Overview

Dataset statistics

Number of variables6
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory54.9 B

Variable types

Numeric4
Text1
Categorical1

Dataset

Description부산광역시 북구 관내 공유 일반재산 현황 데이터로 토지/건물, 소재지, 지목, 면적, 개별공시지가, 재산가액 등의 정보를 제공합니다.
Author부산광역시 북구
URLhttps://www.data.go.kr/data/15021099/fileData.do

Alerts

면적 is highly overall correlated with 재산가액High correlation
재산가액 is highly overall correlated with 면적High correlation
순번 has unique valuesUnique
소재지 has unique valuesUnique
재산가액 has unique valuesUnique

Reproduction

Analysis started2024-03-23 04:24:00.789870
Analysis finished2024-03-23 04:24:06.750723
Duration5.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.5
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-23T04:24:06.993036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.25
Q112.25
median23.5
Q334.75
95-th percentile43.75
Maximum46
Range45
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation13.422618
Coefficient of variation (CV)0.57117522
Kurtosis-1.2
Mean23.5
Median Absolute Deviation (MAD)11.5
Skewness0
Sum1081
Variance180.16667
MonotonicityStrictly increasing
2024-03-23T04:24:07.425090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 1
 
2.2%
36 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
34 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
46 1
2.2%
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%

소재지
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-23T04:24:07.932582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21.5
Mean length19.695652
Min length17

Characters and Unicode

Total characters906
Distinct characters26
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

Unique46 ?
Unique (%)100.0%

Sample

1st row부산광역시 북구 구포동 1075-79
2nd row부산광역시 북구 구포동 1141-205
3rd row부산광역시 북구 구포동 1141-61
4th row부산광역시 북구 구포동 1141-97
5th row부산광역시 북구 구포동 1144-12
ValueCountFrequency (%)
부산광역시 46
25.0%
북구 46
25.0%
구포동 34
18.5%
만덕동 7
 
3.8%
덕천동 4
 
2.2%
97-5 1
 
0.5%
688-18 1
 
0.5%
688-19 1
 
0.5%
688-2 1
 
0.5%
688-21 1
 
0.5%
Other values (42) 42
22.8%
2024-03-23T04:24:09.292748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
184
20.3%
구 80
 
8.8%
1 52
 
5.7%
북 46
 
5.1%
산 46
 
5.1%
동 46
 
5.1%
부 46
 
5.1%
시 46
 
5.1%
역 46
 
5.1%
광 46
 
5.1%
Other values (16) 268
29.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 460
50.8%
Decimal Number 217
24.0%
Space Separator 184
 
20.3%
Dash Punctuation 45
 
5.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 80
17.4%
북 46
10.0%
산 46
10.0%
동 46
10.0%
부 46
10.0%
시 46
10.0%
역 46
10.0%
광 46
10.0%
포 34
7.4%
덕 11
 
2.4%
Other values (4) 13
 
2.8%
Decimal Number
ValueCountFrequency (%)
1 52
24.0%
8 32
14.7%
6 24
11.1%
4 20
 
9.2%
3 19
 
8.8%
7 18
 
8.3%
0 16
 
7.4%
9 13
 
6.0%
2 13
 
6.0%
5 10
 
4.6%
Space Separator
ValueCountFrequency (%)
184
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 460
50.8%
Common 446
49.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 80
17.4%
북 46
10.0%
산 46
10.0%
동 46
10.0%
부 46
10.0%
시 46
10.0%
역 46
10.0%
광 46
10.0%
포 34
7.4%
덕 11
 
2.4%
Other values (4) 13
 
2.8%
Common
ValueCountFrequency (%)
184
41.3%
1 52
 
11.7%
- 45
 
10.1%
8 32
 
7.2%
6 24
 
5.4%
4 20
 
4.5%
3 19
 
4.3%
7 18
 
4.0%
0 16
 
3.6%
9 13
 
2.9%
Other values (2) 23
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 460
50.8%
ASCII 446
49.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
184
41.3%
1 52
 
11.7%
- 45
 
10.1%
8 32
 
7.2%
6 24
 
5.4%
4 20
 
4.5%
3 19
 
4.3%
7 18
 
4.0%
0 16
 
3.6%
9 13
 
2.9%
Other values (2) 23
 
5.2%
Hangul
ValueCountFrequency (%)
구 80
17.4%
북 46
10.0%
산 46
10.0%
동 46
10.0%
부 46
10.0%
시 46
10.0%
역 46
10.0%
광 46
10.0%
포 34
7.4%
덕 11
 
2.4%
Other values (4) 13
 
2.8%

지목
Categorical

Distinct5
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
대
33 
잡종지
5 
답
4 
전
 
2
임야
 
2

Length

Max length3
Median length1
Mean length1.2608696
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row잡종지
2nd row대
3rd row대
4th row대
5th row대

Common Values

ValueCountFrequency (%)
대 33
71.7%
잡종지 5
 
10.9%
답 4
 
8.7%
전 2
 
4.3%
임야 2
 
4.3%

Length

2024-03-23T04:24:09.847642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T04:24:10.308372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 33
71.7%
잡종지 5
 
10.9%
답 4
 
8.7%
전 2
 
4.3%
임야 2
 
4.3%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.56587
Minimum0.5
Maximum579
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-23T04:24:10.875152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile1
Q15.0075
median23.55
Q346.275
95-th percentile197.2
Maximum579
Range578.5
Interquartile range (IQR)41.2675

Descriptive statistics

Standard deviation110.78477
Coefficient of variation (CV)1.9937557
Kurtosis15.249981
Mean55.56587
Median Absolute Deviation (MAD)19.05
Skewness3.8303372
Sum2556.03
Variance12273.265
MonotonicityNot monotonic
2024-03-23T04:24:11.421638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1.0 4
 
8.7%
4.0 4
 
8.7%
2.0 2
 
4.3%
18.0 2
 
4.3%
26.5 1
 
2.2%
21.0 1
 
2.2%
25.0 1
 
2.2%
579.0 1
 
2.2%
38.0 1
 
2.2%
38.1 1
 
2.2%
Other values (28) 28
60.9%
ValueCountFrequency (%)
0.5 1
 
2.2%
1.0 4
8.7%
2.0 2
4.3%
4.0 4
8.7%
5.0 1
 
2.2%
5.03 1
 
2.2%
11.0 1
 
2.2%
14.0 1
 
2.2%
15.0 1
 
2.2%
18.0 2
4.3%
ValueCountFrequency (%)
579.0 1
2.2%
483.4 1
2.2%
223.0 1
2.2%
119.8 1
2.2%
98.02 1
2.2%
89.2 1
2.2%
88.0 1
2.2%
76.0 1
2.2%
75.0 1
2.2%
68.0 1
2.2%

개별공시지가
Real number (ℝ)

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1361708.7
Minimum92100
Maximum7173000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-23T04:24:11.895800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum92100
5-th percentile387675
Q1802625
median1014500
Q31369250
95-th percentile3610000
Maximum7173000
Range7080900
Interquartile range (IQR)566625

Descriptive statistics

Standard deviation1226094.1
Coefficient of variation (CV)0.90040853
Kurtosis11.567013
Mean1361708.7
Median Absolute Deviation (MAD)322500
Skewness3.1032723
Sum62638600
Variance1.5033068 × 1012
MonotonicityNot monotonic
2024-03-23T04:24:12.538661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
969600 3
 
6.5%
817400 2
 
4.3%
1511000 2
 
4.3%
498600 2
 
4.3%
624100 2
 
4.3%
1020000 2
 
4.3%
589100 1
 
2.2%
1201000 1
 
2.2%
797700 1
 
2.2%
285900 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
92100 1
2.2%
285900 1
2.2%
350700 1
2.2%
498600 2
4.3%
589100 1
2.2%
624100 2
4.3%
632800 1
2.2%
734500 1
2.2%
752400 1
2.2%
797700 1
2.2%
ValueCountFrequency (%)
7173000 1
2.2%
4657000 1
2.2%
3707000 1
2.2%
3319000 1
2.2%
2716000 1
2.2%
2045000 1
2.2%
1672000 1
2.2%
1529000 1
2.2%
1511000 2
4.3%
1474000 1
2.2%

재산가액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49307175
Minimum350700
Maximum4.356396 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-23T04:24:13.071696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum350700
5-th percentile1089775
Q19589000
median23565355
Q339366075
95-th percentile1.6436892 × 108
Maximum4.356396 × 108
Range4.352889 × 108
Interquartile range (IQR)29777075

Descriptive statistics

Standard deviation84310874
Coefficient of variation (CV)1.7099109
Kurtosis12.589921
Mean49307175
Median Absolute Deviation (MAD)15784795
Skewness3.4138601
Sum2.26813 × 109
Variance7.1083234 × 1015
MonotonicityNot monotonic
2024-03-23T04:24:13.564339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
20538300 1
 
2.2%
27448780 1
 
2.2%
21420000 1
 
2.2%
4036000 1
 
2.2%
4080000 1
 
2.2%
24240000 1
 
2.2%
350700 1
 
2.2%
2426000 1
 
2.2%
435639600 1
 
2.2%
46512000 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
350700 1
2.2%
755500 1
2.2%
908100 1
2.2%
1634800 1
2.2%
2045000 1
2.2%
2426000 1
2.2%
2716000 1
2.2%
4036000 1
2.2%
4080000 1
2.2%
6116000 1
2.2%
ValueCountFrequency (%)
435639600 1
2.2%
355057300 1
2.2%
176585200 1
2.2%
127720060 1
2.2%
126038000 1
2.2%
107129200 1
2.2%
100422000 1
2.2%
96748000 1
2.2%
46512000 1
2.2%
44182500 1
2.2%

Interactions

2024-03-23T04:24:04.871013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:01.217557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:02.507546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:03.762759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:05.121800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:01.583415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:02.952872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:04.069945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:05.494395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:02.018458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:03.203751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:04.342370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:05.768643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:02.294773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:03.548706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:24:04.616364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T04:24:14.007830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번소재지지목면적개별공시지가재산가액
순번1.0001.0000.7790.4600.4280.000
소재지1.0001.0001.0001.0001.0001.000
지목0.7791.0001.0000.3540.5490.000
면적0.4601.0000.3541.0000.0000.978
개별공시지가0.4281.0000.5490.0001.0000.000
재산가액0.0001.0000.0000.9780.0001.000
2024-03-23T04:24:14.334194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적개별공시지가재산가액지목
순번1.0000.192-0.4990.0930.433
면적0.1921.000-0.3780.8710.241
개별공시지가-0.499-0.3781.000-0.0030.303
재산가액0.0930.871-0.0031.0000.000
지목0.4330.2410.3030.0001.000

Missing values

2024-03-23T04:24:06.219043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T04:24:06.618744image/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

순번소재지지목면적개별공시지가재산가액
01부산광역시 북구 구포동 1075-79잡종지223.09210020538300
12부산광역시 북구 구포동 1141-205대5.016720008360000
23부산광역시 북구 구포동 1141-61대18.0131700023706000
34부산광역시 북구 구포동 1141-97대76.0127300096748000
45부산광역시 북구 구포동 1144-12대11.0137300015103000
56부산광역시 북구 구포동 1166-29대1.027160002716000
67부산광역시 북구 구포동 117-38대119.81474000176585200
78부산광역시 북구 구포동 130-10대0.51511000755500
89부산광역시 북구 구포동 130-13대28.08135700038104560
910부산광역시 북구 구포동 130-3대98.021303000127720060
순번소재지지목면적개별공시지가재산가액
3637부산광역시 북구 덕천동 310-19대26.596950025691750
3738부산광역시 북구 덕천동 784잡종지483.4734500355057300
3839부산광역시 북구 만덕동 376-37답88.028590025159200
3940부산광역시 북구 만덕동 484-12임야63.062410039318300
4041부산광역시 북구 만덕동 484-18임야68.062410042438800
4142부산광역시 북구 만덕동 487-1대75.058910044182500
4243부산광역시 북구 만덕동 907-4대89.21201000107129200
4344부산광역시 북구 만덕동 97-4답24.079770019144800
4445부산광역시 북구 만덕동 97-5답21.563280013605200
4546부산광역시 북구 화명동 360-3대4.015290006116000