Overview

Dataset statistics

Number of variables44
Number of observations4525
Missing cells51501
Missing cells (%)25.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory376.0 B

Variable types

Categorical18
Text7
DateTime4
Unsupported8
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-18697/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (59.0%)Imbalance
등급구분명 is highly imbalanced (59.3%)Imbalance
총인원 is highly imbalanced (74.0%)Imbalance
본사종업원수 is highly imbalanced (73.7%)Imbalance
공장사무직종업원수 is highly imbalanced (73.7%)Imbalance
공장판매직종업원수 is highly imbalanced (73.7%)Imbalance
공장생산직종업원수 is highly imbalanced (73.7%)Imbalance
보증액 is highly imbalanced (73.7%)Imbalance
월세액 is highly imbalanced (73.7%)Imbalance
다중이용업소여부 is highly imbalanced (89.9%)Imbalance
인허가취소일자 has 4525 (100.0%) missing valuesMissing
폐업일자 has 1384 (30.6%) missing valuesMissing
휴업시작일자 has 4525 (100.0%) missing valuesMissing
휴업종료일자 has 4525 (100.0%) missing valuesMissing
재개업일자 has 4525 (100.0%) missing valuesMissing
전화번호 has 2490 (55.0%) missing valuesMissing
도로명주소 has 1572 (34.7%) missing valuesMissing
도로명우편번호 has 1582 (35.0%) missing valuesMissing
좌표정보(X) has 87 (1.9%) missing valuesMissing
좌표정보(Y) has 87 (1.9%) missing valuesMissing
남성종사자수 has 3020 (66.7%) missing valuesMissing
여성종사자수 has 3013 (66.6%) missing valuesMissing
건물소유구분명 has 4525 (100.0%) missing valuesMissing
다중이용업소여부 has 1020 (22.5%) missing valuesMissing
시설총규모 has 1020 (22.5%) missing valuesMissing
전통업소지정번호 has 4525 (100.0%) missing valuesMissing
전통업소주된음식 has 4525 (100.0%) missing valuesMissing
홈페이지 has 4525 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 1320 (29.2%) zerosZeros
여성종사자수 has 1011 (22.3%) zerosZeros

Reproduction

Analysis started2024-05-11 07:02:32.789147
Analysis finished2024-05-11 07:02:37.611563
Duration4.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
3200000
4525 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 4525
100.0%

Length

2024-05-11T07:02:37.923548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:38.363895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 4525
100.0%

관리번호
Text

UNIQUE 

Distinct4525
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
2024-05-11T07:02:39.035863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters99550
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

Unique4525 ?
Unique (%)100.0%

Sample

1st row3200000-104-1971-08507
2nd row3200000-104-1971-08590
3rd row3200000-104-1972-08501
4th row3200000-104-1972-08510
5th row3200000-104-1972-08532
ValueCountFrequency (%)
3200000-104-1971-08507 1
 
< 0.1%
3200000-104-2017-00134 1
 
< 0.1%
3200000-104-2017-00140 1
 
< 0.1%
3200000-104-2017-00139 1
 
< 0.1%
3200000-104-2017-00138 1
 
< 0.1%
3200000-104-2017-00137 1
 
< 0.1%
3200000-104-2017-00147 1
 
< 0.1%
3200000-104-2017-00135 1
 
< 0.1%
3200000-104-2017-00133 1
 
< 0.1%
3200000-104-2017-00142 1
 
< 0.1%
Other values (4515) 4515
99.8%
2024-05-11T07:02:40.880527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 42944
43.1%
- 13575
 
13.6%
2 10818
 
10.9%
1 10435
 
10.5%
3 6216
 
6.2%
4 5950
 
6.0%
9 3175
 
3.2%
8 2284
 
2.3%
7 1438
 
1.4%
6 1393
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85975
86.4%
Dash Punctuation 13575
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 42944
49.9%
2 10818
 
12.6%
1 10435
 
12.1%
3 6216
 
7.2%
4 5950
 
6.9%
9 3175
 
3.7%
8 2284
 
2.7%
7 1438
 
1.7%
6 1393
 
1.6%
5 1322
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 13575
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99550
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 42944
43.1%
- 13575
 
13.6%
2 10818
 
10.9%
1 10435
 
10.5%
3 6216
 
6.2%
4 5950
 
6.0%
9 3175
 
3.2%
8 2284
 
2.3%
7 1438
 
1.4%
6 1393
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 42944
43.1%
- 13575
 
13.6%
2 10818
 
10.9%
1 10435
 
10.5%
3 6216
 
6.2%
4 5950
 
6.0%
9 3175
 
3.2%
8 2284
 
2.3%
7 1438
 
1.4%
6 1393
 
1.4%
Distinct3268
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
Minimum1971-06-16 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T07:02:41.617104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:02:42.472501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4525
Missing (%)100.0%
Memory size39.9 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
3
3141 
1
1384 

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 3141
69.4%
1 1384
30.6%

Length

2024-05-11T07:02:42.999303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:43.493868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3141
69.4%
1 1384
30.6%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
폐업
3141 
영업/정상
1384 

Length

Max length5
Median length2
Mean length2.9175691
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3141
69.4%
영업/정상 1384
30.6%

Length

2024-05-11T07:02:44.145213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:44.507181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3141
69.4%
영업/정상 1384
30.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
2
3141 
1
1384 

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 3141
69.4%
1 1384
30.6%

Length

2024-05-11T07:02:44.807426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:45.114716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3141
69.4%
1 1384
30.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
폐업
3141 
영업
1384 

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 3141
69.4%
영업 1384
30.6%

Length

2024-05-11T07:02:45.463517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:45.737853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3141
69.4%
영업 1384
30.6%

폐업일자
Date

MISSING 

Distinct2410
Distinct (%)76.7%
Missing1384
Missing (%)30.6%
Memory size35.5 KiB
Minimum1984-08-28 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T07:02:46.054734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:02:46.580069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4525
Missing (%)100.0%
Memory size39.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4525
Missing (%)100.0%
Memory size39.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4525
Missing (%)100.0%
Memory size39.9 KiB

전화번호
Text

MISSING 

Distinct1712
Distinct (%)84.1%
Missing2490
Missing (%)55.0%
Memory size35.5 KiB
2024-05-11T07:02:47.511447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.6358722
Min length2

Characters and Unicode

Total characters19609
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

Unique1660 ?
Unique (%)81.6%

Sample

1st row02 8774939
2nd row02
3rd row02 8771894
4th row02 8771457
5th row02 8785635
ValueCountFrequency (%)
02 1651
41.6%
070 61
 
1.5%
877 39
 
1.0%
00000 34
 
0.9%
0 31
 
0.8%
883 26
 
0.7%
882 25
 
0.6%
876 20
 
0.5%
878 20
 
0.5%
888 19
 
0.5%
Other values (1773) 2046
51.5%
2024-05-11T07:02:48.858418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3603
18.4%
8 3099
15.8%
2 2969
15.1%
2427
12.4%
7 1635
8.3%
5 1153
 
5.9%
3 1063
 
5.4%
6 1056
 
5.4%
1 888
 
4.5%
9 879
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17182
87.6%
Space Separator 2427
 
12.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3603
21.0%
8 3099
18.0%
2 2969
17.3%
7 1635
9.5%
5 1153
 
6.7%
3 1063
 
6.2%
6 1056
 
6.1%
1 888
 
5.2%
9 879
 
5.1%
4 837
 
4.9%
Space Separator
ValueCountFrequency (%)
2427
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19609
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3603
18.4%
8 3099
15.8%
2 2969
15.1%
2427
12.4%
7 1635
8.3%
5 1153
 
5.9%
3 1063
 
5.4%
6 1056
 
5.4%
1 888
 
4.5%
9 879
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19609
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3603
18.4%
8 3099
15.8%
2 2969
15.1%
2427
12.4%
7 1635
8.3%
5 1153
 
5.9%
3 1063
 
5.4%
6 1056
 
5.4%
1 888
 
4.5%
9 879
 
4.5%
Distinct2133
Distinct (%)47.4%
Missing26
Missing (%)0.6%
Memory size35.5 KiB
2024-05-11T07:02:49.704514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9190931
Min length3

Characters and Unicode

Total characters22131
Distinct characters12
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

Unique1690 ?
Unique (%)37.6%

Sample

1st row136.38
2nd row51.83
3rd row198.42
4th row129.55
5th row.00
ValueCountFrequency (%)
6.60 212
 
4.7%
3.30 177
 
3.9%
33.00 103
 
2.3%
26.40 65
 
1.4%
30.00 63
 
1.4%
10.00 59
 
1.3%
16.50 57
 
1.3%
9.90 56
 
1.2%
20.00 56
 
1.2%
6.00 54
 
1.2%
Other values (2123) 3597
80.0%
2024-05-11T07:02:51.239946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4534
20.5%
. 4499
20.3%
3 1900
8.6%
2 1825
8.2%
1 1822
8.2%
6 1784
 
8.1%
5 1286
 
5.8%
4 1277
 
5.8%
9 1148
 
5.2%
8 1072
 
4.8%
Other values (2) 984
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17631
79.7%
Other Punctuation 4500
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4534
25.7%
3 1900
10.8%
2 1825
10.4%
1 1822
10.3%
6 1784
 
10.1%
5 1286
 
7.3%
4 1277
 
7.2%
9 1148
 
6.5%
8 1072
 
6.1%
7 983
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 4499
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 22131
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4534
20.5%
. 4499
20.3%
3 1900
8.6%
2 1825
8.2%
1 1822
8.2%
6 1784
 
8.1%
5 1286
 
5.8%
4 1277
 
5.8%
9 1148
 
5.2%
8 1072
 
4.8%
Other values (2) 984
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22131
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4534
20.5%
. 4499
20.3%
3 1900
8.6%
2 1825
8.2%
1 1822
8.2%
6 1784
 
8.1%
5 1286
 
5.8%
4 1277
 
5.8%
9 1148
 
5.2%
8 1072
 
4.8%
Other values (2) 984
 
4.4%
Distinct222
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
2024-05-11T07:02:52.246192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1485083
Min length6

Characters and Unicode

Total characters27822
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

Unique21 ?
Unique (%)0.5%

Sample

1st row151803
2nd row151803
3rd row151050
4th row151810
5th row151853
ValueCountFrequency (%)
151895 199
 
4.4%
151930 168
 
3.7%
151830 136
 
3.0%
151015 112
 
2.5%
151890 109
 
2.4%
151836 104
 
2.3%
151832 101
 
2.2%
151892 98
 
2.2%
151848 94
 
2.1%
151800 91
 
2.0%
Other values (212) 3313
73.2%
2024-05-11T07:02:53.574739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9865
35.5%
5 5599
20.1%
8 4372
15.7%
0 1679
 
6.0%
9 1546
 
5.6%
3 1245
 
4.5%
4 895
 
3.2%
2 799
 
2.9%
- 672
 
2.4%
7 635
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27150
97.6%
Dash Punctuation 672
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9865
36.3%
5 5599
20.6%
8 4372
16.1%
0 1679
 
6.2%
9 1546
 
5.7%
3 1245
 
4.6%
4 895
 
3.3%
2 799
 
2.9%
7 635
 
2.3%
6 515
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 672
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27822
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9865
35.5%
5 5599
20.1%
8 4372
15.7%
0 1679
 
6.0%
9 1546
 
5.6%
3 1245
 
4.5%
4 895
 
3.2%
2 799
 
2.9%
- 672
 
2.4%
7 635
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27822
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9865
35.5%
5 5599
20.1%
8 4372
15.7%
0 1679
 
6.0%
9 1546
 
5.6%
3 1245
 
4.5%
4 895
 
3.2%
2 799
 
2.9%
- 672
 
2.4%
7 635
 
2.3%
Distinct3446
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
2024-05-11T07:02:54.350296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length46
Mean length23.656796
Min length17

Characters and Unicode

Total characters107047
Distinct characters353
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2765 ?
Unique (%)61.1%

Sample

1st row서울특별시 관악구 봉천동 14-52번지
2nd row서울특별시 관악구 봉천동 14-21번지
3rd row서울특별시 관악구 봉천동 399-1번지
4th row서울특별시 관악구 봉천동 32-2번지
5th row서울특별시 관악구 신림동 82-2번지
ValueCountFrequency (%)
서울특별시 4525
23.2%
관악구 4525
23.2%
신림동 2343
12.0%
봉천동 2020
 
10.4%
지상1층 267
 
1.4%
남현동 163
 
0.8%
729-22번지 90
 
0.5%
82
 
0.4%
롯데백화점 51
 
0.3%
지하1층 49
 
0.3%
Other values (3474) 5372
27.6%
2024-05-11T07:02:55.547078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18413
 
17.2%
1 5591
 
5.2%
4614
 
4.3%
4583
 
4.3%
4583
 
4.3%
4577
 
4.3%
4566
 
4.3%
4541
 
4.2%
4531
 
4.2%
4526
 
4.2%
Other values (343) 46522
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60566
56.6%
Decimal Number 23427
 
21.9%
Space Separator 18413
 
17.2%
Dash Punctuation 4422
 
4.1%
Uppercase Letter 79
 
0.1%
Other Punctuation 73
 
0.1%
Close Punctuation 29
 
< 0.1%
Open Punctuation 29
 
< 0.1%
Lowercase Letter 5
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4614
 
7.6%
4583
 
7.6%
4583
 
7.6%
4577
 
7.6%
4566
 
7.5%
4541
 
7.5%
4531
 
7.5%
4526
 
7.5%
4526
 
7.5%
3431
 
5.7%
Other values (302) 16088
26.6%
Uppercase Letter
ValueCountFrequency (%)
A 15
19.0%
B 13
16.5%
S 7
8.9%
M 5
 
6.3%
T 5
 
6.3%
E 5
 
6.3%
I 5
 
6.3%
C 4
 
5.1%
G 3
 
3.8%
K 3
 
3.8%
Other values (9) 14
17.7%
Decimal Number
ValueCountFrequency (%)
1 5591
23.9%
2 2903
12.4%
6 2627
11.2%
5 2245
9.6%
3 2044
 
8.7%
4 2012
 
8.6%
9 1552
 
6.6%
8 1540
 
6.6%
7 1519
 
6.5%
0 1394
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 64
87.7%
@ 7
 
9.6%
& 1
 
1.4%
. 1
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
80.0%
n 1
 
20.0%
Space Separator
ValueCountFrequency (%)
18413
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4422
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60566
56.6%
Common 46396
43.3%
Latin 85
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4614
 
7.6%
4583
 
7.6%
4583
 
7.6%
4577
 
7.6%
4566
 
7.5%
4541
 
7.5%
4531
 
7.5%
4526
 
7.5%
4526
 
7.5%
3431
 
5.7%
Other values (302) 16088
26.6%
Latin
ValueCountFrequency (%)
A 15
17.6%
B 13
15.3%
S 7
 
8.2%
M 5
 
5.9%
T 5
 
5.9%
E 5
 
5.9%
I 5
 
5.9%
e 4
 
4.7%
C 4
 
4.7%
G 3
 
3.5%
Other values (12) 19
22.4%
Common
ValueCountFrequency (%)
18413
39.7%
1 5591
 
12.1%
- 4422
 
9.5%
2 2903
 
6.3%
6 2627
 
5.7%
5 2245
 
4.8%
3 2044
 
4.4%
4 2012
 
4.3%
9 1552
 
3.3%
8 1540
 
3.3%
Other values (9) 3047
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60566
56.6%
ASCII 46480
43.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18413
39.6%
1 5591
 
12.0%
- 4422
 
9.5%
2 2903
 
6.2%
6 2627
 
5.7%
5 2245
 
4.8%
3 2044
 
4.4%
4 2012
 
4.3%
9 1552
 
3.3%
8 1540
 
3.3%
Other values (30) 3131
 
6.7%
Hangul
ValueCountFrequency (%)
4614
 
7.6%
4583
 
7.6%
4583
 
7.6%
4577
 
7.6%
4566
 
7.5%
4541
 
7.5%
4531
 
7.5%
4526
 
7.5%
4526
 
7.5%
3431
 
5.7%
Other values (302) 16088
26.6%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct2524
Distinct (%)85.5%
Missing1572
Missing (%)34.7%
Memory size35.5 KiB
2024-05-11T07:02:56.455938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length55
Mean length31.198442
Min length21

Characters and Unicode

Total characters92129
Distinct characters383
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2221 ?
Unique (%)75.2%

Sample

1st row서울특별시 관악구 남부순환로 1607, 지하1층 (신림동)
2nd row서울특별시 관악구 신림로 149, 지하1층 (신림동)
3rd row서울특별시 관악구 봉천로33길 6, 자하1층 (봉천동)
4th row서울특별시 관악구 남부순환로 1511, 지하1층 (신림동)
5th row서울특별시 관악구 신원로 6-1, 지하1층 (신림동)
ValueCountFrequency (%)
서울특별시 2953
15.6%
관악구 2953
15.6%
1층 1840
 
9.7%
신림동 1506
 
8.0%
봉천동 1308
 
6.9%
남부순환로 346
 
1.8%
지하1층 267
 
1.4%
신림로 198
 
1.0%
관악로 189
 
1.0%
봉천로 167
 
0.9%
Other values (1797) 7205
38.1%
2024-05-11T07:02:58.027003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15979
 
17.3%
1 5402
 
5.9%
3399
 
3.7%
3301
 
3.6%
3161
 
3.4%
, 3138
 
3.4%
3065
 
3.3%
3021
 
3.3%
2984
 
3.2%
2978
 
3.2%
Other values (373) 45701
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52208
56.7%
Space Separator 15979
 
17.3%
Decimal Number 14427
 
15.7%
Other Punctuation 3144
 
3.4%
Close Punctuation 2976
 
3.2%
Open Punctuation 2976
 
3.2%
Dash Punctuation 237
 
0.3%
Uppercase Letter 134
 
0.1%
Math Symbol 33
 
< 0.1%
Lowercase Letter 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3399
 
6.5%
3301
 
6.3%
3161
 
6.1%
3065
 
5.9%
3021
 
5.8%
2984
 
5.7%
2978
 
5.7%
2955
 
5.7%
2954
 
5.7%
2732
 
5.2%
Other values (329) 21658
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 65
48.5%
A 14
 
10.4%
S 8
 
6.0%
T 5
 
3.7%
E 5
 
3.7%
M 5
 
3.7%
C 4
 
3.0%
I 4
 
3.0%
G 4
 
3.0%
L 3
 
2.2%
Other values (10) 17
 
12.7%
Decimal Number
ValueCountFrequency (%)
1 5402
37.4%
2 2030
 
14.1%
3 1319
 
9.1%
0 1159
 
8.0%
4 963
 
6.7%
6 858
 
5.9%
5 788
 
5.5%
7 666
 
4.6%
9 651
 
4.5%
8 591
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
b 7
50.0%
e 4
28.6%
k 1
 
7.1%
s 1
 
7.1%
n 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 3138
99.8%
. 5
 
0.2%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
15979
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2976
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2976
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 237
100.0%
Math Symbol
ValueCountFrequency (%)
~ 33
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52208
56.7%
Common 39772
43.2%
Latin 149
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3399
 
6.5%
3301
 
6.3%
3161
 
6.1%
3065
 
5.9%
3021
 
5.8%
2984
 
5.7%
2978
 
5.7%
2955
 
5.7%
2954
 
5.7%
2732
 
5.2%
Other values (329) 21658
41.5%
Latin
ValueCountFrequency (%)
B 65
43.6%
A 14
 
9.4%
S 8
 
5.4%
b 7
 
4.7%
T 5
 
3.4%
E 5
 
3.4%
M 5
 
3.4%
C 4
 
2.7%
e 4
 
2.7%
I 4
 
2.7%
Other values (16) 28
18.8%
Common
ValueCountFrequency (%)
15979
40.2%
1 5402
 
13.6%
, 3138
 
7.9%
) 2976
 
7.5%
( 2976
 
7.5%
2 2030
 
5.1%
3 1319
 
3.3%
0 1159
 
2.9%
4 963
 
2.4%
6 858
 
2.2%
Other values (8) 2972
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52208
56.7%
ASCII 39920
43.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15979
40.0%
1 5402
 
13.5%
, 3138
 
7.9%
) 2976
 
7.5%
( 2976
 
7.5%
2 2030
 
5.1%
3 1319
 
3.3%
0 1159
 
2.9%
4 963
 
2.4%
6 858
 
2.1%
Other values (33) 3120
 
7.8%
Hangul
ValueCountFrequency (%)
3399
 
6.5%
3301
 
6.3%
3161
 
6.1%
3065
 
5.9%
3021
 
5.8%
2984
 
5.7%
2978
 
5.7%
2955
 
5.7%
2954
 
5.7%
2732
 
5.2%
Other values (329) 21658
41.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct157
Distinct (%)5.3%
Missing1582
Missing (%)35.0%
Infinite0
Infinite (%)0.0%
Mean8779.7866
Minimum8700
Maximum8866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.9 KiB
2024-05-11T07:02:58.664521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8700
5-th percentile8708
Q18750
median8782
Q38812
95-th percentile8852
Maximum8866
Range166
Interquartile range (IQR)62

Descriptive statistics

Standard deviation42.178774
Coefficient of variation (CV)0.0048040773
Kurtosis-0.74153592
Mean8779.7866
Median Absolute Deviation (MAD)31
Skewness0.004100981
Sum25838912
Variance1779.0489
MonotonicityNot monotonic
2024-05-11T07:02:59.189295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8708 94
 
2.1%
8813 92
 
2.0%
8793 86
 
1.9%
8787 79
 
1.7%
8788 72
 
1.6%
8776 67
 
1.5%
8826 66
 
1.5%
8812 57
 
1.3%
8754 55
 
1.2%
8814 55
 
1.2%
Other values (147) 2220
49.1%
(Missing) 1582
35.0%
ValueCountFrequency (%)
8700 10
 
0.2%
8701 23
 
0.5%
8702 22
 
0.5%
8703 3
 
0.1%
8704 10
 
0.2%
8705 19
 
0.4%
8706 12
 
0.3%
8707 23
 
0.5%
8708 94
2.1%
8709 7
 
0.2%
ValueCountFrequency (%)
8866 1
 
< 0.1%
8865 6
 
0.1%
8864 24
0.5%
8863 1
 
< 0.1%
8862 3
 
0.1%
8861 7
 
0.2%
8860 13
0.3%
8859 16
0.4%
8858 14
0.3%
8857 5
 
0.1%
Distinct4141
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
2024-05-11T07:03:00.018121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length29
Mean length7.4377901
Min length1

Characters and Unicode

Total characters33656
Distinct characters901
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3864 ?
Unique (%)85.4%

Sample

1st row소라다방
2nd row새청자
3rd row뉴관악다방
4th row중앙
5th row칠다방
ValueCountFrequency (%)
씨유 122
 
1.9%
gs25 115
 
1.8%
세븐일레븐 103
 
1.6%
신림점 74
 
1.2%
서울대입구역점 48
 
0.8%
카페 41
 
0.7%
coffee 38
 
0.6%
cafe 37
 
0.6%
지에스25 27
 
0.4%
신림역점 27
 
0.4%
Other values (4354) 5666
90.0%
2024-05-11T07:03:01.785026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1780
 
5.3%
1385
 
4.1%
893
 
2.7%
669
 
2.0%
616
 
1.8%
540
 
1.6%
) 527
 
1.6%
( 526
 
1.6%
492
 
1.5%
455
 
1.4%
Other values (891) 25773
76.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25874
76.9%
Lowercase Letter 2012
 
6.0%
Uppercase Letter 1954
 
5.8%
Space Separator 1780
 
5.3%
Decimal Number 818
 
2.4%
Close Punctuation 528
 
1.6%
Open Punctuation 527
 
1.6%
Other Punctuation 141
 
0.4%
Dash Punctuation 20
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1385
 
5.4%
893
 
3.5%
669
 
2.6%
616
 
2.4%
540
 
2.1%
492
 
1.9%
455
 
1.8%
450
 
1.7%
393
 
1.5%
375
 
1.4%
Other values (809) 19606
75.8%
Lowercase Letter
ValueCountFrequency (%)
e 373
18.5%
a 204
10.1%
o 178
 
8.8%
f 177
 
8.8%
c 126
 
6.3%
r 105
 
5.2%
i 104
 
5.2%
n 97
 
4.8%
t 89
 
4.4%
s 89
 
4.4%
Other values (16) 470
23.4%
Uppercase Letter
ValueCountFrequency (%)
C 270
13.8%
S 226
11.6%
G 193
 
9.9%
E 151
 
7.7%
O 117
 
6.0%
F 109
 
5.6%
P 106
 
5.4%
A 98
 
5.0%
U 75
 
3.8%
T 65
 
3.3%
Other values (16) 544
27.8%
Other Punctuation
ValueCountFrequency (%)
. 44
31.2%
& 34
24.1%
' 17
 
12.1%
, 16
 
11.3%
? 8
 
5.7%
# 7
 
5.0%
: 6
 
4.3%
! 4
 
2.8%
/ 2
 
1.4%
; 1
 
0.7%
Other values (2) 2
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 274
33.5%
5 225
27.5%
1 81
 
9.9%
4 63
 
7.7%
3 48
 
5.9%
0 34
 
4.2%
9 25
 
3.1%
6 24
 
2.9%
7 23
 
2.8%
8 21
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 527
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 526
99.8%
[ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1780
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25862
76.8%
Latin 3966
 
11.8%
Common 3816
 
11.3%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1385
 
5.4%
893
 
3.5%
669
 
2.6%
616
 
2.4%
540
 
2.1%
492
 
1.9%
455
 
1.8%
450
 
1.7%
393
 
1.5%
375
 
1.5%
Other values (797) 19594
75.8%
Latin
ValueCountFrequency (%)
e 373
 
9.4%
C 270
 
6.8%
S 226
 
5.7%
a 204
 
5.1%
G 193
 
4.9%
o 178
 
4.5%
f 177
 
4.5%
E 151
 
3.8%
c 126
 
3.2%
O 117
 
3.0%
Other values (42) 1951
49.2%
Common
ValueCountFrequency (%)
1780
46.6%
) 527
 
13.8%
( 526
 
13.8%
2 274
 
7.2%
5 225
 
5.9%
1 81
 
2.1%
4 63
 
1.7%
3 48
 
1.3%
. 44
 
1.2%
& 34
 
0.9%
Other values (20) 214
 
5.6%
Han
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2) 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25862
76.8%
ASCII 7779
 
23.1%
CJK 11
 
< 0.1%
None 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1780
22.9%
) 527
 
6.8%
( 526
 
6.8%
e 373
 
4.8%
2 274
 
3.5%
C 270
 
3.5%
S 226
 
2.9%
5 225
 
2.9%
a 204
 
2.6%
G 193
 
2.5%
Other values (69) 3181
40.9%
Hangul
ValueCountFrequency (%)
1385
 
5.4%
893
 
3.5%
669
 
2.6%
616
 
2.4%
540
 
2.1%
492
 
1.9%
455
 
1.8%
450
 
1.7%
393
 
1.5%
375
 
1.5%
Other values (797) 19594
75.8%
CJK
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%
Distinct3708
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
Minimum1999-01-06 00:00:00
Maximum2024-05-09 17:26:44
2024-05-11T07:03:02.243526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:03:02.829911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
I
3094 
U
1431 

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 3094
68.4%
U 1431
31.6%

Length

2024-05-11T07:03:03.505790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:03.851180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3094
68.4%
u 1431
31.6%
Distinct1145
Distinct (%)25.3%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T07:03:04.283818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:03:04.788578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
커피숍
1372 
일반조리판매
824 
다방
673 
편의점
594 
기타 휴게음식점
377 
Other values (10)
685 

Length

Max length8
Median length3
Mean length3.9637569
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 1372
30.3%
일반조리판매 824
18.2%
다방 673
14.9%
편의점 594
13.1%
기타 휴게음식점 377
 
8.3%
패스트푸드 309
 
6.8%
과자점 308
 
6.8%
아이스크림 19
 
0.4%
백화점 16
 
0.4%
전통찻집 16
 
0.4%
Other values (5) 17
 
0.4%

Length

2024-05-11T07:03:05.314809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1372
28.0%
일반조리판매 824
16.8%
다방 673
13.7%
편의점 594
12.1%
기타 377
 
7.7%
휴게음식점 377
 
7.7%
패스트푸드 309
 
6.3%
과자점 308
 
6.3%
아이스크림 19
 
0.4%
백화점 16
 
0.3%
Other values (6) 33
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2419
Distinct (%)54.5%
Missing87
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean194501.63
Minimum191182
Maximum198793.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.9 KiB
2024-05-11T07:03:05.826674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191182
5-th percentile192261.65
Q1193455.81
median194367.49
Q3195733.49
95-th percentile196981.81
Maximum198793.03
Range7611.0262
Interquartile range (IQR)2277.6768

Descriptive statistics

Standard deviation1537.2646
Coefficient of variation (CV)0.0079036077
Kurtosis-0.41694758
Mean194501.63
Median Absolute Deviation (MAD)1065.601
Skewness0.26208101
Sum8.6319824 × 108
Variance2363182.4
MonotonicityNot monotonic
2024-05-11T07:03:06.487894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193301.885808714 120
 
2.7%
196139.864969792 72
 
1.6%
195703.043681259 40
 
0.9%
193754.427350029 24
 
0.5%
193746.833837509 19
 
0.4%
195759.872774126 14
 
0.3%
198284.078546351 14
 
0.3%
196257.833652996 14
 
0.3%
191334.658955208 13
 
0.3%
193735.829747067 13
 
0.3%
Other values (2409) 4095
90.5%
(Missing) 87
 
1.9%
ValueCountFrequency (%)
191182.000480527 1
< 0.1%
191191.448323925 1
< 0.1%
191204.884621244 1
< 0.1%
191215.176663069 1
< 0.1%
191222.075430617 1
< 0.1%
191224.178786196 1
< 0.1%
191228.411082685 1
< 0.1%
191230.149937176 1
< 0.1%
191234.651997803 1
< 0.1%
191236.170747459 1
< 0.1%
ValueCountFrequency (%)
198793.026677087 1
 
< 0.1%
198449.002171 7
0.2%
198374.473281221 7
0.2%
198351.367148646 1
 
< 0.1%
198288.009848713 1
 
< 0.1%
198287.460384612 3
 
0.1%
198284.487350496 9
0.2%
198284.078546351 14
0.3%
198282.196473514 1
 
< 0.1%
198280.308333613 6
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2420
Distinct (%)54.5%
Missing87
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean441929.26
Minimum439023.17
Maximum443547.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.9 KiB
2024-05-11T07:03:07.074438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile440635.12
Q1441422.55
median442094.09
Q3442510.78
95-th percentile443136.46
Maximum443547.05
Range4523.8826
Interquartile range (IQR)1088.2275

Descriptive statistics

Standard deviation822.93071
Coefficient of variation (CV)0.0018621322
Kurtosis1.0930808
Mean441929.26
Median Absolute Deviation (MAD)535.39571
Skewness-0.88964749
Sum1.9612821 × 109
Variance677214.96
MonotonicityNot monotonic
2024-05-11T07:03:07.660019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443151.561302292 120
 
2.7%
439023.167125842 72
 
1.6%
442094.085759338 40
 
0.9%
442407.201247108 24
 
0.5%
442510.775085572 19
 
0.4%
441941.015435004 14
 
0.3%
443341.379446435 14
 
0.3%
441368.909286824 14
 
0.3%
441993.853241909 13
 
0.3%
442552.922888015 13
 
0.3%
Other values (2410) 4095
90.5%
(Missing) 87
 
1.9%
ValueCountFrequency (%)
439023.167125842 72
1.6%
439787.715563055 3
 
0.1%
439809.669640911 2
 
< 0.1%
439816.999224208 1
 
< 0.1%
439825.822160271 2
 
< 0.1%
439841.501576298 1
 
< 0.1%
439852.868058712 3
 
0.1%
439885.315238411 1
 
< 0.1%
439993.033957335 1
 
< 0.1%
440038.244390558 1
 
< 0.1%
ValueCountFrequency (%)
443547.049696825 8
0.2%
443437.692580028 1
 
< 0.1%
443381.921429128 1
 
< 0.1%
443347.669199144 8
0.2%
443341.379446435 14
0.3%
443336.744163369 2
 
< 0.1%
443332.522660073 1
 
< 0.1%
443325.157422878 1
 
< 0.1%
443322.295671891 1
 
< 0.1%
443318.372247205 2
 
< 0.1%

위생업태명
Categorical

Distinct14
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
1020 
커피숍
882 
다방
667 
일반조리판매
658 
편의점
439 
Other values (9)
859 

Length

Max length8
Median length6
Mean length3.9018785
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1020
22.5%
커피숍 882
19.5%
다방 667
14.7%
일반조리판매 658
14.5%
편의점 439
9.7%
과자점 308
 
6.8%
패스트푸드 271
 
6.0%
기타 휴게음식점 236
 
5.2%
전통찻집 15
 
0.3%
백화점 14
 
0.3%
Other values (4) 15
 
0.3%

Length

2024-05-11T07:03:08.245985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1020
21.4%
커피숍 882
18.5%
다방 667
14.0%
일반조리판매 658
13.8%
편의점 439
9.2%
과자점 308
 
6.5%
패스트푸드 271
 
5.7%
기타 236
 
5.0%
휴게음식점 236
 
5.0%
전통찻집 15
 
0.3%
Other values (5) 29
 
0.6%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.5%
Missing3020
Missing (%)66.7%
Infinite0
Infinite (%)0.0%
Mean0.17209302
Minimum0
Maximum8
Zeros1320
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size39.9 KiB
2024-05-11T07:03:08.627321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.56282668
Coefficient of variation (CV)3.2704794
Kurtosis48.45145
Mean0.17209302
Median Absolute Deviation (MAD)0
Skewness5.5766075
Sum259
Variance0.31677387
MonotonicityNot monotonic
2024-05-11T07:03:09.137912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1320
29.2%
1 137
 
3.0%
2 36
 
0.8%
3 7
 
0.2%
6 2
 
< 0.1%
4 1
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 3020
66.7%
ValueCountFrequency (%)
0 1320
29.2%
1 137
 
3.0%
2 36
 
0.8%
3 7
 
0.2%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
3 7
 
0.2%
2 36
 
0.8%
1 137
 
3.0%
0 1320
29.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.5%
Missing3013
Missing (%)66.6%
Infinite0
Infinite (%)0.0%
Mean0.87367725
Minimum0
Maximum11
Zeros1011
Zeros (%)22.3%
Negative0
Negative (%)0.0%
Memory size39.9 KiB
2024-05-11T07:03:09.635232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4195553
Coefficient of variation (CV)1.6248051
Kurtosis1.7830133
Mean0.87367725
Median Absolute Deviation (MAD)0
Skewness1.4830857
Sum1321
Variance2.0151372
MonotonicityNot monotonic
2024-05-11T07:03:10.084185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1011
 
22.3%
3 187
 
4.1%
1 116
 
2.6%
4 91
 
2.0%
2 87
 
1.9%
5 19
 
0.4%
11 1
 
< 0.1%
(Missing) 3013
66.6%
ValueCountFrequency (%)
0 1011
22.3%
1 116
 
2.6%
2 87
 
1.9%
3 187
 
4.1%
4 91
 
2.0%
5 19
 
0.4%
11 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
5 19
 
0.4%
4 91
 
2.0%
3 187
 
4.1%
2 87
 
1.9%
1 116
 
2.6%
0 1011
22.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
3367 
주택가주변
658 
유흥업소밀집지역
 
245
기타
 
215
아파트지역
 
28
Other values (3)
 
12

Length

Max length8
Median length4
Mean length4.2835359
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3367
74.4%
주택가주변 658
 
14.5%
유흥업소밀집지역 245
 
5.4%
기타 215
 
4.8%
아파트지역 28
 
0.6%
학교정화(상대) 10
 
0.2%
결혼예식장주변 1
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-05-11T07:03:10.683400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:11.435643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3367
74.4%
주택가주변 658
 
14.5%
유흥업소밀집지역 245
 
5.4%
기타 215
 
4.8%
아파트지역 28
 
0.6%
학교정화(상대 10
 
0.2%
결혼예식장주변 1
 
< 0.1%
학교정화(절대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
3421 
기타
828 
지도
 
224
 
40
자율
 
10

Length

Max length4
Median length4
Mean length3.5032044
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3421
75.6%
기타 828
 
18.3%
지도 224
 
5.0%
40
 
0.9%
자율 10
 
0.2%
우수 2
 
< 0.1%

Length

2024-05-11T07:03:11.933883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:12.278259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3421
75.6%
기타 828
 
18.3%
지도 224
 
5.0%
40
 
0.9%
자율 10
 
0.2%
우수 2
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
2347 
상수도전용
2172 
상수도(음용)지하수(주방용)겸용
 
6

Length

Max length17
Median length4
Mean length4.4972376
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2347
51.9%
상수도전용 2172
48.0%
상수도(음용)지하수(주방용)겸용 6
 
0.1%

Length

2024-05-11T07:03:12.749446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:13.041618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2347
51.9%
상수도전용 2172
48.0%
상수도(음용)지하수(주방용)겸용 6
 
0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
4326 
0
 
199

Length

Max length4
Median length4
Mean length3.8680663
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> 4326
95.6%
0 199
 
4.4%

Length

2024-05-11T07:03:13.380634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:13.686037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4326
95.6%
0 199
 
4.4%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
4323 
0
 
202

Length

Max length4
Median length4
Mean length3.8660773
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> 4323
95.5%
0 202
 
4.5%

Length

2024-05-11T07:03:14.048298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:14.763135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4323
95.5%
0 202
 
4.5%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
4323 
0
 
202

Length

Max length4
Median length4
Mean length3.8660773
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> 4323
95.5%
0 202
 
4.5%

Length

2024-05-11T07:03:15.322114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:15.714001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4323
95.5%
0 202
 
4.5%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
4323 
0
 
202

Length

Max length4
Median length4
Mean length3.8660773
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> 4323
95.5%
0 202
 
4.5%

Length

2024-05-11T07:03:16.136560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:16.507059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4323
95.5%
0 202
 
4.5%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
4323 
0
 
202

Length

Max length4
Median length4
Mean length3.8660773
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> 4323
95.5%
0 202
 
4.5%

Length

2024-05-11T07:03:16.889703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:17.234212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4323
95.5%
0 202
 
4.5%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4525
Missing (%)100.0%
Memory size39.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
4323 
0
 
202

Length

Max length4
Median length4
Mean length3.8660773
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> 4323
95.5%
0 202
 
4.5%

Length

2024-05-11T07:03:17.623382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:17.964355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4323
95.5%
0 202
 
4.5%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.5 KiB
<NA>
4323 
0
 
202

Length

Max length4
Median length4
Mean length3.8660773
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> 4323
95.5%
0 202
 
4.5%

Length

2024-05-11T07:03:18.338044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:18.615524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4323
95.5%
0 202
 
4.5%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing1020
Missing (%)22.5%
Memory size9.0 KiB
False
3459 
True
 
46
(Missing)
1020 
ValueCountFrequency (%)
False 3459
76.4%
True 46
 
1.0%
(Missing) 1020
 
22.5%
2024-05-11T07:03:18.851021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct1824
Distinct (%)52.0%
Missing1020
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean46.307104
Minimum0
Maximum1049.88
Zeros36
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size39.9 KiB
2024-05-11T07:03:19.284209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q115.01
median29.77
Q362.22
95-th percentile129.472
Maximum1049.88
Range1049.88
Interquartile range (IQR)47.21

Descriptive statistics

Standard deviation54.873979
Coefficient of variation (CV)1.1850013
Kurtosis65.575916
Mean46.307104
Median Absolute Deviation (MAD)19.77
Skewness5.5073144
Sum162306.4
Variance3011.1536
MonotonicityNot monotonic
2024-05-11T07:03:19.737143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.6 183
 
4.0%
3.3 114
 
2.5%
33.0 68
 
1.5%
26.4 53
 
1.2%
16.5 42
 
0.9%
20.0 40
 
0.9%
6.0 40
 
0.9%
9.9 38
 
0.8%
30.0 37
 
0.8%
0.0 36
 
0.8%
Other values (1814) 2854
63.1%
(Missing) 1020
 
22.5%
ValueCountFrequency (%)
0.0 36
0.8%
0.81 1
 
< 0.1%
1.0 1
 
< 0.1%
1.71 1
 
< 0.1%
1.91 1
 
< 0.1%
2.0 2
 
< 0.1%
2.02 1
 
< 0.1%
2.07 1
 
< 0.1%
2.1 1
 
< 0.1%
2.25 2
 
< 0.1%
ValueCountFrequency (%)
1049.88 1
< 0.1%
969.21 1
< 0.1%
518.0 1
< 0.1%
493.92 2
< 0.1%
474.71 1
< 0.1%
456.92 1
< 0.1%
433.36 1
< 0.1%
410.81 1
< 0.1%
406.77 1
< 0.1%
394.56 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4525
Missing (%)100.0%
Memory size39.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4525
Missing (%)100.0%
Memory size39.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4525
Missing (%)100.0%
Memory size39.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032000003200000-104-1971-0850719710616<NA>3폐업2폐업19930304<NA><NA><NA>02 8774939136.38151803서울특별시 관악구 봉천동 14-52번지<NA><NA>소라다방2001-09-29 00:00:00I2018-08-31 23:59:59.0다방196241.676066442859.33622다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N136.38<NA><NA><NA>
132000003200000-104-1971-0859019710805<NA>3폐업2폐업20010705<NA><NA><NA>0251.83151803서울특별시 관악구 봉천동 14-21번지<NA><NA>새청자2001-09-29 00:00:00I2018-08-31 23:59:59.0다방196247.813759442902.298803다방02주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N51.83<NA><NA><NA>
232000003200000-104-1972-0850119720303<NA>3폐업2폐업19930616<NA><NA><NA>02 8771894198.42151050서울특별시 관악구 봉천동 399-1번지<NA><NA>뉴관악다방2001-09-29 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N198.42<NA><NA><NA>
332000003200000-104-1972-0851019720122<NA>3폐업2폐업19911231<NA><NA><NA>02 8771457129.55151810서울특별시 관악구 봉천동 32-2번지<NA><NA>중앙2001-09-29 00:00:00I2018-08-31 23:59:59.0다방195879.964432442417.634347다방03유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N129.55<NA><NA><NA>
432000003200000-104-1972-0853219720706<NA>3폐업2폐업19930521<NA><NA><NA>02 8785635.00151853서울특별시 관악구 신림동 82-2번지<NA><NA>칠다방2002-01-08 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방04유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532000003200000-104-1972-0857119720807<NA>3폐업2폐업20170313<NA><NA><NA>02 877750497.69151892서울특별시 관악구 신림동 1433-43번지서울특별시 관악구 남부순환로 1607, 지하1층 (신림동)8759길다방2013-08-30 19:35:00I2018-08-31 23:59:59.0다방193672.704403442473.494113다방00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N97.69<NA><NA><NA>
632000003200000-104-1972-0858119720129<NA>3폐업2폐업20070921<NA><NA><NA>020877590647.16151803서울특별시 관악구 봉천동 14-42번지<NA><NA>초원다방2007-07-21 11:35:48I2018-08-31 23:59:59.0다방196257.355289442917.781998다방03주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N47.16<NA><NA><NA>
732000003200000-104-1972-0880119720615<NA>3폐업2폐업20021202<NA><NA><NA>020877132059.10151809서울특별시 관악구 봉천동 62-3번지<NA><NA>응접실커피숍1999-01-22 00:00:00I2018-08-31 23:59:59.0다방195907.768175442331.416801다방04유흥업소밀집지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N59.1<NA><NA><NA>
832000003200000-104-1973-0853619730613<NA>3폐업2폐업19890703<NA><NA><NA>0208779424111.06151856서울특별시 관악구 신림동 131-3번지<NA><NA>신한다방2002-01-08 00:00:00I2018-08-31 23:59:59.0다방194475.762347440984.477341다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N111.06<NA><NA><NA>
932000003200000-104-1974-0885119740715<NA>3폐업2폐업19990402<NA><NA><NA>02129.85151876서울특별시 관악구 신림동 543-22번지<NA><NA>명다방1999-04-02 00:00:00I2018-08-31 23:59:59.0다방192066.160788442150.463347다방03주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N129.85<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
451532000003200000-104-2024-000752024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.00151-891서울특별시 관악구 신림동 1439-15서울특별시 관악구 신림동길 22, 1층 (신림동)8707글라쇼 신림점2024-04-19 17:03:47I2023-12-03 22:01:00.0아이스크림193404.708924442783.524674<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
451632000003200000-104-2024-000762024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00151-848서울특별시 관악구 봉천동 1620-33서울특별시 관악구 관악로14길 103, 1층 (봉천동)8789레인커피 샤로수점2024-04-26 11:37:55I2023-12-03 22:08:00.0커피숍196223.270478441743.150679<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
451732000003200000-104-2024-000772024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.00151-817서울특별시 관악구 봉천동 196-283 준아카데미서울특별시 관악구 낙성대역6길 19, 준아카데미 1층 (봉천동)8799이마트24 낙성대점2024-04-26 13:32:46I2023-12-03 22:08:00.0편의점196578.220845441347.121271<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
451832000003200000-104-2024-000782024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.20151-890서울특별시 관악구 신림동 1421-29 에스케이허브그린서울특별시 관악구 신림로 344, 에스케이허브그린 1층 150호 (신림동)8754구슬구슬 신림점2024-04-29 17:53:34I2023-12-05 00:01:00.0아이스크림193735.829747442552.922888<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
451932000003200000-104-2024-000792024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.00151-858서울특별시 관악구 신림동 231-20서울특별시 관악구 신림로3가길 42, 지하1층 (신림동)8815구동커피2024-05-02 13:55:39I2023-12-05 00:04:00.0커피숍194828.121559440759.120542<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
452032000003200000-104-2024-000802024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>52.20151-841서울특별시 관악구 봉천동 894-16서울특별시 관악구 청룡길 9, 1층 (봉천동)8786요거트아이스크림의정석 봉천점2024-05-03 14:10:37I2023-12-05 00:05:00.0아이스크림195190.792924442139.987786<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
452132000003200000-104-2024-000812024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00151-848서울특별시 관악구 봉천동 1621-9 번영빌딩서울특별시 관악구 관악로14길 88, 번영빌딩 지하1층 (봉천동)8789글라쇼 서울대점2024-05-03 15:22:01I2023-12-05 00:05:00.0아이스크림196145.691539441763.010987<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
452232000003200000-104-2024-000822024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>48.82151-900서울특별시 관악구 신림동 1636-61 남영빌딩서울특별시 관악구 신원로 10, 남영빌딩 2층 (신림동)8775데이굿(DAY GOOD)2024-05-03 17:31:40I2023-12-05 00:05:00.0커피숍193568.725509442015.34406<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
452332000003200000-104-2024-000832024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>11.90151-904서울특별시 관악구 신림동 1668 관악농협 농산물백화점서울특별시 관악구 남부순환로 1369, 관악농협 농산물백화점 지하1층 (신림동)8768수협 바다마트 관악직매장 수산코너2024-05-08 14:24:35I2023-12-04 23:00:00.0기타 휴게음식점191334.658955441993.853242<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
452432000003200000-104-2024-000842024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>66.40151-718서울특별시 관악구 봉천동 729-22 롯데백화점서울특별시 관악구 봉천로 209, 롯데백화점 지하2층 (봉천동)8708카페차이 롯데백화점 관악점2024-05-08 15:20:24I2023-12-04 23:00:00.0커피숍193301.885809443151.561302<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>