Overview

Dataset statistics

Number of variables44
Number of observations467
Missing cells4671
Missing cells (%)22.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory172.1 KiB
Average record size in memory377.3 B

Variable types

Categorical20
Text6
DateTime4
Unsupported8
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-18422/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
남성종사자수 is highly imbalanced (52.9%)Imbalance
영업장주변구분명 is highly imbalanced (60.1%)Imbalance
등급구분명 is highly imbalanced (57.0%)Imbalance
총인원 is highly imbalanced (72.6%)Imbalance
본사종업원수 is highly imbalanced (72.6%)Imbalance
공장사무직종업원수 is highly imbalanced (72.6%)Imbalance
공장판매직종업원수 is highly imbalanced (72.6%)Imbalance
공장생산직종업원수 is highly imbalanced (72.6%)Imbalance
보증액 is highly imbalanced (72.6%)Imbalance
월세액 is highly imbalanced (72.6%)Imbalance
다중이용업소여부 is highly imbalanced (97.3%)Imbalance
인허가취소일자 has 467 (100.0%) missing valuesMissing
폐업일자 has 138 (29.6%) missing valuesMissing
휴업시작일자 has 467 (100.0%) missing valuesMissing
휴업종료일자 has 467 (100.0%) missing valuesMissing
재개업일자 has 467 (100.0%) missing valuesMissing
전화번호 has 253 (54.2%) missing valuesMissing
도로명주소 has 165 (35.3%) missing valuesMissing
도로명우편번호 has 167 (35.8%) missing valuesMissing
좌표정보(X) has 7 (1.5%) missing valuesMissing
좌표정보(Y) has 7 (1.5%) missing valuesMissing
건물소유구분명 has 467 (100.0%) missing valuesMissing
다중이용업소여부 has 97 (20.8%) missing valuesMissing
시설총규모 has 97 (20.8%) missing valuesMissing
전통업소지정번호 has 467 (100.0%) missing valuesMissing
전통업소주된음식 has 467 (100.0%) missing valuesMissing
홈페이지 has 467 (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
시설총규모 has 5 (1.1%) zerosZeros

Reproduction

Analysis started2024-05-11 05:51:18.235779
Analysis finished2024-05-11 05:51:20.374386
Duration2.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3200000
467 

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 467
100.0%

Length

2024-05-11T05:51:20.577387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:20.897127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 467
100.0%

관리번호
Text

UNIQUE 

Distinct467
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T05:51:21.458717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10274
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

Unique467 ?
Unique (%)100.0%

Sample

1st row3200000-121-1978-08225
2nd row3200000-121-1978-08379
3rd row3200000-121-1979-08283
4th row3200000-121-1980-08328
5th row3200000-121-1980-08348
ValueCountFrequency (%)
3200000-121-1978-08225 1
 
0.2%
3200000-121-2015-00012 1
 
0.2%
3200000-121-2016-00010 1
 
0.2%
3200000-121-2016-00009 1
 
0.2%
3200000-121-2016-00008 1
 
0.2%
3200000-121-2016-00007 1
 
0.2%
3200000-121-2016-00006 1
 
0.2%
3200000-121-2016-00005 1
 
0.2%
3200000-121-2016-00004 1
 
0.2%
3200000-121-2016-00003 1
 
0.2%
Other values (457) 457
97.9%
2024-05-11T05:51:22.798317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4348
42.3%
2 1577
 
15.3%
1 1475
 
14.4%
- 1401
 
13.6%
3 608
 
5.9%
9 244
 
2.4%
8 174
 
1.7%
4 152
 
1.5%
7 100
 
1.0%
6 98
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8873
86.4%
Dash Punctuation 1401
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4348
49.0%
2 1577
 
17.8%
1 1475
 
16.6%
3 608
 
6.9%
9 244
 
2.7%
8 174
 
2.0%
4 152
 
1.7%
7 100
 
1.1%
6 98
 
1.1%
5 97
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1401
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10274
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4348
42.3%
2 1577
 
15.3%
1 1475
 
14.4%
- 1401
 
13.6%
3 608
 
5.9%
9 244
 
2.4%
8 174
 
1.7%
4 152
 
1.5%
7 100
 
1.0%
6 98
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10274
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4348
42.3%
2 1577
 
15.3%
1 1475
 
14.4%
- 1401
 
13.6%
3 608
 
5.9%
9 244
 
2.4%
8 174
 
1.7%
4 152
 
1.5%
7 100
 
1.0%
6 98
 
1.0%

인허가일자
Date

Distinct449
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1978-02-18 00:00:00
Maximum2024-04-04 00:00:00
2024-05-11T05:51:23.463782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:51:24.038965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3
329 
1
138 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row1
5th row3

Common Values

ValueCountFrequency (%)
3 329
70.4%
1 138
29.6%

Length

2024-05-11T05:51:24.702996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:25.107774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 329
70.4%
1 138
29.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
329 
영업/정상
138 

Length

Max length5
Median length2
Mean length2.8865096
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row폐업
4th row영업/정상
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 329
70.4%
영업/정상 138
29.6%

Length

2024-05-11T05:51:25.638567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:26.034739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 329
70.4%
영업/정상 138
29.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2
329 
1
138 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 329
70.4%
1 138
29.6%

Length

2024-05-11T05:51:26.360449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:26.634517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 329
70.4%
1 138
29.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
329 
영업
138 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 329
70.4%
영업 138
29.6%

Length

2024-05-11T05:51:26.927339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:27.294983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 329
70.4%
영업 138
29.6%

폐업일자
Date

MISSING 

Distinct296
Distinct (%)90.0%
Missing138
Missing (%)29.6%
Memory size3.8 KiB
Minimum2005-05-13 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T05:51:27.681429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:51:28.173120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

전화번호
Text

MISSING 

Distinct206
Distinct (%)96.3%
Missing253
Missing (%)54.2%
Memory size3.8 KiB
2024-05-11T05:51:29.098870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.443925
Min length2

Characters and Unicode

Total characters2235
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

Unique200 ?
Unique (%)93.5%

Sample

1st row0208773793
2nd row02 8624775
3rd row02 8550987
4th row02 8775297
5th row02 8547444
ValueCountFrequency (%)
02 192
41.6%
070 5
 
1.1%
872 5
 
1.1%
883 5
 
1.1%
873 3
 
0.6%
876 3
 
0.6%
5259 3
 
0.6%
878 3
 
0.6%
862 2
 
0.4%
886 2
 
0.4%
Other values (227) 239
51.7%
2024-05-11T05:51:30.598825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 374
16.7%
8 371
16.6%
2 327
14.6%
316
14.1%
7 186
8.3%
5 145
 
6.5%
3 126
 
5.6%
6 114
 
5.1%
4 94
 
4.2%
9 92
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1919
85.9%
Space Separator 316
 
14.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 374
19.5%
8 371
19.3%
2 327
17.0%
7 186
9.7%
5 145
 
7.6%
3 126
 
6.6%
6 114
 
5.9%
4 94
 
4.9%
9 92
 
4.8%
1 90
 
4.7%
Space Separator
ValueCountFrequency (%)
316
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2235
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 374
16.7%
8 371
16.6%
2 327
14.6%
316
14.1%
7 186
8.3%
5 145
 
6.5%
3 126
 
5.6%
6 114
 
5.1%
4 94
 
4.2%
9 92
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2235
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 374
16.7%
8 371
16.6%
2 327
14.6%
316
14.1%
7 186
8.3%
5 145
 
6.5%
3 126
 
5.6%
6 114
 
5.1%
4 94
 
4.2%
9 92
 
4.1%

소재지면적
Real number (ℝ)

Distinct319
Distinct (%)68.9%
Missing4
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean45.181317
Minimum0
Maximum388.65
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T05:51:31.077247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.569
Q124
median33
Q355.98
95-th percentile100.43
Maximum388.65
Range388.65
Interquartile range (IQR)31.98

Descriptive statistics

Standard deviation41.189793
Coefficient of variation (CV)0.91165542
Kurtosis21.5793
Mean45.181317
Median Absolute Deviation (MAD)12.5
Skewness3.8843717
Sum20918.95
Variance1696.5991
MonotonicityNot monotonic
2024-05-11T05:51:31.555251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 15
 
3.2%
33.0 12
 
2.6%
23.1 8
 
1.7%
26.4 8
 
1.7%
26.0 7
 
1.5%
66.0 7
 
1.5%
16.5 5
 
1.1%
20.0 5
 
1.1%
21.0 5
 
1.1%
27.0 5
 
1.1%
Other values (309) 386
82.7%
ValueCountFrequency (%)
0.0 1
 
0.2%
3.0 2
0.4%
3.75 1
 
0.2%
4.0 2
0.4%
6.15 1
 
0.2%
6.6 4
0.9%
7.0 1
 
0.2%
7.75 1
 
0.2%
8.0 1
 
0.2%
9.0 2
0.4%
ValueCountFrequency (%)
388.65 1
0.2%
313.2 1
0.2%
311.23 1
0.2%
261.93 1
0.2%
250.1 1
0.2%
214.5 1
0.2%
209.58 1
0.2%
203.7 1
0.2%
203.6 1
0.2%
184.05 1
0.2%

소재지우편번호
Text

Distinct128
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T05:51:32.176103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.130621
Min length6

Characters and Unicode

Total characters2863
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

Unique49 ?
Unique (%)10.5%

Sample

1st row151867
2nd row151881
3rd row151883
4th row151854
5th row151888
ValueCountFrequency (%)
151015 19
 
4.1%
151050 17
 
3.6%
151830 16
 
3.4%
151930 15
 
3.2%
151800 15
 
3.2%
151895 14
 
3.0%
151843 12
 
2.6%
151832 12
 
2.6%
151810 11
 
2.4%
151858 9
 
1.9%
Other values (118) 327
70.0%
2024-05-11T05:51:33.200008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1033
36.1%
5 558
19.5%
8 434
15.2%
0 228
 
8.0%
9 145
 
5.1%
3 137
 
4.8%
4 92
 
3.2%
2 65
 
2.3%
- 61
 
2.1%
7 60
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2802
97.9%
Dash Punctuation 61
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1033
36.9%
5 558
19.9%
8 434
15.5%
0 228
 
8.1%
9 145
 
5.2%
3 137
 
4.9%
4 92
 
3.3%
2 65
 
2.3%
7 60
 
2.1%
6 50
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2863
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1033
36.1%
5 558
19.5%
8 434
15.2%
0 228
 
8.0%
9 145
 
5.1%
3 137
 
4.8%
4 92
 
3.2%
2 65
 
2.3%
- 61
 
2.1%
7 60
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2863
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1033
36.1%
5 558
19.5%
8 434
15.2%
0 228
 
8.0%
9 145
 
5.1%
3 137
 
4.8%
4 92
 
3.2%
2 65
 
2.3%
- 61
 
2.1%
7 60
 
2.1%

지번주소
Text

Distinct447
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T05:51:33.952940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length24.593148
Min length17

Characters and Unicode

Total characters11485
Distinct characters148
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique429 ?
Unique (%)91.9%

Sample

1st row서울특별시 관악구 신림동 409-84번지
2nd row서울특별시 관악구 신림동 706-22번지
3rd row서울특별시 관악구 신림동 637-14번지
4th row서울특별시 관악구 신림동 94-296
5th row서울특별시 관악구 신림동 587-46번지
ValueCountFrequency (%)
서울특별시 467
22.4%
관악구 467
22.4%
신림동 233
11.2%
봉천동 210
 
10.1%
지상1층 78
 
3.7%
남현동 24
 
1.1%
지하1층 8
 
0.4%
1층 8
 
0.4%
산 7
 
0.3%
729-22번지 5
 
0.2%
Other values (520) 581
27.8%
2024-05-11T05:51:35.467931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1991
 
17.3%
1 660
 
5.7%
동 478
 
4.2%
서 473
 
4.1%
울 473
 
4.1%
관 472
 
4.1%
악 471
 
4.1%
시 469
 
4.1%
특 467
 
4.1%
별 467
 
4.1%
Other values (138) 5064
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6514
56.7%
Decimal Number 2503
 
21.8%
Space Separator 1991
 
17.3%
Dash Punctuation 443
 
3.9%
Other Punctuation 15
 
0.1%
Lowercase Letter 6
 
0.1%
Uppercase Letter 5
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 478
 
7.3%
서 473
 
7.3%
울 473
 
7.3%
관 472
 
7.2%
악 471
 
7.2%
시 469
 
7.2%
특 467
 
7.2%
별 467
 
7.2%
구 467
 
7.2%
지 430
 
6.6%
Other values (113) 1847
28.4%
Decimal Number
ValueCountFrequency (%)
1 660
26.4%
6 267
10.7%
2 259
 
10.3%
3 214
 
8.5%
5 213
 
8.5%
4 208
 
8.3%
0 183
 
7.3%
7 172
 
6.9%
8 166
 
6.6%
9 161
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
d 2
33.3%
t 1
16.7%
a 1
16.7%
o 1
16.7%
l 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 12
80.0%
@ 2
 
13.3%
. 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
I 2
40.0%
S 1
20.0%
Space Separator
ValueCountFrequency (%)
1991
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 443
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6514
56.7%
Common 4960
43.2%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 478
 
7.3%
서 473
 
7.3%
울 473
 
7.3%
관 472
 
7.2%
악 471
 
7.2%
시 469
 
7.2%
특 467
 
7.2%
별 467
 
7.2%
구 467
 
7.2%
지 430
 
6.6%
Other values (113) 1847
28.4%
Common
ValueCountFrequency (%)
1991
40.1%
1 660
 
13.3%
- 443
 
8.9%
6 267
 
5.4%
2 259
 
5.2%
3 214
 
4.3%
5 213
 
4.3%
4 208
 
4.2%
0 183
 
3.7%
7 172
 
3.5%
Other values (7) 350
 
7.1%
Latin
ValueCountFrequency (%)
d 2
18.2%
B 2
18.2%
I 2
18.2%
t 1
9.1%
a 1
9.1%
o 1
9.1%
l 1
9.1%
S 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6514
56.7%
ASCII 4971
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1991
40.1%
1 660
 
13.3%
- 443
 
8.9%
6 267
 
5.4%
2 259
 
5.2%
3 214
 
4.3%
5 213
 
4.3%
4 208
 
4.2%
0 183
 
3.7%
7 172
 
3.5%
Other values (15) 361
 
7.3%
Hangul
ValueCountFrequency (%)
동 478
 
7.3%
서 473
 
7.3%
울 473
 
7.3%
관 472
 
7.2%
악 471
 
7.2%
시 469
 
7.2%
특 467
 
7.2%
별 467
 
7.2%
구 467
 
7.2%
지 430
 
6.6%
Other values (113) 1847
28.4%

도로명주소
Text

MISSING 

Distinct292
Distinct (%)96.7%
Missing165
Missing (%)35.3%
Memory size3.8 KiB
2024-05-11T05:51:36.084585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length48
Mean length31.142384
Min length21

Characters and Unicode

Total characters9405
Distinct characters194
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)94.0%

Sample

1st row서울특별시 관악구 신림로 259 (신림동)
2nd row서울특별시 관악구 서림길 3 (신림동)
3rd row서울특별시 관악구 남부순환로 1677 (봉천동)
4th row서울특별시 관악구 남부순환로 2060, 1층 (남현동)
5th row서울특별시 관악구 국회단지길 10 (봉천동)
ValueCountFrequency (%)
서울특별시 302
 
15.8%
관악구 302
 
15.8%
1층 184
 
9.6%
신림동 130
 
6.8%
봉천동 129
 
6.7%
남부순환로 31
 
1.6%
난곡로 21
 
1.1%
봉천로 17
 
0.9%
남현동 16
 
0.8%
신림로 16
 
0.8%
Other values (434) 765
40.0%
2024-05-11T05:51:37.460297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1613
 
17.2%
1 544
 
5.8%
관 342
 
3.6%
악 332
 
3.5%
동 328
 
3.5%
서 309
 
3.3%
울 308
 
3.3%
시 306
 
3.3%
, 306
 
3.3%
( 305
 
3.2%
Other values (184) 4712
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5358
57.0%
Space Separator 1613
 
17.2%
Decimal Number 1462
 
15.5%
Other Punctuation 307
 
3.3%
Open Punctuation 305
 
3.2%
Close Punctuation 305
 
3.2%
Dash Punctuation 32
 
0.3%
Uppercase Letter 17
 
0.2%
Lowercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 342
 
6.4%
악 332
 
6.2%
동 328
 
6.1%
서 309
 
5.8%
울 308
 
5.7%
시 306
 
5.7%
구 304
 
5.7%
별 302
 
5.6%
특 302
 
5.6%
로 260
 
4.9%
Other values (157) 2265
42.3%
Decimal Number
ValueCountFrequency (%)
1 544
37.2%
2 200
 
13.7%
0 133
 
9.1%
3 131
 
9.0%
4 103
 
7.0%
6 92
 
6.3%
9 76
 
5.2%
7 68
 
4.7%
5 68
 
4.7%
8 47
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 10
58.8%
S 2
 
11.8%
A 2
 
11.8%
E 1
 
5.9%
I 1
 
5.9%
G 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
d 2
33.3%
t 1
16.7%
a 1
16.7%
o 1
16.7%
l 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 306
99.7%
. 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1613
100.0%
Open Punctuation
ValueCountFrequency (%)
( 305
100.0%
Close Punctuation
ValueCountFrequency (%)
) 305
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5358
57.0%
Common 4024
42.8%
Latin 23
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 342
 
6.4%
악 332
 
6.2%
동 328
 
6.1%
서 309
 
5.8%
울 308
 
5.7%
시 306
 
5.7%
구 304
 
5.7%
별 302
 
5.6%
특 302
 
5.6%
로 260
 
4.9%
Other values (157) 2265
42.3%
Common
ValueCountFrequency (%)
1613
40.1%
1 544
 
13.5%
, 306
 
7.6%
( 305
 
7.6%
) 305
 
7.6%
2 200
 
5.0%
0 133
 
3.3%
3 131
 
3.3%
4 103
 
2.6%
6 92
 
2.3%
Other values (6) 292
 
7.3%
Latin
ValueCountFrequency (%)
B 10
43.5%
S 2
 
8.7%
A 2
 
8.7%
d 2
 
8.7%
E 1
 
4.3%
I 1
 
4.3%
t 1
 
4.3%
a 1
 
4.3%
o 1
 
4.3%
l 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5358
57.0%
ASCII 4047
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1613
39.9%
1 544
 
13.4%
, 306
 
7.6%
( 305
 
7.5%
) 305
 
7.5%
2 200
 
4.9%
0 133
 
3.3%
3 131
 
3.2%
4 103
 
2.5%
6 92
 
2.3%
Other values (17) 315
 
7.8%
Hangul
ValueCountFrequency (%)
관 342
 
6.4%
악 332
 
6.2%
동 328
 
6.1%
서 309
 
5.8%
울 308
 
5.7%
시 306
 
5.7%
구 304
 
5.7%
별 302
 
5.6%
특 302
 
5.6%
로 260
 
4.9%
Other values (157) 2265
42.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)35.3%
Missing167
Missing (%)35.8%
Infinite0
Infinite (%)0.0%
Mean8776.28
Minimum8700
Maximum8864
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T05:51:37.995141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8700
5-th percentile8708
Q18745
median8774.5
Q38806.25
95-th percentile8856.05
Maximum8864
Range164
Interquartile range (IQR)61.25

Descriptive statistics

Standard deviation43.123548
Coefficient of variation (CV)0.0049136477
Kurtosis-0.60829945
Mean8776.28
Median Absolute Deviation (MAD)30.5
Skewness0.27791811
Sum2632884
Variance1859.6404
MonotonicityNot monotonic
2024-05-11T05:51:38.610682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8793 10
 
2.1%
8776 9
 
1.9%
8814 8
 
1.7%
8785 7
 
1.5%
8774 7
 
1.5%
8750 7
 
1.5%
8864 6
 
1.3%
8787 6
 
1.3%
8737 6
 
1.3%
8708 6
 
1.3%
Other values (96) 228
48.8%
(Missing) 167
35.8%
ValueCountFrequency (%)
8700 2
 
0.4%
8701 2
 
0.4%
8702 4
0.9%
8705 1
 
0.2%
8706 2
 
0.4%
8707 3
0.6%
8708 6
1.3%
8709 1
 
0.2%
8710 1
 
0.2%
8711 2
 
0.4%
ValueCountFrequency (%)
8864 6
1.3%
8861 4
0.9%
8860 2
 
0.4%
8859 1
 
0.2%
8858 1
 
0.2%
8857 1
 
0.2%
8856 2
 
0.4%
8855 4
0.9%
8854 2
 
0.4%
8852 2
 
0.4%

사업장명
Text

Distinct408
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T05:51:39.296194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length8.0342612
Min length2

Characters and Unicode

Total characters3752
Distinct characters435
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique372 ?
Unique (%)79.7%

Sample

1st row신라베이커리
2nd row고려제과
3rd row불란서빵집
4th row고려제과
5th row부산뉴욕과자점
ValueCountFrequency (%)
파리바게뜨 30
 
4.7%
베이커리 14
 
2.2%
뚜레쥬르 12
 
1.9%
던킨도너츠 9
 
1.4%
파리바게트 9
 
1.4%
신림역점 6
 
0.9%
빵굼터 6
 
0.9%
관악점 5
 
0.8%
베이커리(bakery 4
 
0.6%
카페 4
 
0.6%
Other values (465) 539
84.5%
2024-05-11T05:51:40.614250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
172
 
4.6%
리 167
 
4.5%
점 140
 
3.7%
이 139
 
3.7%
베 85
 
2.3%
커 81
 
2.2%
빵 71
 
1.9%
( 64
 
1.7%
) 64
 
1.7%
바 62
 
1.7%
Other values (425) 2707
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2949
78.6%
Lowercase Letter 251
 
6.7%
Uppercase Letter 198
 
5.3%
Space Separator 172
 
4.6%
Open Punctuation 64
 
1.7%
Close Punctuation 64
 
1.7%
Decimal Number 35
 
0.9%
Other Punctuation 15
 
0.4%
Dash Punctuation 2
 
0.1%
Connector Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 167
 
5.7%
점 140
 
4.7%
이 139
 
4.7%
베 85
 
2.9%
커 81
 
2.7%
빵 71
 
2.4%
바 62
 
2.1%
게 58
 
2.0%
파 57
 
1.9%
스 55
 
1.9%
Other values (356) 2034
69.0%
Lowercase Letter
ValueCountFrequency (%)
e 48
19.1%
a 30
12.0%
n 18
 
7.2%
r 17
 
6.8%
t 14
 
5.6%
o 14
 
5.6%
d 13
 
5.2%
i 13
 
5.2%
s 12
 
4.8%
u 10
 
4.0%
Other values (14) 62
24.7%
Uppercase Letter
ValueCountFrequency (%)
E 22
 
11.1%
B 21
 
10.6%
A 21
 
10.6%
G 14
 
7.1%
O 12
 
6.1%
T 12
 
6.1%
S 11
 
5.6%
N 10
 
5.1%
C 9
 
4.5%
D 9
 
4.5%
Other values (13) 57
28.8%
Decimal Number
ValueCountFrequency (%)
2 8
22.9%
7 7
20.0%
4 6
17.1%
1 5
14.3%
0 2
 
5.7%
5 2
 
5.7%
9 2
 
5.7%
6 1
 
2.9%
8 1
 
2.9%
3 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
? 5
33.3%
. 3
20.0%
, 3
20.0%
' 1
 
6.7%
: 1
 
6.7%
! 1
 
6.7%
& 1
 
6.7%
Space Separator
ValueCountFrequency (%)
172
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2949
78.6%
Latin 449
 
12.0%
Common 354
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 167
 
5.7%
점 140
 
4.7%
이 139
 
4.7%
베 85
 
2.9%
커 81
 
2.7%
빵 71
 
2.4%
바 62
 
2.1%
게 58
 
2.0%
파 57
 
1.9%
스 55
 
1.9%
Other values (356) 2034
69.0%
Latin
ValueCountFrequency (%)
e 48
 
10.7%
a 30
 
6.7%
E 22
 
4.9%
B 21
 
4.7%
A 21
 
4.7%
n 18
 
4.0%
r 17
 
3.8%
t 14
 
3.1%
G 14
 
3.1%
o 14
 
3.1%
Other values (37) 230
51.2%
Common
ValueCountFrequency (%)
172
48.6%
( 64
 
18.1%
) 64
 
18.1%
2 8
 
2.3%
7 7
 
2.0%
4 6
 
1.7%
? 5
 
1.4%
1 5
 
1.4%
. 3
 
0.8%
, 3
 
0.8%
Other values (12) 17
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2949
78.6%
ASCII 803
 
21.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
172
21.4%
( 64
 
8.0%
) 64
 
8.0%
e 48
 
6.0%
a 30
 
3.7%
E 22
 
2.7%
B 21
 
2.6%
A 21
 
2.6%
n 18
 
2.2%
r 17
 
2.1%
Other values (59) 326
40.6%
Hangul
ValueCountFrequency (%)
리 167
 
5.7%
점 140
 
4.7%
이 139
 
4.7%
베 85
 
2.9%
커 81
 
2.7%
빵 71
 
2.4%
바 62
 
2.1%
게 58
 
2.0%
파 57
 
1.9%
스 55
 
1.9%
Other values (356) 2034
69.0%

최종수정일자
Date

Distinct439
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1999-03-25 00:00:00
Maximum2024-05-08 15:13:16
2024-05-11T05:51:41.052025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:51:41.613449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
I
321 
U
146 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 321
68.7%
U 146
31.3%

Length

2024-05-11T05:51:42.165647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:42.780637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 321
68.7%
u 146
31.3%

데이터갱신일자
Date

Distinct180
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:00:00
2024-05-11T05:51:43.236645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:51:43.991754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
제과점영업
467 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 467
100.0%

Length

2024-05-11T05:51:44.717239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:45.027304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 467
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct387
Distinct (%)84.1%
Missing7
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean194444.44
Minimum191206.52
Maximum198374.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T05:51:45.459193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191206.52
5-th percentile192011.33
Q1193301.89
median194280.77
Q3195787.61
95-th percentile197854.81
Maximum198374.47
Range7167.955
Interquartile range (IQR)2485.7221

Descriptive statistics

Standard deviation1679.9037
Coefficient of variation (CV)0.0086395049
Kurtosis-0.50299139
Mean194444.44
Median Absolute Deviation (MAD)1300.8569
Skewness0.33802547
Sum89444440
Variance2822076.3
MonotonicityNot monotonic
2024-05-11T05:51:46.009461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193301.885808714 7
 
1.5%
198374.473281221 5
 
1.1%
196139.864969792 4
 
0.9%
193957.944323928 4
 
0.9%
192423.122921904 3
 
0.6%
198284.078546351 3
 
0.6%
191334.658955208 3
 
0.6%
192555.79904986 3
 
0.6%
193671.349359142 3
 
0.6%
192597.407974484 3
 
0.6%
Other values (377) 422
90.4%
(Missing) 7
 
1.5%
ValueCountFrequency (%)
191206.518253355 1
 
0.2%
191234.651997803 1
 
0.2%
191237.262245059 1
 
0.2%
191303.792863813 2
0.4%
191334.658955208 3
0.6%
191342.399599631 1
 
0.2%
191376.602183978 1
 
0.2%
191470.252115075 1
 
0.2%
191470.702188116 1
 
0.2%
191517.456209359 1
 
0.2%
ValueCountFrequency (%)
198374.473281221 5
1.1%
198315.174254041 1
 
0.2%
198287.460384612 1
 
0.2%
198284.078546351 3
0.6%
198278.931088754 1
 
0.2%
198278.438025281 2
 
0.4%
198275.013917658 1
 
0.2%
198274.871752809 1
 
0.2%
198273.961198619 1
 
0.2%
198081.693933879 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct387
Distinct (%)84.1%
Missing7
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean442026.88
Minimum439023.17
Maximum443547.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T05:51:46.623389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile440719.12
Q1441509.12
median442222.05
Q3442596.82
95-th percentile443086.57
Maximum443547.05
Range4523.8826
Interquartile range (IQR)1087.6972

Descriptive statistics

Standard deviation787.96327
Coefficient of variation (CV)0.0017826139
Kurtosis1.2194489
Mean442026.88
Median Absolute Deviation (MAD)473.85297
Skewness-0.98965566
Sum2.0333236 × 108
Variance620886.11
MonotonicityNot monotonic
2024-05-11T05:51:47.075931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443151.561302292 7
 
1.5%
441033.513044892 5
 
1.1%
439023.167125842 4
 
0.9%
441437.774867372 4
 
0.9%
441447.827793802 3
 
0.6%
441368.909286824 3
 
0.6%
441993.853241909 3
 
0.6%
442726.678503845 3
 
0.6%
442039.985895904 3
 
0.6%
442498.617590296 3
 
0.6%
Other values (377) 422
90.4%
(Missing) 7
 
1.5%
ValueCountFrequency (%)
439023.167125842 4
0.9%
439816.999224208 1
 
0.2%
439825.822160271 1
 
0.2%
439852.868058712 2
0.4%
439853.488919065 1
 
0.2%
439885.315238411 1
 
0.2%
439931.980156728 1
 
0.2%
440081.520243952 1
 
0.2%
440106.431628897 1
 
0.2%
440200.203716349 1
 
0.2%
ValueCountFrequency (%)
443547.049696825 1
 
0.2%
443362.75555511 1
 
0.2%
443341.379446435 2
 
0.4%
443281.298598318 1
 
0.2%
443220.681393636 1
 
0.2%
443166.848549728 1
 
0.2%
443151.561302292 7
1.5%
443149.499388188 1
 
0.2%
443107.755379371 1
 
0.2%
443103.324505043 2
 
0.4%

위생업태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
제과점영업
370 
<NA>
97 

Length

Max length5
Median length5
Mean length4.7922912
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 370
79.2%
<NA> 97
 
20.8%

Length

2024-05-11T05:51:47.702528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:48.043148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 370
79.2%
na 97
 
20.8%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
287 
0
160 
1
 
13
2
 
4
3
 
2

Length

Max length4
Median length4
Mean length2.8436831
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row1
3rd row2
4th row<NA>
5th row2

Common Values

ValueCountFrequency (%)
<NA> 287
61.5%
0 160
34.3%
1 13
 
2.8%
2 4
 
0.9%
3 2
 
0.4%
4 1
 
0.2%

Length

2024-05-11T05:51:48.532434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:48.866188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 287
61.5%
0 160
34.3%
1 13
 
2.8%
2 4
 
0.9%
3 2
 
0.4%
4 1
 
0.2%

여성종사자수
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
287 
0
158 
1
 
17
2
 
5

Length

Max length4
Median length4
Mean length2.8436831
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 287
61.5%
0 158
33.8%
1 17
 
3.6%
2 5
 
1.1%

Length

2024-05-11T05:51:49.213178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:49.552582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 287
61.5%
0 158
33.8%
1 17
 
3.6%
2 5
 
1.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
365 
주택가주변
57 
기타
 
28
유흥업소밀집지역
 
9
아파트지역
 
6
Other values (2)
 
2

Length

Max length8
Median length4
Mean length4.1070664
Min length2

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 365
78.2%
주택가주변 57
 
12.2%
기타 28
 
6.0%
유흥업소밀집지역 9
 
1.9%
아파트지역 6
 
1.3%
학교정화(상대) 1
 
0.2%
결혼예식장주변 1
 
0.2%

Length

2024-05-11T05:51:49.945044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:50.305959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 365
78.2%
주택가주변 57
 
12.2%
기타 28
 
6.0%
유흥업소밀집지역 9
 
1.9%
아파트지역 6
 
1.3%
학교정화(상대 1
 
0.2%
결혼예식장주변 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
378 
기타
73 
지도
 
12
자율
 
4

Length

Max length4
Median length4
Mean length3.6188437
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 378
80.9%
기타 73
 
15.6%
지도 12
 
2.6%
자율 4
 
0.9%

Length

2024-05-11T05:51:50.832214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:51.163046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 378
80.9%
기타 73
 
15.6%
지도 12
 
2.6%
자율 4
 
0.9%

급수시설구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
282 
상수도전용
183 
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length4
Mean length4.4475375
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 282
60.4%
상수도전용 183
39.2%
상수도(음용)지하수(주방용)겸용 2
 
0.4%

Length

2024-05-11T05:51:51.529858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:51.863901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 282
60.4%
상수도전용 183
39.2%
상수도(음용)지하수(주방용)겸용 2
 
0.4%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
445 
0
 
22

Length

Max length4
Median length4
Mean length3.8586724
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> 445
95.3%
0 22
 
4.7%

Length

2024-05-11T05:51:52.276045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:52.637956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 445
95.3%
0 22
 
4.7%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
445 
0
 
22

Length

Max length4
Median length4
Mean length3.8586724
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> 445
95.3%
0 22
 
4.7%

Length

2024-05-11T05:51:53.140431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:53.539440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 445
95.3%
0 22
 
4.7%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
445 
0
 
22

Length

Max length4
Median length4
Mean length3.8586724
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> 445
95.3%
0 22
 
4.7%

Length

2024-05-11T05:51:53.987188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:54.373528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 445
95.3%
0 22
 
4.7%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
445 
0
 
22

Length

Max length4
Median length4
Mean length3.8586724
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> 445
95.3%
0 22
 
4.7%

Length

2024-05-11T05:51:54.806541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:55.178455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 445
95.3%
0 22
 
4.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
445 
0
 
22

Length

Max length4
Median length4
Mean length3.8586724
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> 445
95.3%
0 22
 
4.7%

Length

2024-05-11T05:51:55.682698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:56.143161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 445
95.3%
0 22
 
4.7%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
445 
0
 
22

Length

Max length4
Median length4
Mean length3.8586724
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> 445
95.3%
0 22
 
4.7%

Length

2024-05-11T05:51:56.599095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:57.104978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 445
95.3%
0 22
 
4.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
445 
0
 
22

Length

Max length4
Median length4
Mean length3.8586724
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> 445
95.3%
0 22
 
4.7%

Length

2024-05-11T05:51:58.100328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:51:58.495926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 445
95.3%
0 22
 
4.7%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing97
Missing (%)20.8%
Memory size1.0 KiB
False
369 
True
 
1
(Missing)
97 
ValueCountFrequency (%)
False 369
79.0%
True 1
 
0.2%
(Missing) 97
 
20.8%
2024-05-11T05:51:58.735202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct268
Distinct (%)72.4%
Missing97
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean43.591243
Minimum0
Maximum388.65
Zeros5
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-05-11T05:51:59.098338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.45
Q124.035
median33.1
Q353.015
95-th percentile99
Maximum388.65
Range388.65
Interquartile range (IQR)28.98

Descriptive statistics

Standard deviation37.603596
Coefficient of variation (CV)0.86264105
Kurtosis29.511678
Mean43.591243
Median Absolute Deviation (MAD)12.29
Skewness4.3193904
Sum16128.76
Variance1414.0304
MonotonicityNot monotonic
2024-05-11T05:51:59.588037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 11
 
2.4%
33.0 8
 
1.7%
26.4 8
 
1.7%
23.1 6
 
1.3%
0.0 5
 
1.1%
26.0 5
 
1.1%
66.0 5
 
1.1%
20.0 5
 
1.1%
16.5 5
 
1.1%
6.6 4
 
0.9%
Other values (258) 308
66.0%
(Missing) 97
 
20.8%
ValueCountFrequency (%)
0.0 5
1.1%
3.0 1
 
0.2%
3.75 1
 
0.2%
4.0 1
 
0.2%
6.15 1
 
0.2%
6.6 4
0.9%
7.0 1
 
0.2%
7.75 1
 
0.2%
9.0 1
 
0.2%
9.7 1
 
0.2%
ValueCountFrequency (%)
388.65 1
0.2%
311.23 1
0.2%
261.93 1
0.2%
214.5 1
0.2%
203.7 1
0.2%
143.38 1
0.2%
132.0 1
0.2%
119.0 1
0.2%
118.04 1
0.2%
111.9 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032000003200000-121-1978-0822519780218<NA>1영업/정상1영업<NA><NA><NA><NA>020877379337.8151867서울특별시 관악구 신림동 409-84번지서울특별시 관악구 신림로 259 (신림동)8844신라베이커리2001-09-29 00:00:00I2018-08-31 23:59:59.0제과점영업193947.948815441746.354572제과점영업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N37.8<NA><NA><NA>
132000003200000-121-1978-0837919781213<NA>3폐업2폐업20080808<NA><NA><NA>02 862477531.06151881서울특별시 관악구 신림동 706-22번지<NA><NA>고려제과2001-09-29 00:00:00I2018-08-31 23:59:59.0제과점영업192759.647509441154.136417제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N31.06<NA><NA><NA>
232000003200000-121-1979-0828319790705<NA>3폐업2폐업20120627<NA><NA><NA>02 855098717.38151883서울특별시 관악구 신림동 637-14번지<NA><NA>불란서빵집2010-12-14 16:55:28I2018-08-31 23:59:59.0제과점영업192866.607104440902.89498제과점영업21주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N17.38<NA><NA><NA>
332000003200000-121-1980-0832819800526<NA>1영업/정상1영업<NA><NA><NA><NA>02 877529740.66151854서울특별시 관악구 신림동 94-296서울특별시 관악구 서림길 3 (신림동)8828고려제과2022-04-15 11:53:45U2021-12-03 23:07:00.0제과점영업194411.343121441527.4392<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
432000003200000-121-1980-0834819800725<NA>3폐업2폐업20120214<NA><NA><NA>02 854744447.71151888서울특별시 관악구 신림동 587-46번지<NA><NA>부산뉴욕과자점2002-01-09 00:00:00I2018-08-31 23:59:59.0제과점영업192485.565227441648.942684제과점영업21주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N47.71<NA><NA><NA>
532000003200000-121-1982-0835119820629<NA>3폐업2폐업20110209<NA><NA><NA>02 875323225.35151823서울특별시 관악구 봉천동 463-1번지<NA><NA>풍년제과2010-04-21 09:25:49I2018-08-31 23:59:59.0제과점영업195285.853834442724.651466제과점영업32주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N25.35<NA><NA><NA>
632000003200000-121-1983-0837019830826<NA>1영업/정상1영업<NA><NA><NA><NA>02 883357929.94151843서울특별시 관악구 봉천동 958-12번지서울특별시 관악구 남부순환로 1677 (봉천동)8756영빈2015-12-18 17:27:00I2018-08-31 23:59:59.0제과점영업194368.491074442508.385744제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.94<NA><NA><NA>
732000003200000-121-1983-084081983-08-22<NA>3폐업2폐업2023-11-30<NA><NA><NA>02 523409366.17151-800서울특별시 관악구 남현동 1057-23서울특별시 관악구 남부순환로 2060, 1층 (남현동)8805빵굼터 착한 빵집2023-11-30 13:10:59U2022-11-02 00:02:00.0제과점영업197940.383932441577.222309<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
832000003200000-121-1984-0833619840125<NA>3폐업2폐업20110425<NA><NA><NA>02 884132952.91151832서울특별시 관악구 봉천동 1657-24번지<NA><NA>빵굼터과자점2008-08-06 14:01:42I2018-08-31 23:59:59.0제과점영업196892.414715441529.42779제과점영업02학교정화(상대)지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N52.91<NA><NA><NA>
932000003200000-121-1986-0831119860826<NA>3폐업2폐업20200130<NA><NA><NA>02 887251541.12151826서울특별시 관악구 봉천동 940-1번지서울특별시 관악구 국회단지길 10 (봉천동)8716대학당제과2020-01-30 10:25:35U2020-02-01 02:40:00.0제과점영업194585.60644442719.679596제과점영업21주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N41.12<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
45732000003200000-121-2023-000152023-10-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.0151-866서울특별시 관악구 신림동 408-38서울특별시 관악구 신림로29길 4-35 (신림동)8845우앙딩2023-10-18 13:40:48I2022-10-30 22:00:00.0제과점영업194262.978646441458.113065<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45832000003200000-121-2023-000162023-12-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.2151-843서울특별시 관악구 봉천동 932-17서울특별시 관악구 봉천로 373-9, 1층 (봉천동)8750Sweet lounge(스윗라운지)2023-12-18 17:58:08I2022-11-01 22:00:00.0제과점영업194775.312149442424.680329<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45932000003200000-121-2023-000172023-12-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.0151-809서울특별시 관악구 봉천동 62-8서울특별시 관악구 관악로 208, 1층 (봉천동)8737BGT호두단팥빵2024-01-16 10:04:22U2023-11-30 23:08:00.0제과점영업195926.453911442352.654686<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46032000003200000-121-2024-000012024-01-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>105.95151-902서울특별시 관악구 신림동 1643서울특별시 관악구 시흥대로 578, 1층 (신림동)8700크리스피크림도넛 구로디지털역점2024-01-05 14:09:40I2023-12-01 00:07:00.0제과점영업191376.602184442456.748277<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46132000003200000-121-2024-000022024-01-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.0151-873서울특별시 관악구 신림동 517-11 송암빌딩서울특별시 관악구 난곡로 368, 송암빌딩 1층 101호 (신림동)8702BGT호두단팥빵 신대방점2024-01-19 11:46:39I2023-11-30 22:01:00.0제과점영업192306.647757442749.767959<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46232000003200000-121-2024-000032024-01-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>4.0151-803서울특별시 관악구 봉천동 738-196서울특별시 관악구 낙성대로3길 33-14, 1층 102호 (봉천동)8799유미양과자2024-01-24 09:29:57I2023-11-30 22:06:00.0제과점영업196442.582399441292.434389<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46332000003200000-121-2024-000042024-02-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>14.08151-869서울특별시 관악구 신림동 1587-6서울특별시 관악구 관천로 45-1, 1층 103호 (신림동)8774소망제과 신원시장점2024-02-28 14:11:06I2023-12-03 00:01:00.0제과점영업193400.081312442352.882249<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46432000003200000-121-2024-000052024-03-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.2151-880서울특별시 관악구 신림동 612-28 봉황빌라서울특별시 관악구 법원단지길 53, 지하층 B03호 (신림동, 봉황빌라)8852쥬오베이커리2024-03-06 18:01:39I2023-12-03 00:08:00.0제과점영업192905.2855441321.792011<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46532000003200000-121-2024-000062024-03-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.0151-869서울특별시 관악구 신림동 1578-11서울특별시 관악구 남부순환로172길 46, 1층 우측 두번째 2호 (신림동)8773PANG&PANG(팡앤팡)2024-03-22 10:50:32I2023-12-02 22:04:00.0제과점영업193155.724183442298.471422<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46632000003200000-121-2024-000072024-04-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.0151-829서울특별시 관악구 봉천동 969-44서울특별시 관악구 봉천로13길 6, 1층 (봉천동)8720구조2024-04-04 10:31:52I2023-12-04 00:06:00.0제과점영업193760.674684442970.492576<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>