Overview

Dataset statistics

Number of variables5
Number of observations161
Missing cells44
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory40.8 B

Variable types

Categorical2
Text3

Dataset

Description경상남도 창녕군 공중위생업 미용업에 대한 현황 데이터를 포함하고 있습니다.(업종명, 업소명, 영업소 주소, 소재지전화번호 제공)
Author경상남도 창녕군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15006909

Alerts

업종명 is highly overall correlated with 업태명High correlation
업태명 is highly overall correlated with 업종명High correlation
업태명 is highly imbalanced (56.8%)Imbalance
전화번호 has 44 (27.3%) missing valuesMissing

Reproduction

Analysis started2023-12-11 00:20:41.021496
Analysis finished2023-12-11 00:20:41.527766
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
미용업
97 
미용업(일반)
30 
미용업(피부)
16 
미용업(손톱ㆍ발톱)
 
7
미용업(종합)
 
4
Other values (4)
 
7

Length

Max length31
Median length3
Mean length5.5403727
Min length3

Unique

Unique3 ?
Unique (%)1.9%

Sample

1st row미용업
2nd row미용업
3rd row미용업
4th row미용업
5th row미용업

Common Values

ValueCountFrequency (%)
미용업 97
60.2%
미용업(일반) 30
 
18.6%
미용업(피부) 16
 
9.9%
미용업(손톱ㆍ발톱) 7
 
4.3%
미용업(종합) 4
 
2.5%
미용업(일반), 미용업(손톱ㆍ발톱), 미용업(화장ㆍ분장) 4
 
2.5%
미용업(일반), 미용업(피부) 1
 
0.6%
미용업(피부), 미용업(손톱ㆍ발톱) 1
 
0.6%
미용업(손톱ㆍ발톱), 미용업(화장ㆍ분장) 1
 
0.6%

Length

2023-12-11T09:20:41.617233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:20:41.756181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미용업 97
56.4%
미용업(일반 35
 
20.3%
미용업(피부 18
 
10.5%
미용업(손톱ㆍ발톱 13
 
7.6%
미용업(화장ㆍ분장 5
 
2.9%
미용업(종합 4
 
2.3%

업태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
일반미용업
133 
피부미용업
17 
네일아트업
 
10
기타
 
1

Length

Max length5
Median length5
Mean length4.9813665
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row일반미용업
2nd row일반미용업
3rd row일반미용업
4th row일반미용업
5th row일반미용업

Common Values

ValueCountFrequency (%)
일반미용업 133
82.6%
피부미용업 17
 
10.6%
네일아트업 10
 
6.2%
기타 1
 
0.6%

Length

2023-12-11T09:20:41.958893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:20:42.077497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 133
82.6%
피부미용업 17
 
10.6%
네일아트업 10
 
6.2%
기타 1
 
0.6%

업소명
Text

Distinct160
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T09:20:42.390379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length5.4223602
Min length2

Characters and Unicode

Total characters873
Distinct characters232
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

Unique159 ?
Unique (%)98.8%

Sample

1st row명랑미용실
2nd row경남미용실
3rd row동백미용실
4th row낙원미용실
5th row은하미장원
ValueCountFrequency (%)
헤어샵 4
 
2.2%
미용실 2
 
1.1%
창녕점 2
 
1.1%
헤어 2
 
1.1%
헤어매니아 2
 
1.1%
진미용실 2
 
1.1%
서울미장원 1
 
0.5%
퀸헤어 1
 
0.5%
여정미용실 1
 
0.5%
빈's헤어 1
 
0.5%
Other values (166) 166
90.2%
2023-12-11T09:20:42.917793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 61
 
7.0%
미 61
 
7.0%
헤 58
 
6.6%
실 53
 
6.1%
용 50
 
5.7%
리 29
 
3.3%
23
 
2.6%
스 15
 
1.7%
머 15
 
1.7%
이 12
 
1.4%
Other values (222) 496
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 808
92.6%
Space Separator 23
 
2.6%
Lowercase Letter 19
 
2.2%
Uppercase Letter 12
 
1.4%
Other Punctuation 5
 
0.6%
Decimal Number 3
 
0.3%
Open Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 61
 
7.5%
미 61
 
7.5%
헤 58
 
7.2%
실 53
 
6.6%
용 50
 
6.2%
리 29
 
3.6%
스 15
 
1.9%
머 15
 
1.9%
이 12
 
1.5%
샵 11
 
1.4%
Other values (193) 443
54.8%
Lowercase Letter
ValueCountFrequency (%)
o 3
15.8%
e 3
15.8%
r 2
10.5%
l 2
10.5%
a 2
10.5%
t 1
 
5.3%
h 1
 
5.3%
n 1
 
5.3%
b 1
 
5.3%
d 1
 
5.3%
Other values (2) 2
10.5%
Uppercase Letter
ValueCountFrequency (%)
S 5
41.7%
D 1
 
8.3%
H 1
 
8.3%
N 1
 
8.3%
R 1
 
8.3%
T 1
 
8.3%
C 1
 
8.3%
F 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
3 1
33.3%
2 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
' 2
40.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 808
92.6%
Common 34
 
3.9%
Latin 31
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 61
 
7.5%
미 61
 
7.5%
헤 58
 
7.2%
실 53
 
6.6%
용 50
 
6.2%
리 29
 
3.6%
스 15
 
1.9%
머 15
 
1.9%
이 12
 
1.5%
샵 11
 
1.4%
Other values (193) 443
54.8%
Latin
ValueCountFrequency (%)
S 5
16.1%
o 3
 
9.7%
e 3
 
9.7%
r 2
 
6.5%
l 2
 
6.5%
a 2
 
6.5%
t 1
 
3.2%
D 1
 
3.2%
h 1
 
3.2%
H 1
 
3.2%
Other values (10) 10
32.3%
Common
ValueCountFrequency (%)
23
67.6%
. 3
 
8.8%
' 2
 
5.9%
( 1
 
2.9%
- 1
 
2.9%
) 1
 
2.9%
1 1
 
2.9%
3 1
 
2.9%
2 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 808
92.6%
ASCII 65
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 61
 
7.5%
미 61
 
7.5%
헤 58
 
7.2%
실 53
 
6.6%
용 50
 
6.2%
리 29
 
3.6%
스 15
 
1.9%
머 15
 
1.9%
이 12
 
1.5%
샵 11
 
1.4%
Other values (193) 443
54.8%
ASCII
ValueCountFrequency (%)
23
35.4%
S 5
 
7.7%
o 3
 
4.6%
. 3
 
4.6%
e 3
 
4.6%
r 2
 
3.1%
' 2
 
3.1%
l 2
 
3.1%
a 2
 
3.1%
t 1
 
1.5%
Other values (19) 19
29.2%

소재지도로명주소
Text

Distinct156
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T09:20:43.332438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length38
Mean length21.832298
Min length17

Characters and Unicode

Total characters3515
Distinct characters115
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

Unique151 ?
Unique (%)93.8%

Sample

1st row경상남도 창녕군 남지읍 남지리 284번지 2호
2nd row경상남도 창녕군 창녕읍 당산1길 26-16
3rd row경상남도 창녕군 영산면 영산중앙길 9
4th row경상남도 창녕군 대합면 창한로 106-1
5th row경상남도 창녕군 이방면 장천리 5번지
ValueCountFrequency (%)
경상남도 161
19.0%
창녕군 161
19.0%
창녕읍 74
 
8.7%
남지읍 39
 
4.6%
영산면 21
 
2.5%
낙동로 14
 
1.7%
부곡면 11
 
1.3%
명덕로 11
 
1.3%
종로 10
 
1.2%
화왕산1로 10
 
1.2%
Other values (200) 335
39.6%
2023-12-11T09:20:43.953193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
719
20.5%
창 250
 
7.1%
녕 246
 
7.0%
남 212
 
6.0%
상 168
 
4.8%
도 166
 
4.7%
경 163
 
4.6%
군 161
 
4.6%
1 128
 
3.6%
읍 113
 
3.2%
Other values (105) 1189
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2268
64.5%
Space Separator 719
 
20.5%
Decimal Number 458
 
13.0%
Dash Punctuation 36
 
1.0%
Other Punctuation 16
 
0.5%
Close Punctuation 9
 
0.3%
Open Punctuation 9
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
창 250
 
11.0%
녕 246
 
10.8%
남 212
 
9.3%
상 168
 
7.4%
도 166
 
7.3%
경 163
 
7.2%
군 161
 
7.1%
읍 113
 
5.0%
길 76
 
3.4%
로 76
 
3.4%
Other values (90) 637
28.1%
Decimal Number
ValueCountFrequency (%)
1 128
27.9%
2 62
13.5%
4 54
11.8%
3 44
 
9.6%
0 37
 
8.1%
9 34
 
7.4%
6 30
 
6.6%
7 26
 
5.7%
5 24
 
5.2%
8 19
 
4.1%
Space Separator
ValueCountFrequency (%)
719
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2268
64.5%
Common 1247
35.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
창 250
 
11.0%
녕 246
 
10.8%
남 212
 
9.3%
상 168
 
7.4%
도 166
 
7.3%
경 163
 
7.2%
군 161
 
7.1%
읍 113
 
5.0%
길 76
 
3.4%
로 76
 
3.4%
Other values (90) 637
28.1%
Common
ValueCountFrequency (%)
719
57.7%
1 128
 
10.3%
2 62
 
5.0%
4 54
 
4.3%
3 44
 
3.5%
0 37
 
3.0%
- 36
 
2.9%
9 34
 
2.7%
6 30
 
2.4%
7 26
 
2.1%
Other values (5) 77
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2268
64.5%
ASCII 1247
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
719
57.7%
1 128
 
10.3%
2 62
 
5.0%
4 54
 
4.3%
3 44
 
3.5%
0 37
 
3.0%
- 36
 
2.9%
9 34
 
2.7%
6 30
 
2.4%
7 26
 
2.1%
Other values (5) 77
 
6.2%
Hangul
ValueCountFrequency (%)
창 250
 
11.0%
녕 246
 
10.8%
남 212
 
9.3%
상 168
 
7.4%
도 166
 
7.3%
경 163
 
7.2%
군 161
 
7.1%
읍 113
 
5.0%
길 76
 
3.4%
로 76
 
3.4%
Other values (90) 637
28.1%

전화번호
Text

MISSING 

Distinct117
Distinct (%)100.0%
Missing44
Missing (%)27.3%
Memory size1.4 KiB
2023-12-11T09:20:44.297570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.017094
Min length12

Characters and Unicode

Total characters1406
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

Unique117 ?
Unique (%)100.0%

Sample

1st row055-526-2331
2nd row055-532-1719
3rd row055-536-2919
4th row055-532-1907
5th row055-532-6034
ValueCountFrequency (%)
055-521-0946 1
 
0.9%
055-521-4117 1
 
0.9%
055-526-1192 1
 
0.9%
055-533-5562 1
 
0.9%
055-532-8782 1
 
0.9%
055-251-7970 1
 
0.9%
055-533-6587 1
 
0.9%
055-532-9091 1
 
0.9%
070-8141-2509 1
 
0.9%
055-536-7212 1
 
0.9%
Other values (107) 107
91.5%
2023-12-11T09:20:44.728321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 388
27.6%
- 234
16.6%
0 178
12.7%
3 148
 
10.5%
2 134
 
9.5%
1 82
 
5.8%
6 80
 
5.7%
7 56
 
4.0%
9 40
 
2.8%
4 34
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1172
83.4%
Dash Punctuation 234
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 388
33.1%
0 178
15.2%
3 148
 
12.6%
2 134
 
11.4%
1 82
 
7.0%
6 80
 
6.8%
7 56
 
4.8%
9 40
 
3.4%
4 34
 
2.9%
8 32
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 234
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1406
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 388
27.6%
- 234
16.6%
0 178
12.7%
3 148
 
10.5%
2 134
 
9.5%
1 82
 
5.8%
6 80
 
5.7%
7 56
 
4.0%
9 40
 
2.8%
4 34
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1406
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 388
27.6%
- 234
16.6%
0 178
12.7%
3 148
 
10.5%
2 134
 
9.5%
1 82
 
5.8%
6 80
 
5.7%
7 56
 
4.0%
9 40
 
2.8%
4 34
 
2.4%

Correlations

2023-12-11T09:20:44.820897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명
업종명1.0000.872
업태명0.8721.000
2023-12-11T09:20:44.898611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명
업종명1.0000.761
업태명0.7611.000
2023-12-11T09:20:45.208272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명
업종명1.0000.761
업태명0.7611.000

Missing values

2023-12-11T09:20:41.362793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:20:41.476880image/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

업종명업태명업소명소재지도로명주소전화번호
0미용업일반미용업명랑미용실경상남도 창녕군 남지읍 남지리 284번지 2호055-526-2331
1미용업일반미용업경남미용실경상남도 창녕군 창녕읍 당산1길 26-16055-532-1719
2미용업일반미용업동백미용실경상남도 창녕군 영산면 영산중앙길 9055-536-2919
3미용업일반미용업낙원미용실경상남도 창녕군 대합면 창한로 106-1055-532-1907
4미용업일반미용업은하미장원경상남도 창녕군 이방면 장천리 5번지055-532-6034
5미용업일반미용업서울미장원경상남도 창녕군 이방면 이방대합로 336-1055-532-5842
6미용업일반미용업소양미용실경상남도 창녕군 창녕읍 옥만길 30055-533-3013
7미용업일반미용업이방미장원경상남도 창녕군 이방면 장천리 6번지 3호055-532-5172
8미용업일반미용업우리미용실경상남도 창녕군 창녕읍 우포2로 1213055-533-7312
9미용업일반미용업새미용실경상남도 창녕군 남지읍 낙동로 466055-526-4300
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151미용업(손톱ㆍ발톱)네일아트업예뻐지는집경상남도 창녕군 창녕읍 남창녕로 76-1<NA>
152미용업(손톱ㆍ발톱)네일아트업네일 고이고이경상남도 창녕군 창녕읍 술정중앙길 34<NA>
153미용업(손톱ㆍ발톱)네일아트업네일빛나다경상남도 창녕군 부곡면 온천1길 49<NA>
154미용업(일반), 미용업(피부)피부미용업제이부띠 창녕점경상남도 창녕군 창녕읍 화왕산1로 12, 104호070-4191-6516
155미용업(피부), 미용업(손톱ㆍ발톱)네일아트업가윤경상남도 창녕군 남지읍 낙동로 480055-521-5554
156미용업(손톱ㆍ발톱), 미용업(화장ㆍ분장)네일아트업나나살롱경상남도 창녕군 창녕읍 종로 7<NA>
157미용업(일반), 미용업(손톱ㆍ발톱), 미용업(화장ㆍ분장)일반미용업킴헤어경상남도 창녕군 남지읍 남지중앙로 8-2<NA>
158미용업(일반), 미용업(손톱ㆍ발톱), 미용업(화장ㆍ분장)일반미용업주니헤어경상남도 창녕군 창녕읍 옥만길 43<NA>
159미용업(일반), 미용업(손톱ㆍ발톱), 미용업(화장ㆍ분장)일반미용업이승연헤어경상남도 창녕군 부곡면 부곡로 42055-536-4405
160미용업(일반), 미용업(손톱ㆍ발톱), 미용업(화장ㆍ분장)일반미용업모아Style경상남도 창녕군 창녕읍 화왕산1로 37, 1층<NA>