Overview

Dataset statistics

Number of variables8
Number of observations1803
Missing cells22
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.3 KiB
Average record size in memory66.1 B

Variable types

Numeric2
Text2
Categorical3
Boolean1

Dataset

Description공유재산 중 행정목적으로 사용하지 않거나 사용할 계획이 없는 일반재산에 대한 데이터 제공으로 공유재산의 효율적이 활용 가능
Author부산광역시 영도구
URLhttps://www.data.go.kr/data/15026434/fileData.do

Alerts

재산구분 has constant value ""Constant
재산관리관 has constant value ""Constant
지목 is highly imbalanced (61.3%)Imbalance
사용허가대부가능 여부 is highly imbalanced (78.1%)Imbalance
사용용도 has 22 (1.2%) missing valuesMissing
연번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2024-03-14 16:45:00.572117
Analysis finished2024-03-14 16:45:03.002436
Duration2.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1803
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean902
Minimum1
Maximum1803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-03-15T01:45:03.223402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile91.1
Q1451.5
median902
Q31352.5
95-th percentile1712.9
Maximum1803
Range1802
Interquartile range (IQR)901

Descriptive statistics

Standard deviation520.62559
Coefficient of variation (CV)0.57719023
Kurtosis-1.2
Mean902
Median Absolute Deviation (MAD)451
Skewness0
Sum1626306
Variance271051
MonotonicityStrictly increasing
2024-03-15T01:45:03.679442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1241 1
 
0.1%
1211 1
 
0.1%
1210 1
 
0.1%
1209 1
 
0.1%
1208 1
 
0.1%
1207 1
 
0.1%
1206 1
 
0.1%
1205 1
 
0.1%
1204 1
 
0.1%
Other values (1793) 1793
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1803 1
0.1%
1802 1
0.1%
1801 1
0.1%
1800 1
0.1%
1799 1
0.1%
1798 1
0.1%
1797 1
0.1%
1796 1
0.1%
1795 1
0.1%
1794 1
0.1%

소재지
Text

UNIQUE 

Distinct1803
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-03-15T01:45:04.545245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length22.270105
Min length17

Characters and Unicode

Total characters40153
Distinct characters34
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

Unique1803 ?
Unique (%)100.0%

Sample

1st row부산광역시 영도구 대교동1가 28-4
2nd row부산광역시 영도구 대교동1가 28-6
3rd row부산광역시 영도구 대교동1가 28-9
4th row부산광역시 영도구 대교동1가 28-20
5th row부산광역시 영도구 대교동1가 76-4
ValueCountFrequency (%)
부산광역시 1803
25.0%
영도구 1803
25.0%
신선동2가 424
 
5.9%
동삼동 402
 
5.6%
청학동 321
 
4.4%
신선동3가 233
 
3.2%
신선동1가 188
 
2.6%
영선동4가 77
 
1.1%
봉래동5가 63
 
0.9%
봉래동4가 21
 
0.3%
Other values (1804) 1886
26.1%
2024-03-15T01:45:05.800044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7221
18.0%
1 2499
 
6.2%
동 2205
 
5.5%
2 2058
 
5.1%
영 1889
 
4.7%
산 1812
 
4.5%
부 1803
 
4.5%
구 1803
 
4.5%
도 1803
 
4.5%
시 1803
 
4.5%
Other values (24) 15257
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20922
52.1%
Decimal Number 10295
25.6%
Space Separator 7221
 
18.0%
Dash Punctuation 1715
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2205
10.5%
영 1889
9.0%
산 1812
8.7%
부 1803
8.6%
구 1803
8.6%
도 1803
8.6%
시 1803
8.6%
역 1803
8.6%
광 1803
8.6%
가 1080
 
5.2%
Other values (12) 3118
14.9%
Decimal Number
ValueCountFrequency (%)
1 2499
24.3%
2 2058
20.0%
3 1448
14.1%
4 805
 
7.8%
6 640
 
6.2%
7 622
 
6.0%
5 588
 
5.7%
9 565
 
5.5%
8 564
 
5.5%
0 506
 
4.9%
Space Separator
ValueCountFrequency (%)
7221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1715
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20922
52.1%
Common 19231
47.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2205
10.5%
영 1889
9.0%
산 1812
8.7%
부 1803
8.6%
구 1803
8.6%
도 1803
8.6%
시 1803
8.6%
역 1803
8.6%
광 1803
8.6%
가 1080
 
5.2%
Other values (12) 3118
14.9%
Common
ValueCountFrequency (%)
7221
37.5%
1 2499
 
13.0%
2 2058
 
10.7%
- 1715
 
8.9%
3 1448
 
7.5%
4 805
 
4.2%
6 640
 
3.3%
7 622
 
3.2%
5 588
 
3.1%
9 565
 
2.9%
Other values (2) 1070
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20922
52.1%
ASCII 19231
47.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7221
37.5%
1 2499
 
13.0%
2 2058
 
10.7%
- 1715
 
8.9%
3 1448
 
7.5%
4 805
 
4.2%
6 640
 
3.3%
7 622
 
3.2%
5 588
 
3.1%
9 565
 
2.9%
Other values (2) 1070
 
5.6%
Hangul
ValueCountFrequency (%)
동 2205
10.5%
영 1889
9.0%
산 1812
8.7%
부 1803
8.6%
구 1803
8.6%
도 1803
8.6%
시 1803
8.6%
역 1803
8.6%
광 1803
8.6%
가 1080
 
5.2%
Other values (12) 3118
14.9%

지목
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
08-대
1340 
01-전
181 
05-임야
170 
28-잡종지
 
61
02-답
 
25
Other values (6)
 
26

Length

Max length8
Median length4
Mean length4.1802551
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row08-대
2nd row08-대
3rd row08-대
4th row08-대
5th row08-대

Common Values

ValueCountFrequency (%)
08-대 1340
74.3%
01-전 181
 
10.0%
05-임야 170
 
9.4%
28-잡종지 61
 
3.4%
02-답 25
 
1.4%
14-도로 14
 
0.8%
27-묘지 6
 
0.3%
22-공원 2
 
0.1%
09-공장용지 2
 
0.1%
18-구거 1
 
0.1%

Length

2024-03-15T01:45:06.080978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08-대 1340
74.3%
01-전 181
 
10.0%
05-임야 170
 
9.4%
28-잡종지 61
 
3.4%
02-답 25
 
1.4%
14-도로 14
 
0.8%
27-묘지 6
 
0.3%
22-공원 2
 
0.1%
09-공장용지 2
 
0.1%
18-구거 1
 
0.1%

면적
Real number (ℝ)

Distinct345
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.34315
Minimum0.1
Maximum4139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-03-15T01:45:06.359946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile1
Q18
median25
Q356
95-th percentile164.7
Maximum4139
Range4138.9
Interquartile range (IQR)48

Descriptive statistics

Standard deviation190.88457
Coefficient of variation (CV)3.2166234
Kurtosis216.98548
Mean59.34315
Median Absolute Deviation (MAD)20
Skewness12.999689
Sum106995.7
Variance36436.918
MonotonicityNot monotonic
2024-03-15T01:45:06.793665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 94
 
5.2%
3.0 82
 
4.5%
2.0 65
 
3.6%
7.0 55
 
3.1%
4.0 46
 
2.6%
10.0 41
 
2.3%
33.0 40
 
2.2%
5.0 39
 
2.2%
13.0 33
 
1.8%
9.0 32
 
1.8%
Other values (335) 1276
70.8%
ValueCountFrequency (%)
0.1 2
 
0.1%
0.3 2
 
0.1%
0.4 3
 
0.2%
0.6 1
 
0.1%
0.7 1
 
0.1%
0.8 1
 
0.1%
0.9 1
 
0.1%
1.0 94
5.2%
1.1 1
 
0.1%
1.3 1
 
0.1%
ValueCountFrequency (%)
4139.0 1
0.1%
3475.0 1
0.1%
2649.3 1
0.1%
2483.0 1
0.1%
2047.0 1
0.1%
1374.0 1
0.1%
1296.0 1
0.1%
1289.0 1
0.1%
1262.0 1
0.1%
1159.0 1
0.1%

재산구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
일반재산
1803 

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 1803
100.0%

Length

2024-03-15T01:45:07.213389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:45:07.531096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반재산 1803
100.0%

재산관리관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
토지정보과
1803 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
토지정보과 1803
100.0%

Length

2024-03-15T01:45:07.838176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:45:08.059169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토지정보과 1803
100.0%

사용용도
Text

MISSING 

Distinct112
Distinct (%)6.3%
Missing22
Missing (%)1.2%
Memory size14.2 KiB
2024-03-15T01:45:08.615985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length1
Mean length2.7271196
Min length1

Characters and Unicode

Total characters4857
Distinct characters170
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)3.3%

Sample

1st row막다른 도로
2nd row막다른 도로
3rd row공지
4th row공지
5th row주택
ValueCountFrequency (%)
주택 318
29.1%
대지 118
 
10.8%
도로 75
 
6.9%
및 50
 
4.6%
골목도로 47
 
4.3%
등 29
 
2.7%
공지 28
 
2.6%
잔여지 24
 
2.2%
임야 23
 
2.1%
사찰 23
 
2.1%
Other values (110) 357
32.7%
2024-03-15T01:45:09.556937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1432
29.5%
주 337
 
6.9%
택 323
 
6.7%
지 315
 
6.5%
도 199
 
4.1%
로 199
 
4.1%
대 164
 
3.4%
구 74
 
1.5%
목 71
 
1.5%
골 70
 
1.4%
Other values (160) 1673
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3214
66.2%
Space Separator 1432
29.5%
Decimal Number 77
 
1.6%
Open Punctuation 45
 
0.9%
Close Punctuation 45
 
0.9%
Math Symbol 41
 
0.8%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 337
 
10.5%
택 323
 
10.0%
지 315
 
9.8%
도 199
 
6.2%
로 199
 
6.2%
대 164
 
5.1%
구 74
 
2.3%
목 71
 
2.2%
골 70
 
2.2%
공 67
 
2.1%
Other values (148) 1395
43.4%
Decimal Number
ValueCountFrequency (%)
5 36
46.8%
3 13
 
16.9%
4 13
 
16.9%
1 7
 
9.1%
6 3
 
3.9%
8 3
 
3.9%
2 2
 
2.6%
Space Separator
ValueCountFrequency (%)
1432
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Math Symbol
ValueCountFrequency (%)
~ 41
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3214
66.2%
Common 1640
33.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 337
 
10.5%
택 323
 
10.0%
지 315
 
9.8%
도 199
 
6.2%
로 199
 
6.2%
대 164
 
5.1%
구 74
 
2.3%
목 71
 
2.2%
골 70
 
2.2%
공 67
 
2.1%
Other values (148) 1395
43.4%
Common
ValueCountFrequency (%)
1432
87.3%
( 45
 
2.7%
) 45
 
2.7%
~ 41
 
2.5%
5 36
 
2.2%
3 13
 
0.8%
4 13
 
0.8%
1 7
 
0.4%
6 3
 
0.2%
8 3
 
0.2%
Latin
ValueCountFrequency (%)
M 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3214
66.2%
ASCII 1643
33.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1432
87.2%
( 45
 
2.7%
) 45
 
2.7%
~ 41
 
2.5%
5 36
 
2.2%
3 13
 
0.8%
4 13
 
0.8%
1 7
 
0.4%
M 3
 
0.2%
6 3
 
0.2%
Other values (2) 5
 
0.3%
Hangul
ValueCountFrequency (%)
주 337
 
10.5%
택 323
 
10.0%
지 315
 
9.8%
도 199
 
6.2%
로 199
 
6.2%
대 164
 
5.1%
구 74
 
2.3%
목 71
 
2.2%
골 70
 
2.2%
공 67
 
2.1%
Other values (148) 1395
43.4%

사용허가대부가능 여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
False
1740 
True
 
63
ValueCountFrequency (%)
False 1740
96.5%
True 63
 
3.5%
2024-03-15T01:45:09.750321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-03-15T01:45:01.825244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:01.047523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:02.094682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:45:01.549010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:45:09.860242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지목면적사용허가대부가능 여부
연번1.0000.4620.0520.238
지목0.4621.0000.1430.251
면적0.0520.1431.0000.201
사용허가대부가능 여부0.2380.2510.2011.000
2024-03-15T01:45:10.068193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용허가대부가능 여부지목
사용허가대부가능 여부1.0000.240
지목0.2401.000
2024-03-15T01:45:10.330737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적지목사용허가대부가능 여부
연번1.0000.1910.2160.182
면적0.1911.0000.0650.200
지목0.2160.0651.0000.240
사용허가대부가능 여부0.1820.2000.2401.000

Missing values

2024-03-15T01:45:02.433526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:45:02.816364image/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

연번소재지지목면적재산구분재산관리관사용용도사용허가대부가능 여부
01부산광역시 영도구 대교동1가 28-408-대3.6일반재산토지정보과막다른 도로N
12부산광역시 영도구 대교동1가 28-608-대3.6일반재산토지정보과막다른 도로N
23부산광역시 영도구 대교동1가 28-908-대9.6일반재산토지정보과공지N
34부산광역시 영도구 대교동1가 28-2008-대2.3일반재산토지정보과공지N
45부산광역시 영도구 대교동1가 76-408-대15.9일반재산토지정보과주택N
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연번소재지지목면적재산구분재산관리관사용용도사용허가대부가능 여부
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17941795부산광역시 영도구 동삼동 산 71-405-임야4139.0일반재산토지정보과임야N
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17981799부산광역시 영도구 동삼동 산 121-2805-임야1289.0일반재산토지정보과N
17991800부산광역시 영도구 동삼동 산 121-47105-임야247.0일반재산토지정보과Y
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