Overview

Dataset statistics

Number of variables24
Number of observations141
Missing cells267
Missing cells (%)7.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.4 KiB
Average record size in memory205.9 B

Variable types

Numeric12
Text6
Categorical4
DateTime1
Unsupported1

Dataset

Description국가 수문기상 공동활용 재난안전 시스템 내 국토교통부 국토지리정보원 공간정보공동활용시스템 내 자연재해위험지구 테이블 입니다.
Author국토교통부 국토지리정보원
URLhttps://www.data.go.kr/data/15123134/fileData.do

Alerts

기타주소 has 125 (88.7%) missing valuesMissing
널값 has 141 (100.0%) missing valuesMissing
공간정보일렬번호 has unique valuesUnique
자연재해위험지구아이디 has unique valuesUnique
피해예상지역위치 has unique valuesUnique
TM좌표X has unique valuesUnique
WGS좌표X축 has unique valuesUnique
WGS좌표Y축 has unique valuesUnique
TM좌표Y has unique valuesUnique
공간정보 has unique valuesUnique
널값 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지정면적 has 4 (2.8%) zerosZeros

Reproduction

Analysis started2023-12-12 17:11:30.853857
Analysis finished2023-12-12 17:11:31.482110
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보일렬번호
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71
Minimum1
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:31.547787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q136
median71
Q3106
95-th percentile134
Maximum141
Range140
Interquartile range (IQR)70

Descriptive statistics

Standard deviation40.847277
Coefficient of variation (CV)0.57531375
Kurtosis-1.2
Mean71
Median Absolute Deviation (MAD)35
Skewness0
Sum10011
Variance1668.5
MonotonicityStrictly increasing
2023-12-13T02:11:31.707919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
98 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
99 1
 
0.7%
90 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%

자연재해위험지구아이디
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.02837
Minimum1
Maximum318
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:31.851379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16
Q144
median117
Q3176
95-th percentile240
Maximum318
Range317
Interquartile range (IQR)132

Descriptive statistics

Standard deviation82.74651
Coefficient of variation (CV)0.68939127
Kurtosis-0.8963424
Mean120.02837
Median Absolute Deviation (MAD)66
Skewness0.38015972
Sum16924
Variance6846.9849
MonotonicityNot monotonic
2023-12-13T02:11:32.030511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201 1
 
0.7%
29 1
 
0.7%
48 1
 
0.7%
46 1
 
0.7%
47 1
 
0.7%
44 1
 
0.7%
60 1
 
0.7%
45 1
 
0.7%
28 1
 
0.7%
278 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
8 1
0.7%
9 1
0.7%
15 1
0.7%
16 1
0.7%
17 1
0.7%
18 1
0.7%
ValueCountFrequency (%)
318 1
0.7%
317 1
0.7%
316 1
0.7%
280 1
0.7%
279 1
0.7%
278 1
0.7%
277 1
0.7%
240 1
0.7%
239 1
0.7%
238 1
0.7%

지구명
Text

Distinct140
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T02:11:32.393375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length2.5460993
Min length2

Characters and Unicode

Total characters359
Distinct characters152
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)98.6%

Sample

1st row양하
2nd row학림
3rd row육동
4th row가학
5th row축정
ValueCountFrequency (%)
입석 2
 
1.4%
성황골 1
 
0.7%
말죽거리근린공원 1
 
0.7%
배다리중앙시장 1
 
0.7%
주진 1
 
0.7%
중리 1
 
0.7%
석문교위 1
 
0.7%
뱃말 1
 
0.7%
절골 1
 
0.7%
하리 1
 
0.7%
Other values (130) 130
92.2%
2023-12-13T02:11:32.959455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 11
 
3.1%
리 9
 
2.5%
1 8
 
2.2%
신 7
 
1.9%
2 7
 
1.9%
호 7
 
1.9%
곡 6
 
1.7%
선 6
 
1.7%
성 6
 
1.7%
석 6
 
1.7%
Other values (142) 286
79.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 329
91.6%
Decimal Number 24
 
6.7%
Open Punctuation 3
 
0.8%
Close Punctuation 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 11
 
3.3%
리 9
 
2.7%
신 7
 
2.1%
호 7
 
2.1%
곡 6
 
1.8%
선 6
 
1.8%
성 6
 
1.8%
석 6
 
1.8%
서 6
 
1.8%
장 5
 
1.5%
Other values (132) 260
79.0%
Decimal Number
ValueCountFrequency (%)
1 8
33.3%
2 7
29.2%
0 3
 
12.5%
3 2
 
8.3%
4 1
 
4.2%
5 1
 
4.2%
9 1
 
4.2%
7 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 329
91.6%
Common 30
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 11
 
3.3%
리 9
 
2.7%
신 7
 
2.1%
호 7
 
2.1%
곡 6
 
1.8%
선 6
 
1.8%
성 6
 
1.8%
석 6
 
1.8%
서 6
 
1.8%
장 5
 
1.5%
Other values (132) 260
79.0%
Common
ValueCountFrequency (%)
1 8
26.7%
2 7
23.3%
0 3
 
10.0%
( 3
 
10.0%
) 3
 
10.0%
3 2
 
6.7%
4 1
 
3.3%
5 1
 
3.3%
9 1
 
3.3%
7 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 329
91.6%
ASCII 30
 
8.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 11
 
3.3%
리 9
 
2.7%
신 7
 
2.1%
호 7
 
2.1%
곡 6
 
1.8%
선 6
 
1.8%
성 6
 
1.8%
석 6
 
1.8%
서 6
 
1.8%
장 5
 
1.5%
Other values (132) 260
79.0%
ASCII
ValueCountFrequency (%)
1 8
26.7%
2 7
23.3%
0 3
 
10.0%
( 3
 
10.0%
) 3
 
10.0%
3 2
 
6.7%
4 1
 
3.3%
5 1
 
3.3%
9 1
 
3.3%
7 1
 
3.3%

피해예상지역위치
Text

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T02:11:33.359881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.546099
Min length13

Characters and Unicode

Total characters2615
Distinct characters170
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)100.0%

Sample

1st row전남 완도 노화읍 신양리 885-1
2nd row전남 완도 완도읍 가용리 3-27
3rd row전남 완도 금당면 차우리 산201-3
4th row전남 완도 금당면 가학리 산92-2
5th row전남 고흥 봉래면 신금리 1000-15
ValueCountFrequency (%)
강원 34
 
5.0%
전남 33
 
4.9%
경북 17
 
2.5%
홍천 14
 
2.1%
문경 13
 
1.9%
전라북도 13
 
1.9%
고흥 11
 
1.6%
충북 7
 
1.0%
임실군 6
 
0.9%
충청북도 6
 
0.9%
Other values (406) 524
77.3%
2023-12-13T02:11:33.923362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
546
 
20.9%
리 123
 
4.7%
1 105
 
4.0%
면 90
 
3.4%
- 82
 
3.1%
3 61
 
2.3%
전 58
 
2.2%
북 57
 
2.2%
남 55
 
2.1%
2 55
 
2.1%
Other values (160) 1383
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1469
56.2%
Space Separator 546
 
20.9%
Decimal Number 518
 
19.8%
Dash Punctuation 82
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 123
 
8.4%
면 90
 
6.1%
전 58
 
3.9%
북 57
 
3.9%
남 55
 
3.7%
원 47
 
3.2%
강 45
 
3.1%
경 45
 
3.1%
도 43
 
2.9%
산 37
 
2.5%
Other values (148) 869
59.2%
Decimal Number
ValueCountFrequency (%)
1 105
20.3%
3 61
11.8%
2 55
10.6%
4 55
10.6%
0 50
9.7%
5 50
9.7%
7 39
 
7.5%
6 39
 
7.5%
8 33
 
6.4%
9 31
 
6.0%
Space Separator
ValueCountFrequency (%)
546
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1469
56.2%
Common 1146
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 123
 
8.4%
면 90
 
6.1%
전 58
 
3.9%
북 57
 
3.9%
남 55
 
3.7%
원 47
 
3.2%
강 45
 
3.1%
경 45
 
3.1%
도 43
 
2.9%
산 37
 
2.5%
Other values (148) 869
59.2%
Common
ValueCountFrequency (%)
546
47.6%
1 105
 
9.2%
- 82
 
7.2%
3 61
 
5.3%
2 55
 
4.8%
4 55
 
4.8%
0 50
 
4.4%
5 50
 
4.4%
7 39
 
3.4%
6 39
 
3.4%
Other values (2) 64
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1469
56.2%
ASCII 1146
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
546
47.6%
1 105
 
9.2%
- 82
 
7.2%
3 61
 
5.3%
2 55
 
4.8%
4 55
 
4.8%
0 50
 
4.4%
5 50
 
4.4%
7 39
 
3.4%
6 39
 
3.4%
Other values (2) 64
 
5.6%
Hangul
ValueCountFrequency (%)
리 123
 
8.4%
면 90
 
6.1%
전 58
 
3.9%
북 57
 
3.9%
남 55
 
3.7%
원 47
 
3.2%
강 45
 
3.1%
경 45
 
3.1%
도 43
 
2.9%
산 37
 
2.5%
Other values (148) 869
59.2%

기타주소
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing125
Missing (%)88.7%
Memory size1.2 KiB
2023-12-13T02:11:34.150738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7
Min length3

Characters and Unicode

Total characters112
Distinct characters61
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

Unique16 ?
Unique (%)100.0%

Sample

1st row정비소
2nd row마을회관
3rd row사내1길
4th row충청북도자연학습원
5th row송면의용소방대
ValueCountFrequency (%)
정비소 1
 
4.5%
마을회관 1
 
4.5%
7 1
 
4.5%
석탑길 1
 
4.5%
16 1
 
4.5%
기와집길3번길 1
 
4.5%
강변길3 1
 
4.5%
1481 1
 
4.5%
오대천로 1
 
4.5%
24 1
 
4.5%
Other values (12) 12
54.5%
2023-12-13T02:11:34.532440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 9
 
8.0%
길 9
 
8.0%
( 9
 
8.0%
6
 
5.4%
1 6
 
5.4%
4 3
 
2.7%
석 3
 
2.7%
흥 2
 
1.8%
도 2
 
1.8%
전 2
 
1.8%
Other values (51) 61
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66
58.9%
Decimal Number 19
 
17.0%
Close Punctuation 9
 
8.0%
Open Punctuation 9
 
8.0%
Space Separator 6
 
5.4%
Dash Punctuation 2
 
1.8%
Math Symbol 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 9
 
13.6%
석 3
 
4.5%
흥 2
 
3.0%
도 2
 
3.0%
전 2
 
3.0%
대 2
 
3.0%
강 2
 
3.0%
비 2
 
3.0%
로 2
 
3.0%
소 2
 
3.0%
Other values (38) 38
57.6%
Decimal Number
ValueCountFrequency (%)
1 6
31.6%
4 3
15.8%
3 2
 
10.5%
6 2
 
10.5%
7 2
 
10.5%
2 2
 
10.5%
8 1
 
5.3%
9 1
 
5.3%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66
58.9%
Common 46
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 9
 
13.6%
석 3
 
4.5%
흥 2
 
3.0%
도 2
 
3.0%
전 2
 
3.0%
대 2
 
3.0%
강 2
 
3.0%
비 2
 
3.0%
로 2
 
3.0%
소 2
 
3.0%
Other values (38) 38
57.6%
Common
ValueCountFrequency (%)
) 9
19.6%
( 9
19.6%
6
13.0%
1 6
13.0%
4 3
 
6.5%
3 2
 
4.3%
6 2
 
4.3%
7 2
 
4.3%
- 2
 
4.3%
2 2
 
4.3%
Other values (3) 3
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66
58.9%
ASCII 46
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 9
19.6%
( 9
19.6%
6
13.0%
1 6
13.0%
4 3
 
6.5%
3 2
 
4.3%
6 2
 
4.3%
7 2
 
4.3%
- 2
 
4.3%
2 2
 
4.3%
Other values (3) 3
 
6.5%
Hangul
ValueCountFrequency (%)
길 9
 
13.6%
석 3
 
4.5%
흥 2
 
3.0%
도 2
 
3.0%
전 2
 
3.0%
대 2
 
3.0%
강 2
 
3.0%
비 2
 
3.0%
로 2
 
3.0%
소 2
 
3.0%
Other values (38) 38
57.6%

유형별
Categorical

Distinct6
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
침수위험
61 
붕괴위험
36 
유실위험
31 
취약방재
10 
고립위험
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row취약방재
2nd row붕괴위험
3rd row붕괴위험
4th row붕괴위험
5th row붕괴위험

Common Values

ValueCountFrequency (%)
침수위험 61
43.3%
붕괴위험 36
25.5%
유실위험 31
22.0%
취약방재 10
 
7.1%
고립위험 2
 
1.4%
해일위험 1
 
0.7%

Length

2023-12-13T02:11:34.707988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:11:34.842695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
침수위험 61
43.3%
붕괴위험 36
25.5%
유실위험 31
22.0%
취약방재 10
 
7.1%
고립위험 2
 
1.4%
해일위험 1
 
0.7%

위험등급
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
나
58 
가
43 
다
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row다
2nd row나
3rd row나
4th row나
5th row가

Common Values

ValueCountFrequency (%)
나 58
41.1%
가 43
30.5%
다 40
28.4%

Length

2023-12-13T02:11:34.983640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:11:35.083330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나 58
41.1%
가 43
30.5%
다 40
28.4%

지정면적
Real number (ℝ)

ZEROS 

Distinct87
Distinct (%)61.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.20515113
Minimum0
Maximum4.125
Zeros4
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:35.197068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00054
Q10.0114
median0.05
Q30.191
95-th percentile0.83
Maximum4.125
Range4.125
Interquartile range (IQR)0.1796

Descriptive statistics

Standard deviation0.45772704
Coefficient of variation (CV)2.2311699
Kurtosis40.794944
Mean0.20515113
Median Absolute Deviation (MAD)0.047
Skewness5.5668287
Sum28.92631
Variance0.20951404
MonotonicityNot monotonic
2023-12-13T02:11:35.327803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02 8
 
5.7%
0.01 8
 
5.7%
0.15 8
 
5.7%
0.14 6
 
4.3%
0.03 4
 
2.8%
0.0 4
 
2.8%
0.05 4
 
2.8%
0.04 4
 
2.8%
0.003 3
 
2.1%
0.06 3
 
2.1%
Other values (77) 89
63.1%
ValueCountFrequency (%)
0.0 4
2.8%
0.0002 1
 
0.7%
0.00032 1
 
0.7%
0.00036 1
 
0.7%
0.00054 1
 
0.7%
0.00099 1
 
0.7%
0.002 1
 
0.7%
0.0024 1
 
0.7%
0.0026 1
 
0.7%
0.003 3
2.1%
ValueCountFrequency (%)
4.125 1
0.7%
2.24 1
0.7%
1.248 1
0.7%
1.23 1
0.7%
1.2 1
0.7%
1.1 1
0.7%
1.0 1
0.7%
0.83 1
0.7%
0.79 1
0.7%
0.738 1
0.7%

지정년도
Real number (ℝ)

Distinct16
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2008.1348
Minimum1993
Maximum2014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:35.435453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1993
5-th percentile1999
Q12006
median2010
Q32010
95-th percentile2013
Maximum2014
Range21
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.8493411
Coefficient of variation (CV)0.0019168739
Kurtosis3.3401736
Mean2008.1348
Median Absolute Deviation (MAD)2
Skewness-1.6689551
Sum283147
Variance14.817427
MonotonicityNot monotonic
2023-12-13T02:11:35.545534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2010 59
41.8%
2006 30
21.3%
2011 9
 
6.4%
2012 8
 
5.7%
2007 7
 
5.0%
2013 7
 
5.0%
1996 5
 
3.5%
2003 4
 
2.8%
2005 2
 
1.4%
2004 2
 
1.4%
Other values (6) 8
 
5.7%
ValueCountFrequency (%)
1993 1
 
0.7%
1996 5
 
3.5%
1999 2
 
1.4%
2002 1
 
0.7%
2003 4
 
2.8%
2004 2
 
1.4%
2005 2
 
1.4%
2006 30
21.3%
2007 7
 
5.0%
2008 2
 
1.4%
ValueCountFrequency (%)
2014 1
 
0.7%
2013 7
 
5.0%
2012 8
 
5.7%
2011 9
 
6.4%
2010 59
41.8%
2009 1
 
0.7%
2008 2
 
1.4%
2007 7
 
5.0%
2006 30
21.3%
2005 2
 
1.4%

지정일자
Date

Distinct64
Distinct (%)45.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1993-10-08 00:00:00
Maximum2014-03-27 00:00:00
2023-12-13T02:11:35.661678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:35.793350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시설명
Text

Distinct97
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T02:11:36.052745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length3
Mean length3.7588652
Min length2

Characters and Unicode

Total characters530
Distinct characters147
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

Unique86 ?
Unique (%)61.0%

Sample

1st row저수지
2nd row급경사지
3rd row급경사지
4th row급경사지
5th row급경사지
ValueCountFrequency (%)
급경사지 25
 
17.7%
도로사면 5
 
3.5%
배수로 4
 
2.8%
죽계천 4
 
2.8%
이주대책 3
 
2.1%
보청천 3
 
2.1%
배수펌프장 3
 
2.1%
영평천 2
 
1.4%
시목천 2
 
1.4%
공원(절개지 2
 
1.4%
Other values (87) 88
62.4%
2023-12-13T02:11:36.461265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 70
 
13.2%
지 35
 
6.6%
사 32
 
6.0%
경 26
 
4.9%
급 25
 
4.7%
교 16
 
3.0%
수 12
 
2.3%
도 10
 
1.9%
로 10
 
1.9%
대 8
 
1.5%
Other values (137) 286
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 494
93.2%
Decimal Number 18
 
3.4%
Close Punctuation 4
 
0.8%
Open Punctuation 4
 
0.8%
Other Punctuation 4
 
0.8%
Math Symbol 2
 
0.4%
Lowercase Letter 2
 
0.4%
Uppercase Letter 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 70
 
14.2%
지 35
 
7.1%
사 32
 
6.5%
경 26
 
5.3%
급 25
 
5.1%
교 16
 
3.2%
수 12
 
2.4%
도 10
 
2.0%
로 10
 
2.0%
대 8
 
1.6%
Other values (121) 250
50.6%
Decimal Number
ValueCountFrequency (%)
1 4
22.2%
3 3
16.7%
0 3
16.7%
9 3
16.7%
6 2
11.1%
2 1
 
5.6%
5 1
 
5.6%
7 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
, 1
 
25.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
L 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 494
93.2%
Common 32
 
6.0%
Latin 4
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 70
 
14.2%
지 35
 
7.1%
사 32
 
6.5%
경 26
 
5.3%
급 25
 
5.1%
교 16
 
3.2%
수 12
 
2.4%
도 10
 
2.0%
로 10
 
2.0%
대 8
 
1.6%
Other values (121) 250
50.6%
Common
ValueCountFrequency (%)
1 4
12.5%
) 4
12.5%
( 4
12.5%
3 3
9.4%
. 3
9.4%
0 3
9.4%
9 3
9.4%
= 2
6.2%
6 2
6.2%
, 1
 
3.1%
Other values (3) 3
9.4%
Latin
ValueCountFrequency (%)
m 2
50.0%
B 1
25.0%
L 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 494
93.2%
ASCII 36
 
6.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 70
 
14.2%
지 35
 
7.1%
사 32
 
6.5%
경 26
 
5.3%
급 25
 
5.1%
교 16
 
3.2%
수 12
 
2.4%
도 10
 
2.0%
로 10
 
2.0%
대 8
 
1.6%
Other values (121) 250
50.6%
ASCII
ValueCountFrequency (%)
1 4
11.1%
) 4
11.1%
( 4
11.1%
3 3
8.3%
. 3
8.3%
0 3
8.3%
9 3
8.3%
= 2
 
5.6%
6 2
 
5.6%
m 2
 
5.6%
Other values (6) 6
16.7%

시설등급
Categorical

Distinct12
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
지방하천
50 
급경사지
32 
소하천
20 
교량
16 
도시방재시설
10 
Other values (7)
13 

Length

Max length6
Median length4
Mean length3.7304965
Min length2

Unique

Unique4 ?
Unique (%)2.8%

Sample

1st row저수지
2nd row급경사지
3rd row급경사지
4th row급경사지
5th row급경사지

Common Values

ValueCountFrequency (%)
지방하천 50
35.5%
급경사지 32
22.7%
소하천 20
 
14.2%
교량 16
 
11.3%
도시방재시설 10
 
7.1%
저수지 4
 
2.8%
이주대책 3
 
2.1%
지방도 2
 
1.4%
소규모시설 1
 
0.7%
저지대 1
 
0.7%
Other values (2) 2
 
1.4%

Length

2023-12-13T02:11:36.608425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지방하천 50
35.5%
급경사지 32
22.7%
소하천 20
 
14.2%
교량 16
 
11.3%
도시방재시설 10
 
7.1%
저수지 4
 
2.8%
이주대책 3
 
2.1%
지방도 2
 
1.4%
소규모시설 1
 
0.7%
저지대 1
 
0.7%
Other values (2) 2
 
1.4%

사업시작
Real number (ℝ)

Distinct13
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.6596
Minimum1997
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:36.722312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1997
5-th percentile2010
Q12013
median2014
Q32015
95-th percentile2016
Maximum2017
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.7847282
Coefficient of variation (CV)0.0013829191
Kurtosis17.598887
Mean2013.6596
Median Absolute Deviation (MAD)1
Skewness-3.4752837
Sum283926
Variance7.7547112
MonotonicityNot monotonic
2023-12-13T02:11:36.847562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2014 36
25.5%
2015 26
18.4%
2016 25
17.7%
2013 23
16.3%
2012 14
 
9.9%
2011 5
 
3.5%
2017 4
 
2.8%
2010 2
 
1.4%
1997 2
 
1.4%
2005 1
 
0.7%
Other values (3) 3
 
2.1%
ValueCountFrequency (%)
1997 2
 
1.4%
2005 1
 
0.7%
2006 1
 
0.7%
2008 1
 
0.7%
2009 1
 
0.7%
2010 2
 
1.4%
2011 5
 
3.5%
2012 14
 
9.9%
2013 23
16.3%
2014 36
25.5%
ValueCountFrequency (%)
2017 4
 
2.8%
2016 25
17.7%
2015 26
18.4%
2014 36
25.5%
2013 23
16.3%
2012 14
 
9.9%
2011 5
 
3.5%
2010 2
 
1.4%
2009 1
 
0.7%
2008 1
 
0.7%

사업종료
Real number (ℝ)

Distinct9
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.1418
Minimum2012
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:36.966184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12014
median2015
Q32016
95-th percentile2018
Maximum2020
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4860377
Coefficient of variation (CV)0.00073743577
Kurtosis0.97941755
Mean2015.1418
Median Absolute Deviation (MAD)1
Skewness0.71987341
Sum284135
Variance2.208308
MonotonicityNot monotonic
2023-12-13T02:11:37.105252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2015 52
36.9%
2014 29
20.6%
2016 27
19.1%
2013 12
 
8.5%
2018 8
 
5.7%
2017 5
 
3.5%
2019 4
 
2.8%
2012 3
 
2.1%
2020 1
 
0.7%
ValueCountFrequency (%)
2012 3
 
2.1%
2013 12
 
8.5%
2014 29
20.6%
2015 52
36.9%
2016 27
19.1%
2017 5
 
3.5%
2018 8
 
5.7%
2019 4
 
2.8%
2020 1
 
0.7%
ValueCountFrequency (%)
2020 1
 
0.7%
2019 4
 
2.8%
2018 8
 
5.7%
2017 5
 
3.5%
2016 27
19.1%
2015 52
36.9%
2014 29
20.6%
2013 12
 
8.5%
2012 3
 
2.1%

사업내용
Text

Distinct134
Distinct (%)95.7%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
2023-12-13T02:11:37.428372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length31.5
Mean length19.714286
Min length5

Characters and Unicode

Total characters2760
Distinct characters175
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)92.9%

Sample

1st row그라우팅,L=0.15km
2nd row옹벽L=0.17km배수로정비L=0.17km안전시설물 1식
3rd row옹벽L=0.5km안전시설물 1식
4th row옹벽L=1.0km안전시설물 1식
5th row옹벽 L=180m가옥보상 4가구
ValueCountFrequency (%)
하천정비 32
 
7.1%
교량 13
 
2.9%
1식 12
 
2.7%
2개소 10
 
2.2%
및 9
 
2.0%
1개소 9
 
2.0%
교량개체 7
 
1.6%
배수펌프장 6
 
1.3%
b=10m축제공 6
 
1.3%
l=200m 6
 
1.3%
Other values (269) 339
75.5%
2023-12-13T02:11:37.898912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
311
 
11.3%
0 193
 
7.0%
m 140
 
5.1%
1 133
 
4.8%
= 117
 
4.2%
L 92
 
3.3%
, 86
 
3.1%
2 71
 
2.6%
개 69
 
2.5%
정 64
 
2.3%
Other values (165) 1484
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1187
43.0%
Decimal Number 592
21.4%
Space Separator 311
 
11.3%
Lowercase Letter 181
 
6.6%
Other Punctuation 162
 
5.9%
Uppercase Letter 150
 
5.4%
Math Symbol 120
 
4.3%
Other Symbol 24
 
0.9%
Close Punctuation 16
 
0.6%
Open Punctuation 16
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 69
 
5.8%
정 64
 
5.4%
비 62
 
5.2%
교 47
 
4.0%
소 46
 
3.9%
량 46
 
3.9%
보 39
 
3.3%
하 39
 
3.3%
수 37
 
3.1%
천 36
 
3.0%
Other values (127) 702
59.1%
Uppercase Letter
ValueCountFrequency (%)
L 92
61.3%
A 14
 
9.3%
B 14
 
9.3%
H 7
 
4.7%
E 6
 
4.0%
O 6
 
4.0%
X 6
 
4.0%
U 1
 
0.7%
C 1
 
0.7%
P 1
 
0.7%
Other values (2) 2
 
1.3%
Decimal Number
ValueCountFrequency (%)
0 193
32.6%
1 133
22.5%
2 71
 
12.0%
5 50
 
8.4%
3 42
 
7.1%
4 35
 
5.9%
6 23
 
3.9%
8 19
 
3.2%
7 16
 
2.7%
9 10
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 86
53.1%
. 64
39.5%
@ 5
 
3.1%
: 4
 
2.5%
* 3
 
1.9%
Other Symbol
ValueCountFrequency (%)
㎡ 12
50.0%
㎞ 10
41.7%
㎥ 2
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
m 140
77.3%
k 41
 
22.7%
Math Symbol
ValueCountFrequency (%)
= 117
97.5%
× 3
 
2.5%
Space Separator
ValueCountFrequency (%)
311
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1242
45.0%
Hangul 1187
43.0%
Latin 331
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 69
 
5.8%
정 64
 
5.4%
비 62
 
5.2%
교 47
 
4.0%
소 46
 
3.9%
량 46
 
3.9%
보 39
 
3.3%
하 39
 
3.3%
수 37
 
3.1%
천 36
 
3.0%
Other values (127) 702
59.1%
Common
ValueCountFrequency (%)
311
25.0%
0 193
15.5%
1 133
10.7%
= 117
 
9.4%
, 86
 
6.9%
2 71
 
5.7%
. 64
 
5.2%
5 50
 
4.0%
3 42
 
3.4%
4 35
 
2.8%
Other values (14) 140
11.3%
Latin
ValueCountFrequency (%)
m 140
42.3%
L 92
27.8%
k 41
 
12.4%
A 14
 
4.2%
B 14
 
4.2%
H 7
 
2.1%
E 6
 
1.8%
O 6
 
1.8%
X 6
 
1.8%
U 1
 
0.3%
Other values (4) 4
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1546
56.0%
Hangul 1187
43.0%
CJK Compat 24
 
0.9%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
311
20.1%
0 193
12.5%
m 140
9.1%
1 133
8.6%
= 117
 
7.6%
L 92
 
6.0%
, 86
 
5.6%
2 71
 
4.6%
. 64
 
4.1%
5 50
 
3.2%
Other values (24) 289
18.7%
Hangul
ValueCountFrequency (%)
개 69
 
5.8%
정 64
 
5.4%
비 62
 
5.2%
교 47
 
4.0%
소 46
 
3.9%
량 46
 
3.9%
보 39
 
3.3%
하 39
 
3.3%
수 37
 
3.1%
천 36
 
3.0%
Other values (127) 702
59.1%
CJK Compat
ValueCountFrequency (%)
㎡ 12
50.0%
㎞ 10
41.7%
㎥ 2
 
8.3%
None
ValueCountFrequency (%)
× 3
100.0%

사업비
Real number (ℝ)

Distinct100
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5624.6809
Minimum300
Maximum72005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:38.048041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile1000
Q11798
median3000
Q36640
95-th percentile15800
Maximum72005
Range71705
Interquartile range (IQR)4842

Descriptive statistics

Standard deviation8384.8416
Coefficient of variation (CV)1.4907231
Kurtosis34.66908
Mean5624.6809
Median Absolute Deviation (MAD)1600
Skewness5.2021773
Sum793080
Variance70305569
MonotonicityNot monotonic
2023-12-13T02:11:38.228315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 11
 
7.8%
1500 7
 
5.0%
1100 5
 
3.5%
1000 4
 
2.8%
5000 3
 
2.1%
1300 3
 
2.1%
3300 3
 
2.1%
2500 3
 
2.1%
3500 3
 
2.1%
1400 2
 
1.4%
Other values (90) 97
68.8%
ValueCountFrequency (%)
300 1
 
0.7%
500 2
 
1.4%
600 1
 
0.7%
1000 4
2.8%
1041 1
 
0.7%
1098 1
 
0.7%
1100 5
3.5%
1200 1
 
0.7%
1300 3
2.1%
1388 1
 
0.7%
ValueCountFrequency (%)
72005 1
0.7%
53201 1
0.7%
27175 1
0.7%
24577 1
0.7%
20000 1
0.7%
17463 1
0.7%
15807 1
0.7%
15800 1
0.7%
14943 1
0.7%
14598 1
0.7%

TM좌표X
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265015.57
Minimum159060.95
Maximum387217.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:38.394609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum159060.95
5-th percentile185822.97
Q1215098.09
median265050
Q3307660.21
95-th percentile375031.26
Maximum387217.64
Range228156.7
Interquartile range (IQR)92562.121

Descriptive statistics

Standard deviation57472.286
Coefficient of variation (CV)0.21686381
Kurtosis-0.78236636
Mean265015.57
Median Absolute Deviation (MAD)47471.68
Skewness0.25000775
Sum37367196
Variance3.3030637 × 109
MonotonicityNot monotonic
2023-12-13T02:11:38.557121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
161278.71745 1
 
0.7%
381548.89664 1
 
0.7%
331228.25198 1
 
0.7%
330738.70184 1
 
0.7%
330765.9612 1
 
0.7%
325209.48871 1
 
0.7%
315297.81544 1
 
0.7%
329111.99695 1
 
0.7%
381305.77934 1
 
0.7%
382663.72804 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
159060.94594 1
0.7%
159684.25891 1
0.7%
161278.71745 1
0.7%
167897.42738 1
0.7%
168052.29343 1
0.7%
176713.53697 1
0.7%
182115.38525 1
0.7%
185822.96619 1
0.7%
187205.86363 1
0.7%
191082.82218 1
0.7%
ValueCountFrequency (%)
387217.64177 1
0.7%
384653.14968 1
0.7%
383576.63486 1
0.7%
382663.72804 1
0.7%
381548.89664 1
0.7%
381305.77934 1
0.7%
380752.72264 1
0.7%
375031.26185 1
0.7%
360584.99769 1
0.7%
353323.24469 1
0.7%

WGS좌표X축
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.73013
Minimum126.5371
Maximum129.1187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:38.701615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5371
5-th percentile126.84359
Q1127.16647
median127.72578
Q3128.2037
95-th percentile128.96155
Maximum129.1187
Range2.5816
Interquartile range (IQR)1.03723

Descriptive statistics

Standard deviation0.64793742
Coefficient of variation (CV)0.0050727063
Kurtosis-0.79131001
Mean127.73013
Median Absolute Deviation (MAD)0.54268
Skewness0.26238881
Sum18009.948
Variance0.4198229
MonotonicityNot monotonic
2023-12-13T02:11:38.866011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.57986 1
 
0.7%
129.04524 1
 
0.7%
128.47772 1
 
0.7%
128.4723 1
 
0.7%
128.47262 1
 
0.7%
128.4101 1
 
0.7%
128.29869 1
 
0.7%
128.45428 1
 
0.7%
129.04273 1
 
0.7%
129.05353 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
126.5371 1
0.7%
126.5427 1
0.7%
126.57986 1
0.7%
126.63709 1
0.7%
126.65153 1
0.7%
126.74697 1
0.7%
126.80478 1
0.7%
126.84359 1
0.7%
126.86011 1
0.7%
126.90162 1
0.7%
ValueCountFrequency (%)
129.1187 1
0.7%
129.0747 1
0.7%
129.06347 1
0.7%
129.05353 1
0.7%
129.04524 1
0.7%
129.04273 1
0.7%
129.03315 1
0.7%
128.96155 1
0.7%
128.82593 1
0.7%
128.73052 1
0.7%

WGS좌표Y축
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.391889
Minimum34.20478
Maximum38.27364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:39.359153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.20478
5-th percentile34.50193
Q135.27012
median36.67168
Q337.48416
95-th percentile37.92261
Maximum38.27364
Range4.06886
Interquartile range (IQR)2.21404

Descriptive statistics

Standard deviation1.2030497
Coefficient of variation (CV)0.033058183
Kurtosis-1.3464141
Mean36.391889
Median Absolute Deviation (MAD)1.03888
Skewness-0.29473661
Sum5131.2564
Variance1.4473287
MonotonicityNot monotonic
2023-12-13T02:11:39.562324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.20478 1
 
0.7%
37.21402 1
 
0.7%
37.17972 1
 
0.7%
37.18437 1
 
0.7%
37.18499 1
 
0.7%
37.18803 1
 
0.7%
37.19997 1
 
0.7%
37.20006 1
 
0.7%
37.22261 1
 
0.7%
37.05627 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
34.20478 1
0.7%
34.32603 1
0.7%
34.43507 1
0.7%
34.44959 1
0.7%
34.46375 1
0.7%
34.4687 1
0.7%
34.48842 1
0.7%
34.50193 1
0.7%
34.5179 1
0.7%
34.52674 1
0.7%
ValueCountFrequency (%)
38.27364 1
0.7%
38.19748 1
0.7%
38.10567 1
0.7%
38.08998 1
0.7%
38.01869 1
0.7%
38.01251 1
0.7%
37.92907 1
0.7%
37.92261 1
0.7%
37.90683 1
0.7%
37.90624 1
0.7%

TM좌표Y
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean321987.51
Minimum78958.63
Maximum530958.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:39.740240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum78958.63
5-th percentile111844.32
Q1197063.61
median352924.78
Q3442745.68
95-th percentile491411.24
Maximum530958.9
Range452000.27
Interquartile range (IQR)245682.06

Descriptive statistics

Standard deviation133760.25
Coefficient of variation (CV)0.41542061
Kurtosis-1.3491287
Mean321987.51
Median Absolute Deviation (MAD)115179.57
Skewness-0.29617812
Sum45400239
Variance1.7891804 × 1010
MonotonicityStrictly increasing
2023-12-13T02:11:39.903051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78958.62972 1
 
0.7%
414725.22973 1
 
0.7%
409980.39773 1
 
0.7%
410489.457 1
 
0.7%
410558.71157 1
 
0.7%
410812.25289 1
 
0.7%
411995.96576 1
 
0.7%
412205.87034 1
 
0.7%
415673.14594 1
 
0.7%
397230.17701 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
78958.62972 1
0.7%
92357.84901 1
0.7%
104425.4124 1
0.7%
106035.48441 1
0.7%
107699.15335 1
0.7%
108159.41679 1
0.7%
110358.47354 1
0.7%
111844.31617 1
0.7%
113639.18297 1
0.7%
114669.99213 1
0.7%
ValueCountFrequency (%)
530958.903 1
0.7%
523097.84512 1
0.7%
512186.56846 1
0.7%
510439.27666 1
0.7%
502104.25401 1
0.7%
501404.83352 1
0.7%
492408.81781 1
0.7%
491411.2373 1
0.7%
491230.69018 1
0.7%
489594.68002 1
0.7%

행정구역아이디
Real number (ℝ)

Distinct104
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3813707 × 109
Minimum1.1650101 × 109
Maximum4.885041 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:11:40.038340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1650101 × 109
5-th percentile4.1250106 × 109
Q14.275025 × 109
median4.519042 × 109
Q34.679041 × 109
95-th percentile4.728037 × 109
Maximum4.885041 × 109
Range3.7200309 × 109
Interquartile range (IQR)4.04016 × 108

Descriptive statistics

Standard deviation6.221775 × 108
Coefficient of variation (CV)0.14200522
Kurtosis18.878204
Mean4.3813707 × 109
Median Absolute Deviation (MAD)2.08983 × 108
Skewness-4.1708434
Sum6.1777327 × 1011
Variance3.8710484 × 1017
MonotonicityNot monotonic
2023-12-13T02:11:40.246073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4275025000 4
 
2.8%
4728037000 4
 
2.8%
4728033000 3
 
2.1%
4272034000 3
 
2.1%
4792039000 3
 
2.1%
4272038000 3
 
2.1%
4376036000 3
 
2.1%
4721037000 3
 
2.1%
4575036000 2
 
1.4%
4272025000 2
 
1.4%
Other values (94) 111
78.7%
ValueCountFrequency (%)
1165010100 1
0.7%
1165010200 1
0.7%
1165010800 2
1.4%
2811014600 1
0.7%
2814010500 1
0.7%
4125010300 1
0.7%
4125010600 1
0.7%
4155025000 1
0.7%
4157035000 1
0.7%
4165035000 1
0.7%
ValueCountFrequency (%)
4885041000 1
 
0.7%
4885035000 1
 
0.7%
4885032000 1
 
0.7%
4792039000 3
2.1%
4792036000 1
 
0.7%
4728037000 4
2.8%
4728036000 1
 
0.7%
4728034000 1
 
0.7%
4728033000 3
2.1%
4728025300 2
1.4%

심볼코드
Categorical

Distinct6
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
poi_05
61 
poi_02
36 
poi_03
31 
poi_04
10 
poi_01
 
2

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st rowpoi_04
2nd rowpoi_02
3rd rowpoi_02
4th rowpoi_02
5th rowpoi_02

Common Values

ValueCountFrequency (%)
poi_05 61
43.3%
poi_02 36
25.5%
poi_03 31
22.0%
poi_04 10
 
7.1%
poi_01 2
 
1.4%
poi_06 1
 
0.7%

Length

2023-12-13T02:11:40.396088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:11:40.503404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
poi_05 61
43.3%
poi_02 36
25.5%
poi_03 31
22.0%
poi_04 10
 
7.1%
poi_01 2
 
1.4%
poi_06 1
 
0.7%

널값
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

공간정보
Text

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T02:11:40.720493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters5922
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)100.0%

Sample

1st row010100000039111E6D1CA55F4026C24F54361A4140
2nd row01010000006046425BCEAF5F400A916B7BBB294140
3rd row0101000000511B4641F0C35F40ECAD203EB0374140
4th row0101000000B260FE0A99C25F4026B3E1218C394140
5th row01010000008FD6135D17DD5F4022AC2E185C3B4140
ValueCountFrequency (%)
010100000039111e6d1ca55f4026c24f54361a4140 1
 
0.7%
0101000000f48e0f7ab6216040d36c07b133874240 1
 
0.7%
010100000050d1a57f490f604045c6afe600974240 1
 
0.7%
010100000096bbe3141d0f604023ac446799974240 1
 
0.7%
0101000000c08de1b11f0f6040c48834b8ad974240 1
 
0.7%
0101000000725c85941f0d6040103e847f11984240 1
 
0.7%
010100000074b354de8e0960402b841bb798994240 1
 
0.7%
0101000000e682807c890e6040baa85c6f9b994240 1
 
0.7%
0101000000bb14139b0f216040aafcc83b878c4240 1
 
0.7%
01010000001f1b412ac5076040a1a6fa230c5d4240 1
 
0.7%
Other values (131) 131
92.9%
2023-12-13T02:11:41.177231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1672
28.2%
4 636
 
10.7%
1 567
 
9.6%
F 310
 
5.2%
5 292
 
4.9%
2 270
 
4.6%
6 247
 
4.2%
C 244
 
4.1%
B 237
 
4.0%
D 221
 
3.7%
Other values (6) 1226
20.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4474
75.5%
Uppercase Letter 1448
 
24.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1672
37.4%
4 636
 
14.2%
1 567
 
12.7%
5 292
 
6.5%
2 270
 
6.0%
6 247
 
5.5%
3 206
 
4.6%
9 203
 
4.5%
7 194
 
4.3%
8 187
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
F 310
21.4%
C 244
16.9%
B 237
16.4%
D 221
15.3%
A 221
15.3%
E 215
14.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4474
75.5%
Latin 1448
 
24.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1672
37.4%
4 636
 
14.2%
1 567
 
12.7%
5 292
 
6.5%
2 270
 
6.0%
6 247
 
5.5%
3 206
 
4.6%
9 203
 
4.5%
7 194
 
4.3%
8 187
 
4.2%
Latin
ValueCountFrequency (%)
F 310
21.4%
C 244
16.9%
B 237
16.4%
D 221
15.3%
A 221
15.3%
E 215
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5922
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1672
28.2%
4 636
 
10.7%
1 567
 
9.6%
F 310
 
5.2%
5 292
 
4.9%
2 270
 
4.6%
6 247
 
4.2%
C 244
 
4.1%
B 237
 
4.0%
D 221
 
3.7%
Other values (6) 1226
20.7%

Sample

공간정보일렬번호자연재해위험지구아이디지구명피해예상지역위치기타주소유형별위험등급지정면적지정년도지정일자시설명시설등급사업시작사업종료사업내용사업비TM좌표XWGS좌표X축WGS좌표Y축TM좌표Y행정구역아이디심볼코드널값공간정보
01201양하전남 완도 노화읍 신양리 885-1<NA>취약방재다0.0320032003-03-10저수지저수지20142015그라우팅,L=0.15km1100161278.71745126.5798634.2047878958.629724689025600poi_04<NA>010100000039111E6D1CA55F4026C24F54361A4140
12202학림전남 완도 완도읍 가용리 3-27<NA>붕괴위험나0.0120032003-08-23급경사지급경사지20122013옹벽L=0.17km배수로정비L=0.17km안전시설물 1식1300176713.53697126.7469734.3260392357.849014689025000poi_02<NA>01010000006046425BCEAF5F400A916B7BBB294140
23199육동전남 완도 금당면 차우리 산201-3<NA>붕괴위험나0.0220032003-08-23급경사지급경사지20132014옹벽L=0.5km안전시설물 1식1100205656.11948127.0615434.43507104425.41244689037000poi_02<NA>0101000000511B4641F0C35F40ECAD203EB0374140
34198가학전남 완도 금당면 가학리 산92-2<NA>붕괴위험나0.0220032003-08-23급경사지급경사지20132014옹벽L=1.0km안전시설물 1식1200203730.11931127.0405934.44959106035.484414689037000poi_02<NA>0101000000B260FE0A99C25F4026B3E1218C394140
45168축정전남 고흥 봉래면 신금리 1000-15<NA>붕괴위험가0.01320102010-05-14급경사지급경사지20132014옹벽 L=180m가옥보상 4가구1652241764.17658127.4545534.46375107699.153354677036000poi_02<NA>01010000008FD6135D17DD5F4022AC2E185C3B4140
56163금산전남 고흥 금산면 신촌리 1405<NA>붕괴위험가0.01320102010-05-14급경사지급경사지20132014옹벽 L=130m가옥보상 2가구2893208880.38644127.0966634.4687108159.416794677033000poi_02<NA>01010000003B3909A52FC65F40CBA11F7EFE3B4140
67164월포하전남 고흥 금산면 신평리 580-105<NA>취약방재나0.2520022002-11-18월포하제저수지20132014그라우팅1식사석정비 L=324m1098217578.31901127.1913734.48842110358.473544677033000poi_04<NA>01010000001791ED7C3FCC5F405B4D5D6A843E4140
78179오산전남 장흥 대덕읍 연지리19-19<NA>유실위험다0.1420062006-02-26오산천소하천20152015하천정비 1.4㎞,교량1개소, 낙차공 7개소2167192665.36842126.9201434.50193111844.316174680025600poi_03<NA>01010000000C3AE97DE3BA5F409C41915F3F404140
89173풍남전남 고흥 풍양면 풍남리 1206-4<NA>붕괴위험가0.00220102010-05-14급경사지급경사지20142015옹벽 L=130m가옥보상 3가구1700222374.25644127.2436734.5179113639.182974677031000poi_02<NA>01010000004638D55A98CF5F40DBBAEA724A424140
910174포두전남 고흥 포두면 상대리 127-1<NA>침수위험나0.04820142014-03-27포두천지방하천20162018호안공 2.0km,교량개수 3개소10744237810.7727127.4118334.52674114669.992134677035000poi_05<NA>0101000000CD99CC785BDA5F4087A999266C434140
공간정보일렬번호자연재해위험지구아이디지구명피해예상지역위치기타주소유형별위험등급지정면적지정년도지정일자시설명시설등급사업시작사업종료사업내용사업비TM좌표XWGS좌표X축WGS좌표Y축TM좌표Y행정구역아이디심볼코드널값공간정보
13113220중앙경기 동두천 중앙동 생연1동 827<NA>침수위험나0.0442120122012-04-02중앙2,3펌프장도시방재시설20132014배수펌프장 2개소 증설(1식), 유입관로 1,239m15800204404.24393127.0500837.90624489594.680024125010300poi_05<NA>0101000000AC8BBE8234C35F405D18ABCDFFF34240
13213324우암강원도 강릉시 주문진읍 주문리 800-3<NA>해일위험가0.0520112011-09-08해안해안시설20122014실시설계용역 1식 소파제 L=430m9035360584.99769128.8259337.90683491230.690184215025000poi_06<NA>0101000000CADB5CFC6D1A6040C08B9DF012F44240
13313419보산경기 동두천 보산동 458<NA>침수위험나1.24820122012-04-02보산1펌프장도시방재시설20162016배수펌프장 1개소 증설(1식)3767205009.773127.0569837.92261491411.23734125010600poi_05<NA>0101000000C1A50D87A5C35F40250776FC17F64240
13413523신북강원 춘천 신북읍 천전리 692-21<NA>침수위험다0.22719961996-12-03소양강국가하천20142014토사매립 680,000㎥4440267980.39059127.7732337.92907492408.817814211025000poi_05<NA>01010000002D154B917CF15F40BBE041B3EBF64240
13513617주원경기 포천 창수 창수면 774<NA>침수위험나0.15320132013-11-08영평천지방하천20162017하천정비 1.2km, 교량 1식, 배수문1식10530216079.30926127.183138.01251501404.833524165035000poi_05<NA>0101000000393BDEE4B7CB5F40165F0A0F9A014340
13613716영평경기 포천 영중면 성동리 636-1일동~영중침수위험나0.73820132013-11-08영평천지방하천20162018보1개소, 홍수방지벽0.3km,교량2개소,지방도숭상 3.7km14943222160.40627127.2523738.01869502104.254014165036000poi_05<NA>01010000004FE5EAC726D05F4045EEEA5564024340
13713858너분동강원 양구 양구읍 정림리 330<NA>취약방재나0.04220062006-02-27너분동저수지저수지20152016제당 H=5m, L=50m 개보수1500285795.56264127.9779938.08998510439.276664280025000poi_04<NA>01010000001B6A257497FE5F405EA6F276840B4340
13813957직곡강원 양구 양구읍 상리 558<NA>침수위험나0.05820102010-05-11직곡천소하천20122013제방 정비 L=1.15km교량 1개소2000286344.877127.9844738.10567512186.568464280025000poi_05<NA>0101000000D97FAE7D01FF5F40F1A20A7F860D4340
13914027노학1강원 속초 교동671-2<NA>침수위험가0.02520062006-07-28배수펌프장도시방재시설20092015보상(토지10필지, 지장물 4개소), PC암거639m, U형측구(0.3*0.3) 118m, 펌프일체형 수문 2개소, 배수펌프장 및 유수지 1식24577338287.704128.5786438.19748523097.845124221010600poi_05<NA>010100000082FF6B4084126040BF5C24ED46194340
14014159오유강원 양구 해안면 오유리 907<NA>취약방재나0.2620062006-02-27오유저수지저수지20142015제당 H=13.5m, L=350m 개보수1700297331.16145128.1122838.27364530958.9034280034000poi_04<NA>01010000001DA4BDC197036040A5F64D9A06234340