Overview

Dataset statistics

Number of variables27
Number of observations799
Missing cells1350
Missing cells (%)6.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory181.2 KiB
Average record size in memory232.2 B

Variable types

Categorical14
Text4
DateTime1
Numeric6
Boolean1
Unsupported1

Dataset

Description경기도 이천시 내의 미용업 인허가 현황으로 헤어, 메이크업, 네일아트와 같은 사업장명, 인허가일자, 영업상태 등의 데이터 입니다.
URLhttps://www.data.go.kr/data/15038408/fileData.do

Alerts

시군명 has constant value ""Constant
영업상태구분코드 has constant value ""Constant
영업상태명 has constant value ""Constant
발한실여부 has constant value ""Constant
여성종사자수 has constant value ""Constant
한실수 is highly imbalanced (92.8%)Imbalance
양실수 is highly imbalanced (92.8%)Imbalance
욕실수 is highly imbalanced (92.8%)Imbalance
세탁기수 is highly imbalanced (92.8%)Imbalance
회수건조수 is highly imbalanced (90.3%)Imbalance
소재지시설전화번호 has 341 (42.7%) missing valuesMissing
소재지지번주소 has 92 (11.5%) missing valuesMissing
건물지하층수 has 11 (1.4%) missing valuesMissing
사용시작지상층수 has 47 (5.9%) missing valuesMissing
사용끝지상층수 has 48 (6.0%) missing valuesMissing
남성종사자수 has 799 (100.0%) missing valuesMissing
남성종사자수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 372 (46.6%) zerosZeros
건물지하층수 has 650 (81.4%) zerosZeros
사용시작지상층수 has 29 (3.6%) zerosZeros
사용끝지상층수 has 37 (4.6%) zerosZeros

Reproduction

Analysis started2023-12-12 14:19:32.706416
Analysis finished2023-12-12 14:19:33.575321
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
이천시
799 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이천시 799
100.0%

Length

2023-12-12T23:19:33.635034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:33.739445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이천시 799
100.0%

사업장명
Text

Distinct783
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2023-12-12T23:19:34.036937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length6.4067584
Min length1

Characters and Unicode

Total characters5119
Distinct characters491
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique767 ?
Unique (%)96.0%

Sample

1st row행복헤어샵
2nd row백화미장원
3rd row은파미장원
4th row슈노아이헤어샵
5th row금잔디미용실
ValueCountFrequency (%)
헤어 27
 
2.5%
네일 20
 
1.9%
hair 16
 
1.5%
nail 11
 
1.0%
이천점 10
 
0.9%
salon 7
 
0.6%
더 7
 
0.6%
에스테틱 7
 
0.6%
미용실 7
 
0.6%
beauty 7
 
0.6%
Other values (881) 959
89.0%
2023-12-12T23:19:34.581206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 322
 
6.3%
헤 302
 
5.9%
280
 
5.5%
미 129
 
2.5%
이 118
 
2.3%
네 96
 
1.9%
일 95
 
1.9%
스 93
 
1.8%
리 92
 
1.8%
a 65
 
1.3%
Other values (481) 3527
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3723
72.7%
Lowercase Letter 489
 
9.6%
Uppercase Letter 375
 
7.3%
Space Separator 280
 
5.5%
Other Punctuation 62
 
1.2%
Open Punctuation 60
 
1.2%
Close Punctuation 60
 
1.2%
Decimal Number 60
 
1.2%
Dash Punctuation 6
 
0.1%
Connector Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 322
 
8.6%
헤 302
 
8.1%
미 129
 
3.5%
이 118
 
3.2%
네 96
 
2.6%
일 95
 
2.6%
스 93
 
2.5%
리 92
 
2.5%
샵 64
 
1.7%
용 63
 
1.7%
Other values (408) 2349
63.1%
Uppercase Letter
ValueCountFrequency (%)
I 38
 
10.1%
H 33
 
8.8%
A 33
 
8.8%
S 29
 
7.7%
N 28
 
7.5%
E 24
 
6.4%
L 22
 
5.9%
M 22
 
5.9%
J 22
 
5.9%
R 21
 
5.6%
Other values (15) 103
27.5%
Lowercase Letter
ValueCountFrequency (%)
a 65
13.3%
e 51
10.4%
i 48
9.8%
o 45
9.2%
n 41
 
8.4%
l 33
 
6.7%
s 30
 
6.1%
r 24
 
4.9%
y 23
 
4.7%
h 22
 
4.5%
Other values (14) 107
21.9%
Decimal Number
ValueCountFrequency (%)
0 14
23.3%
1 11
18.3%
3 8
13.3%
2 6
10.0%
8 5
 
8.3%
4 4
 
6.7%
5 4
 
6.7%
9 3
 
5.0%
6 3
 
5.0%
7 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 17
27.4%
& 14
22.6%
# 10
16.1%
. 9
14.5%
' 6
 
9.7%
: 3
 
4.8%
· 1
 
1.6%
% 1
 
1.6%
; 1
 
1.6%
Space Separator
ValueCountFrequency (%)
280
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3715
72.6%
Latin 864
 
16.9%
Common 532
 
10.4%
Han 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 322
 
8.7%
헤 302
 
8.1%
미 129
 
3.5%
이 118
 
3.2%
네 96
 
2.6%
일 95
 
2.6%
스 93
 
2.5%
리 92
 
2.5%
샵 64
 
1.7%
용 63
 
1.7%
Other values (404) 2341
63.0%
Latin
ValueCountFrequency (%)
a 65
 
7.5%
e 51
 
5.9%
i 48
 
5.6%
o 45
 
5.2%
n 41
 
4.7%
I 38
 
4.4%
H 33
 
3.8%
A 33
 
3.8%
l 33
 
3.8%
s 30
 
3.5%
Other values (39) 447
51.7%
Common
ValueCountFrequency (%)
280
52.6%
( 60
 
11.3%
) 60
 
11.3%
, 17
 
3.2%
& 14
 
2.6%
0 14
 
2.6%
1 11
 
2.1%
# 10
 
1.9%
. 9
 
1.7%
3 8
 
1.5%
Other values (14) 49
 
9.2%
Han
ValueCountFrequency (%)
美 5
62.5%
家 1
 
12.5%
李 1
 
12.5%
愛 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3715
72.6%
ASCII 1395
 
27.3%
CJK 7
 
0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 322
 
8.7%
헤 302
 
8.1%
미 129
 
3.5%
이 118
 
3.2%
네 96
 
2.6%
일 95
 
2.6%
스 93
 
2.5%
리 92
 
2.5%
샵 64
 
1.7%
용 63
 
1.7%
Other values (404) 2341
63.0%
ASCII
ValueCountFrequency (%)
280
20.1%
a 65
 
4.7%
( 60
 
4.3%
) 60
 
4.3%
e 51
 
3.7%
i 48
 
3.4%
o 45
 
3.2%
n 41
 
2.9%
I 38
 
2.7%
H 33
 
2.4%
Other values (62) 674
48.3%
CJK
ValueCountFrequency (%)
美 5
71.4%
家 1
 
14.3%
愛 1
 
14.3%
None
ValueCountFrequency (%)
· 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
李 1
100.0%

인허가일자
Date

Distinct715
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
Minimum1973-11-10 00:00:00
Maximum2023-08-31 00:00:00
2023-12-12T23:19:34.715197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:34.882385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
1
799 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 799
100.0%

Length

2023-12-12T23:19:35.040277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:35.149609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 799
100.0%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
영업
799 

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 799
100.0%

Length

2023-12-12T23:19:35.242843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:35.343227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 799
100.0%

소재지시설전화번호
Text

MISSING 

Distinct454
Distinct (%)99.1%
Missing341
Missing (%)42.7%
Memory size6.4 KiB
2023-12-12T23:19:35.602896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.259825
Min length12

Characters and Unicode

Total characters5615
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

Unique450 ?
Unique (%)98.3%

Sample

1st row031-641-9687
2nd row031-635-4361
3rd row031-641-5170
4th row031-637-5556
5th row031-633-9329
ValueCountFrequency (%)
031-633-0208 2
 
0.4%
031-633-9943 2
 
0.4%
031-633-3760 2
 
0.4%
031-631-7812 2
 
0.4%
031-636-4546 1
 
0.2%
031-638-2485 1
 
0.2%
031-634-4401 1
 
0.2%
031-635-6235 1
 
0.2%
031-637-5595 1
 
0.2%
031-631-0950 1
 
0.2%
Other values (444) 444
96.9%
2023-12-12T23:19:36.123729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1063
18.9%
- 916
16.3%
0 738
13.1%
1 706
12.6%
6 629
11.2%
7 313
 
5.6%
5 296
 
5.3%
2 270
 
4.8%
4 253
 
4.5%
8 229
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4699
83.7%
Dash Punctuation 916
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1063
22.6%
0 738
15.7%
1 706
15.0%
6 629
13.4%
7 313
 
6.7%
5 296
 
6.3%
2 270
 
5.7%
4 253
 
5.4%
8 229
 
4.9%
9 202
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 916
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5615
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1063
18.9%
- 916
16.3%
0 738
13.1%
1 706
12.6%
6 629
11.2%
7 313
 
5.6%
5 296
 
5.3%
2 270
 
4.8%
4 253
 
4.5%
8 229
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5615
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1063
18.9%
- 916
16.3%
0 738
13.1%
1 706
12.6%
6 629
11.2%
7 313
 
5.6%
5 296
 
5.3%
2 270
 
4.8%
4 253
 
4.5%
8 229
 
4.1%

소재지면적정보
Real number (ℝ)

Distinct613
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.808423
Minimum3.47
Maximum341.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-12T23:19:36.280977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.47
5-th percentile16
Q128
median37.05
Q356.055
95-th percentile124.463
Maximum341.58
Range338.11
Interquartile range (IQR)28.055

Descriptive statistics

Standard deviation38.368396
Coefficient of variation (CV)0.78610194
Kurtosis13.870776
Mean48.808423
Median Absolute Deviation (MAD)11.24
Skewness3.0899823
Sum38997.93
Variance1472.1338
MonotonicityNot monotonic
2023-12-12T23:19:36.440594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 14
 
1.8%
30.0 8
 
1.0%
32.0 7
 
0.9%
36.0 6
 
0.8%
45.0 5
 
0.6%
40.0 5
 
0.6%
24.0 5
 
0.6%
16.0 5
 
0.6%
31.2 5
 
0.6%
27.0 4
 
0.5%
Other values (603) 735
92.0%
ValueCountFrequency (%)
3.47 1
0.1%
4.64 1
0.1%
5.44 1
0.1%
6.6 1
0.1%
6.9 2
0.3%
7.5 1
0.1%
7.74 1
0.1%
8.4 1
0.1%
8.8 1
0.1%
8.85 1
0.1%
ValueCountFrequency (%)
341.58 1
0.1%
315.05 1
0.1%
297.0 1
0.1%
288.46 1
0.1%
263.18 1
0.1%
216.76 1
0.1%
214.87 1
0.1%
198.34 1
0.1%
198.0 1
0.1%
196.27 1
0.1%

도로명우편번호
Real number (ℝ)

Distinct77
Distinct (%)9.7%
Missing5
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean17362.649
Minimum17300
Maximum17423
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-12T23:19:36.633950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17300
5-th percentile17324
Q117348
median17364
Q317374
95-th percentile17418
Maximum17423
Range123
Interquartile range (IQR)26

Descriptive statistics

Standard deviation24.169091
Coefficient of variation (CV)0.0013920164
Kurtosis0.62420997
Mean17362.649
Median Absolute Deviation (MAD)11
Skewness0.19917925
Sum13785943
Variance584.14497
MonotonicityNot monotonic
2023-12-12T23:19:36.804681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17364 52
 
6.5%
17374 52
 
6.5%
17369 46
 
5.8%
17387 36
 
4.5%
17370 32
 
4.0%
17332 31
 
3.9%
17375 29
 
3.6%
17368 27
 
3.4%
17344 26
 
3.3%
17418 24
 
3.0%
Other values (67) 439
54.9%
ValueCountFrequency (%)
17300 2
 
0.3%
17301 1
 
0.1%
17302 2
 
0.3%
17303 6
0.8%
17308 2
 
0.3%
17311 1
 
0.1%
17312 5
 
0.6%
17316 12
1.5%
17318 2
 
0.3%
17324 14
1.8%
ValueCountFrequency (%)
17423 1
 
0.1%
17422 3
 
0.4%
17421 1
 
0.1%
17420 17
2.1%
17419 2
 
0.3%
17418 24
3.0%
17413 1
 
0.1%
17411 4
 
0.5%
17408 3
 
0.4%
17405 1
 
0.1%

소재지도로명주소
Text

Distinct773
Distinct (%)96.9%
Missing1
Missing (%)0.1%
Memory size6.4 KiB
2023-12-12T23:19:37.119072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length29.726817
Min length15

Characters and Unicode

Total characters23722
Distinct characters240
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

Unique748 ?
Unique (%)93.7%

Sample

1st row경기도 이천시 장호원읍 장감로77번길 18 (1층)
2nd row경기도 이천시 이섭대천로1217번길 26-1 (창전동)
3rd row경기도 이천시 장호원읍 장터로61번길 25
4th row경기도 이천시 서희로60번길 6-1, 2층 (창전동)
5th row경기도 이천시 애련정로 129 (창전동)
ValueCountFrequency (%)
경기도 798
 
15.7%
이천시 798
 
15.7%
1층 344
 
6.8%
창전동 231
 
4.5%
중리동 104
 
2.0%
2층 99
 
1.9%
부발읍 92
 
1.8%
증포동 54
 
1.1%
영창로 49
 
1.0%
이섭대천로 49
 
1.0%
Other values (782) 2469
48.5%
2023-12-12T23:19:37.588702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4298
 
18.1%
1 1362
 
5.7%
천 988
 
4.2%
이 914
 
3.9%
경 893
 
3.8%
시 810
 
3.4%
도 800
 
3.4%
기 800
 
3.4%
로 797
 
3.4%
2 754
 
3.2%
Other values (230) 11306
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12828
54.1%
Decimal Number 4501
 
19.0%
Space Separator 4298
 
18.1%
Other Punctuation 662
 
2.8%
Close Punctuation 604
 
2.5%
Open Punctuation 603
 
2.5%
Dash Punctuation 185
 
0.8%
Uppercase Letter 39
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 988
 
7.7%
이 914
 
7.1%
경 893
 
7.0%
시 810
 
6.3%
도 800
 
6.2%
기 800
 
6.2%
로 797
 
6.2%
동 699
 
5.4%
층 482
 
3.8%
번 349
 
2.7%
Other values (203) 5296
41.3%
Decimal Number
ValueCountFrequency (%)
1 1362
30.3%
2 754
16.8%
0 470
 
10.4%
3 365
 
8.1%
4 316
 
7.0%
7 276
 
6.1%
5 269
 
6.0%
8 257
 
5.7%
6 220
 
4.9%
9 212
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
A 12
30.8%
B 9
23.1%
I 6
15.4%
S 6
15.4%
D 2
 
5.1%
C 1
 
2.6%
K 1
 
2.6%
J 1
 
2.6%
R 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 660
99.7%
@ 1
 
0.2%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
4298
100.0%
Close Punctuation
ValueCountFrequency (%)
) 604
100.0%
Open Punctuation
ValueCountFrequency (%)
( 603
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12828
54.1%
Common 10855
45.8%
Latin 39
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 988
 
7.7%
이 914
 
7.1%
경 893
 
7.0%
시 810
 
6.3%
도 800
 
6.2%
기 800
 
6.2%
로 797
 
6.2%
동 699
 
5.4%
층 482
 
3.8%
번 349
 
2.7%
Other values (203) 5296
41.3%
Common
ValueCountFrequency (%)
4298
39.6%
1 1362
 
12.5%
2 754
 
6.9%
, 660
 
6.1%
) 604
 
5.6%
( 603
 
5.6%
0 470
 
4.3%
3 365
 
3.4%
4 316
 
2.9%
7 276
 
2.5%
Other values (8) 1147
 
10.6%
Latin
ValueCountFrequency (%)
A 12
30.8%
B 9
23.1%
I 6
15.4%
S 6
15.4%
D 2
 
5.1%
C 1
 
2.6%
K 1
 
2.6%
J 1
 
2.6%
R 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12828
54.1%
ASCII 10894
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4298
39.5%
1 1362
 
12.5%
2 754
 
6.9%
, 660
 
6.1%
) 604
 
5.5%
( 603
 
5.5%
0 470
 
4.3%
3 365
 
3.4%
4 316
 
2.9%
7 276
 
2.5%
Other values (17) 1186
 
10.9%
Hangul
ValueCountFrequency (%)
천 988
 
7.7%
이 914
 
7.1%
경 893
 
7.0%
시 810
 
6.3%
도 800
 
6.2%
기 800
 
6.2%
로 797
 
6.2%
동 699
 
5.4%
층 482
 
3.8%
번 349
 
2.7%
Other values (203) 5296
41.3%

소재지지번주소
Text

MISSING 

Distinct683
Distinct (%)96.6%
Missing92
Missing (%)11.5%
Memory size6.4 KiB
2023-12-12T23:19:37.930596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length41
Mean length23.782178
Min length14

Characters and Unicode

Total characters16814
Distinct characters220
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

Unique661 ?
Unique (%)93.5%

Sample

1st row경기도 이천시 장호원읍 장호원리 35-2 1층
2nd row경기도 이천시 창전동 167-10
3rd row경기도 이천시 장호원읍 장호원리 46-1
4th row경기도 이천시 창전동 159-5 외1필지(2층)
5th row경기도 이천시 창전동 455-10
ValueCountFrequency (%)
경기도 707
18.9%
이천시 707
18.9%
창전동 219
 
5.9%
1층 175
 
4.7%
중리동 88
 
2.4%
부발읍 85
 
2.3%
2층 51
 
1.4%
증포동 50
 
1.3%
장호원읍 46
 
1.2%
장호원리 40
 
1.1%
Other values (823) 1571
42.0%
2023-12-12T23:19:38.432289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3651
21.7%
1 1015
 
6.0%
천 758
 
4.5%
이 737
 
4.4%
시 715
 
4.3%
기 709
 
4.2%
경 709
 
4.2%
도 709
 
4.2%
- 619
 
3.7%
동 582
 
3.5%
Other values (210) 6610
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8610
51.2%
Decimal Number 3715
22.1%
Space Separator 3651
21.7%
Dash Punctuation 619
 
3.7%
Close Punctuation 91
 
0.5%
Open Punctuation 90
 
0.5%
Uppercase Letter 27
 
0.2%
Other Punctuation 10
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 758
 
8.8%
이 737
 
8.6%
시 715
 
8.3%
기 709
 
8.2%
경 709
 
8.2%
도 709
 
8.2%
동 582
 
6.8%
리 315
 
3.7%
층 253
 
2.9%
호 251
 
2.9%
Other values (183) 2872
33.4%
Decimal Number
ValueCountFrequency (%)
1 1015
27.3%
2 499
13.4%
4 428
11.5%
3 340
 
9.2%
0 305
 
8.2%
6 269
 
7.2%
5 255
 
6.9%
7 245
 
6.6%
9 185
 
5.0%
8 174
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 8
29.6%
S 5
18.5%
A 5
18.5%
I 5
18.5%
H 1
 
3.7%
K 1
 
3.7%
J 1
 
3.7%
D 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 6
60.0%
@ 2
 
20.0%
. 1
 
10.0%
/ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
3651
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 619
100.0%
Close Punctuation
ValueCountFrequency (%)
) 91
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8610
51.2%
Common 8177
48.6%
Latin 27
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 758
 
8.8%
이 737
 
8.6%
시 715
 
8.3%
기 709
 
8.2%
경 709
 
8.2%
도 709
 
8.2%
동 582
 
6.8%
리 315
 
3.7%
층 253
 
2.9%
호 251
 
2.9%
Other values (183) 2872
33.4%
Common
ValueCountFrequency (%)
3651
44.6%
1 1015
 
12.4%
- 619
 
7.6%
2 499
 
6.1%
4 428
 
5.2%
3 340
 
4.2%
0 305
 
3.7%
6 269
 
3.3%
5 255
 
3.1%
7 245
 
3.0%
Other values (9) 551
 
6.7%
Latin
ValueCountFrequency (%)
B 8
29.6%
S 5
18.5%
A 5
18.5%
I 5
18.5%
H 1
 
3.7%
K 1
 
3.7%
J 1
 
3.7%
D 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8610
51.2%
ASCII 8204
48.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3651
44.5%
1 1015
 
12.4%
- 619
 
7.5%
2 499
 
6.1%
4 428
 
5.2%
3 340
 
4.1%
0 305
 
3.7%
6 269
 
3.3%
5 255
 
3.1%
7 245
 
3.0%
Other values (17) 578
 
7.0%
Hangul
ValueCountFrequency (%)
천 758
 
8.8%
이 737
 
8.6%
시 715
 
8.3%
기 709
 
8.2%
경 709
 
8.2%
도 709
 
8.2%
동 582
 
6.8%
리 315
 
3.7%
층 253
 
2.9%
호 251
 
2.9%
Other values (183) 2872
33.4%

소재지우편번호
Categorical

Distinct48
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
467-804
110 
467-807
58 
467-808
51 
467-800
 
47
467-070
 
45
Other values (43)
488 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique12 ?
Unique (%)1.5%

Sample

1st row467-901
2nd row467-804
3rd row467-901
4th row467-804
5th row467-807

Common Values

ValueCountFrequency (%)
467-804 110
 
13.8%
467-807 58
 
7.3%
467-808 51
 
6.4%
467-800 47
 
5.9%
467-070 45
 
5.6%
467-806 43
 
5.4%
467-901 42
 
5.3%
467-814 37
 
4.6%
467-020 37
 
4.6%
467-866 34
 
4.3%
Other values (38) 295
36.9%

Length

2023-12-12T23:19:38.595835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
467-804 110
 
13.8%
467-807 58
 
7.3%
467-808 51
 
6.4%
467-800 47
 
5.9%
467-070 45
 
5.6%
467-806 43
 
5.4%
467-901 42
 
5.3%
467-814 37
 
4.6%
467-020 37
 
4.6%
467-866 34
 
4.3%
Other values (38) 295
36.9%

업태구분명정보
Categorical

Distinct15
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
일반미용업
438 
피부미용업
102 
네일미용업
88 
종합미용업
56 
화장ㆍ분장 미용업
 
34
Other values (10)
81 

Length

Max length23
Median length5
Mean length6.3566959
Min length5

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 438
54.8%
피부미용업 102
 
12.8%
네일미용업 88
 
11.0%
종합미용업 56
 
7.0%
화장ㆍ분장 미용업 34
 
4.3%
네일미용업, 화장ㆍ분장 미용업 22
 
2.8%
피부미용업, 네일미용업 11
 
1.4%
일반미용업, 화장ㆍ분장 미용업 11
 
1.4%
피부미용업, 화장ㆍ분장 미용업 11
 
1.4%
일반미용업, 네일미용업, 화장ㆍ분장 미용업 9
 
1.1%
Other values (5) 17
 
2.1%

Length

2023-12-12T23:19:38.735782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 469
47.1%
네일미용업 141
 
14.2%
피부미용업 137
 
13.8%
화장ㆍ분장 96
 
9.6%
미용업 96
 
9.6%
종합미용업 56
 
5.6%

위생업태명정보
Categorical

Distinct12
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
일반미용업
488 
피부미용업
112 
네일아트업
99 
메이크업업
 
33
네일미용업
 
19
Other values (7)
 
48

Length

Max length23
Median length5
Mean length5.0876095
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 488
61.1%
피부미용업 112
 
14.0%
네일아트업 99
 
12.4%
메이크업업 33
 
4.1%
네일미용업 19
 
2.4%
기타 17
 
2.1%
화장ㆍ분장 미용업 13
 
1.6%
종합미용업 12
 
1.5%
피부미용업, 화장ㆍ분장 미용업 2
 
0.3%
네일미용업, 화장ㆍ분장 미용업 2
 
0.3%
Other values (2) 2
 
0.3%

Length

2023-12-12T23:19:39.223412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 489
59.3%
피부미용업 115
 
14.0%
네일아트업 99
 
12.0%
메이크업업 33
 
4.0%
네일미용업 23
 
2.8%
화장ㆍ분장 18
 
2.2%
미용업 18
 
2.2%
기타 17
 
2.1%
종합미용업 12
 
1.5%

건물지상층수
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)2.0%
Missing5
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean1.8450882
Minimum0
Maximum40
Zeros372
Zeros (%)46.6%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-12T23:19:39.366063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum40
Range40
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.4800722
Coefficient of variation (CV)1.8861279
Kurtosis69.503724
Mean1.8450882
Median Absolute Deviation (MAD)1
Skewness7.1379072
Sum1465
Variance12.110903
MonotonicityNot monotonic
2023-12-12T23:19:39.502329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 372
46.6%
3 136
 
17.0%
2 103
 
12.9%
4 70
 
8.8%
1 58
 
7.3%
5 32
 
4.0%
6 6
 
0.8%
9 4
 
0.5%
40 3
 
0.4%
33 2
 
0.3%
Other values (6) 8
 
1.0%
(Missing) 5
 
0.6%
ValueCountFrequency (%)
0 372
46.6%
1 58
 
7.3%
2 103
 
12.9%
3 136
 
17.0%
4 70
 
8.8%
5 32
 
4.0%
6 6
 
0.8%
7 1
 
0.1%
9 4
 
0.5%
10 1
 
0.1%
ValueCountFrequency (%)
40 3
0.4%
33 2
 
0.3%
15 1
 
0.1%
14 2
 
0.3%
12 2
 
0.3%
11 1
 
0.1%
10 1
 
0.1%
9 4
0.5%
7 1
 
0.1%
6 6
0.8%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.8%
Missing11
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean0.24746193
Minimum0
Maximum5
Zeros650
Zeros (%)81.4%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-12T23:19:39.640584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.66758771
Coefficient of variation (CV)2.697739
Kurtosis19.497907
Mean0.24746193
Median Absolute Deviation (MAD)0
Skewness3.9590503
Sum195
Variance0.44567335
MonotonicityNot monotonic
2023-12-12T23:19:39.755913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 650
81.4%
1 110
 
13.8%
2 11
 
1.4%
3 9
 
1.1%
4 4
 
0.5%
5 4
 
0.5%
(Missing) 11
 
1.4%
ValueCountFrequency (%)
0 650
81.4%
1 110
 
13.8%
2 11
 
1.4%
3 9
 
1.1%
4 4
 
0.5%
5 4
 
0.5%
ValueCountFrequency (%)
5 4
 
0.5%
4 4
 
0.5%
3 9
 
1.1%
2 11
 
1.4%
1 110
 
13.8%
0 650
81.4%

사용시작지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)1.2%
Missing47
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean1.275266
Minimum0
Maximum12
Zeros29
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-12T23:19:39.885950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.78604671
Coefficient of variation (CV)0.61637865
Kurtosis54.861055
Mean1.275266
Median Absolute Deviation (MAD)0
Skewness5.1464441
Sum959
Variance0.61786944
MonotonicityNot monotonic
2023-12-12T23:19:40.012435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 544
68.1%
2 143
 
17.9%
3 30
 
3.8%
0 29
 
3.6%
4 2
 
0.3%
5 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
12 1
 
0.1%
(Missing) 47
 
5.9%
ValueCountFrequency (%)
0 29
 
3.6%
1 544
68.1%
2 143
 
17.9%
3 30
 
3.8%
4 2
 
0.3%
5 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%
12 1
 
0.1%
ValueCountFrequency (%)
12 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
5 1
 
0.1%
4 2
 
0.3%
3 30
 
3.8%
2 143
 
17.9%
1 544
68.1%
0 29
 
3.6%

사용끝지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)1.2%
Missing48
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean1.2596538
Minimum0
Maximum12
Zeros37
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-12T23:19:40.129640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.79193224
Coefficient of variation (CV)0.6286904
Kurtosis53.643044
Mean1.2596538
Median Absolute Deviation (MAD)0
Skewness5.0266994
Sum946
Variance0.62715668
MonotonicityNot monotonic
2023-12-12T23:19:40.254390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 537
67.2%
2 143
 
17.9%
0 37
 
4.6%
3 28
 
3.5%
4 2
 
0.3%
5 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
12 1
 
0.1%
(Missing) 48
 
6.0%
ValueCountFrequency (%)
0 37
 
4.6%
1 537
67.2%
2 143
 
17.9%
3 28
 
3.5%
4 2
 
0.3%
5 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%
12 1
 
0.1%
ValueCountFrequency (%)
12 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
5 1
 
0.1%
4 2
 
0.3%
3 28
 
3.5%
2 143
 
17.9%
1 537
67.2%
0 37
 
4.6%

사용시작지하층수
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
508 
<NA>
281 
1
 
9
2
 
1

Length

Max length4
Median length1
Mean length2.0550688
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 508
63.6%
<NA> 281
35.2%
1 9
 
1.1%
2 1
 
0.1%

Length

2023-12-12T23:19:40.381037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:40.500381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 508
63.6%
na 281
35.2%
1 9
 
1.1%
2 1
 
0.1%

사용끝지하층수
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
508 
<NA>
281 
1
 
9
2
 
1

Length

Max length4
Median length1
Mean length2.0550688
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 508
63.6%
<NA> 281
35.2%
1 9
 
1.1%
2 1
 
0.1%

Length

2023-12-12T23:19:40.647010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:40.773551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 508
63.6%
na 281
35.2%
1 9
 
1.1%
2 1
 
0.1%

한실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
792 
<NA>
 
7

Length

Max length4
Median length1
Mean length1.0262829
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 792
99.1%
<NA> 7
 
0.9%

Length

2023-12-12T23:19:40.902499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:41.028791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 792
99.1%
na 7
 
0.9%

양실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
792 
<NA>
 
7

Length

Max length4
Median length1
Mean length1.0262829
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 792
99.1%
<NA> 7
 
0.9%

Length

2023-12-12T23:19:41.164337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:41.299389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 792
99.1%
na 7
 
0.9%

욕실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
792 
<NA>
 
7

Length

Max length4
Median length1
Mean length1.0262829
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 792
99.1%
<NA> 7
 
0.9%

Length

2023-12-12T23:19:41.422744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:41.545447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 792
99.1%
na 7
 
0.9%

발한실여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing1
Missing (%)0.1%
Memory size1.7 KiB
False
798 
(Missing)
 
1
ValueCountFrequency (%)
False 798
99.9%
(Missing) 1
 
0.1%
2023-12-12T23:19:41.645808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

세탁기수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
792 
<NA>
 
7

Length

Max length4
Median length1
Mean length1.0262829
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 792
99.1%
<NA> 7
 
0.9%

Length

2023-12-12T23:19:41.769022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:41.890595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 792
99.1%
na 7
 
0.9%

여성종사자수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
1
799 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 799
100.0%

Length

2023-12-12T23:19:42.004524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:42.139323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 799
100.0%

남성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing799
Missing (%)100.0%
Memory size7.2 KiB

회수건조수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
789 
<NA>
 
10

Length

Max length4
Median length1
Mean length1.0375469
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 789
98.7%
<NA> 10
 
1.3%

Length

2023-12-12T23:19:42.278844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:42.402914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 789
98.7%
na 10
 
1.3%

Sample

시군명사업장명인허가일자영업상태구분코드영업상태명소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호업태구분명정보위생업태명정보건물지상층수건물지하층수사용시작지상층수사용끝지상층수사용시작지하층수사용끝지하층수한실수양실수욕실수발한실여부세탁기수여성종사자수남성종사자수회수건조수
0이천시행복헤어샵1973-11-101영업031-641-968724.117418경기도 이천시 장호원읍 장감로77번길 18 (1층)경기도 이천시 장호원읍 장호원리 35-2 1층467-901일반미용업일반미용업001100000N01<NA>0
1이천시백화미장원1975-03-241영업031-635-436113.2217369경기도 이천시 이섭대천로1217번길 26-1 (창전동)경기도 이천시 창전동 167-10467-804일반미용업일반미용업001100000N01<NA>0
2이천시은파미장원1981-08-291영업031-641-517023.1417420경기도 이천시 장호원읍 장터로61번길 25경기도 이천시 장호원읍 장호원리 46-1467-901일반미용업일반미용업001100000N01<NA>0
3이천시슈노아이헤어샵1984-09-191영업031-637-555615.017369경기도 이천시 서희로60번길 6-1, 2층 (창전동)경기도 이천시 창전동 159-5 외1필지(2층)467-804일반미용업일반미용업002200000N01<NA>0
4이천시금잔디미용실1986-12-191영업031-633-932937.817363경기도 이천시 애련정로 129 (창전동)경기도 이천시 창전동 455-10467-807일반미용업일반미용업000000000N01<NA>0
5이천시진영숙헤어샵1986-11-131영업031-633-604628.717357경기도 이천시 이섭대천로 1304-14, 1층 (창전동)경기도 이천시 창전동 445-7 (1층)467-806일반미용업일반미용업001100000N01<NA>0
6이천시샤론미용실1987-06-221영업031-632-421519.8317312경기도 이천시 백사면 현방로80번길 5-6경기도 이천시 백사면 현방리 69-7467-831일반미용업일반미용업001100000N01<NA>0
7이천시호산나1987-06-231영업031-634-356660.4717312경기도 이천시 백사면 현방로80번길 5-5, 정면출입구 (증축건물)좌측 업소 1층경기도 이천시 백사면 현방리 67-21 1층 정면출입구 (증축건물)좌측 업소467-831일반미용업일반미용업001100000N01<NA>0
8이천시크로바미용실1987-05-291영업031-632-302426.4517408경기도 이천시 모가면 진상미로 1274경기도 이천시 모가면 진가리 79-7467-872일반미용업일반미용업001100000N01<NA>0
9이천시진주미용실1987-10-131영업031-636-619450.617367경기도 이천시 경충대로2674번길 46-2 (관고동)경기도 이천시 관고동 26-6467-020일반미용업일반미용업301100000N01<NA>0
시군명사업장명인허가일자영업상태구분코드영업상태명소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호업태구분명정보위생업태명정보건물지상층수건물지하층수사용시작지상층수사용끝지상층수사용시작지하층수사용끝지하층수한실수양실수욕실수발한실여부세탁기수여성종사자수남성종사자수회수건조수
789이천시러브제제2023-06-201영업0507-1376-477033.017374경기도 이천시 중리천로72번길 8, 1층 (중리동)<NA>467-800화장ㆍ분장 미용업화장ㆍ분장 미용업001100000N01<NA>0
790이천시반하다뷰티2023-07-101영업0507-1422-780436.017365경기도 이천시 향교로52번길 38, 1층 (창전동)<NA>467-805화장ㆍ분장 미용업화장ㆍ분장 미용업001100000N01<NA>0
791이천시솜씨 브로우2023-07-201영업<NA>33.017355경기도 이천시 향교로 49-1, 1층 (창전동)<NA>467-805화장ㆍ분장 미용업화장ㆍ분장 미용업001100000N01<NA>0
792이천시키노2023-08-081영업0507-1432-299738.1317372경기도 이천시 애련정로 67-23, 1층 118호 (안흥동, 이천코아루휴티스1단지)<NA>467-050화장ㆍ분장 미용업화장ㆍ분장 미용업001100000N01<NA>0
793이천시미싱데렐라2023-08-291영업<NA>29.1317374경기도 이천시 중리천로70번길 13, 2층 (중리동)<NA>467-800화장ㆍ분장 미용업화장ㆍ분장 미용업001100000N01<NA>0
794이천시제이아뷰티2023-02-281영업0507-1360-544259.017364경기도 이천시 향교로82번길 56-5, 1층 (창전동)<NA>467-804피부미용업, 화장ㆍ분장 미용업피부미용업, 화장ㆍ분장 미용업001100000N01<NA>0
795이천시디어뷰티2023-04-201영업0507-1336-851024.317347경기도 이천시 이섭대천로 1397, 상가동 (증포동, 선경1차아파트)<NA>467-802피부미용업, 화장ㆍ분장 미용업피부미용업, 화장ㆍ분장 미용업001100000N01<NA>0
796이천시Always beauty2023-02-211영업0507-1479-220438.417365경기도 이천시 영창로153번길 37, 우측 1층 (관고동)<NA>467-020네일미용업, 화장ㆍ분장 미용업네일미용업, 화장ㆍ분장 미용업001100000N01<NA>0
797이천시플로라 뷰티2023-07-191영업0507-1413-870230.017387경기도 이천시 마장면 중앙로10번길 16-14, 1층 102호<NA>467-814네일미용업, 화장ㆍ분장 미용업네일미용업, 화장ㆍ분장 미용업001100000N01<NA>0
798이천시헤어 아뜰리에(HAIR ATELIER)2022-11-111영업031-694-3090100.817370경기도 이천시 영창로 244, 1층 (창전동)<NA>467-807일반미용업, 네일미용업, 화장ㆍ분장 미용업일반미용업, 네일미용업, 화장ㆍ분장 미용업001100000N01<NA>0