Overview

Dataset statistics

Number of variables4
Number of observations43
Missing cells5
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory35.1 B

Variable types

Categorical1
Text3

Dataset

Description부산광역시 북구 관내에 있는 목욕장업소 현황으로 목욕장의 업소명, 영업소 주소, 전화번호 등의 데이터를 제공합니다.
Author부산광역시 북구
URLhttps://www.data.go.kr/data/3069426/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 5 (11.6%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-16 15:50:05.885470
Analysis finished2023-12-16 15:50:08.479850
Duration2.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
목욕장업
43 

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 43
100.0%

Length

2023-12-16T15:50:08.818615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:50:09.334245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 43
100.0%

업소명
Text

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-16T15:50:10.113532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.8837209
Min length3

Characters and Unicode

Total characters167
Distinct characters76
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)95.3%

Sample

1st row금곡탕
2nd row태양탕
3rd row제일탕
4th row백양탕
5th row화목탕
ValueCountFrequency (%)
금수탕 2
 
4.4%
반도탕 1
 
2.2%
신덕탕 1
 
2.2%
호산사우나 1
 
2.2%
새천년탕 1
 
2.2%
낙원탕 1
 
2.2%
황토대중탕 1
 
2.2%
보원목욕탕 1
 
2.2%
낙천탕 1
 
2.2%
오아시스사우나 1
 
2.2%
Other values (34) 34
75.6%
2023-12-16T15:50:12.325730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 35
 
21.0%
수 6
 
3.6%
금 5
 
3.0%
천 5
 
3.0%
나 4
 
2.4%
아 4
 
2.4%
화 4
 
2.4%
동 4
 
2.4%
우 4
 
2.4%
사 4
 
2.4%
Other values (66) 92
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165
98.8%
Space Separator 2
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 35
 
21.2%
수 6
 
3.6%
금 5
 
3.0%
천 5
 
3.0%
나 4
 
2.4%
아 4
 
2.4%
화 4
 
2.4%
동 4
 
2.4%
우 4
 
2.4%
사 4
 
2.4%
Other values (65) 90
54.5%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165
98.8%
Common 2
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 35
 
21.2%
수 6
 
3.6%
금 5
 
3.0%
천 5
 
3.0%
나 4
 
2.4%
아 4
 
2.4%
화 4
 
2.4%
동 4
 
2.4%
우 4
 
2.4%
사 4
 
2.4%
Other values (65) 90
54.5%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165
98.8%
ASCII 2
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 35
 
21.2%
수 6
 
3.6%
금 5
 
3.0%
천 5
 
3.0%
나 4
 
2.4%
아 4
 
2.4%
화 4
 
2.4%
동 4
 
2.4%
우 4
 
2.4%
사 4
 
2.4%
Other values (65) 90
54.5%
ASCII
ValueCountFrequency (%)
2
100.0%

영업소 주소(도로명)
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-16T15:50:13.655675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length35
Mean length27.627907
Min length20

Characters and Unicode

Total characters1188
Distinct characters95
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
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 43
18.2%
북구 43
18.2%
구포동 17
 
7.2%
만덕동 8
 
3.4%
덕천동 7
 
3.0%
화명동 5
 
2.1%
금곡동 4
 
1.7%
효열로 3
 
1.3%
8 3
 
1.3%
29 2
 
0.8%
Other values (94) 101
42.8%
2023-12-16T15:50:16.205962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
193
 
16.2%
구 62
 
5.2%
동 49
 
4.1%
시 49
 
4.1%
) 44
 
3.7%
산 44
 
3.7%
( 44
 
3.7%
북 44
 
3.7%
부 43
 
3.6%
역 43
 
3.6%
Other values (85) 573
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 691
58.2%
Space Separator 193
 
16.2%
Decimal Number 193
 
16.2%
Close Punctuation 44
 
3.7%
Open Punctuation 44
 
3.7%
Other Punctuation 19
 
1.6%
Dash Punctuation 3
 
0.3%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 62
 
9.0%
동 49
 
7.1%
시 49
 
7.1%
산 44
 
6.4%
북 44
 
6.4%
부 43
 
6.2%
역 43
 
6.2%
광 43
 
6.2%
로 40
 
5.8%
길 29
 
4.2%
Other values (69) 245
35.5%
Decimal Number
ValueCountFrequency (%)
1 40
20.7%
2 26
13.5%
3 25
13.0%
0 19
9.8%
8 19
9.8%
4 16
 
8.3%
6 15
 
7.8%
5 15
 
7.8%
7 10
 
5.2%
9 8
 
4.1%
Space Separator
ValueCountFrequency (%)
193
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 691
58.2%
Common 497
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 62
 
9.0%
동 49
 
7.1%
시 49
 
7.1%
산 44
 
6.4%
북 44
 
6.4%
부 43
 
6.2%
역 43
 
6.2%
광 43
 
6.2%
로 40
 
5.8%
길 29
 
4.2%
Other values (69) 245
35.5%
Common
ValueCountFrequency (%)
193
38.8%
) 44
 
8.9%
( 44
 
8.9%
1 40
 
8.0%
2 26
 
5.2%
3 25
 
5.0%
0 19
 
3.8%
, 19
 
3.8%
8 19
 
3.8%
4 16
 
3.2%
Other values (6) 52
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 691
58.2%
ASCII 497
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
193
38.8%
) 44
 
8.9%
( 44
 
8.9%
1 40
 
8.0%
2 26
 
5.2%
3 25
 
5.0%
0 19
 
3.8%
, 19
 
3.8%
8 19
 
3.8%
4 16
 
3.2%
Other values (6) 52
 
10.5%
Hangul
ValueCountFrequency (%)
구 62
 
9.0%
동 49
 
7.1%
시 49
 
7.1%
산 44
 
6.4%
북 44
 
6.4%
부 43
 
6.2%
역 43
 
6.2%
광 43
 
6.2%
로 40
 
5.8%
길 29
 
4.2%
Other values (69) 245
35.5%

소재지전화
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing5
Missing (%)11.6%
Memory size476.0 B
2023-12-16T15:50:17.312078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters456
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

Unique38 ?
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 (%)
051-331-7455 1
 
2.6%
051-331-2100 1
 
2.6%
051-364-5353 1
 
2.6%
051-362-3755 1
 
2.6%
051-337-7035 1
 
2.6%
051-361-5355 1
 
2.6%
051-341-9990 1
 
2.6%
051-362-2000 1
 
2.6%
051-362-1136 1
 
2.6%
051-997-5599 1
 
2.6%
Other values (28) 28
73.7%
2023-12-16T15:50:19.182557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 82
18.0%
- 76
16.7%
5 66
14.5%
1 60
13.2%
0 55
12.1%
2 22
 
4.8%
6 22
 
4.8%
4 19
 
4.2%
7 18
 
3.9%
9 18
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 380
83.3%
Dash Punctuation 76
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 82
21.6%
5 66
17.4%
1 60
15.8%
0 55
14.5%
2 22
 
5.8%
6 22
 
5.8%
4 19
 
5.0%
7 18
 
4.7%
9 18
 
4.7%
8 18
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 456
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 82
18.0%
- 76
16.7%
5 66
14.5%
1 60
13.2%
0 55
12.1%
2 22
 
4.8%
6 22
 
4.8%
4 19
 
4.2%
7 18
 
3.9%
9 18
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 82
18.0%
- 76
16.7%
5 66
14.5%
1 60
13.2%
0 55
12.1%
2 22
 
4.8%
6 22
 
4.8%
4 19
 
4.2%
7 18
 
3.9%
9 18
 
3.9%

Correlations

2023-12-16T15:50:19.815374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)소재지전화
업소명1.0001.0001.000
영업소 주소(도로명)1.0001.0001.000
소재지전화1.0001.0001.000

Missing values

2023-12-16T15:50:07.519593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:50:08.168174image/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)소재지전화
0목욕장업금곡탕부산광역시 북구 만덕대로28번길 36 (덕천동)051-332-7848
1목욕장업태양탕부산광역시 북구 시랑로 70 (구포동)051-332-2502
2목욕장업제일탕부산광역시 북구 백양대로1172번길 5 (구포동)051-333-2526
3목욕장업백양탕부산광역시 북구 덕천로312번길 8 (만덕동)051-335-0135
4목욕장업화목탕부산광역시 북구 가람로8번길 8 (구포동)051-342-6623
5목욕장업아주탕부산광역시 북구 기찰로129번길 52 (덕천동)051-334-8586
6목욕장업대진탕부산광역시 북구 만덕1로51번길 53 (만덕동)051-334-3037
7목욕장업금수탕부산광역시 북구 약초골목길 29 (구포동)051-334-8525
8목욕장업수용탕부산광역시 북구 구포시장길 76 (구포동)<NA>
9목욕장업낙동탕부산광역시 북구 의성로59번길 9 (덕천동)051-331-7455
업종명업소명영업소 주소(도로명)소재지전화
33목욕장업신덕탕부산광역시 북구 함박봉로140번길 8 (만덕동)051-341-7079
34목욕장업동민탕부산광역시 북구 의성로109번길 38 (덕천동)051-364-5901
35목욕장업맑은샘부산광역시 북구 시랑로79번길 17 (구포동)051-338-8801
36목욕장업청정탕부산광역시 북구 백양대로1015번길 20 (구포동)051-332-2666
37목욕장업녹천탕부산광역시 북구 시랑로36번길 16 (구포동)051-336-7309
38목욕장업리치웰휘트니스덕천스파부산광역시 북구 금곡대로8번길 33 (덕천동,아남프라자 3층)051-997-5599
39목욕장업동해탕부산광역시 북구 만덕1로104번가길 54 (만덕동)<NA>
40목욕장업화명온천부산광역시 북구 와석장터로 20, 1~3층 (화명동)051-361-9793
41목욕장업삼한탕부산광역시 북구 화명대로 101, 118동 지하1층 101호 (화명동, 삼한힐파크)<NA>
42목욕장업티티호텔 구포 사우나부산광역시 북구 낙동대로 1684, 3,4층 (구포동)<NA>