Overview

Dataset statistics

Number of variables9
Number of observations150
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.8 KiB
Average record size in memory73.9 B

Variable types

Categorical5
Text3
Numeric1

Dataset

Description충청남도 부여군 산사태취약지역 현황입니다.(시도, 시군, 읍면, 리, 지번, 지적면적, 취약지역유형, 고시번호, 데이터기준일자)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=437&beforeMenuCd=DOM_000000201001001000&publicdatapk=3046051

Alerts

시군 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시도 is highly overall correlated with 읍면High correlation
읍면 is highly overall correlated with 시도High correlation
시도 is highly imbalanced (94.2%)Imbalance

Reproduction

Analysis started2024-01-09 19:46:51.484819
Analysis finished2024-01-09 19:46:51.944527
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
충청남도
149 
제2014-6호
 
1

Length

Max length8
Median length4
Mean length4.0266667
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 149
99.3%
제2014-6호 1
 
0.7%

Length

2024-01-10T04:46:52.001158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:46:52.094186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 149
99.3%
제2014-6호 1
 
0.7%

시군
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
부여군
150 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부여군 150
100.0%

Length

2024-01-10T04:46:52.175959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:46:52.247491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부여군 150
100.0%

읍면
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
외산면
28 
은산면
24 
충화면
19 
내산면
17 
옥산면
13 
Other values (11)
49 

Length

Max length3
Median length3
Mean length2.9933333
Min length2

Unique

Unique2 ?
Unique (%)1.3%

Sample

1st row부여읍
2nd row충화면
3rd row은산면
4th row옥산면
5th row내산면

Common Values

ValueCountFrequency (%)
외산면 28
18.7%
은산면 24
16.0%
충화면 19
12.7%
내산면 17
11.3%
옥산면 13
8.7%
부여읍 8
 
5.3%
임천면 8
 
5.3%
홍산면 8
 
5.3%
구룡면 8
 
5.3%
장암면 7
 
4.7%
Other values (6) 10
 
6.7%

Length

2024-01-10T04:46:52.323704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
외산면 28
18.7%
은산면 24
16.0%
충화면 19
12.7%
내산면 17
11.3%
옥산면 13
8.7%
부여읍 8
 
5.3%
임천면 8
 
5.3%
홍산면 8
 
5.3%
구룡면 8
 
5.3%
장암면 7
 
4.7%
Other values (6) 10
 
6.7%

리
Text

Distinct77
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-10T04:46:52.518823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters450
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)28.0%

Sample

1st row중정리
2nd row천당리
3rd row신대리
4th row상기리
5th row지티리
ValueCountFrequency (%)
나령리 6
 
4.0%
현암리 6
 
4.0%
화성리 5
 
3.3%
만지리 5
 
3.3%
전장리 5
 
3.3%
상기리 4
 
2.7%
토정리 4
 
2.7%
금지리 4
 
2.7%
지토리 4
 
2.7%
군사리 4
 
2.7%
Other values (67) 103
68.7%
2024-01-10T04:46:52.819243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 150
33.3%
지 21
 
4.7%
대 11
 
2.4%
암 11
 
2.4%
산 11
 
2.4%
정 10
 
2.2%
상 10
 
2.2%
신 9
 
2.0%
가 9
 
2.0%
장 9
 
2.0%
Other values (73) 199
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 450
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 150
33.3%
지 21
 
4.7%
대 11
 
2.4%
암 11
 
2.4%
산 11
 
2.4%
정 10
 
2.2%
상 10
 
2.2%
신 9
 
2.0%
가 9
 
2.0%
장 9
 
2.0%
Other values (73) 199
44.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 450
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 150
33.3%
지 21
 
4.7%
대 11
 
2.4%
암 11
 
2.4%
산 11
 
2.4%
정 10
 
2.2%
상 10
 
2.2%
신 9
 
2.0%
가 9
 
2.0%
장 9
 
2.0%
Other values (73) 199
44.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 450
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 150
33.3%
지 21
 
4.7%
대 11
 
2.4%
암 11
 
2.4%
산 11
 
2.4%
정 10
 
2.2%
상 10
 
2.2%
신 9
 
2.0%
가 9
 
2.0%
장 9
 
2.0%
Other values (73) 199
44.2%

지번
Text

Distinct133
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-10T04:46:53.054557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.2066667
Min length3

Characters and Unicode

Total characters781
Distinct characters21
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

Unique120 ?
Unique (%)80.0%

Sample

1st row산19-1
2nd row산77
3rd row133-1대
4th row산51
5th row산43
ValueCountFrequency (%)
산1-1임 4
 
2.5%
임 4
 
2.5%
산35임 3
 
1.9%
산25-1임 3
 
1.9%
산27-2임 2
 
1.3%
구 2
 
1.3%
산29-1임 2
 
1.3%
산8임 2
 
1.3%
산39임 2
 
1.3%
382구 2
 
1.3%
Other values (126) 131
83.4%
2024-01-10T04:46:53.401834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 119
15.2%
1 112
14.3%
임 104
13.3%
- 94
12.0%
3 50
6.4%
2 43
 
5.5%
6 41
 
5.2%
4 40
 
5.1%
8 33
 
4.2%
5 31
 
4.0%
Other values (11) 114
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 427
54.7%
Other Letter 251
32.1%
Dash Punctuation 94
 
12.0%
Space Separator 7
 
0.9%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 112
26.2%
3 50
11.7%
2 43
 
10.1%
6 41
 
9.6%
4 40
 
9.4%
8 33
 
7.7%
5 31
 
7.3%
0 28
 
6.6%
9 26
 
6.1%
7 23
 
5.4%
Other Letter
ValueCountFrequency (%)
산 119
47.4%
임 104
41.4%
구 17
 
6.8%
대 5
 
2.0%
전 3
 
1.2%
답 2
 
0.8%
천 1
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 530
67.9%
Hangul 251
32.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 112
21.1%
- 94
17.7%
3 50
9.4%
2 43
 
8.1%
6 41
 
7.7%
4 40
 
7.5%
8 33
 
6.2%
5 31
 
5.8%
0 28
 
5.3%
9 26
 
4.9%
Other values (4) 32
 
6.0%
Hangul
ValueCountFrequency (%)
산 119
47.4%
임 104
41.4%
구 17
 
6.8%
대 5
 
2.0%
전 3
 
1.2%
답 2
 
0.8%
천 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 530
67.9%
Hangul 251
32.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 119
47.4%
임 104
41.4%
구 17
 
6.8%
대 5
 
2.0%
전 3
 
1.2%
답 2
 
0.8%
천 1
 
0.4%
ASCII
ValueCountFrequency (%)
1 112
21.1%
- 94
17.7%
3 50
9.4%
2 43
 
8.1%
6 41
 
7.7%
4 40
 
7.5%
8 33
 
6.2%
5 31
 
5.8%
0 28
 
5.3%
9 26
 
4.9%
Other values (4) 32
 
6.0%

지적면적(㎡)
Real number (ℝ)

Distinct145
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6296.3521
Minimum1.284
Maximum482000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-01-10T04:46:53.515026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.284
5-th percentile189
Q1748.75
median1328.36
Q32158.5
95-th percentile4282.7
Maximum482000
Range481998.72
Interquartile range (IQR)1409.75

Descriptive statistics

Standard deviation41239.582
Coefficient of variation (CV)6.5497579
Kurtosis121.42659
Mean6296.3521
Median Absolute Deviation (MAD)747.86
Skewness10.702141
Sum944452.82
Variance1.7007031 × 109
MonotonicityNot monotonic
2024-01-10T04:46:53.619364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1250.0 4
 
2.7%
1549.0 2
 
1.3%
487.0 2
 
1.3%
1189.0 1
 
0.7%
3287.0 1
 
0.7%
1804.0 1
 
0.7%
515.0 1
 
0.7%
2547.0 1
 
0.7%
1818.0 1
 
0.7%
720.0 1
 
0.7%
Other values (135) 135
90.0%
ValueCountFrequency (%)
1.284 1
0.7%
2.518 1
0.7%
100.0 1
0.7%
120.0 1
0.7%
129.0 1
0.7%
162.0 1
0.7%
169.0 1
0.7%
180.0 1
0.7%
200.0 1
0.7%
204.0 1
0.7%
ValueCountFrequency (%)
482000.0 1
0.7%
135000.0 1
0.7%
90000.0 1
0.7%
12905.0 1
0.7%
7530.0 1
0.7%
5320.0 1
0.7%
5200.0 1
0.7%
4352.0 1
0.7%
4198.0 1
0.7%
3680.0 1
0.7%

취약지역유형
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
토석류
113 
산사태
37 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
토석류 113
75.3%
산사태 37
 
24.7%

Length

2024-01-10T04:46:53.712987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:46:53.785562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토석류 113
75.3%
산사태 37
 
24.7%

고시번호
Text

Distinct127
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-10T04:46:53.967079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.8066667
Min length8

Characters and Unicode

Total characters1321
Distinct characters13
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

Unique125 ?
Unique (%)83.3%

Sample

1st row제2013-01호
2nd row제2013-02호
3rd row제2013-03호
4th row제2013-04호
5th row제2013-05호
ValueCountFrequency (%)
제2017-64호 22
 
14.7%
제2016-100호 3
 
2.0%
제2015-20호 1
 
0.7%
제2015-48호 1
 
0.7%
제2015-45호 1
 
0.7%
제2015-44호 1
 
0.7%
제2015-43호 1
 
0.7%
제2015-42 1
 
0.7%
제2015-41호 1
 
0.7%
제2015-40호 1
 
0.7%
Other values (117) 117
78.0%
2024-01-10T04:46:54.283959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 193
14.6%
2 184
13.9%
0 174
13.2%
제 150
11.4%
- 150
11.4%
호 149
11.3%
4 84
6.4%
5 80
6.1%
3 47
 
3.6%
6 45
 
3.4%
Other values (3) 65
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 872
66.0%
Other Letter 299
 
22.6%
Dash Punctuation 150
 
11.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 193
22.1%
2 184
21.1%
0 174
20.0%
4 84
9.6%
5 80
9.2%
3 47
 
5.4%
6 45
 
5.2%
7 35
 
4.0%
8 19
 
2.2%
9 11
 
1.3%
Other Letter
ValueCountFrequency (%)
제 150
50.2%
호 149
49.8%
Dash Punctuation
ValueCountFrequency (%)
- 150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1022
77.4%
Hangul 299
 
22.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 193
18.9%
2 184
18.0%
0 174
17.0%
- 150
14.7%
4 84
8.2%
5 80
7.8%
3 47
 
4.6%
6 45
 
4.4%
7 35
 
3.4%
8 19
 
1.9%
Hangul
ValueCountFrequency (%)
제 150
50.2%
호 149
49.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1022
77.4%
Hangul 299
 
22.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 193
18.9%
2 184
18.0%
0 174
17.0%
- 150
14.7%
4 84
8.2%
5 80
7.8%
3 47
 
4.6%
6 45
 
4.4%
7 35
 
3.4%
8 19
 
1.9%
Hangul
ValueCountFrequency (%)
제 150
50.2%
호 149
49.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2021-09-24
150 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-24
2nd row2021-09-24
3rd row2021-09-24
4th row2021-09-24
5th row2021-09-24

Common Values

ValueCountFrequency (%)
2021-09-24 150
100.0%

Length

2024-01-10T04:46:54.394579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:46:54.698823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-24 150
100.0%

Interactions

2024-01-10T04:46:51.729570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T04:46:54.743061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도읍면리지적면적(㎡)취약지역유형
시도1.0000.8120.0000.0000.000
읍면0.8121.0001.0000.6000.468
리0.0001.0001.0000.7310.576
지적면적(㎡)0.0000.6000.7311.0000.000
취약지역유형0.0000.4680.5760.0001.000
2024-01-10T04:46:54.815593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면시도취약지역유형
읍면1.0000.6310.350
시도0.6311.0000.000
취약지역유형0.3500.0001.000
2024-01-10T04:46:54.880084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지적면적(㎡)시도읍면취약지역유형
지적면적(㎡)1.0000.0000.3070.000
시도0.0001.0000.6310.000
읍면0.3070.6311.0000.350
취약지역유형0.0000.0000.3501.000

Missing values

2024-01-10T04:46:51.811220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T04:46:51.906298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시도시군읍면리지번지적면적(㎡)취약지역유형고시번호데이터기준일자
0충청남도부여군부여읍중정리산19-1720.0산사태제2013-01호2021-09-24
1충청남도부여군충화면천당리산77100.0산사태제2013-02호2021-09-24
2충청남도부여군은산면신대리133-1대169.0산사태제2013-03호2021-09-24
3충청남도부여군옥산면상기리산512000.0산사태제2013-04호2021-09-24
4충청남도부여군내산면지티리산43180.0산사태제2013-05호2021-09-24
5충청남도부여군부여읍상금리608구200.0토석류제2013-06호2021-09-24
6충청남도부여군양화면초왕리470-16 구600.0토석류제2013-07호2021-09-24
7충청남도부여군옥산면상기리443-83680.0토석류제2013-08호2021-09-24
8충청남도부여군외산면수신리382구760.0토석류제2013-09호2021-09-24
9충청남도부여군외산면가덕리산11-1 임2150.0토석류제2013-10호2021-09-24
시도시군읍면리지번지적면적(㎡)취약지역유형고시번호데이터기준일자
140충청남도부여군구룡면현암리산27-3임791.0토석류제2017-64호2021-09-24
141충청남도부여군남면마정리790-7임208.0산사태제2017-64호2021-09-24
142충청남도부여군임천면가신리산78-5임1164.0토석류제2017-64호2021-09-24
143충청남도부여군임천면구교리804구1256.0토석류제2017-64호2021-09-24
144충청남도부여군규암면진변리36대(산3-1)120.0산사태제2018-2호2021-09-24
145충청남도부여군부여읍능산리산30-111939.0토석류제2018-3호2021-09-24
146충청남도부여군외산면삼산리산383309.0토석류제2018-4호2021-09-24
147충청남도부여군외산면삼산리산56-12447.0산사태제2018-5호2021-09-24
148충청남도부여군은산면오번리산89-10533.0토석류제2018-7호2021-09-24
149충청남도부여군은산면나령리산39-167530.0토석류제2018-8호2021-09-24