Overview

Dataset statistics

Number of variables44
Number of observations8366
Missing cells94978
Missing cells (%)25.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 MiB
Average record size in memory376.0 B

Variable types

Categorical18
Text7
DateTime4
Unsupported7
Numeric7
Boolean1

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,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-18698/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
건물소유구분명 has constant value ""Constant
영업장주변구분명 is highly imbalanced (61.5%)Imbalance
등급구분명 is highly imbalanced (63.9%)Imbalance
급수시설구분명 is highly imbalanced (56.6%)Imbalance
총인원 is highly imbalanced (71.2%)Imbalance
본사종업원수 is highly imbalanced (71.0%)Imbalance
공장사무직종업원수 is highly imbalanced (71.0%)Imbalance
공장판매직종업원수 is highly imbalanced (71.0%)Imbalance
공장생산직종업원수 is highly imbalanced (71.0%)Imbalance
보증액 is highly imbalanced (71.0%)Imbalance
월세액 is highly imbalanced (71.0%)Imbalance
다중이용업소여부 is highly imbalanced (64.7%)Imbalance
인허가취소일자 has 8366 (100.0%) missing valuesMissing
폐업일자 has 2184 (26.1%) missing valuesMissing
휴업시작일자 has 8366 (100.0%) missing valuesMissing
휴업종료일자 has 8366 (100.0%) missing valuesMissing
재개업일자 has 8366 (100.0%) missing valuesMissing
전화번호 has 4586 (54.8%) missing valuesMissing
소재지면적 has 255 (3.0%) missing valuesMissing
도로명주소 has 2798 (33.4%) missing valuesMissing
도로명우편번호 has 2853 (34.1%) missing valuesMissing
좌표정보(X) has 219 (2.6%) missing valuesMissing
좌표정보(Y) has 219 (2.6%) missing valuesMissing
남성종사자수 has 5634 (67.3%) missing valuesMissing
여성종사자수 has 5627 (67.3%) missing valuesMissing
건물소유구분명 has 8365 (> 99.9%) missing valuesMissing
다중이용업소여부 has 1838 (22.0%) missing valuesMissing
시설총규모 has 1838 (22.0%) missing valuesMissing
전통업소지정번호 has 8366 (100.0%) missing valuesMissing
전통업소주된음식 has 8366 (100.0%) missing valuesMissing
홈페이지 has 8366 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 34.30783729)Skewed
여성종사자수 is highly skewed (γ1 = 28.03689903)Skewed
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
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 223 (2.7%) zerosZeros
남성종사자수 has 2467 (29.5%) zerosZeros
여성종사자수 has 2105 (25.2%) zerosZeros
시설총규모 has 133 (1.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:42:19.422523
Analysis finished2024-05-11 06:42:22.785004
Duration3.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
3210000
8366 

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 8366
100.0%

Length

2024-05-11T15:42:22.886389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:23.030139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 8366
100.0%

관리번호
Text

UNIQUE 

Distinct8366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
2024-05-11T15:42:23.285062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters184052
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

Unique8366 ?
Unique (%)100.0%

Sample

1st row3210000-104-1904-01143
2nd row3210000-104-1953-00572
3rd row3210000-104-1973-01534
4th row3210000-104-1976-01172
5th row3210000-104-1976-01519
ValueCountFrequency (%)
3210000-104-1904-01143 1
 
< 0.1%
3210000-104-2017-00303 1
 
< 0.1%
3210000-104-2017-00301 1
 
< 0.1%
3210000-104-2017-00300 1
 
< 0.1%
3210000-104-2017-00299 1
 
< 0.1%
3210000-104-2017-00298 1
 
< 0.1%
3210000-104-2017-00297 1
 
< 0.1%
3210000-104-2017-00296 1
 
< 0.1%
3210000-104-2017-00295 1
 
< 0.1%
3210000-104-2017-00294 1
 
< 0.1%
Other values (8356) 8356
99.9%
2024-05-11T15:42:23.840452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70518
38.3%
1 27597
 
15.0%
- 25098
 
13.6%
2 20987
 
11.4%
3 12081
 
6.6%
4 11445
 
6.2%
9 5417
 
2.9%
8 2773
 
1.5%
5 2740
 
1.5%
6 2719
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 158954
86.4%
Dash Punctuation 25098
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 70518
44.4%
1 27597
 
17.4%
2 20987
 
13.2%
3 12081
 
7.6%
4 11445
 
7.2%
9 5417
 
3.4%
8 2773
 
1.7%
5 2740
 
1.7%
6 2719
 
1.7%
7 2677
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 25098
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184052
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 70518
38.3%
1 27597
 
15.0%
- 25098
 
13.6%
2 20987
 
11.4%
3 12081
 
6.6%
4 11445
 
6.2%
9 5417
 
2.9%
8 2773
 
1.5%
5 2740
 
1.5%
6 2719
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 184052
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70518
38.3%
1 27597
 
15.0%
- 25098
 
13.6%
2 20987
 
11.4%
3 12081
 
6.6%
4 11445
 
6.2%
9 5417
 
2.9%
8 2773
 
1.5%
5 2740
 
1.5%
6 2719
 
1.5%

인허가일자
Date

Distinct4894
Distinct (%)58.5%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
Minimum1904-08-08 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:42:24.334290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:24.572677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8366
Missing (%)100.0%
Memory size73.7 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
3
6182 
1
2184 

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 6182
73.9%
1 2184
 
26.1%

Length

2024-05-11T15:42:24.834393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:25.026991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 6182
73.9%
1 2184
 
26.1%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
폐업
6182 
영업/정상
2184 

Length

Max length5
Median length2
Mean length2.78317
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6182
73.9%
영업/정상 2184
 
26.1%

Length

2024-05-11T15:42:25.227862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:25.401722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6182
73.9%
영업/정상 2184
 
26.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
2
6182 
1
2184 

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 6182
73.9%
1 2184
 
26.1%

Length

2024-05-11T15:42:25.565609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:25.715573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6182
73.9%
1 2184
 
26.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
폐업
6182 
영업
2184 

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 6182
73.9%
영업 2184
 
26.1%

Length

2024-05-11T15:42:25.894278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:26.052017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6182
73.9%
영업 2184
 
26.1%

폐업일자
Date

MISSING 

Distinct3705
Distinct (%)59.9%
Missing2184
Missing (%)26.1%
Memory size65.5 KiB
Minimum1989-04-04 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:42:26.240078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:26.457967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8366
Missing (%)100.0%
Memory size73.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8366
Missing (%)100.0%
Memory size73.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8366
Missing (%)100.0%
Memory size73.7 KiB

전화번호
Text

MISSING 

Distinct3225
Distinct (%)85.3%
Missing4586
Missing (%)54.8%
Memory size65.5 KiB
2024-05-11T15:42:26.893376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.346825
Min length2

Characters and Unicode

Total characters39111
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3038 ?
Unique (%)80.4%

Sample

1st row0205935096
2nd row02 5356145
3rd row0205720536
4th row02 5863394
5th row0205787232
ValueCountFrequency (%)
02 2408
34.0%
070 80
 
1.1%
031 70
 
1.0%
0200000000 56
 
0.8%
0 45
 
0.6%
00000 35
 
0.5%
537 24
 
0.3%
521 22
 
0.3%
0205350002 21
 
0.3%
522 21
 
0.3%
Other values (3352) 4291
60.7%
2024-05-11T15:42:27.686594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7288
18.6%
2 6042
15.4%
4506
11.5%
5 4455
11.4%
3 3006
7.7%
7 2598
 
6.6%
8 2443
 
6.2%
4 2318
 
5.9%
1 2281
 
5.8%
9 2137
 
5.5%
Other values (2) 2037
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34604
88.5%
Space Separator 4506
 
11.5%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7288
21.1%
2 6042
17.5%
5 4455
12.9%
3 3006
8.7%
7 2598
 
7.5%
8 2443
 
7.1%
4 2318
 
6.7%
1 2281
 
6.6%
9 2137
 
6.2%
6 2036
 
5.9%
Space Separator
ValueCountFrequency (%)
4506
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39111
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7288
18.6%
2 6042
15.4%
4506
11.5%
5 4455
11.4%
3 3006
7.7%
7 2598
 
6.6%
8 2443
 
6.2%
4 2318
 
5.9%
1 2281
 
5.8%
9 2137
 
5.5%
Other values (2) 2037
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7288
18.6%
2 6042
15.4%
4506
11.5%
5 4455
11.4%
3 3006
7.7%
7 2598
 
6.6%
8 2443
 
6.2%
4 2318
 
5.9%
1 2281
 
5.8%
9 2137
 
5.5%
Other values (2) 2037
 
5.2%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct3311
Distinct (%)40.8%
Missing255
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean47.81881
Minimum0
Maximum865.6
Zeros223
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size73.7 KiB
2024-05-11T15:42:27.979084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.27
Q110
median27.54
Q359.705
95-th percentile170.935
Maximum865.6
Range865.6
Interquartile range (IQR)49.705

Descriptive statistics

Standard deviation62.392862
Coefficient of variation (CV)1.3047765
Kurtosis16.919757
Mean47.81881
Median Absolute Deviation (MAD)20.31
Skewness3.2697322
Sum387858.37
Variance3892.8692
MonotonicityNot monotonic
2024-05-11T15:42:28.227595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 365
 
4.4%
10.0 314
 
3.8%
6.6 256
 
3.1%
0.0 223
 
2.7%
9.9 123
 
1.5%
33.0 122
 
1.5%
6.0 110
 
1.3%
9.0 80
 
1.0%
3.0 72
 
0.9%
16.5 70
 
0.8%
Other values (3301) 6376
76.2%
(Missing) 255
 
3.0%
ValueCountFrequency (%)
0.0 223
2.7%
0.09 1
 
< 0.1%
0.45 1
 
< 0.1%
0.63 3
 
< 0.1%
0.9 1
 
< 0.1%
0.94 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 5
 
0.1%
1.2 1
 
< 0.1%
1.21 1
 
< 0.1%
ValueCountFrequency (%)
865.6 1
< 0.1%
684.48 1
< 0.1%
636.35 1
< 0.1%
579.3 1
< 0.1%
577.5 1
< 0.1%
565.0 1
< 0.1%
544.97 1
< 0.1%
520.61 1
< 0.1%
516.7 1
< 0.1%
508.35 1
< 0.1%

소재지우편번호
Text

Distinct297
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
2024-05-11T15:42:28.760444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1491752
Min length6

Characters and Unicode

Total characters51444
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

Unique40 ?
Unique (%)0.5%

Sample

1st row137829
2nd row137713
3rd row137886
4th row137953
5th row137887
ValueCountFrequency (%)
137713 984
 
11.8%
137040 309
 
3.7%
137908 173
 
2.1%
137856 172
 
2.1%
137-713 165
 
2.0%
137893 156
 
1.9%
137787 146
 
1.7%
137881 132
 
1.6%
137882 117
 
1.4%
137810 110
 
1.3%
Other values (287) 5902
70.5%
2024-05-11T15:42:29.787179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 11316
22.0%
1 10894
21.2%
3 10744
20.9%
8 6768
13.2%
0 3304
 
6.4%
9 2172
 
4.2%
6 1501
 
2.9%
5 1331
 
2.6%
- 1248
 
2.4%
4 1170
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50196
97.6%
Dash Punctuation 1248
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 11316
22.5%
1 10894
21.7%
3 10744
21.4%
8 6768
13.5%
0 3304
 
6.6%
9 2172
 
4.3%
6 1501
 
3.0%
5 1331
 
2.7%
4 1170
 
2.3%
2 996
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 1248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 11316
22.0%
1 10894
21.2%
3 10744
20.9%
8 6768
13.2%
0 3304
 
6.4%
9 2172
 
4.2%
6 1501
 
2.9%
5 1331
 
2.6%
- 1248
 
2.4%
4 1170
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 11316
22.0%
1 10894
21.2%
3 10744
20.9%
8 6768
13.2%
0 3304
 
6.4%
9 2172
 
4.2%
6 1501
 
2.9%
5 1331
 
2.6%
- 1248
 
2.4%
4 1170
 
2.3%

지번주소
Text

Distinct6464
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
2024-05-11T15:42:30.300937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length55
Mean length28.969519
Min length14

Characters and Unicode

Total characters242359
Distinct characters523
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5879 ?
Unique (%)70.3%

Sample

1st row서울특별시 서초구 방배동 777-20번지
2nd row서울특별시 서초구 반포동 19-4번지
3rd row서울특별시 서초구 양재동 1-2번지 2층
4th row서울특별시 서초구 서초동 1602-10번지
5th row서울특별시 서초구 양재동 11-19 번지 (지하)
ValueCountFrequency (%)
서초구 8366
18.0%
서울특별시 8365
18.0%
서초동 2466
 
5.3%
1층 2371
 
5.1%
반포동 2351
 
5.1%
지하1층 1347
 
2.9%
방배동 1329
 
2.9%
양재동 1277
 
2.7%
신세계백화점 729
 
1.6%
잠원동 667
 
1.4%
Other values (6230) 17186
37.0%
2024-05-11T15:42:31.098140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44000
18.2%
서 19609
 
8.1%
1 16012
 
6.6%
초 11102
 
4.6%
동 8813
 
3.6%
시 8772
 
3.6%
울 8472
 
3.5%
구 8439
 
3.5%
별 8369
 
3.5%
특 8366
 
3.5%
Other values (513) 100405
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 141047
58.2%
Decimal Number 47002
 
19.4%
Space Separator 44000
 
18.2%
Dash Punctuation 7563
 
3.1%
Uppercase Letter 1149
 
0.5%
Other Punctuation 661
 
0.3%
Open Punctuation 405
 
0.2%
Close Punctuation 404
 
0.2%
Lowercase Letter 86
 
< 0.1%
Math Symbol 35
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 19609
13.9%
초 11102
 
7.9%
동 8813
 
6.2%
시 8772
 
6.2%
울 8472
 
6.0%
구 8439
 
6.0%
별 8369
 
5.9%
특 8366
 
5.9%
지 7624
 
5.4%
번 5521
 
3.9%
Other values (443) 45960
32.6%
Uppercase Letter
ValueCountFrequency (%)
B 361
31.4%
A 224
19.5%
T 218
19.0%
P 40
 
3.5%
C 33
 
2.9%
G 29
 
2.5%
F 28
 
2.4%
L 28
 
2.4%
K 23
 
2.0%
E 21
 
1.8%
Other values (16) 144
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
a 19
22.1%
e 15
17.4%
t 10
11.6%
r 6
 
7.0%
l 6
 
7.0%
i 5
 
5.8%
n 5
 
5.8%
h 4
 
4.7%
f 3
 
3.5%
b 2
 
2.3%
Other values (9) 11
12.8%
Decimal Number
ValueCountFrequency (%)
1 16012
34.1%
3 5456
 
11.6%
2 5026
 
10.7%
0 4102
 
8.7%
5 3131
 
6.7%
9 3098
 
6.6%
4 2919
 
6.2%
7 2824
 
6.0%
6 2404
 
5.1%
8 2030
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 634
95.9%
. 7
 
1.1%
/ 6
 
0.9%
: 5
 
0.8%
? 3
 
0.5%
' 3
 
0.5%
& 2
 
0.3%
@ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
44000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7563
100.0%
Open Punctuation
ValueCountFrequency (%)
( 405
100.0%
Close Punctuation
ValueCountFrequency (%)
) 404
100.0%
Math Symbol
ValueCountFrequency (%)
~ 35
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 141046
58.2%
Common 100071
41.3%
Latin 1240
 
0.5%
Greek 1
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 19609
13.9%
초 11102
 
7.9%
동 8813
 
6.2%
시 8772
 
6.2%
울 8472
 
6.0%
구 8439
 
6.0%
별 8369
 
5.9%
특 8366
 
5.9%
지 7624
 
5.4%
번 5521
 
3.9%
Other values (442) 45959
32.6%
Latin
ValueCountFrequency (%)
B 361
29.1%
A 224
18.1%
T 218
17.6%
P 40
 
3.2%
C 33
 
2.7%
G 29
 
2.3%
F 28
 
2.3%
L 28
 
2.3%
K 23
 
1.9%
E 21
 
1.7%
Other values (35) 235
19.0%
Common
ValueCountFrequency (%)
44000
44.0%
1 16012
 
16.0%
- 7563
 
7.6%
3 5456
 
5.5%
2 5026
 
5.0%
0 4102
 
4.1%
5 3131
 
3.1%
9 3098
 
3.1%
4 2919
 
2.9%
7 2824
 
2.8%
Other values (14) 5940
 
5.9%
Greek
ValueCountFrequency (%)
Ι 1
100.0%
Han
ValueCountFrequency (%)
鮎 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 141046
58.2%
ASCII 101305
41.8%
Number Forms 6
 
< 0.1%
None 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44000
43.4%
1 16012
 
15.8%
- 7563
 
7.5%
3 5456
 
5.4%
2 5026
 
5.0%
0 4102
 
4.0%
5 3131
 
3.1%
9 3098
 
3.1%
4 2919
 
2.9%
7 2824
 
2.8%
Other values (58) 7174
 
7.1%
Hangul
ValueCountFrequency (%)
서 19609
13.9%
초 11102
 
7.9%
동 8813
 
6.2%
시 8772
 
6.2%
울 8472
 
6.0%
구 8439
 
6.0%
별 8369
 
5.9%
특 8366
 
5.9%
지 7624
 
5.4%
번 5521
 
3.9%
Other values (442) 45959
32.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
100.0%
None
ValueCountFrequency (%)
Ι 1
100.0%
CJK
ValueCountFrequency (%)
鮎 1
100.0%

도로명주소
Text

MISSING 

Distinct4224
Distinct (%)75.9%
Missing2798
Missing (%)33.4%
Memory size65.5 KiB
2024-05-11T15:42:31.704290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length56
Mean length35.913614
Min length22

Characters and Unicode

Total characters199967
Distinct characters500
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3858 ?
Unique (%)69.3%

Sample

1st row서울특별시 서초구 서초대로1길 14 (방배동)
2nd row서울특별시 서초구 서초대로 308 (서초동)
3rd row서울특별시 서초구 신반포로 194 (반포동)
4th row서울특별시 서초구 방배중앙로 114 (방배동)
5th row서울특별시 서초구 신반포로 340 (반포동)
ValueCountFrequency (%)
서울특별시 5568
 
14.2%
서초구 5567
 
14.2%
1층 2467
 
6.3%
반포동 1543
 
3.9%
서초동 1413
 
3.6%
지하1층 1317
 
3.4%
신반포로 1169
 
3.0%
176 991
 
2.5%
양재동 834
 
2.1%
방배동 770
 
2.0%
Other values (3210) 17622
44.9%
2024-05-11T15:42:32.457786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33751
 
16.9%
서 13968
 
7.0%
1 10681
 
5.3%
초 8141
 
4.1%
, 7116
 
3.6%
동 6077
 
3.0%
시 5826
 
2.9%
( 5679
 
2.8%
) 5679
 
2.8%
울 5654
 
2.8%
Other values (490) 97395
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117478
58.7%
Space Separator 33751
 
16.9%
Decimal Number 28472
 
14.2%
Other Punctuation 7130
 
3.6%
Open Punctuation 5679
 
2.8%
Close Punctuation 5679
 
2.8%
Uppercase Letter 1046
 
0.5%
Dash Punctuation 626
 
0.3%
Lowercase Letter 82
 
< 0.1%
Math Symbol 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 13968
 
11.9%
초 8141
 
6.9%
동 6077
 
5.2%
시 5826
 
5.0%
울 5654
 
4.8%
구 5634
 
4.8%
별 5571
 
4.7%
특 5570
 
4.7%
로 5497
 
4.7%
층 4655
 
4.0%
Other values (425) 50885
43.3%
Uppercase Letter
ValueCountFrequency (%)
B 260
24.9%
T 250
23.9%
A 234
22.4%
P 39
 
3.7%
C 25
 
2.4%
G 25
 
2.4%
F 24
 
2.3%
K 22
 
2.1%
L 21
 
2.0%
E 20
 
1.9%
Other values (16) 126
12.0%
Lowercase Letter
ValueCountFrequency (%)
a 26
31.7%
e 14
17.1%
t 10
 
12.2%
r 6
 
7.3%
l 6
 
7.3%
n 5
 
6.1%
h 4
 
4.9%
i 3
 
3.7%
u 1
 
1.2%
d 1
 
1.2%
Other values (6) 6
 
7.3%
Decimal Number
ValueCountFrequency (%)
1 10681
37.5%
2 3450
 
12.1%
0 2500
 
8.8%
7 2414
 
8.5%
3 2169
 
7.6%
6 2083
 
7.3%
4 1699
 
6.0%
5 1485
 
5.2%
8 1095
 
3.8%
9 896
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 7116
99.8%
/ 4
 
0.1%
. 4
 
0.1%
? 3
 
< 0.1%
& 2
 
< 0.1%
' 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
33751
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5679
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5679
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 626
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117478
58.7%
Common 81357
40.7%
Latin 1131
 
0.6%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 13968
 
11.9%
초 8141
 
6.9%
동 6077
 
5.2%
시 5826
 
5.0%
울 5654
 
4.8%
구 5634
 
4.8%
별 5571
 
4.7%
특 5570
 
4.7%
로 5497
 
4.7%
층 4655
 
4.0%
Other values (425) 50885
43.3%
Latin
ValueCountFrequency (%)
B 260
23.0%
T 250
22.1%
A 234
20.7%
P 39
 
3.4%
a 26
 
2.3%
C 25
 
2.2%
G 25
 
2.2%
F 24
 
2.1%
K 22
 
1.9%
L 21
 
1.9%
Other values (33) 205
18.1%
Common
ValueCountFrequency (%)
33751
41.5%
1 10681
 
13.1%
, 7116
 
8.7%
( 5679
 
7.0%
) 5679
 
7.0%
2 3450
 
4.2%
0 2500
 
3.1%
7 2414
 
3.0%
3 2169
 
2.7%
6 2083
 
2.6%
Other values (11) 5835
 
7.2%
Greek
ValueCountFrequency (%)
Ι 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117478
58.7%
ASCII 82484
41.2%
Number Forms 4
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33751
40.9%
1 10681
 
12.9%
, 7116
 
8.6%
( 5679
 
6.9%
) 5679
 
6.9%
2 3450
 
4.2%
0 2500
 
3.0%
7 2414
 
2.9%
3 2169
 
2.6%
6 2083
 
2.5%
Other values (52) 6962
 
8.4%
Hangul
ValueCountFrequency (%)
서 13968
 
11.9%
초 8141
 
6.9%
동 6077
 
5.2%
시 5826
 
5.0%
울 5654
 
4.8%
구 5634
 
4.8%
별 5571
 
4.7%
특 5570
 
4.7%
로 5497
 
4.7%
층 4655
 
4.0%
Other values (425) 50885
43.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%
None
ValueCountFrequency (%)
Ι 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct287
Distinct (%)5.2%
Missing2853
Missing (%)34.1%
Infinite0
Infinite (%)0.0%
Mean6635.3127
Minimum6500
Maximum6806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.7 KiB
2024-05-11T15:42:32.667822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6500
5-th percentile6511
Q16546
median6621
Q36723
95-th percentile6784
Maximum6806
Range306
Interquartile range (IQR)177

Descriptive statistics

Standard deviation93.340413
Coefficient of variation (CV)0.014067221
Kurtosis-1.2927398
Mean6635.3127
Median Absolute Deviation (MAD)75
Skewness0.34904063
Sum36580479
Variance8712.4327
MonotonicityNot monotonic
2024-05-11T15:42:32.878193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6546 988
 
11.8%
6774 236
 
2.8%
6545 105
 
1.3%
6511 104
 
1.2%
6500 100
 
1.2%
6797 91
 
1.1%
6771 68
 
0.8%
6634 63
 
0.8%
6611 60
 
0.7%
6655 51
 
0.6%
Other values (277) 3647
43.6%
(Missing) 2853
34.1%
ValueCountFrequency (%)
6500 100
1.2%
6501 6
 
0.1%
6502 22
 
0.3%
6503 15
 
0.2%
6504 4
 
< 0.1%
6505 1
 
< 0.1%
6506 9
 
0.1%
6507 1
 
< 0.1%
6509 13
 
0.2%
6510 11
 
0.1%
ValueCountFrequency (%)
6806 17
 
0.2%
6805 1
 
< 0.1%
6803 5
 
0.1%
6802 38
0.5%
6801 8
 
0.1%
6800 13
 
0.2%
6799 9
 
0.1%
6798 21
 
0.3%
6797 91
1.1%
6794 5
 
0.1%

사업장명
Text

Distinct7240
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
2024-05-11T15:42:33.296121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length7.8700693
Min length1

Characters and Unicode

Total characters65841
Distinct characters1041
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6641 ?
Unique (%)79.4%

Sample

1st row피터팬
2nd row훼미리마트
3rd row한일다방
4th row대호
5th row동호
ValueCountFrequency (%)
gs25 149
 
1.2%
카페 144
 
1.2%
세븐일레븐 110
 
0.9%
주식회사 98
 
0.8%
강남점 94
 
0.8%
cafe 88
 
0.7%
씨유 85
 
0.7%
커피 80
 
0.6%
coffee 66
 
0.5%
양재점 62
 
0.5%
Other values (7854) 11407
92.1%
2024-05-11T15:42:33.895836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4028
 
6.1%
점 2336
 
3.5%
스 2051
 
3.1%
이 1412
 
2.1%
( 1398
 
2.1%
) 1397
 
2.1%
리 1211
 
1.8%
피 1032
 
1.6%
커 916
 
1.4%
서 770
 
1.2%
Other values (1031) 49290
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49867
75.7%
Space Separator 4028
 
6.1%
Lowercase Letter 3862
 
5.9%
Uppercase Letter 3679
 
5.6%
Open Punctuation 1399
 
2.1%
Close Punctuation 1398
 
2.1%
Decimal Number 1321
 
2.0%
Other Punctuation 233
 
0.4%
Dash Punctuation 28
 
< 0.1%
Connector Punctuation 15
 
< 0.1%
Other values (4) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 2336
 
4.7%
스 2051
 
4.1%
이 1412
 
2.8%
리 1211
 
2.4%
피 1032
 
2.1%
커 916
 
1.8%
서 770
 
1.5%
페 734
 
1.5%
카 721
 
1.4%
주 660
 
1.3%
Other values (943) 38024
76.3%
Lowercase Letter
ValueCountFrequency (%)
e 656
17.0%
a 420
10.9%
o 356
 
9.2%
f 282
 
7.3%
i 227
 
5.9%
n 211
 
5.5%
r 205
 
5.3%
t 193
 
5.0%
c 181
 
4.7%
s 176
 
4.6%
Other values (16) 955
24.7%
Uppercase Letter
ValueCountFrequency (%)
C 392
 
10.7%
S 377
 
10.2%
E 327
 
8.9%
G 296
 
8.0%
A 254
 
6.9%
O 227
 
6.2%
F 191
 
5.2%
T 171
 
4.6%
L 144
 
3.9%
N 135
 
3.7%
Other values (16) 1165
31.7%
Other Punctuation
ValueCountFrequency (%)
& 71
30.5%
. 57
24.5%
' 48
20.6%
? 22
 
9.4%
, 19
 
8.2%
! 7
 
3.0%
: 4
 
1.7%
/ 2
 
0.9%
？ 1
 
0.4%
＆ 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 414
31.3%
5 317
24.0%
1 171
12.9%
4 87
 
6.6%
3 83
 
6.3%
0 73
 
5.5%
9 62
 
4.7%
7 51
 
3.9%
6 36
 
2.7%
8 27
 
2.0%
Math Symbol
ValueCountFrequency (%)
+ 2
50.0%
< 1
25.0%
> 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 1398
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1397
99.9%
] 1
 
0.1%
Other Symbol
ValueCountFrequency (%)
㈜ 3
75.0%
℉ 1
 
25.0%
Modifier Symbol
ValueCountFrequency (%)
^ 1
50.0%
` 1
50.0%
Space Separator
ValueCountFrequency (%)
4028
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 15
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49838
75.7%
Common 8429
 
12.8%
Latin 7542
 
11.5%
Han 32
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 2336
 
4.7%
스 2051
 
4.1%
이 1412
 
2.8%
리 1211
 
2.4%
피 1032
 
2.1%
커 916
 
1.8%
서 770
 
1.5%
페 734
 
1.5%
카 721
 
1.4%
주 660
 
1.3%
Other values (917) 37995
76.2%
Latin
ValueCountFrequency (%)
e 656
 
8.7%
a 420
 
5.6%
C 392
 
5.2%
S 377
 
5.0%
o 356
 
4.7%
E 327
 
4.3%
G 296
 
3.9%
f 282
 
3.7%
A 254
 
3.4%
O 227
 
3.0%
Other values (43) 3955
52.4%
Common
ValueCountFrequency (%)
4028
47.8%
( 1398
 
16.6%
) 1397
 
16.6%
2 414
 
4.9%
5 317
 
3.8%
1 171
 
2.0%
4 87
 
1.0%
3 83
 
1.0%
0 73
 
0.9%
& 71
 
0.8%
Other values (24) 390
 
4.6%
Han
ValueCountFrequency (%)
眞 3
 
9.4%
汰 2
 
6.2%
睾 2
 
6.2%
茶 2
 
6.2%
味 1
 
3.1%
月 1
 
3.1%
溫 1
 
3.1%
相 1
 
3.1%
花 1
 
3.1%
玉 1
 
3.1%
Other values (17) 17
53.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49831
75.7%
ASCII 15967
 
24.3%
CJK 30
 
< 0.1%
None 5
 
< 0.1%
Compat Jamo 4
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4028
25.2%
( 1398
 
8.8%
) 1397
 
8.7%
e 656
 
4.1%
a 420
 
2.6%
2 414
 
2.6%
C 392
 
2.5%
S 377
 
2.4%
o 356
 
2.2%
E 327
 
2.0%
Other values (73) 6202
38.8%
Hangul
ValueCountFrequency (%)
점 2336
 
4.7%
스 2051
 
4.1%
이 1412
 
2.8%
리 1211
 
2.4%
피 1032
 
2.1%
커 916
 
1.8%
서 770
 
1.5%
페 734
 
1.5%
카 721
 
1.4%
주 660
 
1.3%
Other values (912) 37988
76.2%
None
ValueCountFrequency (%)
㈜ 3
60.0%
？ 1
 
20.0%
＆ 1
 
20.0%
CJK
ValueCountFrequency (%)
眞 3
 
10.0%
汰 2
 
6.7%
睾 2
 
6.7%
味 1
 
3.3%
月 1
 
3.3%
溫 1
 
3.3%
相 1
 
3.3%
花 1
 
3.3%
玉 1
 
3.3%
咽 1
 
3.3%
Other values (16) 16
53.3%
CJK Compat Ideographs
ValueCountFrequency (%)
茶 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅍ 1
25.0%
ㅋ 1
25.0%
ㅇ 1
25.0%
ㄴ 1
25.0%
Letterlike Symbols
ValueCountFrequency (%)
℉ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정일자
Date

Distinct6702
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
Minimum1999-01-13 00:00:00
Maximum2024-05-09 17:33:09
2024-05-11T15:42:34.084872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:34.269491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
I
5231 
U
3133 
D
 
2

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 5231
62.5%
U 3133
37.4%
D 2
 
< 0.1%

Length

2024-05-11T15:42:34.445955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:34.590036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5231
62.5%
u 3133
37.4%
d 2
 
< 0.1%

데이터갱신일자
Date

Distinct1450
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:42:34.760413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:34.949064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
커피숍
2603 
일반조리판매
1690 
기타 휴게음식점
954 
다방
803 
편의점
742 
Other values (14)
1574 

Length

Max length8
Median length7
Mean length4.2345207
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row다방
2nd row편의점
3rd row다방
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
커피숍 2603
31.1%
일반조리판매 1690
20.2%
기타 휴게음식점 954
 
11.4%
다방 803
 
9.6%
편의점 742
 
8.9%
패스트푸드 462
 
5.5%
과자점 455
 
5.4%
백화점 329
 
3.9%
푸드트럭 198
 
2.4%
아이스크림 55
 
0.7%
Other values (9) 75
 
0.9%

Length

2024-05-11T15:42:35.176078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 2603
27.9%
일반조리판매 1690
18.1%
기타 954
 
10.2%
휴게음식점 954
 
10.2%
다방 803
 
8.6%
편의점 742
 
8.0%
패스트푸드 462
 
5.0%
과자점 455
 
4.9%
백화점 329
 
3.5%
푸드트럭 198
 
2.1%
Other values (10) 130
 
1.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2793
Distinct (%)34.3%
Missing219
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean201135.53
Minimum198341.21
Maximum207858.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.7 KiB
2024-05-11T15:42:35.366335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198341.21
5-th percentile198670.72
Q1200250.45
median200975.31
Q3202183.51
95-th percentile203811.37
Maximum207858.54
Range9517.3306
Interquartile range (IQR)1933.062

Descriptive statistics

Standard deviation1570.587
Coefficient of variation (CV)0.0078086005
Kurtosis-0.43437035
Mean201135.53
Median Absolute Deviation (MAD)996.47535
Skewness0.34941192
Sum1.6386512 × 109
Variance2466743.5
MonotonicityNot monotonic
2024-05-11T15:42:36.044964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200250.447804795 1241
 
14.8%
203392.793460583 240
 
2.9%
200576.608647619 175
 
2.1%
203811.366422118 103
 
1.2%
203204.755637424 93
 
1.1%
199512.055421857 89
 
1.1%
200554.74395758 64
 
0.8%
198791.788015494 44
 
0.5%
201107.634736928 41
 
0.5%
201278.647889967 39
 
0.5%
Other values (2783) 6018
71.9%
(Missing) 219
 
2.6%
ValueCountFrequency (%)
198341.208478761 1
 
< 0.1%
198341.255698142 1
 
< 0.1%
198344.761390706 7
0.1%
198349.158592224 2
 
< 0.1%
198353.821141141 2
 
< 0.1%
198353.824006002 4
< 0.1%
198355.846023337 5
0.1%
198358.536839066 1
 
< 0.1%
198359.032400861 8
0.1%
198360.229504349 1
 
< 0.1%
ValueCountFrequency (%)
207858.539092723 1
 
< 0.1%
207843.274713732 1
 
< 0.1%
207147.911759758 1
 
< 0.1%
206718.158151117 1
 
< 0.1%
206527.143128753 3
< 0.1%
206222.68463863 1
 
< 0.1%
206184.516281334 1
 
< 0.1%
206131.241466 1
 
< 0.1%
206060.42439497 2
< 0.1%
205726.684396697 2
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2793
Distinct (%)34.3%
Missing219
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean443267.05
Minimum437864.71
Maximum446565.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.7 KiB
2024-05-11T15:42:36.318723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437864.71
5-th percentile440136.78
Q1442302.89
median443422.37
Q3444683.22
95-th percentile445320.89
Maximum446565.03
Range8700.3177
Interquartile range (IQR)2380.3312

Descriptive statistics

Standard deviation1600.0651
Coefficient of variation (CV)0.003609709
Kurtosis-0.072491458
Mean443267.05
Median Absolute Deviation (MAD)1260.8528
Skewness-0.61103037
Sum3.6112967 × 109
Variance2560208.2
MonotonicityNot monotonic
2024-05-11T15:42:36.577062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444683.220506107 1241
 
14.8%
440676.379919661 240
 
2.9%
445241.8984183 175
 
2.1%
440070.727589935 103
 
1.2%
440136.781183797 93
 
1.1%
445283.167984819 89
 
1.1%
444811.364826199 64
 
0.8%
444392.672548989 44
 
0.5%
443999.067092566 41
 
0.5%
442099.753091778 39
 
0.5%
Other values (2783) 6018
71.9%
(Missing) 219
 
2.6%
ValueCountFrequency (%)
437864.710924867 3
< 0.1%
437908.032326145 1
 
< 0.1%
437922.839052347 3
< 0.1%
437943.308731913 1
 
< 0.1%
437956.129765365 1
 
< 0.1%
437959.961132488 3
< 0.1%
437962.891874824 1
 
< 0.1%
437968.892025771 2
< 0.1%
437979.542859349 2
< 0.1%
437984.289611067 2
< 0.1%
ValueCountFrequency (%)
446565.028672992 3
 
< 0.1%
446493.163455058 12
0.1%
446331.380046658 3
 
< 0.1%
446314.687402426 5
0.1%
446312.955196265 3
 
< 0.1%
446268.294338007 4
 
< 0.1%
446247.719636035 4
 
< 0.1%
446229.81000994 2
 
< 0.1%
446206.354902748 1
 
< 0.1%
446202.471850496 3
 
< 0.1%

위생업태명
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
커피숍
1875 
<NA>
1838 
일반조리판매
1399 
다방
794 
기타 휴게음식점
559 
Other values (11)
1901 

Length

Max length8
Median length6
Mean length4.0909634
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row다방
2nd row편의점
3rd row다방
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
커피숍 1875
22.4%
<NA> 1838
22.0%
일반조리판매 1399
16.7%
다방 794
9.5%
기타 휴게음식점 559
 
6.7%
편의점 530
 
6.3%
과자점 454
 
5.4%
패스트푸드 407
 
4.9%
백화점 264
 
3.2%
푸드트럭 160
 
1.9%
Other values (6) 86
 
1.0%

Length

2024-05-11T15:42:36.830297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1875
21.0%
na 1838
20.6%
일반조리판매 1399
15.7%
다방 794
8.9%
기타 559
 
6.3%
휴게음식점 559
 
6.3%
편의점 530
 
5.9%
과자점 454
 
5.1%
패스트푸드 407
 
4.6%
백화점 264
 
3.0%
Other values (7) 246
 
2.8%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.3%
Missing5634
Missing (%)67.3%
Infinite0
Infinite (%)0.0%
Mean0.20937042
Minimum0
Maximum93
Zeros2467
Zeros (%)29.5%
Negative0
Negative (%)0.0%
Memory size73.7 KiB
2024-05-11T15:42:37.028835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum93
Range93
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.5644558
Coefficient of variation (CV)12.248415
Kurtosis1229.2417
Mean0.20937042
Median Absolute Deviation (MAD)0
Skewness34.307837
Sum572
Variance6.5764336
MonotonicityNot monotonic
2024-05-11T15:42:37.188116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 2467
29.5%
1 177
 
2.1%
2 69
 
0.8%
3 12
 
0.1%
4 2
 
< 0.1%
5 2
 
< 0.1%
18 1
 
< 0.1%
92 1
 
< 0.1%
93 1
 
< 0.1%
(Missing) 5634
67.3%
ValueCountFrequency (%)
0 2467
29.5%
1 177
 
2.1%
2 69
 
0.8%
3 12
 
0.1%
4 2
 
< 0.1%
5 2
 
< 0.1%
18 1
 
< 0.1%
92 1
 
< 0.1%
93 1
 
< 0.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
92 1
 
< 0.1%
18 1
 
< 0.1%
5 2
 
< 0.1%
4 2
 
< 0.1%
3 12
 
0.1%
2 69
 
0.8%
1 177
 
2.1%
0 2467
29.5%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.4%
Missing5627
Missing (%)67.3%
Infinite0
Infinite (%)0.0%
Mean0.52902519
Minimum0
Maximum94
Zeros2105
Zeros (%)25.2%
Negative0
Negative (%)0.0%
Memory size73.7 KiB
2024-05-11T15:42:37.363110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum94
Range94
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.7962488
Coefficient of variation (CV)5.2856629
Kurtosis906.80887
Mean0.52902519
Median Absolute Deviation (MAD)0
Skewness28.036899
Sum1449
Variance7.8190075
MonotonicityNot monotonic
2024-05-11T15:42:37.534862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 2105
 
25.2%
2 271
 
3.2%
1 228
 
2.7%
3 96
 
1.1%
4 29
 
0.3%
5 5
 
0.1%
6 1
 
< 0.1%
17 1
 
< 0.1%
94 1
 
< 0.1%
93 1
 
< 0.1%
(Missing) 5627
67.3%
ValueCountFrequency (%)
0 2105
25.2%
1 228
 
2.7%
2 271
 
3.2%
3 96
 
1.1%
4 29
 
0.3%
5 5
 
0.1%
6 1
 
< 0.1%
17 1
 
< 0.1%
40 1
 
< 0.1%
93 1
 
< 0.1%
ValueCountFrequency (%)
94 1
 
< 0.1%
93 1
 
< 0.1%
40 1
 
< 0.1%
17 1
 
< 0.1%
6 1
 
< 0.1%
5 5
 
0.1%
4 29
 
0.3%
3 96
 
1.1%
2 271
3.2%
1 228
2.7%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
6705 
기타
 
662
주택가주변
 
591
아파트지역
 
240
유흥업소밀집지역
 
162
Other values (2)
 
6

Length

Max length8
Median length4
Mean length4.0213961
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row기타
2nd row기타
3rd row주택가주변
4th row유흥업소밀집지역
5th row주택가주변

Common Values

ValueCountFrequency (%)
<NA> 6705
80.1%
기타 662
 
7.9%
주택가주변 591
 
7.1%
아파트지역 240
 
2.9%
유흥업소밀집지역 162
 
1.9%
학교정화(상대) 5
 
0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-05-11T15:42:37.725903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:37.913152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6705
80.1%
기타 662
 
7.9%
주택가주변 591
 
7.1%
아파트지역 240
 
2.9%
유흥업소밀집지역 162
 
1.9%
학교정화(상대 5
 
0.1%
학교정화(절대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
6708 
기타
772 
자율
 
522
지도
 
220
을
 
84
Other values (3)
 
60

Length

Max length4
Median length4
Mean length3.5871384
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row자율
2nd row기타
3rd row지도
4th row자율
5th row지도

Common Values

ValueCountFrequency (%)
<NA> 6708
80.2%
기타 772
 
9.2%
자율 522
 
6.2%
지도 220
 
2.6%
을 84
 
1.0%
갑 54
 
0.6%
우수 5
 
0.1%
관리 1
 
< 0.1%

Length

2024-05-11T15:42:38.120080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:38.324933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6708
80.2%
기타 772
 
9.2%
자율 522
 
6.2%
지도 220
 
2.6%
을 84
 
1.0%
갑 54
 
0.6%
우수 5
 
0.1%
관리 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
6007 
상수도전용
2352 
상수도(음용)지하수(주방용)겸용
 
5
지하수전용
 
2

Length

Max length17
Median length4
Mean length4.2891465
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6007
71.8%
상수도전용 2352
 
28.1%
상수도(음용)지하수(주방용)겸용 5
 
0.1%
지하수전용 2
 
< 0.1%

Length

2024-05-11T15:42:38.573941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:38.773105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6007
71.8%
상수도전용 2352
 
28.1%
상수도(음용)지하수(주방용)겸용 5
 
0.1%
지하수전용 2
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
7944 
0
 
422

Length

Max length4
Median length4
Mean length3.8486732
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> 7944
95.0%
0 422
 
5.0%

Length

2024-05-11T15:42:38.949037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:39.116795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7944
95.0%
0 422
 
5.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
7940 
0
 
426

Length

Max length4
Median length4
Mean length3.8472388
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> 7940
94.9%
0 426
 
5.1%

Length

2024-05-11T15:42:39.277450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:39.427513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7940
94.9%
0 426
 
5.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
7940 
0
 
426

Length

Max length4
Median length4
Mean length3.8472388
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> 7940
94.9%
0 426
 
5.1%

Length

2024-05-11T15:42:39.585457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:39.745187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7940
94.9%
0 426
 
5.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
7940 
0
 
426

Length

Max length4
Median length4
Mean length3.8472388
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> 7940
94.9%
0 426
 
5.1%

Length

2024-05-11T15:42:39.914836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:40.062715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7940
94.9%
0 426
 
5.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
7940 
0
 
426

Length

Max length4
Median length4
Mean length3.8472388
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> 7940
94.9%
0 426
 
5.1%

Length

2024-05-11T15:42:40.219974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:40.395815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7940
94.9%
0 426
 
5.1%

건물소유구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing8365
Missing (%)> 99.9%
Memory size65.5 KiB
2024-05-11T15:42:40.506789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row자가
ValueCountFrequency (%)
자가 1
100.0%
2024-05-11T15:42:40.844203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 1
50.0%
가 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 1
50.0%
가 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 1
50.0%
가 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 1
50.0%
가 1
50.0%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
7940 
0
 
426

Length

Max length4
Median length4
Mean length3.8472388
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> 7940
94.9%
0 426
 
5.1%

Length

2024-05-11T15:42:41.087866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:41.250222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7940
94.9%
0 426
 
5.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.5 KiB
<NA>
7940 
0
 
426

Length

Max length4
Median length4
Mean length3.8472388
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> 7940
94.9%
0 426
 
5.1%

Length

2024-05-11T15:42:41.398026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:41.544185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7940
94.9%
0 426
 
5.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1838
Missing (%)22.0%
Memory size16.5 KiB
False
6093 
True
 
435
(Missing)
1838 
ValueCountFrequency (%)
False 6093
72.8%
True 435
 
5.2%
(Missing) 1838
 
22.0%
2024-05-11T15:42:41.655979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct2857
Distinct (%)43.8%
Missing1838
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean46.997978
Minimum0
Maximum865.6
Zeros133
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size73.7 KiB
2024-05-11T15:42:41.802329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q110
median27.855
Q359.8
95-th percentile165
Maximum865.6
Range865.6
Interquartile range (IQR)49.8

Descriptive statistics

Standard deviation59.213852
Coefficient of variation (CV)1.2599234
Kurtosis16.947604
Mean46.997978
Median Absolute Deviation (MAD)20.075
Skewness3.177707
Sum306802.8
Variance3506.2802
MonotonicityNot monotonic
2024-05-11T15:42:41.982055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 259
 
3.1%
10.0 245
 
2.9%
6.6 188
 
2.2%
0.0 133
 
1.6%
9.9 110
 
1.3%
33.0 95
 
1.1%
6.0 89
 
1.1%
9.0 67
 
0.8%
3.0 63
 
0.8%
16.5 59
 
0.7%
Other values (2847) 5220
62.4%
(Missing) 1838
 
22.0%
ValueCountFrequency (%)
0.0 133
1.6%
0.09 1
 
< 0.1%
0.45 1
 
< 0.1%
0.63 3
 
< 0.1%
0.9 1
 
< 0.1%
0.94 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 4
 
< 0.1%
1.2 1
 
< 0.1%
1.21 1
 
< 0.1%
ValueCountFrequency (%)
865.6 1
< 0.1%
579.3 1
< 0.1%
577.5 1
< 0.1%
520.61 1
< 0.1%
516.7 1
< 0.1%
508.35 1
< 0.1%
491.04 1
< 0.1%
490.76 1
< 0.1%
490.47 1
< 0.1%
473.76 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8366
Missing (%)100.0%
Memory size73.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8366
Missing (%)100.0%
Memory size73.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8366
Missing (%)100.0%
Memory size73.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032100003210000-104-1904-0114319040808<NA>3폐업2폐업19940705<NA><NA><NA>0205935096220.1137829서울특별시 서초구 방배동 777-20번지<NA><NA>피터팬2001-09-29 00:00:00I2018-08-31 23:59:59.0다방198757.499773443418.507775다방00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N220.1<NA><NA><NA>
132100003210000-104-1953-0057219530827<NA>3폐업2폐업19970902<NA><NA><NA>02 53561459.72137713서울특별시 서초구 반포동 19-4번지<NA><NA>훼미리마트2001-09-29 00:00:00I2018-08-31 23:59:59.0편의점200554.743958444811.364826편의점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N9.72<NA><NA><NA>
232100003210000-104-1973-0153419730714<NA>3폐업2폐업20090316<NA><NA><NA>020572053662.72137886서울특별시 서초구 양재동 1-2번지 2층<NA><NA>한일다방2004-04-09 00:00:00I2018-08-31 23:59:59.0다방203275.813706442490.506626다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N62.72<NA><NA><NA>
332100003210000-104-1976-0117219761009<NA>3폐업2폐업20071123<NA><NA><NA>02 5863394181.83137953서울특별시 서초구 서초동 1602-10번지<NA><NA>대호2005-03-02 00:00:00I2018-08-31 23:59:59.0다방201330.348734442549.663586다방02유흥업소밀집지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N181.83<NA><NA><NA>
432100003210000-104-1976-0151919760302<NA>3폐업2폐업20040504<NA><NA><NA>0205787232106.43137887서울특별시 서초구 양재동 11-19 번지 (지하)<NA><NA>동호2004-05-04 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N106.43<NA><NA><NA>
532100003210000-104-1977-0099519770425<NA>3폐업2폐업20091123<NA><NA><NA>02 582548762.6137818서울특별시 서초구 방배동 440-33번지<NA><NA>삼성2007-10-29 12:52:46I2018-08-31 23:59:59.0다방198361.128213442140.193111다방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N62.6<NA><NA><NA>
632100003210000-104-1977-0113419771104<NA>3폐업2폐업20010329<NA><NA><NA>02 5879739115.04137881서울특별시 서초구 서초동 1673-1번지 지하1층<NA><NA>민트2001-03-29 00:00:00I2018-08-31 23:59:59.0다방201229.105262443500.998342다방02기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N115.04<NA><NA><NA>
732100003210000-104-1977-0131819770512<NA>3폐업2폐업19991118<NA><NA><NA>02 5475151165.24137809서울특별시 서초구 반포동 723-14번지<NA><NA>산2001-09-29 00:00:00I2018-08-31 23:59:59.0다방201903.684337445089.231098다방02주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N165.24<NA><NA><NA>
832100003210000-104-1978-0094819781213<NA>3폐업2폐업20091211<NA><NA><NA>020599202247.35137830서울특별시 서초구 방배동 796-1번지<NA><NA>삼호다방2001-09-29 00:00:00I2018-08-31 23:59:59.0다방199054.857908443527.101951다방03유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N47.35<NA><NA><NA>
932100003210000-104-1978-0109619780412<NA>3폐업2폐업19950620<NA><NA><NA>02 5917371490.76137800서울특별시 서초구 반포동 9-3번지<NA><NA>길목2001-09-29 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방16기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N490.76<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
835632100003210000-104-2024-001692024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0137-040서울특별시 서초구 반포동 115-5 잠수교 남북단 및 반포한강공원 일원서울특별시 서초구 신반포로11길 40, 잠수교 남북단 및 반포한강공원 일원 (반포동)6500PASTEAK(파스테이크)2024-05-01 14:37:14I2023-12-05 00:03:00.0푸드트럭199512.055422445283.167985<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
835732100003210000-104-2024-001702024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.0137-713서울특별시 서초구 반포동 19-3 신세계백화점 강남점 지하1층 식품관서울특별시 서초구 신반포로 176, 신세계백화점 강남점 지하1층 식품관 (반포동)6546마담잔기지떡2024-05-01 11:28:11I2023-12-05 00:03:00.0백화점200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
835832100003210000-104-2024-001712024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.0137-040서울특별시 서초구 반포동 115-5 한강공원서울특별시 서초구 신반포로11길 40, 한강공원 (반포동)6500별꽃카페2024-05-02 13:08:01I2023-12-05 00:04:00.0푸드트럭199512.055422445283.167985<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
835932100003210000-104-2024-001722024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>110.38137-852서울특별시 서초구 방배동 1459 지하1층서울특별시 서초구 서초대로1길 14, 지하1층 (방배동)6567다정커피숍2024-05-02 16:58:15I2023-12-05 00:04:00.0커피숍198449.316312442813.105573<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
836032100003210000-104-2024-001732024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-713서울특별시 서초구 반포동 19-3 신세계백화점 강남점 지하1층서울특별시 서초구 신반포로 176, 신세계백화점 강남점 지하1층 (반포동)6546(주)정성2024-05-03 10:44:29I2023-12-05 00:05:00.0편의점200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
836132100003210000-104-2024-001742024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-960서울특별시 서초구 반포동 19-3 센트럴시티서울특별시 서초구 신반포로 176, 신세계백화점 지하1층 (반포동)6546주식회사 신이안루2024-05-03 16:19:55I2023-12-05 00:05:00.0일반조리판매200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
836232100003210000-104-2024-001752024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>49.6137-906서울특별시 서초구 잠원동 44-20 1층 101호서울특별시 서초구 신반포로43길 23-6, 1층 101호 (잠원동)6529카페422024-05-07 10:35:28I2023-12-05 00:09:00.0커피숍201458.834922445445.532074<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
836332100003210000-104-2024-001762024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3137-800서울특별시 서초구 반포동 2-8 신반포상가 1층 158호서울특별시 서초구 신반포로15길 29, 신반포상가 1층 158호 (반포동)6503이마트24 신반포점2024-05-07 15:15:04I2023-12-05 00:09:00.0편의점199448.513022444800.550773<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
836432100003210000-104-2024-001772024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.4137-897서울특별시 서초구 양재동 331 1층서울특별시 서초구 동산로2길 16, 1층 (양재동)6787컴포즈커피 양재시민의숲 에브리데이점2024-05-09 09:38:18I2023-12-04 23:01:00.0커피숍203630.238294440753.038269<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
836532100003210000-104-2024-001782024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.0137-865서울특별시 서초구 서초동 1442-19 1층 102-1호서울특별시 서초구 남부순환로339길 47-1, 1층 102-1호 (서초동)6725까페오페라2024-05-09 10:30:45I2023-12-04 23:01:00.0커피숍201849.696349442517.589382<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>