Overview

Dataset statistics

Number of variables44
Number of observations3885
Missing cells40972
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory375.0 B

Variable types

Categorical19
Text7
DateTime4
Unsupported6
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
Author은평구
URLhttps://data.seoul.go.kr/dataList/OA-18688/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
전통업소주된음식 has constant value ""Constant
등급구분명 is highly imbalanced (59.5%)Imbalance
총인원 is highly imbalanced (68.9%)Imbalance
본사종업원수 is highly imbalanced (68.8%)Imbalance
공장사무직종업원수 is highly imbalanced (68.8%)Imbalance
공장판매직종업원수 is highly imbalanced (68.8%)Imbalance
공장생산직종업원수 is highly imbalanced (68.8%)Imbalance
보증액 is highly imbalanced (68.8%)Imbalance
월세액 is highly imbalanced (68.8%)Imbalance
다중이용업소여부 is highly imbalanced (90.9%)Imbalance
전통업소지정번호 is highly imbalanced (94.3%)Imbalance
인허가취소일자 has 3885 (100.0%) missing valuesMissing
폐업일자 has 1299 (33.4%) missing valuesMissing
휴업시작일자 has 3885 (100.0%) missing valuesMissing
휴업종료일자 has 3885 (100.0%) missing valuesMissing
재개업일자 has 3885 (100.0%) missing valuesMissing
전화번호 has 2465 (63.4%) missing valuesMissing
도로명주소 has 971 (25.0%) missing valuesMissing
도로명우편번호 has 981 (25.3%) missing valuesMissing
좌표정보(X) has 140 (3.6%) missing valuesMissing
좌표정보(Y) has 140 (3.6%) missing valuesMissing
남성종사자수 has 2947 (75.9%) missing valuesMissing
여성종사자수 has 2890 (74.4%) missing valuesMissing
건물소유구분명 has 3885 (100.0%) missing valuesMissing
다중이용업소여부 has 959 (24.7%) missing valuesMissing
시설총규모 has 959 (24.7%) missing valuesMissing
전통업소주된음식 has 3884 (> 99.9%) missing valuesMissing
홈페이지 has 3885 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 28.78603602)Skewed
여성종사자수 is highly skewed (γ1 = 26.37867088)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
건물소유구분명 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
남성종사자수 has 724 (18.6%) zerosZeros
여성종사자수 has 609 (15.7%) zerosZeros

Reproduction

Analysis started2024-05-11 09:38:36.181980
Analysis finished2024-05-11 09:38:40.383805
Duration4.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
3110000
3885 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3110000
2nd row3110000
3rd row3110000
4th row3110000
5th row3110000

Common Values

ValueCountFrequency (%)
3110000 3885
100.0%

Length

2024-05-11T09:38:40.674236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:40.968031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3110000 3885
100.0%

관리번호
Text

UNIQUE 

Distinct3885
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
2024-05-11T09:38:41.455891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters85470
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

Unique3885 ?
Unique (%)100.0%

Sample

1st row3110000-104-1964-04727
2nd row3110000-104-1969-04870
3rd row3110000-104-1969-04973
4th row3110000-104-1970-04872
5th row3110000-104-1970-04938
ValueCountFrequency (%)
3110000-104-1964-04727 1
 
< 0.1%
3110000-104-2018-00076 1
 
< 0.1%
3110000-104-2018-00048 1
 
< 0.1%
3110000-104-2018-00061 1
 
< 0.1%
3110000-104-2018-00049 1
 
< 0.1%
3110000-104-2018-00050 1
 
< 0.1%
3110000-104-2018-00051 1
 
< 0.1%
3110000-104-2018-00052 1
 
< 0.1%
3110000-104-2018-00053 1
 
< 0.1%
3110000-104-2018-00054 1
 
< 0.1%
Other values (3875) 3875
99.7%
2024-05-11T09:38:42.295024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33606
39.3%
1 16714
19.6%
- 11655
 
13.6%
2 5687
 
6.7%
4 5331
 
6.2%
3 5156
 
6.0%
9 2233
 
2.6%
6 1301
 
1.5%
7 1289
 
1.5%
8 1268
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73815
86.4%
Dash Punctuation 11655
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33606
45.5%
1 16714
22.6%
2 5687
 
7.7%
4 5331
 
7.2%
3 5156
 
7.0%
9 2233
 
3.0%
6 1301
 
1.8%
7 1289
 
1.7%
8 1268
 
1.7%
5 1230
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 11655
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85470
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33606
39.3%
1 16714
19.6%
- 11655
 
13.6%
2 5687
 
6.7%
4 5331
 
6.2%
3 5156
 
6.0%
9 2233
 
2.6%
6 1301
 
1.5%
7 1289
 
1.5%
8 1268
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33606
39.3%
1 16714
19.6%
- 11655
 
13.6%
2 5687
 
6.7%
4 5331
 
6.2%
3 5156
 
6.0%
9 2233
 
2.6%
6 1301
 
1.5%
7 1289
 
1.5%
8 1268
 
1.5%

인허가일자
Date

Distinct2760
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
Minimum1964-04-02 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T09:38:42.714367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:38:43.169427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3885
Missing (%)100.0%
Memory size34.3 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
3
2586 
1
1299 

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 2586
66.6%
1 1299
33.4%

Length

2024-05-11T09:38:43.619312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:43.938635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2586
66.6%
1 1299
33.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
폐업
2586 
영업/정상
1299 

Length

Max length5
Median length2
Mean length3.0030888
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2586
66.6%
영업/정상 1299
33.4%

Length

2024-05-11T09:38:44.315753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:44.586481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2586
66.6%
영업/정상 1299
33.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
2
2586 
1
1299 

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 2586
66.6%
1 1299
33.4%

Length

2024-05-11T09:38:44.864216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:45.283546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2586
66.6%
1 1299
33.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
폐업
2586 
영업
1299 

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 2586
66.6%
영업 1299
33.4%

Length

2024-05-11T09:38:45.585525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:38:45.887898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2586
66.6%
영업 1299
33.4%

폐업일자
Date

MISSING 

Distinct1942
Distinct (%)75.1%
Missing1299
Missing (%)33.4%
Memory size30.5 KiB
Minimum1993-09-23 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T09:38:46.256700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:38:46.739968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3885
Missing (%)100.0%
Memory size34.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3885
Missing (%)100.0%
Memory size34.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3885
Missing (%)100.0%
Memory size34.3 KiB

전화번호
Text

MISSING 

Distinct1194
Distinct (%)84.1%
Missing2465
Missing (%)63.4%
Memory size30.5 KiB
2024-05-11T09:38:47.276793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.6929577
Min length2

Characters and Unicode

Total characters13764
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

Unique1141 ?
Unique (%)80.4%

Sample

1st row02 3538357
2nd row0203556406
3rd row02 3550803
4th row0203555073
5th row02 3728263
ValueCountFrequency (%)
02 1105
41.3%
070 24
 
0.9%
355 19
 
0.7%
353 17
 
0.6%
352 16
 
0.6%
356 15
 
0.6%
388 13
 
0.5%
031 12
 
0.4%
385 11
 
0.4%
357 11
 
0.4%
Other values (1234) 1434
53.6%
2024-05-11T09:38:48.893138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2514
18.3%
2 2114
15.4%
3 1916
13.9%
1579
11.5%
5 1190
8.6%
8 1135
8.2%
7 791
 
5.7%
4 667
 
4.8%
1 633
 
4.6%
6 624
 
4.5%
Other values (2) 601
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12182
88.5%
Space Separator 1579
 
11.5%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2514
20.6%
2 2114
17.4%
3 1916
15.7%
5 1190
9.8%
8 1135
9.3%
7 791
 
6.5%
4 667
 
5.5%
1 633
 
5.2%
6 624
 
5.1%
9 598
 
4.9%
Space Separator
ValueCountFrequency (%)
1579
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2514
18.3%
2 2114
15.4%
3 1916
13.9%
1579
11.5%
5 1190
8.6%
8 1135
8.2%
7 791
 
5.7%
4 667
 
4.8%
1 633
 
4.6%
6 624
 
4.5%
Other values (2) 601
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2514
18.3%
2 2114
15.4%
3 1916
13.9%
1579
11.5%
5 1190
8.6%
8 1135
8.2%
7 791
 
5.7%
4 667
 
4.8%
1 633
 
4.6%
6 624
 
4.5%
Other values (2) 601
 
4.4%

소재지면적
Real number (ℝ)

Distinct1859
Distinct (%)48.1%
Missing23
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean39.736515
Minimum0
Maximum864.18
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size34.3 KiB
2024-05-11T09:38:49.357105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q114.18
median27.26
Q348.51
95-th percentile111.7575
Maximum864.18
Range864.18
Interquartile range (IQR)34.33

Descriptive statistics

Standard deviation47.949971
Coefficient of variation (CV)1.206698
Kurtosis42.526566
Mean39.736515
Median Absolute Deviation (MAD)15.665
Skewness4.796562
Sum153462.42
Variance2299.1998
MonotonicityNot monotonic
2024-05-11T09:38:49.856027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 261
 
6.7%
6.6 88
 
2.3%
30.0 78
 
2.0%
33.0 74
 
1.9%
10.0 62
 
1.6%
15.0 41
 
1.1%
3.0 39
 
1.0%
9.9 37
 
1.0%
20.0 37
 
1.0%
26.0 33
 
0.8%
Other values (1849) 3112
80.1%
ValueCountFrequency (%)
0.0 3
0.1%
0.13 1
 
< 0.1%
0.22 1
 
< 0.1%
0.25 2
0.1%
0.32 1
 
< 0.1%
0.42 1
 
< 0.1%
0.58 1
 
< 0.1%
0.63 1
 
< 0.1%
0.7 1
 
< 0.1%
0.72 1
 
< 0.1%
ValueCountFrequency (%)
864.18 1
< 0.1%
568.62 1
< 0.1%
489.41 1
< 0.1%
451.74 1
< 0.1%
447.42 1
< 0.1%
427.73 1
< 0.1%
415.79 1
< 0.1%
405.49 1
< 0.1%
399.53 1
< 0.1%
396.0 1
< 0.1%

소재지우편번호
Text

Distinct283
Distinct (%)7.3%
Missing2
Missing (%)0.1%
Memory size30.5 KiB
2024-05-11T09:38:50.992275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1738347
Min length6

Characters and Unicode

Total characters23973
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

Unique51 ?
Unique (%)1.3%

Sample

1st row122845
2nd row122907
3rd row122842
4th row122906
5th row122878
ValueCountFrequency (%)
122200 325
 
8.4%
122837 189
 
4.9%
122-200 101
 
2.6%
122842 98
 
2.5%
122959 80
 
2.1%
122819 75
 
1.9%
122907 64
 
1.6%
122814 61
 
1.6%
122900 61
 
1.6%
122906 58
 
1.5%
Other values (273) 2771
71.4%
2024-05-11T09:38:52.480284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 9007
37.6%
1 4737
19.8%
8 2762
 
11.5%
0 1981
 
8.3%
9 1819
 
7.6%
3 839
 
3.5%
- 675
 
2.8%
7 623
 
2.6%
5 604
 
2.5%
4 588
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23298
97.2%
Dash Punctuation 675
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 9007
38.7%
1 4737
20.3%
8 2762
 
11.9%
0 1981
 
8.5%
9 1819
 
7.8%
3 839
 
3.6%
7 623
 
2.7%
5 604
 
2.6%
4 588
 
2.5%
6 338
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 675
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23973
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 9007
37.6%
1 4737
19.8%
8 2762
 
11.5%
0 1981
 
8.3%
9 1819
 
7.6%
3 839
 
3.5%
- 675
 
2.8%
7 623
 
2.6%
5 604
 
2.5%
4 588
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23973
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 9007
37.6%
1 4737
19.8%
8 2762
 
11.5%
0 1981
 
8.3%
9 1819
 
7.6%
3 839
 
3.5%
- 675
 
2.8%
7 623
 
2.6%
5 604
 
2.5%
4 588
 
2.5%

지번주소
Text

Distinct3504
Distinct (%)90.2%
Missing2
Missing (%)0.1%
Memory size30.5 KiB
2024-05-11T09:38:53.350833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length49
Mean length26.334535
Min length16

Characters and Unicode

Total characters102257
Distinct characters384
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3223 ?
Unique (%)83.0%

Sample

1st row서울특별시 은평구 대조동 224-24번지
2nd row서울특별시 은평구 응암동 87-10번지 (지하1층)
3rd row서울특별시 은평구 대조동 185-5번지 (지하1층)
4th row서울특별시 은평구 응암동 97-1번지 (지상2층)
5th row서울특별시 은평구 수색동 368-1번지 (지하1층)
ValueCountFrequency (%)
서울특별시 3883
19.5%
은평구 3880
19.5%
1층 1188
 
6.0%
응암동 670
 
3.4%
갈현동 572
 
2.9%
대조동 463
 
2.3%
진관동 428
 
2.2%
불광동 413
 
2.1%
역촌동 366
 
1.8%
신사동 286
 
1.4%
Other values (3570) 7747
38.9%
2024-05-11T09:38:54.739894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18721
18.3%
1 5905
 
5.8%
동 4182
 
4.1%
은 4149
 
4.1%
평 4146
 
4.1%
구 4146
 
4.1%
서 3946
 
3.9%
울 3935
 
3.8%
시 3911
 
3.8%
특 3883
 
3.8%
Other values (374) 45333
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58619
57.3%
Decimal Number 20277
 
19.8%
Space Separator 18721
 
18.3%
Dash Punctuation 3279
 
3.2%
Open Punctuation 401
 
0.4%
Close Punctuation 401
 
0.4%
Uppercase Letter 360
 
0.4%
Other Punctuation 172
 
0.2%
Lowercase Letter 16
 
< 0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4182
 
7.1%
은 4149
 
7.1%
평 4146
 
7.1%
구 4146
 
7.1%
서 3946
 
6.7%
울 3935
 
6.7%
시 3911
 
6.7%
특 3883
 
6.6%
별 3883
 
6.6%
지 3021
 
5.2%
Other values (323) 19417
33.1%
Uppercase Letter
ValueCountFrequency (%)
B 75
20.8%
C 66
18.3%
A 50
13.9%
D 38
10.6%
M 32
8.9%
N 25
 
6.9%
T 23
 
6.4%
S 10
 
2.8%
E 7
 
1.9%
P 6
 
1.7%
Other values (13) 28
 
7.8%
Decimal Number
ValueCountFrequency (%)
1 5905
29.1%
2 2765
13.6%
3 1957
 
9.7%
0 1854
 
9.1%
4 1814
 
8.9%
5 1431
 
7.1%
9 1240
 
6.1%
6 1127
 
5.6%
8 1097
 
5.4%
7 1087
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
e 6
37.5%
o 3
18.8%
c 1
 
6.2%
a 1
 
6.2%
u 1
 
6.2%
s 1
 
6.2%
t 1
 
6.2%
r 1
 
6.2%
y 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 167
97.1%
@ 3
 
1.7%
/ 1
 
0.6%
. 1
 
0.6%
Space Separator
ValueCountFrequency (%)
18721
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3279
100.0%
Open Punctuation
ValueCountFrequency (%)
( 401
100.0%
Close Punctuation
ValueCountFrequency (%)
) 401
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58619
57.3%
Common 43262
42.3%
Latin 376
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4182
 
7.1%
은 4149
 
7.1%
평 4146
 
7.1%
구 4146
 
7.1%
서 3946
 
6.7%
울 3935
 
6.7%
시 3911
 
6.7%
특 3883
 
6.6%
별 3883
 
6.6%
지 3021
 
5.2%
Other values (323) 19417
33.1%
Latin
ValueCountFrequency (%)
B 75
19.9%
C 66
17.6%
A 50
13.3%
D 38
10.1%
M 32
8.5%
N 25
 
6.6%
T 23
 
6.1%
S 10
 
2.7%
E 7
 
1.9%
e 6
 
1.6%
Other values (22) 44
11.7%
Common
ValueCountFrequency (%)
18721
43.3%
1 5905
 
13.6%
- 3279
 
7.6%
2 2765
 
6.4%
3 1957
 
4.5%
0 1854
 
4.3%
4 1814
 
4.2%
5 1431
 
3.3%
9 1240
 
2.9%
6 1127
 
2.6%
Other values (9) 3169
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58619
57.3%
ASCII 43638
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18721
42.9%
1 5905
 
13.5%
- 3279
 
7.5%
2 2765
 
6.3%
3 1957
 
4.5%
0 1854
 
4.2%
4 1814
 
4.2%
5 1431
 
3.3%
9 1240
 
2.8%
6 1127
 
2.6%
Other values (41) 3545
 
8.1%
Hangul
ValueCountFrequency (%)
동 4182
 
7.1%
은 4149
 
7.1%
평 4146
 
7.1%
구 4146
 
7.1%
서 3946
 
6.7%
울 3935
 
6.7%
시 3911
 
6.7%
특 3883
 
6.6%
별 3883
 
6.6%
지 3021
 
5.2%
Other values (323) 19417
33.1%

도로명주소
Text

MISSING 

Distinct2621
Distinct (%)89.9%
Missing971
Missing (%)25.0%
Memory size30.5 KiB
2024-05-11T09:38:55.419259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length58
Mean length33.037406
Min length21

Characters and Unicode

Total characters96271
Distinct characters383
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2402 ?
Unique (%)82.4%

Sample

1st row서울특별시 은평구 은평로10길 2 (응암동, 지하1층)
2nd row서울특별시 은평구 응암로 185, 지하1층 (응암동)
3rd row서울특별시 은평구 응암로 204, 지하1층 (응암동)
4th row서울특별시 은평구 은평로 195, 은평구청 (녹번동)
5th row서울특별시 은평구 은평로 242, 지하1층 (응암동)
ValueCountFrequency (%)
서울특별시 2914
 
14.9%
은평구 2911
 
14.9%
1층 1766
 
9.0%
응암동 470
 
2.4%
갈현동 404
 
2.1%
진관동 365
 
1.9%
통일로 323
 
1.7%
역촌동 287
 
1.5%
대조동 283
 
1.4%
불광동 282
 
1.4%
Other values (2031) 9530
48.8%
2024-05-11T09:38:56.724710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16626
 
17.3%
1 5846
 
6.1%
서 3641
 
3.8%
은 3496
 
3.6%
평 3492
 
3.6%
, 3362
 
3.5%
동 3273
 
3.4%
구 3126
 
3.2%
) 3001
 
3.1%
( 3001
 
3.1%
Other values (373) 47407
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53485
55.6%
Space Separator 16626
 
17.3%
Decimal Number 15781
 
16.4%
Other Punctuation 3366
 
3.5%
Close Punctuation 3001
 
3.1%
Open Punctuation 3001
 
3.1%
Dash Punctuation 602
 
0.6%
Uppercase Letter 378
 
0.4%
Math Symbol 16
 
< 0.1%
Lowercase Letter 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 3641
 
6.8%
은 3496
 
6.5%
평 3492
 
6.5%
동 3273
 
6.1%
구 3126
 
5.8%
울 2956
 
5.5%
시 2944
 
5.5%
별 2914
 
5.4%
특 2914
 
5.4%
로 2864
 
5.4%
Other values (323) 21865
40.9%
Uppercase Letter
ValueCountFrequency (%)
B 98
25.9%
C 57
15.1%
A 47
12.4%
D 34
 
9.0%
M 32
 
8.5%
N 25
 
6.6%
E 21
 
5.6%
T 19
 
5.0%
L 7
 
1.9%
S 7
 
1.9%
Other values (13) 31
 
8.2%
Decimal Number
ValueCountFrequency (%)
1 5846
37.0%
2 2225
 
14.1%
0 1600
 
10.1%
3 1248
 
7.9%
4 975
 
6.2%
7 908
 
5.8%
5 850
 
5.4%
9 730
 
4.6%
6 718
 
4.5%
8 681
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 6
40.0%
o 2
 
13.3%
t 1
 
6.7%
c 1
 
6.7%
s 1
 
6.7%
r 1
 
6.7%
y 1
 
6.7%
u 1
 
6.7%
a 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 3362
99.9%
. 3
 
0.1%
@ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
16626
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3001
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3001
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 602
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53485
55.6%
Common 42393
44.0%
Latin 393
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 3641
 
6.8%
은 3496
 
6.5%
평 3492
 
6.5%
동 3273
 
6.1%
구 3126
 
5.8%
울 2956
 
5.5%
시 2944
 
5.5%
별 2914
 
5.4%
특 2914
 
5.4%
로 2864
 
5.4%
Other values (323) 21865
40.9%
Latin
ValueCountFrequency (%)
B 98
24.9%
C 57
14.5%
A 47
12.0%
D 34
 
8.7%
M 32
 
8.1%
N 25
 
6.4%
E 21
 
5.3%
T 19
 
4.8%
L 7
 
1.8%
S 7
 
1.8%
Other values (22) 46
11.7%
Common
ValueCountFrequency (%)
16626
39.2%
1 5846
 
13.8%
, 3362
 
7.9%
) 3001
 
7.1%
( 3001
 
7.1%
2 2225
 
5.2%
0 1600
 
3.8%
3 1248
 
2.9%
4 975
 
2.3%
7 908
 
2.1%
Other values (8) 3601
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53485
55.6%
ASCII 42786
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16626
38.9%
1 5846
 
13.7%
, 3362
 
7.9%
) 3001
 
7.0%
( 3001
 
7.0%
2 2225
 
5.2%
0 1600
 
3.7%
3 1248
 
2.9%
4 975
 
2.3%
7 908
 
2.1%
Other values (40) 3994
 
9.3%
Hangul
ValueCountFrequency (%)
서 3641
 
6.8%
은 3496
 
6.5%
평 3492
 
6.5%
동 3273
 
6.1%
구 3126
 
5.8%
울 2956
 
5.5%
시 2944
 
5.5%
별 2914
 
5.4%
특 2914
 
5.4%
로 2864
 
5.4%
Other values (323) 21865
40.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)7.0%
Missing981
Missing (%)25.3%
Infinite0
Infinite (%)0.0%
Mean3394.0059
Minimum3300
Maximum6500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.3 KiB
2024-05-11T09:38:57.274979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3300
5-th percentile3306
Q13333
median3395
Q33447
95-th percentile3487.85
Maximum6500
Range3200
Interquartile range (IQR)114

Descriptive statistics

Standard deviation89.211166
Coefficient of variation (CV)0.026284918
Kurtosis549.58653
Mean3394.0059
Median Absolute Deviation (MAD)58
Skewness16.918044
Sum9856193
Variance7958.6321
MonotonicityNot monotonic
2024-05-11T09:38:57.815996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3306 147
 
3.8%
3397 93
 
2.4%
3330 72
 
1.9%
3385 53
 
1.4%
3331 52
 
1.3%
3301 47
 
1.2%
3461 46
 
1.2%
3396 35
 
0.9%
3454 35
 
0.9%
3308 34
 
0.9%
Other values (192) 2290
58.9%
(Missing) 981
25.3%
ValueCountFrequency (%)
3300 23
 
0.6%
3301 47
 
1.2%
3302 33
 
0.8%
3303 14
 
0.4%
3304 8
 
0.2%
3305 19
 
0.5%
3306 147
3.8%
3307 13
 
0.3%
3308 34
 
0.9%
3309 8
 
0.2%
ValueCountFrequency (%)
6500 1
 
< 0.1%
5089 1
 
< 0.1%
3682 1
 
< 0.1%
3506 5
 
0.1%
3505 9
 
0.2%
3504 27
0.7%
3503 1
 
< 0.1%
3502 4
 
0.1%
3500 18
0.5%
3499 17
0.4%

사업장명
Text

Distinct3602
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
2024-05-11T09:38:58.620386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length7.58713
Min length1

Characters and Unicode

Total characters29476
Distinct characters873
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3384 ?
Unique (%)87.1%

Sample

1st row케익다운제과점
2nd row낙원다방
3rd row은하수
4th row삼화다방
5th row진궁
ValueCountFrequency (%)
gs25 119
 
2.0%
씨유 116
 
1.9%
세븐일레븐 89
 
1.5%
카페 82
 
1.4%
커피 44
 
0.7%
연신내점 43
 
0.7%
이마트24 40
 
0.7%
지에스25 37
 
0.6%
은평점 33
 
0.6%
coffee 32
 
0.5%
Other values (3938) 5334
89.4%
2024-05-11T09:39:00.014137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2093
 
7.1%
점 1221
 
4.1%
이 695
 
2.4%
스 659
 
2.2%
피 508
 
1.7%
커 473
 
1.6%
) 434
 
1.5%
( 434
 
1.5%
리 408
 
1.4%
은 358
 
1.2%
Other values (863) 22193
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22805
77.4%
Space Separator 2093
 
7.1%
Uppercase Letter 1560
 
5.3%
Lowercase Letter 1225
 
4.2%
Decimal Number 804
 
2.7%
Close Punctuation 434
 
1.5%
Open Punctuation 434
 
1.5%
Other Punctuation 103
 
0.3%
Dash Punctuation 16
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1221
 
5.4%
이 695
 
3.0%
스 659
 
2.9%
피 508
 
2.2%
커 473
 
2.1%
리 408
 
1.8%
은 358
 
1.6%
평 326
 
1.4%
카 314
 
1.4%
페 289
 
1.3%
Other values (787) 17554
77.0%
Uppercase Letter
ValueCountFrequency (%)
S 233
14.9%
C 205
13.1%
G 188
12.1%
P 101
 
6.5%
E 98
 
6.3%
O 76
 
4.9%
F 65
 
4.2%
A 65
 
4.2%
T 55
 
3.5%
D 53
 
3.4%
Other values (16) 421
27.0%
Lowercase Letter
ValueCountFrequency (%)
e 202
16.5%
a 126
10.3%
o 123
10.0%
f 113
 
9.2%
c 92
 
7.5%
i 67
 
5.5%
n 60
 
4.9%
s 58
 
4.7%
r 47
 
3.8%
t 37
 
3.0%
Other values (15) 300
24.5%
Decimal Number
ValueCountFrequency (%)
2 310
38.6%
5 235
29.2%
4 65
 
8.1%
1 57
 
7.1%
0 40
 
5.0%
9 31
 
3.9%
3 29
 
3.6%
6 17
 
2.1%
8 15
 
1.9%
7 5
 
0.6%
Other Punctuation
ValueCountFrequency (%)
& 30
29.1%
. 25
24.3%
, 15
14.6%
' 14
13.6%
? 7
 
6.8%
/ 6
 
5.8%
: 4
 
3.9%
! 1
 
1.0%
# 1
 
1.0%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
2093
100.0%
Close Punctuation
ValueCountFrequency (%)
) 434
100.0%
Open Punctuation
ValueCountFrequency (%)
( 434
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22795
77.3%
Common 3886
 
13.2%
Latin 2785
 
9.4%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1221
 
5.4%
이 695
 
3.0%
스 659
 
2.9%
피 508
 
2.2%
커 473
 
2.1%
리 408
 
1.8%
은 358
 
1.6%
평 326
 
1.4%
카 314
 
1.4%
페 289
 
1.3%
Other values (780) 17544
77.0%
Latin
ValueCountFrequency (%)
S 233
 
8.4%
C 205
 
7.4%
e 202
 
7.3%
G 188
 
6.8%
a 126
 
4.5%
o 123
 
4.4%
f 113
 
4.1%
P 101
 
3.6%
E 98
 
3.5%
c 92
 
3.3%
Other values (41) 1304
46.8%
Common
ValueCountFrequency (%)
2093
53.9%
) 434
 
11.2%
( 434
 
11.2%
2 310
 
8.0%
5 235
 
6.0%
4 65
 
1.7%
1 57
 
1.5%
0 40
 
1.0%
9 31
 
0.8%
& 30
 
0.8%
Other values (15) 157
 
4.0%
Han
ValueCountFrequency (%)
愛 2
20.0%
純 2
20.0%
倉 2
20.0%
情 1
10.0%
秀 1
10.0%
空 1
10.0%
房 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22789
77.3%
ASCII 6671
 
22.6%
CJK 10
 
< 0.1%
Compat Jamo 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2093
31.4%
) 434
 
6.5%
( 434
 
6.5%
2 310
 
4.6%
5 235
 
3.5%
S 233
 
3.5%
C 205
 
3.1%
e 202
 
3.0%
G 188
 
2.8%
a 126
 
1.9%
Other values (66) 2211
33.1%
Hangul
ValueCountFrequency (%)
점 1221
 
5.4%
이 695
 
3.0%
스 659
 
2.9%
피 508
 
2.2%
커 473
 
2.1%
리 408
 
1.8%
은 358
 
1.6%
평 326
 
1.4%
카 314
 
1.4%
페 289
 
1.3%
Other values (776) 17538
77.0%
Compat Jamo
ValueCountFrequency (%)
ㅁ 2
33.3%
ㅋ 2
33.3%
ㅅ 1
16.7%
ㄹ 1
16.7%
CJK
ValueCountFrequency (%)
愛 2
20.0%
純 2
20.0%
倉 2
20.0%
情 1
10.0%
秀 1
10.0%
空 1
10.0%
房 1
10.0%

최종수정일자
Date

Distinct3425
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
Minimum1999-01-08 00:00:00
Maximum2024-05-09 15:08:35
2024-05-11T09:39:00.688118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:39:01.440871image/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 size30.5 KiB
I
2449 
U
1435 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 2449
63.0%
U 1435
36.9%
D 1
 
< 0.1%

Length

2024-05-11T09:39:01.905626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:02.337335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2449
63.0%
u 1435
36.9%
d 1
 
< 0.1%

데이터갱신일자
Date

Distinct1115
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T09:39:02.837821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:39:03.326233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct14
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
일반조리판매
1024 
커피숍
895 
기타 휴게음식점
830 
편의점
336 
다방
297 
Other values (9)
503 

Length

Max length8
Median length6
Mean length4.8862291
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반조리판매 1024
26.4%
커피숍 895
23.0%
기타 휴게음식점 830
21.4%
편의점 336
 
8.6%
다방 297
 
7.6%
과자점 278
 
7.2%
패스트푸드 175
 
4.5%
전통찻집 16
 
0.4%
푸드트럭 16
 
0.4%
키즈카페 7
 
0.2%
Other values (4) 11
 
0.3%

Length

2024-05-11T09:39:03.808893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반조리판매 1024
21.7%
커피숍 895
19.0%
기타 830
17.6%
휴게음식점 830
17.6%
편의점 336
 
7.1%
다방 297
 
6.3%
과자점 278
 
5.9%
패스트푸드 175
 
3.7%
전통찻집 16
 
0.3%
푸드트럭 16
 
0.3%
Other values (5) 18
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2050
Distinct (%)54.7%
Missing140
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean192837.94
Minimum190148.39
Maximum205607.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.3 KiB
2024-05-11T09:39:04.229672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum190148.39
5-th percentile191664.13
Q1192417.7
median192798.66
Q3193301.59
95-th percentile194021.67
Maximum205607.19
Range15458.797
Interquartile range (IQR)883.89682

Descriptive statistics

Standard deviation761.31473
Coefficient of variation (CV)0.0039479509
Kurtosis21.308124
Mean192837.94
Median Absolute Deviation (MAD)418.48697
Skewness1.0933803
Sum7.2217808 × 108
Variance579600.11
MonotonicityNot monotonic
2024-05-11T09:39:04.751193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193661.732383169 106
 
2.7%
192798.659161134 43
 
1.1%
192882.837727443 31
 
0.8%
193208.140166 23
 
0.6%
193884.826418788 22
 
0.6%
190977.850603548 21
 
0.5%
192694.92374224 19
 
0.5%
193103.427054842 17
 
0.4%
194029.235749604 15
 
0.4%
193035.279146132 14
 
0.4%
Other values (2040) 3434
88.4%
(Missing) 140
 
3.6%
ValueCountFrequency (%)
190148.389108835 1
 
< 0.1%
190152.652347372 1
 
< 0.1%
190253.21024219 1
 
< 0.1%
190355.24067022 1
 
< 0.1%
190373.380194267 3
0.1%
190433.07905079 1
 
< 0.1%
190470.571086776 1
 
< 0.1%
190545.226210429 1
 
< 0.1%
190557.243446334 1
 
< 0.1%
190563.176402607 1
 
< 0.1%
ValueCountFrequency (%)
205607.186171597 1
< 0.1%
195524.743560367 2
0.1%
195498.306937492 1
< 0.1%
195358.535748819 1
< 0.1%
195337.443196539 2
0.1%
195324.876960123 1
< 0.1%
195321.836142863 1
< 0.1%
195238.804223929 1
< 0.1%
195083.896525708 1
< 0.1%
194867.72210659 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2049
Distinct (%)54.7%
Missing140
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean456340.31
Minimum447642.16
Maximum461614.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.3 KiB
2024-05-11T09:39:05.184568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447642.16
5-th percentile453698.64
Q1455280.77
median456371.87
Q3457359.24
95-th percentile459646.83
Maximum461614.65
Range13972.488
Interquartile range (IQR)2078.4657

Descriptive statistics

Standard deviation1665.2613
Coefficient of variation (CV)0.0036491654
Kurtosis0.17327851
Mean456340.31
Median Absolute Deviation (MAD)1031.3301
Skewness0.33632909
Sum1.7089944 × 109
Variance2773095.1
MonotonicityNot monotonic
2024-05-11T09:39:05.664307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456379.193899276 106
 
2.7%
459646.827222065 43
 
1.1%
455340.54056388 31
 
0.8%
460165.655248 23
 
0.6%
459328.813094403 22
 
0.6%
453037.787995874 21
 
0.5%
459461.236119623 19
 
0.5%
459986.856034813 17
 
0.4%
456185.615536089 15
 
0.4%
457365.911737494 14
 
0.4%
Other values (2039) 3434
88.4%
(Missing) 140
 
3.6%
ValueCountFrequency (%)
447642.163714896 1
< 0.1%
452799.599269845 1
< 0.1%
452890.003005512 1
< 0.1%
452924.117735363 1
< 0.1%
452946.246733537 2
0.1%
452965.43150519 1
< 0.1%
452992.137815337 2
0.1%
453004.338574203 2
0.1%
453028.082374239 2
0.1%
453032.220651511 1
< 0.1%
ValueCountFrequency (%)
461614.651872297 1
< 0.1%
461597.265893106 1
< 0.1%
461594.341753059 1
< 0.1%
461585.175092979 2
0.1%
461455.876513588 1
< 0.1%
461437.781387469 1
< 0.1%
461423.011700226 1
< 0.1%
461403.797964549 2
0.1%
461189.932191943 1
< 0.1%
461175.2097954 1
< 0.1%

위생업태명
Categorical

Distinct15
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
<NA>
959 
일반조리판매
858 
커피숍
632 
기타 휴게음식점
456 
다방
293 
Other values (10)
687 

Length

Max length8
Median length6
Mean length4.5081081
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 959
24.7%
일반조리판매 858
22.1%
커피숍 632
16.3%
기타 휴게음식점 456
11.7%
다방 293
 
7.5%
과자점 276
 
7.1%
편의점 229
 
5.9%
패스트푸드 149
 
3.8%
전통찻집 15
 
0.4%
키즈카페 6
 
0.2%
Other values (5) 12
 
0.3%

Length

2024-05-11T09:39:06.164872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 959
22.1%
일반조리판매 858
19.8%
커피숍 632
14.6%
기타 456
10.5%
휴게음식점 456
10.5%
다방 293
 
6.7%
과자점 276
 
6.4%
편의점 229
 
5.3%
패스트푸드 149
 
3.4%
전통찻집 15
 
0.3%
Other values (6) 18
 
0.4%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct6
Distinct (%)0.6%
Missing2947
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean0.37846482
Minimum0
Maximum93
Zeros724
Zeros (%)18.6%
Negative0
Negative (%)0.0%
Memory size34.3 KiB
2024-05-11T09:39:06.724392image/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 deviation3.0920846
Coefficient of variation (CV)8.1700714
Kurtosis861.83369
Mean0.37846482
Median Absolute Deviation (MAD)0
Skewness28.786036
Sum355
Variance9.5609872
MonotonicityNot monotonic
2024-05-11T09:39:07.122863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 724
 
18.6%
1 178
 
4.6%
2 28
 
0.7%
3 6
 
0.2%
10 1
 
< 0.1%
93 1
 
< 0.1%
(Missing) 2947
75.9%
ValueCountFrequency (%)
0 724
18.6%
1 178
 
4.6%
2 28
 
0.7%
3 6
 
0.2%
10 1
 
< 0.1%
93 1
 
< 0.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
10 1
 
< 0.1%
3 6
 
0.2%
2 28
 
0.7%
1 178
 
4.6%
0 724
18.6%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.7%
Missing2890
Missing (%)74.4%
Infinite0
Infinite (%)0.0%
Mean0.78090452
Minimum0
Maximum93
Zeros609
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size34.3 KiB
2024-05-11T09:39:07.411350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum93
Range93
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.108086
Coefficient of variation (CV)3.9801101
Kurtosis781.45773
Mean0.78090452
Median Absolute Deviation (MAD)0
Skewness26.378671
Sum777
Variance9.6601984
MonotonicityNot monotonic
2024-05-11T09:39:07.708520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 609
 
15.7%
1 203
 
5.2%
2 85
 
2.2%
3 79
 
2.0%
4 16
 
0.4%
5 2
 
0.1%
93 1
 
< 0.1%
(Missing) 2890
74.4%
ValueCountFrequency (%)
0 609
15.7%
1 203
 
5.2%
2 85
 
2.2%
3 79
 
2.0%
4 16
 
0.4%
5 2
 
0.1%
93 1
 
< 0.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
5 2
 
0.1%
4 16
 
0.4%
3 79
 
2.0%
2 85
 
2.2%
1 203
 
5.2%
0 609
15.7%

영업장주변구분명
Categorical

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
학교정화(상대)
1154 
<NA>
1088 
기타
776 
주택가주변
635 
학교정화(절대)
158 
Other values (3)
 
74

Length

Max length8
Median length7
Mean length5.1634492
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
학교정화(상대) 1154
29.7%
<NA> 1088
28.0%
기타 776
20.0%
주택가주변 635
16.3%
학교정화(절대) 158
 
4.1%
유흥업소밀집지역 37
 
1.0%
아파트지역 35
 
0.9%
결혼예식장주변 2
 
0.1%

Length

2024-05-11T09:39:08.239840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:09.030145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교정화(상대 1154
29.7%
na 1088
28.0%
기타 776
20.0%
주택가주변 635
16.3%
학교정화(절대 158
 
4.1%
유흥업소밀집지역 37
 
1.0%
아파트지역 35
 
0.9%
결혼예식장주변 2
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
자율
2572 
<NA>
1112 
을
 
132
기타
 
26
갑
 
22
Other values (3)
 
21

Length

Max length4
Median length2
Mean length2.5328185
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자율
2nd row을
3rd row을
4th row자율
5th row을

Common Values

ValueCountFrequency (%)
자율 2572
66.2%
<NA> 1112
28.6%
을 132
 
3.4%
기타 26
 
0.7%
갑 22
 
0.6%
지도 11
 
0.3%
우수 7
 
0.2%
관리 3
 
0.1%

Length

2024-05-11T09:39:09.917319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:10.582931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자율 2572
66.2%
na 1112
28.6%
을 132
 
3.4%
기타 26
 
0.7%
갑 22
 
0.6%
지도 11
 
0.3%
우수 7
 
0.2%
관리 3
 
0.1%

급수시설구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
상수도전용
2506 
<NA>
1376 
상수도(음용)지하수(주방용)겸용
 
3

Length

Max length17
Median length5
Mean length4.6550837
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2506
64.5%
<NA> 1376
35.4%
상수도(음용)지하수(주방용)겸용 3
 
0.1%

Length

2024-05-11T09:39:11.186666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:11.616809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2506
64.5%
na 1376
35.4%
상수도(음용)지하수(주방용)겸용 3
 
0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
<NA>
3668 
0
 
217

Length

Max length4
Median length4
Mean length3.8324324
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> 3668
94.4%
0 217
 
5.6%

Length

2024-05-11T09:39:12.034159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:12.415585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3668
94.4%
0 217
 
5.6%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
<NA>
3667 
0
 
218

Length

Max length4
Median length4
Mean length3.8316602
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> 3667
94.4%
0 218
 
5.6%

Length

2024-05-11T09:39:12.987781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:13.216440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3667
94.4%
0 218
 
5.6%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
<NA>
3667 
0
 
218

Length

Max length4
Median length4
Mean length3.8316602
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> 3667
94.4%
0 218
 
5.6%

Length

2024-05-11T09:39:13.547890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:13.857974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3667
94.4%
0 218
 
5.6%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
<NA>
3667 
0
 
218

Length

Max length4
Median length4
Mean length3.8316602
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> 3667
94.4%
0 218
 
5.6%

Length

2024-05-11T09:39:14.191788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:14.509136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3667
94.4%
0 218
 
5.6%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
<NA>
3667 
0
 
218

Length

Max length4
Median length4
Mean length3.8316602
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> 3667
94.4%
0 218
 
5.6%

Length

2024-05-11T09:39:14.816566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:15.258411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3667
94.4%
0 218
 
5.6%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3885
Missing (%)100.0%
Memory size34.3 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
<NA>
3667 
0
 
218

Length

Max length4
Median length4
Mean length3.8316602
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> 3667
94.4%
0 218
 
5.6%

Length

2024-05-11T09:39:15.560836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:15.798970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3667
94.4%
0 218
 
5.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
<NA>
3667 
0
 
218

Length

Max length4
Median length4
Mean length3.8316602
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> 3667
94.4%
0 218
 
5.6%

Length

2024-05-11T09:39:16.038979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:16.356471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3667
94.4%
0 218
 
5.6%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing959
Missing (%)24.7%
Memory size7.7 KiB
False
2892 
True
 
34
(Missing)
959 
ValueCountFrequency (%)
False 2892
74.4%
True 34
 
0.9%
(Missing) 959
 
24.7%
2024-05-11T09:39:16.595616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct1547
Distinct (%)52.9%
Missing959
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean38.215755
Minimum0
Maximum489.41
Zeros13
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size34.3 KiB
2024-05-11T09:39:16.976145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q114.7775
median26.855
Q348.885
95-th percentile107.8125
Maximum489.41
Range489.41
Interquartile range (IQR)34.1075

Descriptive statistics

Standard deviation40.25536
Coefficient of variation (CV)1.0533708
Kurtosis19.129307
Mean38.215755
Median Absolute Deviation (MAD)15.26
Skewness3.3505824
Sum111819.3
Variance1620.494
MonotonicityNot monotonic
2024-05-11T09:39:17.405267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 152
 
3.9%
6.6 70
 
1.8%
33.0 54
 
1.4%
30.0 49
 
1.3%
10.0 47
 
1.2%
15.0 28
 
0.7%
9.9 27
 
0.7%
5.0 25
 
0.6%
24.0 25
 
0.6%
3.0 24
 
0.6%
Other values (1537) 2425
62.4%
(Missing) 959
 
24.7%
ValueCountFrequency (%)
0.0 13
0.3%
0.13 1
 
< 0.1%
0.22 1
 
< 0.1%
0.25 2
 
0.1%
0.32 1
 
< 0.1%
0.42 1
 
< 0.1%
0.58 1
 
< 0.1%
0.63 1
 
< 0.1%
0.7 1
 
< 0.1%
0.72 1
 
< 0.1%
ValueCountFrequency (%)
489.41 1
< 0.1%
405.49 1
< 0.1%
372.06 1
< 0.1%
340.97 1
< 0.1%
330.58 1
< 0.1%
327.43 1
< 0.1%
325.62 1
< 0.1%
324.4 1
< 0.1%
318.27 1
< 0.1%
311.85 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
<NA>
3828 
00000
 
55
`
 
1
[25~
 
1

Length

Max length5
Median length4
Mean length4.0133848
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3828
98.5%
00000 55
 
1.4%
` 1
 
< 0.1%
[25~ 1
 
< 0.1%

Length

2024-05-11T09:39:17.827207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:39:18.192478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3828
98.5%
00000 55
 
1.4%
1
 
< 0.1%
25 1
 
< 0.1%

전통업소주된음식
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3884
Missing (%)> 99.9%
Memory size30.5 KiB
2024-05-11T09:39:18.359287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
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 row`
ValueCountFrequency (%)
1
100.0%
2024-05-11T09:39:18.879560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
` 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Modifier Symbol 1
100.0%

Most frequent character per category

Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
` 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
` 1
100.0%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3885
Missing (%)100.0%
Memory size34.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031100003110000-104-1964-0472719640402<NA>3폐업2폐업19990705<NA><NA><NA>02 353835759.11122845서울특별시 은평구 대조동 224-24번지<NA><NA>케익다운제과점1999-07-05 00:00:00I2018-08-31 23:59:59.0과자점192656.30213456562.163419과자점11주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N59.11<NA><NA><NA>
131100003110000-104-1969-0487019691215<NA>3폐업2폐업20040809<NA><NA><NA>020355640688.27122907서울특별시 은평구 응암동 87-10번지 (지하1층)<NA><NA>낙원다방2003-10-24 00:00:00I2018-08-31 23:59:59.0다방193124.799357455390.93732다방11주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N88.27<NA><NA><NA>
231100003110000-104-1969-0497319690403<NA>3폐업2폐업20100929<NA><NA><NA>02 355080366.63122842서울특별시 은평구 대조동 185-5번지 (지하1층)<NA><NA>은하수2009-02-17 14:27:50I2018-08-31 23:59:59.0다방192998.911045457325.813105다방03주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N66.63<NA><NA><NA>
331100003110000-104-1970-0487219700521<NA>3폐업2폐업20031205<NA><NA><NA>020355507397.96122906서울특별시 은평구 응암동 97-1번지 (지상2층)<NA><NA>삼화다방2003-10-24 00:00:00I2018-08-31 23:59:59.0다방193466.528232455353.03563다방<NA>2주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N97.96<NA><NA><NA>
431100003110000-104-1970-0493819701016<NA>3폐업2폐업20091202<NA><NA><NA>02 372826396.39122878서울특별시 은평구 수색동 368-1번지 (지하1층)<NA><NA>진궁2009-11-02 15:36:43I2018-08-31 23:59:59.0다방190683.969111453360.669715다방03주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N96.39<NA><NA><NA>
531100003110000-104-1970-0499419700917<NA>1영업/정상1영업<NA><NA><NA><NA>02 3556446137.6122908서울특별시 은평구 응암동 103-2번지 (지하1층)서울특별시 은평구 은평로10길 2 (응암동, 지하1층)<NA>청자다방2018-07-16 14:39:33I2018-08-31 23:59:59.0다방193104.149765455304.977186다방05주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y137.6<NA><NA><NA>
631100003110000-104-1971-0485819711223<NA>3폐업2폐업19981103<NA><NA><NA>0203626595127.43122809서울특별시 은평구 갈현동 398-9번지<NA><NA>볼레로커피2001-09-28 00:00:00I2018-08-31 23:59:59.0다방192847.948778457379.925111다방12주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N127.43<NA><NA><NA>
731100003110000-104-1971-0491119710507<NA>3폐업2폐업20100916<NA><NA><NA>02 3551887105.8122030서울특별시 은평구 대조동 3-4번지 ,5(지하1층)<NA><NA>사군자2003-12-17 00:00:00I2018-08-31 23:59:59.0다방193558.87653456652.352338다방04주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N105.8<NA><NA><NA>
831100003110000-104-1971-0495019710719<NA>3폐업2폐업20041102<NA><NA><NA>02 355971990.49122831서울특별시 은평구 녹번동 117-15번지 (지상2층)<NA><NA>대호다방2003-10-24 00:00:00I2018-08-31 23:59:59.0다방193986.989766456081.878123다방02주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N90.49<NA><NA><NA>
931100003110000-104-1971-0500919711225<NA>3폐업2폐업20011203<NA><NA><NA>02 389149751.4122200서울특별시 은평구 진관동 251-8번지<NA><NA>칠칠다방2000-03-21 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N51.4<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
387531100003110000-104-2024-000442024-04-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0122-873서울특별시 은평구 수색동 106-1서울특별시 은평구 수색로 256, 1층 (수색동)3502황금 십원당2024-04-12 13:31:56I2023-12-03 23:04:00.0기타 휴게음식점190741.823965453328.11467<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
387631100003110000-104-2024-000452024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.0122-845서울특별시 은평구 대조동 224-18서울특별시 은평구 연서로 144, 1층 (대조동)3394로드탑2024-04-17 14:07:08I2023-12-03 23:09:00.0기타 휴게음식점192656.116826456593.999523<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
387731100003110000-104-2024-000462024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.01122-952서울특별시 은평구 응암동 754-1 대림시장서울특별시 은평구 응암로4길 22, 대림시장 상가동 1층 83호 (응암동)3480마시는 노리터2024-04-24 09:26:16I2023-12-03 22:06:00.0기타 휴게음식점192661.661319453828.585983<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
387831100003110000-104-2024-000472024-04-25<NA>3폐업2폐업2024-05-07<NA><NA><NA><NA><NA>122-837서울특별시 은평구 대조동 240 NC백화점서울특별시 은평구 불광로 20, NC백화점 지하1층 (대조동)3397행복생활에프앤비2024-05-08 04:15:09U2023-12-04 23:00:00.0기타 휴게음식점193661.732383456379.193899<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
387931100003110000-104-2024-000482024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.54122-912서울특별시 은평구 응암동 159-11서울특별시 은평구 백련산로 159, 1층 (응암동)3462피땀국물2024-04-25 14:55:33I2023-12-03 22:07:00.0기타 휴게음식점193390.431708455211.345339<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
388031100003110000-104-2024-000492024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0122-200서울특별시 은평구 진관동 69-1서울특별시 은평구 진관3로 22, 3층 (진관동)3306라이또 PC 구파발2024-04-29 15:54:16I2023-12-05 00:01:00.0기타 휴게음식점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
388131100003110000-104-2024-000502024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>11.32122-863서울특별시 은평구 불광동 357-9서울특별시 은평구 연서로33길 4, 1층 (불광동)3342산이키운삼 서울서부총판2024-05-07 09:53:58I2023-12-05 00:09:00.0극장193289.931011457633.641881<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
388231100003110000-104-2024-000512024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>73.3122-881서울특별시 은평구 신사동 18-24 새마을금고신사동제2분사무소서울특별시 은평구 갈현로1길 21, 새마을금고신사동제2분사무소 1층 (신사동)3437이디야커피 은평신사점2024-05-07 10:41:03I2023-12-05 00:09:00.0커피숍191794.541629455218.994158<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
388331100003110000-104-2024-000522024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>68.0122-831서울특별시 은평구 녹번동 118-47 제현빌딩서울특별시 은평구 진흥로 184, 제현빌딩 1층 (녹번동)3375제주한방약초카페2024-05-09 10:48:25I2023-12-04 23:01:00.0전통찻집193738.187679456210.937737<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
388431100003110000-104-2024-000532024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>55.41122-908서울특별시 은평구 응암동 105-13서울특별시 은평구 응암로34길 12, 1층 (응암동)3464GS25 응암IS점2024-05-09 15:08:35I2023-12-04 23:01:00.0기타 휴게음식점193048.685469455089.654016<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>