Overview

Dataset statistics

Number of variables6
Number of observations25
Missing cells5
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory53.3 B

Variable types

Categorical1
Text4
DateTime1

Dataset

Description경기도 시흥시 목욕장업 현황입니다.(경기도 시흥시 목욕장업 현황에는 업소명,영업소 주소(도로명소재지,지번소재지) 소재지 전화, 담당자 연락처가 있습니다.)
URLhttps://www.data.go.kr/data/15055101/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant
소재지전화 has 5 (20.0%) missing valuesMissing
업소명 has unique valuesUnique
영업소 주소(도로명) has unique valuesUnique
영업소 주소(지번) has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:00:34.303166
Analysis finished2023-12-12 09:00:34.775477
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
목욕장업
25 

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 25
100.0%

Length

2023-12-12T18:00:34.842369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:00:34.941255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 25
100.0%

업소명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T18:00:35.111646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.64
Min length4

Characters and Unicode

Total characters166
Distinct characters78
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row대야목욕탕
2nd row한방쑥사우나
3rd row동보사우나
4th row비젼목욕탕
5th row아미24시사우나
ValueCountFrequency (%)
대야목욕탕 1
 
3.8%
한방쑥사우나 1
 
3.8%
목감참숯가마 1
 
3.8%
해수랜드 1
 
3.8%
서해그린스포렉스 1
 
3.8%
배곧스파24시사우나 1
 
3.8%
보화황토장작불가마 1
 
3.8%
능곡불가마사우나 1
 
3.8%
오아시스한증막 1
 
3.8%
불가마사우나 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T18:00:35.513136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
나 15
 
9.0%
사 14
 
8.4%
우 14
 
8.4%
목 6
 
3.6%
스 5
 
3.0%
불 4
 
2.4%
탕 4
 
2.4%
욕 4
 
2.4%
시 4
 
2.4%
가 4
 
2.4%
Other values (68) 92
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161
97.0%
Decimal Number 4
 
2.4%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 15
 
9.3%
사 14
 
8.7%
우 14
 
8.7%
목 6
 
3.7%
스 5
 
3.1%
불 4
 
2.5%
탕 4
 
2.5%
욕 4
 
2.5%
시 4
 
2.5%
가 4
 
2.5%
Other values (65) 87
54.0%
Decimal Number
ValueCountFrequency (%)
4 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161
97.0%
Common 5
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 15
 
9.3%
사 14
 
8.7%
우 14
 
8.7%
목 6
 
3.7%
스 5
 
3.1%
불 4
 
2.5%
탕 4
 
2.5%
욕 4
 
2.5%
시 4
 
2.5%
가 4
 
2.5%
Other values (65) 87
54.0%
Common
ValueCountFrequency (%)
4 2
40.0%
2 2
40.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161
97.0%
ASCII 5
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
나 15
 
9.3%
사 14
 
8.7%
우 14
 
8.7%
목 6
 
3.7%
스 5
 
3.1%
불 4
 
2.5%
탕 4
 
2.5%
욕 4
 
2.5%
시 4
 
2.5%
가 4
 
2.5%
Other values (65) 87
54.0%
ASCII
ValueCountFrequency (%)
4 2
40.0%
2 2
40.0%
1
20.0%

영업소 주소(도로명)
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T18:00:35.784389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length30
Min length21

Characters and Unicode

Total characters750
Distinct characters104
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row경기도 시흥시 대골안길 80 (대야동)
2nd row경기도 시흥시 매화2로 18 (매화동)
3rd row경기도 시흥시 수인로 2331 (목감동)
4th row경기도 시흥시 중심상가로 323 (정왕동,4,5층)
5th row경기도 시흥시 중심상가로 161 (정왕동)
ValueCountFrequency (%)
경기도 25
 
17.5%
시흥시 25
 
17.5%
정왕동 6
 
4.2%
중심상가로 4
 
2.8%
2 2
 
1.4%
2층 2
 
1.4%
5,6,7층 2
 
1.4%
신천동 2
 
1.4%
옥구상가1길 2
 
1.4%
37 2
 
1.4%
Other values (68) 71
49.7%
2023-12-12T18:00:36.279096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118
 
15.7%
시 51
 
6.8%
, 35
 
4.7%
1 28
 
3.7%
( 27
 
3.6%
) 27
 
3.6%
도 26
 
3.5%
기 26
 
3.5%
동 26
 
3.5%
경 25
 
3.3%
Other values (94) 361
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 408
54.4%
Decimal Number 127
 
16.9%
Space Separator 118
 
15.7%
Other Punctuation 36
 
4.8%
Open Punctuation 27
 
3.6%
Close Punctuation 27
 
3.6%
Dash Punctuation 4
 
0.5%
Uppercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 51
 
12.5%
도 26
 
6.4%
기 26
 
6.4%
동 26
 
6.4%
경 25
 
6.1%
흥 25
 
6.1%
층 19
 
4.7%
로 18
 
4.4%
길 13
 
3.2%
정 11
 
2.7%
Other values (77) 168
41.2%
Decimal Number
ValueCountFrequency (%)
1 28
22.0%
2 24
18.9%
3 13
10.2%
4 13
10.2%
5 11
 
8.7%
0 10
 
7.9%
6 9
 
7.1%
7 9
 
7.1%
9 5
 
3.9%
8 5
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 35
97.2%
. 1
 
2.8%
Space Separator
ValueCountFrequency (%)
118
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 408
54.4%
Common 339
45.2%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 51
 
12.5%
도 26
 
6.4%
기 26
 
6.4%
동 26
 
6.4%
경 25
 
6.1%
흥 25
 
6.1%
층 19
 
4.7%
로 18
 
4.4%
길 13
 
3.2%
정 11
 
2.7%
Other values (77) 168
41.2%
Common
ValueCountFrequency (%)
118
34.8%
, 35
 
10.3%
1 28
 
8.3%
( 27
 
8.0%
) 27
 
8.0%
2 24
 
7.1%
3 13
 
3.8%
4 13
 
3.8%
5 11
 
3.2%
0 10
 
2.9%
Other values (6) 33
 
9.7%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 408
54.4%
ASCII 342
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118
34.5%
, 35
 
10.2%
1 28
 
8.2%
( 27
 
7.9%
) 27
 
7.9%
2 24
 
7.0%
3 13
 
3.8%
4 13
 
3.8%
5 11
 
3.2%
0 10
 
2.9%
Other values (7) 36
 
10.5%
Hangul
ValueCountFrequency (%)
시 51
 
12.5%
도 26
 
6.4%
기 26
 
6.4%
동 26
 
6.4%
경 25
 
6.1%
흥 25
 
6.1%
층 19
 
4.7%
로 18
 
4.4%
길 13
 
3.2%
정 11
 
2.7%
Other values (77) 168
41.2%

영업소 주소(지번)
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T18:00:36.551914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length24
Min length16

Characters and Unicode

Total characters600
Distinct characters72
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row경기도 시흥시 대야동 497-8
2nd row경기도 시흥시 매화동 212
3rd row경기도 시흥시 목감동 238-6
4th row경기도 시흥시 정왕동 1625-6 4,5층
5th row경기도 시흥시 정왕동 1728-20
ValueCountFrequency (%)
경기도 25
20.2%
시흥시 25
20.2%
정왕동 10
 
8.1%
장곡동 2
 
1.6%
조남동 2
 
1.6%
5,6,7층 2
 
1.6%
신천동 2
 
1.6%
4,5층 2
 
1.6%
1852-1 2
 
1.6%
1층 2
 
1.6%
Other values (49) 50
40.3%
2023-12-12T18:00:37.013898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
123
20.5%
시 50
 
8.3%
1 33
 
5.5%
동 26
 
4.3%
경 25
 
4.2%
기 25
 
4.2%
흥 25
 
4.2%
도 25
 
4.2%
- 21
 
3.5%
2 20
 
3.3%
Other values (62) 227
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 288
48.0%
Decimal Number 149
24.8%
Space Separator 123
20.5%
Dash Punctuation 21
 
3.5%
Other Punctuation 13
 
2.2%
Uppercase Letter 3
 
0.5%
Math Symbol 1
 
0.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 50
17.4%
동 26
 
9.0%
경 25
 
8.7%
기 25
 
8.7%
흥 25
 
8.7%
도 25
 
8.7%
층 15
 
5.2%
정 10
 
3.5%
왕 10
 
3.5%
호 4
 
1.4%
Other values (45) 73
25.3%
Decimal Number
ValueCountFrequency (%)
1 33
22.1%
2 20
13.4%
8 16
10.7%
6 15
10.1%
7 15
10.1%
5 15
10.1%
0 13
 
8.7%
3 11
 
7.4%
4 7
 
4.7%
9 4
 
2.7%
Space Separator
ValueCountFrequency (%)
123
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 309
51.5%
Hangul 288
48.0%
Latin 3
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 50
17.4%
동 26
 
9.0%
경 25
 
8.7%
기 25
 
8.7%
흥 25
 
8.7%
도 25
 
8.7%
층 15
 
5.2%
정 10
 
3.5%
왕 10
 
3.5%
호 4
 
1.4%
Other values (45) 73
25.3%
Common
ValueCountFrequency (%)
123
39.8%
1 33
 
10.7%
- 21
 
6.8%
2 20
 
6.5%
8 16
 
5.2%
6 15
 
4.9%
7 15
 
4.9%
5 15
 
4.9%
0 13
 
4.2%
, 13
 
4.2%
Other values (6) 25
 
8.1%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
52.0%
Hangul 288
48.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
123
39.4%
1 33
 
10.6%
- 21
 
6.7%
2 20
 
6.4%
8 16
 
5.1%
6 15
 
4.8%
7 15
 
4.8%
5 15
 
4.8%
0 13
 
4.2%
, 13
 
4.2%
Other values (7) 28
 
9.0%
Hangul
ValueCountFrequency (%)
시 50
17.4%
동 26
 
9.0%
경 25
 
8.7%
기 25
 
8.7%
흥 25
 
8.7%
도 25
 
8.7%
층 15
 
5.2%
정 10
 
3.5%
왕 10
 
3.5%
호 4
 
1.4%
Other values (45) 73
25.3%

소재지전화
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing5
Missing (%)20.0%
Memory size332.0 B
2023-12-12T18:00:37.222162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters280
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

Unique20 ?
Unique (%)100.0%

Sample

1st row 031- 311-9545
2nd row 031- 313-9092
3rd row 031- 486-8285
4th row031 -432 -0088
5th row 031- 498-3771
ValueCountFrequency (%)
031 18
36.0%
311 2
 
4.0%
5915 1
 
2.0%
480-1511 1
 
2.0%
1
 
2.0%
7555 1
 
2.0%
431 1
 
2.0%
3376 1
 
2.0%
499 1
 
2.0%
5245 1
 
2.0%
Other values (22) 22
44.0%
2023-12-12T18:00:37.578350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 41
14.6%
40
14.3%
- 40
14.3%
3 39
13.9%
0 30
10.7%
5 20
7.1%
4 18
6.4%
9 15
 
5.4%
2 13
 
4.6%
8 13
 
4.6%
Other values (2) 11
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200
71.4%
Space Separator 40
 
14.3%
Dash Punctuation 40
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 41
20.5%
3 39
19.5%
0 30
15.0%
5 20
10.0%
4 18
9.0%
9 15
 
7.5%
2 13
 
6.5%
8 13
 
6.5%
7 7
 
3.5%
6 4
 
2.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 280
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 41
14.6%
40
14.3%
- 40
14.3%
3 39
13.9%
0 30
10.7%
5 20
7.1%
4 18
6.4%
9 15
 
5.4%
2 13
 
4.6%
8 13
 
4.6%
Other values (2) 11
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 41
14.6%
40
14.3%
- 40
14.3%
3 39
13.9%
0 30
10.7%
5 20
7.1%
4 18
6.4%
9 15
 
5.4%
2 13
 
4.6%
8 13
 
4.6%
Other values (2) 11
 
3.9%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum2023-06-09 00:00:00
Maximum2023-06-09 00:00:00
2023-12-12T18:00:37.694710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:37.783819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T18:00:37.867249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)영업소 주소(지번)소재지전화
업소명1.0001.0001.0001.000
영업소 주소(도로명)1.0001.0001.0001.000
영업소 주소(지번)1.0001.0001.0001.000
소재지전화1.0001.0001.0001.000

Missing values

2023-12-12T18:00:34.615187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:00:34.728415image/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)영업소 주소(지번)소재지전화데이터기준일
0목욕장업대야목욕탕경기도 시흥시 대골안길 80 (대야동)경기도 시흥시 대야동 497-8031- 311-95452023-06-09
1목욕장업한방쑥사우나경기도 시흥시 매화2로 18 (매화동)경기도 시흥시 매화동 212031- 313-90922023-06-09
2목욕장업동보사우나경기도 시흥시 수인로 2331 (목감동)경기도 시흥시 목감동 238-6031- 486-82852023-06-09
3목욕장업비젼목욕탕경기도 시흥시 중심상가로 323 (정왕동,4,5층)경기도 시흥시 정왕동 1625-6 4,5층<NA>2023-06-09
4목욕장업아미24시사우나경기도 시흥시 중심상가로 161 (정왕동)경기도 시흥시 정왕동 1728-20031 -432 -00882023-06-09
5목욕장업대영사우나경기도 시흥시 삼미시장3길 20-1 (신천동)경기도 시흥시 신천동 739-12<NA>2023-06-09
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7목욕장업유성보석목욕탕경기도 시흥시 도일로124번길 2 (거모동,3,4층)경기도 시흥시 거모동 1656-8 3,4층031 -492 -55572023-06-09
8목욕장업참나무숯불사우나경기도 시흥시 인선길 104 (장곡동,지하1층)경기도 시흥시 장곡동 803-2 지하1층031 -314 -19192023-06-09
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업종명업소명영업소 주소(도로명)영업소 주소(지번)소재지전화데이터기준일
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16목욕장업워터캐슬 불가마사우나경기도 시흥시 정왕대로 174 (정왕동,광개토빌딩 B101,B201호)경기도 시흥시 정왕동 1726-1 광개토빌딩 B101,B201호02 -2051-01502023-06-09
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18목욕장업능곡불가마사우나경기도 시흥시 장현능곡로 192 (능곡동, 5,6,7층)경기도 시흥시 능곡동 735 5,6,7층031-435 -33092023-06-09
19목욕장업보화황토장작불가마경기도 시흥시 중심상가로 329, 4,5층 (정왕동)경기도 시흥시 정왕동 1625-10 4~5층031 -498 -52452023-06-09
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