Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells101498
Missing cells (%)23.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory384.0 B

Variable types

Numeric6
Text6
DateTime4
Unsupported7
Categorical20
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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16077/S/1/datasetView.do

Alerts

업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (53.0%)Imbalance
위생업태명 is highly imbalanced (62.6%)Imbalance
영업장주변구분명 is highly imbalanced (50.5%)Imbalance
등급구분명 is highly imbalanced (58.2%)Imbalance
급수시설구분명 is highly imbalanced (67.6%)Imbalance
건물소유구분명 is highly imbalanced (50.6%)Imbalance
보증액 is highly imbalanced (58.3%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1143 (11.4%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 1889 (18.9%) missing valuesMissing
소재지면적 has 8773 (87.7%) missing valuesMissing
도로명주소 has 7435 (74.4%) missing valuesMissing
도로명우편번호 has 7508 (75.1%) missing valuesMissing
좌표정보(X) has 1641 (16.4%) missing valuesMissing
좌표정보(Y) has 1641 (16.4%) missing valuesMissing
다중이용업소여부 has 723 (7.2%) missing valuesMissing
시설총규모 has 723 (7.2%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 32.01180832)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 399 (4.0%) zerosZeros
시설총규모 has 9103 (91.0%) zerosZeros

Reproduction

Analysis started2024-04-29 18:51:13.437674
Analysis finished2024-04-29 18:51:15.542667
Duration2.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3047986
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T03:51:15.612481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3000000
Q13010000
median3050000
Q33070000
95-th percentile3100000
Maximum3240000
Range240000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation41609.097
Coefficient of variation (CV)0.013651341
Kurtosis4.4210438
Mean3047986
Median Absolute Deviation (MAD)30000
Skewness1.6498919
Sum3.047986 × 1010
Variance1.7313169 × 109
MonotonicityNot monotonic
2024-04-30T03:51:15.717840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3010000 1608
16.1%
3000000 1100
11.0%
3050000 1063
10.6%
3060000 1052
10.5%
3070000 899
9.0%
3040000 780
7.8%
3020000 772
7.7%
3080000 757
7.6%
3030000 708
7.1%
3090000 703
7.0%
Other values (15) 558
 
5.6%
ValueCountFrequency (%)
3000000 1100
11.0%
3010000 1608
16.1%
3020000 772
7.7%
3030000 708
7.1%
3040000 780
7.8%
3050000 1063
10.6%
3060000 1052
10.5%
3070000 899
9.0%
3080000 757
7.6%
3090000 703
7.0%
ValueCountFrequency (%)
3240000 31
0.3%
3230000 40
0.4%
3220000 35
0.4%
3210000 31
0.3%
3200000 44
0.4%
3190000 29
0.3%
3180000 45
0.4%
3170000 35
0.4%
3160000 33
0.3%
3150000 36
0.4%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T03:51:16.021535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3060000-112-2001-01127
2nd row3050000-112-2002-00074
3rd row3060000-112-1999-00793
4th row3000000-112-1998-01246
5th row3040000-112-2004-00055
ValueCountFrequency (%)
3060000-112-2001-01127 1
 
< 0.1%
3010000-112-1992-02354 1
 
< 0.1%
3060000-112-2001-01025 1
 
< 0.1%
3020000-112-1992-00665 1
 
< 0.1%
3030000-112-1981-00005 1
 
< 0.1%
3010000-112-2003-00007 1
 
< 0.1%
3010000-112-1992-02198 1
 
< 0.1%
3010000-112-1989-01624 1
 
< 0.1%
3010000-112-1985-01082 1
 
< 0.1%
3040000-112-1998-00107 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-30T03:51:16.317672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 83250
37.8%
1 35575
16.2%
- 30000
 
13.6%
2 21244
 
9.7%
3 14814
 
6.7%
9 14563
 
6.6%
8 4602
 
2.1%
5 4189
 
1.9%
6 4076
 
1.9%
4 3973
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 83250
43.8%
1 35575
18.7%
2 21244
 
11.2%
3 14814
 
7.8%
9 14563
 
7.7%
8 4602
 
2.4%
5 4189
 
2.2%
6 4076
 
2.1%
4 3973
 
2.1%
7 3714
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 83250
37.8%
1 35575
16.2%
- 30000
 
13.6%
2 21244
 
9.7%
3 14814
 
6.7%
9 14563
 
6.6%
8 4602
 
2.1%
5 4189
 
1.9%
6 4076
 
1.9%
4 3973
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 83250
37.8%
1 35575
16.2%
- 30000
 
13.6%
2 21244
 
9.7%
3 14814
 
6.7%
9 14563
 
6.6%
8 4602
 
2.1%
5 4189
 
1.9%
6 4076
 
1.9%
4 3973
 
1.8%
Distinct4179
Distinct (%)41.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1962-08-26 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T03:51:16.450414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:51:16.590694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
8857 
1
1143 

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 8857
88.6%
1 1143
 
11.4%

Length

2024-04-30T03:51:16.697470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:16.780155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8857
88.6%
1 1143
 
11.4%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8857 
영업/정상
1143 

Length

Max length5
Median length2
Mean length2.3429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8857
88.6%
영업/정상 1143
 
11.4%

Length

2024-04-30T03:51:16.867316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:16.956186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8857
88.6%
영업/정상 1143
 
11.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8857 
1
1143 

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 8857
88.6%
1 1143
 
11.4%

Length

2024-04-30T03:51:17.052517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:17.128318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8857
88.6%
1 1143
 
11.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8857 
영업
1143 

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 8857
88.6%
영업 1143
 
11.4%

Length

2024-04-30T03:51:17.217527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:17.293339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8857
88.6%
영업 1143
 
11.4%

폐업일자
Date

MISSING 

Distinct3949
Distinct (%)44.6%
Missing1143
Missing (%)11.4%
Memory size156.2 KiB
Minimum1986-03-17 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T03:51:17.390346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:51:17.510678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct4546
Distinct (%)56.0%
Missing1889
Missing (%)18.9%
Memory size156.2 KiB
2024-04-30T03:51:17.751374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length8.1947972
Min length2

Characters and Unicode

Total characters66468
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

Unique4326 ?
Unique (%)53.3%

Sample

1st row0234232481
2nd row02 22150901
3rd row02 4353536
4th row0200000000
5th row02 4569471
ValueCountFrequency (%)
02 5663
46.3%
0200000000 920
 
7.5%
00000 173
 
1.4%
5111762 63
 
0.5%
0 51
 
0.4%
5293326 22
 
0.2%
4166416 22
 
0.2%
0232728988 19
 
0.2%
100 18
 
0.1%
070 15
 
0.1%
Other values (4694) 5253
43.0%
2024-04-30T03:51:18.060758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19697
29.6%
2 12912
19.4%
9 4936
 
7.4%
4926
 
7.4%
4 4201
 
6.3%
1 3631
 
5.5%
3 3532
 
5.3%
7 3434
 
5.2%
6 3327
 
5.0%
5 3070
 
4.6%
Other values (2) 2802
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61538
92.6%
Space Separator 4926
 
7.4%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19697
32.0%
2 12912
21.0%
9 4936
 
8.0%
4 4201
 
6.8%
1 3631
 
5.9%
3 3532
 
5.7%
7 3434
 
5.6%
6 3327
 
5.4%
5 3070
 
5.0%
8 2798
 
4.5%
Space Separator
ValueCountFrequency (%)
4926
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66468
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19697
29.6%
2 12912
19.4%
9 4936
 
7.4%
4926
 
7.4%
4 4201
 
6.3%
1 3631
 
5.5%
3 3532
 
5.3%
7 3434
 
5.2%
6 3327
 
5.0%
5 3070
 
4.6%
Other values (2) 2802
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19697
29.6%
2 12912
19.4%
9 4936
 
7.4%
4926
 
7.4%
4 4201
 
6.3%
1 3631
 
5.5%
3 3532
 
5.3%
7 3434
 
5.2%
6 3327
 
5.0%
5 3070
 
4.6%
Other values (2) 2802
 
4.2%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct157
Distinct (%)12.8%
Missing8773
Missing (%)87.7%
Infinite0
Infinite (%)0.0%
Mean5.4863814
Minimum0
Maximum76
Zeros399
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T03:51:18.174837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.3
Q33.3
95-th percentile27.917
Maximum76
Range76
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation10.179014
Coefficient of variation (CV)1.8553238
Kurtosis12.839453
Mean5.4863814
Median Absolute Deviation (MAD)2.8
Skewness3.3000919
Sum6731.79
Variance103.61232
MonotonicityNot monotonic
2024-04-30T03:51:18.291581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 399
 
4.0%
3.3 373
 
3.7%
3.0 65
 
0.7%
1.0 49
 
0.5%
6.6 25
 
0.2%
3.6 22
 
0.2%
2.0 19
 
0.2%
1.5 14
 
0.1%
5.0 11
 
0.1%
2.4 10
 
0.1%
Other values (147) 240
 
2.4%
(Missing) 8773
87.7%
ValueCountFrequency (%)
0.0 399
4.0%
0.3 2
 
< 0.1%
0.36 1
 
< 0.1%
0.5 3
 
< 0.1%
0.8 3
 
< 0.1%
1.0 49
 
0.5%
1.03 1
 
< 0.1%
1.1 2
 
< 0.1%
1.5 14
 
0.1%
1.65 6
 
0.1%
ValueCountFrequency (%)
76.0 1
< 0.1%
75.75 1
< 0.1%
72.7 1
< 0.1%
70.0 1
< 0.1%
66.3 1
< 0.1%
64.8 1
< 0.1%
62.7 1
< 0.1%
59.5 1
< 0.1%
53.31 1
< 0.1%
52.61 1
< 0.1%
Distinct1714
Distinct (%)17.2%
Missing13
Missing (%)0.1%
Memory size156.2 KiB
2024-04-30T03:51:18.577462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0568739
Min length6

Characters and Unicode

Total characters60490
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

Unique703 ?
Unique (%)7.0%

Sample

1st row131866
2nd row130878
3rd row131813
4th row110826
5th row143824
ValueCountFrequency (%)
142070 137
 
1.4%
142100 124
 
1.2%
142060 61
 
0.6%
136075 61
 
0.6%
136865 52
 
0.5%
133871 51
 
0.5%
130851 51
 
0.5%
100101 49
 
0.5%
130872 47
 
0.5%
140132 44
 
0.4%
Other values (1704) 9310
93.2%
2024-04-30T03:51:18.970766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15626
25.8%
0 10945
18.1%
3 8072
13.3%
8 7948
13.1%
4 4358
 
7.2%
2 4236
 
7.0%
6 2739
 
4.5%
7 2203
 
3.6%
5 2144
 
3.5%
9 1651
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59922
99.1%
Dash Punctuation 568
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15626
26.1%
0 10945
18.3%
3 8072
13.5%
8 7948
13.3%
4 4358
 
7.3%
2 4236
 
7.1%
6 2739
 
4.6%
7 2203
 
3.7%
5 2144
 
3.6%
9 1651
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 568
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15626
25.8%
0 10945
18.1%
3 8072
13.3%
8 7948
13.1%
4 4358
 
7.2%
2 4236
 
7.0%
6 2739
 
4.5%
7 2203
 
3.6%
5 2144
 
3.5%
9 1651
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15626
25.8%
0 10945
18.1%
3 8072
13.3%
8 7948
13.1%
4 4358
 
7.2%
2 4236
 
7.0%
6 2739
 
4.5%
7 2203
 
3.6%
5 2144
 
3.5%
9 1651
 
2.7%
Distinct8410
Distinct (%)84.2%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-04-30T03:51:19.251606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length47
Mean length22.652687
Min length13

Characters and Unicode

Total characters226323
Distinct characters609
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7646 ?
Unique (%)76.5%

Sample

1st row서울특별시 중랑구 신내동 571-12
2nd row서울특별시 동대문구 휘경동 286-234
3rd row서울특별시 중랑구 면목동 462-1
4th row서울특별시 종로구 숭인동 228-6
5th row서울특별시 광진구 구의동 236-28
ValueCountFrequency (%)
서울특별시 9991
 
22.5%
중구 1606
 
3.6%
종로구 1098
 
2.5%
동대문구 1062
 
2.4%
중랑구 1050
 
2.4%
성북구 899
 
2.0%
광진구 782
 
1.8%
용산구 772
 
1.7%
강북구 757
 
1.7%
성동구 708
 
1.6%
Other values (8946) 25728
57.9%
2024-04-30T03:51:19.676665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43671
19.3%
11258
 
5.0%
10350
 
4.6%
10332
 
4.6%
10078
 
4.5%
10043
 
4.4%
9999
 
4.4%
9992
 
4.4%
1 9846
 
4.4%
- 9023
 
4.0%
Other values (599) 91731
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126822
56.0%
Decimal Number 45014
 
19.9%
Space Separator 43671
 
19.3%
Dash Punctuation 9023
 
4.0%
Close Punctuation 672
 
0.3%
Open Punctuation 671
 
0.3%
Uppercase Letter 311
 
0.1%
Other Punctuation 99
 
< 0.1%
Lowercase Letter 33
 
< 0.1%
Math Symbol 4
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11258
 
8.9%
10350
 
8.2%
10332
 
8.1%
10078
 
7.9%
10043
 
7.9%
9999
 
7.9%
9992
 
7.9%
3037
 
2.4%
2371
 
1.9%
2359
 
1.9%
Other values (531) 47003
37.1%
Uppercase Letter
ValueCountFrequency (%)
B 40
12.9%
S 36
11.6%
K 26
 
8.4%
D 25
 
8.0%
T 24
 
7.7%
A 23
 
7.4%
C 18
 
5.8%
G 17
 
5.5%
I 12
 
3.9%
M 11
 
3.5%
Other values (15) 79
25.4%
Lowercase Letter
ValueCountFrequency (%)
e 11
33.3%
o 3
 
9.1%
r 3
 
9.1%
l 2
 
6.1%
t 2
 
6.1%
a 2
 
6.1%
c 2
 
6.1%
n 2
 
6.1%
h 1
 
3.0%
p 1
 
3.0%
Other values (4) 4
 
12.1%
Decimal Number
ValueCountFrequency (%)
1 9846
21.9%
2 6253
13.9%
0 4885
10.9%
3 4674
10.4%
5 3815
 
8.5%
4 3739
 
8.3%
6 3586
 
8.0%
7 3009
 
6.7%
8 2780
 
6.2%
9 2427
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 64
64.6%
/ 16
 
16.2%
. 10
 
10.1%
: 3
 
3.0%
@ 3
 
3.0%
? 1
 
1.0%
* 1
 
1.0%
& 1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 670
99.7%
] 2
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 670
99.9%
[ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
| 2
50.0%
~ 2
50.0%
Space Separator
ValueCountFrequency (%)
43671
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9023
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126823
56.0%
Common 99155
43.8%
Latin 345
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11258
 
8.9%
10350
 
8.2%
10332
 
8.1%
10078
 
7.9%
10043
 
7.9%
9999
 
7.9%
9992
 
7.9%
3037
 
2.4%
2371
 
1.9%
2359
 
1.9%
Other values (532) 47004
37.1%
Latin
ValueCountFrequency (%)
B 40
 
11.6%
S 36
 
10.4%
K 26
 
7.5%
D 25
 
7.2%
T 24
 
7.0%
A 23
 
6.7%
C 18
 
5.2%
G 17
 
4.9%
I 12
 
3.5%
M 11
 
3.2%
Other values (30) 113
32.8%
Common
ValueCountFrequency (%)
43671
44.0%
1 9846
 
9.9%
- 9023
 
9.1%
2 6253
 
6.3%
0 4885
 
4.9%
3 4674
 
4.7%
5 3815
 
3.8%
4 3739
 
3.8%
6 3586
 
3.6%
7 3009
 
3.0%
Other values (17) 6654
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126822
56.0%
ASCII 99499
44.0%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43671
43.9%
1 9846
 
9.9%
- 9023
 
9.1%
2 6253
 
6.3%
0 4885
 
4.9%
3 4674
 
4.7%
5 3815
 
3.8%
4 3739
 
3.8%
6 3586
 
3.6%
7 3009
 
3.0%
Other values (56) 6998
 
7.0%
Hangul
ValueCountFrequency (%)
11258
 
8.9%
10350
 
8.2%
10332
 
8.1%
10078
 
7.9%
10043
 
7.9%
9999
 
7.9%
9992
 
7.9%
3037
 
2.4%
2371
 
1.9%
2359
 
1.9%
Other values (531) 47003
37.1%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct2480
Distinct (%)96.7%
Missing7435
Missing (%)74.4%
Memory size156.2 KiB
2024-04-30T03:51:20.015007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length53
Mean length31.070175
Min length19

Characters and Unicode

Total characters79695
Distinct characters532
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2417 ?
Unique (%)94.2%

Sample

1st row서울특별시 서초구 신반포로 지하 200, 지하1층 25호 (잠원동, 강남터미널지하도상가)
2nd row서울특별시 용산구 녹사평대로 220 (이태원동)
3rd row서울특별시 영등포구 선유로 27, 대륭오피스텔 지하1층 101호 (문래동5가)
4th row서울특별시 강남구 언주로 427, 1층 110호 (역삼동, 디오빌역삼)
5th row서울특별시 종로구 창경궁로 296-12, 지하1,지상1층 (혜화동)
ValueCountFrequency (%)
서울특별시 2565
 
16.5%
1층 700
 
4.5%
종로구 279
 
1.8%
성북구 247
 
1.6%
중구 243
 
1.6%
중랑구 239
 
1.5%
강북구 200
 
1.3%
광진구 196
 
1.3%
성동구 181
 
1.2%
동대문구 168
 
1.1%
Other values (3712) 10548
67.8%
2024-04-30T03:51:20.469318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13005
 
16.3%
1 3487
 
4.4%
3322
 
4.2%
2951
 
3.7%
2818
 
3.5%
( 2746
 
3.4%
) 2746
 
3.4%
2735
 
3.4%
2664
 
3.3%
2610
 
3.3%
Other values (522) 40611
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46891
58.8%
Space Separator 13005
 
16.3%
Decimal Number 11797
 
14.8%
Open Punctuation 2747
 
3.4%
Close Punctuation 2747
 
3.4%
Other Punctuation 1960
 
2.5%
Dash Punctuation 298
 
0.4%
Uppercase Letter 210
 
0.3%
Lowercase Letter 32
 
< 0.1%
Math Symbol 5
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3322
 
7.1%
2951
 
6.3%
2818
 
6.0%
2735
 
5.8%
2664
 
5.7%
2610
 
5.6%
2567
 
5.5%
2565
 
5.5%
1284
 
2.7%
1157
 
2.5%
Other values (456) 22218
47.4%
Uppercase Letter
ValueCountFrequency (%)
B 37
17.6%
S 26
12.4%
C 18
 
8.6%
K 15
 
7.1%
T 15
 
7.1%
A 13
 
6.2%
I 11
 
5.2%
U 11
 
5.2%
G 10
 
4.8%
D 9
 
4.3%
Other values (15) 45
21.4%
Lowercase Letter
ValueCountFrequency (%)
e 11
34.4%
r 3
 
9.4%
c 2
 
6.2%
n 2
 
6.2%
a 2
 
6.2%
o 2
 
6.2%
t 2
 
6.2%
l 2
 
6.2%
h 1
 
3.1%
m 1
 
3.1%
Other values (4) 4
 
12.5%
Decimal Number
ValueCountFrequency (%)
1 3487
29.6%
2 1604
13.6%
3 1152
 
9.8%
0 1032
 
8.7%
4 979
 
8.3%
5 883
 
7.5%
6 769
 
6.5%
7 716
 
6.1%
9 592
 
5.0%
8 583
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 1944
99.2%
. 7
 
0.4%
/ 3
 
0.2%
: 2
 
0.1%
@ 2
 
0.1%
? 1
 
0.1%
& 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2746
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2746
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
13005
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 298
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46892
58.8%
Common 32560
40.9%
Latin 243
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3322
 
7.1%
2951
 
6.3%
2818
 
6.0%
2735
 
5.8%
2664
 
5.7%
2610
 
5.6%
2567
 
5.5%
2565
 
5.5%
1284
 
2.7%
1157
 
2.5%
Other values (457) 22219
47.4%
Latin
ValueCountFrequency (%)
B 37
15.2%
S 26
 
10.7%
C 18
 
7.4%
K 15
 
6.2%
T 15
 
6.2%
A 13
 
5.3%
e 11
 
4.5%
I 11
 
4.5%
U 11
 
4.5%
G 10
 
4.1%
Other values (30) 76
31.3%
Common
ValueCountFrequency (%)
13005
39.9%
1 3487
 
10.7%
( 2746
 
8.4%
) 2746
 
8.4%
, 1944
 
6.0%
2 1604
 
4.9%
3 1152
 
3.5%
0 1032
 
3.2%
4 979
 
3.0%
5 883
 
2.7%
Other values (15) 2982
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46891
58.8%
ASCII 32802
41.2%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13005
39.6%
1 3487
 
10.6%
( 2746
 
8.4%
) 2746
 
8.4%
, 1944
 
5.9%
2 1604
 
4.9%
3 1152
 
3.5%
0 1032
 
3.1%
4 979
 
3.0%
5 883
 
2.7%
Other values (54) 3224
 
9.8%
Hangul
ValueCountFrequency (%)
3322
 
7.1%
2951
 
6.3%
2818
 
6.0%
2735
 
5.8%
2664
 
5.7%
2610
 
5.6%
2567
 
5.5%
2565
 
5.5%
1284
 
2.7%
1157
 
2.5%
Other values (456) 22218
47.4%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1465
Distinct (%)58.8%
Missing7508
Missing (%)75.1%
Infinite0
Infinite (%)0.0%
Mean3738.1449
Minimum1001
Maximum8861
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T03:51:20.590009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile1166.65
Q12241.75
median3156
Q34768
95-th percentile7955
Maximum8861
Range7860
Interquartile range (IQR)2526.25

Descriptive statistics

Standard deviation1929.4325
Coefficient of variation (CV)0.51614706
Kurtosis0.081185412
Mean3738.1449
Median Absolute Deviation (MAD)1399
Skewness0.7592922
Sum9315457
Variance3722709.7
MonotonicityNot monotonic
2024-04-30T03:51:20.704738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5116 17
 
0.2%
4804 11
 
0.1%
2842 11
 
0.1%
3149 9
 
0.1%
2254 9
 
0.1%
3191 9
 
0.1%
3129 8
 
0.1%
4991 8
 
0.1%
4548 7
 
0.1%
4515 7
 
0.1%
Other values (1455) 2396
 
24.0%
(Missing) 7508
75.1%
ValueCountFrequency (%)
1001 1
 
< 0.1%
1002 1
 
< 0.1%
1004 2
< 0.1%
1007 2
< 0.1%
1014 2
< 0.1%
1021 1
 
< 0.1%
1022 2
< 0.1%
1024 2
< 0.1%
1030 3
< 0.1%
1031 3
< 0.1%
ValueCountFrequency (%)
8861 1
< 0.1%
8858 1
< 0.1%
8847 1
< 0.1%
8838 1
< 0.1%
8837 1
< 0.1%
8830 1
< 0.1%
8828 2
< 0.1%
8814 2
< 0.1%
8813 1
< 0.1%
8812 2
< 0.1%
Distinct7980
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T03:51:20.942553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length5.6659
Min length1

Characters and Unicode

Total characters56659
Distinct characters859
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7204 ?
Unique (%)72.0%

Sample

1st row대성서적
2nd row삼육분식
3rd row대성열쇠
4th row이윤자
5th row해피마트
ValueCountFrequency (%)
씨유 110
 
1.0%
gs25 79
 
0.7%
심완조 61
 
0.5%
오광열 56
 
0.5%
이마트24 53
 
0.5%
자판기 53
 
0.5%
김선제 43
 
0.4%
39
 
0.3%
주)보광훼미리마트 36
 
0.3%
세븐일레븐 36
 
0.3%
Other values (8263) 10713
95.0%
2024-04-30T03:51:21.318827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1291
 
2.3%
1159
 
2.0%
886
 
1.6%
882
 
1.6%
816
 
1.4%
) 806
 
1.4%
( 805
 
1.4%
697
 
1.2%
644
 
1.1%
633
 
1.1%
Other values (849) 48040
84.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50388
88.9%
Decimal Number 1902
 
3.4%
Space Separator 1291
 
2.3%
Uppercase Letter 1095
 
1.9%
Close Punctuation 806
 
1.4%
Open Punctuation 805
 
1.4%
Lowercase Letter 221
 
0.4%
Other Punctuation 92
 
0.2%
Dash Punctuation 53
 
0.1%
Math Symbol 3
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1159
 
2.3%
886
 
1.8%
882
 
1.8%
816
 
1.6%
697
 
1.4%
644
 
1.3%
633
 
1.3%
631
 
1.3%
631
 
1.3%
603
 
1.2%
Other values (770) 42806
85.0%
Uppercase Letter
ValueCountFrequency (%)
S 236
21.6%
G 210
19.2%
C 173
15.8%
U 106
9.7%
P 55
 
5.0%
K 36
 
3.3%
L 31
 
2.8%
M 29
 
2.6%
A 28
 
2.6%
T 27
 
2.5%
Other values (16) 164
15.0%
Lowercase Letter
ValueCountFrequency (%)
e 32
14.5%
c 29
13.1%
a 25
11.3%
f 21
9.5%
o 19
8.6%
p 12
 
5.4%
i 10
 
4.5%
n 10
 
4.5%
u 10
 
4.5%
h 6
 
2.7%
Other values (14) 47
21.3%
Decimal Number
ValueCountFrequency (%)
2 587
30.9%
5 311
16.4%
1 267
14.0%
4 240
12.6%
3 150
 
7.9%
0 147
 
7.7%
6 68
 
3.6%
7 62
 
3.3%
8 42
 
2.2%
9 28
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 29
31.5%
/ 24
26.1%
, 12
13.0%
? 10
 
10.9%
* 6
 
6.5%
& 5
 
5.4%
: 2
 
2.2%
; 2
 
2.2%
' 1
 
1.1%
! 1
 
1.1%
Math Symbol
ValueCountFrequency (%)
× 2
66.7%
= 1
33.3%
Space Separator
ValueCountFrequency (%)
1291
100.0%
Close Punctuation
ValueCountFrequency (%)
) 806
100.0%
Open Punctuation
ValueCountFrequency (%)
( 805
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50387
88.9%
Common 4953
 
8.7%
Latin 1317
 
2.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1159
 
2.3%
886
 
1.8%
882
 
1.8%
816
 
1.6%
697
 
1.4%
644
 
1.3%
633
 
1.3%
631
 
1.3%
631
 
1.3%
603
 
1.2%
Other values (769) 42805
85.0%
Latin
ValueCountFrequency (%)
S 236
17.9%
G 210
15.9%
C 173
13.1%
U 106
 
8.0%
P 55
 
4.2%
K 36
 
2.7%
e 32
 
2.4%
L 31
 
2.4%
c 29
 
2.2%
M 29
 
2.2%
Other values (41) 380
28.9%
Common
ValueCountFrequency (%)
1291
26.1%
) 806
16.3%
( 805
16.3%
2 587
11.9%
5 311
 
6.3%
1 267
 
5.4%
4 240
 
4.8%
3 150
 
3.0%
0 147
 
3.0%
6 68
 
1.4%
Other values (17) 281
 
5.7%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50386
88.9%
ASCII 6267
 
11.1%
None 3
 
< 0.1%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1291
20.6%
) 806
12.9%
( 805
12.8%
2 587
9.4%
5 311
 
5.0%
1 267
 
4.3%
4 240
 
3.8%
S 236
 
3.8%
G 210
 
3.4%
C 173
 
2.8%
Other values (66) 1341
21.4%
Hangul
ValueCountFrequency (%)
1159
 
2.3%
886
 
1.8%
882
 
1.8%
816
 
1.6%
697
 
1.4%
644
 
1.3%
633
 
1.3%
631
 
1.3%
631
 
1.3%
603
 
1.2%
Other values (768) 42804
85.0%
None
ValueCountFrequency (%)
× 2
66.7%
1
33.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct4239
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-19 00:00:00
Maximum2024-04-25 14:25:51
2024-04-30T03:51:21.435706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:51:21.555070image/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 size156.2 KiB
I
8996 
U
1004 

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 8996
90.0%
U 1004
 
10.0%

Length

2024-04-30T03:51:21.671633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:21.743511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 8996
90.0%
u 1004
 
10.0%
Distinct780
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-30T03:51:21.824078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:51:22.139151image/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 size156.2 KiB
식품자동판매기영업
10000 

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 10000
100.0%

Length

2024-04-30T03:51:22.248856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:22.322032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 10000
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct6254
Distinct (%)74.8%
Missing1641
Missing (%)16.4%
Infinite0
Infinite (%)0.0%
Mean202249.42
Minimum182141.21
Maximum215915.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T03:51:22.404210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile196456.51
Q1199045.17
median202648.06
Q3205582.04
95-th percentile208202.14
Maximum215915.64
Range33774.439
Interquartile range (IQR)6536.8655

Descriptive statistics

Standard deviation4243.187
Coefficient of variation (CV)0.020979972
Kurtosis1.1031575
Mean202249.42
Median Absolute Deviation (MAD)3184.2995
Skewness-0.64252059
Sum1.6906029 × 109
Variance18004636
MonotonicityNot monotonic
2024-04-30T03:51:22.519291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203684.127182478 46
 
0.5%
196831.461759469 30
 
0.3%
198259.65357739 29
 
0.3%
197761.440311167 26
 
0.3%
196701.958402155 23
 
0.2%
198004.737917005 22
 
0.2%
200463.625303538 19
 
0.2%
200703.625559248 18
 
0.2%
208394.416382167 18
 
0.2%
197675.397522479 18
 
0.2%
Other values (6244) 8110
81.1%
(Missing) 1641
 
16.4%
ValueCountFrequency (%)
182141.205465089 1
< 0.1%
182649.013704222 1
< 0.1%
183237.203672348 1
< 0.1%
183262.49416151 1
< 0.1%
183306.673760838 1
< 0.1%
183469.462931642 1
< 0.1%
184544.625577034 1
< 0.1%
184569.514474049 1
< 0.1%
184708.91631646 2
< 0.1%
184738.261113254 1
< 0.1%
ValueCountFrequency (%)
215915.644224677 1
< 0.1%
215730.622600971 1
< 0.1%
215496.149626989 1
< 0.1%
215010.763627235 1
< 0.1%
214845.602103361 1
< 0.1%
214299.285610196 1
< 0.1%
213860.362849957 1
< 0.1%
213505.546978547 1
< 0.1%
213378.690584816 1
< 0.1%
213354.806799715 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct6253
Distinct (%)74.8%
Missing1641
Missing (%)16.4%
Infinite0
Infinite (%)0.0%
Mean452884.47
Minimum437674.9
Maximum465460.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T03:51:22.627244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437674.9
5-th percentile447333.42
Q1450607.5
median452189.09
Q3455051.3
95-th percentile461376.14
Maximum465460.11
Range27785.209
Interquartile range (IQR)4443.7999

Descriptive statistics

Standard deviation4214.0297
Coefficient of variation (CV)0.0093048667
Kurtosis0.63625535
Mean452884.47
Median Absolute Deviation (MAD)2319.5128
Skewness0.38344537
Sum3.7856613 × 109
Variance17758046
MonotonicityNot monotonic
2024-04-30T03:51:22.736069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450698.570810848 46
 
0.5%
449320.370380461 30
 
0.3%
451392.198218657 29
 
0.3%
451123.194550747 26
 
0.3%
446837.982163744 23
 
0.2%
451589.338993848 22
 
0.2%
450497.460903907 19
 
0.2%
451836.458256618 18
 
0.2%
448165.279999905 18
 
0.2%
450448.56432183 18
 
0.2%
Other values (6243) 8110
81.1%
(Missing) 1641
 
16.4%
ValueCountFrequency (%)
437674.901694125 1
< 0.1%
437731.020341188 1
< 0.1%
437773.047519431 1
< 0.1%
437812.839136767 1
< 0.1%
438365.613175801 1
< 0.1%
438399.831504964 1
< 0.1%
438459.243814272 1
< 0.1%
438483.387454937 1
< 0.1%
438690.814038292 1
< 0.1%
438693.72165701 1
< 0.1%
ValueCountFrequency (%)
465460.110785499 2
< 0.1%
465291.710893362 1
< 0.1%
465180.671733594 2
< 0.1%
465077.944095077 1
< 0.1%
465074.746331547 1
< 0.1%
465060.337410728 2
< 0.1%
465042.493324016 1
< 0.1%
465027.96462562 1
< 0.1%
465024.305928003 1
< 0.1%
465002.243917998 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
식품자동판매기영업
9277 
<NA>
 
723

Length

Max length9
Median length9
Mean length8.6385
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 9277
92.8%
<NA> 723
 
7.2%

Length

2024-04-30T03:51:22.842995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:22.944852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 9277
92.8%
na 723
 
7.2%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4959 
0
4898 
1
 
142
41
 
1

Length

Max length4
Median length1
Mean length2.4878
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4959
49.6%
0 4898
49.0%
1 142
 
1.4%
41 1
 
< 0.1%

Length

2024-04-30T03:51:23.050564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:23.150106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4959
49.6%
0 4898
49.0%
1 142
 
1.4%
41 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4972 
0
4965 
1
 
63

Length

Max length4
Median length1
Mean length2.4916
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4972
49.7%
0 4965
49.6%
1 63
 
0.6%

Length

2024-04-30T03:51:23.252254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:23.336551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4972
49.7%
0 4965
49.6%
1 63
 
0.6%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
기타
5247 
<NA>
3804 
결혼예식장주변
 
521
주택가주변
 
339
아파트지역
 
34
Other values (3)
 
55

Length

Max length8
Median length2
Mean length3.1662
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 5247
52.5%
<NA> 3804
38.0%
결혼예식장주변 521
 
5.2%
주택가주변 339
 
3.4%
아파트지역 34
 
0.3%
학교정화(상대) 25
 
0.2%
유흥업소밀집지역 21
 
0.2%
학교정화(절대) 9
 
0.1%

Length

2024-04-30T03:51:23.427521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:23.524387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 5247
52.5%
na 3804
38.0%
결혼예식장주변 521
 
5.2%
주택가주변 339
 
3.4%
아파트지역 34
 
0.3%
학교정화(상대 25
 
0.2%
유흥업소밀집지역 21
 
0.2%
학교정화(절대 9
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
기타
5731 
<NA>
3804 
자율
 
276
지도
 
167
 
15
Other values (3)
 
7

Length

Max length4
Median length2
Mean length2.759
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 5731
57.3%
<NA> 3804
38.0%
자율 276
 
2.8%
지도 167
 
1.7%
15
 
0.1%
3
 
< 0.1%
우수 3
 
< 0.1%
관리 1
 
< 0.1%

Length

2024-04-30T03:51:23.638234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:23.731403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 5731
57.3%
na 3804
38.0%
자율 276
 
2.8%
지도 167
 
1.7%
15
 
0.1%
3
 
< 0.1%
우수 3
 
< 0.1%
관리 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9409 
상수도전용
 
591

Length

Max length5
Median length4
Mean length4.0591
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> 9409
94.1%
상수도전용 591
 
5.9%

Length

2024-04-30T03:51:23.834208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:23.905711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9409
94.1%
상수도전용 591
 
5.9%

총인원
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8308 
0
1692 

Length

Max length4
Median length4
Mean length3.4924
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> 8308
83.1%
0 1692
 
16.9%

Length

2024-04-30T03:51:23.993457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:24.075217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8308
83.1%
0 1692
 
16.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5609 
0
4391 

Length

Max length4
Median length4
Mean length2.6827
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5609
56.1%
0 4391
43.9%

Length

2024-04-30T03:51:24.156419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:24.236429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5609
56.1%
0 4391
43.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5609 
0
4391 

Length

Max length4
Median length4
Mean length2.6827
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5609
56.1%
0 4391
43.9%

Length

2024-04-30T03:51:24.330266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:24.415598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5609
56.1%
0 4391
43.9%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5609 
0
4390 
1
 
1

Length

Max length4
Median length4
Mean length2.6827
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5609
56.1%
0 4390
43.9%
1 1
 
< 0.1%

Length

2024-04-30T03:51:24.498888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:24.590926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5609
56.1%
0 4390
43.9%
1 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5609 
0
4391 

Length

Max length4
Median length4
Mean length2.6827
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5609
56.1%
0 4391
43.9%

Length

2024-04-30T03:51:24.680154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:24.765536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5609
56.1%
0 4391
43.9%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8120 
자가
1698 
임대
 
182

Length

Max length4
Median length4
Mean length3.624
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8120
81.2%
자가 1698
 
17.0%
임대 182
 
1.8%

Length

2024-04-30T03:51:24.857270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:24.939598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8120
81.2%
자가 1698
 
17.0%
임대 182
 
1.8%

보증액
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7362 
0
2636 
1764840
 
1
17163000
 
1

Length

Max length8
Median length4
Mean length3.2099
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7362
73.6%
0 2636
 
26.4%
1764840 1
 
< 0.1%
17163000 1
 
< 0.1%

Length

2024-04-30T03:51:25.031350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:25.127782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7362
73.6%
0 2636
 
26.4%
1764840 1
 
< 0.1%
17163000 1
 
< 0.1%

월세액
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7362 
0
2637 
1716330
 
1

Length

Max length7
Median length4
Mean length3.2092
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7362
73.6%
0 2637
 
26.4%
1716330 1
 
< 0.1%

Length

2024-04-30T03:51:25.249470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:25.339418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7362
73.6%
0 2637
 
26.4%
1716330 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing723
Missing (%)7.2%
Memory size97.7 KiB
False
9277 
(Missing)
 
723
ValueCountFrequency (%)
False 9277
92.8%
(Missing) 723
 
7.2%
2024-04-30T03:51:25.404647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct30
Distinct (%)0.3%
Missing723
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean0.093657432
Minimum0
Maximum66.3
Zeros9103
Zeros (%)91.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T03:51:25.499566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum66.3
Range66.3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3097263
Coefficient of variation (CV)13.984222
Kurtosis1271.158
Mean0.093657432
Median Absolute Deviation (MAD)0
Skewness32.011808
Sum868.86
Variance1.715383
MonotonicityNot monotonic
2024-04-30T03:51:25.620343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.0 9103
91.0%
3.3 92
 
0.9%
1.0 14
 
0.1%
3.0 10
 
0.1%
3.6 10
 
0.1%
2.0 7
 
0.1%
6.6 6
 
0.1%
2.21 5
 
0.1%
1.5 4
 
< 0.1%
2.4 3
 
< 0.1%
Other values (20) 23
 
0.2%
(Missing) 723
 
7.2%
ValueCountFrequency (%)
0.0 9103
91.0%
0.36 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 14
 
0.1%
1.5 4
 
< 0.1%
1.65 1
 
< 0.1%
2.0 7
 
0.1%
2.21 5
 
0.1%
2.4 3
 
< 0.1%
3.0 10
 
0.1%
ValueCountFrequency (%)
66.3 1
< 0.1%
52.49 1
< 0.1%
44.41 1
< 0.1%
36.3 1
< 0.1%
33.0 1
< 0.1%
24.18 1
< 0.1%
24.0 1
< 0.1%
21.0 2
< 0.1%
20.0 1
< 0.1%
12.0 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1978730600003060000-112-2001-0112720010912<NA>3폐업2폐업20050604<NA><NA><NA>0234232481<NA>131866서울특별시 중랑구 신내동 571-12<NA><NA>대성서적2004-08-05 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
1552430500003050000-112-2002-0007420020326<NA>3폐업2폐업20060321<NA><NA><NA>02 221509010.0130878서울특별시 동대문구 휘경동 286-234<NA><NA>삼육분식2006-02-06 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업205475.21697454035.150123식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
1917430600003060000-112-1999-0079319991125<NA>3폐업2폐업20030625<NA><NA><NA>02 4353536<NA>131813서울특별시 중랑구 면목동 462-1<NA><NA>대성열쇠2003-07-03 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업207907.073122453308.745568식품자동판매기영업10주택가주변자율<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
447630000003000000-112-1998-0124619980817<NA>3폐업2폐업20041101<NA><NA><NA>0200000000<NA>110826서울특별시 종로구 숭인동 228-6<NA><NA>이윤자2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업201614.448901452384.307654식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1317630400003040000-112-2004-0005520041224<NA>3폐업2폐업20051214<NA><NA><NA>02 4569471<NA>143824서울특별시 광진구 구의동 236-28<NA><NA>해피마트2004-12-24 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업207407.361658448951.920487식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1302530400003040000-112-1999-0109119990929<NA>3폐업2폐업20071210<NA><NA><NA>02 4575911<NA>143861서울특별시 광진구 자양동 512-8 부영정육점<NA><NA>부영정육점(자판기)2002-03-14 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업206142.104271448249.988777식품자동판매기영업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
871030100003010000-112-1997-0297119970226<NA>3폐업2폐업20000323<NA><NA><NA>0251121762<NA>100380서울특별시 중구 묵정동 1-19 2573호<NA><NA>(주)보광훼미리마트2000-03-23 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업199856.423395451026.227712식품자동판매기영업00기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
10432100003210000-112-2017-000162017-06-30<NA>3폐업2폐업2023-03-20<NA><NA><NA><NA>2.0137-040서울특별시 서초구 반포동 128-4 강남터미널지하도상가 내 지하1층 25호서울특별시 서초구 신반포로 지하 200, 지하1층 25호 (잠원동, 강남터미널지하도상가)6545강남터미털 지하상가내 25호2023-03-20 11:35:16U2022-12-02 22:02:00.0식품자동판매기영업200367.588604444873.437819<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1490930500003050000-112-1989-0021019890401<NA>3폐업2폐업19961217<NA><NA><NA>02<NA>130812서울특별시 동대문구 신설동 101-7<NA><NA>오광열2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업202056.089579452590.463014식품자동판매기영업00기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631430100003010000-112-1989-0150219890415<NA>3폐업2폐업20150202<NA><NA><NA><NA><NA>100101서울특별시 중구 태평로1가 61-0<NA><NA>소용석2011-05-19 16:45:13I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00결혼예식장주변기타<NA>00000<NA>00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
2601330900003090000-112-2006-0001220060406<NA>3폐업2폐업20070323<NA><NA><NA><NA><NA>132918서울특별시 도봉구 창동 581-12<NA><NA>명진철물2006-04-06 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업203339.702297459789.896596식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
2078830700003070000-112-1986-0008319860308<NA>3폐업2폐업20210430<NA><NA><NA>02 958010<NA>136045서울특별시 성북구 삼선동5가 411-0서울특별시 성북구 보문로 168 (삼선동5가)2848성북구청청사내자판기2021-04-30 11:04:38U2021-05-02 02:40:00.0식품자동판매기영업201416.773357454126.789905식품자동판매기영업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1123330300003030000-112-1998-0029819980522<NA>3폐업2폐업20010803<NA><NA><NA>02<NA>133837서울특별시 성동구 송정동 92-25<NA><NA>이가식당2001-11-22 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업206243.875021450406.274식품자동판매기영업00기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
2408330800003080000-112-1994-0127119940413<NA>3폐업2폐업19941031<NA><NA><NA>0200000000<NA>142100서울특별시 강북구 미아동 산 35-5<NA><NA>삼성빌딩2층2001-09-27 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
89030200003020000-112-2024-000022024-04-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.0140-881서울특별시 용산구 한강로3가 40-708서울특별시 용산구 한강대로23길 25, 4층 (한강로3가)4378솜사탕2024-04-05 13:16:11I2023-12-04 00:07:00.0식품자동판매기영업196785.404802447267.982864<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1854830600003060000-112-2008-0001020080404<NA>3폐업2폐업20090303<NA><NA><NA>02 4331886<NA>131857서울특별시 중랑구 상봉동 74-32<NA><NA>대박해장국2008-04-04 10:15:22I2018-08-31 23:59:59.0식품자동판매기영업208334.946402455204.386079식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
2289430800003080000-112-2016-0001320161019<NA>3폐업2폐업20180313<NA><NA><NA><NA><NA>142879서울특별시 강북구 수유동 251-8서울특별시 강북구 한천로 1102 (수유동)1048수유고려2018-03-13 13:56:18I2018-08-31 23:59:59.0식품자동판매기영업201831.094351460186.414299식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
2451230900003090000-112-2005-0005820051101<NA>3폐업2폐업20091216<NA><NA><NA><NA><NA>132849서울특별시 도봉구 방학동 671-22<NA><NA>삼성유통(영광운수)2005-11-01 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업203063.884845462198.036407식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
528930100003010000-112-1992-0261819921021<NA>3폐업2폐업20070803<NA><NA><NA>02<NA>100840서울특별시 중구 신당동 373-3<NA><NA>황인영2001-10-08 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업200929.515412450242.717074식품자동판매기영업00기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
127331300003130000-112-2024-000012024-03-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.0121-880서울특별시 마포구 창전동 6-131서울특별시 마포구 와우산로 130, 3층 (창전동)4059(주)사운드팩토리2024-03-05 15:44:50I2023-12-03 00:07:00.0식품자동판매기영업193565.518001450125.046928<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>