Overview

Dataset statistics

Number of variables44
Number of observations2528
Missing cells27202
Missing cells (%)24.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory930.8 KiB
Average record size in memory377.1 B

Variable types

Categorical19
Text6
DateTime4
Unsupported8
Numeric6
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
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-18685/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (59.6%)Imbalance
등급구분명 is highly imbalanced (56.0%)Imbalance
총인원 is highly imbalanced (64.0%)Imbalance
본사종업원수 is highly imbalanced (64.0%)Imbalance
공장사무직종업원수 is highly imbalanced (64.0%)Imbalance
공장판매직종업원수 is highly imbalanced (64.0%)Imbalance
공장생산직종업원수 is highly imbalanced (64.0%)Imbalance
보증액 is highly imbalanced (64.0%)Imbalance
월세액 is highly imbalanced (64.0%)Imbalance
다중이용업소여부 is highly imbalanced (94.8%)Imbalance
인허가취소일자 has 2528 (100.0%) missing valuesMissing
폐업일자 has 771 (30.5%) missing valuesMissing
휴업시작일자 has 2528 (100.0%) missing valuesMissing
휴업종료일자 has 2528 (100.0%) missing valuesMissing
재개업일자 has 2528 (100.0%) missing valuesMissing
전화번호 has 1397 (55.3%) missing valuesMissing
소재지면적 has 112 (4.4%) missing valuesMissing
도로명주소 has 819 (32.4%) missing valuesMissing
도로명우편번호 has 828 (32.8%) missing valuesMissing
좌표정보(X) has 72 (2.8%) missing valuesMissing
좌표정보(Y) has 72 (2.8%) missing valuesMissing
남성종사자수 has 1625 (64.3%) missing valuesMissing
건물소유구분명 has 2528 (100.0%) missing valuesMissing
다중이용업소여부 has 639 (25.3%) missing valuesMissing
시설총규모 has 639 (25.3%) missing valuesMissing
전통업소지정번호 has 2528 (100.0%) missing valuesMissing
전통업소주된음식 has 2528 (100.0%) missing valuesMissing
홈페이지 has 2528 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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 763 (30.2%) zerosZeros
시설총규모 has 115 (4.5%) zerosZeros

Reproduction

Analysis started2024-05-11 07:52:52.099979
Analysis finished2024-05-11 07:52:56.175723
Duration4.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
3080000
2528 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 2528
100.0%

Length

2024-05-11T07:52:56.571463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:52:57.053602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 2528
100.0%

관리번호
Text

UNIQUE 

Distinct2528
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
2024-05-11T07:52:57.609104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters55616
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

Unique2528 ?
Unique (%)100.0%

Sample

1st row3080000-104-1968-01593
2nd row3080000-104-1968-01758
3rd row3080000-104-1969-01479
4th row3080000-104-1969-01763
5th row3080000-104-1969-01879
ValueCountFrequency (%)
3080000-104-1968-01593 1
 
< 0.1%
3080000-104-2017-00107 1
 
< 0.1%
3080000-104-2017-00109 1
 
< 0.1%
3080000-104-2017-00101 1
 
< 0.1%
3080000-104-2017-00102 1
 
< 0.1%
3080000-104-2017-00103 1
 
< 0.1%
3080000-104-2017-00104 1
 
< 0.1%
3080000-104-2017-00105 1
 
< 0.1%
3080000-104-2017-00106 1
 
< 0.1%
3080000-104-2017-00099 1
 
< 0.1%
Other values (2518) 2518
99.6%
2024-05-11T07:52:58.846317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24213
43.5%
- 7584
 
13.6%
1 6019
 
10.8%
8 3531
 
6.3%
3 3403
 
6.1%
4 3388
 
6.1%
2 3320
 
6.0%
9 1727
 
3.1%
7 863
 
1.6%
6 797
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48032
86.4%
Dash Punctuation 7584
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24213
50.4%
1 6019
 
12.5%
8 3531
 
7.4%
3 3403
 
7.1%
4 3388
 
7.1%
2 3320
 
6.9%
9 1727
 
3.6%
7 863
 
1.8%
6 797
 
1.7%
5 771
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 7584
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55616
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24213
43.5%
- 7584
 
13.6%
1 6019
 
10.8%
8 3531
 
6.3%
3 3403
 
6.1%
4 3388
 
6.1%
2 3320
 
6.0%
9 1727
 
3.1%
7 863
 
1.6%
6 797
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55616
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24213
43.5%
- 7584
 
13.6%
1 6019
 
10.8%
8 3531
 
6.3%
3 3403
 
6.1%
4 3388
 
6.1%
2 3320
 
6.0%
9 1727
 
3.1%
7 863
 
1.6%
6 797
 
1.4%
Distinct2058
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
Minimum1968-06-11 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T07:52:59.293144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:53:00.046874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2528
Missing (%)100.0%
Memory size22.3 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
3
1757 
1
771 

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 1757
69.5%
1 771
30.5%

Length

2024-05-11T07:53:00.561124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:00.824016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1757
69.5%
1 771
30.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
폐업
1757 
영업/정상
771 

Length

Max length5
Median length2
Mean length2.9149525
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1757
69.5%
영업/정상 771
30.5%

Length

2024-05-11T07:53:01.353857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:01.793890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1757
69.5%
영업/정상 771
30.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
2
1757 
1
771 

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 1757
69.5%
1 771
30.5%

Length

2024-05-11T07:53:02.274700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:02.707133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1757
69.5%
1 771
30.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
폐업
1757 
영업
771 

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 1757
69.5%
영업 771
30.5%

Length

2024-05-11T07:53:03.159756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:03.725652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1757
69.5%
영업 771
30.5%

폐업일자
Date

MISSING 

Distinct1404
Distinct (%)79.9%
Missing771
Missing (%)30.5%
Memory size19.9 KiB
Minimum1979-11-12 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T07:53:04.297936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:53:04.946925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2528
Missing (%)100.0%
Memory size22.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2528
Missing (%)100.0%
Memory size22.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2528
Missing (%)100.0%
Memory size22.3 KiB

전화번호
Text

MISSING 

Distinct963
Distinct (%)85.1%
Missing1397
Missing (%)55.3%
Memory size19.9 KiB
2024-05-11T07:53:06.031302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.219275
Min length2

Characters and Unicode

Total characters11558
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

Unique925 ?
Unique (%)81.8%

Sample

1st row02 00000
2nd row02 9884607
3rd row02 9941552
4th row02 9894229
5th row02 9545767
ValueCountFrequency (%)
02 974
41.8%
00000 61
 
2.6%
0200000000 24
 
1.0%
070 19
 
0.8%
987 16
 
0.7%
980 14
 
0.6%
999 14
 
0.6%
945 13
 
0.6%
900 13
 
0.6%
988 12
 
0.5%
Other values (1010) 1168
50.2%
2024-05-11T07:53:07.469102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2552
22.1%
2 1678
14.5%
1635
14.1%
9 1531
13.2%
8 940
 
8.1%
4 594
 
5.1%
5 593
 
5.1%
7 529
 
4.6%
1 524
 
4.5%
3 516
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9923
85.9%
Space Separator 1635
 
14.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2552
25.7%
2 1678
16.9%
9 1531
15.4%
8 940
 
9.5%
4 594
 
6.0%
5 593
 
6.0%
7 529
 
5.3%
1 524
 
5.3%
3 516
 
5.2%
6 466
 
4.7%
Space Separator
ValueCountFrequency (%)
1635
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11558
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2552
22.1%
2 1678
14.5%
1635
14.1%
9 1531
13.2%
8 940
 
8.1%
4 594
 
5.1%
5 593
 
5.1%
7 529
 
4.6%
1 524
 
4.5%
3 516
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11558
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2552
22.1%
2 1678
14.5%
1635
14.1%
9 1531
13.2%
8 940
 
8.1%
4 594
 
5.1%
5 593
 
5.1%
7 529
 
4.6%
1 524
 
4.5%
3 516
 
4.5%

소재지면적
Real number (ℝ)

MISSING 

Distinct1372
Distinct (%)56.8%
Missing112
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean43.306863
Minimum0
Maximum461
Zeros18
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size22.3 KiB
2024-05-11T07:53:08.066146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q113.2
median28
Q358.6125
95-th percentile124.3025
Maximum461
Range461
Interquartile range (IQR)45.4125

Descriptive statistics

Standard deviation48.791045
Coefficient of variation (CV)1.1266354
Kurtosis17.323695
Mean43.306863
Median Absolute Deviation (MAD)19
Skewness3.2924689
Sum104629.38
Variance2380.5661
MonotonicityNot monotonic
2024-05-11T07:53:08.522292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 162
 
6.4%
6.6 60
 
2.4%
10.0 34
 
1.3%
30.0 30
 
1.2%
5.0 29
 
1.1%
33.0 28
 
1.1%
20.0 25
 
1.0%
15.0 19
 
0.8%
27.0 18
 
0.7%
9.9 18
 
0.7%
Other values (1362) 1993
78.8%
(Missing) 112
 
4.4%
ValueCountFrequency (%)
0.0 18
0.7%
0.9 1
 
< 0.1%
1.0 3
 
0.1%
1.02 1
 
< 0.1%
1.2 1
 
< 0.1%
1.38 1
 
< 0.1%
1.56 2
 
0.1%
1.93 1
 
< 0.1%
2.0 4
 
0.2%
2.05 1
 
< 0.1%
ValueCountFrequency (%)
461.0 1
< 0.1%
441.61 1
< 0.1%
434.98 1
< 0.1%
425.78 1
< 0.1%
425.09 1
< 0.1%
425.0 1
< 0.1%
422.89 1
< 0.1%
386.76 1
< 0.1%
380.0 1
< 0.1%
350.14 1
< 0.1%
Distinct128
Distinct (%)5.1%
Missing2
Missing (%)0.1%
Memory size19.9 KiB
2024-05-11T07:53:09.534670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1666667
Min length6

Characters and Unicode

Total characters15577
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

Unique16 ?
Unique (%)0.6%

Sample

1st row142804
2nd row142805
3rd row142876
4th row142804
5th row142817
ValueCountFrequency (%)
142804 237
 
9.4%
142878 126
 
5.0%
142100 99
 
3.9%
142874 85
 
3.4%
142070 82
 
3.2%
142805 79
 
3.1%
142864 69
 
2.7%
142876 66
 
2.6%
142877 59
 
2.3%
142886 58
 
2.3%
Other values (118) 1566
62.0%
2024-05-11T07:53:10.963295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3136
20.1%
4 3040
19.5%
2 2911
18.7%
8 2706
17.4%
0 1283
8.2%
7 921
 
5.9%
6 578
 
3.7%
- 421
 
2.7%
5 237
 
1.5%
9 196
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15156
97.3%
Dash Punctuation 421
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3136
20.7%
4 3040
20.1%
2 2911
19.2%
8 2706
17.9%
0 1283
8.5%
7 921
 
6.1%
6 578
 
3.8%
5 237
 
1.6%
9 196
 
1.3%
3 148
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 421
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15577
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3136
20.1%
4 3040
19.5%
2 2911
18.7%
8 2706
17.4%
0 1283
8.2%
7 921
 
5.9%
6 578
 
3.7%
- 421
 
2.7%
5 237
 
1.5%
9 196
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15577
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3136
20.1%
4 3040
19.5%
2 2911
18.7%
8 2706
17.4%
0 1283
8.2%
7 921
 
5.9%
6 578
 
3.7%
- 421
 
2.7%
5 237
 
1.5%
9 196
 
1.3%
Distinct2114
Distinct (%)83.7%
Missing2
Missing (%)0.1%
Memory size19.9 KiB
2024-05-11T07:53:12.135161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length24.482581
Min length17

Characters and Unicode

Total characters61843
Distinct characters315
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

Unique1857 ?
Unique (%)73.5%

Sample

1st row서울특별시 강북구 미아동 70-26번지
2nd row서울특별시 강북구 미아동 465-6번지
3rd row서울특별시 강북구 수유동 174-1번지
4th row서울특별시 강북구 미아동 67-1번지
5th row서울특별시 강북구 미아동 628-11번지
ValueCountFrequency (%)
서울특별시 2526
21.6%
강북구 2526
21.6%
미아동 1153
 
9.9%
수유동 912
 
7.8%
번동 372
 
3.2%
1층 232
 
2.0%
지상1층 97
 
0.8%
우이동 90
 
0.8%
롯데백화점 72
 
0.6%
70-6번지 70
 
0.6%
Other values (2363) 3648
31.2%
2024-05-11T07:53:14.017295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11006
 
17.8%
1 2644
 
4.3%
2594
 
4.2%
2562
 
4.1%
2556
 
4.1%
2546
 
4.1%
2543
 
4.1%
2536
 
4.1%
2534
 
4.1%
2529
 
4.1%
Other values (305) 27793
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35019
56.6%
Decimal Number 12605
 
20.4%
Space Separator 11006
 
17.8%
Dash Punctuation 2429
 
3.9%
Open Punctuation 338
 
0.5%
Close Punctuation 338
 
0.5%
Uppercase Letter 44
 
0.1%
Other Punctuation 40
 
0.1%
Lowercase Letter 19
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2594
 
7.4%
2562
 
7.3%
2556
 
7.3%
2546
 
7.3%
2543
 
7.3%
2536
 
7.2%
2534
 
7.2%
2529
 
7.2%
2526
 
7.2%
1826
 
5.2%
Other values (262) 10267
29.3%
Uppercase Letter
ValueCountFrequency (%)
B 14
31.8%
K 8
18.2%
A 4
 
9.1%
S 4
 
9.1%
J 3
 
6.8%
H 2
 
4.5%
G 2
 
4.5%
M 2
 
4.5%
Y 1
 
2.3%
T 1
 
2.3%
Other values (3) 3
 
6.8%
Lowercase Letter
ValueCountFrequency (%)
a 3
15.8%
p 3
15.8%
e 2
10.5%
t 2
10.5%
m 2
10.5%
i 1
 
5.3%
y 1
 
5.3%
b 1
 
5.3%
k 1
 
5.3%
s 1
 
5.3%
Other values (2) 2
10.5%
Decimal Number
ValueCountFrequency (%)
1 2644
21.0%
2 1563
12.4%
4 1379
10.9%
3 1350
10.7%
6 1115
8.8%
5 1062
8.4%
7 1021
 
8.1%
0 977
 
7.8%
8 835
 
6.6%
9 659
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 33
82.5%
. 6
 
15.0%
@ 1
 
2.5%
Space Separator
ValueCountFrequency (%)
11006
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2429
100.0%
Open Punctuation
ValueCountFrequency (%)
( 338
100.0%
Close Punctuation
ValueCountFrequency (%)
) 338
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35019
56.6%
Common 26761
43.3%
Latin 63
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2594
 
7.4%
2562
 
7.3%
2556
 
7.3%
2546
 
7.3%
2543
 
7.3%
2536
 
7.2%
2534
 
7.2%
2529
 
7.2%
2526
 
7.2%
1826
 
5.2%
Other values (262) 10267
29.3%
Latin
ValueCountFrequency (%)
B 14
22.2%
K 8
12.7%
A 4
 
6.3%
S 4
 
6.3%
J 3
 
4.8%
a 3
 
4.8%
p 3
 
4.8%
H 2
 
3.2%
e 2
 
3.2%
t 2
 
3.2%
Other values (15) 18
28.6%
Common
ValueCountFrequency (%)
11006
41.1%
1 2644
 
9.9%
- 2429
 
9.1%
2 1563
 
5.8%
4 1379
 
5.2%
3 1350
 
5.0%
6 1115
 
4.2%
5 1062
 
4.0%
7 1021
 
3.8%
0 977
 
3.7%
Other values (8) 2215
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35019
56.6%
ASCII 26824
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11006
41.0%
1 2644
 
9.9%
- 2429
 
9.1%
2 1563
 
5.8%
4 1379
 
5.1%
3 1350
 
5.0%
6 1115
 
4.2%
5 1062
 
4.0%
7 1021
 
3.8%
0 977
 
3.6%
Other values (33) 2278
 
8.5%
Hangul
ValueCountFrequency (%)
2594
 
7.4%
2562
 
7.3%
2556
 
7.3%
2546
 
7.3%
2543
 
7.3%
2536
 
7.2%
2534
 
7.2%
2529
 
7.2%
2526
 
7.2%
1826
 
5.2%
Other values (262) 10267
29.3%

도로명주소
Text

MISSING 

Distinct1477
Distinct (%)86.4%
Missing819
Missing (%)32.4%
Memory size19.9 KiB
2024-05-11T07:53:14.979665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length54
Mean length30.686951
Min length21

Characters and Unicode

Total characters52444
Distinct characters312
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

Unique1341 ?
Unique (%)78.5%

Sample

1st row서울특별시 강북구 도봉로 242 (미아동)
2nd row서울특별시 강북구 솔샘로 246 (미아동)
3rd row서울특별시 강북구 4.19로 135, 아카데미하우스 (수유동)
4th row서울특별시 강북구 도봉로8길 70 (미아동)
5th row서울특별시 강북구 한천로 1073-13 (수유동)
ValueCountFrequency (%)
서울특별시 1708
16.2%
강북구 1708
16.2%
1층 791
 
7.5%
미아동 693
 
6.6%
수유동 538
 
5.1%
도봉로 305
 
2.9%
번동 232
 
2.2%
삼양로 153
 
1.4%
62 128
 
1.2%
지하2층 90
 
0.9%
Other values (1280) 4228
40.0%
2024-05-11T07:53:16.451221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8866
 
16.9%
1 2559
 
4.9%
( 1884
 
3.6%
) 1884
 
3.6%
1804
 
3.4%
1786
 
3.4%
1747
 
3.3%
1733
 
3.3%
1729
 
3.3%
1728
 
3.3%
Other values (302) 26724
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29755
56.7%
Space Separator 8866
 
16.9%
Decimal Number 8303
 
15.8%
Open Punctuation 1884
 
3.6%
Close Punctuation 1884
 
3.6%
Other Punctuation 1526
 
2.9%
Dash Punctuation 140
 
0.3%
Uppercase Letter 58
 
0.1%
Lowercase Letter 18
 
< 0.1%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1804
 
6.1%
1786
 
6.0%
1747
 
5.9%
1733
 
5.8%
1729
 
5.8%
1728
 
5.8%
1721
 
5.8%
1717
 
5.8%
1711
 
5.8%
1709
 
5.7%
Other values (260) 12370
41.6%
Uppercase Letter
ValueCountFrequency (%)
B 27
46.6%
A 7
 
12.1%
K 6
 
10.3%
J 3
 
5.2%
G 2
 
3.4%
S 2
 
3.4%
H 2
 
3.4%
T 2
 
3.4%
M 2
 
3.4%
N 1
 
1.7%
Other values (4) 4
 
6.9%
Decimal Number
ValueCountFrequency (%)
1 2559
30.8%
2 1134
13.7%
3 929
 
11.2%
4 613
 
7.4%
0 592
 
7.1%
7 555
 
6.7%
6 553
 
6.7%
5 502
 
6.0%
9 455
 
5.5%
8 411
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
a 3
16.7%
p 3
16.7%
b 2
11.1%
t 2
11.1%
m 2
11.1%
e 2
11.1%
i 1
 
5.6%
y 1
 
5.6%
n 1
 
5.6%
r 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 1504
98.6%
. 20
 
1.3%
? 2
 
0.1%
Space Separator
ValueCountFrequency (%)
8866
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1884
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1884
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29755
56.7%
Common 22613
43.1%
Latin 76
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1804
 
6.1%
1786
 
6.0%
1747
 
5.9%
1733
 
5.8%
1729
 
5.8%
1728
 
5.8%
1721
 
5.8%
1717
 
5.8%
1711
 
5.8%
1709
 
5.7%
Other values (260) 12370
41.6%
Latin
ValueCountFrequency (%)
B 27
35.5%
A 7
 
9.2%
K 6
 
7.9%
a 3
 
3.9%
p 3
 
3.9%
J 3
 
3.9%
G 2
 
2.6%
S 2
 
2.6%
H 2
 
2.6%
b 2
 
2.6%
Other values (14) 19
25.0%
Common
ValueCountFrequency (%)
8866
39.2%
1 2559
 
11.3%
( 1884
 
8.3%
) 1884
 
8.3%
, 1504
 
6.7%
2 1134
 
5.0%
3 929
 
4.1%
4 613
 
2.7%
0 592
 
2.6%
7 555
 
2.5%
Other values (8) 2093
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29755
56.7%
ASCII 22689
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8866
39.1%
1 2559
 
11.3%
( 1884
 
8.3%
) 1884
 
8.3%
, 1504
 
6.6%
2 1134
 
5.0%
3 929
 
4.1%
4 613
 
2.7%
0 592
 
2.6%
7 555
 
2.4%
Other values (32) 2169
 
9.6%
Hangul
ValueCountFrequency (%)
1804
 
6.1%
1786
 
6.0%
1747
 
5.9%
1733
 
5.8%
1729
 
5.8%
1728
 
5.8%
1721
 
5.8%
1717
 
5.8%
1711
 
5.8%
1709
 
5.7%
Other values (260) 12370
41.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct213
Distinct (%)12.5%
Missing828
Missing (%)32.8%
Infinite0
Infinite (%)0.0%
Mean1125.8365
Minimum1000
Maximum1237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.3 KiB
2024-05-11T07:53:17.040874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1022
Q11065
median1118
Q31194
95-th percentile1224
Maximum1237
Range237
Interquartile range (IQR)129

Descriptive statistics

Standard deviation68.869594
Coefficient of variation (CV)0.061171933
Kurtosis-1.3520905
Mean1125.8365
Median Absolute Deviation (MAD)61
Skewness0.031093832
Sum1913922
Variance4743.0209
MonotonicityNot monotonic
2024-05-11T07:53:17.556437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1215 132
 
5.2%
1062 30
 
1.2%
1157 27
 
1.1%
1056 27
 
1.1%
1220 25
 
1.0%
1233 23
 
0.9%
1072 23
 
0.9%
1117 23
 
0.9%
1070 22
 
0.9%
1074 20
 
0.8%
Other values (203) 1348
53.3%
(Missing) 828
32.8%
ValueCountFrequency (%)
1000 2
 
0.1%
1001 1
 
< 0.1%
1002 11
0.4%
1004 2
 
0.1%
1005 8
0.3%
1006 15
0.6%
1009 8
0.3%
1010 8
0.3%
1011 7
0.3%
1012 1
 
< 0.1%
ValueCountFrequency (%)
1237 10
0.4%
1234 3
 
0.1%
1233 23
0.9%
1232 5
 
0.2%
1231 5
 
0.2%
1230 5
 
0.2%
1228 12
0.5%
1227 2
 
0.1%
1226 14
0.6%
1224 9
 
0.4%
Distinct2347
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
2024-05-11T07:53:18.544319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length7.3275316
Min length1

Characters and Unicode

Total characters18524
Distinct characters765
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2208 ?
Unique (%)87.3%

Sample

1st row대호다방
2nd row양지
3rd row새다방
4th row연꽃다방
5th row부산뉴욕제과
ValueCountFrequency (%)
씨유 70
 
1.9%
세븐일레븐 64
 
1.8%
gs25 56
 
1.5%
수유점 42
 
1.1%
카페 38
 
1.0%
미아점 37
 
1.0%
수유역점 30
 
0.8%
커피 30
 
0.8%
미아역점 17
 
0.5%
지에스(gs)25 16
 
0.4%
Other values (2554) 3257
89.1%
2024-05-11T07:53:20.090739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1130
 
6.1%
771
 
4.2%
426
 
2.3%
416
 
2.2%
391
 
2.1%
388
 
2.1%
374
 
2.0%
364
 
2.0%
361
 
1.9%
334
 
1.8%
Other values (755) 13569
73.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14692
79.3%
Space Separator 1130
 
6.1%
Lowercase Letter 832
 
4.5%
Uppercase Letter 765
 
4.1%
Decimal Number 460
 
2.5%
Open Punctuation 286
 
1.5%
Close Punctuation 286
 
1.5%
Other Punctuation 60
 
0.3%
Dash Punctuation 11
 
0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
771
 
5.2%
426
 
2.9%
416
 
2.8%
391
 
2.7%
388
 
2.6%
374
 
2.5%
364
 
2.5%
361
 
2.5%
334
 
2.3%
322
 
2.2%
Other values (681) 10545
71.8%
Lowercase Letter
ValueCountFrequency (%)
e 131
15.7%
a 89
 
10.7%
o 73
 
8.8%
f 58
 
7.0%
c 57
 
6.9%
s 44
 
5.3%
r 43
 
5.2%
n 37
 
4.4%
l 37
 
4.4%
t 35
 
4.2%
Other values (15) 228
27.4%
Uppercase Letter
ValueCountFrequency (%)
S 120
15.7%
C 118
15.4%
G 112
14.6%
P 49
 
6.4%
E 44
 
5.8%
O 36
 
4.7%
U 32
 
4.2%
A 31
 
4.1%
F 30
 
3.9%
B 24
 
3.1%
Other values (15) 169
22.1%
Decimal Number
ValueCountFrequency (%)
2 161
35.0%
5 131
28.5%
1 55
 
12.0%
4 39
 
8.5%
9 29
 
6.3%
3 16
 
3.5%
0 10
 
2.2%
7 8
 
1.7%
8 7
 
1.5%
6 4
 
0.9%
Other Punctuation
ValueCountFrequency (%)
& 17
28.3%
. 14
23.3%
' 7
11.7%
, 7
11.7%
? 6
 
10.0%
! 4
 
6.7%
4
 
6.7%
/ 1
 
1.7%
Space Separator
ValueCountFrequency (%)
1130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 286
100.0%
Close Punctuation
ValueCountFrequency (%)
) 286
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14687
79.3%
Common 2235
 
12.1%
Latin 1597
 
8.6%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
771
 
5.2%
426
 
2.9%
416
 
2.8%
391
 
2.7%
388
 
2.6%
374
 
2.5%
364
 
2.5%
361
 
2.5%
334
 
2.3%
322
 
2.2%
Other values (676) 10540
71.8%
Latin
ValueCountFrequency (%)
e 131
 
8.2%
S 120
 
7.5%
C 118
 
7.4%
G 112
 
7.0%
a 89
 
5.6%
o 73
 
4.6%
f 58
 
3.6%
c 57
 
3.6%
P 49
 
3.1%
s 44
 
2.8%
Other values (40) 746
46.7%
Common
ValueCountFrequency (%)
1130
50.6%
( 286
 
12.8%
) 286
 
12.8%
2 161
 
7.2%
5 131
 
5.9%
1 55
 
2.5%
4 39
 
1.7%
9 29
 
1.3%
& 17
 
0.8%
3 16
 
0.7%
Other values (14) 85
 
3.8%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14687
79.3%
ASCII 3828
 
20.7%
CJK 5
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1130
29.5%
( 286
 
7.5%
) 286
 
7.5%
2 161
 
4.2%
e 131
 
3.4%
5 131
 
3.4%
S 120
 
3.1%
C 118
 
3.1%
G 112
 
2.9%
a 89
 
2.3%
Other values (63) 1264
33.0%
Hangul
ValueCountFrequency (%)
771
 
5.2%
426
 
2.9%
416
 
2.8%
391
 
2.7%
388
 
2.6%
374
 
2.5%
364
 
2.5%
361
 
2.5%
334
 
2.3%
322
 
2.2%
Other values (676) 10540
71.8%
None
ValueCountFrequency (%)
4
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Distinct2050
Distinct (%)81.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
Minimum1999-01-09 00:00:00
Maximum2024-05-08 16:12:11
2024-05-11T07:53:20.657762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:53:21.285104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
I
1553 
U
975 

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 1553
61.4%
U 975
38.6%

Length

2024-05-11T07:53:21.717526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:22.032599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1553
61.4%
u 975
38.6%
Distinct730
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T07:53:22.342202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:53:22.762751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct15
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
기타 휴게음식점
682 
커피숍
530 
다방
410 
편의점
266 
과자점
227 
Other values (10)
413 

Length

Max length8
Median length6
Mean length4.5644778
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 휴게음식점 682
27.0%
커피숍 530
21.0%
다방 410
16.2%
편의점 266
 
10.5%
과자점 227
 
9.0%
일반조리판매 200
 
7.9%
패스트푸드 162
 
6.4%
백화점 16
 
0.6%
유원지 8
 
0.3%
푸드트럭 8
 
0.3%
Other values (5) 19
 
0.8%

Length

2024-05-11T07:53:23.209575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 682
21.2%
휴게음식점 682
21.2%
커피숍 530
16.5%
다방 410
12.8%
편의점 266
 
8.3%
과자점 227
 
7.1%
일반조리판매 200
 
6.2%
패스트푸드 162
 
5.0%
백화점 16
 
0.5%
유원지 8
 
0.2%
Other values (6) 27
 
0.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1413
Distinct (%)57.5%
Missing72
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean202074.13
Minimum200020.57
Maximum204157.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.3 KiB
2024-05-11T07:53:23.617862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200020.57
5-th percentile201045.61
Q1201594.47
median202097.84
Q3202545.68
95-th percentile203041.56
Maximum204157.84
Range4137.2715
Interquartile range (IQR)951.20863

Descriptive statistics

Standard deviation639.93888
Coefficient of variation (CV)0.0031668521
Kurtosis-0.054109105
Mean202074.13
Median Absolute Deviation (MAD)472.52516
Skewness0.1111757
Sum4.9629406 × 108
Variance409521.76
MonotonicityNot monotonic
2024-05-11T07:53:24.142459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202625.646264572 134
 
5.3%
202642.446045912 18
 
0.7%
201956.180985499 16
 
0.6%
201059.873232343 13
 
0.5%
201494.627293774 12
 
0.5%
203540.984593238 11
 
0.4%
201589.777957863 10
 
0.4%
201762.419935414 10
 
0.4%
202611.080917488 9
 
0.4%
201760.433753367 8
 
0.3%
Other values (1403) 2215
87.6%
(Missing) 72
 
2.8%
ValueCountFrequency (%)
200020.571943402 1
< 0.1%
200234.13213979 1
< 0.1%
200293.660373936 1
< 0.1%
200327.963390043 1
< 0.1%
200425.020654375 1
< 0.1%
200480.247178897 1
< 0.1%
200521.819348065 1
< 0.1%
200540.026077316 1
< 0.1%
200550.98632709 1
< 0.1%
200557.727235667 1
< 0.1%
ValueCountFrequency (%)
204157.843492258 1
 
< 0.1%
204009.82728814 1
 
< 0.1%
203981.35 5
0.2%
203932.991517795 2
 
0.1%
203923.583561403 1
 
< 0.1%
203920.882629874 3
0.1%
203895.660018622 1
 
< 0.1%
203812.72109062 2
 
0.1%
203798.294450074 2
 
0.1%
203796.175115204 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1413
Distinct (%)57.5%
Missing72
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean458638.56
Minimum456422.95
Maximum462575.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.3 KiB
2024-05-11T07:53:24.628059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456422.95
5-th percentile456742.09
Q1457506.58
median458735.29
Q3459620.74
95-th percentile460566.96
Maximum462575.9
Range6152.9426
Interquartile range (IQR)2114.1589

Descriptive statistics

Standard deviation1292.3937
Coefficient of variation (CV)0.0028178915
Kurtosis-0.70463983
Mean458638.56
Median Absolute Deviation (MAD)1072.8083
Skewness0.16505055
Sum1.1264163 × 109
Variance1670281.5
MonotonicityNot monotonic
2024-05-11T07:53:25.048695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456875.973976242 134
 
5.3%
456636.308192293 18
 
0.7%
458714.365820521 16
 
0.6%
457514.212737818 13
 
0.5%
458136.342274236 12
 
0.5%
457626.759229664 11
 
0.4%
457545.100871485 10
 
0.4%
457441.244070216 10
 
0.4%
456770.630403897 9
 
0.4%
456845.373829971 8
 
0.3%
Other values (1403) 2215
87.6%
(Missing) 72
 
2.8%
ValueCountFrequency (%)
456422.95319709 1
 
< 0.1%
456434.500687631 1
 
< 0.1%
456442.951197483 1
 
< 0.1%
456449.379330053 3
0.1%
456469.071770994 1
 
< 0.1%
456473.886142136 3
0.1%
456502.936579267 1
 
< 0.1%
456517.74915445 2
0.1%
456519.141026461 1
 
< 0.1%
456528.977767312 2
0.1%
ValueCountFrequency (%)
462575.895843052 1
 
< 0.1%
462416.392839185 1
 
< 0.1%
462373.950921999 1
 
< 0.1%
462369.166684114 1
 
< 0.1%
462339.150431724 1
 
< 0.1%
462286.724762047 3
0.1%
462248.262541823 2
0.1%
462243.633653421 1
 
< 0.1%
462234.752178333 1
 
< 0.1%
462229.31622502 1
 
< 0.1%

위생업태명
Categorical

Distinct15
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
639 
다방
406 
기타 휴게음식점
404 
커피숍
348 
과자점
227 
Other values (10)
504 

Length

Max length8
Median length6
Mean length4.210443
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 639
25.3%
다방 406
16.1%
기타 휴게음식점 404
16.0%
커피숍 348
13.8%
과자점 227
 
9.0%
일반조리판매 167
 
6.6%
편의점 159
 
6.3%
패스트푸드 143
 
5.7%
백화점 10
 
0.4%
유원지 8
 
0.3%
Other values (5) 17
 
0.7%

Length

2024-05-11T07:53:25.512571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 639
21.8%
다방 406
13.8%
기타 404
13.8%
휴게음식점 404
13.8%
커피숍 348
11.9%
과자점 227
 
7.7%
일반조리판매 167
 
5.7%
편의점 159
 
5.4%
패스트푸드 143
 
4.9%
백화점 10
 
0.3%
Other values (6) 25
 
0.9%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.8%
Missing1625
Missing (%)64.3%
Infinite0
Infinite (%)0.0%
Mean0.21705426
Minimum0
Maximum10
Zeros763
Zeros (%)30.2%
Negative0
Negative (%)0.0%
Memory size22.3 KiB
2024-05-11T07:53:25.890469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.65201153
Coefficient of variation (CV)3.0039102
Kurtosis66.092996
Mean0.21705426
Median Absolute Deviation (MAD)0
Skewness6.1935485
Sum196
Variance0.42511903
MonotonicityNot monotonic
2024-05-11T07:53:26.245460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 763
30.2%
1 107
 
4.2%
2 23
 
0.9%
3 5
 
0.2%
5 2
 
0.1%
4 2
 
0.1%
10 1
 
< 0.1%
(Missing) 1625
64.3%
ValueCountFrequency (%)
0 763
30.2%
1 107
 
4.2%
2 23
 
0.9%
3 5
 
0.2%
4 2
 
0.1%
5 2
 
0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
5 2
 
0.1%
4 2
 
0.1%
3 5
 
0.2%
2 23
 
0.9%
1 107
 
4.2%
0 763
30.2%
Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
1624 
0
515 
3
 
129
1
 
128
2
 
123

Length

Max length4
Median length4
Mean length2.9272152
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
<NA> 1624
64.2%
0 515
 
20.4%
3 129
 
5.1%
1 128
 
5.1%
2 123
 
4.9%
4 9
 
0.4%

Length

2024-05-11T07:53:26.715165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:26.960485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1624
64.2%
0 515
 
20.4%
3 129
 
5.1%
1 128
 
5.1%
2 123
 
4.9%
4 9
 
0.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
1843 
주택가주변
457 
기타
 
155
유흥업소밀집지역
 
50
아파트지역
 
16
Other values (3)
 
7

Length

Max length8
Median length4
Mean length4.1530854
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1843
72.9%
주택가주변 457
 
18.1%
기타 155
 
6.1%
유흥업소밀집지역 50
 
2.0%
아파트지역 16
 
0.6%
결혼예식장주변 4
 
0.2%
학교정화(상대) 2
 
0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-05-11T07:53:27.351481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:27.745147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1843
72.9%
주택가주변 457
 
18.1%
기타 155
 
6.1%
유흥업소밀집지역 50
 
2.0%
아파트지역 16
 
0.6%
결혼예식장주변 4
 
0.2%
학교정화(상대 2
 
0.1%
학교정화(절대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
1849 
기타
338 
지도
202 
자율
 
85
 
27
Other values (3)
 
27

Length

Max length4
Median length4
Mean length3.4426424
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1849
73.1%
기타 338
 
13.4%
지도 202
 
8.0%
자율 85
 
3.4%
27
 
1.1%
24
 
0.9%
우수 2
 
0.1%
관리 1
 
< 0.1%

Length

2024-05-11T07:53:28.228988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:28.691842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1849
73.1%
기타 338
 
13.4%
지도 202
 
8.0%
자율 85
 
3.4%
27
 
1.1%
24
 
0.9%
우수 2
 
0.1%
관리 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
1337 
상수도전용
1186 
상수도(음용)지하수(주방용)겸용
 
5

Length

Max length17
Median length4
Mean length4.4948576
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1337
52.9%
상수도전용 1186
46.9%
상수도(음용)지하수(주방용)겸용 5
 
0.2%

Length

2024-05-11T07:53:29.452425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:29.843265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1337
52.9%
상수도전용 1186
46.9%
상수도(음용)지하수(주방용)겸용 5
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
2355 
0
 
173

Length

Max length4
Median length4
Mean length3.7946994
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> 2355
93.2%
0 173
 
6.8%

Length

2024-05-11T07:53:30.311370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:30.694934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2355
93.2%
0 173
 
6.8%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
2355 
0
 
173

Length

Max length4
Median length4
Mean length3.7946994
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> 2355
93.2%
0 173
 
6.8%

Length

2024-05-11T07:53:31.122269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:31.447589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2355
93.2%
0 173
 
6.8%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
2355 
0
 
173

Length

Max length4
Median length4
Mean length3.7946994
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> 2355
93.2%
0 173
 
6.8%

Length

2024-05-11T07:53:31.797248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:32.192314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2355
93.2%
0 173
 
6.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
2355 
0
 
173

Length

Max length4
Median length4
Mean length3.7946994
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> 2355
93.2%
0 173
 
6.8%

Length

2024-05-11T07:53:32.512300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:32.816596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2355
93.2%
0 173
 
6.8%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
2355 
0
 
173

Length

Max length4
Median length4
Mean length3.7946994
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> 2355
93.2%
0 173
 
6.8%

Length

2024-05-11T07:53:33.178401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:33.494740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2355
93.2%
0 173
 
6.8%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2528
Missing (%)100.0%
Memory size22.3 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
2355 
0
 
173

Length

Max length4
Median length4
Mean length3.7946994
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> 2355
93.2%
0 173
 
6.8%

Length

2024-05-11T07:53:33.898365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:34.453309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2355
93.2%
0 173
 
6.8%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.9 KiB
<NA>
2355 
0
 
173

Length

Max length4
Median length4
Mean length3.7946994
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> 2355
93.2%
0 173
 
6.8%

Length

2024-05-11T07:53:34.845296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:53:35.173636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2355
93.2%
0 173
 
6.8%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing639
Missing (%)25.3%
Memory size5.1 KiB
False
1878 
True
 
11
(Missing)
639 
ValueCountFrequency (%)
False 1878
74.3%
True 11
 
0.4%
(Missing) 639
 
25.3%
2024-05-11T07:53:35.480465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct1160
Distinct (%)61.4%
Missing639
Missing (%)25.3%
Infinite0
Infinite (%)0.0%
Mean42.646845
Minimum0
Maximum434.98
Zeros115
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size22.3 KiB
2024-05-11T07:53:35.890327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median27.51
Q360.6
95-th percentile122.942
Maximum434.98
Range434.98
Interquartile range (IQR)48.6

Descriptive statistics

Standard deviation47.123278
Coefficient of variation (CV)1.1049652
Kurtosis14.713329
Mean42.646845
Median Absolute Deviation (MAD)20.79
Skewness2.9240645
Sum80559.89
Variance2220.6034
MonotonicityNot monotonic
2024-05-11T07:53:36.488922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 115
 
4.5%
3.3 75
 
3.0%
6.6 39
 
1.5%
10.0 19
 
0.8%
30.0 19
 
0.8%
5.0 19
 
0.8%
33.0 18
 
0.7%
20.0 16
 
0.6%
26.4 12
 
0.5%
15.0 12
 
0.5%
Other values (1150) 1545
61.1%
(Missing) 639
25.3%
ValueCountFrequency (%)
0.0 115
4.5%
0.9 1
 
< 0.1%
1.0 3
 
0.1%
1.02 1
 
< 0.1%
1.2 1
 
< 0.1%
1.56 1
 
< 0.1%
2.0 4
 
0.2%
2.05 1
 
< 0.1%
2.08 1
 
< 0.1%
2.24 2
 
0.1%
ValueCountFrequency (%)
434.98 1
< 0.1%
425.78 1
< 0.1%
425.0 1
< 0.1%
422.89 1
< 0.1%
380.0 1
< 0.1%
350.14 1
< 0.1%
341.21 1
< 0.1%
300.66 1
< 0.1%
291.56 1
< 0.1%
289.8 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2528
Missing (%)100.0%
Memory size22.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2528
Missing (%)100.0%
Memory size22.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2528
Missing (%)100.0%
Memory size22.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030800003080000-104-1968-0159319680611<NA>3폐업2폐업19941024<NA><NA><NA>02 0000059.44142804서울특별시 강북구 미아동 70-26번지<NA><NA>대호다방2001-10-17 00:00:00I2018-08-31 23:59:59.0다방202599.37732457013.344458다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N59.44<NA><NA><NA>
130800003080000-104-1968-0175819681221<NA>3폐업2폐업20010222<NA><NA><NA>02 98846070.0142805서울특별시 강북구 미아동 465-6번지<NA><NA>양지2001-02-22 00:00:00I2018-08-31 23:59:59.0다방202497.04125456751.185305다방03유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230800003080000-104-1969-0147919690515<NA>3폐업2폐업19970120<NA><NA><NA>02 994155219.16142876서울특별시 강북구 수유동 174-1번지<NA><NA>새다방2001-10-17 00:00:00I2018-08-31 23:59:59.0다방202426.032099459837.927511다방02유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N19.16<NA><NA><NA>
330800003080000-104-1969-0176319691231<NA>3폐업2폐업19971231<NA><NA><NA>02 989422996.0142804서울특별시 강북구 미아동 67-1번지<NA><NA>연꽃다방2001-09-26 00:00:00I2018-08-31 23:59:59.0다방202598.720032457044.055168다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N96.0<NA><NA><NA>
430800003080000-104-1969-0187919690921<NA>3폐업2폐업20010820<NA><NA><NA>02 954576724.95142817서울특별시 강북구 미아동 628-11번지<NA><NA>부산뉴욕제과2001-08-20 00:00:00I2018-08-31 23:59:59.0과자점<NA><NA>과자점22주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N24.95<NA><NA><NA>
530800003080000-104-1970-0156119700625<NA>3폐업2폐업20051124<NA><NA><NA>02 994292993.6142868서울특별시 강북구 번동 464-15번지<NA><NA>우리다방2001-09-06 00:00:00I2018-08-31 23:59:59.0다방202524.241571459818.119273다방01주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N93.6<NA><NA><NA>
630800003080000-104-1970-0167519700514<NA>3폐업2폐업20100630<NA><NA><NA>02 989229178.3142874서울특별시 강북구 수유동 92-7번지<NA><NA>화원2003-02-04 00:00:00I2018-08-31 23:59:59.0다방201976.322712458982.587999다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N78.3<NA><NA><NA>
730800003080000-104-1970-0169519700721<NA>3폐업2폐업19941024<NA><NA><NA>02 993121053.58142892서울특별시 강북구 우이동 68-5번지<NA><NA>초원2001-09-26 00:00:00I2018-08-31 23:59:59.0다방201062.343956461422.205481다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N53.58<NA><NA><NA>
830800003080000-104-1970-0169819701130<NA>3폐업2폐업20000607<NA><NA><NA>02 9342284101.5142816서울특별시 강북구 미아동 734-168번지<NA><NA>진다방2000-06-07 00:00:00I2018-08-31 23:59:59.0다방201772.453474457650.18076다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N101.5<NA><NA><NA>
930800003080000-104-1970-0171719700611<NA>3폐업2폐업19970721<NA><NA><NA>02 989064045.8142100서울특별시 강북구 미아동 산 838-96번지<NA><NA>삼성2001-11-08 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N45.8<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
251830800003080000-104-2024-000382024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.0142-800서울특별시 강북구 미아동 82-19 지상1층서울특별시 강북구 오패산로30길 17, 1층 (미아동)1233사랑해 김밥2024-04-23 13:34:43I2023-12-03 22:05:00.0기타 휴게음식점202996.598398456850.658803<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
251930800003080000-104-2024-000392024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>14.0142-808서울특별시 강북구 미아동 128-2 태양빌라 101호서울특별시 강북구 도봉로18길 149, 1층 101호 (미아동, 태양빌라)1160봄이네2024-04-26 13:59:01I2023-12-03 22:08:00.0기타 휴게음식점202533.052654457887.557506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
252030800003080000-104-2024-000402024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3142-866서울특별시 강북구 번동 441-28 우일빌딩서울특별시 강북구 덕릉로 126, 우일빌딩 1층 (번동)1130씨유 번동덕릉로점2024-04-26 14:28:14I2023-12-03 22:08:00.0편의점202382.181277459149.972155<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
252130800003080000-104-2024-000412024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>98.87142-876서울특별시 강북구 수유동 166-73서울특별시 강북구 한천로150길 70, 1층 (수유동)1052빽다방 강북중학교점2024-04-30 13:27:50I2023-12-05 00:03:00.0커피숍202257.690617460203.592827<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
252230800003080000-104-2024-000422024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3142-100서울특별시 강북구 미아동 1353-7 금강빌딩서울특별시 강북구 삼양로19길 214, 금강빌딩 1층 (미아동)1193세븐일레븐 삼각산SK점2024-04-30 16:40:36I2023-12-05 00:03:00.0편의점201293.723872457479.348899<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
252330800003080000-104-2024-000432024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.0142-804서울특별시 강북구 미아동 70-6 롯데백화점 미아점서울특별시 강북구 도봉로 62, 롯데백화점 미아점 지하1층 (미아동)1215플레이버엠2024-05-02 11:29:37I2023-12-05 00:04:00.0기타 휴게음식점202625.646265456875.973976<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
252430800003080000-104-2024-000442024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>79.2142-861서울특별시 강북구 번동 308-3 창암빌딩서울특별시 강북구 오현로34길 12, 창암빌딩 1층 (번동)1224컴포즈커피 강북번동점2024-05-03 10:29:55I2023-12-05 00:05:00.0커피숍203465.746576458475.293439<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
252530800003080000-104-2024-000452024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.33142-813서울특별시 강북구 미아동 238-50서울특별시 강북구 삼양로74길 30, 1층 (미아동)1120크레펭,귄2024-05-02 16:48:59I2023-12-05 00:04:00.0기타 휴게음식점201663.565534458588.236209<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
252630800003080000-104-2024-000462024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.65142-804서울특별시 강북구 미아동 70-6 롯데백화점 미아점서울특별시 강북구 도봉로 62, 롯데백화점 미아점 지하1층 (미아동)1215(주)제이와이에스유통2024-05-02 17:02:19I2023-12-05 00:04:00.0기타 휴게음식점202625.646265456875.973976<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
252730800003080000-104-2024-000472024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.0142-867서울특별시 강북구 번동 446-1서울특별시 강북구 오패산로 413, 1층 (번동)1062버블럽 구슬아이스크림2024-05-08 11:56:01I2023-12-04 23:00:00.0아이스크림202239.162722459453.321569<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>