Overview

Dataset statistics

Number of variables4
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory982.0 B
Average record size in memory39.3 B

Variable types

Categorical3
Text1

Dataset

Description부산광역시북구_U옥외광고물통합관리시스템_특화지역관리_20221125
Author부산광역시 북구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15050083

Alerts

특화지역코드 has constant value ""Constant
법정동코드(변환) has constant value ""Constant
구분 has constant value ""Constant
번지 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:44:42.230480
Analysis finished2023-12-10 17:44:42.774618
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

특화지역코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
1
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 25
100.0%

Length

2023-12-11T02:44:42.914476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:44:43.113042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 25
100.0%

법정동코드(변환)
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
부산광역시 북구 덕천동
25 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 북구 덕천동
2nd row부산광역시 북구 덕천동
3rd row부산광역시 북구 덕천동
4th row부산광역시 북구 덕천동
5th row부산광역시 북구 덕천동

Common Values

ValueCountFrequency (%)
부산광역시 북구 덕천동 25
100.0%

Length

2023-12-11T02:44:43.330469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:44:43.531832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 25
33.3%
북구 25
33.3%
덕천동 25
33.3%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
1
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 25
100.0%

Length

2023-12-11T02:44:43.766893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:44:43.975879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 25
100.0%

번지
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T02:44:44.306131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.52
Min length5

Characters and Unicode

Total characters138
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row400-7
2nd row400-8
3rd row400-9
4th row400-10
5th row400-11
ValueCountFrequency (%)
400-7 1
 
4.0%
402-1 1
 
4.0%
147-3 1
 
4.0%
403-31 1
 
4.0%
403-26 1
 
4.0%
403-25 1
 
4.0%
403-10 1
 
4.0%
403-9 1
 
4.0%
403-7 1
 
4.0%
403-3 1
 
4.0%
Other values (15) 15
60.0%
2023-12-11T02:44:45.094058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 36
26.1%
4 26
18.8%
- 25
18.1%
1 20
14.5%
3 13
 
9.4%
7 5
 
3.6%
2 5
 
3.6%
5 3
 
2.2%
8 2
 
1.4%
9 2
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 113
81.9%
Dash Punctuation 25
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 36
31.9%
4 26
23.0%
1 20
17.7%
3 13
 
11.5%
7 5
 
4.4%
2 5
 
4.4%
5 3
 
2.7%
8 2
 
1.8%
9 2
 
1.8%
6 1
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 138
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 36
26.1%
4 26
18.8%
- 25
18.1%
1 20
14.5%
3 13
 
9.4%
7 5
 
3.6%
2 5
 
3.6%
5 3
 
2.2%
8 2
 
1.4%
9 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 138
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 36
26.1%
4 26
18.8%
- 25
18.1%
1 20
14.5%
3 13
 
9.4%
7 5
 
3.6%
2 5
 
3.6%
5 3
 
2.2%
8 2
 
1.4%
9 2
 
1.4%

Missing values

2023-12-11T02:44:42.439790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:44:42.701692image/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

특화지역코드법정동코드(변환)구분번지
01부산광역시 북구 덕천동1400-7
11부산광역시 북구 덕천동1400-8
21부산광역시 북구 덕천동1400-9
31부산광역시 북구 덕천동1400-10
41부산광역시 북구 덕천동1400-11
51부산광역시 북구 덕천동1400-12
61부산광역시 북구 덕천동1400-13
71부산광역시 북구 덕천동1400-14
81부산광역시 북구 덕천동1400-15
91부산광역시 북구 덕천동1400-18
특화지역코드법정동코드(변환)구분번지
151부산광역시 북구 덕천동1403-2
161부산광역시 북구 덕천동1403-3
171부산광역시 북구 덕천동1403-7
181부산광역시 북구 덕천동1403-9
191부산광역시 북구 덕천동1403-10
201부산광역시 북구 덕천동1403-25
211부산광역시 북구 덕천동1403-26
221부산광역시 북구 덕천동1403-31
231부산광역시 북구 덕천동1147-3
241부산광역시 북구 덕천동1147-5