Overview

Dataset statistics

Number of variables7
Number of observations102
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory60.3 B

Variable types

Numeric3
Categorical3
Text1

Dataset

Description부산광역시 사상구에 소재하는 일반 공유재산 현황(재산관리관, 읍‧면‧동, 면적, 구분 등)에 대한 데이터입니다.
Author부산광역시 사상구
URLhttps://www.data.go.kr/data/3078732/fileData.do

Alerts

재산관리관 has constant value ""Constant
구분 has constant value ""Constant
재산 has constant value ""Constant
면적 is highly overall correlated with 실면적High correlation
실면적 is highly overall correlated with 면적High correlation
순번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2024-03-14 17:16:25.139516
Analysis finished2024-03-14 17:16:28.212308
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.5
Minimum1
Maximum102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-15T02:16:28.436746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.05
Q126.25
median51.5
Q376.75
95-th percentile96.95
Maximum102
Range101
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation29.588849
Coefficient of variation (CV)0.57454076
Kurtosis-1.2
Mean51.5
Median Absolute Deviation (MAD)25.5
Skewness0
Sum5253
Variance875.5
MonotonicityStrictly increasing
2024-03-15T02:16:28.896430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
66 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
Other values (92) 92
90.2%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%

재산관리관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size944.0 B
행정지원국 재무과
102 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row행정지원국 재무과
2nd row행정지원국 재무과
3rd row행정지원국 재무과
4th row행정지원국 재무과
5th row행정지원국 재무과

Common Values

ValueCountFrequency (%)
행정지원국 재무과 102
100.0%

Length

2024-03-15T02:16:29.233195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:16:29.465936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정지원국 102
50.0%
재무과 102
50.0%

소재지
Text

UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size944.0 B
2024-03-15T02:16:30.627608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length20.137255
Min length17

Characters and Unicode

Total characters2054
Distinct characters37
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

Unique102 ?
Unique (%)100.0%

Sample

1st row부산광역시 사상구 삼락동 53-36
2nd row부산광역시 사상구 모라동 75-22
3rd row부산광역시 사상구 모라동 257-11
4th row부산광역시 사상구 모라동 258-4
5th row부산광역시 사상구 모라동 258-19
ValueCountFrequency (%)
부산광역시 102
25.0%
사상구 102
25.0%
엄궁동 26
 
6.4%
주례동 21
 
5.1%
괘법동 18
 
4.4%
덕포동 12
 
2.9%
모라동 10
 
2.5%
감전동 9
 
2.2%
학장동 5
 
1.2%
53-1 1
 
0.2%
Other values (102) 102
25.0%
2024-03-15T02:16:32.268183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
413
20.1%
부 102
 
5.0%
광 102
 
5.0%
역 102
 
5.0%
시 102
 
5.0%
사 102
 
5.0%
상 102
 
5.0%
구 102
 
5.0%
산 102
 
5.0%
동 102
 
5.0%
Other values (27) 723
35.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1122
54.6%
Decimal Number 426
 
20.7%
Space Separator 413
 
20.1%
Dash Punctuation 93
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 102
9.1%
광 102
9.1%
역 102
9.1%
시 102
9.1%
사 102
9.1%
상 102
9.1%
구 102
9.1%
산 102
9.1%
동 102
9.1%
엄 26
 
2.3%
Other values (15) 178
15.9%
Decimal Number
ValueCountFrequency (%)
2 75
17.6%
1 72
16.9%
4 53
12.4%
5 51
12.0%
3 45
10.6%
0 30
 
7.0%
7 29
 
6.8%
6 26
 
6.1%
8 26
 
6.1%
9 19
 
4.5%
Space Separator
ValueCountFrequency (%)
413
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1122
54.6%
Common 932
45.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 102
9.1%
광 102
9.1%
역 102
9.1%
시 102
9.1%
사 102
9.1%
상 102
9.1%
구 102
9.1%
산 102
9.1%
동 102
9.1%
엄 26
 
2.3%
Other values (15) 178
15.9%
Common
ValueCountFrequency (%)
413
44.3%
- 93
 
10.0%
2 75
 
8.0%
1 72
 
7.7%
4 53
 
5.7%
5 51
 
5.5%
3 45
 
4.8%
0 30
 
3.2%
7 29
 
3.1%
6 26
 
2.8%
Other values (2) 45
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1122
54.6%
ASCII 932
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
413
44.3%
- 93
 
10.0%
2 75
 
8.0%
1 72
 
7.7%
4 53
 
5.7%
5 51
 
5.5%
3 45
 
4.8%
0 30
 
3.2%
7 29
 
3.1%
6 26
 
2.8%
Other values (2) 45
 
4.8%
Hangul
ValueCountFrequency (%)
부 102
9.1%
광 102
9.1%
역 102
9.1%
시 102
9.1%
사 102
9.1%
상 102
9.1%
구 102
9.1%
산 102
9.1%
동 102
9.1%
엄 26
 
2.3%
Other values (15) 178
15.9%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.717549
Minimum1
Maximum341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-15T02:16:32.717996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median24
Q346
95-th percentile144.93
Maximum341
Range340
Interquartile range (IQR)39

Descriptive statistics

Standard deviation50.521444
Coefficient of variation (CV)1.3394678
Kurtosis13.826956
Mean37.717549
Median Absolute Deviation (MAD)18
Skewness3.2072659
Sum3847.19
Variance2552.4163
MonotonicityNot monotonic
2024-03-15T02:16:33.491949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 8
 
7.8%
3.0 5
 
4.9%
7.0 5
 
4.9%
6.0 5
 
4.9%
42.0 3
 
2.9%
9.0 3
 
2.9%
23.0 3
 
2.9%
25.0 3
 
2.9%
8.0 3
 
2.9%
53.0 2
 
2.0%
Other values (51) 62
60.8%
ValueCountFrequency (%)
1.0 8
7.8%
2.0 2
 
2.0%
3.0 5
4.9%
4.0 1
 
1.0%
4.3 1
 
1.0%
5.0 1
 
1.0%
6.0 5
4.9%
7.0 5
4.9%
8.0 3
 
2.9%
9.0 3
 
2.9%
ValueCountFrequency (%)
341.0 1
1.0%
213.9 1
1.0%
176.0 1
1.0%
159.0 1
1.0%
152.0 1
1.0%
146.4 1
1.0%
117.0 1
1.0%
116.0 1
1.0%
111.0 1
1.0%
92.0 1
1.0%

실면적
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)60.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.792451
Minimum1
Maximum244.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-15T02:16:34.214325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median22.15
Q344.5
95-th percentile110.05
Maximum244.2
Range243.2
Interquartile range (IQR)37.5

Descriptive statistics

Standard deviation41.774665
Coefficient of variation (CV)1.273911
Kurtosis10.154247
Mean32.792451
Median Absolute Deviation (MAD)16.5
Skewness2.8846888
Sum3344.83
Variance1745.1226
MonotonicityNot monotonic
2024-03-15T02:16:34.864750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 8
 
7.8%
3.0 6
 
5.9%
6.0 5
 
4.9%
7.0 4
 
3.9%
9.0 3
 
2.9%
23.0 3
 
2.9%
25.0 3
 
2.9%
8.0 3
 
2.9%
29.0 2
 
2.0%
30.0 2
 
2.0%
Other values (52) 63
61.8%
ValueCountFrequency (%)
1.0 8
7.8%
2.0 2
 
2.0%
3.0 6
5.9%
4.0 1
 
1.0%
4.3 1
 
1.0%
5.0 1
 
1.0%
6.0 5
4.9%
6.9 1
 
1.0%
7.0 4
3.9%
8.0 3
 
2.9%
ValueCountFrequency (%)
244.2 1
1.0%
213.9 1
1.0%
176.0 1
1.0%
152.0 1
1.0%
116.0 1
1.0%
111.0 1
1.0%
92.0 1
1.0%
88.0 1
1.0%
83.0 1
1.0%
67.0 1
1.0%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size944.0 B
일반재산
102 

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 102
100.0%

Length

2024-03-15T02:16:35.482344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:16:35.842114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반재산 102
100.0%

재산
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size944.0 B
토지
102 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
토지 102
100.0%

Length

2024-03-15T02:16:36.318762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:16:36.634950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토지 102
100.0%

Interactions

2024-03-15T02:16:26.833838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:16:25.339771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:16:26.079523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:16:27.079145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:16:25.587587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:16:26.324324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:16:27.333424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:16:25.838355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:16:26.586154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:16:36.830202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적실면적
순번1.0000.0820.000
면적0.0821.0000.963
실면적0.0000.9631.000
2024-03-15T02:16:37.109683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적실면적
순번1.0000.0570.048
면적0.0571.0000.945
실면적0.0480.9451.000

Missing values

2024-03-15T02:16:27.668511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:16:28.067620image/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

순번재산관리관소재지면적실면적구분재산
01행정지원국 재무과부산광역시 사상구 삼락동 53-3621.321.3일반재산토지
12행정지원국 재무과부산광역시 사상구 모라동 75-2215.115.1일반재산토지
23행정지원국 재무과부산광역시 사상구 모라동 257-1142.042.0일반재산토지
34행정지원국 재무과부산광역시 사상구 모라동 258-41.01.0일반재산토지
45행정지원국 재무과부산광역시 사상구 모라동 258-1949.049.0일반재산토지
56행정지원국 재무과부산광역시 사상구 모라동 273-430.430.4일반재산토지
67행정지원국 재무과부산광역시 사상구 모라동 273-2554.754.7일반재산토지
78행정지원국 재무과부산광역시 사상구 모라동 972-59.09.0일반재산토지
89행정지원국 재무과부산광역시 사상구 모라동 1002-829.029.0일반재산토지
910행정지원국 재무과부산광역시 사상구 모라동 1003-830.030.0일반재산토지
순번재산관리관소재지면적실면적구분재산
9293행정지원국 재무과부산광역시 사상구 엄궁동 219-145.045.0일반재산토지
9394행정지원국 재무과부산광역시 사상구 엄궁동 2757.07.0일반재산토지
9495행정지원국 재무과부산광역시 사상구 엄궁동 28037.037.0일반재산토지
9596행정지원국 재무과부산광역시 사상구 엄궁동 294-088.088.0일반재산토지
9697행정지원국 재무과부산광역시 사상구 엄궁동 305-223.023.0일반재산토지
9798행정지원국 재무과부산광역시 사상구 엄궁동 350152.0152.0일반재산토지
9899행정지원국 재무과부산광역시 사상구 엄궁동 453-230.030.0일반재산토지
99100행정지원국 재무과부산광역시 사상구 엄궁동 454-181.01.0일반재산토지
100101행정지원국 재무과부산광역시 사상구 엄궁동 510-15176.0176.0일반재산토지
101102행정지원국 재무과부산광역시 사상구 엄궁동 519-3159.08.4일반재산토지