Overview

Dataset statistics

Number of variables5
Number of observations57
Missing cells2
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory43.3 B

Variable types

Categorical1
Text3
Numeric1

Dataset

Description부산광역시남구_목욕장업현황_20220630
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15050537

Alerts

업종명 has constant value ""Constant
소재지전화 has 2 (3.5%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:29:58.515204
Analysis finished2023-12-10 16:29:59.348680
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
목욕장업
57 

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 57
100.0%

Length

2023-12-11T01:29:59.464353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:29:59.616323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 57
100.0%

업소명
Text

Distinct54
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-11T01:29:59.945122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length4.1578947
Min length3

Characters and Unicode

Total characters237
Distinct characters91
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

Unique51 ?
Unique (%)89.5%

Sample

1st row석포탕
2nd row거북탕
3rd row선녀탕
4th row복천탕
5th row삼성탕
ValueCountFrequency (%)
석천탕 2
 
3.4%
현대탕 2
 
3.4%
평화탕 2
 
3.4%
대영온천 1
 
1.7%
주)동진스포렉스 1
 
1.7%
주)벽승 1
 
1.7%
명성사우나 1
 
1.7%
못골헬스찜질사우나 1
 
1.7%
석포탕 1
 
1.7%
부경해수탕 1
 
1.7%
Other values (46) 46
78.0%
2023-12-11T01:30:00.456644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 45
 
19.0%
수 10
 
4.2%
우 8
 
3.4%
용 7
 
3.0%
나 6
 
2.5%
사 6
 
2.5%
성 6
 
2.5%
스 6
 
2.5%
천 6
 
2.5%
화 5
 
2.1%
Other values (81) 132
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 226
95.4%
Close Punctuation 4
 
1.7%
Open Punctuation 4
 
1.7%
Space Separator 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 45
 
19.9%
수 10
 
4.4%
우 8
 
3.5%
용 7
 
3.1%
나 6
 
2.7%
사 6
 
2.7%
성 6
 
2.7%
스 6
 
2.7%
천 6
 
2.7%
화 5
 
2.2%
Other values (78) 121
53.5%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 226
95.4%
Common 11
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 45
 
19.9%
수 10
 
4.4%
우 8
 
3.5%
용 7
 
3.1%
나 6
 
2.7%
사 6
 
2.7%
성 6
 
2.7%
스 6
 
2.7%
천 6
 
2.7%
화 5
 
2.2%
Other values (78) 121
53.5%
Common
ValueCountFrequency (%)
) 4
36.4%
( 4
36.4%
3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 226
95.4%
ASCII 11
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 45
 
19.9%
수 10
 
4.4%
우 8
 
3.5%
용 7
 
3.1%
나 6
 
2.7%
사 6
 
2.7%
성 6
 
2.7%
스 6
 
2.7%
천 6
 
2.7%
화 5
 
2.2%
Other values (78) 121
53.5%
ASCII
ValueCountFrequency (%)
) 4
36.4%
( 4
36.4%
3
27.3%

영업소 주소(도로명)
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-11T01:30:00.820442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length36
Mean length26.877193
Min length20

Characters and Unicode

Total characters1532
Distinct characters93
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row부산광역시 남구 석포로91번길 8 (대연동)
2nd row부산광역시 남구 수영로266번길 98-3 (대연동)
3rd row부산광역시 남구 석포로 66-1 (감만동)
4th row부산광역시 남구 우암로176번길 2 (우암동,77-6)
5th row부산광역시 남구 황령대로74번길 97-10 (문현동)
ValueCountFrequency (%)
부산광역시 57
19.3%
남구 57
19.3%
대연동 18
 
6.1%
용호동 13
 
4.4%
문현동 11
 
3.7%
감만동 6
 
2.0%
용당동 3
 
1.0%
49 3
 
1.0%
10 3
 
1.0%
5 3
 
1.0%
Other values (108) 121
41.0%
2023-12-11T01:30:01.336622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
238
 
15.5%
동 67
 
4.4%
남 61
 
4.0%
( 58
 
3.8%
시 58
 
3.8%
) 58
 
3.8%
부 57
 
3.7%
광 57
 
3.7%
역 57
 
3.7%
구 57
 
3.7%
Other values (83) 764
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 894
58.4%
Decimal Number 256
 
16.7%
Space Separator 238
 
15.5%
Open Punctuation 58
 
3.8%
Close Punctuation 58
 
3.8%
Other Punctuation 15
 
1.0%
Dash Punctuation 13
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 67
 
7.5%
남 61
 
6.8%
시 58
 
6.5%
부 57
 
6.4%
광 57
 
6.4%
역 57
 
6.4%
구 57
 
6.4%
산 57
 
6.4%
로 57
 
6.4%
번 42
 
4.7%
Other values (68) 324
36.2%
Decimal Number
ValueCountFrequency (%)
1 54
21.1%
2 30
11.7%
6 30
11.7%
3 29
11.3%
4 23
9.0%
7 22
8.6%
0 21
 
8.2%
9 18
 
7.0%
5 15
 
5.9%
8 14
 
5.5%
Space Separator
ValueCountFrequency (%)
238
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 894
58.4%
Common 638
41.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 67
 
7.5%
남 61
 
6.8%
시 58
 
6.5%
부 57
 
6.4%
광 57
 
6.4%
역 57
 
6.4%
구 57
 
6.4%
산 57
 
6.4%
로 57
 
6.4%
번 42
 
4.7%
Other values (68) 324
36.2%
Common
ValueCountFrequency (%)
238
37.3%
( 58
 
9.1%
) 58
 
9.1%
1 54
 
8.5%
2 30
 
4.7%
6 30
 
4.7%
3 29
 
4.5%
4 23
 
3.6%
7 22
 
3.4%
0 21
 
3.3%
Other values (5) 75
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 894
58.4%
ASCII 638
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
238
37.3%
( 58
 
9.1%
) 58
 
9.1%
1 54
 
8.5%
2 30
 
4.7%
6 30
 
4.7%
3 29
 
4.5%
4 23
 
3.6%
7 22
 
3.4%
0 21
 
3.3%
Other values (5) 75
 
11.8%
Hangul
ValueCountFrequency (%)
동 67
 
7.5%
남 61
 
6.8%
시 58
 
6.5%
부 57
 
6.4%
광 57
 
6.4%
역 57
 
6.4%
구 57
 
6.4%
산 57
 
6.4%
로 57
 
6.4%
번 42
 
4.7%
Other values (68) 324
36.2%

우편번호(도로명)
Real number (ℝ)

Distinct48
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48499.526
Minimum48405
Maximum48591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-11T01:30:01.536803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48405
5-th percentile48416.8
Q148444
median48501
Q348548
95-th percentile48584.4
Maximum48591
Range186
Interquartile range (IQR)104

Descriptive statistics

Standard deviation59.244079
Coefficient of variation (CV)0.0012215393
Kurtosis-1.3847908
Mean48499.526
Median Absolute Deviation (MAD)52
Skewness-0.047968953
Sum2764473
Variance3509.8609
MonotonicityNot monotonic
2023-12-11T01:30:01.723490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
48485 2
 
3.5%
48436 2
 
3.5%
48418 2
 
3.5%
48501 2
 
3.5%
48548 2
 
3.5%
48427 2
 
3.5%
48580 2
 
3.5%
48539 2
 
3.5%
48591 2
 
3.5%
48550 1
 
1.8%
Other values (38) 38
66.7%
ValueCountFrequency (%)
48405 1
1.8%
48411 1
1.8%
48416 1
1.8%
48417 1
1.8%
48418 2
3.5%
48419 1
1.8%
48422 1
1.8%
48423 1
1.8%
48427 2
3.5%
48436 2
3.5%
ValueCountFrequency (%)
48591 2
3.5%
48586 1
1.8%
48584 1
1.8%
48582 1
1.8%
48580 2
3.5%
48578 1
1.8%
48573 1
1.8%
48566 1
1.8%
48564 1
1.8%
48554 1
1.8%

소재지전화
Text

MISSING 

Distinct55
Distinct (%)100.0%
Missing2
Missing (%)3.5%
Memory size588.0 B
2023-12-11T01:30:01.960197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters770
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)100.0%

Sample

1st row 051- 626-7452
2nd row 051- 623-1696
3rd row051 -635 -9042
4th row 051- 646-1853
5th row 051- 646-0311
ValueCountFrequency (%)
051 55
42.6%
646 2
 
1.6%
611 2
 
1.6%
632 2
 
1.6%
626 2
 
1.6%
621 2
 
1.6%
634-1865 1
 
0.8%
647-9030 1
 
0.8%
623-5229 1
 
0.8%
642-4951 1
 
0.8%
Other values (60) 60
46.5%
2023-12-11T01:30:02.297781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110
14.3%
- 110
14.3%
1 96
12.5%
6 91
11.8%
0 88
11.4%
5 79
10.3%
2 56
7.3%
3 41
 
5.3%
4 33
 
4.3%
7 24
 
3.1%
Other values (2) 42
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 550
71.4%
Space Separator 110
 
14.3%
Dash Punctuation 110
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 96
17.5%
6 91
16.5%
0 88
16.0%
5 79
14.4%
2 56
10.2%
3 41
7.5%
4 33
 
6.0%
7 24
 
4.4%
8 23
 
4.2%
9 19
 
3.5%
Space Separator
ValueCountFrequency (%)
110
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 770
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
110
14.3%
- 110
14.3%
1 96
12.5%
6 91
11.8%
0 88
11.4%
5 79
10.3%
2 56
7.3%
3 41
 
5.3%
4 33
 
4.3%
7 24
 
3.1%
Other values (2) 42
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 770
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110
14.3%
- 110
14.3%
1 96
12.5%
6 91
11.8%
0 88
11.4%
5 79
10.3%
2 56
7.3%
3 41
 
5.3%
4 33
 
4.3%
7 24
 
3.1%
Other values (2) 42
 
5.5%

Interactions

2023-12-11T01:29:58.909752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:30:02.401591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)우편번호(도로명)소재지전화
업소명1.0001.0000.9331.000
영업소 주소(도로명)1.0001.0001.0001.000
우편번호(도로명)0.9331.0001.0001.000
소재지전화1.0001.0001.0001.000

Missing values

2023-12-11T01:29:59.116140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:29:59.282594image/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)우편번호(도로명)소재지전화
0목욕장업석포탕부산광역시 남구 석포로91번길 8 (대연동)48486051- 626-7452
1목욕장업거북탕부산광역시 남구 수영로266번길 98-3 (대연동)48501051- 623-1696
2목욕장업선녀탕부산광역시 남구 석포로 66-1 (감만동)48539051 -635 -9042
3목욕장업복천탕부산광역시 남구 우암로176번길 2 (우암동,77-6)48469051- 646-1853
4목욕장업삼성탕부산광역시 남구 황령대로74번길 97-10 (문현동)48411051- 646-0311
5목욕장업백운탕부산광역시 남구 용주로 5 (용호동)48591051- 624-1006
6목욕장업평안탕부산광역시 남구 용호로177번길 17 (용호동)48586051- 623-6698
7목욕장업용림탕부산광역시 남구 동명로100번길 12 (용호동)48564051 -625 -4539
8목욕장업성호탕부산광역시 남구 동명로145번길 60 (용호동)48578051- 622-3479
9목욕장업천지탕부산광역시 남구 수영로39번길 24 (문현동)48419051- 645-3420
업종명업소명영업소 주소(도로명)우편번호(도로명)소재지전화
47목욕장업베르디사우나부산광역시 남구 수영로249번길 3, 3,4층 (대연동, 베르디하우스)48444051- 627-8800
48목욕장업(주)중앙해수랜드부산광역시 남구 용호로 64 (용호동)48523051- 622-8899
49목욕장업용호헬스사우나부산광역시 남구 용호로159번길 108 (용호동, 승진빌딩)48582051- 627-6339
50목욕장업삼육탕부산광역시 남구 이기대공원로26번길 45-4 (용호동)48580051 -626 -4537
51목욕장업대림찜질사우나부산광역시 남구 수영로 26, 지하1층 (문현동, 대림문현시티프라자)48456051 -644 -0603
52목욕장업(주)동진스포렉스부산광역시 남구 황령대로319번가길 137 (대연동)48427051 -623 -9696
53목욕장업대영온천부산광역시 남구 황령대로492번길 10 (대연동)48510051 -611 -0090
54목욕장업문화불한증막부산광역시 남구 유엔평화로 111, 지하1층 (대연동)48531051 -627 -6605
55목욕장업(주)벽승 명성사우나부산광역시 남구 유엔평화로 150, 한신문화타운 2층 (용당동)48535<NA>
56목욕장업우리탕부산광역시 남구 못골로53번길 34, 우리탕 1층 (대연동)48438<NA>