Overview

Dataset statistics

Number of variables44
Number of observations4007
Missing cells39883
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory376.0 B

Variable types

Categorical22
Text6
DateTime4
Unsupported7
Numeric4
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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-18250/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (63.9%)Imbalance
영업상태명 is highly imbalanced (63.9%)Imbalance
상세영업상태코드 is highly imbalanced (63.9%)Imbalance
상세영업상태명 is highly imbalanced (63.9%)Imbalance
데이터갱신구분 is highly imbalanced (69.0%)Imbalance
위생업태명 is highly imbalanced (76.4%)Imbalance
영업장주변구분명 is highly imbalanced (56.0%)Imbalance
급수시설구분명 is highly imbalanced (97.5%)Imbalance
총인원 is highly imbalanced (94.7%)Imbalance
본사종업원수 is highly imbalanced (63.9%)Imbalance
건물소유구분명 is highly imbalanced (58.8%)Imbalance
보증액 is highly imbalanced (63.2%)Imbalance
월세액 is highly imbalanced (63.2%)Imbalance
시설총규모 is highly imbalanced (84.7%)Imbalance
인허가취소일자 has 4007 (100.0%) missing valuesMissing
폐업일자 has 275 (6.9%) missing valuesMissing
휴업시작일자 has 4007 (100.0%) missing valuesMissing
휴업종료일자 has 4007 (100.0%) missing valuesMissing
재개업일자 has 4007 (100.0%) missing valuesMissing
전화번호 has 530 (13.2%) missing valuesMissing
소재지면적 has 3582 (89.4%) missing valuesMissing
도로명주소 has 3394 (84.7%) missing valuesMissing
도로명우편번호 has 3406 (85.0%) missing valuesMissing
좌표정보(X) has 242 (6.0%) missing valuesMissing
좌표정보(Y) has 242 (6.0%) missing valuesMissing
다중이용업소여부 has 155 (3.9%) missing valuesMissing
전통업소지정번호 has 4007 (100.0%) missing valuesMissing
전통업소주된음식 has 4007 (100.0%) missing valuesMissing
홈페이지 has 4007 (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

Reproduction

Analysis started2024-05-11 06:26:00.903675
Analysis finished2024-05-11 06:26:03.246901
Duration2.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
3230000
4007 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 4007
100.0%

Length

2024-05-11T15:26:03.340255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:03.476484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 4007
100.0%

관리번호
Text

UNIQUE 

Distinct4007
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
2024-05-11T15:26:03.756965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters88154
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

Unique4007 ?
Unique (%)100.0%

Sample

1st row3230000-112-1904-01004
2nd row3230000-112-1981-00997
3rd row3230000-112-1981-00998
4th row3230000-112-1981-00999
5th row3230000-112-1981-01000
ValueCountFrequency (%)
3230000-112-1904-01004 1
 
< 0.1%
3230000-112-2000-00680 1
 
< 0.1%
3230000-112-2000-00668 1
 
< 0.1%
3230000-112-2000-00696 1
 
< 0.1%
3230000-112-2000-00669 1
 
< 0.1%
3230000-112-2000-00670 1
 
< 0.1%
3230000-112-2000-00671 1
 
< 0.1%
3230000-112-2000-00672 1
 
< 0.1%
3230000-112-2000-00673 1
 
< 0.1%
3230000-112-2000-00674 1
 
< 0.1%
Other values (3997) 3997
99.8%
2024-05-11T15:26:04.347740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26558
30.1%
1 14027
15.9%
2 12539
14.2%
- 12021
13.6%
3 9719
 
11.0%
9 6664
 
7.6%
4 1525
 
1.7%
8 1414
 
1.6%
5 1299
 
1.5%
7 1242
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76133
86.4%
Dash Punctuation 12021
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26558
34.9%
1 14027
18.4%
2 12539
16.5%
3 9719
 
12.8%
9 6664
 
8.8%
4 1525
 
2.0%
8 1414
 
1.9%
5 1299
 
1.7%
7 1242
 
1.6%
6 1146
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 12021
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88154
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26558
30.1%
1 14027
15.9%
2 12539
14.2%
- 12021
13.6%
3 9719
 
11.0%
9 6664
 
7.6%
4 1525
 
1.7%
8 1414
 
1.6%
5 1299
 
1.5%
7 1242
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88154
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26558
30.1%
1 14027
15.9%
2 12539
14.2%
- 12021
13.6%
3 9719
 
11.0%
9 6664
 
7.6%
4 1525
 
1.7%
8 1414
 
1.6%
5 1299
 
1.5%
7 1242
 
1.4%

인허가일자
Date

Distinct1649
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
Minimum1981-09-01 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T15:26:04.658348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:26:05.027306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4007
Missing (%)100.0%
Memory size35.3 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
3
3732 
1
 
275

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 3732
93.1%
1 275
 
6.9%

Length

2024-05-11T15:26:05.312714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:05.600732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3732
93.1%
1 275
 
6.9%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
폐업
3732 
영업/정상
 
275

Length

Max length5
Median length2
Mean length2.2058897
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3732
93.1%
영업/정상 275
 
6.9%

Length

2024-05-11T15:26:05.787675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:05.972262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3732
93.1%
영업/정상 275
 
6.9%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
2
3732 
1
 
275

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 3732
93.1%
1 275
 
6.9%

Length

2024-05-11T15:26:06.144659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:06.315728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3732
93.1%
1 275
 
6.9%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
폐업
3732 
영업
 
275

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 3732
93.1%
영업 275
 
6.9%

Length

2024-05-11T15:26:06.493704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:06.754681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3732
93.1%
영업 275
 
6.9%

폐업일자
Date

MISSING 

Distinct1885
Distinct (%)50.5%
Missing275
Missing (%)6.9%
Memory size31.4 KiB
Minimum1988-10-25 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T15:26:06.994010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:26:07.194117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4007
Missing (%)100.0%
Memory size35.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4007
Missing (%)100.0%
Memory size35.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4007
Missing (%)100.0%
Memory size35.3 KiB

전화번호
Text

MISSING 

Distinct2406
Distinct (%)69.2%
Missing530
Missing (%)13.2%
Memory size31.4 KiB
2024-05-11T15:26:07.555648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.5332183
Min length2

Characters and Unicode

Total characters33147
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

Unique2171 ?
Unique (%)62.4%

Sample

1st row0204893489
2nd row02 4221963
3rd row02
4th row02
5th row02
ValueCountFrequency (%)
02 3201
48.7%
4079733 110
 
1.7%
0200000000 52
 
0.8%
5621191 46
 
0.7%
4101189 40
 
0.6%
5953691 31
 
0.5%
4293244 23
 
0.4%
0222247886 23
 
0.4%
5111762 22
 
0.3%
0234720333 18
 
0.3%
Other values (2453) 3001
45.7%
2024-05-11T15:26:08.115218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6461
19.5%
2 5821
17.6%
4 4502
13.6%
3267
9.9%
1 2798
8.4%
3 2144
 
6.5%
7 1840
 
5.6%
8 1644
 
5.0%
9 1579
 
4.8%
5 1570
 
4.7%
Other values (2) 1521
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29879
90.1%
Space Separator 3267
 
9.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6461
21.6%
2 5821
19.5%
4 4502
15.1%
1 2798
9.4%
3 2144
 
7.2%
7 1840
 
6.2%
8 1644
 
5.5%
9 1579
 
5.3%
5 1570
 
5.3%
6 1520
 
5.1%
Space Separator
ValueCountFrequency (%)
3267
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33147
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6461
19.5%
2 5821
17.6%
4 4502
13.6%
3267
9.9%
1 2798
8.4%
3 2144
 
6.5%
7 1840
 
5.6%
8 1644
 
5.0%
9 1579
 
4.8%
5 1570
 
4.7%
Other values (2) 1521
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6461
19.5%
2 5821
17.6%
4 4502
13.6%
3267
9.9%
1 2798
8.4%
3 2144
 
6.5%
7 1840
 
5.6%
8 1644
 
5.0%
9 1579
 
4.8%
5 1570
 
4.7%
Other values (2) 1521
 
4.6%

소재지면적
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)17.2%
Missing3582
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean6.3865176
Minimum0
Maximum92.38
Zeros24
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2024-05-11T15:26:08.648939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.3
median3.3
Q33.3
95-th percentile28.996
Maximum92.38
Range92.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.414692
Coefficient of variation (CV)1.630731
Kurtosis18.641617
Mean6.3865176
Median Absolute Deviation (MAD)0
Skewness3.8072153
Sum2714.27
Variance108.46581
MonotonicityNot monotonic
2024-05-11T15:26:08.924618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 229
 
5.7%
0.0 24
 
0.6%
1.0 23
 
0.6%
3.6 19
 
0.5%
2.0 18
 
0.4%
3.0 11
 
0.3%
6.6 11
 
0.3%
33.0 4
 
0.1%
26.0 3
 
0.1%
9.9 3
 
0.1%
Other values (63) 80
 
2.0%
(Missing) 3582
89.4%
ValueCountFrequency (%)
0.0 24
0.6%
0.1 1
 
< 0.1%
0.3 2
 
< 0.1%
0.39 1
 
< 0.1%
0.45 1
 
< 0.1%
0.5 2
 
< 0.1%
0.66 1
 
< 0.1%
0.9 1
 
< 0.1%
1.0 23
0.6%
1.03 1
 
< 0.1%
ValueCountFrequency (%)
92.38 1
< 0.1%
69.59 1
< 0.1%
65.7 1
< 0.1%
49.63 1
< 0.1%
49.5 1
< 0.1%
49.0 1
< 0.1%
45.0 1
< 0.1%
41.55 1
< 0.1%
36.0 1
< 0.1%
35.0 1
< 0.1%

소재지우편번호
Text

Distinct184
Distinct (%)4.6%
Missing4
Missing (%)0.1%
Memory size31.4 KiB
2024-05-11T15:26:09.465718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0269798
Min length6

Characters and Unicode

Total characters24126
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

Unique43 ?
Unique (%)1.1%

Sample

1st row138240
2nd row138908
3rd row138862
4th row138240
5th row138892
ValueCountFrequency (%)
138934 180
 
4.5%
138829 165
 
4.1%
138881 127
 
3.2%
138915 117
 
2.9%
138861 96
 
2.4%
138200 86
 
2.1%
138873 84
 
2.1%
138830 82
 
2.0%
138813 80
 
2.0%
138855 70
 
1.7%
Other values (174) 2916
72.8%
2024-05-11T15:26:10.275515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 7961
33.0%
1 5226
21.7%
3 4863
20.2%
2 1071
 
4.4%
0 1019
 
4.2%
4 949
 
3.9%
9 859
 
3.6%
5 846
 
3.5%
7 615
 
2.5%
6 609
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24018
99.6%
Dash Punctuation 108
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 7961
33.1%
1 5226
21.8%
3 4863
20.2%
2 1071
 
4.5%
0 1019
 
4.2%
4 949
 
4.0%
9 859
 
3.6%
5 846
 
3.5%
7 615
 
2.6%
6 609
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24126
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 7961
33.0%
1 5226
21.7%
3 4863
20.2%
2 1071
 
4.4%
0 1019
 
4.2%
4 949
 
3.9%
9 859
 
3.6%
5 846
 
3.5%
7 615
 
2.5%
6 609
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24126
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 7961
33.0%
1 5226
21.7%
3 4863
20.2%
2 1071
 
4.4%
0 1019
 
4.2%
4 949
 
3.9%
9 859
 
3.6%
5 846
 
3.5%
7 615
 
2.5%
6 609
 
2.5%

지번주소
Text

Distinct3131
Distinct (%)78.2%
Missing4
Missing (%)0.1%
Memory size31.4 KiB
2024-05-11T15:26:10.917891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length39
Mean length21.988509
Min length15

Characters and Unicode

Total characters88020
Distinct characters424
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2698 ?
Unique (%)67.4%

Sample

1st row서울특별시 송파구 신천동 35-2
2nd row서울특별시 송파구 잠실동 19-2 마을금고 구판장내
3rd row서울특별시 송파구 잠실동 192-6 청광빌딩내
4th row서울특별시 송파구 신천동 20-0 잠실시영상가 2101호앞
5th row서울특별시 송파구 잠실동 53-2 동보당약국내
ValueCountFrequency (%)
서울특별시 4003
22.4%
송파구 4003
22.4%
잠실동 655
 
3.7%
가락동 601
 
3.4%
방이동 511
 
2.9%
마천동 278
 
1.6%
송파동 257
 
1.4%
거여동 256
 
1.4%
오금동 252
 
1.4%
문정동 251
 
1.4%
Other values (2933) 6781
38.0%
2024-05-11T15:26:11.802991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17688
20.1%
파 4373
 
5.0%
송 4313
 
4.9%
동 4089
 
4.6%
서 4059
 
4.6%
시 4050
 
4.6%
구 4040
 
4.6%
울 4027
 
4.6%
별 4010
 
4.6%
특 4009
 
4.6%
Other values (414) 33362
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50929
57.9%
Space Separator 17688
 
20.1%
Decimal Number 15264
 
17.3%
Dash Punctuation 3510
 
4.0%
Open Punctuation 193
 
0.2%
Close Punctuation 190
 
0.2%
Uppercase Letter 172
 
0.2%
Other Punctuation 35
 
< 0.1%
Lowercase Letter 34
 
< 0.1%
Math Symbol 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 4373
 
8.6%
송 4313
 
8.5%
동 4089
 
8.0%
서 4059
 
8.0%
시 4050
 
8.0%
구 4040
 
7.9%
울 4027
 
7.9%
별 4010
 
7.9%
특 4009
 
7.9%
가 780
 
1.5%
Other values (366) 13179
25.9%
Uppercase Letter
ValueCountFrequency (%)
A 42
24.4%
B 38
22.1%
C 15
 
8.7%
D 13
 
7.6%
L 7
 
4.1%
S 7
 
4.1%
N 5
 
2.9%
T 5
 
2.9%
I 5
 
2.9%
G 5
 
2.9%
Other values (10) 30
17.4%
Decimal Number
ValueCountFrequency (%)
1 3510
23.0%
2 1918
12.6%
0 1898
12.4%
8 1320
 
8.6%
3 1288
 
8.4%
4 1245
 
8.2%
7 1064
 
7.0%
5 1034
 
6.8%
9 1023
 
6.7%
6 964
 
6.3%
Lowercase Letter
ValueCountFrequency (%)
c 14
41.2%
v 7
20.6%
k 4
 
11.8%
d 4
 
11.8%
h 3
 
8.8%
p 1
 
2.9%
t 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 18
51.4%
/ 13
37.1%
. 4
 
11.4%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
+ 1
33.3%
Space Separator
ValueCountFrequency (%)
17688
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3510
100.0%
Open Punctuation
ValueCountFrequency (%)
( 193
100.0%
Close Punctuation
ValueCountFrequency (%)
) 190
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50926
57.9%
Common 36884
41.9%
Latin 207
 
0.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 4373
 
8.6%
송 4313
 
8.5%
동 4089
 
8.0%
서 4059
 
8.0%
시 4050
 
8.0%
구 4040
 
7.9%
울 4027
 
7.9%
별 4010
 
7.9%
특 4009
 
7.9%
가 780
 
1.5%
Other values (364) 13176
25.9%
Latin
ValueCountFrequency (%)
A 42
20.3%
B 38
18.4%
C 15
 
7.2%
c 14
 
6.8%
D 13
 
6.3%
v 7
 
3.4%
L 7
 
3.4%
S 7
 
3.4%
N 5
 
2.4%
T 5
 
2.4%
Other values (18) 54
26.1%
Common
ValueCountFrequency (%)
17688
48.0%
1 3510
 
9.5%
- 3510
 
9.5%
2 1918
 
5.2%
0 1898
 
5.1%
8 1320
 
3.6%
3 1288
 
3.5%
4 1245
 
3.4%
7 1064
 
2.9%
5 1034
 
2.8%
Other values (10) 2409
 
6.5%
Han
ValueCountFrequency (%)
下 2
66.7%
上 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50926
57.9%
ASCII 37090
42.1%
CJK 3
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17688
47.7%
1 3510
 
9.5%
- 3510
 
9.5%
2 1918
 
5.2%
0 1898
 
5.1%
8 1320
 
3.6%
3 1288
 
3.5%
4 1245
 
3.4%
7 1064
 
2.9%
5 1034
 
2.8%
Other values (37) 2615
 
7.1%
Hangul
ValueCountFrequency (%)
파 4373
 
8.6%
송 4313
 
8.5%
동 4089
 
8.0%
서 4059
 
8.0%
시 4050
 
8.0%
구 4040
 
7.9%
울 4027
 
7.9%
별 4010
 
7.9%
특 4009
 
7.9%
가 780
 
1.5%
Other values (364) 13176
25.9%
CJK
ValueCountFrequency (%)
下 2
66.7%
上 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명주소
Text

MISSING 

Distinct595
Distinct (%)97.1%
Missing3394
Missing (%)84.7%
Memory size31.4 KiB
2024-05-11T15:26:12.377343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length50
Mean length33.649266
Min length21

Characters and Unicode

Total characters20627
Distinct characters317
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique580 ?
Unique (%)94.6%

Sample

1st row서울특별시 송파구 석촌호수로 242 (석촌동)
2nd row서울특별시 송파구 올림픽로 99 (잠실동,고수부지)
3rd row서울특별시 송파구 양재대로 1218 (방이동,선수기자촌아파트 F상가 105호)
4th row서울특별시 송파구 성내천로 260 (마천동)
5th row서울특별시 송파구 바람드리길 28-1 (풍납동)
ValueCountFrequency (%)
서울특별시 613
 
15.0%
송파구 613
 
15.0%
1층 199
 
4.9%
문정동 85
 
2.1%
잠실동 69
 
1.7%
지상1층 64
 
1.6%
가락동 56
 
1.4%
마천동 55
 
1.3%
방이동 54
 
1.3%
송파대로 51
 
1.2%
Other values (860) 2234
54.6%
2024-05-11T15:26:13.198624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3485
 
16.9%
1 947
 
4.6%
파 789
 
3.8%
송 774
 
3.8%
동 701
 
3.4%
시 630
 
3.1%
) 627
 
3.0%
( 627
 
3.0%
, 626
 
3.0%
서 625
 
3.0%
Other values (307) 10796
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12221
59.2%
Space Separator 3485
 
16.9%
Decimal Number 2904
 
14.1%
Other Punctuation 628
 
3.0%
Close Punctuation 627
 
3.0%
Open Punctuation 627
 
3.0%
Uppercase Letter 80
 
0.4%
Dash Punctuation 52
 
0.3%
Letter Number 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 789
 
6.5%
송 774
 
6.3%
동 701
 
5.7%
시 630
 
5.2%
서 625
 
5.1%
울 619
 
5.1%
로 616
 
5.0%
구 616
 
5.0%
별 614
 
5.0%
특 613
 
5.0%
Other values (270) 5624
46.0%
Uppercase Letter
ValueCountFrequency (%)
B 12
15.0%
C 12
15.0%
A 10
12.5%
G 8
10.0%
S 7
8.8%
U 6
7.5%
E 5
 
6.2%
F 3
 
3.8%
R 2
 
2.5%
T 2
 
2.5%
Other values (8) 13
16.2%
Decimal Number
ValueCountFrequency (%)
1 947
32.6%
2 426
14.7%
3 299
 
10.3%
4 264
 
9.1%
0 238
 
8.2%
5 223
 
7.7%
6 173
 
6.0%
7 122
 
4.2%
8 116
 
4.0%
9 96
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 626
99.7%
' 2
 
0.3%
Space Separator
ValueCountFrequency (%)
3485
100.0%
Close Punctuation
ValueCountFrequency (%)
) 627
100.0%
Open Punctuation
ValueCountFrequency (%)
( 627
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12220
59.2%
Common 8324
40.4%
Latin 82
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 789
 
6.5%
송 774
 
6.3%
동 701
 
5.7%
시 630
 
5.2%
서 625
 
5.1%
울 619
 
5.1%
로 616
 
5.0%
구 616
 
5.0%
별 614
 
5.0%
특 613
 
5.0%
Other values (269) 5623
46.0%
Latin
ValueCountFrequency (%)
B 12
14.6%
C 12
14.6%
A 10
12.2%
G 8
9.8%
S 7
8.5%
U 6
 
7.3%
E 5
 
6.1%
F 3
 
3.7%
R 2
 
2.4%
T 2
 
2.4%
Other values (10) 15
18.3%
Common
ValueCountFrequency (%)
3485
41.9%
1 947
 
11.4%
) 627
 
7.5%
( 627
 
7.5%
, 626
 
7.5%
2 426
 
5.1%
3 299
 
3.6%
4 264
 
3.2%
0 238
 
2.9%
5 223
 
2.7%
Other values (7) 562
 
6.8%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12220
59.2%
ASCII 8405
40.7%
Number Forms 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3485
41.5%
1 947
 
11.3%
) 627
 
7.5%
( 627
 
7.5%
, 626
 
7.4%
2 426
 
5.1%
3 299
 
3.6%
4 264
 
3.1%
0 238
 
2.8%
5 223
 
2.7%
Other values (26) 643
 
7.7%
Hangul
ValueCountFrequency (%)
파 789
 
6.5%
송 774
 
6.3%
동 701
 
5.7%
시 630
 
5.2%
서 625
 
5.1%
울 619
 
5.1%
로 616
 
5.0%
구 616
 
5.0%
별 614
 
5.0%
특 613
 
5.0%
Other values (269) 5623
46.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%
CJK
ValueCountFrequency (%)
內 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct255
Distinct (%)42.4%
Missing3406
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean5680.4359
Minimum5500
Maximum5857
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2024-05-11T15:26:13.487159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5500
5-th percentile5507
Q15573
median5691
Q35774
95-th percentile5844
Maximum5857
Range357
Interquartile range (IQR)201

Descriptive statistics

Standard deviation111.62193
Coefficient of variation (CV)0.019650241
Kurtosis-1.3209764
Mean5680.4359
Median Absolute Deviation (MAD)98
Skewness-0.084439099
Sum3413942
Variance12459.456
MonotonicityNot monotonic
2024-05-11T15:26:13.787667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5510 19
 
0.5%
5768 9
 
0.2%
5554 9
 
0.2%
5854 8
 
0.2%
5837 8
 
0.2%
5699 8
 
0.2%
5758 8
 
0.2%
5503 7
 
0.2%
5504 7
 
0.2%
5841 7
 
0.2%
Other values (245) 511
 
12.8%
(Missing) 3406
85.0%
ValueCountFrequency (%)
5500 6
0.1%
5501 2
 
< 0.1%
5502 1
 
< 0.1%
5503 7
0.2%
5504 7
0.2%
5505 4
0.1%
5506 2
 
< 0.1%
5507 2
 
< 0.1%
5508 3
0.1%
5509 1
 
< 0.1%
ValueCountFrequency (%)
5857 1
 
< 0.1%
5856 1
 
< 0.1%
5855 6
0.1%
5854 8
0.2%
5853 2
 
< 0.1%
5852 5
0.1%
5849 4
0.1%
5848 1
 
< 0.1%
5847 1
 
< 0.1%
5846 1
 
< 0.1%

사업장명
Text

Distinct2842
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
2024-05-11T15:26:14.342696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length6.1115548
Min length1

Characters and Unicode

Total characters24489
Distinct characters706
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

Unique2518 ?
Unique (%)62.8%

Sample

1st row라이크종합상가라이크슈퍼체인본부
2nd row커피자동판매
3rd row커피자동판매
4th row커피자동판매
5th row커피자동판매
ValueCountFrequency (%)
192
 
4.3%
주)선호유통 114
 
2.5%
한국체육산업개발(주 56
 
1.2%
씨유 51
 
1.1%
gs25 36
 
0.8%
cu 36
 
0.8%
이마트24 25
 
0.6%
금강벤딩 23
 
0.5%
주)보광 23
 
0.5%
커피자동판매 22
 
0.5%
Other values (2941) 3905
87.1%
2024-05-11T15:26:15.167499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 566
 
2.3%
( 566
 
2.3%
주 534
 
2.2%
485
 
2.0%
점 429
 
1.8%
동 354
 
1.4%
실 313
 
1.3%
퍼 309
 
1.3%
이 304
 
1.2%
유 283
 
1.2%
Other values (696) 20346
83.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21496
87.8%
Decimal Number 598
 
2.4%
Close Punctuation 566
 
2.3%
Open Punctuation 566
 
2.3%
Space Separator 485
 
2.0%
Uppercase Letter 460
 
1.9%
Dash Punctuation 214
 
0.9%
Lowercase Letter 70
 
0.3%
Other Punctuation 32
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 534
 
2.5%
점 429
 
2.0%
동 354
 
1.6%
실 313
 
1.5%
퍼 309
 
1.4%
이 304
 
1.4%
유 283
 
1.3%
스 276
 
1.3%
슈 269
 
1.3%
호 261
 
1.2%
Other values (636) 18164
84.5%
Uppercase Letter
ValueCountFrequency (%)
C 101
22.0%
S 64
13.9%
G 59
12.8%
U 57
12.4%
P 38
 
8.3%
B 16
 
3.5%
A 15
 
3.3%
L 15
 
3.3%
O 14
 
3.0%
E 13
 
2.8%
Other values (13) 68
14.8%
Lowercase Letter
ValueCountFrequency (%)
e 9
12.9%
a 8
11.4%
c 8
11.4%
m 6
8.6%
r 6
8.6%
o 5
7.1%
u 5
7.1%
f 5
7.1%
t 4
 
5.7%
w 3
 
4.3%
Other values (6) 11
15.7%
Decimal Number
ValueCountFrequency (%)
2 212
35.5%
5 99
16.6%
1 82
 
13.7%
4 71
 
11.9%
8 42
 
7.0%
3 35
 
5.9%
0 32
 
5.4%
6 14
 
2.3%
9 6
 
1.0%
7 5
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 23
71.9%
& 3
 
9.4%
! 2
 
6.2%
, 2
 
6.2%
? 1
 
3.1%
/ 1
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 566
100.0%
Open Punctuation
ValueCountFrequency (%)
( 566
100.0%
Space Separator
ValueCountFrequency (%)
485
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 214
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21494
87.8%
Common 2463
 
10.1%
Latin 530
 
2.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 534
 
2.5%
점 429
 
2.0%
동 354
 
1.6%
실 313
 
1.5%
퍼 309
 
1.4%
이 304
 
1.4%
유 283
 
1.3%
스 276
 
1.3%
슈 269
 
1.3%
호 261
 
1.2%
Other values (635) 18162
84.5%
Latin
ValueCountFrequency (%)
C 101
19.1%
S 64
12.1%
G 59
11.1%
U 57
10.8%
P 38
 
7.2%
B 16
 
3.0%
A 15
 
2.8%
L 15
 
2.8%
O 14
 
2.6%
E 13
 
2.5%
Other values (29) 138
26.0%
Common
ValueCountFrequency (%)
) 566
23.0%
( 566
23.0%
485
19.7%
- 214
 
8.7%
2 212
 
8.6%
5 99
 
4.0%
1 82
 
3.3%
4 71
 
2.9%
8 42
 
1.7%
3 35
 
1.4%
Other values (11) 91
 
3.7%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21494
87.8%
ASCII 2993
 
12.2%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 566
18.9%
( 566
18.9%
485
16.2%
- 214
 
7.2%
2 212
 
7.1%
C 101
 
3.4%
5 99
 
3.3%
1 82
 
2.7%
4 71
 
2.4%
S 64
 
2.1%
Other values (50) 533
17.8%
Hangul
ValueCountFrequency (%)
주 534
 
2.5%
점 429
 
2.0%
동 354
 
1.6%
실 313
 
1.5%
퍼 309
 
1.4%
이 304
 
1.4%
유 283
 
1.3%
스 276
 
1.3%
슈 269
 
1.3%
호 261
 
1.2%
Other values (635) 18162
84.5%
CJK
ValueCountFrequency (%)
內 2
100.0%

최종수정일자
Date

Distinct999
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
Minimum1999-10-21 00:00:00
Maximum2024-05-02 12:07:47
2024-05-11T15:26:15.464695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:26:15.813819image/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 size31.4 KiB
I
3784 
U
 
223

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 3784
94.4%
U 223
 
5.6%

Length

2024-05-11T15:26:16.087588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:16.372499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3784
94.4%
u 223
 
5.6%

데이터갱신일자
Date

Distinct272
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T15:26:16.568129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:26:16.883514image/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 size31.4 KiB
식품자동판매기영업
4007 

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 4007
100.0%

Length

2024-05-11T15:26:17.179500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:17.367345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 4007
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2143
Distinct (%)56.9%
Missing242
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean210116.85
Minimum206159.6
Maximum213999.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2024-05-11T15:26:17.609280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206159.6
5-th percentile207125.18
Q1208845.61
median210134.83
Q3211190.25
95-th percentile213184.13
Maximum213999.96
Range7840.356
Interquartile range (IQR)2344.6449

Descriptive statistics

Standard deviation1760.8558
Coefficient of variation (CV)0.0083803647
Kurtosis-0.54512629
Mean210116.85
Median Absolute Deviation (MAD)1132.9884
Skewness0.032930886
Sum7.9108994 × 108
Variance3100613.3
MonotonicityNot monotonic
2024-05-11T15:26:17.901994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209790.959909032 128
 
3.2%
208589.363343145 114
 
2.8%
210199.45921923 86
 
2.1%
209607.590372037 50
 
1.2%
208317.419891103 34
 
0.8%
208233.926974585 28
 
0.7%
208808.460094719 27
 
0.7%
206383.829438022 24
 
0.6%
210849.897330572 24
 
0.6%
209394.231297346 22
 
0.5%
Other values (2133) 3228
80.6%
(Missing) 242
 
6.0%
ValueCountFrequency (%)
206159.600830281 1
 
< 0.1%
206168.53987807 2
 
< 0.1%
206168.604353473 7
 
0.2%
206322.970067697 1
 
< 0.1%
206333.883560842 1
 
< 0.1%
206383.829438022 24
0.6%
206397.34797252 6
 
0.1%
206425.501600423 1
 
< 0.1%
206487.800145227 3
 
0.1%
206498.438841963 2
 
< 0.1%
ValueCountFrequency (%)
213999.956783491 1
 
< 0.1%
213890.713658141 3
0.1%
213873.675372176 1
 
< 0.1%
213860.362849957 2
< 0.1%
213850.50213338 1
 
< 0.1%
213843.762365507 1
 
< 0.1%
213836.818937676 2
< 0.1%
213831.328595107 2
< 0.1%
213822.102456233 1
 
< 0.1%
213818.199465569 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2142
Distinct (%)56.9%
Missing242
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean444783.68
Minimum440933.58
Maximum448610.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.3 KiB
2024-05-11T15:26:18.360031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440933.58
5-th percentile442920.28
Q1443859.92
median444767.32
Q3445473.86
95-th percentile447120.58
Maximum448610.57
Range7676.9861
Interquartile range (IQR)1613.9485

Descriptive statistics

Standard deviation1267.244
Coefficient of variation (CV)0.0028491244
Kurtosis0.40864105
Mean444783.68
Median Absolute Deviation (MAD)826.36063
Skewness0.38285176
Sum1.6746105 × 109
Variance1605907.5
MonotonicityNot monotonic
2024-05-11T15:26:18.688974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443481.212174317 128
 
3.2%
445455.90405262 114
 
2.8%
446539.279382444 86
 
2.1%
447120.577229325 50
 
1.2%
445894.98085039 34
 
0.8%
445435.257647797 28
 
0.7%
446014.471916419 27
 
0.7%
443789.337035202 24
 
0.6%
446030.128073052 24
 
0.6%
443951.236927017 22
 
0.5%
Other values (2132) 3228
80.6%
(Missing) 242
 
6.0%
ValueCountFrequency (%)
440933.57908406 2
< 0.1%
440949.654290777 4
0.1%
440999.735530566 1
 
< 0.1%
441112.927797859 1
 
< 0.1%
441412.0 1
 
< 0.1%
441426.0 2
< 0.1%
441474.303929299 1
 
< 0.1%
441586.029967716 1
 
< 0.1%
441632.0 1
 
< 0.1%
441717.665434824 1
 
< 0.1%
ValueCountFrequency (%)
448610.565204041 1
< 0.1%
448601.324644324 1
< 0.1%
448561.211769962 1
< 0.1%
448499.494831757 1
< 0.1%
448472.581253344 2
< 0.1%
448453.051938704 1
< 0.1%
448440.895172526 2
< 0.1%
448437.083161462 1
< 0.1%
448435.73123223 1
< 0.1%
448432.156952522 2
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
식품자동판매기영업
3852 
<NA>
 
155

Length

Max length9
Median length9
Mean length8.8065885
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 3852
96.1%
<NA> 155
 
3.9%

Length

2024-05-11T15:26:18.960455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:19.181104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 3852
96.1%
na 155
 
3.9%

남성종사자수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
0
2622 
<NA>
1309 
1
 
76

Length

Max length4
Median length1
Mean length1.9800349
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 2622
65.4%
<NA> 1309
32.7%
1 76
 
1.9%

Length

2024-05-11T15:26:19.436969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:19.697399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2622
65.4%
na 1309
32.7%
1 76
 
1.9%

여성종사자수
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
0
2632 
<NA>
1309 
1
 
63
2
 
3

Length

Max length4
Median length1
Mean length1.9800349
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 2632
65.7%
<NA> 1309
32.7%
1 63
 
1.6%
2 3
 
0.1%

Length

2024-05-11T15:26:19.951052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:20.195810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2632
65.7%
na 1309
32.7%
1 63
 
1.6%
2 3
 
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
기타
2731 
<NA>
1043 
주택가주변
 
225
아파트지역
 
5
결혼예식장주변
 
2

Length

Max length8
Median length2
Mean length2.6967806
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 2731
68.2%
<NA> 1043
 
26.0%
주택가주변 225
 
5.6%
아파트지역 5
 
0.1%
결혼예식장주변 2
 
< 0.1%
학교정화(상대) 1
 
< 0.1%

Length

2024-05-11T15:26:20.452455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:20.657466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 2731
68.2%
na 1043
 
26.0%
주택가주변 225
 
5.6%
아파트지역 5
 
0.1%
결혼예식장주변 2
 
< 0.1%
학교정화(상대 1
 
< 0.1%

등급구분명
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
기타
2567 
<NA>
1043 
우수
 
205
지도
 
178
을
 
13

Length

Max length4
Median length2
Mean length2.5173446
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 2567
64.1%
<NA> 1043
26.0%
우수 205
 
5.1%
지도 178
 
4.4%
을 13
 
0.3%
자율 1
 
< 0.1%

Length

2024-05-11T15:26:21.001112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:21.270219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 2567
64.1%
na 1043
26.0%
우수 205
 
5.1%
지도 178
 
4.4%
을 13
 
0.3%
자율 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
<NA>
3997 
상수도전용
 
10

Length

Max length5
Median length4
Mean length4.0024956
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> 3997
99.8%
상수도전용 10
 
0.2%

Length

2024-05-11T15:26:21.604203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:21.840202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3997
99.8%
상수도전용 10
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
<NA>
3983 
0
 
24

Length

Max length4
Median length4
Mean length3.9820314
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> 3983
99.4%
0 24
 
0.6%

Length

2024-05-11T15:26:22.063131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:22.283337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3983
99.4%
0 24
 
0.6%

본사종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
<NA>
3468 
0
538 
1
 
1

Length

Max length4
Median length4
Mean length3.5964562
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3468
86.5%
0 538
 
13.4%
1 1
 
< 0.1%

Length

2024-05-11T15:26:22.570690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:22.944046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3468
86.5%
0 538
 
13.4%
1 1
 
< 0.1%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
<NA>
3468 
0
539 

Length

Max length4
Median length4
Mean length3.5964562
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3468
86.5%
0 539
 
13.5%

Length

2024-05-11T15:26:23.204977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:23.480554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3468
86.5%
0 539
 
13.5%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
<NA>
3468 
0
539 

Length

Max length4
Median length4
Mean length3.5964562
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3468
86.5%
0 539
 
13.5%

Length

2024-05-11T15:26:23.757854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:24.599391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3468
86.5%
0 539
 
13.5%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
<NA>
3468 
0
539 

Length

Max length4
Median length4
Mean length3.5964562
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3468
86.5%
0 539
 
13.5%

Length

2024-05-11T15:26:24.808290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:25.056820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3468
86.5%
0 539
 
13.5%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
<NA>
3453 
자가
487 
임대
 
67

Length

Max length4
Median length4
Mean length3.7234839
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> 3453
86.2%
자가 487
 
12.2%
임대 67
 
1.7%

Length

2024-05-11T15:26:25.311832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:25.576154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3453
86.2%
자가 487
 
12.2%
임대 67
 
1.7%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
<NA>
3724 
0
 
283

Length

Max length4
Median length4
Mean length3.7881208
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> 3724
92.9%
0 283
 
7.1%

Length

2024-05-11T15:26:25.821691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:26.019841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3724
92.9%
0 283
 
7.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
<NA>
3724 
0
 
283

Length

Max length4
Median length4
Mean length3.7881208
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> 3724
92.9%
0 283
 
7.1%

Length

2024-05-11T15:26:26.268872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:26.490210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3724
92.9%
0 283
 
7.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing155
Missing (%)3.9%
Memory size8.0 KiB
False
3852 
(Missing)
 
155
ValueCountFrequency (%)
False 3852
96.1%
(Missing) 155
 
3.9%
2024-05-11T15:26:26.692179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.4 KiB
0.0
3850 
<NA>
 
155
3.3
 
2

Length

Max length4
Median length3
Mean length3.0386823
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 3850
96.1%
<NA> 155
 
3.9%
3.3 2
 
< 0.1%

Length

2024-05-11T15:26:26.903453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:26:27.145347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 3850
96.1%
na 155
 
3.9%
3.3 2
 
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4007
Missing (%)100.0%
Memory size35.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4007
Missing (%)100.0%
Memory size35.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4007
Missing (%)100.0%
Memory size35.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032300003230000-112-1904-0100419810926<NA>3폐업2폐업19931119<NA><NA><NA>0204893489<NA>138240서울특별시 송파구 신천동 35-2<NA><NA>라이크종합상가라이크슈퍼체인본부2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업11기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132300003230000-112-1981-0099719810901<NA>3폐업2폐업20050526<NA><NA><NA>02 4221963<NA>138908서울특별시 송파구 잠실동 19-2 마을금고 구판장내<NA><NA>커피자동판매2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업207223.885155445801.200824식품자동판매기영업00기타지도<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
232300003230000-112-1981-0099819810901<NA>3폐업2폐업19960903<NA><NA><NA>02<NA>138862서울특별시 송파구 잠실동 192-6 청광빌딩내<NA><NA>커피자동판매2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업207111.262447445269.308915식품자동판매기영업10기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332300003230000-112-1981-0099919810904<NA>3폐업2폐업20051228<NA><NA><NA>02<NA>138240서울특별시 송파구 신천동 20-0 잠실시영상가 2101호앞<NA><NA>커피자동판매2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업209744.789378446601.107402식품자동판매기영업11기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
432300003230000-112-1981-0100019810905<NA>3폐업2폐업20101231<NA><NA><NA>02<NA>138892서울특별시 송파구 잠실동 53-2 동보당약국내<NA><NA>커피자동판매2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업11기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532300003230000-112-1981-0100119810926<NA>3폐업2폐업19931119<NA><NA><NA>02<NA>138240서울특별시 송파구 신천동 17-6<NA><NA>라이프슈퍼체인미성점2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업209393.076055446147.977949식품자동판매기영업11기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
632300003230000-112-1981-0100219810926<NA>3폐업2폐업19931119<NA><NA><NA>02<NA>138240서울특별시 송파구 신천동 7 , 8<NA><NA>라이프종합상가라이프슈퍼체인본부2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업208707.089898446299.352775식품자동판매기영업11기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
732300003230000-112-1981-0100319810926<NA>3폐업2폐업19931119<NA><NA><NA>02<NA>138240서울특별시 송파구 신천동 235-2 (신)7-8<NA><NA>라이프종합상가라이프슈퍼체인본부2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업11기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832300003230000-112-1983-0100519830316<NA>3폐업2폐업19990401<NA><NA><NA>02<NA>138836서울특별시 송파구 방이동 226-12 영동교통<NA><NA>커피자동판매기2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업210566.466492444941.292158식품자동판매기영업10기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
932300003230000-112-1983-0100619830322<NA>3폐업2폐업19930619<NA><NA><NA>02<NA>138883서울특별시 송파구 가락동 486-0 가락아파트 가상가 1층입구<NA><NA>커피자동판매기2003-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업02기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
399732300003230000-112-2024-000082024-03-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>41.55138-110서울특별시 송파구 거여동 648 위례포레샤인 18단지서울특별시 송파구 위례북로4길 12, 상가동 1층 104호 (거여동, 위례포레샤인 18단지)5776데이롱 카페 위례포레샤인점2024-03-07 15:04:29I2023-12-03 00:09:00.0식품자동판매기영업213378.690585442856.938828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
399832300003230000-112-2024-000092024-03-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3138-817서울특별시 송파구 마천동 17서울특별시 송파구 마천로31길 14, 1층 (마천동)5733지에스25마천빌리지점2024-03-15 13:20:01I2023-12-02 23:07:00.0식품자동판매기영업212601.045351444396.855247<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
399932300003230000-112-2024-000102024-03-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.0138-830서울특별시 송파구 방이동 136-5서울특별시 송파구 가락로 245, 1층 102호 (방이동)5633더리터24송파방이점2024-03-19 17:06:27I2023-12-02 22:01:00.0식품자동판매기영업210361.923057445336.331493<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
400032300003230000-112-2024-000112024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA>02 407 77583.3138-889서울특별시 송파구 잠실동 1-1 한강공원잠실안내센터서울특별시 송파구 한가람로 65, 한강공원잠실안내센터 1층 (잠실동)5502한강 르네상스 잠실 2호점2024-03-21 14:52:21I2023-12-02 22:03:00.0식품자동판매기영업207280.548176446256.122691<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
400132300003230000-112-2024-000122024-03-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>49.5138-834서울특별시 송파구 방이동 193-17 광진빌딩서울특별시 송파구 양재대로71길 30-1, 광진빌딩 1층 103호 (방이동)5637라커룸 송파2024-03-28 18:02:05I2023-12-02 21:00:00.0식품자동판매기영업210863.691124445473.005139<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
400232300003230000-112-2024-000132024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.0138-815서울특별시 송파구 거여동 567서울특별시 송파구 양산로 38, 1층 101호 (거여동)5773공감 공간 2호점2024-04-02 17:26:09I2023-12-04 00:04:00.0식품자동판매기영업212693.153007443344.439077<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
400332300003230000-112-2024-000142024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.0138-809서울특별시 송파구 가락동 154-19서울특별시 송파구 오금로40길 44, 1층 103호 (가락동)5822엘로우스트릿(YELLOW STREET)2024-04-03 15:39:08I2023-12-04 00:05:00.0식품자동판매기영업211291.125711443894.210382<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
400432300003230000-112-2024-000152024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.0138-888서울특별시 송파구 문정동 652-3 르피에드서울특별시 송파구 송파대로 141, 르피에드 지하1층 104호 (문정동)5855바바스 커피2024-04-19 17:39:01I2023-12-03 22:01:00.0식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
400532300003230000-112-2024-000162024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3138-888서울특별시 송파구 문정동 639-5 힐스테이트에코송파서울특별시 송파구 정의로7길 13, 힐스테이트에코송파 1층 104,105호 (문정동)5835GS25 문정에코점2024-05-01 10:00:47I2023-12-05 00:03:00.0식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
400632300003230000-112-2024-000172024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.4138-820서울특별시 송파구 마천동 180-15서울특별시 송파구 마천로61다길 30, 1층 (마천동)5758커피, 한잔2024-05-02 12:07:47I2023-12-05 00:04:00.0식품자동판매기영업213319.329539443726.289789<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>