Overview

Dataset statistics

Number of variables5
Number of observations791
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.3 KiB
Average record size in memory43.2 B

Variable types

Numeric3
Categorical1
Text1

Dataset

Description부산광역시남구_국공유재산현황_20200531
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3080532

Alerts

순번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:49:07.144284
Analysis finished2023-12-10 16:49:09.246674
Duration2.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct791
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean396
Minimum1
Maximum791
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-11T01:49:09.368022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile40.5
Q1198.5
median396
Q3593.5
95-th percentile751.5
Maximum791
Range790
Interquartile range (IQR)395

Descriptive statistics

Standard deviation228.48632
Coefficient of variation (CV)0.57698567
Kurtosis-1.2
Mean396
Median Absolute Deviation (MAD)198
Skewness0
Sum313236
Variance52206
MonotonicityStrictly increasing
2023-12-11T01:49:09.642172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
521 1
 
0.1%
523 1
 
0.1%
524 1
 
0.1%
525 1
 
0.1%
526 1
 
0.1%
527 1
 
0.1%
528 1
 
0.1%
529 1
 
0.1%
530 1
 
0.1%
Other values (781) 781
98.7%
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 (%)
791 1
0.1%
790 1
0.1%
789 1
0.1%
788 1
0.1%
787 1
0.1%
786 1
0.1%
785 1
0.1%
784 1
0.1%
783 1
0.1%
782 1
0.1%

담당부서명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
재무과
441 
건축과
348 
 
2

Length

Max length3
Median length3
Mean length2.9949431
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재무과 441
55.8%
건축과 348
44.0%
2
 
0.3%

Length

2023-12-11T01:49:09.906862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:49:10.117254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재무과 441
55.9%
건축과 348
44.1%

소재지
Text

UNIQUE 

Distinct791
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T01:49:10.573583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length21.869785
Min length19

Characters and Unicode

Total characters17299
Distinct characters39
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

Unique791 ?
Unique (%)100.0%

Sample

1st row부산광역시 남구 대연동 219-36번지
2nd row부산광역시 남구 대연동 219-41번지
3rd row부산광역시 남구 대연동 219-45번지
4th row부산광역시 남구 대연동 225-3번지
5th row부산광역시 남구 대연동 235-1번지
ValueCountFrequency (%)
부산광역시 791
25.0%
남구 791
25.0%
문현동 496
15.7%
감만동 121
 
3.8%
대연동 113
 
3.6%
우암동 54
 
1.7%
용당동 4
 
0.1%
용호동 3
 
0.1%
잔여지 2
 
0.1%
도로개설 2
 
0.1%
Other values (792) 792
25.0%
2023-12-11T01:49:11.286171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3169
18.3%
지 793
 
4.6%
산 792
 
4.6%
부 791
 
4.6%
번 791
 
4.6%
광 791
 
4.6%
역 791
 
4.6%
시 791
 
4.6%
남 791
 
4.6%
구 791
 
4.6%
Other values (29) 7008
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9507
55.0%
Decimal Number 3841
22.2%
Space Separator 3169
 
18.3%
Dash Punctuation 782
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 793
8.3%
산 792
8.3%
부 791
8.3%
번 791
8.3%
광 791
8.3%
역 791
8.3%
시 791
8.3%
남 791
8.3%
구 791
8.3%
동 791
8.3%
Other values (17) 1594
16.8%
Decimal Number
ValueCountFrequency (%)
1 787
20.5%
2 460
12.0%
3 460
12.0%
5 413
10.8%
6 367
9.6%
8 313
 
8.1%
4 295
 
7.7%
9 267
 
7.0%
7 256
 
6.7%
0 223
 
5.8%
Space Separator
ValueCountFrequency (%)
3169
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 782
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9507
55.0%
Common 7792
45.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 793
8.3%
산 792
8.3%
부 791
8.3%
번 791
8.3%
광 791
8.3%
역 791
8.3%
시 791
8.3%
남 791
8.3%
구 791
8.3%
동 791
8.3%
Other values (17) 1594
16.8%
Common
ValueCountFrequency (%)
3169
40.7%
1 787
 
10.1%
- 782
 
10.0%
2 460
 
5.9%
3 460
 
5.9%
5 413
 
5.3%
6 367
 
4.7%
8 313
 
4.0%
4 295
 
3.8%
9 267
 
3.4%
Other values (2) 479
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9507
55.0%
ASCII 7792
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3169
40.7%
1 787
 
10.1%
- 782
 
10.0%
2 460
 
5.9%
3 460
 
5.9%
5 413
 
5.3%
6 367
 
4.7%
8 313
 
4.0%
4 295
 
3.8%
9 267
 
3.4%
Other values (2) 479
 
6.1%
Hangul
ValueCountFrequency (%)
지 793
8.3%
산 792
8.3%
부 791
8.3%
번 791
8.3%
광 791
8.3%
역 791
8.3%
시 791
8.3%
남 791
8.3%
구 791
8.3%
동 791
8.3%
Other values (17) 1594
16.8%

면적(제곱미터)
Real number (ℝ)

Distinct141
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.933704
Minimum1
Maximum676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-11T01:49:11.529395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median15
Q337.5
95-th percentile117
Maximum676
Range675
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation62.213106
Coefficient of variation (CV)1.8890406
Kurtosis41.862759
Mean32.933704
Median Absolute Deviation (MAD)12
Skewness5.6508044
Sum26050.56
Variance3870.4705
MonotonicityNot monotonic
2023-12-11T01:49:11.767877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 78
 
9.9%
3.0 58
 
7.3%
7.0 49
 
6.2%
2.0 39
 
4.9%
10.0 28
 
3.5%
20.0 26
 
3.3%
6.0 23
 
2.9%
4.0 22
 
2.8%
17.0 20
 
2.5%
23.0 19
 
2.4%
Other values (131) 429
54.2%
ValueCountFrequency (%)
1.0 78
9.9%
1.68 1
 
0.1%
1.9 1
 
0.1%
2.0 39
4.9%
2.6 1
 
0.1%
3.0 58
7.3%
3.87 1
 
0.1%
4.0 22
 
2.8%
5.0 14
 
1.8%
5.8 1
 
0.1%
ValueCountFrequency (%)
676.0 1
0.1%
602.0 1
0.1%
538.0 1
0.1%
530.0 1
0.1%
507.0 1
0.1%
412.0 1
0.1%
369.0 1
0.1%
348.0 1
0.1%
333.0 1
0.1%
324.0 1
0.1%

공시지가(원_제곱미터)
Real number (ℝ)

Distinct461
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean712191.78
Minimum98900
Maximum2565000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-11T01:49:11.999346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum98900
5-th percentile138600
Q1481800
median693000
Q3932650
95-th percentile1340000
Maximum2565000
Range2466100
Interquartile range (IQR)450850

Descriptive statistics

Standard deviation388128.27
Coefficient of variation (CV)0.54497718
Kurtosis1.4276301
Mean712191.78
Median Absolute Deviation (MAD)217800
Skewness0.74075002
Sum5.633437 × 108
Variance1.5064355 × 1011
MonotonicityNot monotonic
2023-12-11T01:49:12.590877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
138600 55
 
7.0%
147800 18
 
2.3%
227700 12
 
1.5%
481800 9
 
1.1%
280500 8
 
1.0%
140400 7
 
0.9%
1240000 7
 
0.9%
661500 6
 
0.8%
1150000 6
 
0.8%
584100 6
 
0.8%
Other values (451) 657
83.1%
ValueCountFrequency (%)
98900 1
 
0.1%
138600 55
7.0%
140400 7
 
0.9%
141600 1
 
0.1%
147800 18
 
2.3%
165000 2
 
0.3%
168300 1
 
0.1%
171600 3
 
0.4%
179800 1
 
0.1%
183800 1
 
0.1%
ValueCountFrequency (%)
2565000 1
0.1%
2210000 2
0.3%
2150000 1
0.1%
2107000 2
0.3%
2104000 1
0.1%
1971000 2
0.3%
1946000 1
0.1%
1910000 1
0.1%
1890000 1
0.1%
1874000 1
0.1%

Interactions

2023-12-11T01:49:08.447170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:07.455331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:07.950371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:08.620316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:07.625458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:08.117732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:08.806102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:07.797772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:08.277733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:49:12.737613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번담당부서명면적(제곱미터)공시지가(원_제곱미터)
순번1.0000.6180.0000.611
담당부서명0.6181.0000.0000.296
면적(제곱미터)0.0000.0001.0000.000
공시지가(원_제곱미터)0.6110.2960.0001.000
2023-12-11T01:49:12.894410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적(제곱미터)공시지가(원_제곱미터)담당부서명
순번1.0000.090-0.3190.461
면적(제곱미터)0.0901.000-0.1750.000
공시지가(원_제곱미터)-0.319-0.1751.0000.185
담당부서명0.4610.0000.1851.000

Missing values

2023-12-11T01:49:09.024298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:49:09.180605image/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

순번담당부서명소재지면적(제곱미터)공시지가(원_제곱미터)
01건축과부산광역시 남구 대연동 219-36번지21.0604500
12건축과부산광역시 남구 대연동 219-41번지1.0214500
23건축과부산광역시 남구 대연동 219-45번지6.0573300
34재무과부산광역시 남구 대연동 225-3번지2.0706800
45재무과부산광역시 남구 대연동 235-1번지50.0356400
56재무과부산광역시 남구 대연동 245-45번지2.0725000
67재무과부산광역시 남구 대연동 245-98번지1.0725000
78재무과부산광역시 남구 대연동 245-222번지18.0304500
89재무과부산광역시 남구 대연동 282-4번지28.61217000
910재무과부산광역시 남구 대연동 317-70번지10.0366300
순번담당부서명소재지면적(제곱미터)공시지가(원_제곱미터)
781782재무과부산광역시 남구 감만동 106-23번지63.0872200
782783재무과부산광역시 남구 감만동 106-24번지62.0872200
783784재무과부산광역시 남구 감만동 168-43번지77.0636300
784785재무과부산광역시 남구 감만동 168-60번지69.0693500
785786재무과부산광역시 남구 감만동 168-94번지21.0636300
786787재무과부산광역시 남구 감만동 168-121번지39.0715400
787788건축과부산광역시 남구 감만동 589-5번지13.01125000
788789건축과부산광역시 남구 감만동 589-14번지14.0517700
789790건축과부산광역시 남구 감만동 590-3번지7.0227700
790791건축과부산광역시 남구 감만동 590-11번지10.0676200