Overview

Dataset statistics

Number of variables44
Number of observations4111
Missing cells42184
Missing cells (%)23.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory376.0 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
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-18228/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (71.9%)Imbalance
영업상태명 is highly imbalanced (71.9%)Imbalance
상세영업상태코드 is highly imbalanced (71.9%)Imbalance
상세영업상태명 is highly imbalanced (71.9%)Imbalance
데이터갱신구분 is highly imbalanced (67.7%)Imbalance
위생업태명 is highly imbalanced (82.0%)Imbalance
남성종사자수 is highly imbalanced (88.4%)Imbalance
여성종사자수 is highly imbalanced (82.0%)Imbalance
등급구분명 is highly imbalanced (56.7%)Imbalance
급수시설구분명 is highly imbalanced (57.0%)Imbalance
총인원 is highly imbalanced (82.0%)Imbalance
본사종업원수 is highly imbalanced (88.4%)Imbalance
공장사무직종업원수 is highly imbalanced (82.0%)Imbalance
공장판매직종업원수 is highly imbalanced (82.0%)Imbalance
공장생산직종업원수 is highly imbalanced (82.0%)Imbalance
건물소유구분명 is highly imbalanced (53.7%)Imbalance
보증액 is highly imbalanced (82.0%)Imbalance
월세액 is highly imbalanced (82.0%)Imbalance
인허가취소일자 has 4111 (100.0%) missing valuesMissing
폐업일자 has 200 (4.9%) missing valuesMissing
휴업시작일자 has 4111 (100.0%) missing valuesMissing
휴업종료일자 has 4111 (100.0%) missing valuesMissing
재개업일자 has 4111 (100.0%) missing valuesMissing
전화번호 has 471 (11.5%) missing valuesMissing
소재지면적 has 3714 (90.3%) missing valuesMissing
도로명주소 has 3512 (85.4%) missing valuesMissing
도로명우편번호 has 3526 (85.8%) missing valuesMissing
좌표정보(X) has 876 (21.3%) missing valuesMissing
좌표정보(Y) has 876 (21.3%) missing valuesMissing
다중이용업소여부 has 112 (2.7%) missing valuesMissing
시설총규모 has 112 (2.7%) missing valuesMissing
전통업소지정번호 has 4111 (100.0%) missing valuesMissing
전통업소주된음식 has 4111 (100.0%) missing valuesMissing
홈페이지 has 4111 (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
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 115 (2.8%) zerosZeros
시설총규모 has 3839 (93.4%) zerosZeros

Reproduction

Analysis started2024-05-17 22:57:49.661460
Analysis finished2024-05-17 22:57:52.292155
Duration2.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
3010000
4111 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 4111
100.0%

Length

2024-05-18T07:57:52.451405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:57:52.634822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 4111
100.0%

관리번호
Text

UNIQUE 

Distinct4111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
2024-05-18T07:57:52.952655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters90442
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

Unique4111 ?
Unique (%)100.0%

Sample

1st row3010000-112-1981-00801
2nd row3010000-112-1981-00802
3rd row3010000-112-1981-00803
4th row3010000-112-1981-00813
5th row3010000-112-1981-00890
ValueCountFrequency (%)
3010000-112-1981-00801 1
 
< 0.1%
3010000-112-1999-00248 1
 
< 0.1%
3010000-112-1999-00423 1
 
< 0.1%
3010000-112-1999-00410 1
 
< 0.1%
3010000-112-1999-00411 1
 
< 0.1%
3010000-112-1999-00412 1
 
< 0.1%
3010000-112-1999-00413 1
 
< 0.1%
3010000-112-1999-00414 1
 
< 0.1%
3010000-112-1999-00415 1
 
< 0.1%
3010000-112-1999-00416 1
 
< 0.1%
Other values (4101) 4101
99.8%
2024-05-18T07:57:53.539792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 31130
34.4%
1 18498
20.5%
- 12333
 
13.6%
2 8254
 
9.1%
9 6717
 
7.4%
3 5777
 
6.4%
8 2234
 
2.5%
5 1596
 
1.8%
4 1332
 
1.5%
6 1321
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78109
86.4%
Dash Punctuation 12333
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31130
39.9%
1 18498
23.7%
2 8254
 
10.6%
9 6717
 
8.6%
3 5777
 
7.4%
8 2234
 
2.9%
5 1596
 
2.0%
4 1332
 
1.7%
6 1321
 
1.7%
7 1250
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 12333
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31130
34.4%
1 18498
20.5%
- 12333
 
13.6%
2 8254
 
9.1%
9 6717
 
7.4%
3 5777
 
6.4%
8 2234
 
2.5%
5 1596
 
1.8%
4 1332
 
1.5%
6 1321
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31130
34.4%
1 18498
20.5%
- 12333
 
13.6%
2 8254
 
9.1%
9 6717
 
7.4%
3 5777
 
6.4%
8 2234
 
2.5%
5 1596
 
1.8%
4 1332
 
1.5%
6 1321
 
1.5%

인허가일자
Date

Distinct1439
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
Minimum1981-08-31 00:00:00
Maximum2024-05-03 00:00:00
2024-05-18T07:57:53.804824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:57:54.244193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4111
Missing (%)100.0%
Memory size36.3 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
3
3911 
1
 
200

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 3911
95.1%
1 200
 
4.9%

Length

2024-05-18T07:57:54.646801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:57:54.954335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3911
95.1%
1 200
 
4.9%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
폐업
3911 
영업/정상
 
200

Length

Max length5
Median length2
Mean length2.1459499
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3911
95.1%
영업/정상 200
 
4.9%

Length

2024-05-18T07:57:55.279959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:57:55.602579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3911
95.1%
영업/정상 200
 
4.9%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
2
3911 
1
 
200

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 3911
95.1%
1 200
 
4.9%

Length

2024-05-18T07:57:55.904695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:57:56.243408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3911
95.1%
1 200
 
4.9%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
폐업
3911 
영업
 
200

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 3911
95.1%
영업 200
 
4.9%

Length

2024-05-18T07:57:56.577100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:57:56.869914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3911
95.1%
영업 200
 
4.9%

폐업일자
Date

MISSING 

Distinct1433
Distinct (%)36.6%
Missing200
Missing (%)4.9%
Memory size32.2 KiB
Minimum1986-03-17 00:00:00
Maximum2024-05-03 00:00:00
2024-05-18T07:57:57.254604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:57:57.781556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4111
Missing (%)100.0%
Memory size36.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4111
Missing (%)100.0%
Memory size36.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4111
Missing (%)100.0%
Memory size36.3 KiB

전화번호
Text

MISSING 

Distinct1071
Distinct (%)29.4%
Missing471
Missing (%)11.5%
Memory size32.2 KiB
2024-05-18T07:57:58.383764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.2681319
Min length2

Characters and Unicode

Total characters22816
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique940 ?
Unique (%)25.8%

Sample

1st row02
2nd row02
3rd row02
4th row02
5th row02
ValueCountFrequency (%)
02 2350
53.4%
0200000000 283
 
6.4%
0 84
 
1.9%
5111762 67
 
1.5%
3351941 24
 
0.5%
028015 18
 
0.4%
015 17
 
0.4%
0234720333 17
 
0.4%
0205621191 17
 
0.4%
3925492 15
 
0.3%
Other values (1105) 1510
34.3%
2024-05-18T07:57:59.471774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7177
31.5%
2 5814
25.5%
7 1459
 
6.4%
1 1381
 
6.1%
3 1372
 
6.0%
5 1135
 
5.0%
1103
 
4.8%
6 990
 
4.3%
4 813
 
3.6%
8 802
 
3.5%
Other values (2) 770
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21711
95.2%
Space Separator 1103
 
4.8%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7177
33.1%
2 5814
26.8%
7 1459
 
6.7%
1 1381
 
6.4%
3 1372
 
6.3%
5 1135
 
5.2%
6 990
 
4.6%
4 813
 
3.7%
8 802
 
3.7%
9 768
 
3.5%
Space Separator
ValueCountFrequency (%)
1103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22816
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7177
31.5%
2 5814
25.5%
7 1459
 
6.4%
1 1381
 
6.1%
3 1372
 
6.0%
5 1135
 
5.0%
1103
 
4.8%
6 990
 
4.3%
4 813
 
3.6%
8 802
 
3.5%
Other values (2) 770
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22816
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7177
31.5%
2 5814
25.5%
7 1459
 
6.4%
1 1381
 
6.1%
3 1372
 
6.0%
5 1135
 
5.0%
1103
 
4.8%
6 990
 
4.3%
4 813
 
3.6%
8 802
 
3.5%
Other values (2) 770
 
3.4%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct50
Distinct (%)12.6%
Missing3714
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean4.3820151
Minimum0
Maximum137.98
Zeros115
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2024-05-18T07:57:59.959342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.3
Q33.3
95-th percentile17.664
Maximum137.98
Range137.98
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation10.714576
Coefficient of variation (CV)2.4451253
Kurtosis70.529777
Mean4.3820151
Median Absolute Deviation (MAD)0.9
Skewness7.2525022
Sum1739.66
Variance114.80214
MonotonicityNot monotonic
2024-05-18T07:58:00.436736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 167
 
4.1%
0.0 115
 
2.8%
3.0 14
 
0.3%
2.4 13
 
0.3%
6.6 10
 
0.2%
1.0 9
 
0.2%
2.21 8
 
0.2%
2.0 6
 
0.1%
3.6 4
 
0.1%
6.0 4
 
0.1%
Other values (40) 47
 
1.1%
(Missing) 3714
90.3%
ValueCountFrequency (%)
0.0 115
2.8%
0.3 1
 
< 0.1%
0.5 3
 
0.1%
0.8 1
 
< 0.1%
0.96 1
 
< 0.1%
1.0 9
 
0.2%
1.09 1
 
< 0.1%
1.5 2
 
< 0.1%
1.8 1
 
< 0.1%
2.0 6
 
0.1%
ValueCountFrequency (%)
137.98 1
< 0.1%
70.2 1
< 0.1%
69.42 1
< 0.1%
52.61 1
< 0.1%
51.0 1
< 0.1%
49.5 1
< 0.1%
40.0 2
< 0.1%
39.72 1
< 0.1%
37.51 1
< 0.1%
36.3 1
< 0.1%

소재지우편번호
Text

Distinct231
Distinct (%)5.6%
Missing4
Missing (%)0.1%
Memory size32.2 KiB
2024-05-18T07:58:01.217106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0177745
Min length6

Characters and Unicode

Total characters24715
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

Unique56 ?
Unique (%)1.4%

Sample

1st row100141
2nd row100141
3rd row100141
4th row100372
5th row100855
ValueCountFrequency (%)
100101 139
 
3.4%
100070 118
 
2.9%
100851 99
 
2.4%
100865 96
 
2.3%
100814 92
 
2.2%
100813 92
 
2.2%
100802 91
 
2.2%
100092 89
 
2.2%
100162 88
 
2.1%
100855 78
 
1.9%
Other values (221) 3125
76.1%
2024-05-18T07:58:02.524227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10364
41.9%
1 6125
24.8%
8 2432
 
9.8%
2 1198
 
4.8%
4 1026
 
4.2%
3 854
 
3.5%
5 837
 
3.4%
6 612
 
2.5%
9 603
 
2.4%
7 591
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24642
99.7%
Dash Punctuation 73
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10364
42.1%
1 6125
24.9%
8 2432
 
9.9%
2 1198
 
4.9%
4 1026
 
4.2%
3 854
 
3.5%
5 837
 
3.4%
6 612
 
2.5%
9 603
 
2.4%
7 591
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24715
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10364
41.9%
1 6125
24.8%
8 2432
 
9.8%
2 1198
 
4.8%
4 1026
 
4.2%
3 854
 
3.5%
5 837
 
3.4%
6 612
 
2.5%
9 603
 
2.4%
7 591
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24715
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10364
41.9%
1 6125
24.8%
8 2432
 
9.8%
2 1198
 
4.8%
4 1026
 
4.2%
3 854
 
3.5%
5 837
 
3.4%
6 612
 
2.5%
9 603
 
2.4%
7 591
 
2.4%

지번주소
Text

Distinct2401
Distinct (%)58.5%
Missing4
Missing (%)0.1%
Memory size32.2 KiB
2024-05-18T07:58:03.221050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length21.772583
Min length14

Characters and Unicode

Total characters89420
Distinct characters372
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

Unique1984 ?
Unique (%)48.3%

Sample

1st row서울특별시 중구 의주로1가 1-0
2nd row서울특별시 중구 의주로1가 1-0
3rd row서울특별시 중구 의주로1가 1-0
4th row서울특별시 중구 만리동2가 47-3
5th row서울특별시 중구 장충동2가 4-0
ValueCountFrequency (%)
중구 4108
22.9%
서울특별시 4107
22.9%
신당동 502
 
2.8%
서소문동 190
 
1.1%
을지로6가 184
 
1.0%
남대문로5가 167
 
0.9%
1층 161
 
0.9%
을지로2가 147
 
0.8%
태평로1가 140
 
0.8%
1-0 139
 
0.8%
Other values (2233) 8095
45.1%
2024-05-18T07:58:04.393364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17811
19.9%
1 4702
 
5.3%
서 4331
 
4.8%
중 4187
 
4.7%
구 4174
 
4.7%
시 4151
 
4.6%
울 4138
 
4.6%
별 4113
 
4.6%
특 4107
 
4.6%
- 3862
 
4.3%
Other values (362) 33844
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49018
54.8%
Decimal Number 18039
 
20.2%
Space Separator 17811
 
19.9%
Dash Punctuation 3862
 
4.3%
Open Punctuation 243
 
0.3%
Close Punctuation 243
 
0.3%
Uppercase Letter 135
 
0.2%
Other Punctuation 36
 
< 0.1%
Lowercase Letter 33
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 4331
 
8.8%
중 4187
 
8.5%
구 4174
 
8.5%
시 4151
 
8.5%
울 4138
 
8.4%
별 4113
 
8.4%
특 4107
 
8.4%
동 2737
 
5.6%
가 2444
 
5.0%
로 1617
 
3.3%
Other values (303) 13019
26.6%
Uppercase Letter
ValueCountFrequency (%)
B 21
15.6%
S 17
12.6%
K 12
 
8.9%
G 11
 
8.1%
C 9
 
6.7%
U 8
 
5.9%
D 8
 
5.9%
T 7
 
5.2%
M 6
 
4.4%
L 5
 
3.7%
Other values (12) 31
23.0%
Lowercase Letter
ValueCountFrequency (%)
o 6
18.2%
e 4
12.1%
l 3
9.1%
t 2
 
6.1%
n 2
 
6.1%
g 2
 
6.1%
r 2
 
6.1%
a 2
 
6.1%
m 2
 
6.1%
x 1
 
3.0%
Other values (7) 7
21.2%
Decimal Number
ValueCountFrequency (%)
1 4702
26.1%
2 2944
16.3%
0 2605
14.4%
3 1594
 
8.8%
5 1514
 
8.4%
4 1110
 
6.2%
6 1031
 
5.7%
8 920
 
5.1%
7 899
 
5.0%
9 720
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 24
66.7%
/ 7
 
19.4%
. 3
 
8.3%
& 1
 
2.8%
: 1
 
2.8%
Close Punctuation
ValueCountFrequency (%)
) 242
99.6%
] 1
 
0.4%
Space Separator
ValueCountFrequency (%)
17811
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3862
100.0%
Open Punctuation
ValueCountFrequency (%)
( 243
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49018
54.8%
Common 40234
45.0%
Latin 168
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 4331
 
8.8%
중 4187
 
8.5%
구 4174
 
8.5%
시 4151
 
8.5%
울 4138
 
8.4%
별 4113
 
8.4%
특 4107
 
8.4%
동 2737
 
5.6%
가 2444
 
5.0%
로 1617
 
3.3%
Other values (303) 13019
26.6%
Latin
ValueCountFrequency (%)
B 21
 
12.5%
S 17
 
10.1%
K 12
 
7.1%
G 11
 
6.5%
C 9
 
5.4%
U 8
 
4.8%
D 8
 
4.8%
T 7
 
4.2%
o 6
 
3.6%
M 6
 
3.6%
Other values (29) 63
37.5%
Common
ValueCountFrequency (%)
17811
44.3%
1 4702
 
11.7%
- 3862
 
9.6%
2 2944
 
7.3%
0 2605
 
6.5%
3 1594
 
4.0%
5 1514
 
3.8%
4 1110
 
2.8%
6 1031
 
2.6%
8 920
 
2.3%
Other values (10) 2141
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49018
54.8%
ASCII 40402
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17811
44.1%
1 4702
 
11.6%
- 3862
 
9.6%
2 2944
 
7.3%
0 2605
 
6.4%
3 1594
 
3.9%
5 1514
 
3.7%
4 1110
 
2.7%
6 1031
 
2.6%
8 920
 
2.3%
Other values (49) 2309
 
5.7%
Hangul
ValueCountFrequency (%)
서 4331
 
8.8%
중 4187
 
8.5%
구 4174
 
8.5%
시 4151
 
8.5%
울 4138
 
8.4%
별 4113
 
8.4%
특 4107
 
8.4%
동 2737
 
5.6%
가 2444
 
5.0%
로 1617
 
3.3%
Other values (303) 13019
26.6%

도로명주소
Text

MISSING 

Distinct544
Distinct (%)90.8%
Missing3512
Missing (%)85.4%
Memory size32.2 KiB
2024-05-18T07:58:05.082628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length46
Mean length30.776294
Min length19

Characters and Unicode

Total characters18435
Distinct characters329
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

Unique514 ?
Unique (%)85.8%

Sample

1st row서울특별시 중구 칠패로 46 (봉래동1가)
2nd row서울특별시 중구 마장로1길 31 (신당동)
3rd row서울특별시 중구 명동8길 3 (명동2가)
4th row서울특별시 중구 수표로6길 33-2 (충무로3가)
5th row서울특별시 중구 장충단로13길 34 (을지로6가)
ValueCountFrequency (%)
중구 600
 
16.1%
서울특별시 599
 
16.1%
1층 156
 
4.2%
신당동 94
 
2.5%
을지로 65
 
1.7%
지하 57
 
1.5%
퇴계로 54
 
1.4%
지하1층 36
 
1.0%
세종대로 33
 
0.9%
다산로 27
 
0.7%
Other values (789) 2004
53.8%
2024-05-18T07:58:06.247797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3127
 
17.0%
1 811
 
4.4%
로 793
 
4.3%
서 653
 
3.5%
) 650
 
3.5%
( 650
 
3.5%
구 640
 
3.5%
시 621
 
3.4%
중 621
 
3.4%
울 607
 
3.3%
Other values (319) 9262
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10643
57.7%
Space Separator 3127
 
17.0%
Decimal Number 2731
 
14.8%
Close Punctuation 650
 
3.5%
Open Punctuation 650
 
3.5%
Other Punctuation 461
 
2.5%
Uppercase Letter 82
 
0.4%
Dash Punctuation 59
 
0.3%
Lowercase Letter 32
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 793
 
7.5%
서 653
 
6.1%
구 640
 
6.0%
시 621
 
5.8%
중 621
 
5.8%
울 607
 
5.7%
별 601
 
5.6%
특 599
 
5.6%
동 517
 
4.9%
가 361
 
3.4%
Other values (264) 4630
43.5%
Uppercase Letter
ValueCountFrequency (%)
B 14
17.1%
S 8
9.8%
G 8
9.8%
U 7
8.5%
C 6
 
7.3%
K 6
 
7.3%
T 6
 
7.3%
E 5
 
6.1%
R 3
 
3.7%
M 3
 
3.7%
Other values (10) 16
19.5%
Lowercase Letter
ValueCountFrequency (%)
o 5
15.6%
e 4
12.5%
l 3
9.4%
g 2
 
6.2%
n 2
 
6.2%
t 2
 
6.2%
r 2
 
6.2%
a 2
 
6.2%
m 2
 
6.2%
d 1
 
3.1%
Other values (7) 7
21.9%
Decimal Number
ValueCountFrequency (%)
1 811
29.7%
2 455
16.7%
3 261
 
9.6%
0 231
 
8.5%
4 216
 
7.9%
5 194
 
7.1%
6 163
 
6.0%
7 147
 
5.4%
9 131
 
4.8%
8 122
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 458
99.3%
& 1
 
0.2%
: 1
 
0.2%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 650
100.0%
Open Punctuation
ValueCountFrequency (%)
( 650
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10643
57.7%
Common 7678
41.6%
Latin 114
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 793
 
7.5%
서 653
 
6.1%
구 640
 
6.0%
시 621
 
5.8%
중 621
 
5.8%
울 607
 
5.7%
별 601
 
5.6%
특 599
 
5.6%
동 517
 
4.9%
가 361
 
3.4%
Other values (264) 4630
43.5%
Latin
ValueCountFrequency (%)
B 14
 
12.3%
S 8
 
7.0%
G 8
 
7.0%
U 7
 
6.1%
C 6
 
5.3%
K 6
 
5.3%
T 6
 
5.3%
o 5
 
4.4%
E 5
 
4.4%
e 4
 
3.5%
Other values (27) 45
39.5%
Common
ValueCountFrequency (%)
3127
40.7%
1 811
 
10.6%
) 650
 
8.5%
( 650
 
8.5%
, 458
 
6.0%
2 455
 
5.9%
3 261
 
3.4%
0 231
 
3.0%
4 216
 
2.8%
5 194
 
2.5%
Other values (8) 625
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10643
57.7%
ASCII 7792
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3127
40.1%
1 811
 
10.4%
) 650
 
8.3%
( 650
 
8.3%
, 458
 
5.9%
2 455
 
5.8%
3 261
 
3.3%
0 231
 
3.0%
4 216
 
2.8%
5 194
 
2.5%
Other values (45) 739
 
9.5%
Hangul
ValueCountFrequency (%)
로 793
 
7.5%
서 653
 
6.1%
구 640
 
6.0%
시 621
 
5.8%
중 621
 
5.8%
울 607
 
5.7%
별 601
 
5.6%
특 599
 
5.6%
동 517
 
4.9%
가 361
 
3.4%
Other values (264) 4630
43.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)20.7%
Missing3526
Missing (%)85.8%
Infinite0
Infinite (%)0.0%
Mean4562.8342
Minimum4501
Maximum4637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2024-05-18T07:58:06.971794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4501
5-th percentile4511
Q14533
median4558
Q34595
95-th percentile4630.6
Maximum4637
Range136
Interquartile range (IQR)62

Descriptive statistics

Standard deviation37.664773
Coefficient of variation (CV)0.0082546881
Kurtosis-0.9511322
Mean4562.8342
Median Absolute Deviation (MAD)29
Skewness0.37434465
Sum2669258
Variance1418.6351
MonotonicityNot monotonic
2024-05-18T07:58:07.513515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4513 17
 
0.4%
4563 16
 
0.4%
4509 15
 
0.4%
4558 13
 
0.3%
4533 13
 
0.3%
4566 12
 
0.3%
4608 12
 
0.3%
4549 12
 
0.3%
4515 11
 
0.3%
4550 10
 
0.2%
Other values (111) 454
 
11.0%
(Missing) 3526
85.8%
ValueCountFrequency (%)
4501 1
 
< 0.1%
4502 1
 
< 0.1%
4503 1
 
< 0.1%
4504 1
 
< 0.1%
4505 6
 
0.1%
4507 1
 
< 0.1%
4509 15
0.4%
4510 3
 
0.1%
4511 5
 
0.1%
4512 1
 
< 0.1%
ValueCountFrequency (%)
4637 9
0.2%
4635 2
 
< 0.1%
4634 8
0.2%
4633 2
 
< 0.1%
4632 3
 
0.1%
4631 6
0.1%
4629 3
 
0.1%
4628 4
0.1%
4627 6
0.1%
4626 6
0.1%

사업장명
Text

Distinct2377
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
2024-05-18T07:58:08.186654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length5.3249818
Min length1

Characters and Unicode

Total characters21891
Distinct characters593
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2009 ?
Unique (%)48.9%

Sample

1st row지석환
2nd row지석환
3rd row지석환
4th row박희웅
5th row김정자
ValueCountFrequency (%)
오광열 85
 
1.8%
주)보광훼미리마트 77
 
1.7%
배영식 64
 
1.4%
자판기 54
 
1.2%
씨유 50
 
1.1%
김선제 48
 
1.0%
gs25 40
 
0.9%
주)휘닉스벤딩서비스 36
 
0.8%
개빈페이튼 36
 
0.8%
심완조 32
 
0.7%
Other values (2425) 4073
88.6%
2024-05-18T07:58:09.415397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
485
 
2.2%
( 457
 
2.1%
) 451
 
2.1%
김 409
 
1.9%
이 404
 
1.8%
주 397
 
1.8%
기 319
 
1.5%
점 310
 
1.4%
동 293
 
1.3%
호 291
 
1.3%
Other values (583) 18075
82.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18974
86.7%
Decimal Number 1086
 
5.0%
Space Separator 485
 
2.2%
Open Punctuation 457
 
2.1%
Close Punctuation 451
 
2.1%
Uppercase Letter 342
 
1.6%
Other Punctuation 48
 
0.2%
Dash Punctuation 27
 
0.1%
Lowercase Letter 20
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 409
 
2.2%
이 404
 
2.1%
주 397
 
2.1%
기 319
 
1.7%
점 310
 
1.6%
동 293
 
1.5%
호 291
 
1.5%
식 279
 
1.5%
지 277
 
1.5%
선 251
 
1.3%
Other values (529) 15744
83.0%
Uppercase Letter
ValueCountFrequency (%)
S 74
21.6%
G 73
21.3%
C 43
12.6%
U 34
9.9%
L 20
 
5.8%
T 13
 
3.8%
K 13
 
3.8%
M 12
 
3.5%
D 11
 
3.2%
B 10
 
2.9%
Other values (12) 39
11.4%
Lowercase Letter
ValueCountFrequency (%)
o 3
15.0%
t 3
15.0%
n 2
10.0%
c 2
10.0%
s 2
10.0%
a 2
10.0%
y 2
10.0%
x 1
 
5.0%
v 1
 
5.0%
r 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
2 276
25.4%
1 177
16.3%
3 139
12.8%
5 126
11.6%
0 117
10.8%
4 117
10.8%
6 45
 
4.1%
8 44
 
4.1%
7 29
 
2.7%
9 16
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 25
52.1%
* 12
25.0%
/ 4
 
8.3%
: 4
 
8.3%
, 2
 
4.2%
& 1
 
2.1%
Space Separator
ValueCountFrequency (%)
485
100.0%
Open Punctuation
ValueCountFrequency (%)
( 457
100.0%
Close Punctuation
ValueCountFrequency (%)
) 451
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18973
86.7%
Common 2555
 
11.7%
Latin 362
 
1.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 409
 
2.2%
이 404
 
2.1%
주 397
 
2.1%
기 319
 
1.7%
점 310
 
1.6%
동 293
 
1.5%
호 291
 
1.5%
식 279
 
1.5%
지 277
 
1.5%
선 251
 
1.3%
Other values (528) 15743
83.0%
Latin
ValueCountFrequency (%)
S 74
20.4%
G 73
20.2%
C 43
11.9%
U 34
9.4%
L 20
 
5.5%
T 13
 
3.6%
K 13
 
3.6%
M 12
 
3.3%
D 11
 
3.0%
B 10
 
2.8%
Other values (23) 59
16.3%
Common
ValueCountFrequency (%)
485
19.0%
( 457
17.9%
) 451
17.7%
2 276
10.8%
1 177
 
6.9%
3 139
 
5.4%
5 126
 
4.9%
0 117
 
4.6%
4 117
 
4.6%
6 45
 
1.8%
Other values (11) 165
 
6.5%
Han
ValueCountFrequency (%)
貞 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18973
86.7%
ASCII 2917
 
13.3%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
485
16.6%
( 457
15.7%
) 451
15.5%
2 276
9.5%
1 177
 
6.1%
3 139
 
4.8%
5 126
 
4.3%
0 117
 
4.0%
4 117
 
4.0%
S 74
 
2.5%
Other values (44) 498
17.1%
Hangul
ValueCountFrequency (%)
김 409
 
2.2%
이 404
 
2.1%
주 397
 
2.1%
기 319
 
1.7%
점 310
 
1.6%
동 293
 
1.5%
호 291
 
1.5%
식 279
 
1.5%
지 277
 
1.5%
선 251
 
1.3%
Other values (528) 15743
83.0%
CJK
ValueCountFrequency (%)
貞 1
100.0%

최종수정일자
Date

Distinct1413
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
Minimum1999-03-03 00:00:00
Maximum2024-05-03 11:27:57
2024-05-18T07:58:09.966531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:58:10.378420image/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 size32.2 KiB
I
3869 
U
 
242

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 3869
94.1%
U 242
 
5.9%

Length

2024-05-18T07:58:10.768095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:11.043798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3869
94.1%
u 242
 
5.9%

데이터갱신일자
Date

Distinct242
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-18T07:58:11.379599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:58:11.959947image/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 size32.2 KiB
식품자동판매기영업
4111 

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 4111
100.0%

Length

2024-05-18T07:58:12.469939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:12.788138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 4111
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1270
Distinct (%)39.3%
Missing876
Missing (%)21.3%
Infinite0
Infinite (%)0.0%
Mean199041.18
Minimum196566.38
Maximum202207.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2024-05-18T07:58:13.064657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196566.38
5-th percentile197346.66
Q1197964.1
median198619.39
Q3200298.4
95-th percentile201442.04
Maximum202207.97
Range5641.5896
Interquartile range (IQR)2334.3012

Descriptive statistics

Standard deviation1344.198
Coefficient of variation (CV)0.0067533661
Kurtosis-0.94500946
Mean199041.18
Median Absolute Deviation (MAD)901.76979
Skewness0.52930105
Sum6.4389822 × 108
Variance1806868.1
MonotonicityNot monotonic
2024-05-18T07:58:13.583417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198259.65357739 77
 
1.9%
198004.737917005 62
 
1.5%
197761.440311167 57
 
1.4%
197243.215346366 45
 
1.1%
200703.625559248 41
 
1.0%
197675.397522479 40
 
1.0%
200463.625303538 39
 
0.9%
197511.245797769 34
 
0.8%
198338.095599974 34
 
0.8%
198744.433228989 33
 
0.8%
Other values (1260) 2773
67.5%
(Missing) 876
 
21.3%
ValueCountFrequency (%)
196566.377385638 1
< 0.1%
196606.636582259 1
< 0.1%
196652.500708538 1
< 0.1%
196655.581895878 1
< 0.1%
196662.44522421 1
< 0.1%
196681.315894651 1
< 0.1%
196690.774845982 1
< 0.1%
196715.271566103 1
< 0.1%
196756.456139632 1
< 0.1%
196766.122640517 1
< 0.1%
ValueCountFrequency (%)
202207.966958973 1
 
< 0.1%
202185.725696826 1
 
< 0.1%
202128.136971071 8
0.2%
202054.715963905 1
 
< 0.1%
202044.047005629 1
 
< 0.1%
202011.800096 1
 
< 0.1%
201993.265455419 1
 
< 0.1%
201992.033568883 1
 
< 0.1%
201991.076017364 2
 
< 0.1%
201988.745220377 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1270
Distinct (%)39.3%
Missing876
Missing (%)21.3%
Infinite0
Infinite (%)0.0%
Mean451184.31
Minimum449547.1
Maximum452413.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2024-05-18T07:58:14.120447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449547.1
5-th percentile450422.76
Q1450912.84
median451248.14
Q3451559.18
95-th percentile451808.1
Maximum452413.41
Range2866.3092
Interquartile range (IQR)646.34143

Descriptive statistics

Standard deviation440.71673
Coefficient of variation (CV)0.00097679977
Kurtosis-0.047539015
Mean451184.31
Median Absolute Deviation (MAD)321.6198
Skewness-0.57832849
Sum1.4595812 × 109
Variance194231.24
MonotonicityNot monotonic
2024-05-18T07:58:14.676696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451392.198218657 77
 
1.9%
451589.338993848 62
 
1.5%
451123.194550747 57
 
1.4%
450655.104239931 45
 
1.1%
451836.458256618 41
 
1.0%
450448.56432183 40
 
1.0%
450497.460903907 39
 
0.9%
451114.28520546 34
 
0.8%
451573.129459787 34
 
0.8%
451677.065126229 33
 
0.8%
Other values (1260) 2773
67.5%
(Missing) 876
 
21.3%
ValueCountFrequency (%)
449547.103651161 1
 
< 0.1%
449611.221496994 2
 
< 0.1%
449638.824308081 6
0.1%
449670.613249189 1
 
< 0.1%
449729.790773778 2
 
< 0.1%
449809.744684888 3
0.1%
449868.526612013 1
 
< 0.1%
449877.44410054 2
 
< 0.1%
449946.116521469 1
 
< 0.1%
449947.401377686 2
 
< 0.1%
ValueCountFrequency (%)
452413.412894 1
 
< 0.1%
452076.818664092 5
0.1%
452016.629661945 1
 
< 0.1%
452008.928365747 1
 
< 0.1%
452002.73062535 1
 
< 0.1%
451995.163058 4
0.1%
451958.495584927 2
 
< 0.1%
451956.351917092 1
 
< 0.1%
451908.773811626 4
0.1%
451906.158530262 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
식품자동판매기영업
3999 
<NA>
 
112

Length

Max length9
Median length9
Mean length8.8637801
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 3999
97.3%
<NA> 112
 
2.7%

Length

2024-05-18T07:58:15.210009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:15.673917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 3999
97.3%
na 112
 
2.7%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
0
3998 
<NA>
 
112
1
 
1

Length

Max length4
Median length1
Mean length1.0817319
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3998
97.3%
<NA> 112
 
2.7%
1 1
 
< 0.1%

Length

2024-05-18T07:58:16.034881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:16.397463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3998
97.3%
na 112
 
2.7%
1 1
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
0
3999 
<NA>
 
112

Length

Max length4
Median length1
Mean length1.0817319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3999
97.3%
<NA> 112
 
2.7%

Length

2024-05-18T07:58:16.884068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:17.269525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3999
97.3%
na 112
 
2.7%

영업장주변구분명
Categorical

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
기타
1674 
결혼예식장주변
1336 
<NA>
987 
학교정화(상대)
 
43
학교정화(절대)
 
23
Other values (3)
 
48

Length

Max length8
Median length7
Mean length4.2466553
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 1674
40.7%
결혼예식장주변 1336
32.5%
<NA> 987
24.0%
학교정화(상대) 43
 
1.0%
학교정화(절대) 23
 
0.6%
아파트지역 21
 
0.5%
유흥업소밀집지역 14
 
0.3%
주택가주변 13
 
0.3%

Length

2024-05-18T07:58:17.776809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:18.248965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 1674
40.7%
결혼예식장주변 1336
32.5%
na 987
24.0%
학교정화(상대 43
 
1.0%
학교정화(절대 23
 
0.6%
아파트지역 21
 
0.5%
유흥업소밀집지역 14
 
0.3%
주택가주변 13
 
0.3%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
기타
3089 
<NA>
987 
자율
 
33
지도
 
2

Length

Max length4
Median length2
Mean length2.4801751
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 3089
75.1%
<NA> 987
 
24.0%
자율 33
 
0.8%
지도 2
 
< 0.1%

Length

2024-05-18T07:58:18.696009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:19.069009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 3089
75.1%
na 987
 
24.0%
자율 33
 
0.8%
지도 2
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
<NA>
3749 
상수도전용
 
362

Length

Max length5
Median length4
Mean length4.0880564
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> 3749
91.2%
상수도전용 362
 
8.8%

Length

2024-05-18T07:58:19.625802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:19.981620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3749
91.2%
상수도전용 362
 
8.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
0
3999 
<NA>
 
112

Length

Max length4
Median length1
Mean length1.0817319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3999
97.3%
<NA> 112
 
2.7%

Length

2024-05-18T07:58:20.459872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:20.880249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3999
97.3%
na 112
 
2.7%

본사종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
0
3998 
<NA>
 
112
1
 
1

Length

Max length4
Median length1
Mean length1.0817319
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3998
97.3%
<NA> 112
 
2.7%
1 1
 
< 0.1%

Length

2024-05-18T07:58:21.317215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:21.721524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3998
97.3%
na 112
 
2.7%
1 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
0
3999 
<NA>
 
112

Length

Max length4
Median length1
Mean length1.0817319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3999
97.3%
<NA> 112
 
2.7%

Length

2024-05-18T07:58:22.214066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:22.656993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3999
97.3%
na 112
 
2.7%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
0
3999 
<NA>
 
112

Length

Max length4
Median length1
Mean length1.0817319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3999
97.3%
<NA> 112
 
2.7%

Length

2024-05-18T07:58:23.132492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:23.495291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3999
97.3%
na 112
 
2.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
0
3999 
<NA>
 
112

Length

Max length4
Median length1
Mean length1.0817319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3999
97.3%
<NA> 112
 
2.7%

Length

2024-05-18T07:58:23.820582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:24.229112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3999
97.3%
na 112
 
2.7%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
<NA>
3459 
자가
544 
임대
 
108

Length

Max length4
Median length4
Mean length3.6828022
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> 3459
84.1%
자가 544
 
13.2%
임대 108
 
2.6%

Length

2024-05-18T07:58:24.677855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:25.065615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3459
84.1%
자가 544
 
13.2%
임대 108
 
2.6%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
0
3999 
<NA>
 
112

Length

Max length4
Median length1
Mean length1.0817319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3999
97.3%
<NA> 112
 
2.7%

Length

2024-05-18T07:58:25.571057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:25.954614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3999
97.3%
na 112
 
2.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 KiB
0
3999 
<NA>
 
112

Length

Max length4
Median length1
Mean length1.0817319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3999
97.3%
<NA> 112
 
2.7%

Length

2024-05-18T07:58:26.399530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:58:27.116003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3999
97.3%
na 112
 
2.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing112
Missing (%)2.7%
Memory size8.2 KiB
False
3999 
(Missing)
 
112
ValueCountFrequency (%)
False 3999
97.3%
(Missing) 112
 
2.7%
2024-05-18T07:58:27.463066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)0.6%
Missing112
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean0.17090273
Minimum0
Maximum40
Zeros3839
Zeros (%)93.4%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2024-05-18T07:58:27.868661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum40
Range40
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2742108
Coefficient of variation (CV)7.4557663
Kurtosis473.75878
Mean0.17090273
Median Absolute Deviation (MAD)0
Skewness18.537828
Sum683.44
Variance1.6236131
MonotonicityNot monotonic
2024-05-18T07:58:28.319968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 3839
93.4%
3.3 111
 
2.7%
3.0 10
 
0.2%
6.6 7
 
0.2%
2.21 7
 
0.2%
2.4 3
 
0.1%
1.0 3
 
0.1%
3.6 3
 
0.1%
6.0 2
 
< 0.1%
36.3 1
 
< 0.1%
Other values (13) 13
 
0.3%
(Missing) 112
 
2.7%
ValueCountFrequency (%)
0.0 3839
93.4%
0.8 1
 
< 0.1%
1.0 3
 
0.1%
1.09 1
 
< 0.1%
1.5 1
 
< 0.1%
2.21 7
 
0.2%
2.4 3
 
0.1%
3.0 10
 
0.2%
3.3 111
 
2.7%
3.33 1
 
< 0.1%
ValueCountFrequency (%)
40.0 1
 
< 0.1%
36.3 1
 
< 0.1%
24.0 1
 
< 0.1%
22.0 1
 
< 0.1%
20.13 1
 
< 0.1%
15.0 1
 
< 0.1%
10.0 1
 
< 0.1%
7.7 1
 
< 0.1%
6.6 7
0.2%
6.0 2
 
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4111
Missing (%)100.0%
Memory size36.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4111
Missing (%)100.0%
Memory size36.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4111
Missing (%)100.0%
Memory size36.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030100003010000-112-1981-0080119810831<NA>3폐업2폐업19970813<NA><NA><NA>02<NA>100141서울특별시 중구 의주로1가 1-0<NA><NA>지석환2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
130100003010000-112-1981-0080219810831<NA>3폐업2폐업19970813<NA><NA><NA>02<NA>100141서울특별시 중구 의주로1가 1-0<NA><NA>지석환2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
230100003010000-112-1981-0080319810831<NA>3폐업2폐업19970813<NA><NA><NA>02<NA>100141서울특별시 중구 의주로1가 1-0<NA><NA>지석환2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
330100003010000-112-1981-0081319810831<NA>3폐업2폐업19980203<NA><NA><NA>02<NA>100372서울특별시 중구 만리동2가 47-3<NA><NA>박희웅2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업196652.500709450312.902717식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
430100003010000-112-1981-0089019810831<NA>3폐업2폐업19980629<NA><NA><NA>02<NA>100855서울특별시 중구 장충동2가 4-0<NA><NA>김정자2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
530100003010000-112-1981-0089119810831<NA>3폐업2폐업19980629<NA><NA><NA>02<NA>100855서울특별시 중구 장충동2가 4-0<NA><NA>김정자2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
630100003010000-112-1981-0089219810831<NA>3폐업2폐업19980629<NA><NA><NA>02<NA>100855서울특별시 중구 장충동2가 4-0<NA><NA>김정자2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
730100003010000-112-1981-0089719810831<NA>3폐업2폐업19980629<NA><NA><NA>02<NA>100855서울특별시 중구 장충동2가 5-19<NA><NA>황의철2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
830100003010000-112-1981-0089819810831<NA>3폐업2폐업19980629<NA><NA><NA>02<NA>100855서울특별시 중구 장충동2가 5-19<NA><NA>황의철2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
930100003010000-112-1981-0092219810831<NA>3폐업2폐업19990705<NA><NA><NA>02<NA>100400서울특별시 중구 쌍림동 151-11<NA><NA>*2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업200247.098068451193.48296식품자동판매기영업00기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
410130100003010000-112-2023-000132023-10-25<NA>1영업/정상1영업<NA><NA><NA><NA>070863310573.3100-851서울특별시 중구 을지로6가 18-12서울특별시 중구 장충단로 275, 지하2층 (을지로6가)4563두타몰 지하2층 푸드코트2023-10-25 14:12:30I2022-10-30 22:07:00.0식품자동판매기영업200703.625559451836.458257<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
410230100003010000-112-2023-000142023-11-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.1100-851서울특별시 중구 을지로6가 18-12 두산타워빌딩서울특별시 중구 장충단로 275, 두산타워빌딩 28층 에듀케이션센터호 (을지로6가)456328층 에듀케이션센터2023-11-20 09:28:37I2022-10-31 22:02:00.0식품자동판매기영업200703.625559451836.458257<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
410330100003010000-112-2024-000012024-03-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>11.15100-192서울특별시 중구 을지로2가 206 IBK파이낸스타워서울특별시 중구 을지로 82, IBK파이낸스타워 2층 (을지로2가)4538무인판매IBK파이낸스2024-03-08 11:29:43I2023-12-02 23:00:00.0식품자동판매기영업198791.046999451496.52816<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
410430100003010000-112-2024-000022024-03-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3100-450서울특별시 중구 신당동 844 남산타운서울특별시 중구 다산로 32, 상가5동 118호 (신당동, 남산타운)4595데이롱 남산타운점 커피앤하이볼2024-03-13 10:55:17I2023-12-02 23:06:00.0식품자동판매기영업200750.455126449638.824308<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
410530100003010000-112-2024-000032024-03-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.2100-831서울특별시 중구 신당동 52-52서울특별시 중구 다산로40길 38, 1층 (신당동)4585데이롱 카페 신당점2024-03-20 11:03:37U2023-12-02 22:02:00.0식품자동판매기영업201528.584799451243.113921<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
410630100003010000-112-2024-000042024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3100-866서울특별시 중구 필동1가 35-1서울특별시 중구 퇴계로 192, 1층 (필동1가)4627지에스25 충무로본점2024-04-23 10:47:25I2023-12-03 22:05:00.0식품자동판매기영업199323.638867450944.799308<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
410730100003010000-112-2024-000052024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3100-400서울특별시 중구 쌍림동 148-2서울특별시 중구 퇴계로 290, 1층 (쌍림동)4615GS25 쌍림중앙2024-04-23 15:29:55I2023-12-03 22:05:00.0식품자동판매기영업200273.106026451226.152682<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
410830100003010000-112-2024-000062024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA>02 266109963.0100-850서울특별시 중구 을지로6가 17-2 현대시티타워서울특별시 중구 장충단로13길 20, 현대시티타워 지하1층 (을지로6가)4563주식회사 에버라인2024-04-25 09:17:16I2023-12-03 22:07:00.0식품자동판매기영업200613.510298451817.515367<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
410930100003010000-112-2024-000072024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0100-816서울특별시 중구 신당동 62-63서울특별시 중구 다산로36가길 26-8, 1층 (신당동)4584데이롱 카페 신당누리점2024-05-03 11:04:34I2023-12-05 00:05:00.0식품자동판매기영업201718.508092450979.121227<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
411030100003010000-112-2024-000082024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA>070 414395381.0100-011서울특별시 중구 충무로1가 24-1 밀레오레 명동서울특별시 중구 퇴계로 115, 밀레오레 명동 3층 305호 (충무로1가)4536(주)굿플레이스 밀리오레호텔점2024-05-03 11:27:57I2023-12-05 00:05:00.0식품자동판매기영업198562.632746450975.116406<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>