Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells207
Missing cells (%)0.3%
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://www.data.go.kr/data/15122717/fileData.do

Alerts

영업상태 has constant value ""Constant
상세영업상태 has constant value ""Constant
다중이용업소여부 is highly imbalanced (99.3%)Imbalance

Reproduction

Analysis started2023-12-12 23:41:33.458032
Analysis finished2023-12-12 23:41:35.975038
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct8624
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T08:41:36.209244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length6.0902
Min length1

Characters and Unicode

Total characters60902
Distinct characters932
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

Unique7862 ?
Unique (%)78.6%

Sample

1st row김용 헤어던!(hair Done!)
2nd row김진혜Skin&Body(스킨앤바디)
3rd row머리하자헤어샵
4th row김난영 스킨케어
5th row나나헤어
ValueCountFrequency (%)
헤어 128
 
1.1%
미용실 128
 
1.1%
hair 97
 
0.8%
네일 57
 
0.5%
에스테틱 55
 
0.5%
헤어샵 55
 
0.5%
nail 46
 
0.4%
beauty 34
 
0.3%
salon 29
 
0.2%
헤어살롱 23
 
0.2%
Other values (8877) 11155
94.5%
2023-12-13T08:41:36.679157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 4071
 
6.7%
헤 3894
 
6.4%
미 2062
 
3.4%
1810
 
3.0%
실 1319
 
2.2%
용 1255
 
2.1%
스 1235
 
2.0%
리 1235
 
2.0%
일 1144
 
1.9%
이 1130
 
1.9%
Other values (922) 41747
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50728
83.3%
Lowercase Letter 3414
 
5.6%
Uppercase Letter 2491
 
4.1%
Space Separator 1810
 
3.0%
Close Punctuation 832
 
1.4%
Open Punctuation 831
 
1.4%
Other Punctuation 424
 
0.7%
Decimal Number 312
 
0.5%
Dash Punctuation 46
 
0.1%
Connector Punctuation 5
 
< 0.1%
Other values (3) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 4071
 
8.0%
헤 3894
 
7.7%
미 2062
 
4.1%
실 1319
 
2.6%
용 1255
 
2.5%
스 1235
 
2.4%
리 1235
 
2.4%
일 1144
 
2.3%
이 1130
 
2.2%
네 1078
 
2.1%
Other values (838) 32305
63.7%
Lowercase Letter
ValueCountFrequency (%)
a 433
12.7%
i 368
10.8%
e 335
9.8%
o 293
 
8.6%
n 248
 
7.3%
l 234
 
6.9%
r 230
 
6.7%
h 196
 
5.7%
y 166
 
4.9%
u 142
 
4.2%
Other values (16) 769
22.5%
Uppercase Letter
ValueCountFrequency (%)
A 247
 
9.9%
H 197
 
7.9%
S 186
 
7.5%
N 183
 
7.3%
I 173
 
6.9%
E 139
 
5.6%
L 135
 
5.4%
J 134
 
5.4%
R 131
 
5.3%
O 129
 
5.2%
Other values (16) 837
33.6%
Other Punctuation
ValueCountFrequency (%)
& 139
32.8%
. 111
26.2%
, 96
22.6%
' 32
 
7.5%
: 29
 
6.8%
· 7
 
1.7%
＆ 3
 
0.7%
! 2
 
0.5%
" 2
 
0.5%
/ 1
 
0.2%
Other values (2) 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 85
27.2%
2 51
16.3%
0 41
13.1%
9 30
 
9.6%
5 21
 
6.7%
7 20
 
6.4%
3 19
 
6.1%
6 17
 
5.4%
8 15
 
4.8%
4 13
 
4.2%
Math Symbol
ValueCountFrequency (%)
~ 3
60.0%
= 1
 
20.0%
+ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1810
100.0%
Close Punctuation
ValueCountFrequency (%)
) 832
100.0%
Open Punctuation
ValueCountFrequency (%)
( 831
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
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 50685
83.2%
Latin 5908
 
9.7%
Common 4266
 
7.0%
Han 43
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 4071
 
8.0%
헤 3894
 
7.7%
미 2062
 
4.1%
실 1319
 
2.6%
용 1255
 
2.5%
스 1235
 
2.4%
리 1235
 
2.4%
일 1144
 
2.3%
이 1130
 
2.2%
네 1078
 
2.1%
Other values (823) 32262
63.7%
Latin
ValueCountFrequency (%)
a 433
 
7.3%
i 368
 
6.2%
e 335
 
5.7%
o 293
 
5.0%
n 248
 
4.2%
A 247
 
4.2%
l 234
 
4.0%
r 230
 
3.9%
H 197
 
3.3%
h 196
 
3.3%
Other values (43) 3127
52.9%
Common
ValueCountFrequency (%)
1810
42.4%
) 832
19.5%
( 831
19.5%
& 139
 
3.3%
. 111
 
2.6%
, 96
 
2.3%
1 85
 
2.0%
2 51
 
1.2%
- 46
 
1.1%
0 41
 
1.0%
Other values (21) 224
 
5.3%
Han
ValueCountFrequency (%)
美 26
60.5%
愛 3
 
7.0%
利 2
 
4.7%
人 1
 
2.3%
喜 1
 
2.3%
炎 1
 
2.3%
守 1
 
2.3%
作 1
 
2.3%
月 1
 
2.3%
熙 1
 
2.3%
Other values (5) 5
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50685
83.2%
ASCII 10161
 
16.7%
CJK 43
 
0.1%
None 10
 
< 0.1%
Number Forms 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 4071
 
8.0%
헤 3894
 
7.7%
미 2062
 
4.1%
실 1319
 
2.6%
용 1255
 
2.5%
스 1235
 
2.4%
리 1235
 
2.4%
일 1144
 
2.3%
이 1130
 
2.2%
네 1078
 
2.1%
Other values (823) 32262
63.7%
ASCII
ValueCountFrequency (%)
1810
 
17.8%
) 832
 
8.2%
( 831
 
8.2%
a 433
 
4.3%
i 368
 
3.6%
e 335
 
3.3%
o 293
 
2.9%
n 248
 
2.4%
A 247
 
2.4%
l 234
 
2.3%
Other values (71) 4530
44.6%
CJK
ValueCountFrequency (%)
美 26
60.5%
愛 3
 
7.0%
利 2
 
4.7%
人 1
 
2.3%
喜 1
 
2.3%
炎 1
 
2.3%
守 1
 
2.3%
作 1
 
2.3%
月 1
 
2.3%
熙 1
 
2.3%
Other values (5) 5
 
11.6%
None
ValueCountFrequency (%)
· 7
70.0%
＆ 3
30.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%

지번주소
Text

Distinct9471
Distinct (%)95.1%
Missing37
Missing (%)0.4%
Memory size156.2 KiB
2023-12-13T08:41:36.995021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length54
Mean length28.054401
Min length16

Characters and Unicode

Total characters279506
Distinct characters575
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9104 ?
Unique (%)91.4%

Sample

1st row경상남도 창원시 의창구 대원동 121번지 더시티세븐 W124호
2nd row경상남도 김해시 진영읍 진영리 1594-5번지
3rd row경상남도 하동군 진교면 진교리 288-1
4th row경상남도 거제시 고현동 820-7 3층
5th row경상남도 창원시 의창구 팔용동 125번지
ValueCountFrequency (%)
경상남도 9963
 
18.0%
창원시 3388
 
6.1%
김해시 1676
 
3.0%
진주시 1208
 
2.2%
1층 1132
 
2.0%
양산시 1048
 
1.9%
의창구 802
 
1.4%
성산구 759
 
1.4%
거제시 670
 
1.2%
마산회원구 653
 
1.2%
Other values (10941) 34117
61.6%
2023-12-13T08:41:37.474162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54047
19.3%
1 13742
 
4.9%
상 12198
 
4.4%
남 10876
 
3.9%
도 10290
 
3.7%
경 10121
 
3.6%
동 9437
 
3.4%
시 9303
 
3.3%
- 8568
 
3.1%
지 8238
 
2.9%
Other values (565) 132686
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163487
58.5%
Space Separator 54047
 
19.3%
Decimal Number 51862
 
18.6%
Dash Punctuation 8568
 
3.1%
Open Punctuation 391
 
0.1%
Uppercase Letter 391
 
0.1%
Close Punctuation 390
 
0.1%
Other Punctuation 247
 
0.1%
Lowercase Letter 111
 
< 0.1%
Math Symbol 9
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 12198
 
7.5%
남 10876
 
6.7%
도 10290
 
6.3%
경 10121
 
6.2%
동 9437
 
5.8%
시 9303
 
5.7%
지 8238
 
5.0%
번 7277
 
4.5%
창 4888
 
3.0%
원 4667
 
2.9%
Other values (494) 76192
46.6%
Uppercase Letter
ValueCountFrequency (%)
A 81
20.7%
B 56
14.3%
S 27
 
6.9%
N 25
 
6.4%
E 22
 
5.6%
C 22
 
5.6%
D 19
 
4.9%
I 16
 
4.1%
T 13
 
3.3%
P 13
 
3.3%
Other values (15) 97
24.8%
Lowercase Letter
ValueCountFrequency (%)
e 32
28.8%
a 24
21.6%
l 8
 
7.2%
t 8
 
7.2%
s 7
 
6.3%
i 4
 
3.6%
m 4
 
3.6%
h 4
 
3.6%
c 3
 
2.7%
w 3
 
2.7%
Other values (11) 14
12.6%
Decimal Number
ValueCountFrequency (%)
1 13742
26.5%
2 7234
13.9%
3 5103
 
9.8%
0 4948
 
9.5%
4 4283
 
8.3%
5 3877
 
7.5%
6 3722
 
7.2%
7 3346
 
6.5%
8 2817
 
5.4%
9 2790
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 194
78.5%
. 17
 
6.9%
' 16
 
6.5%
@ 11
 
4.5%
/ 6
 
2.4%
: 2
 
0.8%
& 1
 
0.4%
Space Separator
ValueCountFrequency (%)
54047
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8568
100.0%
Open Punctuation
ValueCountFrequency (%)
( 391
100.0%
Close Punctuation
ValueCountFrequency (%)
) 390
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163487
58.5%
Common 115516
41.3%
Latin 503
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 12198
 
7.5%
남 10876
 
6.7%
도 10290
 
6.3%
경 10121
 
6.2%
동 9437
 
5.8%
시 9303
 
5.7%
지 8238
 
5.0%
번 7277
 
4.5%
창 4888
 
3.0%
원 4667
 
2.9%
Other values (494) 76192
46.6%
Latin
ValueCountFrequency (%)
A 81
16.1%
B 56
 
11.1%
e 32
 
6.4%
S 27
 
5.4%
N 25
 
5.0%
a 24
 
4.8%
E 22
 
4.4%
C 22
 
4.4%
D 19
 
3.8%
I 16
 
3.2%
Other values (37) 179
35.6%
Common
ValueCountFrequency (%)
54047
46.8%
1 13742
 
11.9%
- 8568
 
7.4%
2 7234
 
6.3%
3 5103
 
4.4%
0 4948
 
4.3%
4 4283
 
3.7%
5 3877
 
3.4%
6 3722
 
3.2%
7 3346
 
2.9%
Other values (14) 6646
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163486
58.5%
ASCII 116018
41.5%
Compat Jamo 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54047
46.6%
1 13742
 
11.8%
- 8568
 
7.4%
2 7234
 
6.2%
3 5103
 
4.4%
0 4948
 
4.3%
4 4283
 
3.7%
5 3877
 
3.3%
6 3722
 
3.2%
7 3346
 
2.9%
Other values (60) 7148
 
6.2%
Hangul
ValueCountFrequency (%)
상 12198
 
7.5%
남 10876
 
6.7%
도 10290
 
6.3%
경 10121
 
6.2%
동 9437
 
5.8%
시 9303
 
5.7%
지 8238
 
5.0%
번 7277
 
4.5%
창 4888
 
3.0%
원 4667
 
2.9%
Other values (493) 76191
46.6%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

Distinct9667
Distinct (%)97.6%
Missing95
Missing (%)0.9%
Memory size156.2 KiB
2023-12-13T08:41:37.784130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length56
Mean length32.815447
Min length5

Characters and Unicode

Total characters325037
Distinct characters585
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

Unique9445 ?
Unique (%)95.4%

Sample

1st row경상남도 창원시 의창구 원이대로 320, W124호 (대원동, 더시티세븐)
2nd row경상남도 김해시 진영읍 김해대로321번길 4-14, 1층
3rd row경상남도 하동군 진교면 민다리안길 116
4th row경상남도 거제시 거제중앙로 1897 (고현동,3층)
5th row경상남도 창원시 의창구 남산로 20 (팔용동)
ValueCountFrequency (%)
경상남도 9904
 
14.7%
창원시 3340
 
5.0%
1층 2925
 
4.3%
김해시 1677
 
2.5%
진주시 1208
 
1.8%
양산시 1033
 
1.5%
2층 1022
 
1.5%
의창구 797
 
1.2%
성산구 755
 
1.1%
거제시 672
 
1.0%
Other values (8193) 43976
65.3%
2023-12-13T08:41:38.221798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
57444
 
17.7%
1 16331
 
5.0%
상 12482
 
3.8%
남 11263
 
3.5%
동 10884
 
3.3%
도 10366
 
3.2%
경 10156
 
3.1%
시 9399
 
2.9%
, 8781
 
2.7%
2 8428
 
2.6%
Other values (575) 169503
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 186826
57.5%
Space Separator 57444
 
17.7%
Decimal Number 52350
 
16.1%
Other Punctuation 8886
 
2.7%
Open Punctuation 8306
 
2.6%
Close Punctuation 8305
 
2.6%
Dash Punctuation 2347
 
0.7%
Uppercase Letter 464
 
0.1%
Lowercase Letter 93
 
< 0.1%
Math Symbol 14
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 12482
 
6.7%
남 11263
 
6.0%
동 10884
 
5.8%
도 10366
 
5.5%
경 10156
 
5.4%
시 9399
 
5.0%
로 7837
 
4.2%
층 5310
 
2.8%
길 5105
 
2.7%
원 5069
 
2.7%
Other values (508) 98955
53.0%
Uppercase Letter
ValueCountFrequency (%)
A 117
25.2%
B 89
19.2%
S 34
 
7.3%
D 26
 
5.6%
E 23
 
5.0%
C 22
 
4.7%
N 21
 
4.5%
I 14
 
3.0%
K 13
 
2.8%
H 11
 
2.4%
Other values (15) 94
20.3%
Lowercase Letter
ValueCountFrequency (%)
e 33
35.5%
a 19
20.4%
t 8
 
8.6%
l 6
 
6.5%
s 5
 
5.4%
c 5
 
5.4%
h 4
 
4.3%
m 3
 
3.2%
n 2
 
2.2%
y 2
 
2.2%
Other values (5) 6
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 16331
31.2%
2 8428
16.1%
0 5258
 
10.0%
3 4968
 
9.5%
4 3719
 
7.1%
5 3429
 
6.6%
6 2884
 
5.5%
7 2700
 
5.2%
8 2348
 
4.5%
9 2285
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 8781
98.8%
· 54
 
0.6%
. 18
 
0.2%
@ 14
 
0.2%
' 8
 
0.1%
/ 6
 
0.1%
: 3
 
< 0.1%
* 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 8304
> 99.9%
[ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 8303
> 99.9%
] 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
57444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2347
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 186826
57.5%
Common 137653
42.3%
Latin 558
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 12482
 
6.7%
남 11263
 
6.0%
동 10884
 
5.8%
도 10366
 
5.5%
경 10156
 
5.4%
시 9399
 
5.0%
로 7837
 
4.2%
층 5310
 
2.8%
길 5105
 
2.7%
원 5069
 
2.7%
Other values (508) 98955
53.0%
Latin
ValueCountFrequency (%)
A 117
21.0%
B 89
15.9%
S 34
 
6.1%
e 33
 
5.9%
D 26
 
4.7%
E 23
 
4.1%
C 22
 
3.9%
N 21
 
3.8%
a 19
 
3.4%
I 14
 
2.5%
Other values (31) 160
28.7%
Common
ValueCountFrequency (%)
57444
41.7%
1 16331
 
11.9%
, 8781
 
6.4%
2 8428
 
6.1%
( 8304
 
6.0%
) 8303
 
6.0%
0 5258
 
3.8%
3 4968
 
3.6%
4 3719
 
2.7%
5 3429
 
2.5%
Other values (16) 12688
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 186825
57.5%
ASCII 138156
42.5%
None 54
 
< 0.1%
Number Forms 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57444
41.6%
1 16331
 
11.8%
, 8781
 
6.4%
2 8428
 
6.1%
( 8304
 
6.0%
) 8303
 
6.0%
0 5258
 
3.8%
3 4968
 
3.6%
4 3719
 
2.7%
5 3429
 
2.5%
Other values (55) 13191
 
9.5%
Hangul
ValueCountFrequency (%)
상 12482
 
6.7%
남 11263
 
6.0%
동 10884
 
5.8%
도 10366
 
5.5%
경 10156
 
5.4%
시 9399
 
5.0%
로 7837
 
4.2%
층 5310
 
2.8%
길 5105
 
2.7%
원 5069
 
2.7%
Other values (507) 98954
53.0%
None
ValueCountFrequency (%)
· 54
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%

인허가일자
Date

Distinct4705
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1956-11-08 00:00:00
Maximum2023-06-08 00:00:00
2023-12-13T08:41:38.340978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:41:38.445365image/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

2023-12-13T08:41:38.539653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:41:38.608965image/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

2023-12-13T08:41:38.682332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:41:38.755223image/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
6687 
피부미용업
1625 
네일아트업
1228 
메이크업업
 
319
기타
 
136
Other values (2)
 
5

Length

Max length6
Median length5
Mean length4.9596
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 6687
66.9%
피부미용업 1625
 
16.2%
네일아트업 1228
 
12.3%
메이크업업 319
 
3.2%
기타 136
 
1.4%
미용업 기타 4
 
< 0.1%
일반이용업 1
 
< 0.1%

Length

2023-12-13T08:41:38.845437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:41:38.959409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 6687
66.8%
피부미용업 1625
 
16.2%
네일아트업 1228
 
12.3%
메이크업업 319
 
3.2%
기타 140
 
1.4%
미용업 4
 
< 0.1%
일반이용업 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing75
Missing (%)0.8%
Memory size97.7 KiB
False
9919 
True
 
6
(Missing)
 
75
ValueCountFrequency (%)
False 9919
99.2%
True 6
 
0.1%
(Missing) 75
 
0.8%
2023-12-13T08:41:39.072413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:41:39.118025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태구분다중이용업소여부
업태구분1.0000.000
다중이용업소여부0.0001.000
2023-12-13T08:41:39.192692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태구분다중이용업소여부
업태구분1.0000.000
다중이용업소여부0.0001.000
2023-12-13T08:41:39.263315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태구분다중이용업소여부
업태구분1.0000.000
다중이용업소여부0.0001.000

Missing values

2023-12-13T08:41:35.658835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:41:35.790797image/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.
2023-12-13T08:41:35.911097image/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
8127김용 헤어던!(hair Done!)경상남도 창원시 의창구 대원동 121번지 더시티세븐 W124호경상남도 창원시 의창구 원이대로 320, W124호 (대원동, 더시티세븐)2016-07-12영업/정상영업일반미용업N
2557김진혜Skin&Body(스킨앤바디)경상남도 김해시 진영읍 진영리 1594-5번지경상남도 김해시 진영읍 김해대로321번길 4-14, 1층2015-12-08영업/정상영업피부미용업N
10838머리하자헤어샵경상남도 하동군 진교면 진교리 288-1경상남도 하동군 진교면 민다리안길 1162010-11-19영업/정상영업일반미용업N
3991김난영 스킨케어경상남도 거제시 고현동 820-7 3층경상남도 거제시 거제중앙로 1897 (고현동,3층)2009-07-17영업/정상영업피부미용업N
8489나나헤어경상남도 창원시 의창구 팔용동 125번지경상남도 창원시 의창구 남산로 20 (팔용동)2012-08-22영업/정상영업일반미용업N
961수성헤어샵경상남도 진주시 상봉동 1106-26번지 1층일부경상남도 진주시 창렬로 89 (상봉동,1층일부)1999-05-20영업/정상영업일반미용업N
4531머리하는예쁜누나경상남도 거제시 장평동 612 용마에이스빌라2차경상남도 거제시 장평1로16길 15, B동 1층 101-2호 (장평동, 용마에이스빌라2차)2019-04-09영업/정상영업일반미용업N
11256앨리스헤어바이예윤경상남도 창원시 의창구 중동 776-3 D7PARK 310호경상남도 창원시 의창구 중동중앙로 83, D7 PARK 3층 310호 (중동)2021-10-19영업/정상영업일반미용업N
11215이든뷰티경상남도 창원시 마산합포구 두월동2가 7-1 두월동 상우 the 헤라우스경상남도 창원시 마산합포구 문화북1길 65, 2층 203호 (두월동2가, 두월동 상우 the 헤라우스)2021-10-07영업/정상영업메이크업업N
882영생헤어숍경상남도 진주시 상평동 221-33번지 1층일부경상남도 진주시 공단로91번길 11-1 (상평동, 1층일부)1987-02-03영업/정상영업일반미용업N
사업장명지번주소도로명주소인허가일자영업상태상세영업상태업태구분다중이용업소여부
357머리애봄경상남도 진주시 평거동 723-5번지 1층일부경상남도 진주시 진양호로111번길 10 (평거동, 1층일부)2014-08-01영업/정상영업일반미용업N
814라렌느경상남도 진주시 강남동 108-25번지 1층일부경상남도 진주시 망경로297번길 7-1 (강남동, 1층일부)2017-08-04영업/정상영업일반미용업N
11576디바머리방경상남도 거제시 옥포동 522-16 명성빌라 101호경상남도 거제시 옥포로20길 31, 1층 101(일부)호 (옥포동, 명성빌라)2022-02-25영업/정상영업일반미용업N
490애리헤어숍경상남도 진주시 신안동 454-2번지 번지 (상가동 109호)경상남도 진주시 진양호로 308, 109호 (신안동)2005-04-26영업/정상영업일반미용업N
6595꽃피우다경상남도 창원시 마산합포구 창포동2가 2번지 7동 1층 104호경상남도 창원시 마산합포구 문화동14길 74, 7동 1층 104호 (창포동2가, 경남창포아파트)2019-11-18영업/정상영업피부미용업N
3282나미헤어경상남도 김해시 삼정동 599-11번지 경주아파트 101호경상남도 김해시 활천로16번길 7, 101호 (삼정동, 경주아파트)2012-01-09영업/정상영업일반미용업N
1607MORIAH by Kara경상남도 통영시 광도면 죽림리 1573-2번지 주영더팰리스5차아파트경상남도 통영시 광도면 죽림5로 56, 523동 203호 (주영더팰리스5차아파트)2019-03-11영업/정상영업일반미용업N
795샛별미용실경상남도 진주시 일반성면 창촌리 729-13번지경상남도 진주시 일반성면 동부로 19571975-12-17영업/정상영업일반미용업N
8977프리티네일경상남도 창원시 의창구 대원동 40번지 대원 꿈에그린 121동 3층 310호경상남도 창원시 의창구 창원천로 34, 121동 3층 310호 (대원동, 대원 꿈에그린)2014-11-10영업/정상영업네일아트업N
6464아림테라피경상남도 거창군 거창읍 상림리 836-3경상남도 거창군 거창읍 공수들1길 522011-12-15영업/정상영업피부미용업N