Overview

Dataset statistics

Number of variables44
Number of observations2056
Missing cells21125
Missing cells (%)23.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory755.1 KiB
Average record size in memory376.1 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric5
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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-18239/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
영업상태코드 is highly imbalanced (69.3%)Imbalance
영업상태명 is highly imbalanced (69.3%)Imbalance
상세영업상태코드 is highly imbalanced (69.3%)Imbalance
상세영업상태명 is highly imbalanced (69.3%)Imbalance
데이터갱신구분 is highly imbalanced (50.2%)Imbalance
위생업태명 is highly imbalanced (62.3%)Imbalance
영업장주변구분명 is highly imbalanced (60.6%)Imbalance
급수시설구분명 is highly imbalanced (81.0%)Imbalance
총인원 is highly imbalanced (93.1%)Imbalance
보증액 is highly imbalanced (53.8%)Imbalance
월세액 is highly imbalanced (53.8%)Imbalance
다중이용업소여부 is highly imbalanced (99.4%)Imbalance
인허가취소일자 has 2056 (100.0%) missing valuesMissing
폐업일자 has 113 (5.5%) missing valuesMissing
휴업시작일자 has 2056 (100.0%) missing valuesMissing
휴업종료일자 has 2056 (100.0%) missing valuesMissing
재개업일자 has 2056 (100.0%) missing valuesMissing
전화번호 has 533 (25.9%) missing valuesMissing
소재지면적 has 1839 (89.4%) missing valuesMissing
도로명주소 has 1605 (78.1%) missing valuesMissing
도로명우편번호 has 1617 (78.6%) missing valuesMissing
좌표정보(X) has 362 (17.6%) missing valuesMissing
좌표정보(Y) has 362 (17.6%) missing valuesMissing
다중이용업소여부 has 150 (7.3%) missing valuesMissing
시설총규모 has 150 (7.3%) missing valuesMissing
전통업소지정번호 has 2056 (100.0%) missing valuesMissing
전통업소주된음식 has 2056 (100.0%) missing valuesMissing
홈페이지 has 2056 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 30.01026868)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 166 (8.1%) zerosZeros
시설총규모 has 1896 (92.2%) zerosZeros

Reproduction

Analysis started2024-05-11 02:33:04.864304
Analysis finished2024-05-11 02:33:07.770694
Duration2.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
3120000
2056 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 2056
100.0%

Length

2024-05-11T02:33:07.995363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:08.408612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 2056
100.0%

관리번호
Text

UNIQUE 

Distinct2056
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2024-05-11T02:33:09.196042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters45232
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

Unique2056 ?
Unique (%)100.0%

Sample

1st row3120000-112-1981-00001
2nd row3120000-112-1981-00002
3rd row3120000-112-1981-00003
4th row3120000-112-1981-00004
5th row3120000-112-1981-00680
ValueCountFrequency (%)
3120000-112-1981-00001 1
 
< 0.1%
3120000-112-2002-00170 1
 
< 0.1%
3120000-112-2002-00136 1
 
< 0.1%
3120000-112-2002-00135 1
 
< 0.1%
3120000-112-2002-00134 1
 
< 0.1%
3120000-112-2002-00133 1
 
< 0.1%
3120000-112-2002-00132 1
 
< 0.1%
3120000-112-2002-00131 1
 
< 0.1%
3120000-112-2002-00130 1
 
< 0.1%
3120000-112-2002-00129 1
 
< 0.1%
Other values (2046) 2046
99.5%
2024-05-11T02:33:10.101948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15500
34.3%
1 8935
19.8%
2 6267
13.9%
- 6168
 
13.6%
3 2955
 
6.5%
9 2354
 
5.2%
4 723
 
1.6%
8 647
 
1.4%
5 583
 
1.3%
6 567
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39064
86.4%
Dash Punctuation 6168
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15500
39.7%
1 8935
22.9%
2 6267
16.0%
3 2955
 
7.6%
9 2354
 
6.0%
4 723
 
1.9%
8 647
 
1.7%
5 583
 
1.5%
6 567
 
1.5%
7 533
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 6168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45232
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15500
34.3%
1 8935
19.8%
2 6267
13.9%
- 6168
 
13.6%
3 2955
 
6.5%
9 2354
 
5.2%
4 723
 
1.6%
8 647
 
1.4%
5 583
 
1.3%
6 567
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15500
34.3%
1 8935
19.8%
2 6267
13.9%
- 6168
 
13.6%
3 2955
 
6.5%
9 2354
 
5.2%
4 723
 
1.6%
8 647
 
1.4%
5 583
 
1.3%
6 567
 
1.3%

인허가일자
Date

Distinct1049
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Minimum1981-08-11 00:00:00
Maximum2024-04-29 00:00:00
2024-05-11T02:33:10.591851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:33:11.129679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2056
Missing (%)100.0%
Memory size18.2 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
3
1943 
1
 
113

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 1943
94.5%
1 113
 
5.5%

Length

2024-05-11T02:33:11.692220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:12.083223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1943
94.5%
1 113
 
5.5%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
폐업
1943 
영업/정상
 
113

Length

Max length5
Median length2
Mean length2.1648833
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1943
94.5%
영업/정상 113
 
5.5%

Length

2024-05-11T02:33:12.586698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:12.971343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1943
94.5%
영업/정상 113
 
5.5%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2
1943 
1
 
113

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 1943
94.5%
1 113
 
5.5%

Length

2024-05-11T02:33:13.404628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:13.777691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1943
94.5%
1 113
 
5.5%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
폐업
1943 
영업
 
113

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 1943
94.5%
영업 113
 
5.5%

Length

2024-05-11T02:33:14.177386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:14.527445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1943
94.5%
영업 113
 
5.5%

폐업일자
Date

MISSING 

Distinct1154
Distinct (%)59.4%
Missing113
Missing (%)5.5%
Memory size16.2 KiB
Minimum1987-09-17 00:00:00
Maximum2024-04-22 00:00:00
2024-05-11T02:33:14.976783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:33:15.489856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2056
Missing (%)100.0%
Memory size18.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2056
Missing (%)100.0%
Memory size18.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2056
Missing (%)100.0%
Memory size18.2 KiB

전화번호
Text

MISSING 

Distinct834
Distinct (%)54.8%
Missing533
Missing (%)25.9%
Memory size16.2 KiB
2024-05-11T02:33:16.087095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.0538411
Min length2

Characters and Unicode

Total characters13789
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

Unique783 ?
Unique (%)51.4%

Sample

1st row02
2nd row02
3rd row02
4th row02
5th row02
ValueCountFrequency (%)
02 856
37.6%
0200000000 345
 
15.2%
0234720333 19
 
0.8%
3923481 14
 
0.6%
0232728988 13
 
0.6%
3619222 8
 
0.4%
7435353 7
 
0.3%
379 6
 
0.3%
070 6
 
0.3%
363 6
 
0.3%
Other values (874) 995
43.7%
2024-05-11T02:33:17.162804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5089
36.9%
2 2259
16.4%
3 1524
 
11.1%
872
 
6.3%
9 627
 
4.5%
1 626
 
4.5%
7 616
 
4.5%
6 602
 
4.4%
4 567
 
4.1%
5 562
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12917
93.7%
Space Separator 872
 
6.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5089
39.4%
2 2259
17.5%
3 1524
 
11.8%
9 627
 
4.9%
1 626
 
4.8%
7 616
 
4.8%
6 602
 
4.7%
4 567
 
4.4%
5 562
 
4.4%
8 445
 
3.4%
Space Separator
ValueCountFrequency (%)
872
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13789
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5089
36.9%
2 2259
16.4%
3 1524
 
11.1%
872
 
6.3%
9 627
 
4.5%
1 626
 
4.5%
7 616
 
4.5%
6 602
 
4.4%
4 567
 
4.1%
5 562
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5089
36.9%
2 2259
16.4%
3 1524
 
11.1%
872
 
6.3%
9 627
 
4.5%
1 626
 
4.5%
7 616
 
4.5%
6 602
 
4.4%
4 567
 
4.1%
5 562
 
4.1%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)10.1%
Missing1839
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean4.9772811
Minimum0
Maximum319.5
Zeros166
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-05-11T02:33:17.618225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile19.76
Maximum319.5
Range319.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation25.734907
Coefficient of variation (CV)5.1704749
Kurtosis107.12092
Mean4.9772811
Median Absolute Deviation (MAD)0
Skewness9.529628
Sum1080.07
Variance662.28543
MonotonicityNot monotonic
2024-05-11T02:33:17.914251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 166
 
8.1%
3.3 13
 
0.6%
3.0 7
 
0.3%
3.6 6
 
0.3%
6.6 4
 
0.2%
19.76 2
 
0.1%
33.0 2
 
0.1%
2.0 2
 
0.1%
9.9 2
 
0.1%
15.0 1
 
< 0.1%
Other values (12) 12
 
0.6%
(Missing) 1839
89.4%
ValueCountFrequency (%)
0.0 166
8.1%
0.5 1
 
< 0.1%
2.0 2
 
0.1%
2.8 1
 
< 0.1%
3.0 7
 
0.3%
3.3 13
 
0.6%
3.6 6
 
0.3%
6.6 4
 
0.2%
9.9 2
 
0.1%
11.67 1
 
< 0.1%
ValueCountFrequency (%)
319.5 1
< 0.1%
116.4 1
< 0.1%
107.96 1
< 0.1%
100.0 1
< 0.1%
66.0 1
< 0.1%
39.7 1
< 0.1%
33.0 2
0.1%
23.0 1
< 0.1%
22.37 1
< 0.1%
19.76 2
0.1%

소재지우편번호
Text

Distinct150
Distinct (%)7.3%
Missing1
Missing (%)< 0.1%
Memory size16.2 KiB
2024-05-11T02:33:18.584941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0423358
Min length6

Characters and Unicode

Total characters12417
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

Unique34 ?
Unique (%)1.7%

Sample

1st row120831
2nd row120012
3rd row120070
4th row120825
5th row120834
ValueCountFrequency (%)
120140 109
 
5.3%
120012 77
 
3.7%
120834 74
 
3.6%
120808 72
 
3.5%
120848 68
 
3.3%
120857 64
 
3.1%
120050 61
 
3.0%
120859 59
 
2.9%
120805 57
 
2.8%
120833 57
 
2.8%
Other values (140) 1357
66.0%
2024-05-11T02:33:19.701018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3275
26.4%
1 2804
22.6%
2 2491
20.1%
8 1749
14.1%
4 471
 
3.8%
3 435
 
3.5%
5 432
 
3.5%
7 258
 
2.1%
6 211
 
1.7%
9 204
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12330
99.3%
Dash Punctuation 87
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3275
26.6%
1 2804
22.7%
2 2491
20.2%
8 1749
14.2%
4 471
 
3.8%
3 435
 
3.5%
5 432
 
3.5%
7 258
 
2.1%
6 211
 
1.7%
9 204
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12417
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3275
26.4%
1 2804
22.6%
2 2491
20.1%
8 1749
14.1%
4 471
 
3.8%
3 435
 
3.5%
5 432
 
3.5%
7 258
 
2.1%
6 211
 
1.7%
9 204
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3275
26.4%
1 2804
22.6%
2 2491
20.1%
8 1749
14.1%
4 471
 
3.8%
3 435
 
3.5%
5 432
 
3.5%
7 258
 
2.1%
6 211
 
1.7%
9 204
 
1.6%

지번주소
Text

Distinct1615
Distinct (%)78.6%
Missing1
Missing (%)< 0.1%
Memory size16.2 KiB
2024-05-11T02:33:20.498216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length45
Mean length23.827251
Min length18

Characters and Unicode

Total characters48965
Distinct characters323
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1435 ?
Unique (%)69.8%

Sample

1st row서울특별시 서대문구 연희동 421-1
2nd row서울특별시 서대문구 충정로2가 185-10
3rd row서울특별시 서대문구 영천동 305-0 한국상업은
4th row서울특별시 서대문구 연희동 131-1
5th row서울특별시 서대문구 창천동 30-15
ValueCountFrequency (%)
서울특별시 2055
22.5%
서대문구 2055
22.5%
홍제동 288
 
3.2%
남가좌동 235
 
2.6%
홍은동 205
 
2.2%
연희동 192
 
2.1%
북가좌동 182
 
2.0%
창천동 160
 
1.8%
북아현동 160
 
1.8%
대현동 125
 
1.4%
Other values (1755) 3462
38.0%
2024-05-11T02:33:21.967717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8960
18.3%
서 4161
 
8.5%
대 2306
 
4.7%
문 2083
 
4.3%
울 2070
 
4.2%
시 2065
 
4.2%
구 2063
 
4.2%
별 2062
 
4.2%
특 2056
 
4.2%
1 2011
 
4.1%
Other values (313) 19128
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28788
58.8%
Space Separator 8960
 
18.3%
Decimal Number 8922
 
18.2%
Dash Punctuation 1795
 
3.7%
Close Punctuation 194
 
0.4%
Open Punctuation 185
 
0.4%
Uppercase Letter 63
 
0.1%
Other Punctuation 57
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 4161
14.5%
대 2306
 
8.0%
문 2083
 
7.2%
울 2070
 
7.2%
시 2065
 
7.2%
구 2063
 
7.2%
별 2062
 
7.2%
특 2056
 
7.1%
동 1925
 
6.7%
가 636
 
2.2%
Other values (279) 7361
25.6%
Uppercase Letter
ValueCountFrequency (%)
C 10
15.9%
S 8
12.7%
M 6
9.5%
K 6
9.5%
B 6
9.5%
D 6
9.5%
U 5
7.9%
A 3
 
4.8%
G 3
 
4.8%
V 2
 
3.2%
Other values (7) 8
12.7%
Decimal Number
ValueCountFrequency (%)
1 2011
22.5%
3 1262
14.1%
2 1262
14.1%
0 836
9.4%
4 742
 
8.3%
5 660
 
7.4%
6 599
 
6.7%
9 576
 
6.5%
7 554
 
6.2%
8 420
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 56
98.2%
@ 1
 
1.8%
Space Separator
ValueCountFrequency (%)
8960
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1795
100.0%
Close Punctuation
ValueCountFrequency (%)
) 194
100.0%
Open Punctuation
ValueCountFrequency (%)
( 185
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28788
58.8%
Common 20114
41.1%
Latin 63
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 4161
14.5%
대 2306
 
8.0%
문 2083
 
7.2%
울 2070
 
7.2%
시 2065
 
7.2%
구 2063
 
7.2%
별 2062
 
7.2%
특 2056
 
7.1%
동 1925
 
6.7%
가 636
 
2.2%
Other values (279) 7361
25.6%
Common
ValueCountFrequency (%)
8960
44.5%
1 2011
 
10.0%
- 1795
 
8.9%
3 1262
 
6.3%
2 1262
 
6.3%
0 836
 
4.2%
4 742
 
3.7%
5 660
 
3.3%
6 599
 
3.0%
9 576
 
2.9%
Other values (7) 1411
 
7.0%
Latin
ValueCountFrequency (%)
C 10
15.9%
S 8
12.7%
M 6
9.5%
K 6
9.5%
B 6
9.5%
D 6
9.5%
U 5
7.9%
A 3
 
4.8%
G 3
 
4.8%
V 2
 
3.2%
Other values (7) 8
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28788
58.8%
ASCII 20177
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8960
44.4%
1 2011
 
10.0%
- 1795
 
8.9%
3 1262
 
6.3%
2 1262
 
6.3%
0 836
 
4.1%
4 742
 
3.7%
5 660
 
3.3%
6 599
 
3.0%
9 576
 
2.9%
Other values (24) 1474
 
7.3%
Hangul
ValueCountFrequency (%)
서 4161
14.5%
대 2306
 
8.0%
문 2083
 
7.2%
울 2070
 
7.2%
시 2065
 
7.2%
구 2063
 
7.2%
별 2062
 
7.2%
특 2056
 
7.1%
동 1925
 
6.7%
가 636
 
2.2%
Other values (279) 7361
25.6%

도로명주소
Text

MISSING 

Distinct390
Distinct (%)86.5%
Missing1605
Missing (%)78.1%
Memory size16.2 KiB
2024-05-11T02:33:22.904908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length50
Mean length31.427938
Min length23

Characters and Unicode

Total characters14174
Distinct characters275
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

Unique371 ?
Unique (%)82.3%

Sample

1st row서울특별시 서대문구 연세로 50 (신촌동)
2nd row서울특별시 서대문구 연세로 50 (신촌동)
3rd row서울특별시 서대문구 연세로 50 (신촌동)
4th row서울특별시 서대문구 연세로 50 (신촌동)
5th row서울특별시 서대문구 연세로 50 (신촌동)
ValueCountFrequency (%)
서울특별시 451
 
16.7%
서대문구 451
 
16.7%
1층 98
 
3.6%
연세로 62
 
2.3%
50 55
 
2.0%
연희동 51
 
1.9%
신촌동 51
 
1.9%
홍제동 49
 
1.8%
남가좌동 44
 
1.6%
홍은동 43
 
1.6%
Other values (579) 1348
49.9%
2024-05-11T02:33:24.512364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2255
 
15.9%
서 933
 
6.6%
대 542
 
3.8%
1 504
 
3.6%
문 492
 
3.5%
) 488
 
3.4%
( 488
 
3.4%
동 476
 
3.4%
시 464
 
3.3%
울 462
 
3.3%
Other values (265) 7070
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8759
61.8%
Space Separator 2255
 
15.9%
Decimal Number 1743
 
12.3%
Close Punctuation 488
 
3.4%
Open Punctuation 488
 
3.4%
Other Punctuation 323
 
2.3%
Dash Punctuation 58
 
0.4%
Uppercase Letter 57
 
0.4%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 933
 
10.7%
대 542
 
6.2%
문 492
 
5.6%
동 476
 
5.4%
시 464
 
5.3%
울 462
 
5.3%
구 453
 
5.2%
별 452
 
5.2%
특 451
 
5.1%
로 432
 
4.9%
Other values (234) 3602
41.1%
Uppercase Letter
ValueCountFrequency (%)
B 11
19.3%
C 10
17.5%
S 6
10.5%
D 6
10.5%
M 6
10.5%
K 5
8.8%
A 3
 
5.3%
G 3
 
5.3%
U 2
 
3.5%
H 2
 
3.5%
Other values (3) 3
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 504
28.9%
2 239
13.7%
0 209
12.0%
3 181
 
10.4%
5 172
 
9.9%
4 129
 
7.4%
7 87
 
5.0%
9 78
 
4.5%
8 76
 
4.4%
6 68
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
g 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
2255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 488
100.0%
Open Punctuation
ValueCountFrequency (%)
( 488
100.0%
Other Punctuation
ValueCountFrequency (%)
, 323
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8759
61.8%
Common 5356
37.8%
Latin 59
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 933
 
10.7%
대 542
 
6.2%
문 492
 
5.6%
동 476
 
5.4%
시 464
 
5.3%
울 462
 
5.3%
구 453
 
5.2%
별 452
 
5.2%
특 451
 
5.1%
로 432
 
4.9%
Other values (234) 3602
41.1%
Common
ValueCountFrequency (%)
2255
42.1%
1 504
 
9.4%
) 488
 
9.1%
( 488
 
9.1%
, 323
 
6.0%
2 239
 
4.5%
0 209
 
3.9%
3 181
 
3.4%
5 172
 
3.2%
4 129
 
2.4%
Other values (6) 368
 
6.9%
Latin
ValueCountFrequency (%)
B 11
18.6%
C 10
16.9%
S 6
10.2%
D 6
10.2%
M 6
10.2%
K 5
8.5%
A 3
 
5.1%
G 3
 
5.1%
U 2
 
3.4%
H 2
 
3.4%
Other values (5) 5
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8759
61.8%
ASCII 5415
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2255
41.6%
1 504
 
9.3%
) 488
 
9.0%
( 488
 
9.0%
, 323
 
6.0%
2 239
 
4.4%
0 209
 
3.9%
3 181
 
3.3%
5 172
 
3.2%
4 129
 
2.4%
Other values (21) 427
 
7.9%
Hangul
ValueCountFrequency (%)
서 933
 
10.7%
대 542
 
6.2%
문 492
 
5.6%
동 476
 
5.4%
시 464
 
5.3%
울 462
 
5.3%
구 453
 
5.2%
별 452
 
5.2%
특 451
 
5.1%
로 432
 
4.9%
Other values (234) 3602
41.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct136
Distinct (%)31.0%
Missing1617
Missing (%)78.6%
Infinite0
Infinite (%)0.0%
Mean3706.1048
Minimum3600
Maximum3789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-05-11T02:33:25.145541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3600
5-th percentile3620
Q13671.5
median3720
Q33737.5
95-th percentile3779.1
Maximum3789
Range189
Interquartile range (IQR)66

Descriptive statistics

Standard deviation47.303913
Coefficient of variation (CV)0.012763782
Kurtosis-0.68461372
Mean3706.1048
Median Absolute Deviation (MAD)32
Skewness-0.33811466
Sum1626980
Variance2237.6602
MonotonicityNot monotonic
2024-05-11T02:33:25.779258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3722 60
 
2.9%
3739 12
 
0.6%
3732 9
 
0.4%
3650 7
 
0.3%
3780 7
 
0.3%
3741 7
 
0.3%
3671 7
 
0.3%
3789 7
 
0.3%
3779 7
 
0.3%
3745 7
 
0.3%
Other values (126) 309
 
15.0%
(Missing) 1617
78.6%
ValueCountFrequency (%)
3600 2
 
0.1%
3601 1
 
< 0.1%
3605 5
0.2%
3606 1
 
< 0.1%
3610 2
 
0.1%
3611 2
 
0.1%
3612 1
 
< 0.1%
3614 1
 
< 0.1%
3615 1
 
< 0.1%
3617 3
0.1%
ValueCountFrequency (%)
3789 7
0.3%
3788 1
 
< 0.1%
3785 3
0.1%
3782 2
 
0.1%
3781 2
 
0.1%
3780 7
0.3%
3779 7
0.3%
3778 2
 
0.1%
3777 3
0.1%
3774 3
0.1%

사업장명
Text

Distinct1572
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2024-05-11T02:33:26.488799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length5.7534047
Min length2

Characters and Unicode

Total characters11829
Distinct characters607
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1420 ?
Unique (%)69.1%

Sample

1st row성산회관
2nd row(주)해동화재해상보험
3rd row서동근
4th row백석현
5th row양정물산(주)
ValueCountFrequency (%)
연세대학교 39
 
1.7%
오광열 31
 
1.4%
씨유 29
 
1.3%
동서실업 27
 
1.2%
경찰청후생관 23
 
1.0%
세브란스신협 23
 
1.0%
명지대학교 22
 
1.0%
이정욱 19
 
0.8%
gs25 14
 
0.6%
경기대학교 14
 
0.6%
Other values (1628) 2039
89.4%
2024-05-11T02:33:27.951299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 304
 
2.6%
점 247
 
2.1%
226
 
1.9%
동 198
 
1.7%
학 184
 
1.6%
이 178
 
1.5%
서 178
 
1.5%
스 174
 
1.5%
지 167
 
1.4%
문 162
 
1.4%
Other values (597) 9811
82.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10914
92.3%
Decimal Number 233
 
2.0%
Space Separator 226
 
1.9%
Uppercase Letter 183
 
1.5%
Close Punctuation 108
 
0.9%
Open Punctuation 107
 
0.9%
Lowercase Letter 32
 
0.3%
Dash Punctuation 18
 
0.2%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 304
 
2.8%
점 247
 
2.3%
동 198
 
1.8%
학 184
 
1.7%
이 178
 
1.6%
서 178
 
1.6%
스 174
 
1.6%
지 167
 
1.5%
문 162
 
1.5%
교 157
 
1.4%
Other values (543) 8965
82.1%
Uppercase Letter
ValueCountFrequency (%)
C 36
19.7%
S 31
16.9%
G 31
16.9%
U 27
14.8%
B 7
 
3.8%
M 6
 
3.3%
I 5
 
2.7%
P 5
 
2.7%
T 5
 
2.7%
O 5
 
2.7%
Other values (12) 25
13.7%
Lowercase Letter
ValueCountFrequency (%)
e 5
15.6%
o 5
15.6%
t 4
12.5%
s 3
9.4%
i 2
 
6.2%
h 2
 
6.2%
c 2
 
6.2%
a 2
 
6.2%
l 1
 
3.1%
x 1
 
3.1%
Other values (5) 5
15.6%
Decimal Number
ValueCountFrequency (%)
2 77
33.0%
5 50
21.5%
1 38
16.3%
4 31
13.3%
3 15
 
6.4%
0 12
 
5.2%
8 4
 
1.7%
6 2
 
0.9%
7 2
 
0.9%
9 2
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
, 2
25.0%
& 2
25.0%
Space Separator
ValueCountFrequency (%)
226
100.0%
Close Punctuation
ValueCountFrequency (%)
) 108
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10914
92.3%
Common 700
 
5.9%
Latin 215
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 304
 
2.8%
점 247
 
2.3%
동 198
 
1.8%
학 184
 
1.7%
이 178
 
1.6%
서 178
 
1.6%
스 174
 
1.6%
지 167
 
1.5%
문 162
 
1.5%
교 157
 
1.4%
Other values (543) 8965
82.1%
Latin
ValueCountFrequency (%)
C 36
16.7%
S 31
14.4%
G 31
14.4%
U 27
12.6%
B 7
 
3.3%
M 6
 
2.8%
e 5
 
2.3%
I 5
 
2.3%
o 5
 
2.3%
P 5
 
2.3%
Other values (27) 57
26.5%
Common
ValueCountFrequency (%)
226
32.3%
) 108
15.4%
( 107
15.3%
2 77
 
11.0%
5 50
 
7.1%
1 38
 
5.4%
4 31
 
4.4%
- 18
 
2.6%
3 15
 
2.1%
0 12
 
1.7%
Other values (7) 18
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10914
92.3%
ASCII 915
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 304
 
2.8%
점 247
 
2.3%
동 198
 
1.8%
학 184
 
1.7%
이 178
 
1.6%
서 178
 
1.6%
스 174
 
1.6%
지 167
 
1.5%
문 162
 
1.5%
교 157
 
1.4%
Other values (543) 8965
82.1%
ASCII
ValueCountFrequency (%)
226
24.7%
) 108
11.8%
( 107
11.7%
2 77
 
8.4%
5 50
 
5.5%
1 38
 
4.2%
C 36
 
3.9%
S 31
 
3.4%
4 31
 
3.4%
G 31
 
3.4%
Other values (44) 180
19.7%

최종수정일자
Date

Distinct876
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Minimum1999-09-28 00:00:00
Maximum2024-05-09 17:07:15
2024-05-11T02:33:28.567820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:33:29.143738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
I
1831 
U
225 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1831
89.1%
U 225
 
10.9%

Length

2024-05-11T02:33:29.697793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:30.010558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1831
89.1%
u 225
 
10.9%

데이터갱신일자
Date

Distinct196
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:01:00
2024-05-11T02:33:30.477262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:33:30.980421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
식품자동판매기영업
2056 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 2056
100.0%

Length

2024-05-11T02:33:31.463660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:31.846607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 2056
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1046
Distinct (%)61.7%
Missing362
Missing (%)17.6%
Infinite0
Infinite (%)0.0%
Mean194652.98
Minimum191434.89
Maximum197147.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-05-11T02:33:32.312954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191434.89
5-th percentile192275.42
Q1193643.28
median194751
Q3195568.86
95-th percentile196836.22
Maximum197147.39
Range5712.5072
Interquartile range (IQR)1925.5815

Descriptive statistics

Standard deviation1369.6901
Coefficient of variation (CV)0.0070365741
Kurtosis-0.73484262
Mean194652.98
Median Absolute Deviation (MAD)971.64661
Skewness-0.171305
Sum3.2974215 × 108
Variance1876051.1
MonotonicityNot monotonic
2024-05-11T02:33:32.861268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194584.959249312 80
 
3.9%
193139.52394401 39
 
1.9%
195287.766418517 30
 
1.5%
196602.387940718 25
 
1.2%
195806.732723093 25
 
1.2%
197062.989911966 24
 
1.2%
196561.763885973 19
 
0.9%
196058.441601385 15
 
0.7%
196879.053918764 14
 
0.7%
196851.907463121 13
 
0.6%
Other values (1036) 1410
68.6%
(Missing) 362
 
17.6%
ValueCountFrequency (%)
191434.887463719 1
< 0.1%
191497.867040904 2
0.1%
191540.260492627 1
< 0.1%
191546.472462363 1
< 0.1%
191552.612967645 1
< 0.1%
191559.918118738 1
< 0.1%
191570.192406712 1
< 0.1%
191572.384552653 1
< 0.1%
191632.602812304 1
< 0.1%
191658.428464659 2
0.1%
ValueCountFrequency (%)
197147.394631349 2
 
0.1%
197144.015440398 1
 
< 0.1%
197062.989911966 24
1.2%
197060.360211907 1
 
< 0.1%
197054.98327451 1
 
< 0.1%
197053.685372291 1
 
< 0.1%
197004.364341776 1
 
< 0.1%
196993.66534559 4
 
0.2%
196945.454641052 2
 
0.1%
196934.602353655 4
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1045
Distinct (%)61.7%
Missing362
Missing (%)17.6%
Infinite0
Infinite (%)0.0%
Mean452272.44
Minimum450367.37
Maximum455710.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-05-11T02:33:33.317594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450367.37
5-th percentile450515.63
Q1451143.79
median451923.21
Q3453348.09
95-th percentile454766.06
Maximum455710.43
Range5343.0582
Interquartile range (IQR)2204.3001

Descriptive statistics

Standard deviation1369.1329
Coefficient of variation (CV)0.0030272304
Kurtosis-0.94768183
Mean452272.44
Median Absolute Deviation (MAD)1155.2041
Skewness0.43683896
Sum7.6614952 × 108
Variance1874524.8
MonotonicityNot monotonic
2024-05-11T02:33:33.801260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451381.585492051 81
 
3.9%
453106.002592232 39
 
1.9%
451143.789306014 30
 
1.5%
451683.338400967 25
 
1.2%
451160.409173293 25
 
1.2%
451257.725174623 24
 
1.2%
451392.818087251 19
 
0.9%
452437.094345339 15
 
0.7%
451436.098712399 14
 
0.7%
451181.654966493 13
 
0.6%
Other values (1035) 1409
68.5%
(Missing) 362
 
17.6%
ValueCountFrequency (%)
450367.371729263 1
 
< 0.1%
450375.488731434 4
0.2%
450379.216435725 1
 
< 0.1%
450387.139950052 3
0.1%
450390.671043197 1
 
< 0.1%
450391.53849739 2
 
0.1%
450392.774100774 1
 
< 0.1%
450400.49762862 2
 
0.1%
450414.724902658 5
0.2%
450415.700852123 1
 
< 0.1%
ValueCountFrequency (%)
455710.429910779 1
< 0.1%
455601.317191626 2
0.1%
455588.317096857 1
< 0.1%
455484.478875325 1
< 0.1%
455441.037117879 1
< 0.1%
455433.804754546 1
< 0.1%
455422.498445639 1
< 0.1%
455414.392407621 1
< 0.1%
455396.252167005 1
< 0.1%
455372.155821625 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
식품자동판매기영업
1906 
<NA>
 
150

Length

Max length9
Median length9
Mean length8.635214
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 1906
92.7%
<NA> 150
 
7.3%

Length

2024-05-11T02:33:34.468184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:34.750344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 1906
92.7%
na 150
 
7.3%

남성종사자수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1168 
0
841 
1
 
47

Length

Max length4
Median length4
Mean length2.7042802
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1168
56.8%
0 841
40.9%
1 47
 
2.3%

Length

2024-05-11T02:33:35.056395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:35.372994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1168
56.8%
0 841
40.9%
1 47
 
2.3%

여성종사자수
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1168 
0
854 
1
 
33
2
 
1

Length

Max length4
Median length4
Mean length2.7042802
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1168
56.8%
0 854
41.5%
1 33
 
1.6%
2 1
 
< 0.1%

Length

2024-05-11T02:33:35.763762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:36.107562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1168
56.8%
0 854
41.5%
1 33
 
1.6%
2 1
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
기타
1084 
<NA>
945 
주택가주변
 
13
유흥업소밀집지역
 
10
학교정화(상대)
 
2
Other values (2)
 
2

Length

Max length8
Median length2
Mean length2.9771401
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 1084
52.7%
<NA> 945
46.0%
주택가주변 13
 
0.6%
유흥업소밀집지역 10
 
0.5%
학교정화(상대) 2
 
0.1%
결혼예식장주변 1
 
< 0.1%
아파트지역 1
 
< 0.1%

Length

2024-05-11T02:33:36.628375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:37.065583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 1084
52.7%
na 945
46.0%
주택가주변 13
 
0.6%
유흥업소밀집지역 10
 
0.5%
학교정화(상대 2
 
0.1%
결혼예식장주변 1
 
< 0.1%
아파트지역 1
 
< 0.1%

등급구분명
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
기타
999 
<NA>
945 
지도
 
96
을
 
10
자율
 
6

Length

Max length4
Median length2
Mean length2.9143969
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 999
48.6%
<NA> 945
46.0%
지도 96
 
4.7%
을 10
 
0.5%
자율 6
 
0.3%

Length

2024-05-11T02:33:37.530283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:37.985502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 999
48.6%
na 945
46.0%
지도 96
 
4.7%
을 10
 
0.5%
자율 6
 
0.3%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1996 
상수도전용
 
60

Length

Max length5
Median length4
Mean length4.0291829
Min length4

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> 1996
97.1%
상수도전용 60
 
2.9%

Length

2024-05-11T02:33:38.470635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:38.813240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1996
97.1%
상수도전용 60
 
2.9%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
2039 
0
 
17

Length

Max length4
Median length4
Mean length3.9751946
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> 2039
99.2%
0 17
 
0.8%

Length

2024-05-11T02:33:39.236450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:39.679974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2039
99.2%
0 17
 
0.8%

본사종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
0
1132 
<NA>
924 

Length

Max length4
Median length1
Mean length2.348249
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1132
55.1%
<NA> 924
44.9%

Length

2024-05-11T02:33:40.131864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:40.521014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1132
55.1%
na 924
44.9%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
0
1132 
<NA>
924 

Length

Max length4
Median length1
Mean length2.348249
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1132
55.1%
<NA> 924
44.9%

Length

2024-05-11T02:33:41.051885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:41.413580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1132
55.1%
na 924
44.9%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
0
1132 
<NA>
924 

Length

Max length4
Median length1
Mean length2.348249
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1132
55.1%
<NA> 924
44.9%

Length

2024-05-11T02:33:41.883430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:42.282446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1132
55.1%
na 924
44.9%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
0
1132 
<NA>
924 

Length

Max length4
Median length1
Mean length2.348249
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1132
55.1%
<NA> 924
44.9%

Length

2024-05-11T02:33:42.785669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:43.373412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1132
55.1%
na 924
44.9%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1589 
자가
442 
임대
 
25

Length

Max length4
Median length4
Mean length3.5457198
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1589
77.3%
자가 442
 
21.5%
임대 25
 
1.2%

Length

2024-05-11T02:33:43.812938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:44.327219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1589
77.3%
자가 442
 
21.5%
임대 25
 
1.2%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1640 
0
415 
20000000
 
1

Length

Max length8
Median length4
Mean length3.3964008
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1640
79.8%
0 415
 
20.2%
20000000 1
 
< 0.1%

Length

2024-05-11T02:33:44.795042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:45.205254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1640
79.8%
0 415
 
20.2%
20000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1640 
0
415 
1900000
 
1

Length

Max length7
Median length4
Mean length3.3959144
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1640
79.8%
0 415
 
20.2%
1900000 1
 
< 0.1%

Length

2024-05-11T02:33:45.676580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:33:46.061512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1640
79.8%
0 415
 
20.2%
1900000 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing150
Missing (%)7.3%
Memory size4.1 KiB
False
1905 
True
 
1
(Missing)
 
150
ValueCountFrequency (%)
False 1905
92.7%
True 1
 
< 0.1%
(Missing) 150
 
7.3%
2024-05-11T02:33:46.365244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.5%
Missing150
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean0.38579748
Minimum0
Maximum319.5
Zeros1896
Zeros (%)92.2%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-05-11T02:33:46.640324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum319.5
Range319.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.6197226
Coefficient of variation (CV)22.34261
Kurtosis1027.412
Mean0.38579748
Median Absolute Deviation (MAD)0
Skewness30.010269
Sum735.33
Variance74.299618
MonotonicityNot monotonic
2024-05-11T02:33:47.055538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 1896
92.2%
3.3 2
 
0.1%
3.6 2
 
0.1%
107.96 1
 
< 0.1%
100.0 1
 
< 0.1%
66.0 1
 
< 0.1%
11.67 1
 
< 0.1%
319.5 1
 
< 0.1%
116.4 1
 
< 0.1%
(Missing) 150
 
7.3%
ValueCountFrequency (%)
0.0 1896
92.2%
3.3 2
 
0.1%
3.6 2
 
0.1%
11.67 1
 
< 0.1%
66.0 1
 
< 0.1%
100.0 1
 
< 0.1%
107.96 1
 
< 0.1%
116.4 1
 
< 0.1%
319.5 1
 
< 0.1%
ValueCountFrequency (%)
319.5 1
 
< 0.1%
116.4 1
 
< 0.1%
107.96 1
 
< 0.1%
100.0 1
 
< 0.1%
66.0 1
 
< 0.1%
11.67 1
 
< 0.1%
3.6 2
 
0.1%
3.3 2
 
0.1%
0.0 1896
92.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2056
Missing (%)100.0%
Memory size18.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2056
Missing (%)100.0%
Memory size18.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2056
Missing (%)100.0%
Memory size18.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031200003120000-112-1981-0000119810831<NA>3폐업2폐업19970320<NA><NA><NA>02<NA>120831서울특별시 서대문구 연희동 421-1<NA><NA>성산회관2001-12-20 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업193393.590065451598.501283식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131200003120000-112-1981-0000219810831<NA>3폐업2폐업19960401<NA><NA><NA>02<NA>120012서울특별시 서대문구 충정로2가 185-10<NA><NA>(주)해동화재해상보험2001-12-20 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업196741.831918451271.112323식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231200003120000-112-1981-0000319810904<NA>3폐업2폐업19900917<NA><NA><NA>02<NA>120070서울특별시 서대문구 영천동 305-0 한국상업은<NA><NA>서동근2001-09-30 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업196521.312331452048.722527식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331200003120000-112-1981-0000419810811<NA>3폐업2폐업20220826<NA><NA><NA>02<NA>120825서울특별시 서대문구 연희동 131-1<NA><NA>백석현2022-08-26 13:16:10U2021-12-07 22:08:00.0식품자동판매기영업193716.339878451653.563672<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
431200003120000-112-1981-0068019810827<NA>3폐업2폐업19960503<NA><NA><NA>02<NA>120834서울특별시 서대문구 창천동 30-15<NA><NA>양정물산(주)2002-03-26 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00주택가주변자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531200003120000-112-1981-0068119810914<NA>3폐업2폐업19900914<NA><NA><NA>02<NA>120819서울특별시 서대문구 북아현동 135-14 상업은행북<NA><NA>김길수2001-09-30 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631200003120000-112-1981-0106619810831<NA>3폐업2폐업20010213<NA><NA><NA>02<NA>120050서울특별시 서대문구 냉천동 244-0 신성원<NA><NA>김영석2001-09-30 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업196846.622253451647.530591식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731200003120000-112-1983-0000519830207<NA>3폐업2폐업19930902<NA><NA><NA>02<NA>120140서울특별시 서대문구 신촌동 134<NA><NA>세브란스신용협동조합2001-12-20 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업194584.959249451381.585492식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831200003120000-112-1983-0000619830207<NA>3폐업2폐업20140707<NA><NA><NA>02 3923481<NA>120140서울특별시 서대문구 신촌동 134서울특별시 서대문구 연세로 50 (신촌동)3722세브란스신협2002-03-12 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업194584.959249451381.585492식품자동판매기영업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
931200003120000-112-1983-0000719830207<NA>3폐업2폐업20140707<NA><NA><NA>02 3923481<NA>120140서울특별시 서대문구 신촌동 134서울특별시 서대문구 연세로 50 (신촌동)3722세브란스신협2002-03-12 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업194584.959249451381.585492식품자동판매기영업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
204631200003120000-112-2023-000162023-11-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.0120-807서울특별시 서대문구 남가좌동 343-28서울특별시 서대문구 거북골로 53-31, 1층 (남가좌동)366524시무인카페만월경명지대점2023-11-09 13:54:37I2022-10-31 23:01:00.0식품자동판매기영업193144.094148452888.667274<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
204731200003120000-112-2023-000172023-11-14<NA>1영업/정상1영업<NA><NA><NA><NA>02632414053.0120-833서울특별시 서대문구 창천동 18-55 즐거운빌딩서울특별시 서대문구 연세로 10-1, 즐거운빌딩 9층 (창천동)3779피투피시스템즈2023-11-14 11:43:02I2022-10-31 23:06:00.0식품자동판매기영업194375.081073450469.851632<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
204831200003120000-112-2023-000182023-12-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0120-855서울특별시 서대문구 홍제동 156-200 고은맨숀아파트서울특별시 서대문구 모래내로 453, 가동 지하1층 3호 (홍제동, 고은맨숀아파트)3646사람없는 커피어때2023-12-29 15:00:52I2022-11-01 21:01:00.0식품자동판매기영업195056.433402453713.396936<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
204931200003120000-112-2024-000012024-01-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0120-818서울특별시 서대문구 북아현동 189-2서울특별시 서대문구 북아현로 105, 1층 (북아현동)3761지에스(GS)25 북아현로점2024-01-09 10:57:03I2023-11-30 23:01:00.0식품자동판매기영업195666.451641451394.022868<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205031200003120000-112-2024-000022024-02-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3120-120서울특별시 서대문구 남가좌동 377 DMC래미안클라시스서울특별시 서대문구 증가로 191, 상가동 104호 (남가좌동, DMC래미안클라시스)3686카페프리헷 남가좌점2024-02-01 17:07:28I2023-12-02 00:03:00.0식품자동판매기영업192559.994725452852.020155<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205131200003120000-112-2024-000032024-03-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3120-140서울특별시 서대문구 신촌동 134 세브란스병원서울특별시 서대문구 연세로 50-1, 신종합관 지하1층 (신촌동)3722지에스25 연세장례식장 1호점2024-03-12 14:48:46I2023-12-02 23:04:00.0식품자동판매기영업194584.959249451381.585492<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205231200003120000-112-2024-000042024-04-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3120-012서울특별시 서대문구 충정로2가 107서울특별시 서대문구 충정로9길 16, 1층 (충정로2가)3736카페 만월경 충정로점2024-04-16 13:12:24I2023-12-03 23:08:00.0식품자동판매기영업196791.469788451356.274986<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205331200003120000-112-2024-000052024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2.0120-832서울특별시 서대문구 연희동 609서울특별시 서대문구 증가로 83, 1층 (연희동)3700GS25 서대문연희점2024-04-17 10:16:46I2023-12-03 23:09:00.0식품자동판매기영업193467.836973452491.540026<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205431200003120000-112-2024-000062024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0120-807서울특별시 서대문구 남가좌동 342-4서울특별시 서대문구 증가로10길 36-8, 1층 (남가좌동)3665같이,가치(Gachi Gachi)2024-04-23 10:28:01I2023-12-03 22:05:00.0식품자동판매기영업193246.337473452910.49745<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205531200003120000-112-2024-000072024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA>02 33049996.6120-100서울특별시 서대문구 홍은동 433 아름인도서관 양측서울특별시 서대문구 연희로 262-32, 아름인도서관 양측 (홍은동)3653서대문구청 카페폭포2024-04-29 14:23:29I2023-12-05 00:01:00.0식품자동판매기영업194368.454372453199.635156<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>