Overview

Dataset statistics

Number of variables3
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory682.0 B
Average record size in memory31.0 B

Variable types

Numeric1
Text1
Boolean1

Dataset

Description부산광역시 영도구 옥외광고물에 관한 데이터 항목으로 법정동 코드 및 법정동명, 그리고 법정동 존폐여부를 제공합니다.
Author부산광역시 영도구
URLhttps://www.data.go.kr/data/15072280/fileData.do

Alerts

존폐여부 has constant value ""Constant
법정동코드 has unique valuesUnique
법정동명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:58:53.519718
Analysis finished2023-12-12 02:58:53.890838
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

법정동코드
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6200106 × 109
Minimum2.62 × 109
Maximum2.6200121 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T11:58:53.976042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.62 × 109
5-th percentile2.6200101 × 109
Q12.6200105 × 109
median2.620011 × 109
Q32.6200116 × 109
95-th percentile2.620012 × 109
Maximum2.6200121 × 109
Range12100
Interquartile range (IQR)1050

Descriptive statistics

Standard deviation2442.7692
Coefficient of variation (CV)9.3235087 × 10-7
Kurtosis18.994605
Mean2.6200106 × 109
Median Absolute Deviation (MAD)550
Skewness-4.2229199
Sum5.7640233 × 1010
Variance5967121.2
MonotonicityStrictly increasing
2023-12-12T11:58:54.185570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2620000000 1
 
4.5%
2620011200 1
 
4.5%
2620012100 1
 
4.5%
2620012000 1
 
4.5%
2620011900 1
 
4.5%
2620011800 1
 
4.5%
2620011700 1
 
4.5%
2620011600 1
 
4.5%
2620011500 1
 
4.5%
2620011400 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
2620000000 1
4.5%
2620010100 1
4.5%
2620010200 1
4.5%
2620010300 1
4.5%
2620010400 1
4.5%
2620010500 1
4.5%
2620010600 1
4.5%
2620010700 1
4.5%
2620010800 1
4.5%
2620010900 1
4.5%
ValueCountFrequency (%)
2620012100 1
4.5%
2620012000 1
4.5%
2620011900 1
4.5%
2620011800 1
4.5%
2620011700 1
4.5%
2620011600 1
4.5%
2620011500 1
4.5%
2620011400 1
4.5%
2620011300 1
4.5%
2620011200 1
4.5%

법정동명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T11:58:54.416884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length14.545455
Min length9

Characters and Unicode

Total characters320
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row부산광역시 영도구
2nd row부산광역시 영도구 대교동1가
3rd row부산광역시 영도구 대교동2가
4th row부산광역시 영도구 대평동1가
5th row부산광역시 영도구 대평동2가
ValueCountFrequency (%)
부산광역시 22
33.8%
영도구 22
33.8%
영선동4가 1
 
1.5%
청학동 1
 
1.5%
봉래동5가 1
 
1.5%
봉래동4가 1
 
1.5%
봉래동3가 1
 
1.5%
봉래동2가 1
 
1.5%
봉래동1가 1
 
1.5%
신선동3가 1
 
1.5%
Other values (13) 13
20.0%
2023-12-12T11:58:54.857206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
13.4%
영 26
 
8.1%
부 22
 
6.9%
광 22
 
6.9%
역 22
 
6.9%
시 22
 
6.9%
도 22
 
6.9%
구 22
 
6.9%
산 22
 
6.9%
동 22
 
6.9%
Other values (18) 75
23.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 258
80.6%
Space Separator 43
 
13.4%
Decimal Number 19
 
5.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 26
10.1%
부 22
8.5%
광 22
8.5%
역 22
8.5%
시 22
8.5%
도 22
8.5%
구 22
8.5%
산 22
8.5%
동 22
8.5%
가 19
7.4%
Other values (12) 37
14.3%
Decimal Number
ValueCountFrequency (%)
2 6
31.6%
1 6
31.6%
3 4
21.1%
4 2
 
10.5%
5 1
 
5.3%
Space Separator
ValueCountFrequency (%)
43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 258
80.6%
Common 62
 
19.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 26
10.1%
부 22
8.5%
광 22
8.5%
역 22
8.5%
시 22
8.5%
도 22
8.5%
구 22
8.5%
산 22
8.5%
동 22
8.5%
가 19
7.4%
Other values (12) 37
14.3%
Common
ValueCountFrequency (%)
43
69.4%
2 6
 
9.7%
1 6
 
9.7%
3 4
 
6.5%
4 2
 
3.2%
5 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 258
80.6%
ASCII 62
 
19.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43
69.4%
2 6
 
9.7%
1 6
 
9.7%
3 4
 
6.5%
4 2
 
3.2%
5 1
 
1.6%
Hangul
ValueCountFrequency (%)
영 26
10.1%
부 22
8.5%
광 22
8.5%
역 22
8.5%
시 22
8.5%
도 22
8.5%
구 22
8.5%
산 22
8.5%
동 22
8.5%
가 19
7.4%
Other values (12) 37
14.3%

존폐여부
Boolean

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size154.0 B
True
22 
ValueCountFrequency (%)
True 22
100.0%
2023-12-12T11:58:55.025479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T11:58:53.611971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:58:55.118924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드법정동명
법정동코드1.0001.000
법정동명1.0001.000

Missing values

2023-12-12T11:58:53.740014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:58:53.849626image/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

법정동코드법정동명존폐여부
02620000000부산광역시 영도구Y
12620010100부산광역시 영도구 대교동1가Y
22620010200부산광역시 영도구 대교동2가Y
32620010300부산광역시 영도구 대평동1가Y
42620010400부산광역시 영도구 대평동2가Y
52620010500부산광역시 영도구 남항동1가Y
62620010600부산광역시 영도구 남항동2가Y
72620010700부산광역시 영도구 남항동3가Y
82620010800부산광역시 영도구 영선동1가Y
92620010900부산광역시 영도구 영선동2가Y
법정동코드법정동명존폐여부
122620011200부산광역시 영도구 신선동1가Y
132620011300부산광역시 영도구 신선동2가Y
142620011400부산광역시 영도구 신선동3가Y
152620011500부산광역시 영도구 봉래동1가Y
162620011600부산광역시 영도구 봉래동2가Y
172620011700부산광역시 영도구 봉래동3가Y
182620011800부산광역시 영도구 봉래동4가Y
192620011900부산광역시 영도구 봉래동5가Y
202620012000부산광역시 영도구 청학동Y
212620012100부산광역시 영도구 동삼동Y