Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory722.7 KiB
Average record size in memory74.0 B

Variable types

Numeric2
Categorical3
Boolean2
Text1

Dataset

Description공유수면 관리 및 매립에 관한 법률에 의거 육상공유수면현황 조사 정보 육상공유수면면적, 육상공유수면지목명, 육상공유수면점용사용여부 등을 목록화하여 제공(2023.6) 하는 자료
URLhttps://www.data.go.kr/data/15114297/fileData.do

Alerts

육상공유수면점용사용여부 has constant value ""Constant
육상공유수면형상내용 has constant value ""Constant
육상공유수면사례내용 is highly overall correlated with 육상공유수면이용여부High correlation
육상공유수면이용여부 is highly overall correlated with 육상공유수면사례내용High correlation
육상공유수면지목명 is highly imbalanced (62.0%)Imbalance
육상공유수면사례내용 is highly imbalanced (61.1%)Imbalance
육상공유수면이용여부 is highly imbalanced (61.1%)Imbalance
육상공유수면면적 is highly skewed (γ1 = 51.24474484)Skewed
육상공유수면토지고유번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:52:58.919702
Analysis finished2023-12-12 06:53:00.658180
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

육상공유수면토지고유번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6740904 × 1018
Minimum4.6150126 × 1018
Maximum4.68804 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:53:00.731230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.6150126 × 1018
5-th percentile4.617038 × 1018
Q14.673037 × 1018
median4.680032 × 1018
Q34.684033 × 1018
95-th percentile4.688034 × 1018
Maximum4.68804 × 1018
Range7.3027432 × 1016
Interquartile range (IQR)1.0995995 × 1016

Descriptive statistics

Standard deviation1.9482041 × 1016
Coefficient of variation (CV)0.0041680925
Kurtosis3.8860283
Mean4.6740904 × 1018
Median Absolute Deviation (MAD)4.0010046 × 1015
Skewness-2.3040174
Sum-3.1455139 × 1018
Variance3.7954993 × 1032
MonotonicityNot monotonic
2023-12-12T15:53:00.870212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4684034031105510001 1
 
< 0.1%
4686033025104120001 1
 
< 0.1%
4679036029109860002 1
 
< 0.1%
4677041024105890004 1
 
< 0.1%
4671040031105550010 1
 
< 0.1%
4687037031106210003 1
 
< 0.1%
4615025024106730005 1
 
< 0.1%
4684034024106330016 1
 
< 0.1%
4679039026103780003 1
 
< 0.1%
4615033031101770002 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
4615012600100650021 1
< 0.1%
4615012800200430004 1
< 0.1%
4615025024106730000 1
< 0.1%
4615025024106730005 1
< 0.1%
4615031022111810001 1
< 0.1%
4615031022111820001 1
< 0.1%
4615031027101460000 1
< 0.1%
4615032021106710001 1
< 0.1%
4615032021106730004 1
< 0.1%
4615032021106740001 1
< 0.1%
ValueCountFrequency (%)
4688040032200200000 1
< 0.1%
4688040032107360002 1
< 0.1%
4688040032106940000 1
< 0.1%
4688040032106780000 1
< 0.1%
4688040032106760000 1
< 0.1%
4688040032101940002 1
< 0.1%
4688040032101830004 1
< 0.1%
4688040032101780002 1
< 0.1%
4688040031200600006 1
< 0.1%
4688040031200270001 1
< 0.1%

육상공유수면면적
Real number (ℝ)

SKEWED 

Distinct3938
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7461.5829
Minimum1
Maximum9426347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:53:01.018821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile36
Q1203.75
median608
Q31625
95-th percentile8232.4
Maximum9426347
Range9426346
Interquartile range (IQR)1421.25

Descriptive statistics

Standard deviation130256.48
Coefficient of variation (CV)17.456951
Kurtosis3210.1284
Mean7461.5829
Median Absolute Deviation (MAD)494
Skewness51.244745
Sum74615829
Variance1.6966752 × 1010
MonotonicityNot monotonic
2023-12-12T15:53:01.163611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 39
 
0.4%
198.0 34
 
0.3%
40.0 34
 
0.3%
397.0 32
 
0.3%
50.0 31
 
0.3%
496.0 31
 
0.3%
73.0 29
 
0.3%
36.0 29
 
0.3%
298.0 28
 
0.3%
46.0 27
 
0.3%
Other values (3928) 9686
96.9%
ValueCountFrequency (%)
1.0 3
 
< 0.1%
2.0 3
 
< 0.1%
3.0 8
0.1%
4.0 7
0.1%
5.0 5
 
0.1%
6.0 7
0.1%
7.0 17
0.2%
7.5 1
 
< 0.1%
8.0 8
0.1%
9.0 10
0.1%
ValueCountFrequency (%)
9426347.0 1
< 0.1%
5457850.0 1
< 0.1%
4545421.0 1
< 0.1%
2128066.0 1
< 0.1%
1789487.0 1
< 0.1%
1743666.0 1
< 0.1%
1675411.0 1
< 0.1%
1544729.0 1
< 0.1%
1521322.0 1
< 0.1%
1161820.0 1
< 0.1%

육상공유수면지목명
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
도
7105 
답
1079 
임
 
678
전
 
391
철
 
191
Other values (14)
 
556

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
도 7105
71.0%
답 1079
 
10.8%
임 678
 
6.8%
전 391
 
3.9%
철 191
 
1.9%
제 189
 
1.9%
잡 132
 
1.3%
수 130
 
1.3%
대 70
 
0.7%
과 7
 
0.1%
Other values (9) 28
 
0.3%

Length

2023-12-12T15:53:01.283378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도 7105
71.0%
답 1079
 
10.8%
임 678
 
6.8%
전 391
 
3.9%
철 191
 
1.9%
제 189
 
1.9%
잡 132
 
1.3%
수 130
 
1.3%
대 70
 
0.7%
목 7
 
0.1%
Other values (9) 28
 
0.3%

육상공유수면점용사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2023-12-12T15:53:01.387324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

육상공유수면사례내용
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
관리점검
9238 
우심관리
 
762

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row우심관리
2nd row관리점검
3rd row관리점검
4th row관리점검
5th row관리점검

Common Values

ValueCountFrequency (%)
관리점검 9238
92.4%
우심관리 762
 
7.6%

Length

2023-12-12T15:53:01.489972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:53:01.600053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관리점검 9238
92.4%
우심관리 762
 
7.6%

육상공유수면형상내용
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수면·수류 분포
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수면·수류 분포
2nd row수면·수류 분포
3rd row수면·수류 분포
4th row수면·수류 분포
5th row수면·수류 분포

Common Values

ValueCountFrequency (%)
수면·수류 분포 10000
100.0%

Length

2023-12-12T15:53:01.720763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:53:01.841926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수면·수류 10000
50.0%
분포 10000
50.0%

육상공유수면이용여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
9238 
False
 
762
ValueCountFrequency (%)
True 9238
92.4%
False 762
 
7.6%
2023-12-12T15:53:01.942538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

육상공유수면주소
Text

Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:53:02.347801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length21.7415
Min length16

Characters and Unicode

Total characters217415
Distinct characters280
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

Unique9998 ?
Unique (%)> 99.9%

Sample

1st row전라남도 무안군 현경면 마산리 551-1
2nd row전라남도 해남군 산이면 초송리 1477
3rd row전라남도 해남군 계곡면 성진리 156-15
4th row전라남도 무안군 해제면 광산리 26-3
5th row전라남도 나주시 왕곡면 양산리 563-2
ValueCountFrequency (%)
전라남도 10000
 
20.0%
보성군 909
 
1.8%
장성군 809
 
1.6%
해남군 733
 
1.5%
함평군 728
 
1.5%
고흥군 728
 
1.5%
담양군 717
 
1.4%
무안군 708
 
1.4%
나주시 649
 
1.3%
장흥군 603
 
1.2%
Other values (9174) 33366
66.8%
2023-12-12T15:53:02.882412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39950
18.4%
남 11388
 
5.2%
도 10528
 
4.8%
전 10469
 
4.8%
라 10029
 
4.6%
리 9917
 
4.6%
군 9154
 
4.2%
1 8138
 
3.7%
면 7940
 
3.7%
- 7309
 
3.4%
Other values (270) 92593
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130340
59.9%
Space Separator 39950
 
18.4%
Decimal Number 39816
 
18.3%
Dash Punctuation 7309
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 11388
 
8.7%
도 10528
 
8.1%
전 10469
 
8.0%
라 10029
 
7.7%
리 9917
 
7.6%
군 9154
 
7.0%
면 7940
 
6.1%
산 3398
 
2.6%
성 3268
 
2.5%
장 2049
 
1.6%
Other values (258) 52200
40.0%
Decimal Number
ValueCountFrequency (%)
1 8138
20.4%
2 5047
12.7%
3 4171
10.5%
4 3838
9.6%
5 3596
9.0%
6 3278
8.2%
7 3222
 
8.1%
8 2934
 
7.4%
9 2851
 
7.2%
0 2741
 
6.9%
Space Separator
ValueCountFrequency (%)
39950
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130340
59.9%
Common 87075
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 11388
 
8.7%
도 10528
 
8.1%
전 10469
 
8.0%
라 10029
 
7.7%
리 9917
 
7.6%
군 9154
 
7.0%
면 7940
 
6.1%
산 3398
 
2.6%
성 3268
 
2.5%
장 2049
 
1.6%
Other values (258) 52200
40.0%
Common
ValueCountFrequency (%)
39950
45.9%
1 8138
 
9.3%
- 7309
 
8.4%
2 5047
 
5.8%
3 4171
 
4.8%
4 3838
 
4.4%
5 3596
 
4.1%
6 3278
 
3.8%
7 3222
 
3.7%
8 2934
 
3.4%
Other values (2) 5592
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130340
59.9%
ASCII 87075
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39950
45.9%
1 8138
 
9.3%
- 7309
 
8.4%
2 5047
 
5.8%
3 4171
 
4.8%
4 3838
 
4.4%
5 3596
 
4.1%
6 3278
 
3.8%
7 3222
 
3.7%
8 2934
 
3.4%
Other values (2) 5592
 
6.4%
Hangul
ValueCountFrequency (%)
남 11388
 
8.7%
도 10528
 
8.1%
전 10469
 
8.0%
라 10029
 
7.7%
리 9917
 
7.6%
군 9154
 
7.0%
면 7940
 
6.1%
산 3398
 
2.6%
성 3268
 
2.5%
장 2049
 
1.6%
Other values (258) 52200
40.0%

Interactions

2023-12-12T15:53:00.193660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:52:59.972698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:53:00.288976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:53:00.101044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:53:03.004176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
육상공유수면토지고유번호육상공유수면면적육상공유수면지목명육상공유수면사례내용육상공유수면이용여부
육상공유수면토지고유번호1.0000.0500.1940.0390.039
육상공유수면면적0.0501.0000.0910.0000.000
육상공유수면지목명0.1940.0911.0000.2780.278
육상공유수면사례내용0.0390.0000.2781.0001.000
육상공유수면이용여부0.0390.0000.2781.0001.000
2023-12-12T15:53:03.135004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
육상공유수면사례내용육상공유수면이용여부육상공유수면지목명
육상공유수면사례내용1.0000.9990.246
육상공유수면이용여부0.9991.0000.246
육상공유수면지목명0.2460.2461.000
2023-12-12T15:53:03.236601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
육상공유수면토지고유번호육상공유수면면적육상공유수면지목명육상공유수면사례내용육상공유수면이용여부
육상공유수면토지고유번호1.0000.0410.0970.0480.048
육상공유수면면적0.0411.0000.0420.0000.000
육상공유수면지목명0.0970.0421.0000.2460.246
육상공유수면사례내용0.0480.0000.2461.0000.999
육상공유수면이용여부0.0480.0000.2460.9991.000

Missing values

2023-12-12T15:53:00.419841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:53:00.595784image/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

육상공유수면토지고유번호육상공유수면면적육상공유수면지목명육상공유수면점용사용여부육상공유수면사례내용육상공유수면형상내용육상공유수면이용여부육상공유수면주소
71800468403403110551000110.0도N우심관리수면·수류 분포N전라남도 무안군 현경면 마산리 551-1
617164682041026114770000901.6도N관리점검수면·수류 분포Y전라남도 해남군 산이면 초송리 1477
584104682038021101560015155.0도N관리점검수면·수류 분포Y전라남도 해남군 계곡면 성진리 156-15
727994684036032100260003361.0도N관리점검수면·수류 분포Y전라남도 무안군 해제면 광산리 26-3
33014617032031105630002241.0도N관리점검수면·수류 분포Y전라남도 나주시 왕곡면 양산리 563-2
29000467703202210700000383.0도N관리점검수면·수류 분포Y전라남도 고흥군 도덕면 신양리 700-3
498346170370221091600111318.0도N관리점검수면·수류 분포Y전라남도 나주시 문평면 송산리 916-11
417174679034037201140000140033.0임N관리점검수면·수류 분포Y전라남도 화순군 이양면 증리 산114
67244617036025108950032383.0도N관리점검수면·수류 분포Y전라남도 나주시 다시면 복암리 895-32
641394683033030106500026251.0도N관리점검수면·수류 분포Y전라남도 영암군 신북면 월평리 650-26
육상공유수면토지고유번호육상공유수면면적육상공유수면지목명육상공유수면점용사용여부육상공유수면사례내용육상공유수면형상내용육상공유수면이용여부육상공유수면주소
78956468603702311017003446.0답N관리점검수면·수류 분포Y전라남도 함평군 해보면 용산리 1017-34
18894467203302410888000333.0답N관리점검수면·수류 분포Y전라남도 곡성군 석곡면 당월리 888-3
87697468803202810727000830.0답N관리점검수면·수류 분포Y전라남도 장성군 남면 삼태리 727-8
92321468803702210835000128.0전N관리점검수면·수류 분포Y전라남도 장성군 서삼면 송현리 835-1
368024678039022100410009343.0답N관리점검수면·수류 분포Y전라남도 보성군 회천면 벽교리 41-9
3965346780250221008400171715.0답N관리점검수면·수류 분포Y전라남도 보성군 보성읍 우산리 84-17
50094617043025104920007615.0도N우심관리수면·수류 분포N전라남도 나주시 봉황면 장성리 492-7
7508046860250321054800401026.0전N관리점검수면·수류 분포Y전라남도 함평군 함평읍 장년리 548-40
767294686033028115560000178.0도N관리점검수면·수류 분포Y전라남도 함평군 학교면 월산리 1556
512244681025028107140001370.0도N우심관리수면·수류 분포N전라남도 강진군 강진읍 학명리 714-1