Overview

Dataset statistics

Number of variables44
Number of observations2364
Missing cells26883
Missing cells (%)25.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory870.5 KiB
Average record size in memory377.1 B

Variable types

Categorical18
Text6
DateTime4
Unsupported8
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
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-18686/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (66.2%)Imbalance
등급구분명 is highly imbalanced (63.6%)Imbalance
급수시설구분명 is highly imbalanced (50.6%)Imbalance
총인원 is highly imbalanced (67.4%)Imbalance
본사종업원수 is highly imbalanced (66.7%)Imbalance
공장사무직종업원수 is highly imbalanced (66.7%)Imbalance
공장판매직종업원수 is highly imbalanced (66.7%)Imbalance
공장생산직종업원수 is highly imbalanced (66.7%)Imbalance
보증액 is highly imbalanced (66.7%)Imbalance
월세액 is highly imbalanced (66.7%)Imbalance
다중이용업소여부 is highly imbalanced (91.2%)Imbalance
인허가취소일자 has 2364 (100.0%) missing valuesMissing
폐업일자 has 692 (29.3%) missing valuesMissing
휴업시작일자 has 2364 (100.0%) missing valuesMissing
휴업종료일자 has 2364 (100.0%) missing valuesMissing
재개업일자 has 2364 (100.0%) missing valuesMissing
전화번호 has 1129 (47.8%) missing valuesMissing
소재지면적 has 83 (3.5%) missing valuesMissing
도로명주소 has 799 (33.8%) missing valuesMissing
도로명우편번호 has 813 (34.4%) missing valuesMissing
좌표정보(X) has 57 (2.4%) missing valuesMissing
좌표정보(Y) has 57 (2.4%) missing valuesMissing
남성종사자수 has 1610 (68.1%) missing valuesMissing
여성종사자수 has 1601 (67.7%) missing valuesMissing
건물소유구분명 has 2364 (100.0%) missing valuesMissing
다중이용업소여부 has 565 (23.9%) missing valuesMissing
시설총규모 has 565 (23.9%) missing valuesMissing
전통업소지정번호 has 2364 (100.0%) missing valuesMissing
전통업소주된음식 has 2364 (100.0%) missing valuesMissing
홈페이지 has 2364 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 35.82640056)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
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
남성종사자수 has 667 (28.2%) zerosZeros
여성종사자수 has 562 (23.8%) zerosZeros
시설총규모 has 105 (4.4%) zerosZeros

Reproduction

Analysis started2024-04-29 19:46:58.996931
Analysis finished2024-04-29 19:47:00.300093
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
3090000
2364 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 2364
100.0%

Length

2024-04-30T04:47:00.362946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:00.433005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 2364
100.0%

관리번호
Text

UNIQUE 

Distinct2364
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2024-04-30T04:47:00.581444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters52008
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

Unique2364 ?
Unique (%)100.0%

Sample

1st row3090000-104-1947-01116
2nd row3090000-104-1970-01444
3rd row3090000-104-1971-01315
4th row3090000-104-1971-01409
5th row3090000-104-1973-01823
ValueCountFrequency (%)
3090000-104-1947-01116 1
 
< 0.1%
3090000-104-2017-00060 1
 
< 0.1%
3090000-104-2017-00044 1
 
< 0.1%
3090000-104-2017-00051 1
 
< 0.1%
3090000-104-2017-00045 1
 
< 0.1%
3090000-104-2017-00046 1
 
< 0.1%
3090000-104-2017-00047 1
 
< 0.1%
3090000-104-2017-00048 1
 
< 0.1%
3090000-104-2017-00049 1
 
< 0.1%
3090000-104-2017-00050 1
 
< 0.1%
Other values (2354) 2354
99.6%
2024-04-30T04:47:00.869806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23364
44.9%
- 7092
 
13.6%
1 5048
 
9.7%
9 3834
 
7.4%
2 3361
 
6.5%
3 3292
 
6.3%
4 3177
 
6.1%
8 739
 
1.4%
5 737
 
1.4%
6 709
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44916
86.4%
Dash Punctuation 7092
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23364
52.0%
1 5048
 
11.2%
9 3834
 
8.5%
2 3361
 
7.5%
3 3292
 
7.3%
4 3177
 
7.1%
8 739
 
1.6%
5 737
 
1.6%
6 709
 
1.6%
7 655
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7092
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52008
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23364
44.9%
- 7092
 
13.6%
1 5048
 
9.7%
9 3834
 
7.4%
2 3361
 
6.5%
3 3292
 
6.3%
4 3177
 
6.1%
8 739
 
1.4%
5 737
 
1.4%
6 709
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23364
44.9%
- 7092
 
13.6%
1 5048
 
9.7%
9 3834
 
7.4%
2 3361
 
6.5%
3 3292
 
6.3%
4 3177
 
6.1%
8 739
 
1.4%
5 737
 
1.4%
6 709
 
1.4%

인허가일자
Date

Distinct1951
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
Minimum1947-03-11 00:00:00
Maximum2024-04-15 00:00:00
2024-04-30T04:47:00.993543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:47:01.103909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2364
Missing (%)100.0%
Memory size20.9 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
3
1672 
1
692 

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 1672
70.7%
1 692
29.3%

Length

2024-04-30T04:47:01.200492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:01.269221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1672
70.7%
1 692
29.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
폐업
1672 
영업/정상
692 

Length

Max length5
Median length2
Mean length2.8781726
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1672
70.7%
영업/정상 692
29.3%

Length

2024-04-30T04:47:01.351159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:01.439868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1672
70.7%
영업/정상 692
29.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2
1672 
1
692 

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 1672
70.7%
1 692
29.3%

Length

2024-04-30T04:47:01.533526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:01.607928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1672
70.7%
1 692
29.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
폐업
1672 
영업
692 

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 1672
70.7%
영업 692
29.3%

Length

2024-04-30T04:47:01.685681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:01.772678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1672
70.7%
영업 692
29.3%

폐업일자
Date

MISSING 

Distinct1371
Distinct (%)82.0%
Missing692
Missing (%)29.3%
Memory size18.6 KiB
Minimum1986-07-25 00:00:00
Maximum2024-04-25 00:00:00
2024-04-30T04:47:01.885432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:47:02.019588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2364
Missing (%)100.0%
Memory size20.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2364
Missing (%)100.0%
Memory size20.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2364
Missing (%)100.0%
Memory size20.9 KiB

전화번호
Text

MISSING 

Distinct1110
Distinct (%)89.9%
Missing1129
Missing (%)47.8%
Memory size18.6 KiB
2024-04-30T04:47:02.321971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.320648
Min length2

Characters and Unicode

Total characters12746
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

Unique1076 ?
Unique (%)87.1%

Sample

1st row0234921884
2nd row02 9070771
3rd row02
4th row0200000000
5th row0200000000
ValueCountFrequency (%)
02 830
35.5%
0200000000 47
 
2.0%
955 28
 
1.2%
070 26
 
1.1%
956 23
 
1.0%
954 18
 
0.8%
900 17
 
0.7%
903 17
 
0.7%
999 14
 
0.6%
904 13
 
0.6%
Other values (1153) 1308
55.9%
2024-04-30T04:47:02.691013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2831
22.2%
9 1830
14.4%
2 1824
14.3%
1431
11.2%
5 874
 
6.9%
3 770
 
6.0%
4 740
 
5.8%
1 644
 
5.1%
7 616
 
4.8%
6 602
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11315
88.8%
Space Separator 1431
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2831
25.0%
9 1830
16.2%
2 1824
16.1%
5 874
 
7.7%
3 770
 
6.8%
4 740
 
6.5%
1 644
 
5.7%
7 616
 
5.4%
6 602
 
5.3%
8 584
 
5.2%
Space Separator
ValueCountFrequency (%)
1431
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12746
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2831
22.2%
9 1830
14.4%
2 1824
14.3%
1431
11.2%
5 874
 
6.9%
3 770
 
6.0%
4 740
 
5.8%
1 644
 
5.1%
7 616
 
4.8%
6 602
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2831
22.2%
9 1830
14.4%
2 1824
14.3%
1431
11.2%
5 874
 
6.9%
3 770
 
6.0%
4 740
 
5.8%
1 644
 
5.1%
7 616
 
4.8%
6 602
 
4.7%

소재지면적
Real number (ℝ)

MISSING 

Distinct1126
Distinct (%)49.4%
Missing83
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean38.860132
Minimum0
Maximum700
Zeros22
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-04-30T04:47:02.867148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q112.84
median25.92
Q346.49
95-th percentile107.8
Maximum700
Range700
Interquartile range (IQR)33.65

Descriptive statistics

Standard deviation50.393684
Coefficient of variation (CV)1.2967965
Kurtosis40.372767
Mean38.860132
Median Absolute Deviation (MAD)16.02
Skewness4.9951055
Sum88639.96
Variance2539.5234
MonotonicityNot monotonic
2024-04-30T04:47:03.048874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 211
 
8.9%
6.6 97
 
4.1%
33.0 39
 
1.6%
9.9 32
 
1.4%
26.4 32
 
1.4%
23.1 30
 
1.3%
16.5 26
 
1.1%
30.0 25
 
1.1%
20.0 23
 
1.0%
0.0 22
 
0.9%
Other values (1116) 1744
73.8%
(Missing) 83
 
3.5%
ValueCountFrequency (%)
0.0 22
0.9%
0.11 1
 
< 0.1%
0.32 1
 
< 0.1%
1.05 1
 
< 0.1%
1.12 1
 
< 0.1%
1.69 1
 
< 0.1%
2.0 2
 
0.1%
2.1 1
 
< 0.1%
2.3 1
 
< 0.1%
2.56 1
 
< 0.1%
ValueCountFrequency (%)
700.0 1
< 0.1%
600.0 1
< 0.1%
583.13 1
< 0.1%
544.5 1
< 0.1%
452.0 1
< 0.1%
450.0 1
< 0.1%
391.92 1
< 0.1%
375.0 1
< 0.1%
363.12 1
< 0.1%
335.29 1
< 0.1%

소재지우편번호
Text

Distinct233
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2024-04-30T04:47:03.313522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.142978
Min length6

Characters and Unicode

Total characters14522
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 (%)2.2%

Sample

1st row132822
2nd row132858
3rd row132819
4th row132866
5th row132864
ValueCountFrequency (%)
132854 149
 
6.3%
132898 138
 
5.8%
132904 78
 
3.3%
132924 73
 
3.1%
132885 60
 
2.5%
132848 43
 
1.8%
132820 41
 
1.7%
132917 41
 
1.7%
132040 38
 
1.6%
132819 36
 
1.5%
Other values (223) 1667
70.5%
2024-04-30T04:47:03.689402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2929
20.2%
1 2840
19.6%
3 2653
18.3%
8 1981
13.6%
9 1120
 
7.7%
0 758
 
5.2%
4 694
 
4.8%
5 546
 
3.8%
6 398
 
2.7%
- 338
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14184
97.7%
Dash Punctuation 338
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2929
20.7%
1 2840
20.0%
3 2653
18.7%
8 1981
14.0%
9 1120
 
7.9%
0 758
 
5.3%
4 694
 
4.9%
5 546
 
3.8%
6 398
 
2.8%
7 265
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 338
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14522
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2929
20.2%
1 2840
19.6%
3 2653
18.3%
8 1981
13.6%
9 1120
 
7.7%
0 758
 
5.2%
4 694
 
4.8%
5 546
 
3.8%
6 398
 
2.7%
- 338
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14522
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2929
20.2%
1 2840
19.6%
3 2653
18.3%
8 1981
13.6%
9 1120
 
7.7%
0 758
 
5.2%
4 694
 
4.8%
5 546
 
3.8%
6 398
 
2.7%
- 338
 
2.3%

지번주소
Text

Distinct2086
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2024-04-30T04:47:03.979235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length25.639594
Min length15

Characters and Unicode

Total characters60612
Distinct characters334
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1906 ?
Unique (%)80.6%

Sample

1st row서울특별시 도봉구 도봉동 634-9번지
2nd row서울특별시 도봉구 쌍문동 41-3번지
3rd row서울특별시 도봉구 도봉동 600-1번지
4th row서울특별시 도봉구 쌍문동 123-2번지
5th row서울특별시 도봉구 쌍문동 96-29번지
ValueCountFrequency (%)
서울특별시 2363
20.3%
도봉구 2362
20.3%
창동 918
 
7.9%
방학동 591
 
5.1%
쌍문동 530
 
4.5%
1층 356
 
3.1%
도봉동 340
 
2.9%
지상1층 224
 
1.9%
지하1층 102
 
0.9%
1-10번지 74
 
0.6%
Other values (2184) 3793
32.5%
2024-04-30T04:47:04.411809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10920
18.0%
1 2810
 
4.6%
도 2766
 
4.6%
봉 2759
 
4.6%
동 2672
 
4.4%
시 2386
 
3.9%
서 2377
 
3.9%
구 2377
 
3.9%
울 2369
 
3.9%
별 2364
 
3.9%
Other values (324) 26812
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35059
57.8%
Decimal Number 11979
 
19.8%
Space Separator 10920
 
18.0%
Dash Punctuation 2052
 
3.4%
Uppercase Letter 205
 
0.3%
Open Punctuation 144
 
0.2%
Close Punctuation 144
 
0.2%
Other Punctuation 95
 
0.2%
Other Symbol 6
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 2766
 
7.9%
봉 2759
 
7.9%
동 2672
 
7.6%
시 2386
 
6.8%
서 2377
 
6.8%
구 2377
 
6.8%
울 2369
 
6.8%
별 2364
 
6.7%
특 2363
 
6.7%
지 2011
 
5.7%
Other values (281) 10615
30.3%
Uppercase Letter
ValueCountFrequency (%)
A 54
26.3%
E 42
20.5%
S 25
12.2%
B 14
 
6.8%
T 14
 
6.8%
R 13
 
6.3%
M 12
 
5.9%
G 6
 
2.9%
L 6
 
2.9%
Q 4
 
2.0%
Other values (9) 15
 
7.3%
Decimal Number
ValueCountFrequency (%)
1 2810
23.5%
6 1450
12.1%
2 1347
11.2%
3 1151
9.6%
0 1135
9.5%
5 1082
 
9.0%
7 1028
 
8.6%
4 839
 
7.0%
8 646
 
5.4%
9 491
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 88
92.6%
. 2
 
2.1%
' 2
 
2.1%
! 2
 
2.1%
@ 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
t 1
33.3%
p 1
33.3%
a 1
33.3%
Space Separator
ValueCountFrequency (%)
10920
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2052
100.0%
Open Punctuation
ValueCountFrequency (%)
( 144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 144
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35065
57.9%
Common 25339
41.8%
Latin 208
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 2766
 
7.9%
봉 2759
 
7.9%
동 2672
 
7.6%
시 2386
 
6.8%
서 2377
 
6.8%
구 2377
 
6.8%
울 2369
 
6.8%
별 2364
 
6.7%
특 2363
 
6.7%
지 2011
 
5.7%
Other values (282) 10621
30.3%
Latin
ValueCountFrequency (%)
A 54
26.0%
E 42
20.2%
S 25
12.0%
B 14
 
6.7%
T 14
 
6.7%
R 13
 
6.2%
M 12
 
5.8%
G 6
 
2.9%
L 6
 
2.9%
Q 4
 
1.9%
Other values (12) 18
 
8.7%
Common
ValueCountFrequency (%)
10920
43.1%
1 2810
 
11.1%
- 2052
 
8.1%
6 1450
 
5.7%
2 1347
 
5.3%
3 1151
 
4.5%
0 1135
 
4.5%
5 1082
 
4.3%
7 1028
 
4.1%
4 839
 
3.3%
Other values (10) 1525
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35059
57.8%
ASCII 25547
42.1%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10920
42.7%
1 2810
 
11.0%
- 2052
 
8.0%
6 1450
 
5.7%
2 1347
 
5.3%
3 1151
 
4.5%
0 1135
 
4.4%
5 1082
 
4.2%
7 1028
 
4.0%
4 839
 
3.3%
Other values (32) 1733
 
6.8%
Hangul
ValueCountFrequency (%)
도 2766
 
7.9%
봉 2759
 
7.9%
동 2672
 
7.6%
시 2386
 
6.8%
서 2377
 
6.8%
구 2377
 
6.8%
울 2369
 
6.8%
별 2364
 
6.7%
특 2363
 
6.7%
지 2011
 
5.7%
Other values (281) 10615
30.3%
None
ValueCountFrequency (%)
㈜ 6
100.0%

도로명주소
Text

MISSING 

Distinct1401
Distinct (%)89.5%
Missing799
Missing (%)33.8%
Memory size18.6 KiB
2024-04-30T04:47:04.662164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length56
Mean length33.478594
Min length21

Characters and Unicode

Total characters52394
Distinct characters332
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1279 ?
Unique (%)81.7%

Sample

1st row서울특별시 도봉구 덕릉로 212, 지하1층 (창동)
2nd row서울특별시 도봉구 도봉로110길 9 (창동)
3rd row서울특별시 도봉구 방학로 156 (방학동)
4th row서울특별시 도봉구 덕릉로 253, 지하1층 (창동)
5th row서울특별시 도봉구 삼양로 544 (쌍문동)
ValueCountFrequency (%)
도봉구 1565
 
15.2%
서울특별시 1564
 
15.2%
1층 835
 
8.1%
창동 573
 
5.6%
방학동 342
 
3.3%
쌍문동 338
 
3.3%
도봉동 200
 
1.9%
도봉로 142
 
1.4%
지상1층 120
 
1.2%
마들로11길 88
 
0.9%
Other values (1257) 4552
44.1%
2024-04-30T04:47:05.058455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8755
 
16.7%
1 3274
 
6.2%
도 2480
 
4.7%
봉 2430
 
4.6%
, 1881
 
3.6%
동 1866
 
3.6%
시 1660
 
3.2%
) 1603
 
3.1%
( 1603
 
3.1%
구 1582
 
3.0%
Other values (322) 25260
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29161
55.7%
Decimal Number 9032
 
17.2%
Space Separator 8755
 
16.7%
Other Punctuation 1891
 
3.6%
Close Punctuation 1604
 
3.1%
Open Punctuation 1604
 
3.1%
Uppercase Letter 186
 
0.4%
Dash Punctuation 151
 
0.3%
Other Symbol 6
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 2480
 
8.5%
봉 2430
 
8.3%
동 1866
 
6.4%
시 1660
 
5.7%
구 1582
 
5.4%
서 1578
 
5.4%
울 1570
 
5.4%
특 1564
 
5.4%
별 1564
 
5.4%
로 1560
 
5.3%
Other values (279) 11307
38.8%
Uppercase Letter
ValueCountFrequency (%)
A 44
23.7%
E 36
19.4%
B 22
11.8%
S 20
10.8%
R 13
 
7.0%
M 12
 
6.5%
T 12
 
6.5%
L 6
 
3.2%
G 6
 
3.2%
C 3
 
1.6%
Other values (8) 12
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 3274
36.2%
0 957
 
10.6%
2 950
 
10.5%
6 732
 
8.1%
3 729
 
8.1%
4 650
 
7.2%
5 599
 
6.6%
7 424
 
4.7%
8 387
 
4.3%
9 330
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 1881
99.5%
/ 3
 
0.2%
' 2
 
0.1%
! 2
 
0.1%
. 1
 
0.1%
: 1
 
0.1%
* 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1603
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1603
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8755
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 151
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29167
55.7%
Common 23041
44.0%
Latin 186
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 2480
 
8.5%
봉 2430
 
8.3%
동 1866
 
6.4%
시 1660
 
5.7%
구 1582
 
5.4%
서 1578
 
5.4%
울 1570
 
5.4%
특 1564
 
5.4%
별 1564
 
5.4%
로 1560
 
5.3%
Other values (280) 11313
38.8%
Common
ValueCountFrequency (%)
8755
38.0%
1 3274
 
14.2%
, 1881
 
8.2%
) 1603
 
7.0%
( 1603
 
7.0%
0 957
 
4.2%
2 950
 
4.1%
6 732
 
3.2%
3 729
 
3.2%
4 650
 
2.8%
Other values (14) 1907
 
8.3%
Latin
ValueCountFrequency (%)
A 44
23.7%
E 36
19.4%
B 22
11.8%
S 20
10.8%
R 13
 
7.0%
M 12
 
6.5%
T 12
 
6.5%
L 6
 
3.2%
G 6
 
3.2%
C 3
 
1.6%
Other values (8) 12
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29161
55.7%
ASCII 23227
44.3%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8755
37.7%
1 3274
 
14.1%
, 1881
 
8.1%
) 1603
 
6.9%
( 1603
 
6.9%
0 957
 
4.1%
2 950
 
4.1%
6 732
 
3.2%
3 729
 
3.1%
4 650
 
2.8%
Other values (32) 2093
 
9.0%
Hangul
ValueCountFrequency (%)
도 2480
 
8.5%
봉 2430
 
8.3%
동 1866
 
6.4%
시 1660
 
5.7%
구 1582
 
5.4%
서 1578
 
5.4%
울 1570
 
5.4%
특 1564
 
5.4%
별 1564
 
5.4%
로 1560
 
5.3%
Other values (279) 11307
38.8%
None
ValueCountFrequency (%)
㈜ 6
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct179
Distinct (%)11.5%
Missing813
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean1400.2089
Minimum1300
Maximum11615
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-04-30T04:47:05.189846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1300
5-th percentile1310
Q11348.5
median1397
Q31440
95-th percentile1473
Maximum11615
Range10315
Interquartile range (IQR)91.5

Descriptive statistics

Standard deviation268.2671
Coefficient of variation (CV)0.19159077
Kurtosis1359.5008
Mean1400.2089
Median Absolute Deviation (MAD)46
Skewness35.826401
Sum2171724
Variance71967.238
MonotonicityNot monotonic
2024-04-30T04:47:05.525395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1413 61
 
2.6%
1332 53
 
2.2%
1405 44
 
1.9%
1455 43
 
1.8%
1368 37
 
1.6%
1414 37
 
1.6%
1318 32
 
1.4%
1399 31
 
1.3%
1394 30
 
1.3%
1454 28
 
1.2%
Other values (169) 1155
48.9%
(Missing) 813
34.4%
ValueCountFrequency (%)
1300 3
 
0.1%
1301 8
0.3%
1302 5
 
0.2%
1303 10
0.4%
1304 16
0.7%
1305 6
 
0.3%
1306 1
 
< 0.1%
1307 14
0.6%
1309 7
0.3%
1310 12
0.5%
ValueCountFrequency (%)
11615 1
 
< 0.1%
3109 1
 
< 0.1%
1489 1
 
< 0.1%
1488 1
 
< 0.1%
1487 4
0.2%
1486 3
0.1%
1485 5
0.2%
1484 5
0.2%
1483 1
 
< 0.1%
1482 1
 
< 0.1%

사업장명
Text

Distinct2191
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2024-04-30T04:47:05.759006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length7.2165821
Min length1

Characters and Unicode

Total characters17060
Distinct characters748
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2060 ?
Unique (%)87.1%

Sample

1st row삐에로도봉점
2nd row성수 다방
3rd row산다커피전문점
4th row고개다방
5th row지하다방
ValueCountFrequency (%)
세븐일레븐 35
 
1.2%
창동점 20
 
0.7%
씨유 18
 
0.6%
쌍문점 17
 
0.6%
gs25 15
 
0.5%
방학점 15
 
0.5%
창동역점 14
 
0.5%
쌍문역점 13
 
0.4%
지에스(gs)25 13
 
0.4%
메가엠지씨커피 11
 
0.4%
Other values (2359) 2772
94.2%
2024-04-30T04:47:06.108375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 740
 
4.3%
579
 
3.4%
스 427
 
2.5%
이 400
 
2.3%
( 322
 
1.9%
) 322
 
1.9%
방 320
 
1.9%
피 314
 
1.8%
동 283
 
1.7%
커 266
 
1.6%
Other values (738) 13087
76.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14135
82.9%
Uppercase Letter 671
 
3.9%
Lowercase Letter 616
 
3.6%
Space Separator 579
 
3.4%
Decimal Number 366
 
2.1%
Open Punctuation 322
 
1.9%
Close Punctuation 322
 
1.9%
Other Punctuation 48
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 740
 
5.2%
스 427
 
3.0%
이 400
 
2.8%
방 320
 
2.3%
피 314
 
2.2%
동 283
 
2.0%
커 266
 
1.9%
리 260
 
1.8%
도 256
 
1.8%
창 247
 
1.7%
Other values (665) 10622
75.1%
Uppercase Letter
ValueCountFrequency (%)
S 96
14.3%
C 94
14.0%
G 83
12.4%
P 49
 
7.3%
U 36
 
5.4%
E 34
 
5.1%
A 33
 
4.9%
O 25
 
3.7%
L 22
 
3.3%
T 20
 
3.0%
Other values (16) 179
26.7%
Lowercase Letter
ValueCountFrequency (%)
e 100
16.2%
o 62
 
10.1%
a 57
 
9.3%
f 41
 
6.7%
n 37
 
6.0%
i 36
 
5.8%
t 29
 
4.7%
r 29
 
4.7%
l 27
 
4.4%
c 26
 
4.2%
Other values (15) 172
27.9%
Decimal Number
ValueCountFrequency (%)
2 143
39.1%
5 119
32.5%
1 28
 
7.7%
3 20
 
5.5%
4 16
 
4.4%
0 14
 
3.8%
8 10
 
2.7%
9 9
 
2.5%
7 6
 
1.6%
6 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 14
29.2%
& 14
29.2%
' 9
18.8%
! 4
 
8.3%
. 3
 
6.2%
: 2
 
4.2%
# 1
 
2.1%
? 1
 
2.1%
Space Separator
ValueCountFrequency (%)
579
100.0%
Open Punctuation
ValueCountFrequency (%)
( 322
100.0%
Close Punctuation
ValueCountFrequency (%)
) 322
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14131
82.8%
Common 1638
 
9.6%
Latin 1287
 
7.5%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 740
 
5.2%
스 427
 
3.0%
이 400
 
2.8%
방 320
 
2.3%
피 314
 
2.2%
동 283
 
2.0%
커 266
 
1.9%
리 260
 
1.8%
도 256
 
1.8%
창 247
 
1.7%
Other values (661) 10618
75.1%
Latin
ValueCountFrequency (%)
e 100
 
7.8%
S 96
 
7.5%
C 94
 
7.3%
G 83
 
6.4%
o 62
 
4.8%
a 57
 
4.4%
P 49
 
3.8%
f 41
 
3.2%
n 37
 
2.9%
U 36
 
2.8%
Other values (41) 632
49.1%
Common
ValueCountFrequency (%)
579
35.3%
( 322
19.7%
) 322
19.7%
2 143
 
8.7%
5 119
 
7.3%
1 28
 
1.7%
3 20
 
1.2%
4 16
 
1.0%
0 14
 
0.9%
, 14
 
0.9%
Other values (12) 61
 
3.7%
Han
ValueCountFrequency (%)
日 1
25.0%
月 1
25.0%
飡 1
25.0%
秀 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14131
82.8%
ASCII 2925
 
17.1%
CJK 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 740
 
5.2%
스 427
 
3.0%
이 400
 
2.8%
방 320
 
2.3%
피 314
 
2.2%
동 283
 
2.0%
커 266
 
1.9%
리 260
 
1.8%
도 256
 
1.8%
창 247
 
1.7%
Other values (661) 10618
75.1%
ASCII
ValueCountFrequency (%)
579
19.8%
( 322
 
11.0%
) 322
 
11.0%
2 143
 
4.9%
5 119
 
4.1%
e 100
 
3.4%
S 96
 
3.3%
C 94
 
3.2%
G 83
 
2.8%
o 62
 
2.1%
Other values (63) 1005
34.4%
CJK
ValueCountFrequency (%)
日 1
25.0%
月 1
25.0%
飡 1
25.0%
秀 1
25.0%

최종수정일자
Date

Distinct2022
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
Minimum1999-02-09 00:00:00
Maximum2024-04-25 17:29:23
2024-04-30T04:47:06.231783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:47:06.352673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
I
1582 
U
782 

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 1582
66.9%
U 782
33.1%

Length

2024-04-30T04:47:06.480366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:06.557857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1582
66.9%
u 782
33.1%

데이터갱신일자
Date

Distinct712
Distinct (%)30.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:04:00
2024-04-30T04:47:06.649169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:47:06.773245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct16
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
커피숍
603 
일반조리판매
542 
편의점
305 
다방
242 
기타 휴게음식점
241 
Other values (11)
431 

Length

Max length8
Median length6
Mean length4.2584602
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 603
25.5%
일반조리판매 542
22.9%
편의점 305
12.9%
다방 242
10.2%
기타 휴게음식점 241
 
10.2%
과자점 200
 
8.5%
패스트푸드 172
 
7.3%
백화점 15
 
0.6%
떡카페 13
 
0.5%
푸드트럭 11
 
0.5%
Other values (6) 20
 
0.8%

Length

2024-04-30T04:47:06.916128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 603
23.1%
일반조리판매 542
20.8%
편의점 305
11.7%
다방 242
9.3%
기타 241
 
9.3%
휴게음식점 241
 
9.3%
과자점 200
 
7.7%
패스트푸드 172
 
6.6%
백화점 15
 
0.6%
떡카페 13
 
0.5%
Other values (7) 31
 
1.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1192
Distinct (%)51.7%
Missing57
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean203380.15
Minimum201076.85
Maximum204719.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-04-30T04:47:07.042549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201076.85
5-th percentile201968.49
Q1203017.63
median203469.05
Q3203921.54
95-th percentile204413.62
Maximum204719.28
Range3642.4242
Interquartile range (IQR)903.91745

Descriptive statistics

Standard deviation739.24913
Coefficient of variation (CV)0.0036348146
Kurtosis1.3642212
Mean203380.15
Median Absolute Deviation (MAD)452.22833
Skewness-1.0616577
Sum4.69198 × 108
Variance546489.28
MonotonicityNot monotonic
2024-04-30T04:47:07.182187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204413.616574592 100
 
4.2%
203790.013568785 46
 
1.9%
204107.090272108 38
 
1.6%
203920.444016775 34
 
1.4%
204169.847670316 19
 
0.8%
201393.038238284 16
 
0.7%
203242.968498731 15
 
0.6%
203953.833720651 12
 
0.5%
202966.7837047 11
 
0.5%
203089.442773514 10
 
0.4%
Other values (1182) 2006
84.9%
(Missing) 57
 
2.4%
ValueCountFrequency (%)
201076.85313831 3
0.1%
201080.934192453 3
0.1%
201081.915285607 4
0.2%
201094.369420008 1
 
< 0.1%
201095.903057318 5
0.2%
201098.838622013 2
 
0.1%
201103.54012205 2
 
0.1%
201106.663338126 2
 
0.1%
201109.927189862 2
 
0.1%
201111.814808903 2
 
0.1%
ValueCountFrequency (%)
204719.277363253 1
 
< 0.1%
204682.545958314 1
 
< 0.1%
204569.769384803 3
0.1%
204510.908809878 2
 
0.1%
204506.921108086 2
 
0.1%
204502.118604099 3
0.1%
204488.650732578 1
 
< 0.1%
204468.657003222 6
0.3%
204462.811445887 2
 
0.1%
204428.262955437 6
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1192
Distinct (%)51.7%
Missing57
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean461748.7
Minimum452645.6
Maximum472423.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-04-30T04:47:07.326164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452645.6
5-th percentile459715.87
Q1460890.01
median461513.91
Q3462594.9
95-th percentile464463.4
Maximum472423.07
Range19777.469
Interquartile range (IQR)1704.883

Descriptive statistics

Standard deviation1338.7434
Coefficient of variation (CV)0.00289929
Kurtosis2.4021854
Mean461748.7
Median Absolute Deviation (MAD)921.51381
Skewness0.52253597
Sum1.0652543 × 109
Variance1792233.8
MonotonicityNot monotonic
2024-04-30T04:47:07.457455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461378.588676784 100
 
4.2%
462495.417040876 46
 
1.9%
461072.642448925 38
 
1.6%
462830.484935873 34
 
1.4%
464814.717432497 19
 
0.8%
460991.434614302 16
 
0.7%
460001.081136921 15
 
0.6%
462675.950480622 12
 
0.5%
460551.406386109 11
 
0.5%
461770.488758803 10
 
0.4%
Other values (1182) 2006
84.9%
(Missing) 57
 
2.4%
ValueCountFrequency (%)
452645.597987725 1
 
< 0.1%
458919.238880777 1
 
< 0.1%
458940.711388052 5
0.2%
458968.625259996 1
 
< 0.1%
458990.391547966 1
 
< 0.1%
458996.979353087 1
 
< 0.1%
459013.265219713 1
 
< 0.1%
459026.486447676 1
 
< 0.1%
459038.222873743 2
 
0.1%
459052.547149504 1
 
< 0.1%
ValueCountFrequency (%)
472423.067326834 1
 
< 0.1%
465460.429107353 1
 
< 0.1%
465271.405409815 1
 
< 0.1%
465263.53667852 1
 
< 0.1%
465232.296832032 2
 
0.1%
465180.671733594 8
0.3%
465175.420371013 1
 
< 0.1%
465115.162846828 1
 
< 0.1%
465095.727340317 1
 
< 0.1%
465080.181458971 1
 
< 0.1%

위생업태명
Categorical

Distinct17
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
565 
일반조리판매
475 
커피숍
371 
다방
242 
과자점
200 
Other values (12)
511 

Length

Max length8
Median length6
Mean length4.1302876
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 565
23.9%
일반조리판매 475
20.1%
커피숍 371
15.7%
다방 242
10.2%
과자점 200
 
8.5%
편의점 200
 
8.5%
패스트푸드 155
 
6.6%
기타 휴게음식점 118
 
5.0%
백화점 15
 
0.6%
철도역구내 5
 
0.2%
Other values (7) 18
 
0.8%

Length

2024-04-30T04:47:07.567125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 565
22.8%
일반조리판매 475
19.1%
커피숍 371
14.9%
다방 242
9.8%
과자점 200
 
8.1%
편의점 200
 
8.1%
패스트푸드 155
 
6.2%
기타 118
 
4.8%
휴게음식점 118
 
4.8%
백화점 15
 
0.6%
Other values (8) 23
 
0.9%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.8%
Missing1610
Missing (%)68.1%
Infinite0
Infinite (%)0.0%
Mean0.14058355
Minimum-1
Maximum4
Zeros667
Zeros (%)28.2%
Negative3
Negative (%)0.1%
Memory size20.9 KiB
2024-04-30T04:47:07.659694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum4
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.47388388
Coefficient of variation (CV)3.3708344
Kurtosis23.124663
Mean0.14058355
Median Absolute Deviation (MAD)0
Skewness4.1614917
Sum106
Variance0.22456593
MonotonicityNot monotonic
2024-04-30T04:47:07.750849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 667
28.2%
1 67
 
2.8%
2 12
 
0.5%
4 3
 
0.1%
-1 3
 
0.1%
3 2
 
0.1%
(Missing) 1610
68.1%
ValueCountFrequency (%)
-1 3
 
0.1%
0 667
28.2%
1 67
 
2.8%
2 12
 
0.5%
3 2
 
0.1%
4 3
 
0.1%
ValueCountFrequency (%)
4 3
 
0.1%
3 2
 
0.1%
2 12
 
0.5%
1 67
 
2.8%
0 667
28.2%
-1 3
 
0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.9%
Missing1601
Missing (%)67.7%
Infinite0
Infinite (%)0.0%
Mean0.43643512
Minimum-1
Maximum5
Zeros562
Zeros (%)23.8%
Negative2
Negative (%)0.1%
Memory size20.9 KiB
2024-04-30T04:47:07.843231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.85548033
Coefficient of variation (CV)1.9601546
Kurtosis3.9391933
Mean0.43643512
Median Absolute Deviation (MAD)0
Skewness2.0457516
Sum333
Variance0.73184659
MonotonicityNot monotonic
2024-04-30T04:47:07.920756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 562
 
23.8%
1 103
 
4.4%
2 61
 
2.6%
3 32
 
1.4%
-1 2
 
0.1%
5 2
 
0.1%
4 1
 
< 0.1%
(Missing) 1601
67.7%
ValueCountFrequency (%)
-1 2
 
0.1%
0 562
23.8%
1 103
 
4.4%
2 61
 
2.6%
3 32
 
1.4%
4 1
 
< 0.1%
5 2
 
0.1%
ValueCountFrequency (%)
5 2
 
0.1%
4 1
 
< 0.1%
3 32
 
1.4%
2 61
 
2.6%
1 103
 
4.4%
0 562
23.8%
-1 2
 
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
1911 
주택가주변
256 
기타
 
109
아파트지역
 
73
결혼예식장주변
 
5
Other values (3)
 
10

Length

Max length8
Median length4
Mean length4.07022
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1911
80.8%
주택가주변 256
 
10.8%
기타 109
 
4.6%
아파트지역 73
 
3.1%
결혼예식장주변 5
 
0.2%
학교정화(상대) 4
 
0.2%
유흥업소밀집지역 4
 
0.2%
학교정화(절대) 2
 
0.1%

Length

2024-04-30T04:47:08.014842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:08.118672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1911
80.8%
주택가주변 256
 
10.8%
기타 109
 
4.6%
아파트지역 73
 
3.1%
결혼예식장주변 5
 
0.2%
학교정화(상대 4
 
0.2%
유흥업소밀집지역 4
 
0.2%
학교정화(절대 2
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
1921 
기타
 
172
자율
 
130
지도
 
78
을
 
28
Other values (3)
 
35

Length

Max length4
Median length4
Mean length3.6104061
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1921
81.3%
기타 172
 
7.3%
자율 130
 
5.5%
지도 78
 
3.3%
을 28
 
1.2%
우수 25
 
1.1%
갑 7
 
0.3%
관리 3
 
0.1%

Length

2024-04-30T04:47:08.241355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:08.336168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1921
81.3%
기타 172
 
7.3%
자율 130
 
5.5%
지도 78
 
3.3%
을 28
 
1.2%
우수 25
 
1.1%
갑 7
 
0.3%
관리 3
 
0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
1383 
상수도전용
979 
상수도(음용)지하수(주방용)겸용
 
1
지하수전용
 
1

Length

Max length17
Median length4
Mean length4.4200508
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1383
58.5%
상수도전용 979
41.4%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%
지하수전용 1
 
< 0.1%

Length

2024-04-30T04:47:08.444268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:08.531323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1383
58.5%
상수도전용 979
41.4%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2223 
0
 
141

Length

Max length4
Median length4
Mean length3.821066
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> 2223
94.0%
0 141
 
6.0%

Length

2024-04-30T04:47:08.622759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:08.704497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2223
94.0%
0 141
 
6.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2219 
0
 
145

Length

Max length4
Median length4
Mean length3.8159898
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> 2219
93.9%
0 145
 
6.1%

Length

2024-04-30T04:47:08.789818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:08.870964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2219
93.9%
0 145
 
6.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2219 
0
 
145

Length

Max length4
Median length4
Mean length3.8159898
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> 2219
93.9%
0 145
 
6.1%

Length

2024-04-30T04:47:08.957485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:09.040715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2219
93.9%
0 145
 
6.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2219 
0
 
145

Length

Max length4
Median length4
Mean length3.8159898
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> 2219
93.9%
0 145
 
6.1%

Length

2024-04-30T04:47:09.125271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:09.213488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2219
93.9%
0 145
 
6.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2219 
0
 
145

Length

Max length4
Median length4
Mean length3.8159898
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> 2219
93.9%
0 145
 
6.1%

Length

2024-04-30T04:47:09.302931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:09.382281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2219
93.9%
0 145
 
6.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2364
Missing (%)100.0%
Memory size20.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2219 
0
 
145

Length

Max length4
Median length4
Mean length3.8159898
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> 2219
93.9%
0 145
 
6.1%

Length

2024-04-30T04:47:09.468509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:09.543600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2219
93.9%
0 145
 
6.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2219 
0
 
145

Length

Max length4
Median length4
Mean length3.8159898
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> 2219
93.9%
0 145
 
6.1%

Length

2024-04-30T04:47:09.620211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:09.691903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2219
93.9%
0 145
 
6.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing565
Missing (%)23.9%
Memory size4.7 KiB
False
1779 
True
 
20
(Missing)
565 
ValueCountFrequency (%)
False 1779
75.3%
True 20
 
0.8%
(Missing) 565
 
23.9%
2024-04-30T04:47:09.755366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct925
Distinct (%)51.4%
Missing565
Missing (%)23.9%
Infinite0
Infinite (%)0.0%
Mean37.365281
Minimum0
Maximum700
Zeros105
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-04-30T04:47:09.845499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.9
median24.79
Q345.55
95-th percentile104.46
Maximum700
Range700
Interquartile range (IQR)35.65

Descriptive statistics

Standard deviation51.542052
Coefficient of variation (CV)1.3794103
Kurtosis46.713104
Mean37.365281
Median Absolute Deviation (MAD)16.11
Skewness5.4694328
Sum67220.14
Variance2656.5831
MonotonicityNot monotonic
2024-04-30T04:47:09.954933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 136
 
5.8%
0.0 105
 
4.4%
6.6 74
 
3.1%
23.1 29
 
1.2%
26.4 28
 
1.2%
33.0 28
 
1.2%
9.9 26
 
1.1%
13.2 19
 
0.8%
26.0 17
 
0.7%
20.0 17
 
0.7%
Other values (915) 1320
55.8%
(Missing) 565
23.9%
ValueCountFrequency (%)
0.0 105
4.4%
1.05 1
 
< 0.1%
1.12 1
 
< 0.1%
1.69 1
 
< 0.1%
2.0 2
 
0.1%
2.3 1
 
< 0.1%
2.56 1
 
< 0.1%
2.6 1
 
< 0.1%
2.7 1
 
< 0.1%
3.0 4
 
0.2%
ValueCountFrequency (%)
700.0 1
< 0.1%
600.0 1
< 0.1%
583.13 1
< 0.1%
544.5 1
< 0.1%
470.88 1
< 0.1%
452.0 1
< 0.1%
450.0 1
< 0.1%
391.92 1
< 0.1%
375.0 1
< 0.1%
335.29 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2364
Missing (%)100.0%
Memory size20.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2364
Missing (%)100.0%
Memory size20.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2364
Missing (%)100.0%
Memory size20.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030900003090000-104-1947-0111619470311<NA>3폐업2폐업19980922<NA><NA><NA>023492188422.11132822서울특별시 도봉구 도봉동 634-9번지<NA><NA>삐에로도봉점2002-01-18 00:00:00I2018-08-31 23:59:59.0패스트푸드204052.028207463220.899653패스트푸드<NA><NA>아파트지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N22.11<NA><NA><NA>
130900003090000-104-1970-0144419700701<NA>3폐업2폐업20050920<NA><NA><NA>02 907077161.4132858서울특별시 도봉구 쌍문동 41-3번지<NA><NA>성수 다방2001-10-30 00:00:00I2018-08-31 23:59:59.0다방203304.624854461732.315767다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N61.4<NA><NA><NA>
230900003090000-104-1971-0131519711116<NA>3폐업2폐업20031215<NA><NA><NA>0255.41132819서울특별시 도봉구 도봉동 600-1번지<NA><NA>산다커피전문점2002-11-08 00:00:00I2018-08-31 23:59:59.0다방203868.297542463890.837689다방12주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N55.41<NA><NA><NA>
330900003090000-104-1971-0140919711030<NA>3폐업2폐업19860725<NA><NA><NA>02000000000.0132866서울특별시 도봉구 쌍문동 123-2번지<NA><NA>고개다방2002-01-18 00:00:00I2018-08-31 23:59:59.0다방202729.202501460661.520157다방03아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430900003090000-104-1973-0182319731117<NA>3폐업2폐업19970926<NA><NA><NA>020000000041.16132864서울특별시 도봉구 쌍문동 96-29번지<NA><NA>지하다방2002-01-18 00:00:00I2018-08-31 23:59:59.0다방202918.542479460608.475228다방00주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N41.16<NA><NA><NA>
530900003090000-104-1974-0141019740730<NA>3폐업2폐업19920901<NA><NA><NA>020000000085.31132010서울특별시 도봉구 도봉동 250-13번지<NA><NA>삼양다방2002-01-30 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N85.31<NA><NA><NA>
630900003090000-104-1977-0285219770826<NA>3폐업2폐업20190225<NA><NA><NA>02 9937503100.23132917서울특별시 도봉구 창동 552-42번지 지하1층서울특별시 도봉구 덕릉로 212, 지하1층 (창동)1477원다방2019-02-25 14:39:52U2019-02-27 02:40:00.0다방203191.972289459420.243091다방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N100.23<NA><NA><NA>
730900003090000-104-1977-0462819771221<NA>3폐업2폐업20011219<NA><NA><NA>02 907366077.78132959서울특별시 도봉구 창동 578-142번지<NA><NA>영베이커리2001-12-19 00:00:00I2018-08-31 23:59:59.0과자점203216.530362459520.660717과자점11주택가주변지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N77.78<NA><NA><NA>
830900003090000-104-1978-0283919780302<NA>3폐업2폐업19990909<NA><NA><NA>020983346540.95132917서울특별시 도봉구 창동 568-7번지<NA><NA>고려제과2002-01-18 00:00:00I2018-08-31 23:59:59.0과자점<NA><NA>과자점21주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.95<NA><NA><NA>
930900003090000-104-1979-0203319790810<NA>3폐업2폐업19991215<NA><NA><NA>020903545543.45132850서울특별시 도봉구 방학동 682-33번지<NA><NA>고려베이커리2002-01-18 00:00:00I2018-08-31 23:59:59.0과자점203616.697316462479.758657과자점22주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.45<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
235430900003090000-104-2024-000212024-03-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>62.09132-885서울특별시 도봉구 쌍문동 423-2 쌍문동 덕성여대역리가 빌딩서울특별시 도봉구 삼양로 538-5, 1층 103호 (쌍문동, 쌍문동 덕성여대역리가 빌딩)1368메가엠지씨커피 덕성여대점2024-04-01 17:29:30U2023-12-04 00:03:00.0커피숍201112.008025460988.148093<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235530900003090000-104-2024-000222024-03-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>78.1132-843서울특별시 도봉구 방학동 633-15 2층서울특별시 도봉구 도당로13가길 17, 2층 (방학동)1355힐링사랑방2024-03-12 14:02:25I2023-12-02 23:04:00.0기타 휴게음식점203123.852636462618.006267<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235630900003090000-104-2024-000232024-03-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>99.65132-906서울특별시 도봉구 창동 219-5 1층서울특별시 도봉구 도봉로136가길 69, 1층 (창동)1400커피홀 창동점2024-03-15 14:07:20I2023-12-02 23:07:00.0커피숍203690.345158461528.669311<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235730900003090000-104-2024-000242024-03-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>89.25132-904서울특별시 도봉구 창동 134-36 우림빌딩서울특별시 도봉구 노해로63길 79, 우림빌딩 2층 206호 (창동)1399창동역점 설빙2024-03-19 16:18:13I2023-12-02 22:01:00.0기타 휴게음식점204011.919617461194.791887<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235830900003090000-104-2024-000252024-03-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.0132-890서울특별시 도봉구 쌍문동 507-1 에드가쌍문서울특별시 도봉구 삼양로 602, 1층 104호 (쌍문동, 에드가쌍문)1366씨유 솔밭공원역점2024-03-25 15:00:40I2023-12-02 22:07:00.0편의점201154.262049461576.90605<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235930900003090000-104-2024-000262024-03-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3132-884서울특별시 도봉구 쌍문동 378서울특별시 도봉구 노해로 149, 1층 (쌍문동)1381지에스(GS)25 도봉우체국점2024-03-25 16:35:02I2023-12-02 22:07:00.0편의점202243.247665460642.094501<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
236030900003090000-104-2024-000272024-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.84132-885서울특별시 도봉구 쌍문동 419서울특별시 도봉구 삼양로144길 33, 덕성여자대학교 예술관 앞 노천카페 (쌍문동)1369카페아이엔지 덕성여대점2024-03-29 15:31:51I2023-12-02 21:01:00.0커피숍201393.038238460991.434614<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
236130900003090000-104-2024-000282024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.0132-906서울특별시 도봉구 창동 254-35서울특별시 도봉구 노해로63가길 12, 1층 (창동)1399매머드 익스프레스 창동역2번출구점2024-04-01 16:08:50I2023-12-04 00:03:00.0커피숍203921.890231461205.974818<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
236230900003090000-104-2024-000292024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3132-867서울특별시 도봉구 쌍문동 139-1서울특별시 도봉구 노해로 206, 1층 (쌍문동)1441지에스(GS)25 쌍문노해로점2024-04-15 09:57:55I2023-12-03 23:07:00.0편의점202663.246206460934.324974<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
236330900003090000-104-2024-000302024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.5132-850서울특별시 도봉구 방학동 683-33서울특별시 도봉구 방학로2길 50, 1층 (방학동)1340UNI 투어2024-04-15 13:52:59I2023-12-03 23:07:00.0기타 휴게음식점203549.640253462535.544219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>