Overview

Dataset statistics

Number of variables4
Number of observations38
Missing cells3
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory35.5 B

Variable types

Categorical1
Text3

Dataset

Description부산광역시_서구_공중목욕탕현황_20220412
Author부산광역시 서구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15055156

Alerts

업종명 has constant value ""Constant
소재지전화 has 3 (7.9%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:56:34.169389
Analysis finished2023-12-10 16:56:34.748891
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
목욕장업
38 

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 38
100.0%

Length

2023-12-11T01:56:34.863652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:35.062416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 38
100.0%

업소명
Text

Distinct36
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-11T01:56:35.471593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.7105263
Min length3

Characters and Unicode

Total characters141
Distinct characters65
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

Unique34 ?
Unique (%)89.5%

Sample

1st row늘푸른스파동광
2nd row대영탕
3rd row동아탕
4th row부산탕
5th row서호탕
ValueCountFrequency (%)
대영탕 2
 
5.0%
부산탕 2
 
5.0%
까치탕 1
 
2.5%
삼익탕 1
 
2.5%
대명탕 1
 
2.5%
대성탕 1
 
2.5%
산수탕 1
 
2.5%
정휴탕 1
 
2.5%
장수탕 1
 
2.5%
약수탕 1
 
2.5%
Other values (28) 28
70.0%
2023-12-11T01:56:36.101722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 32
22.7%
수 6
 
4.3%
부 5
 
3.5%
천 4
 
2.8%
대 4
 
2.8%
산 4
 
2.8%
성 3
 
2.1%
나 3
 
2.1%
우 3
 
2.1%
사 3
 
2.1%
Other values (55) 74
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
98.6%
Space Separator 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 32
23.0%
수 6
 
4.3%
부 5
 
3.6%
천 4
 
2.9%
대 4
 
2.9%
산 4
 
2.9%
성 3
 
2.2%
나 3
 
2.2%
우 3
 
2.2%
사 3
 
2.2%
Other values (54) 72
51.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139
98.6%
Common 2
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 32
23.0%
수 6
 
4.3%
부 5
 
3.6%
천 4
 
2.9%
대 4
 
2.9%
산 4
 
2.9%
성 3
 
2.2%
나 3
 
2.2%
우 3
 
2.2%
사 3
 
2.2%
Other values (54) 72
51.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
98.6%
ASCII 2
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 32
23.0%
수 6
 
4.3%
부 5
 
3.6%
천 4
 
2.9%
대 4
 
2.9%
산 4
 
2.9%
성 3
 
2.2%
나 3
 
2.2%
우 3
 
2.2%
사 3
 
2.2%
Other values (54) 72
51.8%
ASCII
ValueCountFrequency (%)
2
100.0%

영업소 주소(도로명)
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-11T01:56:36.597035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28.5
Mean length26.578947
Min length21

Characters and Unicode

Total characters1010
Distinct characters63
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

Unique38 ?
Unique (%)100.0%

Sample

1st row부산광역시 서구 충무시장길 58 (충무동3가)
2nd row부산광역시 서구 대영로86번길 4 (동대신동1가)
3rd row부산광역시 서구 보수대로 262 (동대신동3가)
4th row부산광역시 서구 구덕로280번길 56 (동대신동1가)
5th row부산광역시 서구 까치고개로198번길 13 (아미동2가)
ValueCountFrequency (%)
부산광역시 38
19.9%
서구 38
19.9%
남부민동 8
 
4.2%
아미동2가 5
 
2.6%
서대신동3가 4
 
2.1%
해돋이로 3
 
1.6%
동대신동2가 3
 
1.6%
동대신동3가 3
 
1.6%
동대신동1가 2
 
1.0%
33 2
 
1.0%
Other values (74) 85
44.5%
2023-12-11T01:56:37.375478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
153
 
15.1%
부 49
 
4.9%
동 48
 
4.8%
구 46
 
4.6%
서 45
 
4.5%
시 41
 
4.1%
1 39
 
3.9%
( 38
 
3.8%
광 38
 
3.8%
역 38
 
3.8%
Other values (53) 475
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 609
60.3%
Decimal Number 166
 
16.4%
Space Separator 153
 
15.1%
Open Punctuation 38
 
3.8%
Close Punctuation 38
 
3.8%
Dash Punctuation 4
 
0.4%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 49
 
8.0%
동 48
 
7.9%
구 46
 
7.6%
서 45
 
7.4%
시 41
 
6.7%
광 38
 
6.2%
역 38
 
6.2%
산 38
 
6.2%
로 33
 
5.4%
가 26
 
4.3%
Other values (38) 207
34.0%
Decimal Number
ValueCountFrequency (%)
1 39
23.5%
2 28
16.9%
3 27
16.3%
6 14
 
8.4%
5 13
 
7.8%
9 12
 
7.2%
4 10
 
6.0%
8 10
 
6.0%
0 8
 
4.8%
7 5
 
3.0%
Space Separator
ValueCountFrequency (%)
153
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 609
60.3%
Common 401
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 49
 
8.0%
동 48
 
7.9%
구 46
 
7.6%
서 45
 
7.4%
시 41
 
6.7%
광 38
 
6.2%
역 38
 
6.2%
산 38
 
6.2%
로 33
 
5.4%
가 26
 
4.3%
Other values (38) 207
34.0%
Common
ValueCountFrequency (%)
153
38.2%
1 39
 
9.7%
( 38
 
9.5%
) 38
 
9.5%
2 28
 
7.0%
3 27
 
6.7%
6 14
 
3.5%
5 13
 
3.2%
9 12
 
3.0%
4 10
 
2.5%
Other values (5) 29
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 609
60.3%
ASCII 401
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
153
38.2%
1 39
 
9.7%
( 38
 
9.5%
) 38
 
9.5%
2 28
 
7.0%
3 27
 
6.7%
6 14
 
3.5%
5 13
 
3.2%
9 12
 
3.0%
4 10
 
2.5%
Other values (5) 29
 
7.2%
Hangul
ValueCountFrequency (%)
부 49
 
8.0%
동 48
 
7.9%
구 46
 
7.6%
서 45
 
7.4%
시 41
 
6.7%
광 38
 
6.2%
역 38
 
6.2%
산 38
 
6.2%
로 33
 
5.4%
가 26
 
4.3%
Other values (38) 207
34.0%

소재지전화
Text

MISSING 

Distinct35
Distinct (%)100.0%
Missing3
Missing (%)7.9%
Memory size436.0 B
2023-12-11T01:56:37.697237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters490
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

Unique35 ?
Unique (%)100.0%

Sample

1st row 051- 244-6788
2nd row 051- 256-2007
3rd row 051- 242-8446
4th row 051- 242-8360
5th row 051- 256-0989
ValueCountFrequency (%)
051 35
48.6%
718 1
 
1.4%
245-6955 1
 
1.4%
243-7365 1
 
1.4%
916-7700 1
 
1.4%
341-0355 1
 
1.4%
257-3366 1
 
1.4%
241-7980 1
 
1.4%
254-3138 1
 
1.4%
2000 1
 
1.4%
Other values (28) 28
38.9%
2023-12-11T01:56:38.238384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 74
15.1%
70
14.3%
- 70
14.3%
0 58
11.8%
1 52
10.6%
2 47
9.6%
6 30
6.1%
4 25
 
5.1%
3 21
 
4.3%
8 20
 
4.1%
Other values (2) 23
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 350
71.4%
Space Separator 70
 
14.3%
Dash Punctuation 70
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 74
21.1%
0 58
16.6%
1 52
14.9%
2 47
13.4%
6 30
8.6%
4 25
 
7.1%
3 21
 
6.0%
8 20
 
5.7%
7 16
 
4.6%
9 7
 
2.0%
Space Separator
ValueCountFrequency (%)
70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 74
15.1%
70
14.3%
- 70
14.3%
0 58
11.8%
1 52
10.6%
2 47
9.6%
6 30
6.1%
4 25
 
5.1%
3 21
 
4.3%
8 20
 
4.1%
Other values (2) 23
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 74
15.1%
70
14.3%
- 70
14.3%
0 58
11.8%
1 52
10.6%
2 47
9.6%
6 30
6.1%
4 25
 
5.1%
3 21
 
4.3%
8 20
 
4.1%
Other values (2) 23
 
4.7%

Correlations

2023-12-11T01:56:38.437710image/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

2023-12-11T01:56:34.508454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:56:34.675611image/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
0목욕장업늘푸른스파동광부산광역시 서구 충무시장길 58 (충무동3가)051- 244-6788
1목욕장업대영탕부산광역시 서구 대영로86번길 4 (동대신동1가)051- 256-2007
2목욕장업동아탕부산광역시 서구 보수대로 262 (동대신동3가)051- 242-8446
3목욕장업부산탕부산광역시 서구 구덕로280번길 56 (동대신동1가)051- 242-8360
4목욕장업서호탕부산광역시 서구 까치고개로198번길 13 (아미동2가)051- 256-0989
5목욕장업청신탕부산광역시 서구 대신로 12-14 (서대신동3가)051- 248-6835
6목욕장업초장탕부산광역시 서구 구덕로163번길 19 (초장동)051- 256-0155
7목욕장업천연탕부산광역시 서구 천마로 115-1 (남부민동)051- 254-0826
8목욕장업남부탕부산광역시 서구 천마로 106-1 (남부민동)051- 256-3076
9목욕장업창신탕부산광역시 서구 구덕로301번길 9 (서대신동2가)051- 248-3014
업종명업소명영업소 주소(도로명)소재지전화
28목욕장업까치탕부산광역시 서구 까치고개로 104 (아미동2가)051- 242-6367
29목욕장업대명탕부산광역시 서구 천마로193번길 6 (남부민동)051- 248-6776
30목욕장업송도해모수 찜질사우나부산광역시 서구 충무대로 8 (암남동)051- 231-5235
31목욕장업한웅레포츠부산광역시 서구 보수대로 105-1 (부용동1가)051- 245-2700
32목욕장업금천사우나부산광역시 서구 해돋이로 279 (아미동2가)051- 242-8413
33목욕장업송도해수피아부산광역시 서구 충무대로 134 (남부민동)051 -718 -2000
34목욕장업녹천탕부산광역시 서구 해돋이로335번길 4 (부용동2가)<NA>
35목욕장업복지목욕탕부산광역시 서구 해안새벽시장길 88 (남부민동)051 -255 -1836
36목욕장업동선탕부산광역시 서구 망양로92번길 33 (동대신동3가)<NA>
37목욕장업구덕 사우나부산광역시 서구 구덕로333번길 33, 3층,5층 (서대신동3가)<NA>