Overview

Dataset statistics

Number of variables9
Number of observations1937
Missing cells9
Missing cells (%)0.1%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory142.0 KiB
Average record size in memory75.1 B

Variable types

Categorical2
Text2
Numeric3
Boolean1
DateTime1

Dataset

Description남해군 내 국·공유지 관련 대부 여부 등 정보에 대한 데이터로 남해군 내 국유재산 토지, 군유재산 토지 등의 정보를 제공합니다.
Author경상남도 남해군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15109541

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
제공유형 is highly overall correlated with 지목명 and 1 other fieldsHigh correlation
지목명 is highly overall correlated with 제공유형 and 1 other fieldsHigh correlation
대부여부 is highly overall correlated with 제공유형 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-11 00:08:59.416154
Analysis finished2023-12-11 00:09:01.401044
Duration1.98 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

제공유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
군유
1353 
국유
584 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군유 1353
69.9%
국유 584
30.1%

Length

2023-12-11T09:09:01.473055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:09:01.585244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군유 1353
69.9%
국유 584
30.1%

지번주소
Text

Distinct1936
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
2023-12-11T09:09:01.870979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length22.952504
Min length19

Characters and Unicode

Total characters44459
Distinct characters105
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

Unique1935 ?
Unique (%)99.9%

Sample

1st row경상남도 남해군 남면 덕월리 408-1
2nd row경상남도 남해군 이동면 초음리 2140-3
3rd row경상남도 남해군 남면 선구리 627-13
4th row경상남도 남해군 삼동면 영지리 2186-11
5th row경상남도 남해군 상주면 상주리 2201-6
ValueCountFrequency (%)
경상남도 1937
19.9%
남해군 1937
19.9%
미조면 425
 
4.4%
미조리 387
 
4.0%
창선면 245
 
2.5%
남해읍 210
 
2.2%
설천면 191
 
2.0%
삼동면 187
 
1.9%
이동면 172
 
1.8%
서면 170
 
1.8%
Other values (1960) 3849
39.6%
2023-12-11T09:09:02.303586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9130
20.5%
남 4302
 
9.7%
상 2158
 
4.9%
해 2147
 
4.8%
1 2025
 
4.6%
도 1976
 
4.4%
경 1937
 
4.4%
군 1937
 
4.4%
리 1937
 
4.4%
- 1793
 
4.0%
Other values (95) 15117
34.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24904
56.0%
Space Separator 9130
 
20.5%
Decimal Number 8632
 
19.4%
Dash Punctuation 1793
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 4302
17.3%
상 2158
8.7%
해 2147
8.6%
도 1976
 
7.9%
경 1937
 
7.8%
군 1937
 
7.8%
리 1937
 
7.8%
면 1745
 
7.0%
미 812
 
3.3%
조 812
 
3.3%
Other values (83) 5141
20.6%
Decimal Number
ValueCountFrequency (%)
1 2025
23.5%
2 1098
12.7%
6 826
9.6%
3 804
 
9.3%
4 726
 
8.4%
7 704
 
8.2%
5 678
 
7.9%
8 660
 
7.6%
0 591
 
6.8%
9 520
 
6.0%
Space Separator
ValueCountFrequency (%)
9130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1793
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24904
56.0%
Common 19555
44.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 4302
17.3%
상 2158
8.7%
해 2147
8.6%
도 1976
 
7.9%
경 1937
 
7.8%
군 1937
 
7.8%
리 1937
 
7.8%
면 1745
 
7.0%
미 812
 
3.3%
조 812
 
3.3%
Other values (83) 5141
20.6%
Common
ValueCountFrequency (%)
9130
46.7%
1 2025
 
10.4%
- 1793
 
9.2%
2 1098
 
5.6%
6 826
 
4.2%
3 804
 
4.1%
4 726
 
3.7%
7 704
 
3.6%
5 678
 
3.5%
8 660
 
3.4%
Other values (2) 1111
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24904
56.0%
ASCII 19555
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9130
46.7%
1 2025
 
10.4%
- 1793
 
9.2%
2 1098
 
5.6%
6 826
 
4.2%
3 804
 
4.1%
4 726
 
3.7%
7 704
 
3.6%
5 678
 
3.5%
8 660
 
3.4%
Other values (2) 1111
 
5.7%
Hangul
ValueCountFrequency (%)
남 4302
17.3%
상 2158
8.7%
해 2147
8.6%
도 1976
 
7.9%
경 1937
 
7.8%
군 1937
 
7.8%
리 1937
 
7.8%
면 1745
 
7.0%
미 812
 
3.3%
조 812
 
3.3%
Other values (83) 5141
20.6%

지목명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
전
627 
답
306 
대
248 
잡종지
200 
대지
171 
Other values (13)
385 

Length

Max length4
Median length1
Mean length1.5219411
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row전
2nd row임야
3rd row전
4th row도로
5th row도로

Common Values

ValueCountFrequency (%)
전 627
32.4%
답 306
15.8%
대 248
 
12.8%
잡종지 200
 
10.3%
대지 171
 
8.8%
도로 160
 
8.3%
임야 140
 
7.2%
묘지 21
 
1.1%
학교용지 18
 
0.9%
구거 14
 
0.7%
Other values (8) 32
 
1.7%

Length

2023-12-11T09:09:02.484319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전 627
32.4%
답 306
15.8%
대 248
 
12.8%
잡종지 200
 
10.3%
대지 171
 
8.8%
도로 160
 
8.3%
임야 140
 
7.2%
묘지 21
 
1.1%
학교용지 18
 
0.9%
구거 14
 
0.7%
Other values (8) 32
 
1.7%

대지면적
Real number (ℝ)

Distinct654
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean352.74344
Minimum1
Maximum25468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.2 KiB
2023-12-11T09:09:02.652159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q136
median105
Q3301
95-th percentile1193.6
Maximum25468
Range25467
Interquartile range (IQR)265

Descriptive statistics

Standard deviation1137.4391
Coefficient of variation (CV)3.2245506
Kurtosis185.25459
Mean352.74344
Median Absolute Deviation (MAD)87
Skewness11.628552
Sum683264.05
Variance1293767.7
MonotonicityNot monotonic
2023-12-11T09:09:02.833281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17.0 24
 
1.2%
10.0 23
 
1.2%
9.0 21
 
1.1%
12.0 21
 
1.1%
3.0 21
 
1.1%
7.0 20
 
1.0%
14.0 19
 
1.0%
13.0 18
 
0.9%
40.0 18
 
0.9%
6.0 17
 
0.9%
Other values (644) 1735
89.6%
ValueCountFrequency (%)
1.0 5
 
0.3%
2.0 10
0.5%
3.0 21
1.1%
4.0 12
0.6%
5.0 16
0.8%
5.5 1
 
0.1%
6.0 17
0.9%
7.0 20
1.0%
8.0 14
0.7%
9.0 21
1.1%
ValueCountFrequency (%)
25468.0 1
0.1%
15880.0 1
0.1%
14876.0 1
0.1%
14418.0 1
0.1%
12893.0 1
0.1%
11433.0 1
0.1%
9160.0 1
0.1%
8838.0 1
0.1%
8051.0 1
0.1%
7844.0 1
0.1%

개별공시지가
Text

Distinct906
Distinct (%)46.9%
Missing5
Missing (%)0.3%
Memory size15.3 KiB
2023-12-11T09:09:03.296781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.6464803
Min length2

Characters and Unicode

Total characters8977
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique549 ?
Unique (%)28.4%

Sample

1st row85700
2nd row1610
3rd row25000
4th row62200
5th row18500
ValueCountFrequency (%)
9000 52
 
2.7%
7380 44
 
2.3%
2780 29
 
1.5%
4880 27
 
1.4%
6790 27
 
1.4%
8000 21
 
1.1%
12000 20
 
1.0%
2070 17
 
0.9%
7200 13
 
0.7%
10000 13
 
0.7%
Other values (893) 1667
86.4%
2023-12-11T09:09:03.872902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3732
41.6%
1 848
 
9.4%
2 686
 
7.6%
8 609
 
6.8%
7 564
 
6.3%
3 551
 
6.1%
6 541
 
6.0%
4 522
 
5.8%
5 495
 
5.5%
9 417
 
4.6%
Other values (3) 12
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8965
99.9%
Space Separator 8
 
0.1%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3732
41.6%
1 848
 
9.5%
2 686
 
7.7%
8 609
 
6.8%
7 564
 
6.3%
3 551
 
6.1%
6 541
 
6.0%
4 522
 
5.8%
5 495
 
5.5%
9 417
 
4.7%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
? 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8977
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3732
41.6%
1 848
 
9.4%
2 686
 
7.6%
8 609
 
6.8%
7 564
 
6.3%
3 551
 
6.1%
6 541
 
6.0%
4 522
 
5.8%
5 495
 
5.5%
9 417
 
4.6%
Other values (3) 12
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3732
41.6%
1 848
 
9.4%
2 686
 
7.6%
8 609
 
6.8%
7 564
 
6.3%
3 551
 
6.1%
6 541
 
6.0%
4 522
 
5.8%
5 495
 
5.5%
9 417
 
4.6%
Other values (3) 12
 
0.1%

대부여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
False
1340 
True
597 
ValueCountFrequency (%)
False 1340
69.2%
True 597
30.8%
2023-12-11T09:09:04.031104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1934
Distinct (%)99.9%
Missing2
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean34.81335
Minimum34.697087
Maximum34.946848
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.2 KiB
2023-12-11T09:09:04.155458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.697087
5-th percentile34.708248
Q134.743329
median34.825332
Q334.867972
95-th percentile34.926103
Maximum34.946848
Range0.24976178
Interquartile range (IQR)0.12464268

Descriptive statistics

Standard deviation0.07150004
Coefficient of variation (CV)0.002053811
Kurtosis-1.153382
Mean34.81335
Median Absolute Deviation (MAD)0.05628258
Skewness-0.09428888
Sum67363.832
Variance0.0051122557
MonotonicityNot monotonic
2023-12-11T09:09:04.346369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.81202829 2
 
0.1%
34.71808837 1
 
0.1%
34.71731156 1
 
0.1%
34.71740493 1
 
0.1%
34.71745305 1
 
0.1%
34.71751662 1
 
0.1%
34.71758955 1
 
0.1%
34.71768307 1
 
0.1%
34.71775378 1
 
0.1%
34.71784655 1
 
0.1%
Other values (1924) 1924
99.3%
(Missing) 2
 
0.1%
ValueCountFrequency (%)
34.69708655 1
0.1%
34.69731754 1
0.1%
34.69758488 1
0.1%
34.69758955 1
0.1%
34.69788276 1
0.1%
34.70311408 1
0.1%
34.70315359 1
0.1%
34.70317625 1
0.1%
34.70319476 1
0.1%
34.70325977 1
0.1%
ValueCountFrequency (%)
34.94684833 1
0.1%
34.94257956 1
0.1%
34.94227146 1
0.1%
34.94215508 1
0.1%
34.9413162 1
0.1%
34.9413147 1
0.1%
34.94109373 1
0.1%
34.94106009 1
0.1%
34.94080722 1
0.1%
34.94080219 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1934
Distinct (%)99.9%
Missing2
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean127.95296
Minimum127.80859
Maximum128.06179
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.2 KiB
2023-12-11T09:09:04.516208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.80859
5-th percentile127.83081
Q1127.89098
median127.95347
Q3128.03598
95-th percentile128.05178
Maximum128.06179
Range0.2532068
Interquartile range (IQR)0.1449958

Descriptive statistics

Standard deviation0.0764134
Coefficient of variation (CV)0.00059719915
Kurtosis-1.3942333
Mean127.95296
Median Absolute Deviation (MAD)0.0747807
Skewness-0.13409303
Sum247588.98
Variance0.0058390077
MonotonicityNot monotonic
2023-12-11T09:09:04.732281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.8315412 2
 
0.1%
128.0367847 1
 
0.1%
128.0364047 1
 
0.1%
128.036458 1
 
0.1%
128.0363431 1
 
0.1%
128.0362237 1
 
0.1%
128.0364565 1
 
0.1%
128.0364933 1
 
0.1%
128.0363928 1
 
0.1%
128.0364226 1
 
0.1%
Other values (1924) 1924
99.3%
(Missing) 2
 
0.1%
ValueCountFrequency (%)
127.8085853 1
0.1%
127.8091171 1
0.1%
127.8091973 1
0.1%
127.8100542 1
0.1%
127.8102504 1
0.1%
127.8104207 1
0.1%
127.8112865 1
0.1%
127.8113371 1
0.1%
127.8113864 1
0.1%
127.8113947 1
0.1%
ValueCountFrequency (%)
128.0617921 1
0.1%
128.0616723 1
0.1%
128.0616603 1
0.1%
128.0614871 1
0.1%
128.0610908 1
0.1%
128.0606951 1
0.1%
128.0606739 1
0.1%
128.0604445 1
0.1%
128.0602669 1
0.1%
128.0601711 1
0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
Minimum2022-08-16 00:00:00
Maximum2022-08-16 00:00:00
2023-12-11T09:09:04.883097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:09:04.996092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T09:09:00.616294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:08:59.966739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:09:00.280770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:09:00.742584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:09:00.071144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:09:00.372846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:09:00.868950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:09:00.165609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:09:00.479794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:09:05.094404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제공유형지목명대지면적대부여부위도경도
제공유형1.0000.7730.0830.9250.3200.300
지목명0.7731.0000.2000.6750.5020.450
대지면적0.0830.2001.0000.0740.0820.067
대부여부0.9250.6750.0741.0000.3520.262
위도0.3200.5020.0820.3521.0000.823
경도0.3000.4500.0670.2620.8231.000
2023-12-11T09:09:05.194161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지목명제공유형대부여부
지목명1.0000.6260.539
제공유형0.6261.0000.751
대부여부0.5390.7511.000
2023-12-11T09:09:05.302858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대지면적위도경도제공유형지목명대부여부
대지면적1.000-0.0690.0890.0620.0850.056
위도-0.0691.000-0.5190.2450.2170.269
경도0.089-0.5191.0000.2300.1890.201
제공유형0.0620.2450.2301.0000.6260.751
지목명0.0850.2170.1890.6261.0000.539
대부여부0.0560.2690.2010.7510.5391.000

Missing values

2023-12-11T09:09:01.020273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:09:01.162860image/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.
2023-12-11T09:09:01.315708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

제공유형지번주소지목명대지면적개별공시지가대부여부위도경도데이터기준일자
0국유경상남도 남해군 남면 덕월리 408-1전78.085700N34.782497127.8535972022-08-16
1국유경상남도 남해군 이동면 초음리 2140-3임야98.01610N34.831878127.9293262022-08-16
2국유경상남도 남해군 남면 선구리 627-13전9.0<NA>N34.730279127.8621272022-08-16
3국유경상남도 남해군 삼동면 영지리 2186-11도로6.025000N34.808876127.9780012022-08-16
4국유경상남도 남해군 상주면 상주리 2201-6도로21.062200N34.727456127.9833072022-08-16
5국유경상남도 남해군 설천면 금음리 581-6전264.018500N34.927176127.920672022-08-16
6국유경상남도 남해군 남면 홍현리 813-1전190.032900N34.72262127.8907032022-08-16
7국유경상남도 남해군 남면 홍현리 813-2전89.032900N34.722555127.8907942022-08-16
8국유경상남도 남해군 미조면 미조리 164-44대지57.0152800N34.711622128.0484112022-08-16
9국유경상남도 남해군 서면 남상리 245대지190.063400N34.847755127.8211232022-08-16
제공유형지번주소지목명대지면적개별공시지가대부여부위도경도데이터기준일자
1927군유경상남도 남해군 창선면 진동리 708-45잡종지9.028500N34.851739128.0550292022-08-16
1928군유경상남도 남해군 창선면 진동리 997-4대229.017400N34.860494128.0590342022-08-16
1929군유경상남도 남해군 창선면 진동리 997-20임야304.0433N34.85997128.0598752022-08-16
1930군유경상남도 남해군 창선면 진동리 1063-32대48.032900N34.859661128.0575852022-08-16
1931군유경상남도 남해군 창선면 진동리 1073-3대8.033200N34.860147128.058152022-08-16
1932군유경상남도 남해군 창선면 진동리 1076-4도로27.01320N34.860443128.0588892022-08-16
1933군유경상남도 남해군 창선면 진동리 1076-6대12.033200N34.860466128.0587462022-08-16
1934군유경상남도 남해군 창선면 진동리 1283답2421.06100N34.84644128.0506032022-08-16
1935군유경상남도 남해군 창선면 진동리 1284답1434.06100N34.846213128.0505822022-08-16
1936군유경상남도 남해군 창선면 진동리 1303잡종지8.07020N34.846717128.0491392022-08-16

Duplicate rows

Most frequently occurring

제공유형지번주소지목명대지면적개별공시지가대부여부위도경도데이터기준일자# duplicates
0군유경상남도 남해군 서면 서상리 1333-7대242.042800N34.812028127.8315412022-08-162