Overview

Dataset statistics

Number of variables7
Number of observations38
Missing cells1
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory59.5 B

Variable types

Text4
DateTime1
Categorical2

Dataset

Description울산광역시 중구에 소재한 목욕탕에 대한 데이터로 업소명, 신고일자, 업종명, 주소, 연락처 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15055272/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
전화번호 has 1 (2.6%) missing valuesMissing
업소명 has unique valuesUnique
신고일자 has unique valuesUnique
업소소재지(도로명) has unique valuesUnique
업소소재지(지번) has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:22:08.482613
Analysis finished2023-12-12 13:22:08.989227
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T22:22:09.148041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length4.7368421
Min length3

Characters and Unicode

Total characters180
Distinct characters81
Distinct categories6 ?
Distinct scripts3 ?
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 row청강탕
2nd row학성탕
3rd row선경탕
4th row청수탕
5th row수정탕
ValueCountFrequency (%)
청강탕 1
 
2.6%
학성사우나 1
 
2.6%
애천탕 1
 
2.6%
정안탕 1
 
2.6%
스카이리조트 1
 
2.6%
옥사우나 1
 
2.6%
우정사우나 1
 
2.6%
태화사우나 1
 
2.6%
헬스 1
 
2.6%
진영탕 1
 
2.6%
Other values (29) 29
74.4%
2023-12-12T22:22:09.490879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 22
 
12.2%
우 10
 
5.6%
스 9
 
5.0%
사 9
 
5.0%
나 9
 
5.0%
청 5
 
2.8%
이 4
 
2.2%
천 4
 
2.2%
수 4
 
2.2%
화 3
 
1.7%
Other values (71) 101
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 171
95.0%
Uppercase Letter 3
 
1.7%
Close Punctuation 2
 
1.1%
Open Punctuation 2
 
1.1%
Other Punctuation 1
 
0.6%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 22
 
12.9%
우 10
 
5.8%
스 9
 
5.3%
사 9
 
5.3%
나 9
 
5.3%
청 5
 
2.9%
이 4
 
2.3%
천 4
 
2.3%
수 4
 
2.3%
화 3
 
1.8%
Other values (64) 92
53.8%
Uppercase Letter
ValueCountFrequency (%)
W 1
33.3%
S 1
33.3%
H 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 171
95.0%
Common 6
 
3.3%
Latin 3
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 22
 
12.9%
우 10
 
5.8%
스 9
 
5.3%
사 9
 
5.3%
나 9
 
5.3%
청 5
 
2.9%
이 4
 
2.3%
천 4
 
2.3%
수 4
 
2.3%
화 3
 
1.8%
Other values (64) 92
53.8%
Common
ValueCountFrequency (%)
) 2
33.3%
( 2
33.3%
. 1
16.7%
1
16.7%
Latin
ValueCountFrequency (%)
W 1
33.3%
S 1
33.3%
H 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 171
95.0%
ASCII 9
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 22
 
12.9%
우 10
 
5.8%
스 9
 
5.3%
사 9
 
5.3%
나 9
 
5.3%
청 5
 
2.9%
이 4
 
2.3%
천 4
 
2.3%
수 4
 
2.3%
화 3
 
1.8%
Other values (64) 92
53.8%
ASCII
ValueCountFrequency (%)
) 2
22.2%
( 2
22.2%
W 1
11.1%
S 1
11.1%
. 1
11.1%
H 1
11.1%
1
11.1%

신고일자
Date

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum1976-11-30 00:00:00
Maximum2020-11-10 00:00:00
2023-12-12T22:22:09.638567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:09.763959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

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

2023-12-12T22:22:09.889927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:22:09.985656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 38
100.0%

업소소재지(도로명)
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T22:22:10.224251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length39
Mean length24.578947
Min length17

Characters and Unicode

Total characters934
Distinct characters85
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

Unique38 ?
Unique (%)100.0%

Sample

1st row울산광역시 중구 옥교4길 20 (옥교동)
2nd row울산광역시 중구 옥교14길 36 (학성동)
3rd row울산광역시 중구 우정4길 4 (우정동)
4th row울산광역시 중구 서원2길 67 (반구동)
5th row울산광역시 중구 서원1길 41 (반구동)
ValueCountFrequency (%)
울산광역시 38
 
18.7%
중구 38
 
18.7%
태화동 6
 
3.0%
반구동 5
 
2.5%
서동 4
 
2.0%
성안동 3
 
1.5%
다운동 3
 
1.5%
우정동 3
 
1.5%
9 3
 
1.5%
1,2,3층 2
 
1.0%
Other values (88) 98
48.3%
2023-12-12T22:22:10.592528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
165
17.7%
구 46
 
4.9%
산 44
 
4.7%
동 40
 
4.3%
역 39
 
4.2%
중 39
 
4.2%
울 38
 
4.1%
광 38
 
4.1%
시 38
 
4.1%
1 38
 
4.1%
Other values (75) 409
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 527
56.4%
Space Separator 165
 
17.7%
Decimal Number 139
 
14.9%
Open Punctuation 37
 
4.0%
Close Punctuation 37
 
4.0%
Other Punctuation 22
 
2.4%
Math Symbol 5
 
0.5%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 46
 
8.7%
산 44
 
8.3%
동 40
 
7.6%
역 39
 
7.4%
중 39
 
7.4%
울 38
 
7.2%
광 38
 
7.2%
시 38
 
7.2%
길 31
 
5.9%
층 13
 
2.5%
Other values (59) 161
30.6%
Decimal Number
ValueCountFrequency (%)
1 38
27.3%
2 21
15.1%
4 19
13.7%
3 18
12.9%
5 9
 
6.5%
8 8
 
5.8%
7 8
 
5.8%
6 6
 
4.3%
9 6
 
4.3%
0 6
 
4.3%
Space Separator
ValueCountFrequency (%)
165
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 527
56.4%
Common 407
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 46
 
8.7%
산 44
 
8.3%
동 40
 
7.6%
역 39
 
7.4%
중 39
 
7.4%
울 38
 
7.2%
광 38
 
7.2%
시 38
 
7.2%
길 31
 
5.9%
층 13
 
2.5%
Other values (59) 161
30.6%
Common
ValueCountFrequency (%)
165
40.5%
1 38
 
9.3%
( 37
 
9.1%
) 37
 
9.1%
, 22
 
5.4%
2 21
 
5.2%
4 19
 
4.7%
3 18
 
4.4%
5 9
 
2.2%
8 8
 
2.0%
Other values (6) 33
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 527
56.4%
ASCII 407
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165
40.5%
1 38
 
9.3%
( 37
 
9.1%
) 37
 
9.1%
, 22
 
5.4%
2 21
 
5.2%
4 19
 
4.7%
3 18
 
4.4%
5 9
 
2.2%
8 8
 
2.0%
Other values (6) 33
 
8.1%
Hangul
ValueCountFrequency (%)
구 46
 
8.7%
산 44
 
8.3%
동 40
 
7.6%
역 39
 
7.4%
중 39
 
7.4%
울 38
 
7.2%
광 38
 
7.2%
시 38
 
7.2%
길 31
 
5.9%
층 13
 
2.5%
Other values (59) 161
30.6%

업소소재지(지번)
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T22:22:10.794838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length20.526316
Min length16

Characters and Unicode

Total characters780
Distinct characters54
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 row울산광역시 중구 옥교동 315-4
2nd row울산광역시 중구 학성동 156-3
3rd row울산광역시 중구 우정동 380-23
4th row울산광역시 중구 반구동 103-11
5th row울산광역시 중구 반구동 98-3
ValueCountFrequency (%)
울산광역시 38
23.5%
중구 38
23.5%
태화동 7
 
4.3%
반구동 5
 
3.1%
서동 4
 
2.5%
다운동 3
 
1.9%
성안동 3
 
1.9%
우정동 3
 
1.9%
2,3층 2
 
1.2%
복산동 2
 
1.2%
Other values (54) 57
35.2%
2023-12-12T22:22:11.191453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
20.8%
구 43
 
5.5%
산 41
 
5.3%
동 40
 
5.1%
중 38
 
4.9%
울 38
 
4.9%
시 38
 
4.9%
역 38
 
4.9%
광 38
 
4.9%
- 33
 
4.2%
Other values (44) 271
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 400
51.3%
Decimal Number 166
21.3%
Space Separator 162
20.8%
Dash Punctuation 33
 
4.2%
Other Punctuation 9
 
1.2%
Close Punctuation 5
 
0.6%
Open Punctuation 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 43
10.8%
산 41
10.2%
동 40
10.0%
중 38
9.5%
울 38
9.5%
시 38
9.5%
역 38
9.5%
광 38
9.5%
태 7
 
1.8%
층 7
 
1.8%
Other values (29) 72
18.0%
Decimal Number
ValueCountFrequency (%)
1 32
19.3%
5 27
16.3%
3 23
13.9%
2 21
12.7%
4 19
11.4%
7 12
 
7.2%
0 10
 
6.0%
6 9
 
5.4%
8 8
 
4.8%
9 5
 
3.0%
Space Separator
ValueCountFrequency (%)
162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 400
51.3%
Common 380
48.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 43
10.8%
산 41
10.2%
동 40
10.0%
중 38
9.5%
울 38
9.5%
시 38
9.5%
역 38
9.5%
광 38
9.5%
태 7
 
1.8%
층 7
 
1.8%
Other values (29) 72
18.0%
Common
ValueCountFrequency (%)
162
42.6%
- 33
 
8.7%
1 32
 
8.4%
5 27
 
7.1%
3 23
 
6.1%
2 21
 
5.5%
4 19
 
5.0%
7 12
 
3.2%
0 10
 
2.6%
, 9
 
2.4%
Other values (5) 32
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 400
51.3%
ASCII 380
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
42.6%
- 33
 
8.7%
1 32
 
8.4%
5 27
 
7.1%
3 23
 
6.1%
2 21
 
5.5%
4 19
 
5.0%
7 12
 
3.2%
0 10
 
2.6%
, 9
 
2.4%
Other values (5) 32
 
8.4%
Hangul
ValueCountFrequency (%)
구 43
10.8%
산 41
10.2%
동 40
10.0%
중 38
9.5%
울 38
9.5%
시 38
9.5%
역 38
9.5%
광 38
9.5%
태 7
 
1.8%
층 7
 
1.8%
Other values (29) 72
18.0%

전화번호
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing1
Missing (%)2.6%
Memory size436.0 B
2023-12-12T22:22:11.427186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.081081
Min length12

Characters and Unicode

Total characters447
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

Unique37 ?
Unique (%)100.0%

Sample

1st row052-242-1411
2nd row052-297-7722
3rd row052-243-3763
4th row052-293-7317
5th row052-292-4248
ValueCountFrequency (%)
052-242-1411 1
 
2.7%
052-294-2252 1
 
2.7%
052-245-5720 1
 
2.7%
052-291-3399 1
 
2.7%
052-248-5800 1
 
2.7%
052-245-8188 1
 
2.7%
052-248-5533 1
 
2.7%
052-243-9232 1
 
2.7%
052-285-1177 1
 
2.7%
070-8292-3295 1
 
2.7%
Other values (27) 27
73.0%
2023-12-12T22:22:11.809380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 100
22.4%
- 74
16.6%
0 63
14.1%
5 62
13.9%
4 28
 
6.3%
1 24
 
5.4%
3 23
 
5.1%
7 22
 
4.9%
9 21
 
4.7%
8 21
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 373
83.4%
Dash Punctuation 74
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 100
26.8%
0 63
16.9%
5 62
16.6%
4 28
 
7.5%
1 24
 
6.4%
3 23
 
6.2%
7 22
 
5.9%
9 21
 
5.6%
8 21
 
5.6%
6 9
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 447
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 100
22.4%
- 74
16.6%
0 63
14.1%
5 62
13.9%
4 28
 
6.3%
1 24
 
5.4%
3 23
 
5.1%
7 22
 
4.9%
9 21
 
4.7%
8 21
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 447
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 100
22.4%
- 74
16.6%
0 63
14.1%
5 62
13.9%
4 28
 
6.3%
1 24
 
5.4%
3 23
 
5.1%
7 22
 
4.9%
9 21
 
4.7%
8 21
 
4.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-08-08
38 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-08
2nd row2023-08-08
3rd row2023-08-08
4th row2023-08-08
5th row2023-08-08

Common Values

ValueCountFrequency (%)
2023-08-08 38
100.0%

Length

2023-12-12T22:22:11.972798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:22:12.073777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-08 38
100.0%

Correlations

2023-12-12T22:22:12.149663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명신고일자업소소재지(도로명)업소소재지(지번)전화번호
업소명1.0001.0001.0001.0001.000
신고일자1.0001.0001.0001.0001.000
업소소재지(도로명)1.0001.0001.0001.0001.000
업소소재지(지번)1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2023-12-12T22:22:08.821621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:22:08.937281image/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

업소명신고일자업종명업소소재지(도로명)업소소재지(지번)전화번호데이터기준일자
0청강탕1976-11-30목욕장업울산광역시 중구 옥교4길 20 (옥교동)울산광역시 중구 옥교동 315-4052-242-14112023-08-08
1학성탕1979-11-23목욕장업울산광역시 중구 옥교14길 36 (학성동)울산광역시 중구 학성동 156-3052-297-77222023-08-08
2선경탕1982-01-16목욕장업울산광역시 중구 우정4길 4 (우정동)울산광역시 중구 우정동 380-23052-243-37632023-08-08
3청수탕1982-10-13목욕장업울산광역시 중구 서원2길 67 (반구동)울산광역시 중구 반구동 103-11052-293-73172023-08-08
4수정탕1985-02-15목욕장업울산광역시 중구 서원1길 41 (반구동)울산광역시 중구 반구동 98-3052-292-42482023-08-08
5한샘탕1986-12-26목욕장업울산광역시 중구 병영10길 5 (동동)울산광역시 중구 동동 695052-293-92052023-08-08
6안젤여성사우나1988-01-20목욕장업울산광역시 중구 옥골샘7길 3 (옥교동)울산광역시 중구 옥교동 262-3<NA>2023-08-08
7로얄탕1989-05-20목욕장업울산광역시 중구 신기8길 9 (태화동)울산광역시 중구 태화동 445-13052-243-04562023-08-08
8옥수탕1994-03-12목욕장업울산광역시 중구 다운로 119 (다운동)울산광역시 중구 다운동 780-3052-223-54722023-08-08
9백조탕1994-11-24목욕장업울산광역시 중구 곽남8길 31 (남외동)울산광역시 중구 남외동 58-1052-0294-12312023-08-08
업소명신고일자업종명업소소재지(도로명)업소소재지(지번)전화번호데이터기준일자
28황토찜질방2006-04-17목욕장업울산광역시 중구 화합로 418-1 (반구동)울산광역시 중구 반구동 57-15052-251-12012023-08-08
29진영탕2008-08-07목욕장업울산광역시 중구 병영11길 31 (서동)울산광역시 중구 서동 250070-8292-32952023-08-08
30일신스포렉스2009-05-12목욕장업울산광역시 중구 화진4길 6, 2,3층 (태화동)울산광역시 중구 태화동 24-11 (2,3층)052-225-64002023-08-08
31청유사우나2011-01-28목욕장업울산광역시 중구 성안7길 21, 1,2,3층 (성안동)울산광역시 중구 성안동 503-16 (1,2,3층)052-243-93332023-08-08
32더블유(W)사우나2012-01-02목욕장업울산광역시 중구 산전길 16, 1~4층 (남외동)울산광역시 중구 남외동 550-1052-282-01002023-08-08
33탑유황온천2012-01-06목욕장업울산광역시 중구 북부순환도로 180, 제2동 지상1,2,3층 (태화동)울산광역시 중구 태화동 304 외 1필지(지상1,2,3층) 제2동052-224-87002023-08-08
34셀레늄스파2012-02-06목욕장업울산광역시 중구 구역전2길 30, 1,2,3층 (학성동)울산광역시 중구 학성동 433-1052-293-77882023-08-08
35중앙헬스사우나2016-11-24목욕장업울산광역시 중구 중앙2길 11, 3~4층 (성남동)울산광역시 중구 성남동 157052-211-70702023-08-08
36케이제이건강온천헬스2019-07-19목욕장업울산광역시 중구 북부순환도로 862, 케이제이 스포츠센터 1~3층 (서동)울산광역시 중구 서동 55-4 케이제이 스포츠센터052-282-38002023-08-08
37에스에이치(S.H)스포츠센터2020-11-10목욕장업울산광역시 중구 번영로 417, 2층일부,3~4층 (복산동)울산광역시 중구 복산동 470-1052-292-80002023-08-08