Overview

Dataset statistics

Number of variables47
Number of observations4133
Missing cells41632
Missing cells (%)21.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory404.0 B

Variable types

Categorical19
Text7
DateTime4
Unsupported4
Numeric11
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-17923/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
사용시작지하층 is highly imbalanced (50.9%)Imbalance
사용끝지하층 is highly imbalanced (60.0%)Imbalance
조건부허가시작일자 is highly imbalanced (99.7%)Imbalance
조건부허가종료일자 is highly imbalanced (99.7%)Imbalance
남성종사자수 is highly imbalanced (58.4%)Imbalance
인허가취소일자 has 4133 (100.0%) missing valuesMissing
폐업일자 has 1408 (34.1%) missing valuesMissing
휴업시작일자 has 4133 (100.0%) missing valuesMissing
휴업종료일자 has 4133 (100.0%) missing valuesMissing
재개업일자 has 4133 (100.0%) missing valuesMissing
전화번호 has 1754 (42.4%) missing valuesMissing
도로명주소 has 1205 (29.2%) missing valuesMissing
도로명우편번호 has 1236 (29.9%) missing valuesMissing
좌표정보(X) has 117 (2.8%) missing valuesMissing
좌표정보(Y) has 117 (2.8%) missing valuesMissing
건물지상층수 has 1586 (38.4%) missing valuesMissing
건물지하층수 has 1594 (38.6%) missing valuesMissing
사용시작지상층 has 1678 (40.6%) missing valuesMissing
사용끝지상층 has 2153 (52.1%) missing valuesMissing
발한실여부 has 865 (20.9%) missing valuesMissing
좌석수 has 1164 (28.2%) missing valuesMissing
조건부허가신고사유 has 4132 (> 99.9%) missing valuesMissing
여성종사자수 has 3083 (74.6%) missing valuesMissing
침대수 has 2179 (52.7%) missing valuesMissing
다중이용업소여부 has 822 (19.9%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 389 (9.4%) zerosZeros
건물지상층수 has 2391 (57.9%) zerosZeros
건물지하층수 has 2423 (58.6%) zerosZeros
사용시작지상층 has 619 (15.0%) zerosZeros
사용끝지상층 has 163 (3.9%) zerosZeros
좌석수 has 539 (13.0%) zerosZeros
여성종사자수 has 1004 (24.3%) zerosZeros
침대수 has 1133 (27.4%) zerosZeros

Reproduction

Analysis started2024-04-06 11:52:33.322127
Analysis finished2024-04-06 11:52:36.271239
Duration2.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
3210000
4133 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 4133
100.0%

Length

2024-04-06T20:52:36.385495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:36.573383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 4133
100.0%

관리번호
Text

UNIQUE 

Distinct4133
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
2024-04-06T20:52:36.877789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters90926
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

Unique4133 ?
Unique (%)100.0%

Sample

1st row3210000-204-1971-00001
2nd row3210000-204-1976-00907
3rd row3210000-204-1976-01225
4th row3210000-204-1977-01214
5th row3210000-204-1978-01221
ValueCountFrequency (%)
3210000-204-1971-00001 1
 
< 0.1%
3210000-213-1998-00010 1
 
< 0.1%
3210000-213-1996-00003 1
 
< 0.1%
3210000-213-1997-00009 1
 
< 0.1%
3210000-213-1996-00004 1
 
< 0.1%
3210000-213-1996-00005 1
 
< 0.1%
3210000-213-1996-00006 1
 
< 0.1%
3210000-213-1996-00008 1
 
< 0.1%
3210000-213-1996-00009 1
 
< 0.1%
3210000-213-1996-00010 1
 
< 0.1%
Other values (4123) 4123
99.8%
2024-04-06T20:52:37.490195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35215
38.7%
2 14820
16.3%
1 12727
 
14.0%
- 12399
 
13.6%
3 6415
 
7.1%
9 2418
 
2.7%
4 2187
 
2.4%
5 1373
 
1.5%
8 1252
 
1.4%
6 1135
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78527
86.4%
Dash Punctuation 12399
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35215
44.8%
2 14820
18.9%
1 12727
 
16.2%
3 6415
 
8.2%
9 2418
 
3.1%
4 2187
 
2.8%
5 1373
 
1.7%
8 1252
 
1.6%
6 1135
 
1.4%
7 985
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 12399
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90926
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35215
38.7%
2 14820
16.3%
1 12727
 
14.0%
- 12399
 
13.6%
3 6415
 
7.1%
9 2418
 
2.7%
4 2187
 
2.4%
5 1373
 
1.5%
8 1252
 
1.4%
6 1135
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35215
38.7%
2 14820
16.3%
1 12727
 
14.0%
- 12399
 
13.6%
3 6415
 
7.1%
9 2418
 
2.7%
4 2187
 
2.4%
5 1373
 
1.5%
8 1252
 
1.4%
6 1135
 
1.2%
Distinct2929
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
Minimum1971-03-09 00:00:00
Maximum2024-04-03 00:00:00
2024-04-06T20:52:37.732077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:52:38.075754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4133
Missing (%)100.0%
Memory size36.5 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
3
2725 
1
1408 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 2725
65.9%
1 1408
34.1%

Length

2024-04-06T20:52:38.366701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:38.552876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2725
65.9%
1 1408
34.1%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
폐업
2725 
영업/정상
1408 

Length

Max length5
Median length2
Mean length3.0220179
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2725
65.9%
영업/정상 1408
34.1%

Length

2024-04-06T20:52:38.774004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:38.983598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2725
65.9%
영업/정상 1408
34.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
2
2725 
1
1408 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 2725
65.9%
1 1408
34.1%

Length

2024-04-06T20:52:39.191611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:39.376411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2725
65.9%
1 1408
34.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
폐업
2725 
영업
1408 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2725
65.9%
영업 1408
34.1%

Length

2024-04-06T20:52:39.594761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:39.783939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2725
65.9%
영업 1408
34.1%

폐업일자
Date

MISSING 

Distinct1969
Distinct (%)72.3%
Missing1408
Missing (%)34.1%
Memory size32.4 KiB
Minimum1989-05-16 00:00:00
Maximum2024-04-02 00:00:00
2024-04-06T20:52:40.034344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:52:40.306098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4133
Missing (%)100.0%
Memory size36.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4133
Missing (%)100.0%
Memory size36.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4133
Missing (%)100.0%
Memory size36.5 KiB

전화번호
Text

MISSING 

Distinct2249
Distinct (%)94.5%
Missing1754
Missing (%)42.4%
Memory size32.4 KiB
2024-04-06T20:52:40.827369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9096259
Min length2

Characters and Unicode

Total characters23575
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

Unique2146 ?
Unique (%)90.2%

Sample

1st row02 5412365
2nd row0205990095
3rd row02 5377045
4th row0205990206
5th row0205827902
ValueCountFrequency (%)
02 1205
27.8%
070 34
 
0.8%
532 31
 
0.7%
522 27
 
0.6%
585 24
 
0.6%
525 24
 
0.6%
537 22
 
0.5%
533 21
 
0.5%
534 20
 
0.5%
588 18
 
0.4%
Other values (2301) 2903
67.1%
2024-04-06T20:52:41.606349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3544
15.0%
2 3458
14.7%
5 3332
14.1%
2514
10.7%
3 1956
8.3%
8 1647
7.0%
7 1616
6.9%
4 1533
6.5%
9 1469
6.2%
1 1268
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21061
89.3%
Space Separator 2514
 
10.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3544
16.8%
2 3458
16.4%
5 3332
15.8%
3 1956
9.3%
8 1647
7.8%
7 1616
7.7%
4 1533
7.3%
9 1469
7.0%
1 1268
 
6.0%
6 1238
 
5.9%
Space Separator
ValueCountFrequency (%)
2514
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23575
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3544
15.0%
2 3458
14.7%
5 3332
14.1%
2514
10.7%
3 1956
8.3%
8 1647
7.0%
7 1616
6.9%
4 1533
6.5%
9 1469
6.2%
1 1268
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23575
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3544
15.0%
2 3458
14.7%
5 3332
14.1%
2514
10.7%
3 1956
8.3%
8 1647
7.0%
7 1616
6.9%
4 1533
6.5%
9 1469
6.2%
1 1268
 
5.4%

소재지면적
Real number (ℝ)

ZEROS 

Distinct1940
Distinct (%)47.0%
Missing7
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean53.628415
Minimum0
Maximum920.82
Zeros389
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:52:41.943152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119.8
median33
Q365.13
95-th percentile169.535
Maximum920.82
Range920.82
Interquartile range (IQR)45.33

Descriptive statistics

Standard deviation62.910163
Coefficient of variation (CV)1.1730752
Kurtosis28.197674
Mean53.628415
Median Absolute Deviation (MAD)17.465
Skewness3.8435966
Sum221270.84
Variance3957.6886
MonotonicityNot monotonic
2024-04-06T20:52:42.200950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 389
 
9.4%
33.0 94
 
2.3%
30.0 58
 
1.4%
20.0 39
 
0.9%
26.4 38
 
0.9%
25.0 30
 
0.7%
23.0 28
 
0.7%
66.0 26
 
0.6%
40.0 26
 
0.6%
10.0 26
 
0.6%
Other values (1930) 3372
81.6%
ValueCountFrequency (%)
0.0 389
9.4%
1.0 1
 
< 0.1%
2.08 1
 
< 0.1%
3.0 2
 
< 0.1%
3.3 11
 
0.3%
3.75 1
 
< 0.1%
3.88 1
 
< 0.1%
4.5 1
 
< 0.1%
4.55 2
 
< 0.1%
4.68 1
 
< 0.1%
ValueCountFrequency (%)
920.82 1
< 0.1%
800.84 1
< 0.1%
796.32 1
< 0.1%
696.16 1
< 0.1%
557.24 1
< 0.1%
546.64 1
< 0.1%
513.43 1
< 0.1%
493.08 1
< 0.1%
492.52 1
< 0.1%
406.81 2
< 0.1%
Distinct244
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
2024-04-06T20:52:42.735096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.123639
Min length6

Characters and Unicode

Total characters25309
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

Unique30 ?
Unique (%)0.7%

Sample

1st row137808
2nd row137040
3rd row137829
4th row137828
5th row137845
ValueCountFrequency (%)
137040 170
 
4.1%
137810 151
 
3.7%
137856 99
 
2.4%
137829 97
 
2.3%
137809 94
 
2.3%
137858 90
 
2.2%
137887 84
 
2.0%
137860 83
 
2.0%
137855 80
 
1.9%
137882 73
 
1.8%
Other values (234) 3112
75.3%
2024-04-06T20:52:43.564919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4902
19.4%
7 4880
19.3%
3 4739
18.7%
8 4079
16.1%
0 1916
 
7.6%
9 1185
 
4.7%
5 909
 
3.6%
4 819
 
3.2%
6 710
 
2.8%
2 659
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24798
98.0%
Dash Punctuation 511
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4902
19.8%
7 4880
19.7%
3 4739
19.1%
8 4079
16.4%
0 1916
 
7.7%
9 1185
 
4.8%
5 909
 
3.7%
4 819
 
3.3%
6 710
 
2.9%
2 659
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 511
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4902
19.4%
7 4880
19.3%
3 4739
18.7%
8 4079
16.1%
0 1916
 
7.6%
9 1185
 
4.7%
5 909
 
3.6%
4 819
 
3.2%
6 710
 
2.8%
2 659
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4902
19.4%
7 4880
19.3%
3 4739
18.7%
8 4079
16.1%
0 1916
 
7.6%
9 1185
 
4.7%
5 909
 
3.6%
4 819
 
3.2%
6 710
 
2.8%
2 659
 
2.6%
Distinct3748
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
2024-04-06T20:52:44.056341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length52
Mean length27.746915
Min length15

Characters and Unicode

Total characters114678
Distinct characters409
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3434 ?
Unique (%)83.1%

Sample

1st row서울특별시 서초구 반포동 705-4번지
2nd row서울특별시 서초구 반포동 885-0번지
3rd row서울특별시 서초구 방배동 780-17번지
4th row서울특별시 서초구 방배동 758-2번지 삼호상가 1 6호
5th row서울특별시 서초구 방배동 951-30번지
ValueCountFrequency (%)
서울특별시 4133
18.6%
서초구 4133
18.6%
서초동 1317
 
5.9%
방배동 1175
 
5.3%
반포동 806
 
3.6%
1층 720
 
3.2%
2층 418
 
1.9%
양재동 391
 
1.8%
잠원동 356
 
1.6%
3층 165
 
0.7%
Other values (3762) 8556
38.6%
2024-04-06T20:52:44.860466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20446
17.8%
9751
 
8.5%
1 6892
 
6.0%
5590
 
4.9%
4403
 
3.8%
4183
 
3.6%
4148
 
3.6%
4141
 
3.6%
4134
 
3.6%
4133
 
3.6%
Other values (399) 46857
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63017
55.0%
Decimal Number 26261
22.9%
Space Separator 20446
 
17.8%
Dash Punctuation 3789
 
3.3%
Uppercase Letter 400
 
0.3%
Other Punctuation 277
 
0.2%
Open Punctuation 201
 
0.2%
Close Punctuation 201
 
0.2%
Math Symbol 47
 
< 0.1%
Lowercase Letter 30
 
< 0.1%
Other values (2) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9751
15.5%
5590
 
8.9%
4403
 
7.0%
4183
 
6.6%
4148
 
6.6%
4141
 
6.6%
4134
 
6.6%
4133
 
6.6%
3082
 
4.9%
2695
 
4.3%
Other values (336) 16757
26.6%
Uppercase Letter
ValueCountFrequency (%)
B 198
49.5%
A 41
 
10.2%
E 18
 
4.5%
M 13
 
3.2%
F 12
 
3.0%
L 12
 
3.0%
R 11
 
2.8%
P 11
 
2.8%
C 10
 
2.5%
G 9
 
2.2%
Other values (15) 65
 
16.2%
Lowercase Letter
ValueCountFrequency (%)
l 5
16.7%
i 4
13.3%
e 4
13.3%
o 2
 
6.7%
w 2
 
6.7%
r 2
 
6.7%
m 2
 
6.7%
s 2
 
6.7%
g 1
 
3.3%
n 1
 
3.3%
Other values (5) 5
16.7%
Decimal Number
ValueCountFrequency (%)
1 6892
26.2%
2 3627
13.8%
3 3202
12.2%
0 2716
 
10.3%
4 1919
 
7.3%
7 1893
 
7.2%
5 1777
 
6.8%
6 1529
 
5.8%
8 1432
 
5.5%
9 1274
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 255
92.1%
. 13
 
4.7%
/ 7
 
2.5%
& 1
 
0.4%
@ 1
 
0.4%
Letter Number
ValueCountFrequency (%)
6
75.0%
2
 
25.0%
Space Separator
ValueCountFrequency (%)
20446
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3789
100.0%
Open Punctuation
ValueCountFrequency (%)
( 201
100.0%
Close Punctuation
ValueCountFrequency (%)
) 201
100.0%
Math Symbol
ValueCountFrequency (%)
~ 47
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63015
54.9%
Common 51223
44.7%
Latin 437
 
0.4%
Han 2
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9751
15.5%
5590
 
8.9%
4403
 
7.0%
4183
 
6.6%
4148
 
6.6%
4141
 
6.6%
4134
 
6.6%
4133
 
6.6%
3082
 
4.9%
2695
 
4.3%
Other values (334) 16755
26.6%
Latin
ValueCountFrequency (%)
B 198
45.3%
A 41
 
9.4%
E 18
 
4.1%
M 13
 
3.0%
F 12
 
2.7%
L 12
 
2.7%
R 11
 
2.5%
P 11
 
2.5%
C 10
 
2.3%
G 9
 
2.1%
Other values (31) 102
23.3%
Common
ValueCountFrequency (%)
20446
39.9%
1 6892
 
13.5%
- 3789
 
7.4%
2 3627
 
7.1%
3 3202
 
6.3%
0 2716
 
5.3%
4 1919
 
3.7%
7 1893
 
3.7%
5 1777
 
3.5%
6 1529
 
3.0%
Other values (11) 3433
 
6.7%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%
Greek
ValueCountFrequency (%)
Ι 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63015
54.9%
ASCII 51651
45.0%
Number Forms 8
 
< 0.1%
CJK 2
 
< 0.1%
CJK Compat 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20446
39.6%
1 6892
 
13.3%
- 3789
 
7.3%
2 3627
 
7.0%
3 3202
 
6.2%
0 2716
 
5.3%
4 1919
 
3.7%
7 1893
 
3.7%
5 1777
 
3.4%
6 1529
 
3.0%
Other values (49) 3861
 
7.5%
Hangul
ValueCountFrequency (%)
9751
15.5%
5590
 
8.9%
4403
 
7.0%
4183
 
6.6%
4148
 
6.6%
4141
 
6.6%
4134
 
6.6%
4133
 
6.6%
3082
 
4.9%
2695
 
4.3%
Other values (334) 16755
26.6%
Number Forms
ValueCountFrequency (%)
6
75.0%
2
 
25.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
Ι 1
100.0%

도로명주소
Text

MISSING 

Distinct2573
Distinct (%)87.9%
Missing1205
Missing (%)29.2%
Memory size32.4 KiB
2024-04-06T20:52:45.426008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length54
Mean length35.049863
Min length21

Characters and Unicode

Total characters102626
Distinct characters409
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2296 ?
Unique (%)78.4%

Sample

1st row서울특별시 서초구 사임당로 138, 1층 (서초동, 신동아1차상가)
2nd row서울특별시 서초구 방배중앙로 166 (방배동,방배빌딩 1층)
3rd row서울특별시 서초구 동작대로 134 (방배동,10층)
4th row서울특별시 서초구 서초중앙로 245 (반포동)
5th row서울특별시 서초구 도구로 60 (방배동,지층)
ValueCountFrequency (%)
서울특별시 2928
 
14.7%
서초구 2928
 
14.7%
서초동 911
 
4.6%
방배동 682
 
3.4%
1층 665
 
3.3%
반포동 517
 
2.6%
2층 440
 
2.2%
양재동 236
 
1.2%
잠원동 234
 
1.2%
강남대로 195
 
1.0%
Other values (2192) 10155
51.1%
2024-04-06T20:52:46.334492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16967
 
16.5%
7712
 
7.5%
4656
 
4.5%
1 4422
 
4.3%
, 3801
 
3.7%
3355
 
3.3%
2 3035
 
3.0%
2985
 
2.9%
) 2970
 
2.9%
( 2970
 
2.9%
Other values (399) 49753
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57542
56.1%
Decimal Number 17391
 
16.9%
Space Separator 16967
 
16.5%
Other Punctuation 3814
 
3.7%
Close Punctuation 2970
 
2.9%
Open Punctuation 2970
 
2.9%
Dash Punctuation 472
 
0.5%
Uppercase Letter 452
 
0.4%
Math Symbol 19
 
< 0.1%
Lowercase Letter 17
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7712
 
13.4%
4656
 
8.1%
3355
 
5.8%
2985
 
5.2%
2968
 
5.2%
2936
 
5.1%
2929
 
5.1%
2928
 
5.1%
2888
 
5.0%
1866
 
3.2%
Other values (340) 22319
38.8%
Uppercase Letter
ValueCountFrequency (%)
B 211
46.7%
A 42
 
9.3%
E 22
 
4.9%
R 16
 
3.5%
T 15
 
3.3%
P 14
 
3.1%
M 12
 
2.7%
C 12
 
2.7%
L 12
 
2.7%
F 11
 
2.4%
Other values (16) 85
18.8%
Decimal Number
ValueCountFrequency (%)
1 4422
25.4%
2 3035
17.5%
3 1946
11.2%
0 1929
11.1%
5 1356
 
7.8%
4 1354
 
7.8%
7 1066
 
6.1%
6 840
 
4.8%
8 812
 
4.7%
9 631
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
e 3
17.6%
f 2
11.8%
i 2
11.8%
v 2
11.8%
b 2
11.8%
s 2
11.8%
r 1
 
5.9%
o 1
 
5.9%
h 1
 
5.9%
a 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 3801
99.7%
& 4
 
0.1%
. 4
 
0.1%
/ 4
 
0.1%
@ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
7
63.6%
4
36.4%
Space Separator
ValueCountFrequency (%)
16967
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2970
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2970
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 472
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57542
56.1%
Common 44604
43.5%
Latin 479
 
0.5%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7712
 
13.4%
4656
 
8.1%
3355
 
5.8%
2985
 
5.2%
2968
 
5.2%
2936
 
5.1%
2929
 
5.1%
2928
 
5.1%
2888
 
5.0%
1866
 
3.2%
Other values (340) 22319
38.8%
Latin
ValueCountFrequency (%)
B 211
44.1%
A 42
 
8.8%
E 22
 
4.6%
R 16
 
3.3%
T 15
 
3.1%
P 14
 
2.9%
M 12
 
2.5%
C 12
 
2.5%
L 12
 
2.5%
F 11
 
2.3%
Other values (27) 112
23.4%
Common
ValueCountFrequency (%)
16967
38.0%
1 4422
 
9.9%
, 3801
 
8.5%
2 3035
 
6.8%
) 2970
 
6.7%
( 2970
 
6.7%
3 1946
 
4.4%
0 1929
 
4.3%
5 1356
 
3.0%
4 1354
 
3.0%
Other values (11) 3854
 
8.6%
Greek
ValueCountFrequency (%)
Ι 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57542
56.1%
ASCII 45071
43.9%
Number Forms 11
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16967
37.6%
1 4422
 
9.8%
, 3801
 
8.4%
2 3035
 
6.7%
) 2970
 
6.6%
( 2970
 
6.6%
3 1946
 
4.3%
0 1929
 
4.3%
5 1356
 
3.0%
4 1354
 
3.0%
Other values (45) 4321
 
9.6%
Hangul
ValueCountFrequency (%)
7712
 
13.4%
4656
 
8.1%
3355
 
5.8%
2985
 
5.2%
2968
 
5.2%
2936
 
5.1%
2929
 
5.1%
2928
 
5.1%
2888
 
5.0%
1866
 
3.2%
Other values (340) 22319
38.8%
Number Forms
ValueCountFrequency (%)
7
63.6%
4
36.4%
None
ValueCountFrequency (%)
Ι 1
50.0%
1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct253
Distinct (%)8.7%
Missing1236
Missing (%)29.9%
Infinite0
Infinite (%)0.0%
Mean6623.8229
Minimum6501
Maximum6802
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:52:46.638450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6501
5-th percentile6515
Q16554
median6615
Q36683
95-th percentile6771
Maximum6802
Range301
Interquartile range (IQR)129

Descriptive statistics

Standard deviation78.568468
Coefficient of variation (CV)0.011861499
Kurtosis-0.83145536
Mean6623.8229
Median Absolute Deviation (MAD)63
Skewness0.40874382
Sum19189215
Variance6173.0042
MonotonicityNot monotonic
2024-04-06T20:52:46.929158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6536 82
 
2.0%
6627 76
 
1.8%
6611 75
 
1.8%
6621 52
 
1.3%
6626 47
 
1.1%
6568 46
 
1.1%
6544 44
 
1.1%
6577 42
 
1.0%
6540 40
 
1.0%
6524 38
 
0.9%
Other values (243) 2355
57.0%
(Missing) 1236
29.9%
ValueCountFrequency (%)
6501 8
 
0.2%
6502 34
0.8%
6503 15
0.4%
6506 14
 
0.3%
6509 9
 
0.2%
6510 8
 
0.2%
6511 1
 
< 0.1%
6512 37
0.9%
6514 7
 
0.2%
6515 19
0.5%
ValueCountFrequency (%)
6802 10
0.2%
6800 6
0.1%
6798 2
 
< 0.1%
6797 2
 
< 0.1%
6793 3
 
0.1%
6791 1
 
< 0.1%
6790 1
 
< 0.1%
6789 3
 
0.1%
6787 10
0.2%
6786 6
0.1%
Distinct3722
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
2024-04-06T20:52:47.504485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length7.2729252
Min length1

Characters and Unicode

Total characters30059
Distinct characters754
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3392 ?
Unique (%)82.1%

Sample

1st row미지헤어
2nd row박은숙
3rd row경희미용실
4th row은도
5th row주정란헤어써클
ValueCountFrequency (%)
헤어 186
 
2.9%
미용실 83
 
1.3%
에스테틱 83
 
1.3%
네일 80
 
1.2%
hair 56
 
0.9%
뷰티 38
 
0.6%
nail 37
 
0.6%
36
 
0.6%
살롱 36
 
0.6%
32
 
0.5%
Other values (4155) 5753
89.6%
2024-04-06T20:52:48.796407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2297
 
7.6%
1210
 
4.0%
1146
 
3.8%
915
 
3.0%
799
 
2.7%
656
 
2.2%
636
 
2.1%
595
 
2.0%
( 522
 
1.7%
) 522
 
1.7%
Other values (744) 20761
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22032
73.3%
Space Separator 2297
 
7.6%
Lowercase Letter 2280
 
7.6%
Uppercase Letter 1924
 
6.4%
Open Punctuation 523
 
1.7%
Close Punctuation 523
 
1.7%
Other Punctuation 226
 
0.8%
Decimal Number 225
 
0.7%
Dash Punctuation 12
 
< 0.1%
Connector Punctuation 6
 
< 0.1%
Other values (5) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1210
 
5.5%
1146
 
5.2%
915
 
4.2%
799
 
3.6%
656
 
3.0%
636
 
2.9%
595
 
2.7%
473
 
2.1%
383
 
1.7%
360
 
1.6%
Other values (661) 14859
67.4%
Uppercase Letter
ValueCountFrequency (%)
A 193
 
10.0%
N 155
 
8.1%
S 147
 
7.6%
H 141
 
7.3%
I 130
 
6.8%
O 121
 
6.3%
E 120
 
6.2%
L 107
 
5.6%
R 97
 
5.0%
T 89
 
4.6%
Other values (16) 624
32.4%
Lowercase Letter
ValueCountFrequency (%)
a 307
13.5%
e 277
12.1%
i 243
10.7%
l 179
 
7.9%
n 169
 
7.4%
o 157
 
6.9%
r 147
 
6.4%
h 116
 
5.1%
t 107
 
4.7%
s 106
 
4.6%
Other values (15) 472
20.7%
Other Punctuation
ValueCountFrequency (%)
& 63
27.9%
. 57
25.2%
? 34
15.0%
' 24
 
10.6%
# 24
 
10.6%
, 11
 
4.9%
: 9
 
4.0%
; 2
 
0.9%
% 1
 
0.4%
1
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 49
21.8%
0 44
19.6%
2 42
18.7%
5 17
 
7.6%
8 16
 
7.1%
3 16
 
7.1%
4 16
 
7.1%
9 9
 
4.0%
6 9
 
4.0%
7 7
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 522
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 522
99.8%
] 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%
Other Symbol
ValueCountFrequency (%)
° 3
100.0%
Modifier Letter
ValueCountFrequency (%)
ː 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22014
73.2%
Latin 4205
 
14.0%
Common 3822
 
12.7%
Han 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1210
 
5.5%
1146
 
5.2%
915
 
4.2%
799
 
3.6%
656
 
3.0%
636
 
2.9%
595
 
2.7%
473
 
2.1%
383
 
1.7%
360
 
1.6%
Other values (650) 14841
67.4%
Latin
ValueCountFrequency (%)
a 307
 
7.3%
e 277
 
6.6%
i 243
 
5.8%
A 193
 
4.6%
l 179
 
4.3%
n 169
 
4.0%
o 157
 
3.7%
N 155
 
3.7%
r 147
 
3.5%
S 147
 
3.5%
Other values (42) 2231
53.1%
Common
ValueCountFrequency (%)
2297
60.1%
( 522
 
13.7%
) 522
 
13.7%
& 63
 
1.6%
. 57
 
1.5%
1 49
 
1.3%
0 44
 
1.2%
2 42
 
1.1%
? 34
 
0.9%
' 24
 
0.6%
Other values (21) 168
 
4.4%
Han
ValueCountFrequency (%)
8
44.4%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22014
73.2%
ASCII 8021
 
26.7%
CJK 17
 
0.1%
None 4
 
< 0.1%
Modifier Letters 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2297
28.6%
( 522
 
6.5%
) 522
 
6.5%
a 307
 
3.8%
e 277
 
3.5%
i 243
 
3.0%
A 193
 
2.4%
l 179
 
2.2%
n 169
 
2.1%
o 157
 
2.0%
Other values (69) 3155
39.3%
Hangul
ValueCountFrequency (%)
1210
 
5.5%
1146
 
5.2%
915
 
4.2%
799
 
3.6%
656
 
3.0%
636
 
2.9%
595
 
2.7%
473
 
2.1%
383
 
1.7%
360
 
1.6%
Other values (650) 14841
67.4%
CJK
ValueCountFrequency (%)
8
47.1%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
None
ValueCountFrequency (%)
° 3
75.0%
1
 
25.0%
Modifier Letters
ValueCountFrequency (%)
ː 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct3430
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
Minimum1999-01-16 00:00:00
Maximum2024-04-03 13:59:25
2024-04-06T20:52:49.030778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:52:49.328896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
I
2696 
U
1413 
D
 
24

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2696
65.2%
U 1413
34.2%
D 24
 
0.6%

Length

2024-04-06T20:52:49.588508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:49.810962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2696
65.2%
u 1413
34.2%
d 24
 
0.6%
Distinct998
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-06T20:52:50.045013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:52:50.356182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
일반미용업
2541 
피부미용업
924 
네일아트업
418 
메이크업업
 
160
기타
 
90

Length

Max length5
Median length5
Mean length4.9346722
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 2541
61.5%
피부미용업 924
 
22.4%
네일아트업 418
 
10.1%
메이크업업 160
 
3.9%
기타 90
 
2.2%

Length

2024-04-06T20:52:50.721892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:51.016118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 2541
61.5%
피부미용업 924
 
22.4%
네일아트업 418
 
10.1%
메이크업업 160
 
3.9%
기타 90
 
2.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1804
Distinct (%)44.9%
Missing117
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean200953.67
Minimum198344.76
Maximum207147.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:52:51.298748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198344.76
5-th percentile198524.53
Q1199513.04
median201230.69
Q3202044.14
95-th percentile203584.2
Maximum207147.91
Range8803.1504
Interquartile range (IQR)2531.0995

Descriptive statistics

Standard deviation1571.9296
Coefficient of variation (CV)0.0078223482
Kurtosis-0.83916705
Mean200953.67
Median Absolute Deviation (MAD)1199.2408
Skewness0.013710491
Sum8.0702995 × 108
Variance2470962.7
MonotonicityNot monotonic
2024-04-06T20:52:51.616055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200800.417027918 33
 
0.8%
202478.1048837 27
 
0.7%
199513.040528302 24
 
0.6%
202053.5363317 23
 
0.6%
202245.377899369 20
 
0.5%
201853.889908967 20
 
0.5%
202389.26 19
 
0.5%
200005.626362552 19
 
0.5%
202580.644821513 19
 
0.5%
201643.318591414 18
 
0.4%
Other values (1794) 3794
91.8%
(Missing) 117
 
2.8%
ValueCountFrequency (%)
198344.761390706 2
< 0.1%
198345.279900118 1
 
< 0.1%
198349.158592224 1
 
< 0.1%
198351.955 3
0.1%
198355.846023337 1
 
< 0.1%
198359.631134461 1
 
< 0.1%
198361.492288503 1
 
< 0.1%
198367.956597525 1
 
< 0.1%
198371.633126437 1
 
< 0.1%
198374.818173024 1
 
< 0.1%
ValueCountFrequency (%)
207147.911759758 1
 
< 0.1%
205583.30209169 1
 
< 0.1%
205231.176713429 1
 
< 0.1%
205221.03374911 2
< 0.1%
205219.282487819 1
 
< 0.1%
205203.899329664 1
 
< 0.1%
205062.232093186 1
 
< 0.1%
205049.592851657 1
 
< 0.1%
204999.751243915 1
 
< 0.1%
204964.487244211 3
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1804
Distinct (%)44.9%
Missing117
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean443366.35
Minimum438068.09
Maximum446565.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:52:51.907534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438068.09
5-th percentile441130.88
Q1442441.16
median443306.06
Q3444439.9
95-th percentile445551.95
Maximum446565.03
Range8496.934
Interquartile range (IQR)1998.7396

Descriptive statistics

Standard deviation1359.4174
Coefficient of variation (CV)0.0030661267
Kurtosis0.054604439
Mean443366.35
Median Absolute Deviation (MAD)977.4839
Skewness-0.18921986
Sum1.7805593 × 109
Variance1848015.8
MonotonicityNot monotonic
2024-04-06T20:52:52.361737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444989.874340522 33
 
0.8%
443306.064904505 27
 
0.7%
442328.58100894 24
 
0.6%
444426.026431763 23
 
0.6%
442987.986999742 20
 
0.5%
444549.812390159 20
 
0.5%
443804.065 19
 
0.5%
444680.521703344 19
 
0.5%
443264.557852558 19
 
0.5%
443772.466475611 18
 
0.4%
Other values (1794) 3794
91.8%
(Missing) 117
 
2.8%
ValueCountFrequency (%)
438068.094636291 1
 
< 0.1%
438140.645891284 1
 
< 0.1%
438416.991038311 2
< 0.1%
438418.0 1
 
< 0.1%
438473.237373955 1
 
< 0.1%
438491.712309438 3
0.1%
438521.810569305 1
 
< 0.1%
438648.715942165 1
 
< 0.1%
438972.976710982 2
< 0.1%
439034.848861341 1
 
< 0.1%
ValueCountFrequency (%)
446565.028672992 7
0.2%
446331.380046658 3
 
0.1%
446268.294338007 6
0.1%
446247.719636035 3
 
0.1%
446206.354902748 1
 
< 0.1%
446202.471850496 8
0.2%
446179.309516814 2
 
< 0.1%
446144.110278895 3
 
0.1%
446115.427252649 2
 
< 0.1%
446102.588876 4
0.1%

위생업태명
Categorical

Distinct17
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
미용업
926 
<NA>
822 
종합미용업
700 
일반미용업
671 
피부미용업
581 
Other values (12)
433 

Length

Max length23
Median length5
Mean length4.9383015
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 926
22.4%
<NA> 822
19.9%
종합미용업 700
16.9%
일반미용업 671
16.2%
피부미용업 581
14.1%
네일미용업 179
 
4.3%
일반미용업, 화장ㆍ분장 미용업 55
 
1.3%
피부미용업, 네일미용업 45
 
1.1%
화장ㆍ분장 미용업 37
 
0.9%
네일미용업, 화장ㆍ분장 미용업 30
 
0.7%
Other values (7) 87
 
2.1%

Length

2024-04-06T20:52:52.653655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 1095
24.1%
na 822
18.1%
일반미용업 782
17.2%
종합미용업 700
15.4%
피부미용업 673
14.8%
네일미용업 310
 
6.8%
화장ㆍ분장 169
 
3.7%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)0.7%
Missing1586
Missing (%)38.4%
Infinite0
Infinite (%)0.0%
Mean0.33765214
Minimum0
Maximum46
Zeros2391
Zeros (%)57.9%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:52:52.892297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum46
Range46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.0984806
Coefficient of variation (CV)6.2149189
Kurtosis221.7534
Mean0.33765214
Median Absolute Deviation (MAD)0
Skewness12.776743
Sum860
Variance4.403621
MonotonicityNot monotonic
2024-04-06T20:52:53.125885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 2391
57.9%
5 33
 
0.8%
1 23
 
0.6%
2 22
 
0.5%
3 22
 
0.5%
6 16
 
0.4%
4 15
 
0.4%
8 6
 
0.1%
15 5
 
0.1%
7 3
 
0.1%
Other values (8) 11
 
0.3%
(Missing) 1586
38.4%
ValueCountFrequency (%)
0 2391
57.9%
1 23
 
0.6%
2 22
 
0.5%
3 22
 
0.5%
4 15
 
0.4%
5 33
 
0.8%
6 16
 
0.4%
7 3
 
0.1%
8 6
 
0.1%
10 2
 
< 0.1%
ValueCountFrequency (%)
46 2
 
< 0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
21 1
 
< 0.1%
20 2
 
< 0.1%
19 1
 
< 0.1%
15 5
0.1%
11 1
 
< 0.1%
10 2
 
< 0.1%
8 6
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.4%
Missing1594
Missing (%)38.6%
Infinite0
Infinite (%)0.0%
Mean0.081134305
Minimum0
Maximum20
Zeros2423
Zeros (%)58.6%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:52:53.381866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.60314592
Coefficient of variation (CV)7.4339199
Kurtosis507.91431
Mean0.081134305
Median Absolute Deviation (MAD)0
Skewness18.510451
Sum206
Variance0.363785
MonotonicityNot monotonic
2024-04-06T20:52:53.569233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 2423
58.6%
1 90
 
2.2%
2 9
 
0.2%
5 5
 
0.1%
3 4
 
0.1%
6 3
 
0.1%
4 2
 
< 0.1%
7 1
 
< 0.1%
20 1
 
< 0.1%
8 1
 
< 0.1%
(Missing) 1594
38.6%
ValueCountFrequency (%)
0 2423
58.6%
1 90
 
2.2%
2 9
 
0.2%
3 4
 
0.1%
4 2
 
< 0.1%
5 5
 
0.1%
6 3
 
0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
6 3
 
0.1%
5 5
 
0.1%
4 2
 
< 0.1%
3 4
 
0.1%
2 9
 
0.2%
1 90
 
2.2%
0 2423
58.6%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.7%
Missing1678
Missing (%)40.6%
Infinite0
Infinite (%)0.0%
Mean1.510387
Minimum0
Maximum33
Zeros619
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:52:53.767530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum33
Range33
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7772772
Coefficient of variation (CV)1.1767032
Kurtosis49.04107
Mean1.510387
Median Absolute Deviation (MAD)1
Skewness4.5110359
Sum3708
Variance3.1587144
MonotonicityNot monotonic
2024-04-06T20:52:53.966684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 928
22.5%
0 619
 
15.0%
2 517
 
12.5%
3 182
 
4.4%
4 85
 
2.1%
5 56
 
1.4%
6 26
 
0.6%
7 10
 
0.2%
10 8
 
0.2%
8 7
 
0.2%
Other values (6) 17
 
0.4%
(Missing) 1678
40.6%
ValueCountFrequency (%)
0 619
15.0%
1 928
22.5%
2 517
12.5%
3 182
 
4.4%
4 85
 
2.1%
5 56
 
1.4%
6 26
 
0.6%
7 10
 
0.2%
8 7
 
0.2%
9 4
 
0.1%
ValueCountFrequency (%)
33 1
 
< 0.1%
15 2
 
< 0.1%
13 2
 
< 0.1%
12 5
 
0.1%
11 3
 
0.1%
10 8
 
0.2%
9 4
 
0.1%
8 7
 
0.2%
7 10
 
0.2%
6 26
0.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)0.8%
Missing2153
Missing (%)52.1%
Infinite0
Infinite (%)0.0%
Mean1.8424242
Minimum0
Maximum15
Zeros163
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:52:54.195554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile5
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.659011
Coefficient of variation (CV)0.90045005
Kurtosis13.340106
Mean1.8424242
Median Absolute Deviation (MAD)1
Skewness2.9400607
Sum3648
Variance2.7523175
MonotonicityNot monotonic
2024-04-06T20:52:54.424144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 914
22.1%
2 514
 
12.4%
3 181
 
4.4%
0 163
 
3.9%
4 85
 
2.1%
5 56
 
1.4%
6 27
 
0.7%
7 10
 
0.2%
10 8
 
0.2%
8 7
 
0.2%
Other values (5) 15
 
0.4%
(Missing) 2153
52.1%
ValueCountFrequency (%)
0 163
 
3.9%
1 914
22.1%
2 514
12.4%
3 181
 
4.4%
4 85
 
2.1%
5 56
 
1.4%
6 27
 
0.7%
7 10
 
0.2%
8 7
 
0.2%
9 4
 
0.1%
ValueCountFrequency (%)
15 2
 
< 0.1%
13 3
 
0.1%
12 4
 
0.1%
11 2
 
< 0.1%
10 8
 
0.2%
9 4
 
0.1%
8 7
 
0.2%
7 10
 
0.2%
6 27
0.7%
5 56
1.4%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
2831 
0
1059 
1
 
226
2
 
16
3
 
1

Length

Max length4
Median length4
Mean length3.0549238
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 2831
68.5%
0 1059
 
25.6%
1 226
 
5.5%
2 16
 
0.4%
3 1
 
< 0.1%

Length

2024-04-06T20:52:54.681247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:54.906237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2831
68.5%
0 1059
 
25.6%
1 226
 
5.5%
2 16
 
0.4%
3 1
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
3290 
0
600 
1
 
226
2
 
16
3
 
1

Length

Max length4
Median length4
Mean length3.3880958
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3290
79.6%
0 600
 
14.5%
1 226
 
5.5%
2 16
 
0.4%
3 1
 
< 0.1%

Length

2024-04-06T20:52:55.170884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:55.374974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3290
79.6%
0 600
 
14.5%
1 226
 
5.5%
2 16
 
0.4%
3 1
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
0
2674 
<NA>
1459 

Length

Max length4
Median length1
Mean length2.059037
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2674
64.7%
<NA> 1459
35.3%

Length

2024-04-06T20:52:55.612822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:55.842159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2674
64.7%
na 1459
35.3%

양실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
0
2674 
<NA>
1459 

Length

Max length4
Median length1
Mean length2.059037
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2674
64.7%
<NA> 1459
35.3%

Length

2024-04-06T20:52:56.167158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:56.388104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2674
64.7%
na 1459
35.3%

욕실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
0
2674 
<NA>
1459 

Length

Max length4
Median length1
Mean length2.059037
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2674
64.7%
<NA> 1459
35.3%

Length

2024-04-06T20:52:56.605576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:56.825980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2674
64.7%
na 1459
35.3%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing865
Missing (%)20.9%
Memory size8.2 KiB
False
3268 
(Missing)
865 
ValueCountFrequency (%)
False 3268
79.1%
(Missing) 865
 
20.9%
2024-04-06T20:52:57.006339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)1.1%
Missing1164
Missing (%)28.2%
Infinite0
Infinite (%)0.0%
Mean3.6699225
Minimum0
Maximum38
Zeros539
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:52:57.176177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile10
Maximum38
Range38
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.5150104
Coefficient of variation (CV)0.95778871
Kurtosis16.224139
Mean3.6699225
Median Absolute Deviation (MAD)1
Skewness2.9205948
Sum10896
Variance12.355298
MonotonicityNot monotonic
2024-04-06T20:52:57.501664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
3 740
17.9%
0 539
13.0%
4 480
11.6%
2 404
 
9.8%
5 220
 
5.3%
6 143
 
3.5%
8 81
 
2.0%
1 77
 
1.9%
7 69
 
1.7%
10 65
 
1.6%
Other values (22) 151
 
3.7%
(Missing) 1164
28.2%
ValueCountFrequency (%)
0 539
13.0%
1 77
 
1.9%
2 404
9.8%
3 740
17.9%
4 480
11.6%
5 220
 
5.3%
6 143
 
3.5%
7 69
 
1.7%
8 81
 
2.0%
9 31
 
0.8%
ValueCountFrequency (%)
38 2
< 0.1%
33 1
 
< 0.1%
32 1
 
< 0.1%
31 1
 
< 0.1%
30 1
 
< 0.1%
28 2
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
23 1
 
< 0.1%
22 3
0.1%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing4132
Missing (%)> 99.9%
Memory size32.4 KiB
2024-04-06T20:52:57.864909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row가설건출물 존치기간
ValueCountFrequency (%)
가설건출물 1
50.0%
존치기간 1
50.0%
2024-04-06T20:52:58.462867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9
90.0%
Space Separator 1
 
10.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9
90.0%
Common 1
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9
90.0%
ASCII 1
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
ASCII
ValueCountFrequency (%)
1
100.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
4132 
20130622
 
1

Length

Max length8
Median length4
Mean length4.0009678
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4132
> 99.9%
20130622 1
 
< 0.1%

Length

2024-04-06T20:52:58.788054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:59.004748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4132
> 99.9%
20130622 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
4132 
20160621
 
1

Length

Max length8
Median length4
Mean length4.0009678
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4132
> 99.9%
20160621 1
 
< 0.1%

Length

2024-04-06T20:52:59.224858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:59.442281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4132
> 99.9%
20160621 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
2444 
임대
1679 
자가
 
10

Length

Max length4
Median length4
Mean length3.182676
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2444
59.1%
임대 1679
40.6%
자가 10
 
0.2%

Length

2024-04-06T20:52:59.660087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:52:59.900692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2444
59.1%
임대 1679
40.6%
자가 10
 
0.2%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
0
2070 
<NA>
2063 

Length

Max length4
Median length1
Mean length2.4974595
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 2070
50.1%
<NA> 2063
49.9%

Length

2024-04-06T20:53:00.171134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:53:00.497813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2070
50.1%
na 2063
49.9%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.9%
Missing3083
Missing (%)74.6%
Infinite0
Infinite (%)0.0%
Mean0.088571429
Minimum0
Maximum10
Zeros1004
Zeros (%)24.3%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:53:00.680628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5665971
Coefficient of variation (CV)6.3970641
Kurtosis134.47774
Mean0.088571429
Median Absolute Deviation (MAD)0
Skewness10.285297
Sum93
Variance0.32103228
MonotonicityNot monotonic
2024-04-06T20:53:00.896111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 1004
 
24.3%
1 28
 
0.7%
2 8
 
0.2%
4 3
 
0.1%
3 3
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 3083
74.6%
ValueCountFrequency (%)
0 1004
24.3%
1 28
 
0.7%
2 8
 
0.2%
3 3
 
0.1%
4 3
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 3
 
0.1%
3 3
 
0.1%
2 8
 
0.2%
1 28
 
0.7%
0 1004
24.3%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
3086 
0
1040 
1
 
6
2
 
1

Length

Max length4
Median length4
Mean length3.2400194
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3086
74.7%
0 1040
 
25.2%
1 6
 
0.1%
2 1
 
< 0.1%

Length

2024-04-06T20:53:01.276661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:53:01.545200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3086
74.7%
0 1040
 
25.2%
1 6
 
0.1%
2 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 KiB
<NA>
2156 
0
1977 

Length

Max length4
Median length4
Mean length2.5649649
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2156
52.2%
0 1977
47.8%

Length

2024-04-06T20:53:02.355186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:53:02.569048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2156
52.2%
0 1977
47.8%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)1.4%
Missing2179
Missing (%)52.7%
Infinite0
Infinite (%)0.0%
Mean1.6847492
Minimum0
Maximum58
Zeros1133
Zeros (%)27.4%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-04-06T20:53:02.852255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile7
Maximum58
Range58
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.4864822
Coefficient of variation (CV)2.0694369
Kurtosis63.840917
Mean1.6847492
Median Absolute Deviation (MAD)0
Skewness6.064209
Sum3292
Variance12.155558
MonotonicityNot monotonic
2024-04-06T20:53:03.106961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 1133
27.4%
2 192
 
4.6%
1 171
 
4.1%
3 124
 
3.0%
4 86
 
2.1%
5 71
 
1.7%
6 56
 
1.4%
7 46
 
1.1%
8 22
 
0.5%
9 15
 
0.4%
Other values (17) 38
 
0.9%
(Missing) 2179
52.7%
ValueCountFrequency (%)
0 1133
27.4%
1 171
 
4.1%
2 192
 
4.6%
3 124
 
3.0%
4 86
 
2.1%
5 71
 
1.7%
6 56
 
1.4%
7 46
 
1.1%
8 22
 
0.5%
9 15
 
0.4%
ValueCountFrequency (%)
58 1
< 0.1%
45 1
< 0.1%
35 1
< 0.1%
31 1
< 0.1%
30 1
< 0.1%
28 2
< 0.1%
27 1
< 0.1%
25 2
< 0.1%
24 1
< 0.1%
22 2
< 0.1%

다중이용업소여부
Boolean

MISSING 

Distinct2
Distinct (%)0.1%
Missing822
Missing (%)19.9%
Memory size8.2 KiB
False
2672 
True
639 
(Missing)
822 
ValueCountFrequency (%)
False 2672
64.7%
True 639
 
15.5%
(Missing) 822
 
19.9%
2024-04-06T20:53:03.347266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032100003210000-204-1971-0000119710309<NA>3폐업2폐업20080807<NA><NA><NA>02 54123650.0137808서울특별시 서초구 반포동 705-4번지<NA><NA>미지헤어2004-02-04 00:00:00I2018-08-31 23:59:59.0일반미용업201668.490077445323.646858미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N6<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
132100003210000-204-1976-0090719760324<NA>3폐업2폐업19910402<NA><NA><NA>020599009515.68137040서울특별시 서초구 반포동 885-0번지<NA><NA>박은숙2001-09-29 00:00:00I2018-08-31 23:59:59.0일반미용업198845.040146444439.89559미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
232100003210000-204-1976-0122519760727<NA>3폐업2폐업19980430<NA><NA><NA>02 537704516.8137829서울특별시 서초구 방배동 780-17번지<NA><NA>경희미용실2001-09-29 00:00:00I2018-08-31 23:59:59.0일반미용업198561.871114443397.842302미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
332100003210000-204-1977-0121419770819<NA>3폐업2폐업19951219<NA><NA><NA>020599020616.1137828서울특별시 서초구 방배동 758-2번지 삼호상가 1 6호<NA><NA>은도2001-09-29 00:00:00I2018-08-31 23:59:59.0일반미용업198845.657798443825.965071미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
432100003210000-204-1978-0122119780112<NA>3폐업2폐업20061125<NA><NA><NA>020582790222.81137845서울특별시 서초구 방배동 951-30번지<NA><NA>주정란헤어써클2003-03-29 00:00:00I2018-08-31 23:59:59.0일반미용업198677.87453442535.535954미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
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732100003210000-204-1979-0121019790228<NA>3폐업2폐업19951219<NA><NA><NA>020533335613.12137833서울특별시 서초구 방배동 825-2번지<NA><NA>2001-09-29 00:00:00I2018-08-31 23:59:59.0일반미용업198599.563993443169.713857미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
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412732100003210000-226-2022-0000220220425<NA>1영업/정상1영업<NA><NA><NA><NA><NA>57.72137852서울특별시 서초구 방배동 1397 4층서울특별시 서초구 서초대로1길 6, 4층 (방배동)6568오아스틱 네일2022-04-25 11:18:11I2021-12-03 22:08:00.0네일아트업198441.844414442739.948706<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
412832100003210000-226-2022-0000320220429<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.39137876서울특별시 서초구 서초동 1593-7 1층105호서울특별시 서초구 효령로53길 45, 1층 105호 (서초동, 서초이오빌)6652마이제이네일(MY-J nail)2022-04-29 13:50:58I2021-12-05 00:03:00.0네일아트업201070.374374442706.851935<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
412932100003210000-226-2022-0000420220927<NA>1영업/정상1영업<NA><NA><NA><NA><NA>75.0137808서울특별시 서초구 반포동 711-9 1층서울특별시 서초구 주흥13길 14-3, 1층 (반포동)6533제이하우스2022-09-27 16:02:49I2021-12-08 22:09:00.0메이크업업201555.578223445150.937285<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413032100003210000-226-2023-000012023-03-14<NA>3폐업2폐업2023-09-07<NA><NA><NA><NA>9.0137-860서울특별시 서초구 서초동 1337-17 보원빌딩 203호서울특별시 서초구 사임당로 180, 203호 (서초동)6627뷰뷰 살롱2023-09-07 11:49:28U2022-12-09 00:09:00.0메이크업업202521.383139443368.091262<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413132100003210000-226-2023-000022023-03-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.0137-851서울특별시 서초구 방배동 1020-11서울특별시 서초구 효령로34길 66, 1층 3호 (방배동)6705휴(Hue:)2023-05-11 17:23:57I2022-12-04 23:03:00.0피부미용업199994.361677441849.524895<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413232100003210000-226-2024-000012024-01-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.81137-856서울특별시 서초구 서초동 1315 진흥상가 1층 9호서울특별시 서초구 서초대로 389, 진흥상가 1층 9호 (서초동)6617루시아네일2024-01-29 15:38:21I2023-11-30 21:01:00.0네일아트업201930.014908443904.461724<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>