Overview

Dataset statistics

Number of variables5
Number of observations54
Missing cells2
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory43.4 B

Variable types

Categorical1
Text3
Numeric1

Dataset

Description부산광역시 남구 목욕장업의 현황에 대한 데이터로써 업종, 업소명, 주소, 전화번호, 우편번호 등 자료를 제공합니다.
URLhttps://www.data.go.kr/data/15050537/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 2 (3.7%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:33:03.646833
Analysis finished2023-12-12 03:33:04.300196
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
목욕장업
54 

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 54
100.0%

Length

2023-12-12T12:33:04.364712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:33:04.458949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 54
100.0%

업소명
Text

Distinct52
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T12:33:04.710419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length4.1296296
Min length3

Characters and Unicode

Total characters223
Distinct characters95
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

Unique50 ?
Unique (%)92.6%

Sample

1st row석포탕
2nd row거북탕
3rd row선녀탕
4th row복천탕
5th row백운탕
ValueCountFrequency (%)
현대탕 2
 
3.6%
평화탕 2
 
3.6%
주)센츄리스포렉스 1
 
1.8%
부경해수탕 1
 
1.8%
석포탕 1
 
1.8%
약수탕 1
 
1.8%
금강탕 1
 
1.8%
용호레포츠 1
 
1.8%
신선해수탕 1
 
1.8%
수목탕 1
 
1.8%
Other values (44) 44
78.6%
2023-12-12T12:33:05.187976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 42
 
18.8%
수 10
 
4.5%
우 8
 
3.6%
용 7
 
3.1%
나 6
 
2.7%
사 6
 
2.7%
화 5
 
2.2%
천 5
 
2.2%
대 5
 
2.2%
성 5
 
2.2%
Other values (85) 124
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 214
96.0%
Close Punctuation 3
 
1.3%
Space Separator 3
 
1.3%
Open Punctuation 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 42
 
19.6%
수 10
 
4.7%
우 8
 
3.7%
용 7
 
3.3%
나 6
 
2.8%
사 6
 
2.8%
화 5
 
2.3%
천 5
 
2.3%
대 5
 
2.3%
성 5
 
2.3%
Other values (82) 115
53.7%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 214
96.0%
Common 9
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 42
 
19.6%
수 10
 
4.7%
우 8
 
3.7%
용 7
 
3.3%
나 6
 
2.8%
사 6
 
2.8%
화 5
 
2.3%
천 5
 
2.3%
대 5
 
2.3%
성 5
 
2.3%
Other values (82) 115
53.7%
Common
ValueCountFrequency (%)
) 3
33.3%
3
33.3%
( 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 214
96.0%
ASCII 9
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 42
 
19.6%
수 10
 
4.7%
우 8
 
3.7%
용 7
 
3.3%
나 6
 
2.8%
사 6
 
2.8%
화 5
 
2.3%
천 5
 
2.3%
대 5
 
2.3%
성 5
 
2.3%
Other values (82) 115
53.7%
ASCII
ValueCountFrequency (%)
) 3
33.3%
3
33.3%
( 3
33.3%

영업소 주소(도로명)
Text

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T12:33:05.524237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length36
Mean length26.925926
Min length20

Characters and Unicode

Total characters1454
Distinct characters94
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

Unique54 ?
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 용주로 5 (용호동)
ValueCountFrequency (%)
부산광역시 54
19.2%
남구 54
19.2%
대연동 17
 
6.0%
용호동 13
 
4.6%
문현동 9
 
3.2%
감만동 6
 
2.1%
49 3
 
1.1%
10 3
 
1.1%
용당동 3
 
1.1%
5 3
 
1.1%
Other values (105) 116
41.3%
2023-12-12T12:33:06.121024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
227
 
15.6%
동 62
 
4.3%
남 58
 
4.0%
) 55
 
3.8%
( 55
 
3.8%
시 55
 
3.8%
로 54
 
3.7%
부 54
 
3.7%
구 54
 
3.7%
역 54
 
3.7%
Other values (84) 726
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 846
58.2%
Decimal Number 243
 
16.7%
Space Separator 227
 
15.6%
Close Punctuation 55
 
3.8%
Open Punctuation 55
 
3.8%
Other Punctuation 16
 
1.1%
Dash Punctuation 12
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 62
 
7.3%
남 58
 
6.9%
시 55
 
6.5%
로 54
 
6.4%
부 54
 
6.4%
구 54
 
6.4%
역 54
 
6.4%
광 54
 
6.4%
산 54
 
6.4%
번 39
 
4.6%
Other values (69) 308
36.4%
Decimal Number
ValueCountFrequency (%)
1 51
21.0%
6 31
12.8%
2 29
11.9%
3 28
11.5%
4 22
9.1%
0 20
 
8.2%
7 18
 
7.4%
9 15
 
6.2%
5 15
 
6.2%
8 14
 
5.8%
Space Separator
ValueCountFrequency (%)
227
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 846
58.2%
Common 608
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 62
 
7.3%
남 58
 
6.9%
시 55
 
6.5%
로 54
 
6.4%
부 54
 
6.4%
구 54
 
6.4%
역 54
 
6.4%
광 54
 
6.4%
산 54
 
6.4%
번 39
 
4.6%
Other values (69) 308
36.4%
Common
ValueCountFrequency (%)
227
37.3%
) 55
 
9.0%
( 55
 
9.0%
1 51
 
8.4%
6 31
 
5.1%
2 29
 
4.8%
3 28
 
4.6%
4 22
 
3.6%
0 20
 
3.3%
7 18
 
3.0%
Other values (5) 72
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 846
58.2%
ASCII 608
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
227
37.3%
) 55
 
9.0%
( 55
 
9.0%
1 51
 
8.4%
6 31
 
5.1%
2 29
 
4.8%
3 28
 
4.6%
4 22
 
3.6%
0 20
 
3.3%
7 18
 
3.0%
Other values (5) 72
 
11.8%
Hangul
ValueCountFrequency (%)
동 62
 
7.3%
남 58
 
6.9%
시 55
 
6.5%
로 54
 
6.4%
부 54
 
6.4%
구 54
 
6.4%
역 54
 
6.4%
광 54
 
6.4%
산 54
 
6.4%
번 39
 
4.6%
Other values (69) 308
36.4%

우편번호(도로명)
Real number (ℝ)

Distinct46
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48503.204
Minimum48400
Maximum48591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T12:33:06.408514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48400
5-th percentile48417.65
Q148446
median48509
Q348549.5
95-th percentile48584.7
Maximum48591
Range191
Interquartile range (IQR)103.5

Descriptive statistics

Standard deviation58.581786
Coefficient of variation (CV)0.0012077921
Kurtosis-1.3139807
Mean48503.204
Median Absolute Deviation (MAD)50.5
Skewness-0.14982892
Sum2619173
Variance3431.8256
MonotonicityNot monotonic
2023-12-12T12:33:06.599326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
48580 2
 
3.7%
48539 2
 
3.7%
48591 2
 
3.7%
48501 2
 
3.7%
48485 2
 
3.7%
48548 2
 
3.7%
48436 2
 
3.7%
48418 2
 
3.7%
48445 1
 
1.9%
48584 1
 
1.9%
Other values (36) 36
66.7%
ValueCountFrequency (%)
48400 1
1.9%
48416 1
1.9%
48417 1
1.9%
48418 2
3.7%
48419 1
1.9%
48422 1
1.9%
48423 1
1.9%
48427 1
1.9%
48436 2
3.7%
48438 1
1.9%
ValueCountFrequency (%)
48591 2
3.7%
48586 1
1.9%
48584 1
1.9%
48582 1
1.9%
48580 2
3.7%
48578 1
1.9%
48573 1
1.9%
48566 1
1.9%
48564 1
1.9%
48554 1
1.9%

소재지전화
Text

MISSING 

Distinct52
Distinct (%)100.0%
Missing2
Missing (%)3.7%
Memory size564.0 B
2023-12-12T12:33:06.873982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.961538
Min length12

Characters and Unicode

Total characters726
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

Unique52 ?
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- 624-1006
ValueCountFrequency (%)
051 51
42.5%
621 2
 
1.7%
611 2
 
1.7%
626 2
 
1.7%
646 2
 
1.7%
632 2
 
1.7%
634-1865 1
 
0.8%
647-9030 1
 
0.8%
623-5229 1
 
0.8%
642-4951 1
 
0.8%
Other values (55) 55
45.8%
2023-12-12T12:33:07.379796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 104
14.3%
102
14.0%
1 91
12.5%
0 85
11.7%
6 84
11.6%
5 76
10.5%
2 53
7.3%
3 36
 
5.0%
4 30
 
4.1%
7 24
 
3.3%
Other values (2) 41
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
71.6%
Dash Punctuation 104
 
14.3%
Space Separator 102
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 91
17.5%
0 85
16.3%
6 84
16.2%
5 76
14.6%
2 53
10.2%
3 36
 
6.9%
4 30
 
5.8%
7 24
 
4.6%
8 22
 
4.2%
9 19
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Space Separator
ValueCountFrequency (%)
102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 726
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 104
14.3%
102
14.0%
1 91
12.5%
0 85
11.7%
6 84
11.6%
5 76
10.5%
2 53
7.3%
3 36
 
5.0%
4 30
 
4.1%
7 24
 
3.3%
Other values (2) 41
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 104
14.3%
102
14.0%
1 91
12.5%
0 85
11.7%
6 84
11.6%
5 76
10.5%
2 53
7.3%
3 36
 
5.0%
4 30
 
4.1%
7 24
 
3.3%
Other values (2) 41
 
5.6%

Interactions

2023-12-12T12:33:03.962727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:33:07.509864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)우편번호(도로명)소재지전화
업소명1.0001.0000.8661.000
영업소 주소(도로명)1.0001.0001.0001.000
우편번호(도로명)0.8661.0001.0001.000
소재지전화1.0001.0001.0001.000

Missing values

2023-12-12T12:33:04.134573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:33:04.260126image/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
4목욕장업백운탕부산광역시 남구 용주로 5 (용호동)48591051- 624-1006
5목욕장업평안탕부산광역시 남구 용호로177번길 17 (용호동)48586051- 623-6698
6목욕장업용림탕부산광역시 남구 동명로100번길 12 (용호동)48564051 -625 -4539
7목욕장업성호탕부산광역시 남구 동명로145번길 60 (용호동)48578051- 622-3479
8목욕장업천지탕부산광역시 남구 수영로39번길 24 (문현동)48419051- 645-3420
9목욕장업산수탕부산광역시 남구 장고개로67번길 22 (문현동)48477051 -632 -0917
업종명업소명영업소 주소(도로명)우편번호(도로명)소재지전화
44목욕장업베르디사우나부산광역시 남구 수영로249번길 3, 3,4층 (대연동, 베르디하우스)48444051- 627-8800
45목욕장업(주)중앙해수랜드부산광역시 남구 용호로 64 (용호동)48523051- 622-8899
46목욕장업용호헬스사우나부산광역시 남구 용호로159번길 108 (용호동, 승진빌딩)48582051- 627-6339
47목욕장업삼육탕부산광역시 남구 이기대공원로26번길 45-4 (용호동)48580051 -626 -4537
48목욕장업대림찜질사우나부산광역시 남구 수영로 26, 지하1층 (문현동, 대림문현시티프라자)48456051 -644 -0603
49목욕장업아바니핏부산광역시 남구 전포대로 133, 6층 (문현동)48400051-791-5890
50목욕장업대영온천부산광역시 남구 황령대로492번길 10 (대연동)48510051 -611 -0090
51목욕장업문화불한증막부산광역시 남구 유엔평화로 111, 지하1층 (대연동)48531051 -627 -6605
52목욕장업(주)벽승 명성사우나부산광역시 남구 유엔평화로 150, 한신문화타운 2층 (용당동)48535<NA>
53목욕장업우리탕부산광역시 남구 못골로53번길 34, 우리탕 1층 (대연동)48438<NA>