Overview

Dataset statistics

Number of variables5
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory44.5 B

Variable types

Numeric2
Categorical2
Text1

Dataset

Description국유부동산 기본정보에 관한 데이터로 재산 종류, 재산 구분, 소재지, 대장 면적 등에 관한 정보를 제공합니다. 지번검색과 도로명검색 두 가지 옵션을 제공합니다.
Author기획재정부
URLhttps://www.data.go.kr/data/15087888/fileData.do

Alerts

재산구분 has constant value ""Constant
번호 has unique valuesUnique
소재지 has unique valuesUnique
대장면적(m2) has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:41:03.633453
Analysis finished2023-12-12 05:41:04.235444
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.5
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T14:41:04.345571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median26.5
Q339.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation15.154757
Coefficient of variation (CV)0.57187763
Kurtosis-1.2
Mean26.5
Median Absolute Deviation (MAD)13
Skewness0
Sum1378
Variance229.66667
MonotonicityStrictly increasing
2023-12-12T14:41:04.785401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
28 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

재산종류
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
토지
34 
건물
18 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건물
2nd row토지
3rd row건물
4th row토지
5th row토지

Common Values

ValueCountFrequency (%)
토지 34
65.4%
건물 18
34.6%

Length

2023-12-12T14:41:04.932328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:41:05.035520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토지 34
65.4%
건물 18
34.6%

재산구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
일반재산
52 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반재산 52
100.0%

Length

2023-12-12T14:41:05.147688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:41:05.244493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반재산 52
100.0%

소재지
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-12T14:41:05.615391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.730769
Min length16

Characters and Unicode

Total characters1026
Distinct characters136
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

Unique52 ?
Unique (%)100.0%

Sample

1st row서울특별시 용산구 한남동 732-182
2nd row서울특별시 용산구 용산동1가 2-6
3rd row서울특별시 영등포구 문래동3가 2
4th row서울특별시 영등포구 신길동 9-5
5th row서울특별시 강남구 대치동 900-59
ValueCountFrequency (%)
서울특별시 5
 
2.2%
충청북도 3
 
1.3%
강원도 3
 
1.3%
광주광역시 3
 
1.3%
세종특별자치시 3
 
1.3%
전라남도 3
 
1.3%
울산광역시 3
 
1.3%
충청남도 3
 
1.3%
남구 3
 
1.3%
경상북도 3
 
1.3%
Other values (175) 194
85.8%
2023-12-12T14:41:06.206326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
174
 
17.0%
1 46
 
4.5%
- 44
 
4.3%
시 44
 
4.3%
동 39
 
3.8%
도 30
 
2.9%
2 28
 
2.7%
구 27
 
2.6%
4 24
 
2.3%
광 22
 
2.1%
Other values (126) 548
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 602
58.7%
Decimal Number 206
 
20.1%
Space Separator 174
 
17.0%
Dash Punctuation 44
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 44
 
7.3%
동 39
 
6.5%
도 30
 
5.0%
구 27
 
4.5%
광 22
 
3.7%
산 21
 
3.5%
리 18
 
3.0%
역 18
 
3.0%
남 17
 
2.8%
주 12
 
2.0%
Other values (114) 354
58.8%
Decimal Number
ValueCountFrequency (%)
1 46
22.3%
2 28
13.6%
4 24
11.7%
7 21
10.2%
6 19
9.2%
3 17
 
8.3%
9 15
 
7.3%
8 14
 
6.8%
0 11
 
5.3%
5 11
 
5.3%
Space Separator
ValueCountFrequency (%)
174
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 602
58.7%
Common 424
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 44
 
7.3%
동 39
 
6.5%
도 30
 
5.0%
구 27
 
4.5%
광 22
 
3.7%
산 21
 
3.5%
리 18
 
3.0%
역 18
 
3.0%
남 17
 
2.8%
주 12
 
2.0%
Other values (114) 354
58.8%
Common
ValueCountFrequency (%)
174
41.0%
1 46
 
10.8%
- 44
 
10.4%
2 28
 
6.6%
4 24
 
5.7%
7 21
 
5.0%
6 19
 
4.5%
3 17
 
4.0%
9 15
 
3.5%
8 14
 
3.3%
Other values (2) 22
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 602
58.7%
ASCII 424
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
174
41.0%
1 46
 
10.8%
- 44
 
10.4%
2 28
 
6.6%
4 24
 
5.7%
7 21
 
5.0%
6 19
 
4.5%
3 17
 
4.0%
9 15
 
3.5%
8 14
 
3.3%
Other values (2) 22
 
5.2%
Hangul
ValueCountFrequency (%)
시 44
 
7.3%
동 39
 
6.5%
도 30
 
5.0%
구 27
 
4.5%
광 22
 
3.7%
산 21
 
3.5%
리 18
 
3.0%
역 18
 
3.0%
남 17
 
2.8%
주 12
 
2.0%
Other values (114) 354
58.8%

대장면적(m2)
Real number (ℝ)

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean259.82365
Minimum18
Maximum989.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T14:41:06.420733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile50.279
Q1114.865
median216.5
Q3334.75
95-th percentile698.704
Maximum989.17
Range971.17
Interquartile range (IQR)219.885

Descriptive statistics

Standard deviation216.26844
Coefficient of variation (CV)0.83236626
Kurtosis3.6246415
Mean259.82365
Median Absolute Deviation (MAD)106.5
Skewness1.8202632
Sum13510.83
Variance46772.04
MonotonicityNot monotonic
2023-12-12T14:41:06.620482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
116.16 1
 
1.9%
290.0 1
 
1.9%
142.88 1
 
1.9%
108.0 1
 
1.9%
32.0 1
 
1.9%
115.82 1
 
1.9%
164.0 1
 
1.9%
334.0 1
 
1.9%
262.81 1
 
1.9%
107.0 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
18.0 1
1.9%
32.0 1
1.9%
46.0 1
1.9%
53.78 1
1.9%
56.0 1
1.9%
63.8 1
1.9%
70.8 1
1.9%
91.0 1
1.9%
93.89 1
1.9%
105.0 1
1.9%
ValueCountFrequency (%)
989.17 1
1.9%
981.24 1
1.9%
709.0 1
1.9%
690.28 1
1.9%
639.3 1
1.9%
498.6 1
1.9%
419.0 1
1.9%
403.0 1
1.9%
377.0 1
1.9%
367.0 1
1.9%

Interactions

2023-12-12T14:41:03.922477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:03.778934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:03.995047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:03.847157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:41:06.749929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호재산종류소재지대장면적(m2)
번호1.0000.0001.0000.000
재산종류0.0001.0001.0000.458
소재지1.0001.0001.0001.000
대장면적(m2)0.0000.4581.0001.000
2023-12-12T14:41:06.868841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호대장면적(m2)재산종류
번호1.0000.2360.000
대장면적(m2)0.2361.0000.320
재산종류0.0000.3201.000

Missing values

2023-12-12T14:41:04.095722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:41:04.178542image/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

번호재산종류재산구분소재지대장면적(m2)
01건물일반재산서울특별시 용산구 한남동 732-182116.16
12토지일반재산서울특별시 용산구 용산동1가 2-663.8
23건물일반재산서울특별시 영등포구 문래동3가 293.89
34토지일반재산서울특별시 영등포구 신길동 9-5105.0
45토지일반재산서울특별시 강남구 대치동 900-59297.4
56토지일반재산부산광역시 해운대구 우동 산 64-3165.0
67토지일반재산부산광역시 수영구 광안동 615-2191.0
78건물일반재산부산광역시 동래구 온천동 210-87989.17
89건물일반재산대구광역시 수성구 수성동1가 613192.54
910토지일반재산대구광역시 남구 봉덕동 1296-1139.0
번호재산종류재산구분소재지대장면적(m2)
4243토지일반재산전라남도 목포시 달동 326-6377.0
4344토지일반재산전라남도 완도군 신지면 송곡리 307-1142.0
4445건물일반재산경상북도 경주시 동부동 198-4690.28
4546토지일반재산경상북도 예천군 호명면 직산리 907-2337.0
4647토지일반재산경상북도 영덕군 지품면 오천리 426129.0
4748건물일반재산경상남도 김해시 내동 171-7125.38
4849토지일반재산경상남도 통영시 산양읍 남평리 584-5364.0
4950토지일반재산경상남도 사천시 향촌동 1084-2215.0
5051토지일반재산제주특별자치도 서귀포시 서홍동 46-1340.0
5152건물일반재산제주특별자치도 제주시 일도일동 1102-43243.48