Overview

Dataset statistics

Number of variables5
Number of observations801
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.8 KiB
Average record size in memory43.2 B

Variable types

Numeric3
Categorical1
Text1

Dataset

Description부산광역시남구_국공유재산현황_20210831
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3080532

Alerts

순번 is highly overall correlated with 담당부서명High correlation
담당부서명 is highly overall correlated with 순번High correlation
면적 is highly skewed (γ1 = 24.98042646)Skewed
순번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:48:50.225403
Analysis finished2023-12-10 16:48:51.712896
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct801
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean401
Minimum1
Maximum801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-11T01:48:51.815323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile41
Q1201
median401
Q3601
95-th percentile761
Maximum801
Range800
Interquartile range (IQR)400

Descriptive statistics

Standard deviation231.37308
Coefficient of variation (CV)0.57699021
Kurtosis-1.2
Mean401
Median Absolute Deviation (MAD)200
Skewness0
Sum321201
Variance53533.5
MonotonicityStrictly increasing
2023-12-11T01:48:52.035456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
539 1
 
0.1%
529 1
 
0.1%
530 1
 
0.1%
531 1
 
0.1%
532 1
 
0.1%
533 1
 
0.1%
534 1
 
0.1%
535 1
 
0.1%
536 1
 
0.1%
Other values (791) 791
98.8%
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 (%)
801 1
0.1%
800 1
0.1%
799 1
0.1%
798 1
0.1%
797 1
0.1%
796 1
0.1%
795 1
0.1%
794 1
0.1%
793 1
0.1%
792 1
0.1%

담당부서명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
재무담당관
455 
건축과
346 

Length

Max length5
Median length5
Mean length4.1360799
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건축과
2nd row건축과
3rd row건축과
4th row재무담당관
5th row재무담당관

Common Values

ValueCountFrequency (%)
재무담당관 455
56.8%
건축과 346
43.2%

Length

2023-12-11T01:48:52.234675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:48:52.359428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재무담당관 455
56.8%
건축과 346
43.2%

소재지
Text

UNIQUE 

Distinct801
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2023-12-11T01:48:52.778079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length19.902622
Min length17

Characters and Unicode

Total characters15942
Distinct characters45
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique801 ?
Unique (%)100.0%

Sample

1st row부산광역시 남구 대연동 219-36
2nd row부산광역시 남구 대연동 219-41
3rd row부산광역시 남구 대연동 219-45
4th row부산광역시 남구 대연동 225-3
5th row부산광역시 남구 대연동 235-1
ValueCountFrequency (%)
부산광역시 801
24.9%
남구 801
24.9%
문현동 494
15.4%
감만동 130
 
4.0%
대연동 115
 
3.6%
우암동 53
 
1.6%
용당동 5
 
0.2%
용호동 4
 
0.1%
도로개설 2
 
0.1%
잔여지 2
 
0.1%
Other values (805) 806
25.1%
2023-12-11T01:48:53.417431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3213
20.2%
1 805
 
5.0%
부 803
 
5.0%
산 803
 
5.0%
동 803
 
5.0%
광 801
 
5.0%
역 801
 
5.0%
시 801
 
5.0%
남 801
 
5.0%
구 801
 
5.0%
Other values (35) 5510
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8045
50.5%
Decimal Number 3891
24.4%
Space Separator 3213
 
20.2%
Dash Punctuation 792
 
5.0%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 803
10.0%
산 803
10.0%
동 803
10.0%
광 801
10.0%
역 801
10.0%
시 801
10.0%
남 801
10.0%
구 801
10.0%
현 494
6.1%
문 494
6.1%
Other values (22) 643
8.0%
Decimal Number
ValueCountFrequency (%)
1 805
20.7%
2 465
12.0%
3 461
11.8%
5 415
10.7%
6 372
9.6%
8 313
 
8.0%
4 302
 
7.8%
9 274
 
7.0%
7 258
 
6.6%
0 226
 
5.8%
Space Separator
ValueCountFrequency (%)
3213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 792
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8045
50.5%
Common 7897
49.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 803
10.0%
산 803
10.0%
동 803
10.0%
광 801
10.0%
역 801
10.0%
시 801
10.0%
남 801
10.0%
구 801
10.0%
현 494
6.1%
문 494
6.1%
Other values (22) 643
8.0%
Common
ValueCountFrequency (%)
3213
40.7%
1 805
 
10.2%
- 792
 
10.0%
2 465
 
5.9%
3 461
 
5.8%
5 415
 
5.3%
6 372
 
4.7%
8 313
 
4.0%
4 302
 
3.8%
9 274
 
3.5%
Other values (3) 485
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8045
50.5%
ASCII 7897
49.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3213
40.7%
1 805
 
10.2%
- 792
 
10.0%
2 465
 
5.9%
3 461
 
5.8%
5 415
 
5.3%
6 372
 
4.7%
8 313
 
4.0%
4 302
 
3.8%
9 274
 
3.5%
Other values (3) 485
 
6.1%
Hangul
ValueCountFrequency (%)
부 803
10.0%
산 803
10.0%
동 803
10.0%
광 801
10.0%
역 801
10.0%
시 801
10.0%
남 801
10.0%
구 801
10.0%
현 494
6.1%
문 494
6.1%
Other values (22) 643
8.0%

면적
Real number (ℝ)

SKEWED 

Distinct146
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.845618
Minimum1
Maximum9017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-11T01:48:53.610364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median16
Q340
95-th percentile125
Maximum9017
Range9016
Interquartile range (IQR)35

Descriptive statistics

Standard deviation332.22666
Coefficient of variation (CV)6.8015652
Kurtosis667.55299
Mean48.845618
Median Absolute Deviation (MAD)13
Skewness24.980426
Sum39125.34
Variance110374.55
MonotonicityNot monotonic
2023-12-11T01:48:53.763767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 77
 
9.6%
3.0 59
 
7.4%
7.0 50
 
6.2%
2.0 39
 
4.9%
10.0 26
 
3.2%
20.0 25
 
3.1%
6.0 24
 
3.0%
4.0 23
 
2.9%
17.0 21
 
2.6%
23.0 19
 
2.4%
Other values (136) 438
54.7%
ValueCountFrequency (%)
1.0 77
9.6%
1.9 1
 
0.1%
2.0 39
4.9%
3.0 59
7.4%
4.0 23
 
2.9%
5.0 14
 
1.7%
5.8 1
 
0.1%
6.0 24
 
3.0%
7.0 50
6.2%
8.0 8
 
1.0%
ValueCountFrequency (%)
9017.0 1
0.1%
2083.0 1
0.1%
832.0 1
0.1%
676.0 1
0.1%
538.0 1
0.1%
530.0 1
0.1%
507.0 1
0.1%
412.0 1
0.1%
380.0 1
0.1%
369.0 1
0.1%

공시지가
Real number (ℝ)

Distinct460
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean858149.06
Minimum123100
Maximum2915000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-11T01:48:53.927595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum123100
5-th percentile148500
Q1553600
median816300
Q31132000
95-th percentile1662000
Maximum2915000
Range2791900
Interquartile range (IQR)578400

Descriptive statistics

Standard deviation485232.97
Coefficient of variation (CV)0.56544136
Kurtosis1.0457668
Mean858149.06
Median Absolute Deviation (MAD)289300
Skewness0.69836059
Sum6.873774 × 108
Variance2.3545104 × 1011
MonotonicityNot monotonic
2023-12-11T01:48:54.161015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
148500 54
 
6.7%
162500 18
 
2.2%
254100 9
 
1.1%
553600 9
 
1.1%
1046000 8
 
1.0%
341500 8
 
1.0%
1036000 7
 
0.9%
783600 7
 
0.9%
372900 7
 
0.9%
149800 7
 
0.9%
Other values (450) 667
83.3%
ValueCountFrequency (%)
123100 1
 
0.1%
138600 1
 
0.1%
148500 54
6.7%
149800 7
 
0.9%
151800 1
 
0.1%
162500 18
 
2.2%
190500 2
 
0.2%
193300 1
 
0.1%
196000 1
 
0.1%
200900 3
 
0.4%
ValueCountFrequency (%)
2915000 1
0.1%
2888000 1
0.1%
2733000 1
0.1%
2679000 1
0.1%
2626000 1
0.1%
2568000 1
0.1%
2520000 2
0.2%
2268000 1
0.1%
2220000 1
0.1%
2209000 1
0.1%

Interactions

2023-12-11T01:48:50.994513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:50.400007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:50.679444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:51.180275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:50.494874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:50.794960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:51.290747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:50.577294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:48:50.887681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:48:54.334513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번담당부서명면적공시지가
순번1.0000.8260.0000.649
담당부서명0.8261.0000.0000.351
면적0.0000.0001.0000.099
공시지가0.6490.3510.0991.000
2023-12-11T01:48:54.562279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적공시지가담당부서명
순번1.0000.096-0.3340.656
면적0.0961.000-0.1650.000
공시지가-0.334-0.1651.0000.269
담당부서명0.6560.0000.2691.000

Missing values

2023-12-11T01:48:51.450343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:48:51.658364image/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

순번담당부서명소재지면적공시지가
01건축과부산광역시 남구 대연동 219-3621.0577300
12건축과부산광역시 남구 대연동 219-411.0220200
23건축과부산광역시 남구 대연동 219-456.0546600
34재무담당관부산광역시 남구 대연동 225-32.0697500
45재무담당관부산광역시 남구 대연동 235-150.0447100
56재무담당관부산광역시 남구 대연동 245-452.0911800
67재무담당관부산광역시 남구 대연동 245-981.0911800
78재무담당관부산광역시 남구 대연동 245-22218.0342800
89재무담당관부산광역시 남구 대연동 282-428.61517000
910재무담당관부산광역시 남구 대연동 317-7010.0463600
순번담당부서명소재지면적공시지가
791792재무담당관부산광역시 남구 감만동 199-12182.0783200
792793재무담당관부산광역시 남구 감만동 199-19132.0775500
793794재무담당관부산광역시 남구 감만동 205-111108.01119000
794795재무담당관부산광역시 남구 감만동 217-11106.0802900
795796재무담당관부산광역시 남구 감만동 351-0 동항부녀경로당(감만1동 351번지98.0766900
796797재무담당관부산광역시 남구 감만동 484-0380.0764900
797798건축과부산광역시 남구 감만동 589-513.01202000
798799건축과부산광역시 남구 감만동 589-1414.0605700
799800건축과부산광역시 남구 감만동 590-37.0254100
800801건축과부산광역시 남구 감만동 590-1110.0746900