Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells193
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory703.1 KiB
Average record size in memory72.0 B

Variable types

Text3
DateTime1
Categorical3
Boolean1

Dataset

Description경상남도 빅데이터 허브 플랫폼 DB 내 인허가 미용업 중 정상 영업상태인 업장에 대한 데이터로, 사업장명, 주소, 인허가일자, 영업상태, 업태구분(네일아트, 피부미용, 일반미용 등), 다중이용업소여부 정보를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15122717

Alerts

영업상태 has constant value ""Constant
상세영업상태 has constant value ""Constant
다중이용업소여부 is highly imbalanced (99.2%)Imbalance

Reproduction

Analysis started2023-12-11 00:11:27.091997
Analysis finished2023-12-11 00:11:28.970887
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct8633
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:11:29.258549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length6.0566
Min length1

Characters and Unicode

Total characters60566
Distinct characters935
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7864 ?
Unique (%)78.6%

Sample

1st row달네일
2nd row뷰티더제이
3rd row굿헤어
4th row살롱드 센텀
5th row이삭컷트클럽
ValueCountFrequency (%)
헤어 131
 
1.1%
미용실 127
 
1.1%
hair 96
 
0.8%
네일 60
 
0.5%
nail 56
 
0.5%
에스테틱 55
 
0.5%
헤어샵 55
 
0.5%
beauty 34
 
0.3%
salon 26
 
0.2%
by 25
 
0.2%
Other values (8844) 11136
94.4%
2023-12-11T09:11:29.835752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 4042
 
6.7%
헤 3870
 
6.4%
미 2081
 
3.4%
1804
 
3.0%
실 1344
 
2.2%
용 1278
 
2.1%
리 1243
 
2.1%
스 1202
 
2.0%
일 1125
 
1.9%
이 1119
 
1.8%
Other values (925) 41458
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50664
83.7%
Lowercase Letter 3246
 
5.4%
Uppercase Letter 2441
 
4.0%
Space Separator 1804
 
3.0%
Close Punctuation 812
 
1.3%
Open Punctuation 811
 
1.3%
Other Punctuation 409
 
0.7%
Decimal Number 319
 
0.5%
Dash Punctuation 45
 
0.1%
Math Symbol 6
 
< 0.1%
Other values (3) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 4042
 
8.0%
헤 3870
 
7.6%
미 2081
 
4.1%
실 1344
 
2.7%
용 1278
 
2.5%
리 1243
 
2.5%
스 1202
 
2.4%
일 1125
 
2.2%
이 1119
 
2.2%
네 1060
 
2.1%
Other values (839) 32300
63.8%
Lowercase Letter
ValueCountFrequency (%)
a 409
12.6%
i 357
11.0%
e 324
10.0%
o 273
 
8.4%
l 234
 
7.2%
n 230
 
7.1%
r 218
 
6.7%
h 197
 
6.1%
y 159
 
4.9%
s 140
 
4.3%
Other values (16) 705
21.7%
Uppercase Letter
ValueCountFrequency (%)
A 246
 
10.1%
N 193
 
7.9%
H 184
 
7.5%
S 176
 
7.2%
I 167
 
6.8%
E 134
 
5.5%
O 134
 
5.5%
J 132
 
5.4%
L 130
 
5.3%
M 129
 
5.3%
Other values (16) 816
33.4%
Other Punctuation
ValueCountFrequency (%)
& 133
32.5%
. 105
25.7%
, 90
22.0%
: 31
 
7.6%
' 30
 
7.3%
· 8
 
2.0%
＆ 4
 
1.0%
% 2
 
0.5%
" 2
 
0.5%
! 2
 
0.5%
Other values (2) 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 91
28.5%
2 49
15.4%
0 46
14.4%
9 31
 
9.7%
5 22
 
6.9%
7 21
 
6.6%
3 20
 
6.3%
8 14
 
4.4%
4 13
 
4.1%
6 12
 
3.8%
Math Symbol
ValueCountFrequency (%)
~ 3
50.0%
+ 2
33.3%
= 1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 811
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 810
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1804
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50621
83.6%
Latin 5690
 
9.4%
Common 4212
 
7.0%
Han 43
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 4042
 
8.0%
헤 3870
 
7.6%
미 2081
 
4.1%
실 1344
 
2.7%
용 1278
 
2.5%
리 1243
 
2.5%
스 1202
 
2.4%
일 1125
 
2.2%
이 1119
 
2.2%
네 1060
 
2.1%
Other values (825) 32257
63.7%
Latin
ValueCountFrequency (%)
a 409
 
7.2%
i 357
 
6.3%
e 324
 
5.7%
o 273
 
4.8%
A 246
 
4.3%
l 234
 
4.1%
n 230
 
4.0%
r 218
 
3.8%
h 197
 
3.5%
N 193
 
3.4%
Other values (43) 3009
52.9%
Common
ValueCountFrequency (%)
1804
42.8%
) 811
19.3%
( 810
19.2%
& 133
 
3.2%
. 105
 
2.5%
1 91
 
2.2%
, 90
 
2.1%
2 49
 
1.2%
0 46
 
1.1%
- 45
 
1.1%
Other values (23) 228
 
5.4%
Han
ValueCountFrequency (%)
美 28
65.1%
愛 3
 
7.0%
珍 1
 
2.3%
熙 1
 
2.3%
作 1
 
2.3%
子 1
 
2.3%
秀 1
 
2.3%
家 1
 
2.3%
男 1
 
2.3%
守 1
 
2.3%
Other values (4) 4
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50621
83.6%
ASCII 9887
 
16.3%
CJK 43
 
0.1%
None 12
 
< 0.1%
Number Forms 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 4042
 
8.0%
헤 3870
 
7.6%
미 2081
 
4.1%
실 1344
 
2.7%
용 1278
 
2.5%
리 1243
 
2.5%
스 1202
 
2.4%
일 1125
 
2.2%
이 1119
 
2.2%
네 1060
 
2.1%
Other values (825) 32257
63.7%
ASCII
ValueCountFrequency (%)
1804
18.2%
) 811
 
8.2%
( 810
 
8.2%
a 409
 
4.1%
i 357
 
3.6%
e 324
 
3.3%
o 273
 
2.8%
A 246
 
2.5%
l 234
 
2.4%
n 230
 
2.3%
Other values (73) 4389
44.4%
CJK
ValueCountFrequency (%)
美 28
65.1%
愛 3
 
7.0%
珍 1
 
2.3%
熙 1
 
2.3%
作 1
 
2.3%
子 1
 
2.3%
秀 1
 
2.3%
家 1
 
2.3%
男 1
 
2.3%
守 1
 
2.3%
Other values (4) 4
 
9.3%
None
ValueCountFrequency (%)
· 8
66.7%
＆ 4
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%

지번주소
Text

Distinct9483
Distinct (%)95.1%
Missing33
Missing (%)0.3%
Memory size156.2 KiB
2023-12-11T09:11:30.237602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length54
Mean length28.071837
Min length15

Characters and Unicode

Total characters279792
Distinct characters579
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9129 ?
Unique (%)91.6%

Sample

1st row경상남도 김해시 관동동 1106-6
2nd row경상남도 창원시 성산구 상남동 23-8 밀레니엄타워
3rd row경상남도 창원시 마산회원구 내서읍 삼계리 25-4번지
4th row경상남도 양산시 물금읍 범어리 502-3번지 근로자복지아파트
5th row경상남도 김해시 율하동 1404번지
ValueCountFrequency (%)
경상남도 9967
 
18.0%
창원시 3409
 
6.1%
김해시 1688
 
3.0%
진주시 1178
 
2.1%
1층 1115
 
2.0%
양산시 1037
 
1.9%
의창구 821
 
1.5%
성산구 769
 
1.4%
거제시 678
 
1.2%
마산회원구 656
 
1.2%
Other values (10968) 34124
61.5%
2023-12-11T09:11:30.834156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54065
19.3%
1 13654
 
4.9%
상 12183
 
4.4%
남 10864
 
3.9%
도 10294
 
3.7%
경 10122
 
3.6%
동 9452
 
3.4%
시 9313
 
3.3%
- 8589
 
3.1%
지 8197
 
2.9%
Other values (569) 133059
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163664
58.5%
Space Separator 54065
 
19.3%
Decimal Number 51885
 
18.5%
Dash Punctuation 8589
 
3.1%
Uppercase Letter 397
 
0.1%
Close Punctuation 389
 
0.1%
Open Punctuation 388
 
0.1%
Other Punctuation 271
 
0.1%
Lowercase Letter 134
 
< 0.1%
Math Symbol 8
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 12183
 
7.4%
남 10864
 
6.6%
도 10294
 
6.3%
경 10122
 
6.2%
동 9452
 
5.8%
시 9313
 
5.7%
지 8197
 
5.0%
번 7258
 
4.4%
창 4914
 
3.0%
원 4701
 
2.9%
Other values (501) 76366
46.7%
Uppercase Letter
ValueCountFrequency (%)
A 86
21.7%
B 62
15.6%
N 24
 
6.0%
E 22
 
5.5%
C 22
 
5.5%
S 22
 
5.5%
D 18
 
4.5%
I 17
 
4.3%
P 14
 
3.5%
T 14
 
3.5%
Other values (14) 96
24.2%
Lowercase Letter
ValueCountFrequency (%)
e 36
26.9%
a 28
20.9%
l 10
 
7.5%
t 10
 
7.5%
s 8
 
6.0%
m 5
 
3.7%
i 5
 
3.7%
h 4
 
3.0%
c 4
 
3.0%
o 3
 
2.2%
Other values (11) 21
15.7%
Decimal Number
ValueCountFrequency (%)
1 13654
26.3%
2 7303
14.1%
3 5078
 
9.8%
0 4923
 
9.5%
4 4269
 
8.2%
5 3938
 
7.6%
6 3715
 
7.2%
7 3368
 
6.5%
8 2870
 
5.5%
9 2767
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 213
78.6%
' 18
 
6.6%
. 17
 
6.3%
@ 13
 
4.8%
/ 7
 
2.6%
: 3
 
1.1%
Space Separator
ValueCountFrequency (%)
54065
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8589
100.0%
Close Punctuation
ValueCountFrequency (%)
) 389
100.0%
Open Punctuation
ValueCountFrequency (%)
( 388
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163664
58.5%
Common 115596
41.3%
Latin 532
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 12183
 
7.4%
남 10864
 
6.6%
도 10294
 
6.3%
경 10122
 
6.2%
동 9452
 
5.8%
시 9313
 
5.7%
지 8197
 
5.0%
번 7258
 
4.4%
창 4914
 
3.0%
원 4701
 
2.9%
Other values (501) 76366
46.7%
Latin
ValueCountFrequency (%)
A 86
16.2%
B 62
 
11.7%
e 36
 
6.8%
a 28
 
5.3%
N 24
 
4.5%
E 22
 
4.1%
C 22
 
4.1%
S 22
 
4.1%
D 18
 
3.4%
I 17
 
3.2%
Other values (36) 195
36.7%
Common
ValueCountFrequency (%)
54065
46.8%
1 13654
 
11.8%
- 8589
 
7.4%
2 7303
 
6.3%
3 5078
 
4.4%
0 4923
 
4.3%
4 4269
 
3.7%
5 3938
 
3.4%
6 3715
 
3.2%
7 3368
 
2.9%
Other values (12) 6694
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163663
58.5%
ASCII 116127
41.5%
Compat Jamo 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54065
46.6%
1 13654
 
11.8%
- 8589
 
7.4%
2 7303
 
6.3%
3 5078
 
4.4%
0 4923
 
4.2%
4 4269
 
3.7%
5 3938
 
3.4%
6 3715
 
3.2%
7 3368
 
2.9%
Other values (57) 7225
 
6.2%
Hangul
ValueCountFrequency (%)
상 12183
 
7.4%
남 10864
 
6.6%
도 10294
 
6.3%
경 10122
 
6.2%
동 9452
 
5.8%
시 9313
 
5.7%
지 8197
 
5.0%
번 7258
 
4.4%
창 4914
 
3.0%
원 4701
 
2.9%
Other values (500) 76365
46.7%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

Distinct9670
Distinct (%)97.6%
Missing91
Missing (%)0.9%
Memory size156.2 KiB
2023-12-11T09:11:31.189736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length56
Mean length32.8681
Min length5

Characters and Unicode

Total characters325690
Distinct characters581
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9447 ?
Unique (%)95.3%

Sample

1st row경상남도 김해시 관동로 112, 1층 (관동동)
2nd row경상남도 창원시 성산구 단정로 7, 밀레니엄타워 6층 602호 (상남동)
3rd row경상남도 창원시 진해구 병암로45번길 10-2, 1층 (경화동)
4th row경상남도 창원시 마산회원구 내서읍 경남대로 933, 위너스빌딩 1층
5th row경상남도 양산시 물금읍 오봉로 185, 상가동 105호 (근로자복지아파트)
ValueCountFrequency (%)
경상남도 9908
 
14.7%
창원시 3359
 
5.0%
1층 2950
 
4.4%
김해시 1689
 
2.5%
진주시 1178
 
1.7%
양산시 1024
 
1.5%
2층 1004
 
1.5%
의창구 815
 
1.2%
성산구 766
 
1.1%
거제시 679
 
1.0%
Other values (8194) 44028
65.3%
2023-12-11T09:11:31.749607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
57526
 
17.7%
1 16359
 
5.0%
상 12484
 
3.8%
남 11246
 
3.5%
동 10883
 
3.3%
도 10365
 
3.2%
경 10162
 
3.1%
시 9415
 
2.9%
, 8813
 
2.7%
2 8460
 
2.6%
Other values (571) 169977
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187177
57.5%
Space Separator 57526
 
17.7%
Decimal Number 52487
 
16.1%
Other Punctuation 8933
 
2.7%
Open Punctuation 8303
 
2.5%
Close Punctuation 8303
 
2.5%
Dash Punctuation 2359
 
0.7%
Uppercase Letter 470
 
0.1%
Lowercase Letter 118
 
< 0.1%
Math Symbol 12
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 12484
 
6.7%
남 11246
 
6.0%
동 10883
 
5.8%
도 10365
 
5.5%
경 10162
 
5.4%
시 9415
 
5.0%
로 7842
 
4.2%
층 5320
 
2.8%
길 5116
 
2.7%
원 5099
 
2.7%
Other values (502) 99245
53.0%
Uppercase Letter
ValueCountFrequency (%)
A 119
25.3%
B 92
19.6%
S 28
 
6.0%
C 24
 
5.1%
D 24
 
5.1%
E 24
 
5.1%
N 22
 
4.7%
I 17
 
3.6%
K 13
 
2.8%
L 10
 
2.1%
Other values (15) 97
20.6%
Lowercase Letter
ValueCountFrequency (%)
e 35
29.7%
a 27
22.9%
t 10
 
8.5%
l 8
 
6.8%
c 6
 
5.1%
s 6
 
5.1%
m 4
 
3.4%
h 4
 
3.4%
y 3
 
2.5%
i 3
 
2.5%
Other values (6) 12
 
10.2%
Decimal Number
ValueCountFrequency (%)
1 16359
31.2%
2 8460
16.1%
0 5291
 
10.1%
3 5014
 
9.6%
4 3670
 
7.0%
5 3446
 
6.6%
6 2877
 
5.5%
7 2718
 
5.2%
8 2370
 
4.5%
9 2282
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 8813
98.7%
· 59
 
0.7%
. 19
 
0.2%
@ 15
 
0.2%
' 12
 
0.1%
/ 7
 
0.1%
: 5
 
0.1%
* 2
 
< 0.1%
& 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 8301
> 99.9%
[ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 8301
> 99.9%
] 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
57526
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2359
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187177
57.5%
Common 137924
42.3%
Latin 589
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 12484
 
6.7%
남 11246
 
6.0%
동 10883
 
5.8%
도 10365
 
5.5%
경 10162
 
5.4%
시 9415
 
5.0%
로 7842
 
4.2%
층 5320
 
2.8%
길 5116
 
2.7%
원 5099
 
2.7%
Other values (502) 99245
53.0%
Latin
ValueCountFrequency (%)
A 119
20.2%
B 92
15.6%
e 35
 
5.9%
S 28
 
4.8%
a 27
 
4.6%
C 24
 
4.1%
D 24
 
4.1%
E 24
 
4.1%
N 22
 
3.7%
I 17
 
2.9%
Other values (32) 177
30.1%
Common
ValueCountFrequency (%)
57526
41.7%
1 16359
 
11.9%
, 8813
 
6.4%
2 8460
 
6.1%
( 8301
 
6.0%
) 8301
 
6.0%
0 5291
 
3.8%
3 5014
 
3.6%
4 3670
 
2.7%
5 3446
 
2.5%
Other values (17) 12743
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 187176
57.5%
ASCII 138453
42.5%
None 59
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57526
41.5%
1 16359
 
11.8%
, 8813
 
6.4%
2 8460
 
6.1%
( 8301
 
6.0%
) 8301
 
6.0%
0 5291
 
3.8%
3 5014
 
3.6%
4 3670
 
2.7%
5 3446
 
2.5%
Other values (57) 13272
 
9.6%
Hangul
ValueCountFrequency (%)
상 12484
 
6.7%
남 11246
 
6.0%
동 10883
 
5.8%
도 10365
 
5.5%
경 10162
 
5.4%
시 9415
 
5.0%
로 7842
 
4.2%
층 5320
 
2.8%
길 5116
 
2.7%
원 5099
 
2.7%
Other values (501) 99244
53.0%
None
ValueCountFrequency (%)
· 59
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

인허가일자
Date

Distinct4702
Distinct (%)47.0%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum1956-11-08 00:00:00
Maximum2023-06-08 00:00:00
2023-12-11T09:11:31.936428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:11:32.087322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 10000
100.0%

Length

2023-12-11T09:11:32.245366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:11:32.364238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 10000
100.0%

상세영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 10000
100.0%

Length

2023-12-11T09:11:32.716750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:11:32.808924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 10000
100.0%

업태구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반미용업
6679 
피부미용업
1608 
네일아트업
1235 
메이크업업
 
346
기타
 
128
Other values (2)
 
4

Length

Max length6
Median length5
Mean length4.9619
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row네일아트업
2nd row피부미용업
3rd row기타
4th row일반미용업
5th row일반미용업

Common Values

ValueCountFrequency (%)
일반미용업 6679
66.8%
피부미용업 1608
 
16.1%
네일아트업 1235
 
12.3%
메이크업업 346
 
3.5%
기타 128
 
1.3%
미용업 기타 3
 
< 0.1%
일반이용업 1
 
< 0.1%

Length

2023-12-11T09:11:32.936110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:11:33.082608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 6679
66.8%
피부미용업 1608
 
16.1%
네일아트업 1235
 
12.3%
메이크업업 346
 
3.5%
기타 131
 
1.3%
미용업 3
 
< 0.1%
일반이용업 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing68
Missing (%)0.7%
Memory size97.7 KiB
False
9925 
True
 
7
(Missing)
 
68
ValueCountFrequency (%)
False 9925
99.2%
True 7
 
0.1%
(Missing) 68
 
0.7%
2023-12-11T09:11:33.203220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:11:33.260580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태구분다중이용업소여부
업태구분1.0000.000
다중이용업소여부0.0001.000
2023-12-11T09:11:33.353677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태구분다중이용업소여부
업태구분1.0000.000
다중이용업소여부0.0001.000
2023-12-11T09:11:33.445277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태구분다중이용업소여부
업태구분1.0000.000
다중이용업소여부0.0001.000

Missing values

2023-12-11T09:11:28.651566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:11:28.781124image/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.
2023-12-11T09:11:28.899003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

사업장명지번주소도로명주소인허가일자영업상태상세영업상태업태구분다중이용업소여부
11033달네일경상남도 김해시 관동동 1106-6경상남도 김해시 관동로 112, 1층 (관동동)2019-06-10영업/정상영업네일아트업N
10799뷰티더제이경상남도 창원시 성산구 상남동 23-8 밀레니엄타워경상남도 창원시 성산구 단정로 7, 밀레니엄타워 6층 602호 (상남동)2021-05-10영업/정상영업피부미용업N
7327굿헤어<NA>경상남도 창원시 진해구 병암로45번길 10-2, 1층 (경화동)1996-07-26영업/정상영업기타N
7076살롱드 센텀경상남도 창원시 마산회원구 내서읍 삼계리 25-4번지경상남도 창원시 마산회원구 내서읍 경남대로 933, 위너스빌딩 1층2018-09-11영업/정상영업일반미용업N
4753이삭컷트클럽경상남도 양산시 물금읍 범어리 502-3번지 근로자복지아파트경상남도 양산시 물금읍 오봉로 185, 상가동 105호 (근로자복지아파트)2006-06-07영업/정상영업일반미용업N
2517설렘헤어샾경상남도 김해시 율하동 1404번지경상남도 김해시 율하2로 178, 2층 201`호 (율하동)2016-08-16영업/정상영업일반미용업N
10067승지미용실경상남도 창원시 마산합포구 오동동 307-1경상남도 창원시 마산합포구 오동동14길 62, 1층 일부호 (오동동)2020-10-15영업/정상영업일반미용업N
10761아네뜨헤어(Anette헤어)경상남도 진주시 가좌동 478-6 JS현서빌딩 1층 101호경상남도 진주시 진주대로 540, JS현서빌딩 1층 101호 (가좌동)2021-04-30영업/정상영업일반미용업N
7816제이원미용실경상남도 창원시 마산합포구 남성동 172-2번지 (지상1층)경상남도 창원시 마산합포구 동서북7길 38 (남성동,(지상1층))2003-10-29영업/정상영업일반미용업N
2883민피부바디관리경상남도 김해시 대청동 315-2번지 2층 재영사우나(여탕내)경상남도 김해시 삼문로 26, 재영사우나(여탕내) 2층 (대청동)2015-01-30영업/정상영업피부미용업N
사업장명지번주소도로명주소인허가일자영업상태상세영업상태업태구분다중이용업소여부
8895김영희헤어콜렉션미용실경상남도 창원시 성산구 남양동 23번지 개나리3차a'상가 108호경상남도 창원시 성산구 대정로 102, 108호 (남양동, 개나리3차a'상가)1998-06-13영업/정상영업일반미용업N
3778상동경상남도 밀양시 상동면 금산리 882-6번지경상남도 밀양시 상동면 상동로 5831997-12-27영업/정상영업일반이용업N
3873리앤리네일경상남도 밀양시 가곡동 654-9번지경상남도 밀양시 중앙로 132-2 (가곡동)2013-03-11영업/정상영업일반미용업N
8067조은 헤어펌경상남도 창원시 의창구 팔용동 135-1번지 1층경상남도 창원시 의창구 사화로18번길 1 (팔용동, 1층)2004-04-14영업/정상영업일반미용업N
5640세븐헤어라인경상남도 함안군 가야읍 말산리 457-19번지 세븐헤어라인경상남도 함안군 가야읍 가야로 26, 세븐헤어라인1996-09-12영업/정상영업일반미용업N
5674강 헤어경상남도 함안군 법수면 윤외리 145-9번지경상남도 함안군 법수면 석무길 144, 1호2009-06-29영업/정상영업일반미용업N
1062눈부신날에경상남도 진주시 충무공동 82-2번지 201호경상남도 진주시 범골로 56 (충무공동, 201호)2017-12-07영업/정상영업피부미용업N
10241도도미용실경상남도 김해시 삼정동 601-7경상남도 김해시 김해대로2471번길 17, 1층 (삼정동)2020-12-02영업/정상영업일반미용업N
7420제이제이(JJ)퀸즈 헤어경상남도 창원시 마산합포구 산호동 114-8번지 (지상1층)경상남도 창원시 마산합포구 산호남로 42 (산호동,(지상1층))2002-09-02영업/정상영업일반미용업N
4187머릿터경상남도 거제시 옥포동 513-1번지 (1층)경상남도 거제시 옥포중앙로 44 (옥포동,(1층))2010-10-15영업/정상영업일반미용업N