Overview

Dataset statistics

Number of variables5
Number of observations298
Missing cells54
Missing cells (%)3.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory41.4 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description남해군의 현재 등록된 목욕장업 현황입니다. 등록된 목용장업의 업소명, 업소소재지(도로명주소), 전화번호 등을 포함한 정보입니다.
Author경상남도 남해군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15006888

Alerts

연번 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번High correlation
전화번호 has 54 (18.1%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:10:38.735705
Analysis finished2023-12-11 00:10:39.354393
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct298
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149.5
Minimum1
Maximum298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T09:10:39.447680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.85
Q175.25
median149.5
Q3223.75
95-th percentile283.15
Maximum298
Range297
Interquartile range (IQR)148.5

Descriptive statistics

Standard deviation86.169407
Coefficient of variation (CV)0.57638399
Kurtosis-1.2
Mean149.5
Median Absolute Deviation (MAD)74.5
Skewness0
Sum44551
Variance7425.1667
MonotonicityStrictly increasing
2023-12-11T09:10:39.660503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
206 1
 
0.3%
204 1
 
0.3%
203 1
 
0.3%
202 1
 
0.3%
201 1
 
0.3%
200 1
 
0.3%
199 1
 
0.3%
198 1
 
0.3%
197 1
 
0.3%
Other values (288) 288
96.6%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
298 1
0.3%
297 1
0.3%
296 1
0.3%
295 1
0.3%
294 1
0.3%
293 1
0.3%
292 1
0.3%
291 1
0.3%
290 1
0.3%
289 1
0.3%

업종명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
숙박업(생활)
67 
숙박업(일반)
65 
미용업
61 
이용업
30 
목욕장업
20 
Other values (11)
55 

Length

Max length31
Median length7
Mean length5.6778523
Min length3

Unique

Unique5 ?
Unique (%)1.7%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
숙박업(생활) 67
22.5%
숙박업(일반) 65
21.8%
미용업 61
20.5%
이용업 30
10.1%
목욕장업 20
 
6.7%
미용업(일반) 17
 
5.7%
세탁업 12
 
4.0%
미용업(피부) 11
 
3.7%
건물위생관리업 5
 
1.7%
미용업(종합) 3
 
1.0%
Other values (6) 7
 
2.3%

Length

2023-12-11T09:10:39.822304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(생활 67
22.0%
숙박업(일반 65
21.4%
미용업 61
20.1%
이용업 30
9.9%
목욕장업 20
 
6.6%
미용업(일반 20
 
6.6%
미용업(피부 13
 
4.3%
세탁업 12
 
3.9%
미용업(손톱ㆍ발톱 6
 
2.0%
건물위생관리업 5
 
1.6%
Other values (2) 5
 
1.6%

업소명
Text

Distinct293
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-11T09:10:40.104368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length5.704698
Min length2

Characters and Unicode

Total characters1700
Distinct characters324
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique288 ?
Unique (%)96.6%

Sample

1st row재두장여관
2nd row해주여관
3rd row한려산장
4th rowK모텔
5th row영남장여관
ValueCountFrequency (%)
신흥이용원 2
 
0.6%
현대이용원 2
 
0.6%
salon 2
 
0.6%
펜션 2
 
0.6%
모텔 2
 
0.6%
벨비앙펜션 2
 
0.6%
9 2
 
0.6%
eg미조힐링리조트 2
 
0.6%
헤어 2
 
0.6%
서울미용실 2
 
0.6%
Other values (318) 320
94.1%
2023-12-11T09:10:40.588778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 71
 
4.2%
미 61
 
3.6%
텔 49
 
2.9%
모 46
 
2.7%
이 46
 
2.7%
실 43
 
2.5%
42
 
2.5%
펜 40
 
2.4%
션 40
 
2.4%
스 37
 
2.2%
Other values (314) 1225
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1534
90.2%
Uppercase Letter 47
 
2.8%
Space Separator 42
 
2.5%
Lowercase Letter 35
 
2.1%
Close Punctuation 13
 
0.8%
Open Punctuation 13
 
0.8%
Decimal Number 9
 
0.5%
Other Punctuation 4
 
0.2%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 71
 
4.6%
미 61
 
4.0%
텔 49
 
3.2%
모 46
 
3.0%
이 46
 
3.0%
실 43
 
2.8%
펜 40
 
2.6%
션 40
 
2.6%
스 37
 
2.4%
원 34
 
2.2%
Other values (271) 1067
69.6%
Uppercase Letter
ValueCountFrequency (%)
O 6
12.8%
A 6
12.8%
I 4
 
8.5%
N 4
 
8.5%
S 3
 
6.4%
L 3
 
6.4%
R 3
 
6.4%
H 2
 
4.3%
G 2
 
4.3%
E 2
 
4.3%
Other values (8) 12
25.5%
Lowercase Letter
ValueCountFrequency (%)
a 5
14.3%
e 5
14.3%
r 4
11.4%
l 4
11.4%
t 3
8.6%
o 3
8.6%
u 2
 
5.7%
i 2
 
5.7%
h 2
 
5.7%
g 1
 
2.9%
Other values (4) 4
11.4%
Decimal Number
ValueCountFrequency (%)
9 3
33.3%
2 3
33.3%
1 2
22.2%
5 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
& 2
50.0%
· 1
25.0%
. 1
25.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1532
90.1%
Common 84
 
4.9%
Latin 82
 
4.8%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 71
 
4.6%
미 61
 
4.0%
텔 49
 
3.2%
모 46
 
3.0%
이 46
 
3.0%
실 43
 
2.8%
펜 40
 
2.6%
션 40
 
2.6%
스 37
 
2.4%
원 34
 
2.2%
Other values (269) 1065
69.5%
Latin
ValueCountFrequency (%)
O 6
 
7.3%
A 6
 
7.3%
a 5
 
6.1%
e 5
 
6.1%
r 4
 
4.9%
l 4
 
4.9%
I 4
 
4.9%
N 4
 
4.9%
S 3
 
3.7%
L 3
 
3.7%
Other values (22) 38
46.3%
Common
ValueCountFrequency (%)
42
50.0%
) 13
 
15.5%
( 13
 
15.5%
- 3
 
3.6%
9 3
 
3.6%
2 3
 
3.6%
& 2
 
2.4%
1 2
 
2.4%
· 1
 
1.2%
. 1
 
1.2%
Han
ValueCountFrequency (%)
美 1
50.0%
作 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1532
90.1%
ASCII 165
 
9.7%
CJK 2
 
0.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 71
 
4.6%
미 61
 
4.0%
텔 49
 
3.2%
모 46
 
3.0%
이 46
 
3.0%
실 43
 
2.8%
펜 40
 
2.6%
션 40
 
2.6%
스 37
 
2.4%
원 34
 
2.2%
Other values (269) 1065
69.5%
ASCII
ValueCountFrequency (%)
42
25.5%
) 13
 
7.9%
( 13
 
7.9%
O 6
 
3.6%
A 6
 
3.6%
a 5
 
3.0%
e 5
 
3.0%
r 4
 
2.4%
l 4
 
2.4%
I 4
 
2.4%
Other values (32) 63
38.2%
CJK
ValueCountFrequency (%)
美 1
50.0%
作 1
50.0%
None
ValueCountFrequency (%)
· 1
100.0%

업소소재지
Text

Distinct285
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-11T09:10:40.912380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length24.426174
Min length18

Characters and Unicode

Total characters7279
Distinct characters123
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

Unique272 ?
Unique (%)91.3%

Sample

1st row경상남도 남해군 상주면 남해대로 918-6
2nd row경상남도 남해군 상주면 상주로 17-6
3rd row경상남도 남해군 상주면 남해대로 591-56
4th row경상남도 남해군 남해읍 화전로 52-9
5th row경상남도 남해군 남해읍 화전로38번길 28
ValueCountFrequency (%)
경상남도 298
18.7%
남해군 298
18.7%
남해읍 113
 
7.1%
화전로 45
 
2.8%
창선면 36
 
2.3%
미조면 34
 
2.1%
삼동면 28
 
1.8%
이동면 23
 
1.4%
2층 23
 
1.4%
남해대로 22
 
1.4%
Other values (343) 675
42.3%
2023-12-11T09:10:41.389865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1326
18.2%
남 795
 
10.9%
해 448
 
6.2%
상 326
 
4.5%
경 298
 
4.1%
도 298
 
4.1%
군 298
 
4.1%
1 295
 
4.1%
로 293
 
4.0%
2 217
 
3.0%
Other values (113) 2685
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4386
60.3%
Decimal Number 1337
 
18.4%
Space Separator 1326
 
18.2%
Dash Punctuation 132
 
1.8%
Open Punctuation 48
 
0.7%
Close Punctuation 48
 
0.7%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 795
18.1%
해 448
 
10.2%
상 326
 
7.4%
경 298
 
6.8%
도 298
 
6.8%
군 298
 
6.8%
로 293
 
6.7%
면 193
 
4.4%
길 121
 
2.8%
번 118
 
2.7%
Other values (98) 1198
27.3%
Decimal Number
ValueCountFrequency (%)
1 295
22.1%
2 217
16.2%
3 147
11.0%
6 109
 
8.2%
5 106
 
7.9%
4 99
 
7.4%
7 99
 
7.4%
9 95
 
7.1%
8 89
 
6.7%
0 81
 
6.1%
Space Separator
ValueCountFrequency (%)
1326
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4386
60.3%
Common 2893
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 795
18.1%
해 448
 
10.2%
상 326
 
7.4%
경 298
 
6.8%
도 298
 
6.8%
군 298
 
6.8%
로 293
 
6.7%
면 193
 
4.4%
길 121
 
2.8%
번 118
 
2.7%
Other values (98) 1198
27.3%
Common
ValueCountFrequency (%)
1326
45.8%
1 295
 
10.2%
2 217
 
7.5%
3 147
 
5.1%
- 132
 
4.6%
6 109
 
3.8%
5 106
 
3.7%
4 99
 
3.4%
7 99
 
3.4%
9 95
 
3.3%
Other values (5) 268
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4386
60.3%
ASCII 2893
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1326
45.8%
1 295
 
10.2%
2 217
 
7.5%
3 147
 
5.1%
- 132
 
4.6%
6 109
 
3.8%
5 106
 
3.7%
4 99
 
3.4%
7 99
 
3.4%
9 95
 
3.3%
Other values (5) 268
 
9.3%
Hangul
ValueCountFrequency (%)
남 795
18.1%
해 448
 
10.2%
상 326
 
7.4%
경 298
 
6.8%
도 298
 
6.8%
군 298
 
6.8%
로 293
 
6.7%
면 193
 
4.4%
길 121
 
2.8%
번 118
 
2.7%
Other values (98) 1198
27.3%

전화번호
Text

MISSING 

Distinct240
Distinct (%)98.4%
Missing54
Missing (%)18.1%
Memory size2.5 KiB
2023-12-11T09:10:41.666522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.991803
Min length9

Characters and Unicode

Total characters2926
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

Unique236 ?
Unique (%)96.7%

Sample

1st row055-862-6022
2nd row055-862-6042
3rd row055-864-2981
4th row055-864-2478
5th row055-867-6078
ValueCountFrequency (%)
055-867-6543 2
 
0.8%
055-864-6672 2
 
0.8%
055-863-0807 2
 
0.8%
055-863-0020 2
 
0.8%
055-864-8171 1
 
0.4%
055-864-4917 1
 
0.4%
055-864-2250 1
 
0.4%
055-862-5119 1
 
0.4%
055-864-7956 1
 
0.4%
055-863-3541 1
 
0.4%
Other values (230) 230
94.3%
2023-12-11T09:10:42.098717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 599
20.5%
- 487
16.6%
0 356
12.2%
8 342
11.7%
6 327
11.2%
7 183
 
6.3%
3 161
 
5.5%
4 145
 
5.0%
2 135
 
4.6%
1 114
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2439
83.4%
Dash Punctuation 487
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 599
24.6%
0 356
14.6%
8 342
14.0%
6 327
13.4%
7 183
 
7.5%
3 161
 
6.6%
4 145
 
5.9%
2 135
 
5.5%
1 114
 
4.7%
9 77
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 487
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2926
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 599
20.5%
- 487
16.6%
0 356
12.2%
8 342
11.7%
6 327
11.2%
7 183
 
6.3%
3 161
 
5.5%
4 145
 
5.0%
2 135
 
4.6%
1 114
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 599
20.5%
- 487
16.6%
0 356
12.2%
8 342
11.7%
6 327
11.2%
7 183
 
6.3%
3 161
 
5.5%
4 145
 
5.0%
2 135
 
4.6%
1 114
 
3.9%

Interactions

2023-12-11T09:10:39.069583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:10:42.208832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.905
업종명0.9051.000
2023-12-11T09:10:42.298148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.652
업종명0.6521.000

Missing values

2023-12-11T09:10:39.192894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:10:39.311794image/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

연번업종명업소명업소소재지전화번호
01숙박업(일반)재두장여관경상남도 남해군 상주면 남해대로 918-6055-862-6022
12숙박업(일반)해주여관경상남도 남해군 상주면 상주로 17-6055-862-6042
23숙박업(일반)한려산장경상남도 남해군 상주면 남해대로 591-56<NA>
34숙박업(일반)K모텔경상남도 남해군 남해읍 화전로 52-9055-864-2981
45숙박업(일반)영남장여관경상남도 남해군 남해읍 화전로38번길 28055-864-2478
56숙박업(일반)미송여관경상남도 남해군 미조면 미조로 232-4055-867-6078
67숙박업(일반)진주장여관경상남도 남해군 남해읍 화전로 52055-864-2232
78숙박업(일반)금화여관경상남도 남해군 미조면 미조로 248055-867-7001
89숙박업(일반)J모텔경상남도 남해군 남해읍 화전로38번길 25055-862-1501
910숙박업(일반)남해장여관경상남도 남해군 남해읍 화전로96번길 6-3055-864-2273
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288289미용업(일반) 미용업(피부)주노(Juno)경상남도 남해군 남해읍 화전로59번길 5<NA>
289290미용업(일반) 미용업(손톱ㆍ발톱)네일스토리경상남도 남해군 남해읍 화전로 126 2층<NA>
290291미용업(피부) 미용업(손톱ㆍ발톱)영스킨경상남도 남해군 남해읍 화전로 143 (2층)<NA>
291292미용업(손톱ㆍ발톱) 미용업(화장ㆍ분장)제이속눈썹 네일경상남도 남해군 남해읍 화전로 75-1 (2층)<NA>
292293미용업(일반) 미용업(손톱ㆍ발톱) 미용업(화장ㆍ분장)수 헤어샵경상남도 남해군 상주면 남해대로697번길 5 1층<NA>
293294건물위생관리업주식회사 청소박사경상남도 남해군 남해읍 화전로122번가길 19055-864-4222
294295건물위생관리업금산종합환경경상남도 남해군 남해읍 망운로10번가길 53-3 (신흥아파트 상가 102호)055-863-6110
295296건물위생관리업미창건설주식회사경상남도 남해군 이동면 남해대로 2406-4055-864-0007
296297건물위생관리업클린해드림(dream)경상남도 남해군 고현면 남해대로 3051-5 상가 라동 103호 (풍산아파트)055-864-6672
297298건물위생관리업(주)서호경상남도 남해군 남해읍 남해대로 2835 남해공용터미널(1층)107호<NA>