍 36
 
6.4%
마천면 32
 
5.7%
곤명면 32
 
5.7%
군북면 30
 
5.3%
진성면 27
 
4.8%
횡천면 22
 
3.9%
양보면 17
 
3.0%
마산회원구 17
 
3.0%
내서읍 16
 
2.9%
Other values (83) 280
49.9%
2023-12-12T11:48:25.802091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 439
24.9%
읍 91
 
5.2%
동 80
 
4.5%
천 78
 
4.4%
산 76
 
4.3%
내 68
 
3.9%
성 63
 
3.6%
북 60
 
3.4%
마 49
 
2.8%
진 48
 
2.7%
Other values (85) 708
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1744
99.1%
Space Separator 15
 
0.9%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 439
25.2%
읍 91
 
5.2%
동 80
 
4.6%
천 78
 
4.5%
산 76
 
4.4%
내 68
 
3.9%
성 63
 
3.6%
북 60
 
3.4%
마 49
 
2.8%
진 48
 
2.8%
Other values (83) 692
39.7%
Space Separator
ValueCountFrequency (%)
15
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1744
99.1%
Common 16
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 439
25.2%
읍 91
 
5.2%
동 80
 
4.6%
천 78
 
4.5%
산 76
 
4.4%
내 68
 
3.9%
성 63
 
3.6%
북 60
 
3.4%
마 49
 
2.8%
진 48
 
2.8%
Other values (83) 692
39.7%
Common
ValueCountFrequency (%)
15
93.8%
2 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1744
99.1%
ASCII 16
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 439
25.2%
읍 91
 
5.2%
동 80
 
4.6%
천 78
 
4.5%
산 76
 
4.4%
내 68
 
3.9%
성 63
 
3.6%
북 60
 
3.4%
마 49
 
2.8%
진 48
 
2.8%
Other values (83) 692
39.7%
ASCII
ValueCountFrequency (%)
15
93.8%
2 1
 
6.2%

위치_리동
Text

Distinct233
Distinct (%)40.3%
Missing5
Missing (%)0.9%
Memory size4.7 KiB
2023-12-12T11:48:26.123435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length4
Mean length4.9602076
Min length2

Characters and Unicode

Total characters2867
Distinct characters163
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

Unique146 ?
Unique (%)25.3%

Sample

1st row관덕리
2nd row덕포리
3rd row하소리
4th row비진리
5th row서호동
ValueCountFrequency (%)
경전선(양보-횡천간 21
 
3.2%
독산리 19
 
2.9%
원북리 16
 
2.4%
삼정리 16
 
2.4%
유수리 15
 
2.3%
경전선(횡천-하동간 15
 
2.3%
가좌동 14
 
2.1%
감당리 13
 
2.0%
천곡리 13
 
2.0%
옥산리 13
 
2.0%
Other values (212) 511
76.7%
2023-12-12T11:48:26.624356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 531
 
18.5%
407
 
14.2%
천 100
 
3.5%
동 88
 
3.1%
산 81
 
2.8%
전 81
 
2.8%
간 70
 
2.4%
경 60
 
2.1%
선 59
 
2.1%
- 55
 
1.9%
Other values (153) 1335
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2271
79.2%
Space Separator 407
 
14.2%
Dash Punctuation 55
 
1.9%
Close Punctuation 52
 
1.8%
Open Punctuation 52
 
1.8%
Math Symbol 18
 
0.6%
Decimal Number 12
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 531
23.4%
천 100
 
4.4%
동 88
 
3.9%
산 81
 
3.6%
전 81
 
3.6%
간 70
 
3.1%
경 60
 
2.6%
선 59
 
2.6%
곡 54
 
2.4%
횡 47
 
2.1%
Other values (141) 1100
48.4%
Decimal Number
ValueCountFrequency (%)
4 3
25.0%
6 3
25.0%
3 2
16.7%
9 1
 
8.3%
1 1
 
8.3%
8 1
 
8.3%
7 1
 
8.3%
Space Separator
ValueCountFrequency (%)
407
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2271
79.2%
Common 596
 
20.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 531
23.4%
천 100
 
4.4%
동 88
 
3.9%
산 81
 
3.6%
전 81
 
3.6%
간 70
 
3.1%
경 60
 
2.6%
선 59
 
2.6%
곡 54
 
2.4%
횡 47
 
2.1%
Other values (141) 1100
48.4%
Common
ValueCountFrequency (%)
407
68.3%
- 55
 
9.2%
) 52
 
8.7%
( 52
 
8.7%
~ 18
 
3.0%
4 3
 
0.5%
6 3
 
0.5%
3 2
 
0.3%
9 1
 
0.2%
1 1
 
0.2%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2271
79.2%
ASCII 596
 
20.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 531
23.4%
천 100
 
4.4%
동 88
 
3.9%
산 81
 
3.6%
전 81
 
3.6%
간 70
 
3.1%
경 60
 
2.6%
선 59
 
2.6%
곡 54
 
2.4%
횡 47
 
2.1%
Other values (141) 1100
48.4%
ASCII
ValueCountFrequency (%)
407
68.3%
- 55
 
9.2%
) 52
 
8.7%
( 52
 
8.7%
~ 18
 
3.0%
4 3
 
0.5%
6 3
 
0.5%
3 2
 
0.3%
9 1
 
0.2%
1 1
 
0.2%
Other values (2) 2
 
0.3%

위치_지번
Text

Distinct481
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-12T11:48:26.957144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length7.2109777
Min length1

Characters and Unicode

Total characters4204
Distinct characters35
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

Unique407 ?
Unique (%)69.8%

Sample

1st row산278번지
2nd row산129번지
3rd row499-5번지
4th row147번지
5th row11-1번지
ValueCountFrequency (%)
산 218
 
26.6%
161번지 12
 
1.5%
208번지 8
 
1.0%
임번지 8
 
1.0%
번지 7
 
0.9%
160번지 5
 
0.6%
282번지 4
 
0.5%
130-2번지 3
 
0.4%
7-3번지 3
 
0.4%
50-1번지 3
 
0.4%
Other values (471) 549
67.0%
2023-12-12T11:48:27.465266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
번 582
13.8%
지 582
13.8%
1 436
10.4%
- 427
10.2%
2 310
7.4%
산 289
 
6.9%
245
 
5.8%
3 205
 
4.9%
4 190
 
4.5%
5 167
 
4.0%
Other values (25) 771
18.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2044
48.6%
Other Letter 1486
35.3%
Dash Punctuation 427
 
10.2%
Space Separator 245
 
5.8%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 582
39.2%
지 582
39.2%
산 289
19.4%
임 8
 
0.5%
리 7
 
0.5%
도 2
 
0.1%
동 2
 
0.1%
성 1
 
0.1%
월 1
 
0.1%
남 1
 
0.1%
Other values (11) 11
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 436
21.3%
2 310
15.2%
3 205
10.0%
4 190
9.3%
5 167
 
8.2%
6 162
 
7.9%
7 161
 
7.9%
9 139
 
6.8%
8 138
 
6.8%
0 136
 
6.7%
Dash Punctuation
ValueCountFrequency (%)
- 427
100.0%
Space Separator
ValueCountFrequency (%)
245
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2718
64.7%
Hangul 1486
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 582
39.2%
지 582
39.2%
산 289
19.4%
임 8
 
0.5%
리 7
 
0.5%
도 2
 
0.1%
동 2
 
0.1%
성 1
 
0.1%
월 1
 
0.1%
남 1
 
0.1%
Other values (11) 11
 
0.7%
Common
ValueCountFrequency (%)
1 436
16.0%
- 427
15.7%
2 310
11.4%
245
9.0%
3 205
7.5%
4 190
7.0%
5 167
 
6.1%
6 162
 
6.0%
7 161
 
5.9%
9 139
 
5.1%
Other values (4) 276
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2718
64.7%
Hangul 1486
35.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
번 582
39.2%
지 582
39.2%
산 289
19.4%
임 8
 
0.5%
리 7
 
0.5%
도 2
 
0.1%
동 2
 
0.1%
성 1
 
0.1%
월 1
 
0.1%
남 1
 
0.1%
Other values (11) 11
 
0.7%
ASCII
ValueCountFrequency (%)
1 436
16.0%
- 427
15.7%
2 310
11.4%
245
9.0%
3 205
7.5%
4 190
7.0%
5 167
 
6.1%
6 162
 
6.0%
7 161
 
5.9%
9 139
 
5.1%
Other values (4) 276
10.2%

용도_종류
Categorical

Distinct7
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
철도
377 
도로
102 
공원
58 
주택
 
24
기타
 
16
Other values (2)
 
6

Length

Max length3
Median length2
Mean length2.0085763
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row기타
2nd row기타
3rd row도로
4th row도로
5th row주택

Common Values

ValueCountFrequency (%)
철도 377
64.7%
도로 102
 
17.5%
공원 58
 
9.9%
주택 24
 
4.1%
기타 16
 
2.7%
아파트 5
 
0.9%
공단 1
 
0.2%

Length

2023-12-12T11:48:27.636165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:27.803664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철도 377
64.7%
도로 102
 
17.5%
공원 58
 
9.9%
주택 24
 
4.1%
기타 16
 
2.7%
아파트 5
 
0.9%
공단 1
 
0.2%

용도_기타상세
Categorical

IMBALANCE 

Distinct37
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
<NA>
443 
공원
57 
도로(지,군,비)
 
14
면도
 
11
여방수로
 
9
Other values (32)
49 

Length

Max length9
Median length4
Mean length3.8113208
Min length1

Unique

Unique26 ?
Unique (%)4.5%

Sample

1st row토사
2nd row암반
3rd row토사
4th row옹벽
5th row토사

Common Values

ValueCountFrequency (%)
<NA> 443
76.0%
공원 57
 
9.8%
도로(지,군,비) 14
 
2.4%
면도 11
 
1.9%
여방수로 9
 
1.5%
아파트 5
 
0.9%
리도 5
 
0.9%
토사 5
 
0.9%
관리도로 3
 
0.5%
군3 3
 
0.5%
Other values (27) 28
 
4.8%

Length

2023-12-12T11:48:27.992047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 443
75.5%
공원 57
 
9.7%
도로(지,군,비 14
 
2.4%
면도 11
 
1.9%
여방수로 9
 
1.5%
아파트 5
 
0.9%
리도 5
 
0.9%
토사 5
 
0.9%
군3 3
 
0.5%
관리도로 3
 
0.5%
Other values (28) 32
 
5.5%

분류_유형
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
인공
443 
자연 또는 산지
61 
옹벽 및 축대
 
38
자연
 
21
인공비탈면
 
14
Other values (2)
 
6

Length

Max length11
Median length2
Mean length3.0668954
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
인공 443
76.0%
자연 또는 산지 61
 
10.5%
옹벽 및 축대 38
 
6.5%
자연 21
 
3.6%
인공비탈면 14
 
2.4%
자연비탈면 5
 
0.9%
자연비탈면 또는 산지 1
 
0.2%

Length

2023-12-12T11:48:28.139726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:28.298887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인공 443
56.6%
자연 82
 
10.5%
또는 62
 
7.9%
산지 62
 
7.9%
옹벽 38
 
4.9%
및 38
 
4.9%
축대 38
 
4.9%
인공비탈면 14
 
1.8%
자연비탈면 6
 
0.8%

분류_구조
Categorical

Distinct8
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
암반
193 
복합
154 
토사
103 
기타
80 
석축
28 
Other values (3)
25 

Length

Max length6
Median length2
Mean length2.1063465
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row토사
2nd row암반
3rd row토사
4th row옹벽
5th row토사

Common Values

ValueCountFrequency (%)
암반 193
33.1%
복합 154
26.4%
토사 103
17.7%
기타 80
13.7%
석축 28
 
4.8%
콘크리트옹벽 15
 
2.6%
옹벽 9
 
1.5%
<NA> 1
 
0.2%

Length

2023-12-12T11:48:28.463681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:28.646968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
암반 193
33.1%
복합 154
26.4%
토사 103
17.7%
기타 80
13.7%
석축 28
 
4.8%
콘크리트옹벽 15
 
2.6%
옹벽 9
 
1.5%
na 1
 
0.2%

자연 또는 인공종류
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
인공
495 
자연
88 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인공 495
84.9%
자연 88
 
15.1%

Length

2023-12-12T11:48:28.803942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:28.904113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인공 495
84.9%
자연 88
 
15.1%

제원_길이_미터
Real number (ℝ)

Distinct115
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean145.30017
Minimum5
Maximum3500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-12T11:48:29.017361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile20
Q150
median100
Q3150
95-th percentile400
Maximum3500
Range3495
Interquartile range (IQR)100

Descriptive statistics

Standard deviation233.8354
Coefficient of variation (CV)1.6093264
Kurtosis88.649168
Mean145.30017
Median Absolute Deviation (MAD)50
Skewness7.9566219
Sum84710
Variance54678.994
MonotonicityNot monotonic
2023-12-12T11:48:29.205672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 46
 
7.9%
50 44
 
7.5%
40 31
 
5.3%
70 30
 
5.1%
20 24
 
4.1%
150 23
 
3.9%
120 22
 
3.8%
80 22
 
3.8%
30 18
 
3.1%
140 17
 
2.9%
Other values (105) 306
52.5%
ValueCountFrequency (%)
5 4
 
0.7%
7 1
 
0.2%
9 1
 
0.2%
10 4
 
0.7%
12 1
 
0.2%
15 5
 
0.9%
20 24
4.1%
22 1
 
0.2%
23 2
 
0.3%
24 1
 
0.2%
ValueCountFrequency (%)
3500 1
0.2%
1900 1
0.2%
1727 1
0.2%
1681 1
0.2%
1610 1
0.2%
1500 1
0.2%
1000 2
0.3%
920 1
0.2%
800 1
0.2%
660 1
0.2%

제원_높이_미터
Text

Distinct72
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-12T11:48:29.477521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length1.6466552
Min length1

Characters and Unicode

Total characters960
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)5.5%

Sample

1st row50
2nd row50
3rd row15
4th row15
5th row15
ValueCountFrequency (%)
5 79
13.6%
6 60
 
10.3%
7 57
 
9.8%
15 41
 
7.0%
10 39
 
6.7%
20 38
 
6.5%
8 34
 
5.8%
4 24
 
4.1%
30 16
 
2.7%
12 14
 
2.4%
Other values (62) 181
31.0%
2023-12-12T11:48:29.892668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 185
19.3%
1 165
17.2%
2 123
12.8%
0 120
12.5%
7 78
8.1%
6 77
8.0%
4 64
 
6.7%
8 51
 
5.3%
3 41
 
4.3%
. 36
 
3.8%
Other values (2) 20
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 920
95.8%
Other Punctuation 36
 
3.8%
Math Symbol 4
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 185
20.1%
1 165
17.9%
2 123
13.4%
0 120
13.0%
7 78
8.5%
6 77
8.4%
4 64
 
7.0%
8 51
 
5.5%
3 41
 
4.5%
9 16
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 36
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 960
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 185
19.3%
1 165
17.2%
2 123
12.8%
0 120
12.5%
7 78
8.1%
6 77
8.0%
4 64
 
6.7%
8 51
 
5.3%
3 41
 
4.3%
. 36
 
3.8%
Other values (2) 20
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 185
19.3%
1 165
17.2%
2 123
12.8%
0 120
12.5%
7 78
8.1%
6 77
8.0%
4 64
 
6.7%
8 51
 
5.3%
3 41
 
4.3%
. 36
 
3.8%
Other values (2) 20
 
2.1%

제원_평균경사_도
Real number (ℝ)

MISSING 

Distinct57
Distinct (%)10.0%
Missing14
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean62.336555
Minimum1
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-12T11:48:30.060406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile37
Q155
median65
Q370
95-th percentile80
Maximum90
Range89
Interquartile range (IQR)15

Descriptive statistics

Standard deviation12.948286
Coefficient of variation (CV)0.20771577
Kurtosis0.69814372
Mean62.336555
Median Absolute Deviation (MAD)5
Skewness-0.68818793
Sum35469.5
Variance167.6581
MonotonicityNot monotonic
2023-12-12T11:48:30.235815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70.0 149
25.6%
60.0 87
14.9%
65.0 48
 
8.2%
80.0 31
 
5.3%
45.0 30
 
5.1%
55.0 30
 
5.1%
50.0 25
 
4.3%
75.0 21
 
3.6%
64.0 19
 
3.3%
63.0 9
 
1.5%
Other values (47) 120
20.6%
(Missing) 14
 
2.4%
ValueCountFrequency (%)
1.0 1
 
0.2%
24.0 1
 
0.2%
27.0 1
 
0.2%
28.0 1
 
0.2%
30.0 6
1.0%
31.0 1
 
0.2%
32.0 1
 
0.2%
33.0 1
 
0.2%
34.0 5
0.9%
35.0 1
 
0.2%
ValueCountFrequency (%)
90.0 1
 
0.2%
89.0 2
 
0.3%
88.0 5
 
0.9%
87.0 2
 
0.3%
85.0 8
 
1.4%
83.0 1
 
0.2%
82.0 6
 
1.0%
81.0 1
 
0.2%
80.0 31
5.3%
78.0 1
 
0.2%

관리기관
Categorical

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
국가철도공단
377 
지자체
131 
국립공원공단
57 
한국농어촌공사
 
12
한국토지주택공사
 
5

Length

Max length8
Median length6
Mean length5.3619211
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
국가철도공단 377
64.7%
지자체 131
 
22.5%
국립공원공단 57
 
9.8%
한국농어촌공사 12
 
2.1%
한국토지주택공사 5
 
0.9%
지방산림청 1
 
0.2%

Length

2023-12-12T11:48:30.362813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:30.473787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국가철도공단 377
64.7%
지자체 131
 
22.5%
국립공원공단 57
 
9.8%
한국농어촌공사 12
 
2.1%
한국토지주택공사 5
 
0.9%
지방산림청 1
 
0.2%

관리기관 세부현황
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
<NA>
452 
지자체
127 
기업
 
2
개인
 
2

Length

Max length4
Median length4
Mean length3.7684391
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지자체
2nd row기업
3rd row지자체
4th row지자체
5th row지자체

Common Values

ValueCountFrequency (%)
<NA> 452
77.5%
지자체 127
 
21.8%
기업 2
 
0.3%
개인 2
 
0.3%

Length

2023-12-12T11:48:30.823433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:30.930366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 452
77.5%
지자체 127
 
21.8%
기업 2
 
0.3%
개인 2
 
0.3%

관리기관_소유자나 점유자 혹은 관계인
Categorical

IMBALANCE 

Distinct29
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
영남본부
377 
지리산국립공원경남사무소
 
35
건설과
 
26
남해군
 
19
안전총괄과
 
18
Other values (24)
108 

Length

Max length17
Median length4
Mean length5.2212693
Min length2

Unique

Unique9 ?
Unique (%)1.5%

Sample

1st row통영시
2nd rowSPP조선㈜
3rd row통영시
4th row통영시
5th row통영시

Common Values

ValueCountFrequency (%)
영남본부 377
64.7%
지리산국립공원경남사무소 35
 
6.0%
건설과 26
 
4.5%
남해군 19
 
3.3%
안전총괄과 18
 
3.1%
안전도시과 17
 
2.9%
덕유산국립공원사무소 13
 
2.2%
경상남도 도로관리사업소 10
 
1.7%
경상남도 도로관리사업소 진주지소 9
 
1.5%
안전건설과 7
 
1.2%
Other values (19) 52
 
8.9%

Length

2023-12-12T11:48:31.026741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영남본부 377
60.4%
지리산국립공원경남사무소 35
 
5.6%
건설과 26
 
4.2%
남해군 19
 
3.0%
경상남도 19
 
3.0%
도로관리사업소 19
 
3.0%
안전총괄과 18
 
2.9%
안전도시과 17
 
2.7%
덕유산국립공원사무소 13
 
2.1%
경남지역본부 11
 
1.8%
Other values (23) 70
 
11.2%

관리기관_공공 또는 민간
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
공공
575 
민간
 
8

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공 575
98.6%
민간 8
 
1.4%

Length

2023-12-12T11:48:31.145655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:31.233389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공 575
98.6%
민간 8
 
1.4%

재해위험도평가_점수
Text

Distinct71
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-12T11:48:31.412744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.058319
Min length1

Characters and Unicode

Total characters1200
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

Unique11 ?
Unique (%)1.9%

Sample

1st row70
2nd row70
3rd row70
4th row61
5th row70
ValueCountFrequency (%)
32 34
 
5.8%
35 34
 
5.8%
34 33
 
5.7%
33 26
 
4.5%
27 24
 
4.1%
31 20
 
3.4%
38 19
 
3.3%
37 18
 
3.1%
43 17
 
2.9%
30 17
 
2.9%
Other values (61) 341
58.5%
2023-12-12T11:48:31.811424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 318
26.5%
2 176
14.7%
4 152
12.7%
1 121
 
10.1%
6 117
 
9.8%
7 86
 
7.2%
5 84
 
7.0%
0 61
 
5.1%
8 41
 
3.4%
9 32
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1188
99.0%
Math Symbol 12
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 318
26.8%
2 176
14.8%
4 152
12.8%
1 121
 
10.2%
6 117
 
9.8%
7 86
 
7.2%
5 84
 
7.1%
0 61
 
5.1%
8 41
 
3.5%
9 32
 
2.7%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1200
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 318
26.5%
2 176
14.7%
4 152
12.7%
1 121
 
10.1%
6 117
 
9.8%
7 86
 
7.2%
5 84
 
7.0%
0 61
 
5.1%
8 41
 
3.4%
9 32
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 318
26.5%
2 176
14.7%
4 152
12.7%
1 121
 
10.1%
6 117
 
9.8%
7 86
 
7.2%
5 84
 
7.0%
0 61
 
5.1%
8 41
 
3.4%
9 32
 
2.7%

재해위험도평가_등급
Categorical

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
B
342 
C
107 
D
89 
A
43 
E
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
B 342
58.7%
C 107
 
18.4%
D 89
 
15.3%
A 43
 
7.4%
E 2
 
0.3%

Length

2023-12-12T11:48:31.959502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:32.105102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b 342
58.7%
c 107
 
18.4%
d 89
 
15.3%
a 43
 
7.4%
e 2
 
0.3%

붕괴위험지역_지정여부
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
부
452 
여
131 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부 452
77.5%
여 131
 
22.5%

Length

2023-12-12T11:48:32.246557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:32.361236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부 452
77.5%
여 131
 
22.5%

붕괴위험지역_중기계획 수립여부
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
부
404 
여
179 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부 404
69.3%
여 179
30.7%

Length

2023-12-12T11:48:32.470492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:32.572006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부 404
69.3%
여 179
30.7%

붕괴위험지역_정비 사업 계획 수립 여부
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
부
422 
여
161 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부
2nd row부
3rd row여
4th row부
5th row부

Common Values

ValueCountFrequency (%)
부 422
72.4%
여 161
 
27.6%

Length

2023-12-12T11:48:32.672077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:32.763772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부 422
72.4%
여 161
 
27.6%

붕괴위험지역_정비사업 실시여부
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
부
481 
여
102 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여
2nd row부
3rd row여
4th row여
5th row여

Common Values

ValueCountFrequency (%)
부 481
82.5%
여 102
 
17.5%

Length

2023-12-12T11:48:32.859327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:32.975112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부 481
82.5%
여 102
 
17.5%

붕괴위험지역_지정고시일
Date

MISSING 

Distinct36
Distinct (%)31.6%
Missing469
Missing (%)80.4%
Memory size4.7 KiB
Minimum2009-11-10 00:00:00
Maximum2021-10-05 00:00:00
2023-12-12T11:48:33.079799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:33.217927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)

붕괴위험지역_상시계측현황
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
해당없음
567 
운영중
 
15
설치예정
 
1

Length

Max length4
Median length4
Mean length3.974271
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
해당없음 567
97.3%
운영중 15
 
2.6%
설치예정 1
 
0.2%

Length

2023-12-12T11:48:33.357253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:33.449233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 567
97.3%
운영중 15
 
2.6%
설치예정 1
 
0.2%

붕괴위험지역_주민대피 관리기준 제정여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
부
527 
여
56 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부 527
90.4%
여 56
 
9.6%

Length

2023-12-12T11:48:33.557621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:33.651078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부 527
90.4%
여 56
 
9.6%

붕괴위험지역_지정해제일
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
해당없음
545 
미해제
 
37
여
 
1

Length

Max length4
Median length4
Mean length3.9313894
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
해당없음 545
93.5%
미해제 37
 
6.3%
여 1
 
0.2%

Length

2023-12-12T11:48:33.809605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:33.913660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 545
93.5%
미해제 37
 
6.3%
여 1
 
0.2%

기타_과거사고 발생현황
Categorical

IMBALANCE 

Distinct9
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
해당없음
552 
<NA>
 
19
"2012 태풍'산바' 2016 집중호우"
 
5
재산(50백만원)
 
2
낙석발생
 
1
Other values (4)
 
4

Length

Max length23
Median length4
Mean length4.2555746
Min length4

Unique

Unique5 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
해당없음 552
94.7%
<NA> 19
 
3.3%
"2012 태풍'산바' 2016 집중호우" 5
 
0.9%
재산(50백만원) 2
 
0.3%
낙석발생 1
 
0.2%
재산(250백만원) 1
 
0.2%
재산(9백만원) 1
 
0.2%
2012 태풍'산바' 2016 집중호우 1
 
0.2%
2012 태풍 산바 2016 집중호우 1
 
0.2%

Length

2023-12-12T11:48:34.058915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:34.225949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 552
91.2%
na 19
 
3.1%
2012 7
 
1.2%
2016 7
 
1.2%
집중호우 7
 
1.2%
태풍'산바 6
 
1.0%
재산(50백만원 2
 
0.3%
낙석발생 1
 
0.2%
재산(250백만원 1
 
0.2%
재산(9백만원 1
 
0.2%
Other values (2) 2
 
0.3%

기타_산마루측구여부
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
부
497 
여
86 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부 497
85.2%
여 86
 
14.8%

Length

2023-12-12T11:48:34.354644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:34.472226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부 497
85.2%
여 86
 
14.8%

기타_비고
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
<NA>
577 
일반국도
 
5
군도
 
1

Length

Max length4
Median length4
Mean length3.9965695
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 577
99.0%
일반국도 5
 
0.9%
군도 1
 
0.2%

Length

2023-12-12T11:48:34.661031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:34.801892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 577
99.0%
일반국도 5
 
0.9%
군도 1
 
0.2%

Sample

지구명위치_시도위치_시군구위치_읍면위치_리동위치_지번용도_종류용도_기타상세분류_유형분류_구조자연 또는 인공종류제원_길이_미터제원_높이_미터제원_평균경사_도관리기관관리기관 세부현황관리기관_소유자나 점유자 혹은 관계인관리기관_공공 또는 민간재해위험도평가_점수재해위험도평가_등급붕괴위험지역_지정여부붕괴위험지역_중기계획 수립여부붕괴위험지역_정비 사업 계획 수립 여부붕괴위험지역_정비사업 실시여부붕괴위험지역_지정고시일붕괴위험지역_상시계측현황붕괴위험지역_주민대피 관리기준 제정여부붕괴위험지역_지정해제일기타_과거사고 발생현황기타_산마루측구여부기타_비고
0관덕경남도통영시도산면관덕리산278번지기타토사인공토사인공4005045.0지자체지자체통영시공공70D여여부여2009-11-10해당없음부미해제해당없음부<NA>
1덕포구집경남도통영시광도면덕포리산129번지기타암반인공암반인공4005070.0지자체기업SPP조선㈜공공70D여여부부2009-11-10해당없음부미해제해당없음부<NA>
2한산죽전경남도통영시한산면하소리499-5번지도로토사인공토사인공201575.0지자체지자체통영시공공70D여여여여2009-11-10해당없음부미해제해당없음부<NA>
3비진경남도통영시한산면비진리147번지도로옹벽인공옹벽인공501580.0지자체지자체통영시공공61D여여부여2016-08-31해당없음부미해제해당없음부<NA>
4서피랑경남도통영시<NA>서호동11-1번지주택토사인공토사인공1001570.0지자체지자체통영시공공70D여여부여2009-11-10해당없음부미해제해당없음부<NA>
5망일봉경남도통영시<NA>정량동816-1번지도로토사인공토사인공904050.0지자체지자체통영시공공76D여여부여2016-11-08해당없음부미해제해당없음여<NA>
6노산공원2경남도사천시<NA>서금동100-2번지공원<NA>인공복합인공100151.0지자체지자체재난안전과공공65D여여여여2016-12-02해당없음여미해제해당없음여<NA>
7선진공원2경남도사천시용현면선진리994번지주택<NA>인공복합인공1201275.0지자체지자체재난안전과공공68D여여여여2016-12-02해당없음여미해제해당없음부<NA>
8통창공원경남도사천시<NA>동금동236-1번지공원<NA>인공복합인공1202048.0지자체지자체재난안전과공공72D여여여여2020-02-20해당없음부미해제해당없음부<NA>
9청널공원경남도사천시<NA>서동353번지공원<NA>인공복합인공14030<NA>지자체지자체재난안전과공공61D여여부부2021-02-04해당없음부미해제해당없음부<NA>
지구명위치_시도위치_시군구위치_읍면위치_리동위치_지번용도_종류용도_기타상세분류_유형분류_구조자연 또는 인공종류제원_길이_미터제원_높이_미터제원_평균경사_도관리기관관리기관 세부현황관리기관_소유자나 점유자 혹은 관계인관리기관_공공 또는 민간재해위험도평가_점수재해위험도평가_등급붕괴위험지역_지정여부붕괴위험지역_중기계획 수립여부붕괴위험지역_정비 사업 계획 수립 여부붕괴위험지역_정비사업 실시여부붕괴위험지역_지정고시일붕괴위험지역_상시계측현황붕괴위험지역_주민대피 관리기준 제정여부붕괴위험지역_지정해제일기타_과거사고 발생현황기타_산마루측구여부기타_비고
573송계지구경남도거창군북상면소정리산 160번지공원공원자연 또는 산지암반자연352144.0국립공원공단<NA>덕유산국립공원사무소공공42C부여여여<NA>운영중부해당없음해당없음부<NA>
574송계지구경남도거창군북상면소정리산 160번지공원공원자연 또는 산지복합자연401570.0국립공원공단<NA>덕유산국립공원사무소공공51C부여여여<NA>운영중부해당없음해당없음부<NA>
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