Overview

Dataset statistics

Number of variables5
Number of observations47
Missing cells3
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory42.8 B

Variable types

Categorical1
Text4

Dataset

Description부산광역시북구_목욕장업현황_20221222
Author부산광역시 북구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3069426

Alerts

업종명 has constant value ""Constant
소재지전화 has 3 (6.4%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique
영업소 주소(지번) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:00:29.329537
Analysis finished2023-12-10 16:00:30.134420
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
목욕장업
47 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
목욕장업 47
100.0%

Length

2023-12-11T01:00:30.211860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:00:30.318506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 47
100.0%

업소명
Text

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T01:00:30.530600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.6595745
Min length2

Characters and Unicode

Total characters172
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)95.7%

Sample

1st row금곡탕
2nd row태양탕
3rd row제일탕
4th row백양탕
5th row화목탕
ValueCountFrequency (%)
금수탕 2
 
4.3%
오아시스사우나 1
 
2.1%
화명온천 1
 
2.1%
신덕탕 1
 
2.1%
옥금탕 1
 
2.1%
호산사우나 1
 
2.1%
새천년탕 1
 
2.1%
낙원탕 1
 
2.1%
황토대중탕 1
 
2.1%
보원목욕탕 1
 
2.1%
Other values (36) 36
76.6%
2023-12-11T01:00:30.921894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 38
22.1%
수 7
 
4.1%
금 5
 
2.9%
천 5
 
2.9%
동 4
 
2.3%
정 4
 
2.3%
화 4
 
2.3%
아 4
 
2.3%
우 4
 
2.3%
대 3
 
1.7%
Other values (68) 94
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 172
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 38
22.1%
수 7
 
4.1%
금 5
 
2.9%
천 5
 
2.9%
동 4
 
2.3%
정 4
 
2.3%
화 4
 
2.3%
아 4
 
2.3%
우 4
 
2.3%
대 3
 
1.7%
Other values (68) 94
54.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 172
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 38
22.1%
수 7
 
4.1%
금 5
 
2.9%
천 5
 
2.9%
동 4
 
2.3%
정 4
 
2.3%
화 4
 
2.3%
아 4
 
2.3%
우 4
 
2.3%
대 3
 
1.7%
Other values (68) 94
54.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 172
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 38
22.1%
수 7
 
4.1%
금 5
 
2.9%
천 5
 
2.9%
동 4
 
2.3%
정 4
 
2.3%
화 4
 
2.3%
아 4
 
2.3%
우 4
 
2.3%
대 3
 
1.7%
Other values (68) 94
54.7%

영업소 주소(도로명)
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T01:00:31.191051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length27.893617
Min length20

Characters and Unicode

Total characters1311
Distinct characters100
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row부산광역시 북구 만덕대로28번길 36 (덕천동)
2nd row부산광역시 북구 시랑로 70 (구포동)
3rd row부산광역시 북구 백양대로1172번길 5 (구포동)
4th row부산광역시 북구 덕천로312번길 8 (만덕동)
5th row부산광역시 북구 가람로8번길 8 (구포동)
ValueCountFrequency (%)
부산광역시 47
18.2%
북구 47
18.2%
구포동 17
 
6.6%
덕천동 9
 
3.5%
만덕동 8
 
3.1%
화명동 6
 
2.3%
금곡동 4
 
1.6%
8 3
 
1.2%
효열로 3
 
1.2%
시랑로 2
 
0.8%
Other values (104) 112
43.4%
2023-12-11T01:00:31.669048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
211
 
16.1%
구 67
 
5.1%
시 55
 
4.2%
동 53
 
4.0%
북 48
 
3.7%
) 48
 
3.7%
( 48
 
3.7%
산 48
 
3.7%
부 47
 
3.6%
광 47
 
3.6%
Other values (90) 639
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 761
58.0%
Decimal Number 215
 
16.4%
Space Separator 211
 
16.1%
Close Punctuation 48
 
3.7%
Open Punctuation 48
 
3.7%
Other Punctuation 22
 
1.7%
Dash Punctuation 4
 
0.3%
Math Symbol 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 67
 
8.8%
시 55
 
7.2%
동 53
 
7.0%
북 48
 
6.3%
산 48
 
6.3%
부 47
 
6.2%
광 47
 
6.2%
역 47
 
6.2%
로 43
 
5.7%
길 33
 
4.3%
Other values (72) 273
35.9%
Decimal Number
ValueCountFrequency (%)
1 46
21.4%
2 30
14.0%
3 29
13.5%
0 21
9.8%
8 20
9.3%
4 18
 
8.4%
5 17
 
7.9%
6 14
 
6.5%
7 11
 
5.1%
9 9
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 21
95.5%
@ 1
 
4.5%
Space Separator
ValueCountFrequency (%)
211
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 761
58.0%
Common 549
41.9%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 67
 
8.8%
시 55
 
7.2%
동 53
 
7.0%
북 48
 
6.3%
산 48
 
6.3%
부 47
 
6.2%
광 47
 
6.2%
역 47
 
6.2%
로 43
 
5.7%
길 33
 
4.3%
Other values (72) 273
35.9%
Common
ValueCountFrequency (%)
211
38.4%
) 48
 
8.7%
( 48
 
8.7%
1 46
 
8.4%
2 30
 
5.5%
3 29
 
5.3%
, 21
 
3.8%
0 21
 
3.8%
8 20
 
3.6%
4 18
 
3.3%
Other values (7) 57
 
10.4%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 761
58.0%
ASCII 550
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211
38.4%
) 48
 
8.7%
( 48
 
8.7%
1 46
 
8.4%
2 30
 
5.5%
3 29
 
5.3%
, 21
 
3.8%
0 21
 
3.8%
8 20
 
3.6%
4 18
 
3.3%
Other values (8) 58
 
10.5%
Hangul
ValueCountFrequency (%)
구 67
 
8.8%
시 55
 
7.2%
동 53
 
7.0%
북 48
 
6.3%
산 48
 
6.3%
부 47
 
6.2%
광 47
 
6.2%
역 47
 
6.2%
로 43
 
5.7%
길 33
 
4.3%
Other values (72) 273
35.9%

영업소 주소(지번)
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T01:00:31.933915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length32
Mean length23.276596
Min length18

Characters and Unicode

Total characters1094
Distinct characters67
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row부산광역시 북구 덕천동 415-14 T통B반
2nd row부산광역시 북구 구포동 1218-12
3rd row부산광역시 북구 구포동 610-6
4th row부산광역시 북구 만덕동 847-6
5th row부산광역시 북구 구포동 1054-5 T통B반
ValueCountFrequency (%)
부산광역시 47
21.0%
북구 47
21.0%
구포동 17
 
7.6%
t통b반 13
 
5.8%
덕천동 10
 
4.5%
만덕동 8
 
3.6%
화명동 7
 
3.1%
금곡동 5
 
2.2%
665-1 1
 
0.4%
201호 1
 
0.4%
Other values (68) 68
30.4%
2023-12-11T01:00:32.416601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
221
20.2%
구 64
 
5.9%
동 51
 
4.7%
산 49
 
4.5%
북 47
 
4.3%
1 47
 
4.3%
부 47
 
4.3%
시 47
 
4.3%
역 47
 
4.3%
광 47
 
4.3%
Other values (57) 427
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 548
50.1%
Decimal Number 242
22.1%
Space Separator 221
20.2%
Dash Punctuation 45
 
4.1%
Uppercase Letter 27
 
2.5%
Other Punctuation 7
 
0.6%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 64
11.7%
동 51
9.3%
산 49
8.9%
북 47
8.6%
부 47
8.6%
시 47
8.6%
역 47
8.6%
광 47
8.6%
덕 18
 
3.3%
포 18
 
3.3%
Other values (38) 113
20.6%
Decimal Number
ValueCountFrequency (%)
1 47
19.4%
4 30
12.4%
2 30
12.4%
8 23
9.5%
3 23
9.5%
5 20
8.3%
6 20
8.3%
9 17
 
7.0%
7 17
 
7.0%
0 15
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
B 13
48.1%
T 13
48.1%
A 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
@ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 548
50.1%
Common 519
47.4%
Latin 27
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 64
11.7%
동 51
9.3%
산 49
8.9%
북 47
8.6%
부 47
8.6%
시 47
8.6%
역 47
8.6%
광 47
8.6%
덕 18
 
3.3%
포 18
 
3.3%
Other values (38) 113
20.6%
Common
ValueCountFrequency (%)
221
42.6%
1 47
 
9.1%
- 45
 
8.7%
4 30
 
5.8%
2 30
 
5.8%
8 23
 
4.4%
3 23
 
4.4%
5 20
 
3.9%
6 20
 
3.9%
9 17
 
3.3%
Other values (6) 43
 
8.3%
Latin
ValueCountFrequency (%)
B 13
48.1%
T 13
48.1%
A 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 548
50.1%
ASCII 546
49.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
221
40.5%
1 47
 
8.6%
- 45
 
8.2%
4 30
 
5.5%
2 30
 
5.5%
8 23
 
4.2%
3 23
 
4.2%
5 20
 
3.7%
6 20
 
3.7%
9 17
 
3.1%
Other values (9) 70
 
12.8%
Hangul
ValueCountFrequency (%)
구 64
11.7%
동 51
9.3%
산 49
8.9%
북 47
8.6%
부 47
8.6%
시 47
8.6%
역 47
8.6%
광 47
8.6%
덕 18
 
3.3%
포 18
 
3.3%
Other values (38) 113
20.6%

소재지전화
Text

MISSING 

Distinct44
Distinct (%)100.0%
Missing3
Missing (%)6.4%
Memory size508.0 B
2023-12-11T01:00:32.730553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.022727
Min length12

Characters and Unicode

Total characters529
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

Unique44 ?
Unique (%)100.0%

Sample

1st row051-332-7848
2nd row051-332-2502
3rd row051-333-2526
4th row051-335-0135
5th row051-342-6623
ValueCountFrequency (%)
051-332-2502 1
 
2.3%
051-333-2526 1
 
2.3%
051-337-1589 1
 
2.3%
051-362-3755 1
 
2.3%
051-337-7035 1
 
2.3%
051-361-5355 1
 
2.3%
051-341-9990 1
 
2.3%
051-362-2000 1
 
2.3%
051-362-1136 1
 
2.3%
051-363-9788 1
 
2.3%
Other values (34) 34
77.3%
2023-12-11T01:00:33.169297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 94
17.8%
- 88
16.6%
5 72
13.6%
1 66
12.5%
0 65
12.3%
2 30
 
5.7%
6 29
 
5.5%
4 25
 
4.7%
8 23
 
4.3%
7 19
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 441
83.4%
Dash Punctuation 88
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 94
21.3%
5 72
16.3%
1 66
15.0%
0 65
14.7%
2 30
 
6.8%
6 29
 
6.6%
4 25
 
5.7%
8 23
 
5.2%
7 19
 
4.3%
9 18
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 529
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 94
17.8%
- 88
16.6%
5 72
13.6%
1 66
12.5%
0 65
12.3%
2 30
 
5.7%
6 29
 
5.5%
4 25
 
4.7%
8 23
 
4.3%
7 19
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 529
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 94
17.8%
- 88
16.6%
5 72
13.6%
1 66
12.5%
0 65
12.3%
2 30
 
5.7%
6 29
 
5.5%
4 25
 
4.7%
8 23
 
4.3%
7 19
 
3.6%

Correlations

2023-12-11T01:00:33.293060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)영업소 주소(지번)소재지전화
업소명1.0001.0001.0001.000
영업소 주소(도로명)1.0001.0001.0001.000
영업소 주소(지번)1.0001.0001.0001.000
소재지전화1.0001.0001.0001.000

Missing values

2023-12-11T01:00:29.968616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:00:30.085584image/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

업종명업소명영업소 주소(도로명)영업소 주소(지번)소재지전화
0목욕장업금곡탕부산광역시 북구 만덕대로28번길 36 (덕천동)부산광역시 북구 덕천동 415-14 T통B반051-332-7848
1목욕장업태양탕부산광역시 북구 시랑로 70 (구포동)부산광역시 북구 구포동 1218-12051-332-2502
2목욕장업제일탕부산광역시 북구 백양대로1172번길 5 (구포동)부산광역시 북구 구포동 610-6051-333-2526
3목욕장업백양탕부산광역시 북구 덕천로312번길 8 (만덕동)부산광역시 북구 만덕동 847-6051-335-0135
4목욕장업화목탕부산광역시 북구 가람로8번길 8 (구포동)부산광역시 북구 구포동 1054-5 T통B반051-342-6623
5목욕장업아주탕부산광역시 북구 기찰로129번길 52 (덕천동)부산광역시 북구 덕천동 369-1 T통B반051-334-8586
6목욕장업새한탕부산광역시 북구 의성로115번길 83 (덕천동)부산광역시 북구 덕천동 388-11051-334-0062
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