Overview

Dataset statistics

Number of variables44
Number of observations526
Missing cells5276
Missing cells (%)22.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory193.3 KiB
Average record size in memory376.3 B

Variable types

Categorical20
Text7
DateTime4
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-18412/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
건물소유구분명 has constant value ""Constant
남성종사자수 is highly imbalanced (56.5%)Imbalance
여성종사자수 is highly imbalanced (58.5%)Imbalance
영업장주변구분명 is highly imbalanced (62.1%)Imbalance
등급구분명 is highly imbalanced (74.3%)Imbalance
총인원 is highly imbalanced (74.9%)Imbalance
본사종업원수 is highly imbalanced (74.9%)Imbalance
공장사무직종업원수 is highly imbalanced (74.9%)Imbalance
공장판매직종업원수 is highly imbalanced (74.9%)Imbalance
공장생산직종업원수 is highly imbalanced (74.9%)Imbalance
보증액 is highly imbalanced (74.9%)Imbalance
월세액 is highly imbalanced (74.9%)Imbalance
다중이용업소여부 is highly imbalanced (90.5%)Imbalance
인허가취소일자 has 526 (100.0%) missing valuesMissing
폐업일자 has 161 (30.6%) missing valuesMissing
휴업시작일자 has 526 (100.0%) missing valuesMissing
휴업종료일자 has 526 (100.0%) missing valuesMissing
재개업일자 has 526 (100.0%) missing valuesMissing
전화번호 has 257 (48.9%) missing valuesMissing
소재지면적 has 37 (7.0%) missing valuesMissing
도로명주소 has 175 (33.3%) missing valuesMissing
도로명우편번호 has 177 (33.7%) missing valuesMissing
좌표정보(X) has 17 (3.2%) missing valuesMissing
좌표정보(Y) has 17 (3.2%) missing valuesMissing
건물소유구분명 has 525 (99.8%) missing valuesMissing
다중이용업소여부 has 114 (21.7%) missing valuesMissing
시설총규모 has 114 (21.7%) missing valuesMissing
전통업소지정번호 has 526 (100.0%) missing valuesMissing
전통업소주된음식 has 526 (100.0%) missing valuesMissing
홈페이지 has 526 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 23 (4.4%) zerosZeros

Reproduction

Analysis started2024-05-11 05:42:04.126663
Analysis finished2024-05-11 05:42:05.177273
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
3100000
526 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 526
100.0%

Length

2024-05-11T14:42:05.256289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:05.419502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 526
100.0%

관리번호
Text

UNIQUE 

Distinct526
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-05-11T14:42:05.667187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters11572
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

Unique526 ?
Unique (%)100.0%

Sample

1st row3100000-121-1970-05185
2nd row3100000-121-1978-05171
3rd row3100000-121-1980-05173
4th row3100000-121-1983-05175
5th row3100000-121-1984-05189
ValueCountFrequency (%)
3100000-121-1970-05185 1
 
0.2%
3100000-121-2016-00002 1
 
0.2%
3100000-121-2015-00014 1
 
0.2%
3100000-121-2015-00013 1
 
0.2%
3100000-121-2015-00012 1
 
0.2%
3100000-121-2015-00011 1
 
0.2%
3100000-121-2015-00010 1
 
0.2%
3100000-121-2015-00009 1
 
0.2%
3100000-121-2015-00008 1
 
0.2%
3100000-121-2015-00007 1
 
0.2%
Other values (516) 516
98.1%
2024-05-11T14:42:06.100215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4901
42.4%
1 2140
18.5%
- 1578
 
13.6%
2 1273
 
11.0%
3 666
 
5.8%
9 272
 
2.4%
5 172
 
1.5%
6 171
 
1.5%
4 150
 
1.3%
7 134
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9994
86.4%
Dash Punctuation 1578
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4901
49.0%
1 2140
21.4%
2 1273
 
12.7%
3 666
 
6.7%
9 272
 
2.7%
5 172
 
1.7%
6 171
 
1.7%
4 150
 
1.5%
7 134
 
1.3%
8 115
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1578
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4901
42.4%
1 2140
18.5%
- 1578
 
13.6%
2 1273
 
11.0%
3 666
 
5.8%
9 272
 
2.4%
5 172
 
1.5%
6 171
 
1.5%
4 150
 
1.3%
7 134
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4901
42.4%
1 2140
18.5%
- 1578
 
13.6%
2 1273
 
11.0%
3 666
 
5.8%
9 272
 
2.4%
5 172
 
1.5%
6 171
 
1.5%
4 150
 
1.3%
7 134
 
1.2%

인허가일자
Date

Distinct489
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum1970-04-11 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:42:06.298022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:42:06.465756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing526
Missing (%)100.0%
Memory size4.8 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
3
365 
1
161 

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 (%)
3 365
69.4%
1 161
30.6%

Length

2024-05-11T14:42:06.619710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:06.744304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 365
69.4%
1 161
30.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
폐업
365 
영업/정상
161 

Length

Max length5
Median length2
Mean length2.918251
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 365
69.4%
영업/정상 161
30.6%

Length

2024-05-11T14:42:06.896440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:07.047519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 365
69.4%
영업/정상 161
30.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2
365 
1
161 

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 (%)
2 365
69.4%
1 161
30.6%

Length

2024-05-11T14:42:07.468173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:07.599644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 365
69.4%
1 161
30.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
폐업
365 
영업
161 

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 365
69.4%
영업 161
30.6%

Length

2024-05-11T14:42:07.757708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:07.899668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 365
69.4%
영업 161
30.6%

폐업일자
Date

MISSING 

Distinct323
Distinct (%)88.5%
Missing161
Missing (%)30.6%
Memory size4.2 KiB
Minimum2005-08-29 00:00:00
Maximum2024-05-01 00:00:00
2024-05-11T14:42:08.061798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:42:08.270603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing526
Missing (%)100.0%
Memory size4.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing526
Missing (%)100.0%
Memory size4.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing526
Missing (%)100.0%
Memory size4.8 KiB

전화번호
Text

MISSING 

Distinct261
Distinct (%)97.0%
Missing257
Missing (%)48.9%
Memory size4.2 KiB
2024-05-11T14:42:08.718661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.63197
Min length9

Characters and Unicode

Total characters2860
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

Unique257 ?
Unique (%)95.5%

Sample

1st row02 9173952
2nd row02 9723883
3rd row02 9757691
4th row02 9739789
5th row02 9687031
ValueCountFrequency (%)
02 216
38.1%
031 10
 
1.8%
070 8
 
1.4%
71237600 4
 
0.7%
4242193 4
 
0.7%
971 4
 
0.7%
951 3
 
0.5%
931 3
 
0.5%
936 3
 
0.5%
937 2
 
0.4%
Other values (299) 310
54.7%
2024-05-11T14:42:09.410749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 481
16.8%
2 408
14.3%
369
12.9%
9 348
12.2%
3 252
8.8%
7 207
7.2%
1 183
 
6.4%
4 167
 
5.8%
5 164
 
5.7%
8 148
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2491
87.1%
Space Separator 369
 
12.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 481
19.3%
2 408
16.4%
9 348
14.0%
3 252
10.1%
7 207
8.3%
1 183
 
7.3%
4 167
 
6.7%
5 164
 
6.6%
8 148
 
5.9%
6 133
 
5.3%
Space Separator
ValueCountFrequency (%)
369
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2860
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 481
16.8%
2 408
14.3%
369
12.9%
9 348
12.2%
3 252
8.8%
7 207
7.2%
1 183
 
6.4%
4 167
 
5.8%
5 164
 
5.7%
8 148
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 481
16.8%
2 408
14.3%
369
12.9%
9 348
12.2%
3 252
8.8%
7 207
7.2%
1 183
 
6.4%
4 167
 
5.8%
5 164
 
5.7%
8 148
 
5.2%

소재지면적
Real number (ℝ)

MISSING 

Distinct385
Distinct (%)78.7%
Missing37
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean42.819427
Minimum1.4
Maximum279.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-05-11T14:42:09.585802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.4
5-th percentile7.338
Q121.43
median33
Q350.18
95-th percentile115.116
Maximum279.96
Range278.56
Interquartile range (IQR)28.75

Descriptive statistics

Standard deviation37.530394
Coefficient of variation (CV)0.87648052
Kurtosis11.551803
Mean42.819427
Median Absolute Deviation (MAD)13
Skewness2.852221
Sum20938.7
Variance1408.5305
MonotonicityNot monotonic
2024-05-11T14:42:09.730043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 14
 
2.7%
26.4 6
 
1.1%
3.3 6
 
1.1%
30.0 6
 
1.1%
23.1 5
 
1.0%
20.0 5
 
1.0%
25.7 4
 
0.8%
2.0 4
 
0.8%
12.12 4
 
0.8%
40.0 4
 
0.8%
Other values (375) 431
81.9%
(Missing) 37
 
7.0%
ValueCountFrequency (%)
1.4 1
 
0.2%
2.0 4
0.8%
2.4 1
 
0.2%
2.6 1
 
0.2%
3.3 6
1.1%
5.0 2
 
0.4%
5.65 1
 
0.2%
6.0 2
 
0.4%
6.15 1
 
0.2%
6.6 4
0.8%
ValueCountFrequency (%)
279.96 1
0.2%
269.42 1
0.2%
268.68 1
0.2%
231.0 1
0.2%
218.61 1
0.2%
207.0 1
0.2%
189.48 1
0.2%
182.31 1
0.2%
168.5 1
0.2%
161.49 1
0.2%

소재지우편번호
Text

Distinct109
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-05-11T14:42:10.000341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1368821
Min length6

Characters and Unicode

Total characters3228
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

Unique33 ?
Unique (%)6.3%

Sample

1st row139846
2nd row139808
3rd row139804
4th row139240
5th row139818
ValueCountFrequency (%)
139200 36
 
6.8%
139240 30
 
5.7%
139865 23
 
4.4%
139816 19
 
3.6%
139708 19
 
3.6%
139800 17
 
3.2%
139860 16
 
3.0%
139838 15
 
2.9%
139821 15
 
2.9%
139861 14
 
2.7%
Other values (99) 322
61.2%
2024-05-11T14:42:10.409114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 653
20.2%
3 623
19.3%
9 550
17.0%
8 428
13.3%
0 302
9.4%
2 207
 
6.4%
6 127
 
3.9%
4 112
 
3.5%
5 78
 
2.4%
7 76
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3156
97.8%
Dash Punctuation 72
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 653
20.7%
3 623
19.7%
9 550
17.4%
8 428
13.6%
0 302
9.6%
2 207
 
6.6%
6 127
 
4.0%
4 112
 
3.5%
5 78
 
2.5%
7 76
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3228
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 653
20.2%
3 623
19.3%
9 550
17.0%
8 428
13.3%
0 302
9.4%
2 207
 
6.4%
6 127
 
3.9%
4 112
 
3.5%
5 78
 
2.4%
7 76
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 653
20.2%
3 623
19.3%
9 550
17.0%
8 428
13.3%
0 302
9.4%
2 207
 
6.4%
6 127
 
3.9%
4 112
 
3.5%
5 78
 
2.4%
7 76
 
2.4%

지번주소
Text

Distinct482
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-05-11T14:42:10.825511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length42
Mean length27.619772
Min length17

Characters and Unicode

Total characters14528
Distinct characters236
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique451 ?
Unique (%)85.7%

Sample

1st row서울특별시 노원구 월계동 410-7번지
2nd row서울특별시 노원구 공릉동 661-11번지
3rd row서울특별시 노원구 공릉동 420-2번지
4th row서울특별시 노원구 공릉동 395-8번지
5th row서울특별시 노원구 상계동 389-680번지
ValueCountFrequency (%)
서울특별시 525
19.0%
노원구 525
19.0%
상계동 234
 
8.5%
중계동 115
 
4.2%
공릉동 95
 
3.4%
월계동 57
 
2.1%
1층 47
 
1.7%
지하1층 32
 
1.2%
하계동 25
 
0.9%
713 23
 
0.8%
Other values (722) 1084
39.2%
2024-05-11T14:42:11.479206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2597
 
17.9%
1 774
 
5.3%
동 571
 
3.9%
원 543
 
3.7%
노 542
 
3.7%
구 531
 
3.7%
시 530
 
3.6%
울 529
 
3.6%
서 525
 
3.6%
특 525
 
3.6%
Other values (226) 6861
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8487
58.4%
Decimal Number 2936
 
20.2%
Space Separator 2597
 
17.9%
Dash Punctuation 381
 
2.6%
Other Punctuation 62
 
0.4%
Close Punctuation 22
 
0.2%
Open Punctuation 22
 
0.2%
Uppercase Letter 21
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 571
 
6.7%
원 543
 
6.4%
노 542
 
6.4%
구 531
 
6.3%
시 530
 
6.2%
울 529
 
6.2%
서 525
 
6.2%
특 525
 
6.2%
별 525
 
6.2%
계 470
 
5.5%
Other values (199) 3196
37.7%
Decimal Number
ValueCountFrequency (%)
1 774
26.4%
3 331
11.3%
0 320
10.9%
2 296
 
10.1%
6 262
 
8.9%
5 238
 
8.1%
7 219
 
7.5%
4 184
 
6.3%
9 164
 
5.6%
8 148
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 6
28.6%
G 4
19.0%
S 3
14.3%
A 3
14.3%
L 2
 
9.5%
T 1
 
4.8%
O 1
 
4.8%
D 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 47
75.8%
@ 8
 
12.9%
. 4
 
6.5%
? 2
 
3.2%
/ 1
 
1.6%
Space Separator
ValueCountFrequency (%)
2597
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 381
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8487
58.4%
Common 6020
41.4%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 571
 
6.7%
원 543
 
6.4%
노 542
 
6.4%
구 531
 
6.3%
시 530
 
6.2%
울 529
 
6.2%
서 525
 
6.2%
특 525
 
6.2%
별 525
 
6.2%
계 470
 
5.5%
Other values (199) 3196
37.7%
Common
ValueCountFrequency (%)
2597
43.1%
1 774
 
12.9%
- 381
 
6.3%
3 331
 
5.5%
0 320
 
5.3%
2 296
 
4.9%
6 262
 
4.4%
5 238
 
4.0%
7 219
 
3.6%
4 184
 
3.1%
Other values (9) 418
 
6.9%
Latin
ValueCountFrequency (%)
B 6
28.6%
G 4
19.0%
S 3
14.3%
A 3
14.3%
L 2
 
9.5%
T 1
 
4.8%
O 1
 
4.8%
D 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8487
58.4%
ASCII 6041
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2597
43.0%
1 774
 
12.8%
- 381
 
6.3%
3 331
 
5.5%
0 320
 
5.3%
2 296
 
4.9%
6 262
 
4.3%
5 238
 
3.9%
7 219
 
3.6%
4 184
 
3.0%
Other values (17) 439
 
7.3%
Hangul
ValueCountFrequency (%)
동 571
 
6.7%
원 543
 
6.4%
노 542
 
6.4%
구 531
 
6.3%
시 530
 
6.2%
울 529
 
6.2%
서 525
 
6.2%
특 525
 
6.2%
별 525
 
6.2%
계 470
 
5.5%
Other values (199) 3196
37.7%

도로명주소
Text

MISSING 

Distinct330
Distinct (%)94.0%
Missing175
Missing (%)33.3%
Memory size4.2 KiB
2024-05-11T14:42:11.788979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length49
Mean length36.928775
Min length22

Characters and Unicode

Total characters12962
Distinct characters232
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

Unique321 ?
Unique (%)91.5%

Sample

1st row서울특별시 노원구 상계로27길 11 (상계동)
2nd row서울특별시 노원구 공릉로46길 6 (공릉동, 421-19 현대프라자 103호)
3rd row서울특별시 노원구 한글비석로 474, 157호 (상계동,보람상가)
4th row서울특별시 노원구 동일로227길 26 (상계동, 642-015단지2층지하1층)
5th row서울특별시 노원구 동일로 1493, 상계주공아파트(10단지) 상가동 112호 (상계동)
ValueCountFrequency (%)
서울특별시 351
 
14.5%
노원구 351
 
14.5%
상계동 164
 
6.8%
동일로 97
 
4.0%
1층 89
 
3.7%
공릉동 60
 
2.5%
중계동 49
 
2.0%
월계동 36
 
1.5%
한글비석로 34
 
1.4%
지하1층 30
 
1.2%
Other values (634) 1165
48.0%
2024-05-11T14:42:12.339733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2077
 
16.0%
1 826
 
6.4%
동 547
 
4.2%
, 418
 
3.2%
노 397
 
3.1%
계 395
 
3.0%
원 391
 
3.0%
( 375
 
2.9%
) 375
 
2.9%
구 356
 
2.7%
Other values (222) 6805
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7116
54.9%
Decimal Number 2475
 
19.1%
Space Separator 2077
 
16.0%
Other Punctuation 442
 
3.4%
Open Punctuation 375
 
2.9%
Close Punctuation 375
 
2.9%
Dash Punctuation 90
 
0.7%
Uppercase Letter 11
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 547
 
7.7%
노 397
 
5.6%
계 395
 
5.6%
원 391
 
5.5%
구 356
 
5.0%
시 355
 
5.0%
울 354
 
5.0%
로 353
 
5.0%
서 352
 
4.9%
별 351
 
4.9%
Other values (197) 3265
45.9%
Decimal Number
ValueCountFrequency (%)
1 826
33.4%
0 292
 
11.8%
2 273
 
11.0%
3 230
 
9.3%
4 226
 
9.1%
5 168
 
6.8%
7 138
 
5.6%
6 118
 
4.8%
9 104
 
4.2%
8 100
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 418
94.6%
. 18
 
4.1%
@ 3
 
0.7%
? 2
 
0.5%
/ 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
B 5
45.5%
S 2
 
18.2%
G 2
 
18.2%
A 1
 
9.1%
D 1
 
9.1%
Space Separator
ValueCountFrequency (%)
2077
100.0%
Open Punctuation
ValueCountFrequency (%)
( 375
100.0%
Close Punctuation
ValueCountFrequency (%)
) 375
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7116
54.9%
Common 5835
45.0%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 547
 
7.7%
노 397
 
5.6%
계 395
 
5.6%
원 391
 
5.5%
구 356
 
5.0%
시 355
 
5.0%
울 354
 
5.0%
로 353
 
5.0%
서 352
 
4.9%
별 351
 
4.9%
Other values (197) 3265
45.9%
Common
ValueCountFrequency (%)
2077
35.6%
1 826
 
14.2%
, 418
 
7.2%
( 375
 
6.4%
) 375
 
6.4%
0 292
 
5.0%
2 273
 
4.7%
3 230
 
3.9%
4 226
 
3.9%
5 168
 
2.9%
Other values (10) 575
 
9.9%
Latin
ValueCountFrequency (%)
B 5
45.5%
S 2
 
18.2%
G 2
 
18.2%
A 1
 
9.1%
D 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7116
54.9%
ASCII 5846
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2077
35.5%
1 826
 
14.1%
, 418
 
7.2%
( 375
 
6.4%
) 375
 
6.4%
0 292
 
5.0%
2 273
 
4.7%
3 230
 
3.9%
4 226
 
3.9%
5 168
 
2.9%
Other values (15) 586
 
10.0%
Hangul
ValueCountFrequency (%)
동 547
 
7.7%
노 397
 
5.6%
계 395
 
5.6%
원 391
 
5.5%
구 356
 
5.0%
시 355
 
5.0%
울 354
 
5.0%
로 353
 
5.0%
서 352
 
4.9%
별 351
 
4.9%
Other values (197) 3265
45.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct134
Distinct (%)38.4%
Missing177
Missing (%)33.7%
Infinite0
Infinite (%)0.0%
Mean1746.7479
Minimum1601
Maximum1914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-05-11T14:42:12.535702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1601
5-th percentile1620
Q11685
median1726
Q31824
95-th percentile1905.6
Maximum1914
Range313
Interquartile range (IQR)139

Descriptive statistics

Standard deviation85.502299
Coefficient of variation (CV)0.048949423
Kurtosis-0.90413452
Mean1746.7479
Median Absolute Deviation (MAD)53
Skewness0.35546682
Sum609615
Variance7310.6431
MonotonicityNot monotonic
2024-05-11T14:42:12.724800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1695 35
 
6.7%
1693 12
 
2.3%
1906 9
 
1.7%
1756 8
 
1.5%
1699 7
 
1.3%
1684 7
 
1.3%
1674 7
 
1.3%
1849 6
 
1.1%
1751 5
 
1.0%
1914 5
 
1.0%
Other values (124) 248
47.1%
(Missing) 177
33.7%
ValueCountFrequency (%)
1601 2
0.4%
1604 4
0.8%
1606 1
 
0.2%
1607 1
 
0.2%
1608 1
 
0.2%
1612 2
0.4%
1614 2
0.4%
1616 1
 
0.2%
1617 3
0.6%
1620 4
0.8%
ValueCountFrequency (%)
1914 5
1.0%
1913 2
 
0.4%
1911 2
 
0.4%
1906 9
1.7%
1905 1
 
0.2%
1903 1
 
0.2%
1902 4
0.8%
1900 1
 
0.2%
1897 2
 
0.4%
1895 1
 
0.2%

사업장명
Text

Distinct461
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-05-11T14:42:13.078443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length7.8098859
Min length2

Characters and Unicode

Total characters4108
Distinct characters434
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

Unique424 ?
Unique (%)80.6%

Sample

1st row뚜레쥬르
2nd row케익하우스 엠마
3rd row뉴델리과자점
4th row쎄무아베이커리
5th row부래옥과자점
ValueCountFrequency (%)
파리바게뜨 29
 
3.9%
뚜레쥬르 21
 
2.8%
베이커리 12
 
1.6%
롯데백화점 8
 
1.1%
주)신세계푸드 8
 
1.1%
중계점 7
 
0.9%
따삐오 6
 
0.8%
노원점 6
 
0.8%
신라명과 5
 
0.7%
브레드원 5
 
0.7%
Other values (527) 630
85.5%
2024-05-11T14:42:13.588281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
211
 
5.1%
점 200
 
4.9%
리 183
 
4.5%
이 120
 
2.9%
계 103
 
2.5%
레 87
 
2.1%
) 74
 
1.8%
( 74
 
1.8%
베 71
 
1.7%
바 67
 
1.6%
Other values (424) 2918
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3524
85.8%
Space Separator 211
 
5.1%
Lowercase Letter 118
 
2.9%
Close Punctuation 74
 
1.8%
Open Punctuation 74
 
1.8%
Uppercase Letter 55
 
1.3%
Decimal Number 35
 
0.9%
Other Punctuation 10
 
0.2%
Dash Punctuation 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 200
 
5.7%
리 183
 
5.2%
이 120
 
3.4%
계 103
 
2.9%
레 87
 
2.5%
베 71
 
2.0%
바 67
 
1.9%
커 64
 
1.8%
스 63
 
1.8%
파 59
 
1.7%
Other values (364) 2507
71.1%
Lowercase Letter
ValueCountFrequency (%)
e 17
14.4%
a 13
11.0%
r 12
10.2%
y 11
9.3%
o 10
 
8.5%
k 9
 
7.6%
s 6
 
5.1%
l 6
 
5.1%
i 5
 
4.2%
n 4
 
3.4%
Other values (13) 25
21.2%
Uppercase Letter
ValueCountFrequency (%)
B 10
18.2%
A 7
12.7%
E 5
9.1%
L 5
9.1%
R 4
 
7.3%
M 3
 
5.5%
D 3
 
5.5%
H 2
 
3.6%
U 2
 
3.6%
C 2
 
3.6%
Other values (9) 12
21.8%
Decimal Number
ValueCountFrequency (%)
2 12
34.3%
1 7
20.0%
7 4
 
11.4%
8 3
 
8.6%
3 3
 
8.6%
0 3
 
8.6%
9 1
 
2.9%
6 1
 
2.9%
5 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
& 5
50.0%
? 2
 
20.0%
, 1
 
10.0%
. 1
 
10.0%
' 1
 
10.0%
Space Separator
ValueCountFrequency (%)
211
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3524
85.8%
Common 411
 
10.0%
Latin 173
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 200
 
5.7%
리 183
 
5.2%
이 120
 
3.4%
계 103
 
2.9%
레 87
 
2.5%
베 71
 
2.0%
바 67
 
1.9%
커 64
 
1.8%
스 63
 
1.8%
파 59
 
1.7%
Other values (364) 2507
71.1%
Latin
ValueCountFrequency (%)
e 17
 
9.8%
a 13
 
7.5%
r 12
 
6.9%
y 11
 
6.4%
o 10
 
5.8%
B 10
 
5.8%
k 9
 
5.2%
A 7
 
4.0%
s 6
 
3.5%
l 6
 
3.5%
Other values (32) 72
41.6%
Common
ValueCountFrequency (%)
211
51.3%
) 74
 
18.0%
( 74
 
18.0%
2 12
 
2.9%
- 7
 
1.7%
1 7
 
1.7%
& 5
 
1.2%
7 4
 
1.0%
8 3
 
0.7%
3 3
 
0.7%
Other values (8) 11
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3524
85.8%
ASCII 584
 
14.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211
36.1%
) 74
 
12.7%
( 74
 
12.7%
e 17
 
2.9%
a 13
 
2.2%
r 12
 
2.1%
2 12
 
2.1%
y 11
 
1.9%
o 10
 
1.7%
B 10
 
1.7%
Other values (50) 140
24.0%
Hangul
ValueCountFrequency (%)
점 200
 
5.7%
리 183
 
5.2%
이 120
 
3.4%
계 103
 
2.9%
레 87
 
2.5%
베 71
 
2.0%
바 67
 
1.9%
커 64
 
1.8%
스 63
 
1.8%
파 59
 
1.7%
Other values (364) 2507
71.1%

최종수정일자
Date

Distinct490
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum1999-12-08 00:00:00
Maximum2024-05-08 09:25:11
2024-05-11T14:42:13.789147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:42:13.965673image/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 size4.2 KiB
I
321 
U
205 

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 321
61.0%
U 205
39.0%

Length

2024-05-11T14:42:14.152414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:14.284948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 321
61.0%
u 205
39.0%

데이터갱신일자
Date

Distinct185
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:42:14.471936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:42:14.678893image/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 size4.2 KiB
제과점영업
526 

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 526
100.0%

Length

2024-05-11T14:42:14.858584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:14.983275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 526
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct301
Distinct (%)59.1%
Missing17
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean205938.54
Minimum203794.8
Maximum209288.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-05-11T14:42:15.123585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203794.8
5-th percentile204772.37
Q1205320.28
median205845.31
Q3206547.35
95-th percentile207216.75
Maximum209288.47
Range5493.6742
Interquartile range (IQR)1227.0686

Descriptive statistics

Standard deviation803.75647
Coefficient of variation (CV)0.0039028949
Kurtosis0.81079539
Mean205938.54
Median Absolute Deviation (MAD)542.41191
Skewness0.6025309
Sum1.0482272 × 108
Variance646024.46
MonotonicityNot monotonic
2024-05-11T14:42:15.336312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205320.28476675 32
 
6.1%
205391.070378059 10
 
1.9%
205985.953324881 8
 
1.5%
205994.811815848 8
 
1.5%
206033.023278317 7
 
1.3%
205387.083540216 7
 
1.3%
205931.05327036 6
 
1.1%
205010.833443366 5
 
1.0%
204855.557180678 5
 
1.0%
205715.538939251 5
 
1.0%
Other values (291) 416
79.1%
(Missing) 17
 
3.2%
ValueCountFrequency (%)
203794.798378498 1
0.2%
204454.974085477 2
0.4%
204489.998187538 2
0.4%
204493.316247866 1
0.2%
204495.071606517 1
0.2%
204502.184797871 1
0.2%
204566.568641642 1
0.2%
204579.0 1
0.2%
204589.830805772 1
0.2%
204610.071935062 1
0.2%
ValueCountFrequency (%)
209288.472624641 2
0.4%
208761.191287888 3
0.6%
207918.320414714 1
 
0.2%
207892.695157902 1
 
0.2%
207794.259011921 1
 
0.2%
207749.307579592 1
 
0.2%
207664.317647853 1
 
0.2%
207577.515810212 2
0.4%
207503.415333333 1
 
0.2%
207311.175792021 4
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct301
Distinct (%)59.1%
Missing17
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean460492.15
Minimum456994.52
Maximum464964.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-05-11T14:42:15.500381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456994.52
5-th percentile457477.5
Q1458453.09
median460903.98
Q3461858.09
95-th percentile463524.96
Maximum464964.28
Range7969.767
Interquartile range (IQR)3405.0084

Descriptive statistics

Standard deviation1926.8277
Coefficient of variation (CV)0.0041842792
Kurtosis-0.9460673
Mean460492.15
Median Absolute Deviation (MAD)1299.6714
Skewness-0.13776225
Sum2.3439051 × 108
Variance3712665.1
MonotonicityNot monotonic
2024-05-11T14:42:15.673374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461419.881795004 32
 
6.1%
458333.989216339 10
 
1.9%
459730.43776924 8
 
1.5%
459502.645279682 8
 
1.5%
461935.33920381 7
 
1.3%
460970.929075231 7
 
1.3%
459884.197207567 6
 
1.1%
462726.458573708 5
 
1.0%
464199.048415229 5
 
1.0%
462416.211580109 5
 
1.0%
Other values (291) 416
79.1%
(Missing) 17
 
3.2%
ValueCountFrequency (%)
456994.517426262 3
0.6%
457018.943974424 1
 
0.2%
457053.212479203 1
 
0.2%
457056.775895934 2
0.4%
457060.262096119 1
 
0.2%
457062.050344449 2
0.4%
457065.63437521 1
 
0.2%
457078.810041553 1
 
0.2%
457101.818557239 1
 
0.2%
457102.323781569 1
 
0.2%
ValueCountFrequency (%)
464964.284423079 1
 
0.2%
464920.0 1
 
0.2%
464346.663669239 1
 
0.2%
464208.305428933 2
 
0.4%
464199.048415229 5
1.0%
464080.593904719 5
1.0%
463977.646458819 1
 
0.2%
463966.29285643 1
 
0.2%
463895.862348388 2
 
0.4%
463866.419009316 1
 
0.2%

위생업태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
제과점영업
412 
<NA>
114 

Length

Max length5
Median length5
Mean length4.78327
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 412
78.3%
<NA> 114
 
21.7%

Length

2024-05-11T14:42:15.838036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:15.937999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 412
78.3%
na 114
 
21.7%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
415 
0
99 
1
 
7
2
 
5

Length

Max length4
Median length4
Mean length3.3669202
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 415
78.9%
0 99
 
18.8%
1 7
 
1.3%
2 5
 
1.0%

Length

2024-05-11T14:42:16.078867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:16.202573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 415
78.9%
0 99
 
18.8%
1 7
 
1.3%
2 5
 
1.0%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
416 
0
102 
1
 
6
2
 
2

Length

Max length4
Median length4
Mean length3.3726236
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 416
79.1%
0 102
 
19.4%
1 6
 
1.1%
2 2
 
0.4%

Length

2024-05-11T14:42:16.380174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:16.512376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 416
79.1%
0 102
 
19.4%
1 6
 
1.1%
2 2
 
0.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
456 
아파트지역
 
32
주택가주변
 
28
기타
 
10

Length

Max length5
Median length4
Mean length4.0760456
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 456
86.7%
아파트지역 32
 
6.1%
주택가주변 28
 
5.3%
기타 10
 
1.9%

Length

2024-05-11T14:42:16.664277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:16.849312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 456
86.7%
아파트지역 32
 
6.1%
주택가주변 28
 
5.3%
기타 10
 
1.9%

등급구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
465 
갑
 
31
기타
 
15
자율
 
12
우수
 
1
Other values (2)
 
2

Length

Max length4
Median length4
Mean length3.7072243
Min length1

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st row자율
2nd row우수
3rd row자율
4th row자율
5th row자율

Common Values

ValueCountFrequency (%)
<NA> 465
88.4%
갑 31
 
5.9%
기타 15
 
2.9%
자율 12
 
2.3%
우수 1
 
0.2%
을 1
 
0.2%
지도 1
 
0.2%

Length

2024-05-11T14:42:16.968763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:17.395975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 465
88.4%
갑 31
 
5.9%
기타 15
 
2.9%
자율 12
 
2.3%
우수 1
 
0.2%
을 1
 
0.2%
지도 1
 
0.2%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
454 
상수도전용
72 

Length

Max length5
Median length4
Mean length4.1368821
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 454
86.3%
상수도전용 72
 
13.7%

Length

2024-05-11T14:42:17.569465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:17.717437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 454
86.3%
상수도전용 72
 
13.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
504 
0
 
22

Length

Max length4
Median length4
Mean length3.8745247
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> 504
95.8%
0 22
 
4.2%

Length

2024-05-11T14:42:17.870706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:17.988934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 504
95.8%
0 22
 
4.2%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
504 
0
 
22

Length

Max length4
Median length4
Mean length3.8745247
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> 504
95.8%
0 22
 
4.2%

Length

2024-05-11T14:42:18.122933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:18.285708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 504
95.8%
0 22
 
4.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
504 
0
 
22

Length

Max length4
Median length4
Mean length3.8745247
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> 504
95.8%
0 22
 
4.2%

Length

2024-05-11T14:42:18.421740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:18.535079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 504
95.8%
0 22
 
4.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
504 
0
 
22

Length

Max length4
Median length4
Mean length3.8745247
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> 504
95.8%
0 22
 
4.2%

Length

2024-05-11T14:42:18.658386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:18.788177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 504
95.8%
0 22
 
4.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
504 
0
 
22

Length

Max length4
Median length4
Mean length3.8745247
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> 504
95.8%
0 22
 
4.2%

Length

2024-05-11T14:42:18.904119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:19.059519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 504
95.8%
0 22
 
4.2%

건물소유구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing525
Missing (%)99.8%
Memory size4.2 KiB
2024-05-11T14:42:19.149115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row자가
ValueCountFrequency (%)
자가 1
100.0%
2024-05-11T14:42:19.445072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 1
50.0%
가 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 1
50.0%
가 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 1
50.0%
가 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 1
50.0%
가 1
50.0%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
504 
0
 
22

Length

Max length4
Median length4
Mean length3.8745247
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> 504
95.8%
0 22
 
4.2%

Length

2024-05-11T14:42:19.602437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:19.750654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 504
95.8%
0 22
 
4.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
504 
0
 
22

Length

Max length4
Median length4
Mean length3.8745247
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> 504
95.8%
0 22
 
4.2%

Length

2024-05-11T14:42:19.932888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:42:20.109624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 504
95.8%
0 22
 
4.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing114
Missing (%)21.7%
Memory size1.2 KiB
False
407 
True
 
5
(Missing)
114 
ValueCountFrequency (%)
False 407
77.4%
True 5
 
1.0%
(Missing) 114
 
21.7%
2024-05-11T14:42:20.225382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct323
Distinct (%)78.4%
Missing114
Missing (%)21.7%
Infinite0
Infinite (%)0.0%
Mean40.889927
Minimum0
Maximum279.96
Zeros23
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-05-11T14:42:20.379624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median32.62
Q348.895
95-th percentile116.875
Maximum279.96
Range279.96
Interquartile range (IQR)28.895

Descriptive statistics

Standard deviation38.280942
Coefficient of variation (CV)0.93619492
Kurtosis10.15627
Mean40.889927
Median Absolute Deviation (MAD)13.955
Skewness2.6456627
Sum16846.65
Variance1465.4305
MonotonicityNot monotonic
2024-05-11T14:42:20.554171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 23
 
4.4%
33.0 11
 
2.1%
3.3 5
 
1.0%
20.0 5
 
1.0%
12.12 4
 
0.8%
2.0 4
 
0.8%
40.0 4
 
0.8%
23.1 4
 
0.8%
23.0 3
 
0.6%
17.0 3
 
0.6%
Other values (313) 346
65.8%
(Missing) 114
 
21.7%
ValueCountFrequency (%)
0.0 23
4.4%
2.0 4
 
0.8%
2.4 1
 
0.2%
2.6 1
 
0.2%
3.3 5
 
1.0%
5.0 2
 
0.4%
5.65 1
 
0.2%
6.0 1
 
0.2%
6.15 1
 
0.2%
6.6 2
 
0.4%
ValueCountFrequency (%)
279.96 1
0.2%
268.68 1
0.2%
231.0 1
0.2%
218.61 1
0.2%
207.0 1
0.2%
189.48 1
0.2%
182.31 1
0.2%
161.49 1
0.2%
154.99 1
0.2%
147.76 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing526
Missing (%)100.0%
Memory size4.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing526
Missing (%)100.0%
Memory size4.8 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing526
Missing (%)100.0%
Memory size4.8 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-121-1970-0518519700411<NA>3폐업2폐업20110114<NA><NA><NA>02 917395275.72139846서울특별시 노원구 월계동 410-7번지<NA><NA>뚜레쥬르2010-12-07 09:35:30I2018-08-31 23:59:59.0제과점영업205287.68355457833.667655제과점영업22주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N75.72<NA><NA><NA>
131000003100000-121-1978-0517119781104<NA>3폐업2폐업20100517<NA><NA><NA>02 972388352.56139808서울특별시 노원구 공릉동 661-11번지<NA><NA>케익하우스 엠마2002-05-28 00:00:00I2018-08-31 23:59:59.0제과점영업206841.762398457391.995285제과점영업22주택가주변우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N52.56<NA><NA><NA>
231000003100000-121-1980-0517319800312<NA>3폐업2폐업20080918<NA><NA><NA>02 975769131.97139804서울특별시 노원구 공릉동 420-2번지<NA><NA>뉴델리과자점2007-12-24 09:26:34I2018-08-31 23:59:59.0제과점영업206918.939595458317.423099제과점영업11주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N31.97<NA><NA><NA>
331000003100000-121-1983-0517519831101<NA>3폐업2폐업20051220<NA><NA><NA>02 973978955.93139240서울특별시 노원구 공릉동 395-8번지<NA><NA>쎄무아베이커리1999-12-08 00:00:00I2018-08-31 23:59:59.0제과점영업206414.706924458105.675471제과점영업11주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N55.93<NA><NA><NA>
431000003100000-121-1984-0518919841112<NA>3폐업2폐업20140430<NA><NA><NA>02 968703120.79139818서울특별시 노원구 상계동 389-680번지서울특별시 노원구 상계로27길 11 (상계동)1684부래옥과자점1999-12-08 00:00:00I2018-08-31 23:59:59.0제과점영업206146.437779461858.094547제과점영업11주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N20.79<NA><NA><NA>
531000003100000-121-1985-0000119851220<NA>3폐업2폐업20130830<NA><NA><NA>02 452003169.3139804서울특별시 노원구 공릉동 421-19번지 현대프라자 103호서울특별시 노원구 공릉로46길 6 (공릉동, 421-19 현대프라자 103호)1815케익하우스엠마2012-09-17 09:44:12I2018-08-31 23:59:59.0제과점영업206948.010916458283.894145제과점영업0<NA>주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N69.3<NA><NA><NA>
631000003100000-121-1987-0520519871102<NA>3폐업2폐업20081105<NA><NA><NA>020977617438.16139855서울특별시 노원구 중계동 85-12번지<NA><NA>쥬떼므베이커리2003-08-08 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N38.16<NA><NA><NA>
731000003100000-121-1988-0523619881231<NA>3폐업2폐업20120117<NA><NA><NA>02 978125549.4139865서울특별시 노원구 중계동 515-2번지 정안프라자 1층<NA><NA>파리바게뜨 중계역점2007-01-09 00:00:00I2018-08-31 23:59:59.0제과점영업205764.01735460516.391783제과점영업00아파트지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N49.4<NA><NA><NA>
831000003100000-121-1988-0620119880816<NA>3폐업2폐업20070405<NA><NA><NA>02 973926322.8139873서울특별시 노원구 하계동 271-3번지 벽산@상가 108-1호<NA><NA>크라운베이커리 하계벽산지점2003-08-08 00:00:00I2018-08-31 23:59:59.0제과점영업205601.066016459233.675552제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N22.8<NA><NA><NA>
931000003100000-121-1989-0519319890804<NA>1영업/정상1영업<NA><NA><NA><NA>02 931000897.3139822서울특별시 노원구 상계동 639-1 보람상가 157호서울특별시 노원구 한글비석로 474, 157호 (상계동,보람상가)1671민부곤과자점2021-11-16 16:12:55U2021-11-18 02:40:00.0제과점영업205707.281108462498.174061제과점영업00아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N97.3<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
51631000003100000-121-2024-000042024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.44139-816서울특별시 노원구 상계동 186-3서울특별시 노원구 노원로30길 51, 1층 (상계동)1703맨드라미2024-04-02 16:34:48I2023-12-04 00:04:00.0제과점영업206094.999667461438.664667<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51731000003100000-121-2024-000052024-04-11<NA>3폐업2폐업2024-04-13<NA><NA><NA><NA><NA>139-708서울특별시 노원구 상계동 713 롯데백화점서울특별시 노원구 동일로 1414, 롯데백화점 맞은편 먹거리존 (상계동)1695오오키베이크2024-04-14 04:15:09U2023-12-03 23:06:00.0제과점영업205320.284767461419.881795<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51831000003100000-121-2024-000062024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>59.28139-848서울특별시 노원구 월계동 562 월계아파트형공장서울특별시 노원구 월계로45길 28, 월계아파트형공장 1층 2-4,2-5,2-7호 (월계동)1882파리바게뜨2024-04-24 11:41:39I2023-12-03 22:06:00.0제과점영업204454.974085458289.069882<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51931000003100000-121-2024-000072024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>120.96139-821서울특별시 노원구 상계동 617 화랑빌딩서울특별시 노원구 상계로 64, 화랑빌딩 105, 106호 (상계동)1695뚜레쥬르 카페노원역점2024-04-25 16:31:12I2023-12-03 22:07:00.0제과점영업205430.356783461479.6133<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52031000003100000-121-2024-000082024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>69.9139-240서울특별시 노원구 공릉동 1-1 생도회관<NA><NA>파리바게뜨 생도점2024-05-03 17:14:04I2023-12-05 00:05:00.0제과점영업208761.191288457863.465711<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52131000003100000-121-2024-000092024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>34.35139-240서울특별시 노원구 공릉동 1-1 충무관 1층<NA><NA>파리바게뜨 충무점2024-05-03 17:20:09I2023-12-05 00:05:00.0제과점영업208761.191288457863.465711<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52231000003100000-121-2024-000102024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>48.77139-240서울특별시 노원구 공릉동 1-1 화랑회관 1층<NA><NA>파리바게뜨 화랑회관2024-05-03 17:23:49I2023-12-05 00:05:00.0제과점영업208761.191288457863.465711<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52331000003100000-121-2024-000112024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 화랑빌딩서울특별시 노원구 동일로192길 63, 인근 축제장 (공릉동)1841꽃피앙2024-05-07 12:51:46I2023-12-05 00:09:00.0제과점영업206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52431000003100000-121-2024-000122024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 인근 축제장서울특별시 노원구 동일로192길 63, 인근 축제장 (공릉동)1841Memory2024-05-07 13:24:45I2023-12-05 00:09:00.0제과점영업206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52531000003100000-121-2024-000132024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 인근 축제장서울특별시 노원구 동일로192길 63, 인근 축제장 (공릉동)1841칸텐2024-05-08 09:25:11I2023-12-04 23:00:00.0제과점영업206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>