Overview

Dataset statistics

Number of variables5
Number of observations183
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory41.7 B

Variable types

Text2
Numeric1
Categorical2

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

데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2024-01-09 19:46:55.462002
Analysis finished2024-01-09 19:46:55.775788
Duration0.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지번주소
Text

Distinct179
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-01-10T04:46:56.021117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length22.038251
Min length19

Characters and Unicode

Total characters4033
Distinct characters121
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

Unique176 ?
Unique (%)96.2%

Sample

1st row충청남도 부여군 부여읍 중정리 산19-1
2nd row충청남도 부여군 충화면 천당리 산77
3rd row충청남도 부여군 은산면 신대리 133-1대
4th row충청남도 부여군 옥산면 상기리 산51
5th row충청남도 부여군 내산면 지티리 산43
ValueCountFrequency (%)
부여군 183
19.8%
충청남도 182
19.7%
외산면 31
 
3.4%
은산면 27
 
2.9%
내산면 23
 
2.5%
충화면 22
 
2.4%
옥산면 15
 
1.6%
부여읍 11
 
1.2%
구룡면 10
 
1.1%
임천면 10
 
1.1%
Other values (263) 409
44.3%
2024-01-10T04:46:56.440080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
740
18.3%
산 265
 
6.6%
충 205
 
5.1%
부 194
 
4.8%
여 194
 
4.8%
남 188
 
4.7%
군 187
 
4.6%
도 185
 
4.6%
청 185
 
4.6%
리 183
 
4.5%
Other values (111) 1507
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2656
65.9%
Space Separator 740
 
18.3%
Decimal Number 518
 
12.8%
Dash Punctuation 117
 
2.9%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 265
 
10.0%
충 205
 
7.7%
부 194
 
7.3%
여 194
 
7.3%
남 188
 
7.1%
군 187
 
7.0%
도 185
 
7.0%
청 185
 
7.0%
리 183
 
6.9%
면 172
 
6.5%
Other values (97) 698
26.3%
Decimal Number
ValueCountFrequency (%)
1 135
26.1%
3 62
12.0%
2 53
 
10.2%
4 52
 
10.0%
6 47
 
9.1%
5 40
 
7.7%
8 37
 
7.1%
0 34
 
6.6%
9 32
 
6.2%
7 26
 
5.0%
Space Separator
ValueCountFrequency (%)
740
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 117
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2656
65.9%
Common 1377
34.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 265
 
10.0%
충 205
 
7.7%
부 194
 
7.3%
여 194
 
7.3%
남 188
 
7.1%
군 187
 
7.0%
도 185
 
7.0%
청 185
 
7.0%
리 183
 
6.9%
면 172
 
6.5%
Other values (97) 698
26.3%
Common
ValueCountFrequency (%)
740
53.7%
1 135
 
9.8%
- 117
 
8.5%
3 62
 
4.5%
2 53
 
3.8%
4 52
 
3.8%
6 47
 
3.4%
5 40
 
2.9%
8 37
 
2.7%
0 34
 
2.5%
Other values (4) 60
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2656
65.9%
ASCII 1377
34.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
740
53.7%
1 135
 
9.8%
- 117
 
8.5%
3 62
 
4.5%
2 53
 
3.8%
4 52
 
3.8%
6 47
 
3.4%
5 40
 
2.9%
8 37
 
2.7%
0 34
 
2.5%
Other values (4) 60
 
4.4%
Hangul
ValueCountFrequency (%)
산 265
 
10.0%
충 205
 
7.7%
부 194
 
7.3%
여 194
 
7.3%
남 188
 
7.1%
군 187
 
7.0%
도 185
 
7.0%
청 185
 
7.0%
리 183
 
6.9%
면 172
 
6.5%
Other values (97) 698
26.3%

지적면적(제곱미터)
Real number (ℝ)

Distinct176
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5369.5837
Minimum1.284
Maximum482000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-01-10T04:46:56.555351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.284
5-th percentile163.6
Q1622.5
median1243
Q32144
95-th percentile4336.6
Maximum482000
Range481998.72
Interquartile range (IQR)1521.5

Descriptive statistics

Standard deviation37371.426
Coefficient of variation (CV)6.9598367
Kurtosis148.17163
Mean5369.5837
Median Absolute Deviation (MAD)743
Skewness11.819653
Sum982633.82
Variance1.3966235 × 109
MonotonicityNot monotonic
2024-01-10T04:46:56.664806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1250.0 4
 
2.2%
487.0 2
 
1.1%
1549.0 2
 
1.1%
1000.0 2
 
1.1%
2829.0 2
 
1.1%
1914.0 1
 
0.5%
2634.0 1
 
0.5%
1787.0 1
 
0.5%
1680.0 1
 
0.5%
1368.0 1
 
0.5%
Other values (166) 166
90.7%
ValueCountFrequency (%)
1.284 1
0.5%
2.518 1
0.5%
100.0 1
0.5%
108.0 1
0.5%
120.0 1
0.5%
124.0 1
0.5%
129.0 1
0.5%
140.0 1
0.5%
162.0 1
0.5%
163.0 1
0.5%
ValueCountFrequency (%)
482000.0 1
0.5%
135000.0 1
0.5%
90000.0 1
0.5%
12905.0 1
0.5%
7530.0 1
0.5%
6636.0 1
0.5%
5320.0 1
0.5%
5200.0 1
0.5%
5062.0 1
0.5%
4352.0 1
0.5%

취약지역유형
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
토석류
131 
산사태
52 

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 131
71.6%
산사태 52
 
28.4%

Length

2024-01-10T04:46:56.764193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:46:56.839857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토석류 131
71.6%
산사태 52
 
28.4%

고시번호
Text

Distinct181
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-01-10T04:46:57.013200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.6612022
Min length8

Characters and Unicode

Total characters1585
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

Unique180 ?
Unique (%)98.4%

Sample

1st row제2013-01호
2nd row제2013-02호
3rd row제2013-03호
4th row제2013-04호
5th row제2013-05호
ValueCountFrequency (%)
제2016-100호 3
 
1.6%
제2015-46호 1
 
0.5%
제2017-5호 1
 
0.5%
제2016-6호 1
 
0.5%
제2016-7호 1
 
0.5%
제2016-8호 1
 
0.5%
제2016-9호 1
 
0.5%
제2017-1호 1
 
0.5%
제2017-2호 1
 
0.5%
제2017-3호 1
 
0.5%
Other values (171) 171
93.4%
2024-01-10T04:46:57.321797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 265
16.7%
1 238
15.0%
0 211
13.3%
제 183
11.5%
- 183
11.5%
호 182
11.5%
5 86
 
5.4%
4 68
 
4.3%
3 53
 
3.3%
7 38
 
2.4%
Other values (3) 78
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1037
65.4%
Other Letter 365
 
23.0%
Dash Punctuation 183
 
11.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 265
25.6%
1 238
23.0%
0 211
20.3%
5 86
 
8.3%
4 68
 
6.6%
3 53
 
5.1%
7 38
 
3.7%
6 30
 
2.9%
9 26
 
2.5%
8 22
 
2.1%
Other Letter
ValueCountFrequency (%)
제 183
50.1%
호 182
49.9%
Dash Punctuation
ValueCountFrequency (%)
- 183
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1220
77.0%
Hangul 365
 
23.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 265
21.7%
1 238
19.5%
0 211
17.3%
- 183
15.0%
5 86
 
7.0%
4 68
 
5.6%
3 53
 
4.3%
7 38
 
3.1%
6 30
 
2.5%
9 26
 
2.1%
Hangul
ValueCountFrequency (%)
제 183
50.1%
호 182
49.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1220
77.0%
Hangul 365
 
23.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 265
21.7%
1 238
19.5%
0 211
17.3%
- 183
15.0%
5 86
 
7.0%
4 68
 
5.6%
3 53
 
4.3%
7 38
 
3.1%
6 30
 
2.5%
9 26
 
2.1%
Hangul
ValueCountFrequency (%)
제 183
50.1%
호 182
49.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-09-30
183 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-30
2nd row2023-09-30
3rd row2023-09-30
4th row2023-09-30
5th row2023-09-30

Common Values

ValueCountFrequency (%)
2023-09-30 183
100.0%

Length

2024-01-10T04:46:57.429229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:46:57.505694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-30 183
100.0%

Interactions

2024-01-10T04:46:55.598909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T04:46:57.550438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지적면적(제곱미터)취약지역유형
지적면적(제곱미터)1.0000.000
취약지역유형0.0001.000
2024-01-10T04:46:57.612536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지적면적(제곱미터)취약지역유형
지적면적(제곱미터)1.0000.000
취약지역유형0.0001.000

Missing values

2024-01-10T04:46:55.676967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T04:46:55.746888image/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

지번주소지적면적(제곱미터)취약지역유형고시번호데이터기준일자
0충청남도 부여군 부여읍 중정리 산19-1720.0산사태제2013-01호2023-09-30
1충청남도 부여군 충화면 천당리 산77100.0산사태제2013-02호2023-09-30
2충청남도 부여군 은산면 신대리 133-1대169.0산사태제2013-03호2023-09-30
3충청남도 부여군 옥산면 상기리 산512000.0산사태제2013-04호2023-09-30
4충청남도 부여군 내산면 지티리 산43180.0산사태제2013-05호2023-09-30
5충청남도 부여군 부여읍 상금리 608구200.0토석류제2013-06호2023-09-30
6충청남도 부여군 양화면 초왕리 470-16 구600.0토석류제2013-07호2023-09-30
7충청남도 부여군 옥산면 상기리 443-83680.0토석류제2013-08호2023-09-30
8충청남도 부여군 외산면 수신리 382구760.0토석류제2013-09호2023-09-30
9충청남도 부여군 외산면 가덕리 산11-1 임2150.0토석류제2013-10호2023-09-30
지번주소지적면적(제곱미터)취약지역유형고시번호데이터기준일자
173충청남도 부여군 규암면 나복리 산49-1304.0토석류제2022-7호2023-09-30
174충청남도 부여군 규암면 모리 산9-7436.0토석류제2022-8호2023-09-30
175충청남도 부여군 남면 송암리 산6-1238.0토석류제2022-9호2023-09-30
176충청남도 부여군 내산면 금지리 산57-4527.0토석류제2022-10호2023-09-30
177충청남도 부여군 내산면 묘원리 산60-1788.0토석류제2022-11호2023-09-30
178충청남도 부여군 내산면 운치리 산54-101243.0토석류제2022-12호2023-09-30
179충청남도 부여군 내산면 운치리 산54-12473.0토석류제2022-13호2023-09-30
180충청남도 부여군 석성면 봉정리 산12-1124.0토석류제2022-14호2023-09-30
181충청남도 부여군 외산면 장항리 산402563.0토석류제2022-15호2023-09-30
182충청남도 부여군 임천면 가신리 산73-1381.0토석류제2022-16호2023-09-30