Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells103649
Missing cells (%)23.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory384.0 B

Variable types

Numeric7
Text7
DateTime4
Unsupported7
Categorical18
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16084/S/1/datasetView.do

Alerts

업태구분명 is highly imbalanced (99.9%)Imbalance
영업장주변구분명 is highly imbalanced (60.4%)Imbalance
등급구분명 is highly imbalanced (60.5%)Imbalance
급수시설구분명 is highly imbalanced (53.1%)Imbalance
총인원 is highly imbalanced (70.7%)Imbalance
본사종업원수 is highly imbalanced (70.3%)Imbalance
공장사무직종업원수 is highly imbalanced (70.3%)Imbalance
공장판매직종업원수 is highly imbalanced (70.3%)Imbalance
공장생산직종업원수 is highly imbalanced (70.3%)Imbalance
보증액 is highly imbalanced (70.3%)Imbalance
월세액 is highly imbalanced (70.3%)Imbalance
다중이용업소여부 is highly imbalanced (90.3%)Imbalance
전통업소지정번호 is highly imbalanced (99.7%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2755 (27.6%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 5228 (52.3%) missing valuesMissing
소재지면적 has 824 (8.2%) missing valuesMissing
도로명주소 has 2757 (27.6%) missing valuesMissing
도로명우편번호 has 2831 (28.3%) missing valuesMissing
좌표정보(X) has 317 (3.2%) missing valuesMissing
좌표정보(Y) has 317 (3.2%) missing valuesMissing
남성종사자수 has 6757 (67.6%) missing valuesMissing
여성종사자수 has 6759 (67.6%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 2527 (25.3%) missing valuesMissing
시설총규모 has 2527 (25.3%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 70.06985335)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 2421 (24.2%) zerosZeros
여성종사자수 has 2322 (23.2%) zerosZeros
시설총규모 has 244 (2.4%) zerosZeros

Reproduction

Analysis started2024-05-17 23:52:37.936358
Analysis finished2024-05-17 23:52:44.280125
Duration6.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3143664
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:52:44.524785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13080000
median3150000
Q33210000
95-th percentile3240000
Maximum3240000
Range240000
Interquartile range (IQR)130000

Descriptive statistics

Standard deviation74502.551
Coefficient of variation (CV)0.023699273
Kurtosis-1.1193362
Mean3143664
Median Absolute Deviation (MAD)70000
Skewness-0.3994625
Sum3.143664 × 1010
Variance5.5506302 × 109
MonotonicityNot monotonic
2024-05-18T08:52:45.045538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 1112
 
11.1%
3240000 776
 
7.8%
3210000 701
 
7.0%
3230000 608
 
6.1%
3130000 514
 
5.1%
3150000 487
 
4.9%
3180000 445
 
4.5%
3140000 437
 
4.4%
3010000 407
 
4.1%
3100000 355
 
3.5%
Other values (15) 4158
41.6%
ValueCountFrequency (%)
3000000 229
2.3%
3010000 407
4.1%
3020000 270
2.7%
3030000 255
2.5%
3040000 304
3.0%
3050000 336
3.4%
3060000 236
2.4%
3070000 325
3.2%
3080000 199
2.0%
3090000 199
2.0%
ValueCountFrequency (%)
3240000 776
7.8%
3230000 608
6.1%
3220000 1112
11.1%
3210000 701
7.0%
3200000 311
 
3.1%
3190000 281
 
2.8%
3180000 445
4.5%
3170000 285
 
2.9%
3160000 321
 
3.2%
3150000 487
4.9%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T08:52:45.669770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row3210000-121-2002-00044
2nd row3180000-121-2022-00007
3rd row3060000-121-2011-00013
4th row3200000-121-2004-00013
5th row3240000-121-1983-05061
ValueCountFrequency (%)
3210000-121-2002-00044 1
 
< 0.1%
3180000-121-2014-00001 1
 
< 0.1%
3050000-121-1995-09867 1
 
< 0.1%
3050000-121-2010-00021 1
 
< 0.1%
3070000-121-1994-09012 1
 
< 0.1%
3180000-121-2014-00021 1
 
< 0.1%
3130000-121-2008-00006 1
 
< 0.1%
3100000-121-2024-00012 1
 
< 0.1%
3220000-121-2022-00130 1
 
< 0.1%
3220000-121-2005-00096 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-18T08:52:46.655734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86797
39.5%
1 36003
16.4%
- 30000
 
13.6%
2 29747
 
13.5%
3 14499
 
6.6%
9 5559
 
2.5%
4 4505
 
2.0%
8 3479
 
1.6%
5 3298
 
1.5%
7 3062
 
1.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86797
45.7%
1 36003
18.9%
2 29747
 
15.7%
3 14499
 
7.6%
9 5559
 
2.9%
4 4505
 
2.4%
8 3479
 
1.8%
5 3298
 
1.7%
7 3062
 
1.6%
6 3051
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86797
39.5%
1 36003
16.4%
- 30000
 
13.6%
2 29747
 
13.5%
3 14499
 
6.6%
9 5559
 
2.5%
4 4505
 
2.0%
8 3479
 
1.6%
5 3298
 
1.5%
7 3062
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86797
39.5%
1 36003
16.4%
- 30000
 
13.6%
2 29747
 
13.5%
3 14499
 
6.6%
9 5559
 
2.5%
4 4505
 
2.0%
8 3479
 
1.6%
5 3298
 
1.5%
7 3062
 
1.4%
Distinct5648
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1952-05-13 00:00:00
Maximum2024-05-16 00:00:00
2024-05-18T08:52:47.324964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:52:48.147607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
7245 
1
2755 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7245
72.5%
1 2755
 
27.6%

Length

2024-05-18T08:52:48.650221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:52:49.033444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7245
72.5%
1 2755
 
27.6%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7245 
영업/정상
2755 

Length

Max length5
Median length2
Mean length2.8265
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7245
72.5%
영업/정상 2755
 
27.6%

Length

2024-05-18T08:52:49.505970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:52:49.987190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7245
72.5%
영업/정상 2755
 
27.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7245 
1
2755 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7245
72.5%
1 2755
 
27.6%

Length

2024-05-18T08:52:50.680173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:52:51.121474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7245
72.5%
1 2755
 
27.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7245 
영업
2755 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7245
72.5%
영업 2755
 
27.6%

Length

2024-05-18T08:52:51.719878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:52:52.267142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7245
72.5%
영업 2755
 
27.6%

폐업일자
Date

MISSING 

Distinct3754
Distinct (%)51.8%
Missing2755
Missing (%)27.6%
Memory size156.2 KiB
Minimum1984-12-07 00:00:00
Maximum2024-05-14 00:00:00
2024-05-18T08:52:52.851310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:52:53.642726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전화번호
Text

MISSING 

Distinct4248
Distinct (%)89.0%
Missing5228
Missing (%)52.3%
Memory size156.2 KiB
2024-05-18T08:52:55.052276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.267184
Min length2

Characters and Unicode

Total characters48995
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

Unique4035 ?
Unique (%)84.6%

Sample

1st row070 71237600
2nd row02 8822654
3rd row0204720850
4th row02 9152603
5th row02 517 9346
ValueCountFrequency (%)
02 2977
34.3%
070 96
 
1.1%
031 74
 
0.9%
0200000000 52
 
0.6%
525 21
 
0.2%
0 18
 
0.2%
728 16
 
0.2%
4882233 14
 
0.2%
532 13
 
0.1%
6011 12
 
0.1%
Other values (4546) 5390
62.1%
2024-05-18T08:52:56.911468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9151
18.7%
2 8400
17.1%
5102
10.4%
4 3737
7.6%
3 3602
 
7.4%
8 3331
 
6.8%
5 3325
 
6.8%
6 3219
 
6.6%
7 3194
 
6.5%
1 2967
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43893
89.6%
Space Separator 5102
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9151
20.8%
2 8400
19.1%
4 3737
8.5%
3 3602
 
8.2%
8 3331
 
7.6%
5 3325
 
7.6%
6 3219
 
7.3%
7 3194
 
7.3%
1 2967
 
6.8%
9 2967
 
6.8%
Space Separator
ValueCountFrequency (%)
5102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48995
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9151
18.7%
2 8400
17.1%
5102
10.4%
4 3737
7.6%
3 3602
 
7.4%
8 3331
 
6.8%
5 3325
 
6.8%
6 3219
 
6.6%
7 3194
 
6.5%
1 2967
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48995
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9151
18.7%
2 8400
17.1%
5102
10.4%
4 3737
7.6%
3 3602
 
7.4%
8 3331
 
6.8%
5 3325
 
6.8%
6 3219
 
6.6%
7 3194
 
6.5%
1 2967
 
6.1%

소재지면적
Text

MISSING 

Distinct3947
Distinct (%)43.0%
Missing824
Missing (%)8.2%
Memory size156.2 KiB
2024-05-18T08:52:58.259269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.9667611
Min length3

Characters and Unicode

Total characters45575
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2676 ?
Unique (%)29.2%

Sample

1st row8.25
2nd row3.00
3rd row31.60
4th row23.51
5th row29.70
ValueCountFrequency (%)
33.00 168
 
1.8%
6.60 152
 
1.7%
30.00 123
 
1.3%
3.30 115
 
1.3%
00 96
 
1.0%
10.00 92
 
1.0%
26.40 89
 
1.0%
9.90 83
 
0.9%
20.00 83
 
0.9%
16.50 64
 
0.7%
Other values (3937) 8111
88.4%
2024-05-18T08:53:00.031563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9176
20.1%
0 8746
19.2%
2 4180
9.2%
3 3798
8.3%
1 3664
 
8.0%
6 3271
 
7.2%
4 3101
 
6.8%
5 3005
 
6.6%
9 2400
 
5.3%
8 2250
 
4.9%
Other values (2) 1984
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36395
79.9%
Other Punctuation 9180
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8746
24.0%
2 4180
11.5%
3 3798
10.4%
1 3664
10.1%
6 3271
 
9.0%
4 3101
 
8.5%
5 3005
 
8.3%
9 2400
 
6.6%
8 2250
 
6.2%
7 1980
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 9176
> 99.9%
, 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 45575
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9176
20.1%
0 8746
19.2%
2 4180
9.2%
3 3798
8.3%
1 3664
 
8.0%
6 3271
 
7.2%
4 3101
 
6.8%
5 3005
 
6.6%
9 2400
 
5.3%
8 2250
 
4.9%
Other values (2) 1984
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45575
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9176
20.1%
0 8746
19.2%
2 4180
9.2%
3 3798
8.3%
1 3664
 
8.0%
6 3271
 
7.2%
4 3101
 
6.8%
5 3005
 
6.6%
9 2400
 
5.3%
8 2250
 
4.9%
Other values (2) 1984
 
4.4%
Distinct2802
Distinct (%)28.1%
Missing25
Missing (%)0.2%
Memory size156.2 KiB
2024-05-18T08:53:00.952456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1630075
Min length6

Characters and Unicode

Total characters61476
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

Unique1092 ?
Unique (%)10.9%

Sample

1st row137713
2nd row150875
3rd row131-872
4th row151810
5th row134830
ValueCountFrequency (%)
137713 154
 
1.5%
100011 93
 
0.9%
158050 80
 
0.8%
135090 68
 
0.7%
134830 60
 
0.6%
135902 55
 
0.6%
134874 51
 
0.5%
135724 47
 
0.5%
135730 47
 
0.5%
100070 46
 
0.5%
Other values (2792) 9274
93.0%
2024-05-18T08:53:02.608886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13966
22.7%
8 8830
14.4%
3 7851
12.8%
0 6976
11.3%
5 5620
9.1%
2 4421
 
7.2%
7 3693
 
6.0%
4 3458
 
5.6%
9 2816
 
4.6%
6 2219
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59850
97.4%
Dash Punctuation 1626
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13966
23.3%
8 8830
14.8%
3 7851
13.1%
0 6976
11.7%
5 5620
9.4%
2 4421
 
7.4%
7 3693
 
6.2%
4 3458
 
5.8%
9 2816
 
4.7%
6 2219
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 1626
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61476
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13966
22.7%
8 8830
14.4%
3 7851
12.8%
0 6976
11.3%
5 5620
9.1%
2 4421
 
7.2%
7 3693
 
6.0%
4 3458
 
5.6%
9 2816
 
4.6%
6 2219
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13966
22.7%
8 8830
14.4%
3 7851
12.8%
0 6976
11.3%
5 5620
9.1%
2 4421
 
7.2%
7 3693
 
6.0%
4 3458
 
5.6%
9 2816
 
4.6%
6 2219
 
3.6%
Distinct8604
Distinct (%)86.3%
Missing25
Missing (%)0.2%
Memory size156.2 KiB
2024-05-18T08:53:03.805943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length54
Mean length26.961704
Min length14

Characters and Unicode

Total characters268943
Distinct characters604
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8194 ?
Unique (%)82.1%

Sample

1st row서울특별시 서초구 반포동 19-3번지 신세계백화점 지하1층
2nd row서울특별시 영등포구 여의도동 22 파크원
3rd row서울특별시 중랑구 신내동 645
4th row서울특별시 관악구 봉천동 36-2번지 지상1층
5th row서울특별시 강동구 명일동 324-2번지
ValueCountFrequency (%)
서울특별시 9973
 
19.8%
1층 1249
 
2.5%
강남구 1109
 
2.2%
강동구 776
 
1.5%
서초구 701
 
1.4%
송파구 608
 
1.2%
지상1층 590
 
1.2%
지하1층 583
 
1.2%
마포구 509
 
1.0%
강서구 487
 
1.0%
Other values (10591) 33773
67.1%
2024-05-18T08:53:05.435976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47353
 
17.6%
1 13378
 
5.0%
12081
 
4.5%
11829
 
4.4%
10826
 
4.0%
10346
 
3.8%
10038
 
3.7%
9975
 
3.7%
9974
 
3.7%
8547
 
3.2%
Other values (594) 124596
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159049
59.1%
Decimal Number 51168
 
19.0%
Space Separator 47353
 
17.6%
Dash Punctuation 8007
 
3.0%
Open Punctuation 947
 
0.4%
Close Punctuation 946
 
0.4%
Uppercase Letter 735
 
0.3%
Other Punctuation 599
 
0.2%
Lowercase Letter 79
 
< 0.1%
Math Symbol 47
 
< 0.1%
Other values (2) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12081
 
7.6%
11829
 
7.4%
10826
 
6.8%
10346
 
6.5%
10038
 
6.3%
9975
 
6.3%
9974
 
6.3%
8547
 
5.4%
6156
 
3.9%
3432
 
2.2%
Other values (520) 65845
41.4%
Uppercase Letter
ValueCountFrequency (%)
B 171
23.3%
A 103
14.0%
S 68
 
9.3%
C 54
 
7.3%
T 42
 
5.7%
E 33
 
4.5%
G 33
 
4.5%
K 31
 
4.2%
D 28
 
3.8%
I 26
 
3.5%
Other values (16) 146
19.9%
Lowercase Letter
ValueCountFrequency (%)
e 19
24.1%
a 9
11.4%
s 6
 
7.6%
n 6
 
7.6%
u 4
 
5.1%
b 4
 
5.1%
r 3
 
3.8%
h 3
 
3.8%
l 3
 
3.8%
o 3
 
3.8%
Other values (11) 19
24.1%
Decimal Number
ValueCountFrequency (%)
1 13378
26.1%
2 6547
12.8%
3 5031
 
9.8%
0 4702
 
9.2%
4 4692
 
9.2%
5 3927
 
7.7%
9 3538
 
6.9%
6 3529
 
6.9%
7 3135
 
6.1%
8 2689
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 513
85.6%
. 55
 
9.2%
@ 18
 
3.0%
? 6
 
1.0%
/ 5
 
0.8%
: 1
 
0.2%
& 1
 
0.2%
Letter Number
ValueCountFrequency (%)
8
66.7%
3
 
25.0%
1
 
8.3%
Math Symbol
ValueCountFrequency (%)
~ 46
97.9%
> 1
 
2.1%
Space Separator
ValueCountFrequency (%)
47353
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8007
100.0%
Open Punctuation
ValueCountFrequency (%)
( 947
100.0%
Close Punctuation
ValueCountFrequency (%)
) 946
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 159050
59.1%
Common 109067
40.6%
Latin 826
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12081
 
7.6%
11829
 
7.4%
10826
 
6.8%
10346
 
6.5%
10038
 
6.3%
9975
 
6.3%
9974
 
6.3%
8547
 
5.4%
6156
 
3.9%
3432
 
2.2%
Other values (521) 65846
41.4%
Latin
ValueCountFrequency (%)
B 171
20.7%
A 103
12.5%
S 68
 
8.2%
C 54
 
6.5%
T 42
 
5.1%
E 33
 
4.0%
G 33
 
4.0%
K 31
 
3.8%
D 28
 
3.4%
I 26
 
3.1%
Other values (40) 237
28.7%
Common
ValueCountFrequency (%)
47353
43.4%
1 13378
 
12.3%
- 8007
 
7.3%
2 6547
 
6.0%
3 5031
 
4.6%
0 4702
 
4.3%
4 4692
 
4.3%
5 3927
 
3.6%
9 3538
 
3.2%
6 3529
 
3.2%
Other values (13) 8363
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159047
59.1%
ASCII 109881
40.9%
Number Forms 12
 
< 0.1%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47353
43.1%
1 13378
 
12.2%
- 8007
 
7.3%
2 6547
 
6.0%
3 5031
 
4.6%
0 4702
 
4.3%
4 4692
 
4.3%
5 3927
 
3.6%
9 3538
 
3.2%
6 3529
 
3.2%
Other values (60) 9177
 
8.4%
Hangul
ValueCountFrequency (%)
12081
 
7.6%
11829
 
7.4%
10826
 
6.8%
10346
 
6.5%
10038
 
6.3%
9975
 
6.3%
9974
 
6.3%
8547
 
5.4%
6156
 
3.9%
3432
 
2.2%
Other values (518) 65843
41.4%
Number Forms
ValueCountFrequency (%)
8
66.7%
3
 
25.0%
1
 
8.3%
None
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct6287
Distinct (%)86.8%
Missing2757
Missing (%)27.6%
Memory size156.2 KiB
2024-05-18T08:53:06.464546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length58
Mean length35.257352
Min length21

Characters and Unicode

Total characters255369
Distinct characters625
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6039 ?
Unique (%)83.4%

Sample

1st row서울특별시 영등포구 여의대로 108, 더현대서울 지하1층 (여의도동)
2nd row서울특별시 중랑구 신내로 201, 지하1층 (신내동, 홈플러스신내점)
3rd row서울특별시 성북구 삼양로 50 (길음동)
4th row서울특별시 강남구 압구정로 343, 갤러리아백화점 지하1층 (압구정동)
5th row서울특별시 노원구 한글비석로 242, 삼부프라자 1층 118호 (중계동)
ValueCountFrequency (%)
서울특별시 7242
 
14.8%
1층 2393
 
4.9%
지하1층 1291
 
2.6%
강남구 1007
 
2.1%
서초구 542
 
1.1%
지상1층 459
 
0.9%
송파구 449
 
0.9%
마포구 440
 
0.9%
영등포구 376
 
0.8%
강서구 372
 
0.8%
Other values (7480) 34450
70.3%
2024-05-18T08:53:07.741878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41814
 
16.4%
1 13550
 
5.3%
9686
 
3.8%
9100
 
3.6%
, 8554
 
3.3%
8271
 
3.2%
7822
 
3.1%
) 7582
 
3.0%
( 7581
 
3.0%
7551
 
3.0%
Other values (615) 133858
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148610
58.2%
Space Separator 41814
 
16.4%
Decimal Number 39161
 
15.3%
Other Punctuation 8605
 
3.4%
Close Punctuation 7583
 
3.0%
Open Punctuation 7582
 
3.0%
Uppercase Letter 924
 
0.4%
Dash Punctuation 911
 
0.4%
Lowercase Letter 106
 
< 0.1%
Math Symbol 61
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9686
 
6.5%
9100
 
6.1%
8271
 
5.6%
7822
 
5.3%
7551
 
5.1%
7404
 
5.0%
7245
 
4.9%
7245
 
4.9%
5862
 
3.9%
3302
 
2.2%
Other values (538) 75122
50.5%
Uppercase Letter
ValueCountFrequency (%)
B 282
30.5%
A 97
 
10.5%
S 83
 
9.0%
C 64
 
6.9%
T 53
 
5.7%
E 51
 
5.5%
D 37
 
4.0%
G 33
 
3.6%
W 28
 
3.0%
K 25
 
2.7%
Other values (16) 171
18.5%
Lowercase Letter
ValueCountFrequency (%)
e 26
24.5%
s 10
 
9.4%
a 9
 
8.5%
l 7
 
6.6%
t 6
 
5.7%
n 6
 
5.7%
w 5
 
4.7%
f 4
 
3.8%
u 4
 
3.8%
b 4
 
3.8%
Other values (10) 25
23.6%
Decimal Number
ValueCountFrequency (%)
1 13550
34.6%
2 5155
 
13.2%
0 3816
 
9.7%
3 3734
 
9.5%
5 2702
 
6.9%
4 2627
 
6.7%
6 2311
 
5.9%
7 2219
 
5.7%
8 1686
 
4.3%
9 1361
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 8554
99.4%
. 35
 
0.4%
? 7
 
0.1%
@ 5
 
0.1%
* 1
 
< 0.1%
& 1
 
< 0.1%
: 1
 
< 0.1%
/ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 59
96.7%
+ 1
 
1.6%
> 1
 
1.6%
Letter Number
ValueCountFrequency (%)
7
63.6%
3
27.3%
1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 7582
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 7581
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
41814
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 911
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 148610
58.2%
Common 105717
41.4%
Latin 1041
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9686
 
6.5%
9100
 
6.1%
8271
 
5.6%
7822
 
5.3%
7551
 
5.1%
7404
 
5.0%
7245
 
4.9%
7245
 
4.9%
5862
 
3.9%
3302
 
2.2%
Other values (538) 75122
50.5%
Latin
ValueCountFrequency (%)
B 282
27.1%
A 97
 
9.3%
S 83
 
8.0%
C 64
 
6.1%
T 53
 
5.1%
E 51
 
4.9%
D 37
 
3.6%
G 33
 
3.2%
W 28
 
2.7%
e 26
 
2.5%
Other values (39) 287
27.6%
Common
ValueCountFrequency (%)
41814
39.6%
1 13550
 
12.8%
, 8554
 
8.1%
) 7582
 
7.2%
( 7581
 
7.2%
2 5155
 
4.9%
0 3816
 
3.6%
3 3734
 
3.5%
5 2702
 
2.6%
4 2627
 
2.5%
Other values (17) 8602
 
8.1%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148607
58.2%
ASCII 106747
41.8%
Number Forms 11
 
< 0.1%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41814
39.2%
1 13550
 
12.7%
, 8554
 
8.0%
) 7582
 
7.1%
( 7581
 
7.1%
2 5155
 
4.8%
0 3816
 
3.6%
3 3734
 
3.5%
5 2702
 
2.5%
4 2627
 
2.5%
Other values (63) 9632
 
9.0%
Hangul
ValueCountFrequency (%)
9686
 
6.5%
9100
 
6.1%
8271
 
5.6%
7822
 
5.3%
7551
 
5.1%
7404
 
5.0%
7245
 
4.9%
7245
 
4.9%
5862
 
3.9%
3302
 
2.2%
Other values (535) 75119
50.5%
Number Forms
ValueCountFrequency (%)
7
63.6%
3
27.3%
1
 
9.1%
None
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct2732
Distinct (%)38.1%
Missing2831
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean5353.3431
Minimum1005
Maximum11930
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:53:08.208698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1005
5-th percentile1714.4
Q13984
median5564
Q36797
95-th percentile8323
Maximum11930
Range10925
Interquartile range (IQR)2813

Descriptive statistics

Standard deviation1993.7827
Coefficient of variation (CV)0.37243694
Kurtosis-0.76120175
Mean5353.3431
Median Absolute Deviation (MAD)1494
Skewness-0.2682047
Sum38378117
Variance3975169.6
MonotonicityNot monotonic
2024-05-18T08:53:08.678130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6546 185
 
1.8%
6164 158
 
1.6%
6001 114
 
1.1%
6008 113
 
1.1%
4530 108
 
1.1%
7998 82
 
0.8%
7335 67
 
0.7%
5554 56
 
0.6%
4533 50
 
0.5%
2730 48
 
0.5%
Other values (2722) 6188
61.9%
(Missing) 2831
28.3%
ValueCountFrequency (%)
1005 1
< 0.1%
1011 2
< 0.1%
1014 1
< 0.1%
1026 2
< 0.1%
1030 2
< 0.1%
1031 1
< 0.1%
1034 1
< 0.1%
1038 1
< 0.1%
1044 1
< 0.1%
1045 1
< 0.1%
ValueCountFrequency (%)
11930 1
 
< 0.1%
8864 5
0.1%
8861 3
< 0.1%
8860 2
 
< 0.1%
8859 1
 
< 0.1%
8858 1
 
< 0.1%
8857 1
 
< 0.1%
8856 1
 
< 0.1%
8855 2
 
< 0.1%
8854 2
 
< 0.1%
Distinct7775
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T08:53:09.238035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length7.9876
Min length1

Characters and Unicode

Total characters79876
Distinct characters958
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6905 ?
Unique (%)69.0%

Sample

1st row에구찌
2nd row얀쿠브레
3rd row몽블랑제(주)신내점행사매대
4th row크라운베이커리봉천우성점
5th row거북당
ValueCountFrequency (%)
파리바게뜨 363
 
2.6%
뚜레쥬르 266
 
1.9%
베이커리 162
 
1.2%
파리바게트 107
 
0.8%
던킨도너츠 86
 
0.6%
크라운베이커리 78
 
0.6%
빵굼터 53
 
0.4%
브레댄코 45
 
0.3%
주식회사 44
 
0.3%
핫브레드 43
 
0.3%
Other values (8272) 12553
91.0%
2024-05-18T08:53:10.389122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3809
 
4.8%
3293
 
4.1%
3040
 
3.8%
2703
 
3.4%
) 1709
 
2.1%
( 1707
 
2.1%
1601
 
2.0%
1480
 
1.9%
1327
 
1.7%
1305
 
1.6%
Other values (948) 57902
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64656
80.9%
Lowercase Letter 4145
 
5.2%
Space Separator 3809
 
4.8%
Uppercase Letter 2962
 
3.7%
Close Punctuation 1709
 
2.1%
Open Punctuation 1707
 
2.1%
Decimal Number 628
 
0.8%
Other Punctuation 218
 
0.3%
Dash Punctuation 33
 
< 0.1%
Connector Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3293
 
5.1%
3040
 
4.7%
2703
 
4.2%
1601
 
2.5%
1480
 
2.3%
1327
 
2.1%
1305
 
2.0%
1077
 
1.7%
1049
 
1.6%
1012
 
1.6%
Other values (870) 46769
72.3%
Lowercase Letter
ValueCountFrequency (%)
e 613
14.8%
a 466
11.2%
o 374
 
9.0%
r 310
 
7.5%
n 287
 
6.9%
i 256
 
6.2%
l 208
 
5.0%
t 200
 
4.8%
s 173
 
4.2%
u 158
 
3.8%
Other values (16) 1100
26.5%
Uppercase Letter
ValueCountFrequency (%)
B 277
 
9.4%
E 269
 
9.1%
A 269
 
9.1%
S 164
 
5.5%
O 159
 
5.4%
C 159
 
5.4%
T 152
 
5.1%
N 151
 
5.1%
R 147
 
5.0%
I 135
 
4.6%
Other values (16) 1080
36.5%
Decimal Number
ValueCountFrequency (%)
2 159
25.3%
1 114
18.2%
3 77
12.3%
0 57
 
9.1%
5 49
 
7.8%
9 49
 
7.8%
4 41
 
6.5%
7 35
 
5.6%
8 28
 
4.5%
6 19
 
3.0%
Other Punctuation
ValueCountFrequency (%)
? 57
26.1%
& 53
24.3%
. 47
21.6%
' 33
15.1%
, 17
 
7.8%
! 4
 
1.8%
# 3
 
1.4%
: 2
 
0.9%
@ 1
 
0.5%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
3809
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1709
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1707
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64640
80.9%
Common 8113
 
10.2%
Latin 7107
 
8.9%
Han 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3293
 
5.1%
3040
 
4.7%
2703
 
4.2%
1601
 
2.5%
1480
 
2.3%
1327
 
2.1%
1305
 
2.0%
1077
 
1.7%
1049
 
1.6%
1012
 
1.6%
Other values (860) 46753
72.3%
Latin
ValueCountFrequency (%)
e 613
 
8.6%
a 466
 
6.6%
o 374
 
5.3%
r 310
 
4.4%
n 287
 
4.0%
B 277
 
3.9%
E 269
 
3.8%
A 269
 
3.8%
i 256
 
3.6%
l 208
 
2.9%
Other values (42) 3778
53.2%
Common
ValueCountFrequency (%)
3809
46.9%
) 1709
21.1%
( 1707
21.0%
2 159
 
2.0%
1 114
 
1.4%
3 77
 
0.9%
? 57
 
0.7%
0 57
 
0.7%
& 53
 
0.7%
5 49
 
0.6%
Other values (16) 322
 
4.0%
Han
ValueCountFrequency (%)
3
18.8%
2
12.5%
2
12.5%
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64640
80.9%
ASCII 15220
 
19.1%
CJK 16
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3809
25.0%
) 1709
 
11.2%
( 1707
 
11.2%
e 613
 
4.0%
a 466
 
3.1%
o 374
 
2.5%
r 310
 
2.0%
n 287
 
1.9%
B 277
 
1.8%
E 269
 
1.8%
Other values (68) 5399
35.5%
Hangul
ValueCountFrequency (%)
3293
 
5.1%
3040
 
4.7%
2703
 
4.2%
1601
 
2.5%
1480
 
2.3%
1327
 
2.1%
1305
 
2.0%
1077
 
1.7%
1049
 
1.6%
1012
 
1.6%
Other values (860) 46753
72.3%
CJK
ValueCountFrequency (%)
3
18.8%
2
12.5%
2
12.5%
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Distinct8829
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-11 00:00:00
Maximum2024-05-16 20:45:16
2024-05-18T08:53:10.875221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:53:11.366514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6136 
U
3864 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6136
61.4%
U 3864
38.6%

Length

2024-05-18T08:53:11.780756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:12.089923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6136
61.4%
u 3864
38.6%
Distinct1595
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-18T08:53:12.482811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:53:12.988646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제과점영업
9999 
푸드트럭
 
1

Length

Max length5
Median length5
Mean length4.9999
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 9999
> 99.9%
푸드트럭 1
 
< 0.1%

Length

2024-05-18T08:53:13.413583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:13.758664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 9999
> 99.9%
푸드트럭 1
 
< 0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct6524
Distinct (%)67.4%
Missing317
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean199707.03
Minimum182141.21
Maximum216029.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:53:14.119190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile186837.88
Q1193252.69
median200841.73
Q3205210.36
95-th percentile211788.61
Maximum216029.39
Range33888.183
Interquartile range (IQR)11957.664

Descriptive statistics

Standard deviation7635.4585
Coefficient of variation (CV)0.038233299
Kurtosis-0.89993085
Mean199707.03
Median Absolute Deviation (MAD)6028.7151
Skewness-0.15181161
Sum1.9337631 × 109
Variance58300226
MonotonicityNot monotonic
2024-05-18T08:53:14.548702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200250.447804795 213
 
2.1%
205210.358779172 134
 
1.3%
202358.505687227 119
 
1.2%
203470.848439305 114
 
1.1%
188884.075622342 97
 
1.0%
198263.90839194 83
 
0.8%
208589.363343145 68
 
0.7%
193592.000380036 67
 
0.7%
198259.65357739 56
 
0.6%
194265.067639805 50
 
0.5%
Other values (6514) 8682
86.8%
(Missing) 317
 
3.2%
ValueCountFrequency (%)
182141.205465089 2
 
< 0.1%
182524.823835629 18
0.2%
182846.62641593 1
 
< 0.1%
182876.367858149 2
 
< 0.1%
182908.975451896 1
 
< 0.1%
182914.770762913 1
 
< 0.1%
182944.731406147 2
 
< 0.1%
182957.325956453 1
 
< 0.1%
182974.850127567 3
 
< 0.1%
182984.891498757 1
 
< 0.1%
ValueCountFrequency (%)
216029.388021 1
< 0.1%
215743.278884315 1
< 0.1%
215422.746119624 1
< 0.1%
215384.844269 1
< 0.1%
215289.815449411 1
< 0.1%
215277.575586465 1
< 0.1%
215257.766510608 1
< 0.1%
215254.0 1
< 0.1%
215212.625424847 1
< 0.1%
215181.448713688 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct6524
Distinct (%)67.4%
Missing317
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean448936.09
Minimum436911.77
Maximum465524.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:53:15.255993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436911.77
5-th percentile441833.41
Q1445037.75
median448340.7
Q3451596.67
95-th percentile459685.15
Maximum465524.59
Range28612.818
Interquartile range (IQR)6558.9157

Descriptive statistics

Standard deviation5201.8341
Coefficient of variation (CV)0.011587026
Kurtosis0.085333606
Mean448936.09
Median Absolute Deviation (MAD)3286.2904
Skewness0.64815536
Sum4.3470482 × 109
Variance27059078
MonotonicityNot monotonic
2024-05-18T08:53:15.855006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444683.220506107 213
 
2.1%
445154.42225208 134
 
1.3%
447232.955697694 119
 
1.2%
447369.579851952 114
 
1.1%
447186.888604306 97
 
1.0%
450960.762964932 83
 
0.8%
445455.90405262 68
 
0.7%
447092.629432527 67
 
0.7%
451392.198218657 56
 
0.6%
450433.691021245 50
 
0.5%
Other values (6514) 8682
86.8%
(Missing) 317
 
3.2%
ValueCountFrequency (%)
436911.774494656 1
< 0.1%
437562.242368734 1
< 0.1%
437601.753603288 1
< 0.1%
437602.625094324 2
< 0.1%
438266.70898504 2
< 0.1%
438307.423372216 1
< 0.1%
438365.613175801 2
< 0.1%
438410.522111193 2
< 0.1%
438436.109390506 1
< 0.1%
438438.498339338 1
< 0.1%
ValueCountFrequency (%)
465524.592030404 1
< 0.1%
465180.671733594 1
< 0.1%
465042.493324016 1
< 0.1%
465011.262691591 1
< 0.1%
464932.504318827 1
< 0.1%
464920.0 1
< 0.1%
464866.74995962 1
< 0.1%
464814.717432497 1
< 0.1%
464767.746320978 1
< 0.1%
464654.516411871 1
< 0.1%

위생업태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제과점영업
7473 
<NA>
2527 

Length

Max length5
Median length5
Mean length4.7473
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 7473
74.7%
<NA> 2527
 
25.3%

Length

2024-05-18T08:53:16.384872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:16.704112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 7473
74.7%
na 2527
 
25.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.3%
Missing6757
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean0.36293555
Minimum0
Maximum10
Zeros2421
Zeros (%)24.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:53:17.012285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.75618463
Coefficient of variation (CV)2.0835232
Kurtosis20.234355
Mean0.36293555
Median Absolute Deviation (MAD)0
Skewness3.3359089
Sum1177
Variance0.57181519
MonotonicityNot monotonic
2024-05-18T08:53:17.403925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 2421
 
24.2%
1 574
 
5.7%
2 183
 
1.8%
3 43
 
0.4%
4 14
 
0.1%
5 3
 
< 0.1%
6 3
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 6757
67.6%
ValueCountFrequency (%)
0 2421
24.2%
1 574
 
5.7%
2 183
 
1.8%
3 43
 
0.4%
4 14
 
0.1%
5 3
 
< 0.1%
6 3
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
9 1
 
< 0.1%
6 3
 
< 0.1%
5 3
 
< 0.1%
4 14
 
0.1%
3 43
 
0.4%
2 183
 
1.8%
1 574
 
5.7%
0 2421
24.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)0.4%
Missing6759
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean0.43227399
Minimum0
Maximum15
Zeros2322
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:53:17.854183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.88355765
Coefficient of variation (CV)2.043976
Kurtosis36.691072
Mean0.43227399
Median Absolute Deviation (MAD)0
Skewness4.150947
Sum1401
Variance0.78067412
MonotonicityNot monotonic
2024-05-18T08:53:18.316140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 2322
 
23.2%
1 608
 
6.1%
2 214
 
2.1%
3 68
 
0.7%
4 13
 
0.1%
5 7
 
0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 6759
67.6%
ValueCountFrequency (%)
0 2322
23.2%
1 608
 
6.1%
2 214
 
2.1%
3 68
 
0.7%
4 13
 
0.1%
5 7
 
0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
10 1
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
7 2
 
< 0.1%
6 3
 
< 0.1%
5 7
 
0.1%
4 13
 
0.1%
3 68
 
0.7%
2 214
2.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7762 
주택가주변
920 
기타
834 
아파트지역
 
274
학교정화(상대)
 
97
Other values (3)
 
113

Length

Max length8
Median length4
Mean length4.0358
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7762
77.6%
주택가주변 920
 
9.2%
기타 834
 
8.3%
아파트지역 274
 
2.7%
학교정화(상대) 97
 
1.0%
유흥업소밀집지역 95
 
0.9%
학교정화(절대) 10
 
0.1%
결혼예식장주변 8
 
0.1%

Length

2024-05-18T08:53:18.828203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:19.307755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7762
77.6%
주택가주변 920
 
9.2%
기타 834
 
8.3%
아파트지역 274
 
2.7%
학교정화(상대 97
 
1.0%
유흥업소밀집지역 95
 
0.9%
학교정화(절대 10
 
0.1%
결혼예식장주변 8
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7914 
기타
 
726
자율
 
685
지도
 
323
 
216
Other values (3)
 
136

Length

Max length4
Median length4
Mean length3.5521
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7914
79.1%
기타 726
 
7.3%
자율 685
 
6.9%
지도 323
 
3.2%
216
 
2.2%
91
 
0.9%
우수 38
 
0.4%
관리 7
 
0.1%

Length

2024-05-18T08:53:19.697559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:20.061062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7914
79.1%
기타 726
 
7.3%
자율 685
 
6.9%
지도 323
 
3.2%
216
 
2.2%
91
 
0.9%
우수 38
 
0.4%
관리 7
 
0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6564 
상수도전용
3426 
상수도(음용)지하수(주방용)겸용
 
7
지하수전용
 
3

Length

Max length17
Median length4
Mean length4.352
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6564
65.6%
상수도전용 3426
34.3%
상수도(음용)지하수(주방용)겸용 7
 
0.1%
지하수전용 3
 
< 0.1%

Length

2024-05-18T08:53:20.561791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:20.960397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6564
65.6%
상수도전용 3426
34.3%
상수도(음용)지하수(주방용)겸용 7
 
0.1%
지하수전용 3
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9485 
0
 
515

Length

Max length4
Median length4
Mean length3.8455
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9485
94.8%
0 515
 
5.1%

Length

2024-05-18T08:53:21.326794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:21.729941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9485
94.8%
0 515
 
5.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9474 
0
 
526

Length

Max length4
Median length4
Mean length3.8422
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9474
94.7%
0 526
 
5.3%

Length

2024-05-18T08:53:22.165310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:22.495828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9474
94.7%
0 526
 
5.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9474 
0
 
526

Length

Max length4
Median length4
Mean length3.8422
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9474
94.7%
0 526
 
5.3%

Length

2024-05-18T08:53:22.979191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:23.366656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9474
94.7%
0 526
 
5.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9474 
0
 
526

Length

Max length4
Median length4
Mean length3.8422
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9474
94.7%
0 526
 
5.3%

Length

2024-05-18T08:53:23.822899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:24.323430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9474
94.7%
0 526
 
5.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9474 
0
 
526

Length

Max length4
Median length4
Mean length3.8422
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9474
94.7%
0 526
 
5.3%

Length

2024-05-18T08:53:24.630725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:24.984746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9474
94.7%
0 526
 
5.3%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9474 
0
 
526

Length

Max length4
Median length4
Mean length3.8422
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9474
94.7%
0 526
 
5.3%

Length

2024-05-18T08:53:25.421619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:25.885979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9474
94.7%
0 526
 
5.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9474 
0
 
526

Length

Max length4
Median length4
Mean length3.8422
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9474
94.7%
0 526
 
5.3%

Length

2024-05-18T08:53:26.303778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:26.755101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9474
94.7%
0 526
 
5.3%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing2527
Missing (%)25.3%
Memory size97.7 KiB
False
7379 
True
 
94
(Missing)
2527 
ValueCountFrequency (%)
False 7379
73.8%
True 94
 
0.9%
(Missing) 2527
 
25.3%
2024-05-18T08:53:27.073784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct3319
Distinct (%)44.4%
Missing2527
Missing (%)25.3%
Infinite0
Infinite (%)0.0%
Mean83.78402
Minimum0
Maximum184133
Zeros244
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T08:53:27.557806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q120.25
median33
Q354.68
95-th percentile125.274
Maximum184133
Range184133
Interquartile range (IQR)34.43

Descriptive statistics

Standard deviation2357.1947
Coefficient of variation (CV)28.134181
Kurtosis5201.7454
Mean83.78402
Median Absolute Deviation (MAD)16.05
Skewness70.069853
Sum626117.98
Variance5556367
MonotonicityNot monotonic
2024-05-18T08:53:28.163713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 244
 
2.4%
33.0 134
 
1.3%
6.6 110
 
1.1%
30.0 95
 
0.9%
3.3 77
 
0.8%
26.4 77
 
0.8%
9.9 71
 
0.7%
10.0 59
 
0.6%
20.0 53
 
0.5%
16.5 53
 
0.5%
Other values (3309) 6500
65.0%
(Missing) 2527
 
25.3%
ValueCountFrequency (%)
0.0 244
2.4%
0.5 1
 
< 0.1%
0.75 1
 
< 0.1%
1.0 5
 
0.1%
1.08 3
 
< 0.1%
1.12 1
 
< 0.1%
1.2 1
 
< 0.1%
1.4 1
 
< 0.1%
1.5 3
 
< 0.1%
1.62 2
 
< 0.1%
ValueCountFrequency (%)
184133.0 1
< 0.1%
85033.58 1
< 0.1%
20035.7 1
< 0.1%
921.94 1
< 0.1%
789.63 1
< 0.1%
617.77 1
< 0.1%
608.57 1
< 0.1%
572.66 1
< 0.1%
555.64 1
< 0.1%
539.97 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9998 
0
 
2

Length

Max length4
Median length4
Mean length3.9994
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> 9998
> 99.9%
0 2
 
< 0.1%

Length

2024-05-18T08:53:28.703022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:53:29.175610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9998
> 99.9%
0 2
 
< 0.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1081332100003210000-121-2002-0004420020423<NA>3폐업2폐업20100615<NA><NA><NA><NA>8.25137713서울특별시 서초구 반포동 19-3번지 신세계백화점 지하1층<NA><NA>에구찌2008-01-03 11:11:16I2018-08-31 23:59:59.0제과점영업200250.447805444683.220506제과점영업00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N8.25<NA><NA><NA>
938931800003180000-121-2022-0000720220203<NA>3폐업2폐업20220217<NA><NA><NA><NA><NA>150875서울특별시 영등포구 여의도동 22 파크원서울특별시 영등포구 여의대로 108, 더현대서울 지하1층 (여의도동)7335얀쿠브레2022-02-18 04:15:09U2022-02-20 02:40:00.0제과점영업193592.00038447092.629433제과점영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
455630600003060000-121-2011-000132011-08-26<NA>1영업/정상1영업<NA><NA><NA><NA>070 712376003.00131-872서울특별시 중랑구 신내동 645서울특별시 중랑구 신내로 201, 지하1층 (신내동, 홈플러스신내점)2024몽블랑제(주)신내점행사매대2024-02-21 13:28:40U2023-12-01 22:03:00.0제과점영업208208.786685457054.793656<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1039732000003200000-121-2004-0001320040302<NA>3폐업2폐업20080619<NA><NA><NA>02 882265431.60151810서울특별시 관악구 봉천동 36-2번지 지상1층<NA><NA>크라운베이커리봉천우성점2006-06-13 00:00:00I2018-08-31 23:59:59.0제과점영업196125.757366442574.064255제과점영업00주택가주변<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N31.6<NA><NA><NA>
1410432400003240000-121-1983-0506119830902<NA>3폐업2폐업19930324<NA><NA><NA>020472085023.51134830서울특별시 강동구 명일동 324-2번지<NA><NA>거북당2002-06-05 00:00:00I2018-08-31 23:59:59.0제과점영업212667.48838449804.059281제과점영업00주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.51<NA><NA><NA>
488530700003070000-121-1983-0868719830509<NA>1영업/정상1영업<NA><NA><NA><NA>02 915260329.70136801서울특별시 성북구 길음동 1154번지서울특별시 성북구 삼양로 50 (길음동)2731독일베이커리2010-08-12 10:48:39I2018-08-31 23:59:59.0제과점영업202028.368342456136.725218제과점영업11주택가주변<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.7<NA><NA><NA>
1109632100003210000-121-2006-0004020061115<NA>3폐업2폐업20080929<NA><NA><NA><NA>86.10137875서울특별시 서초구 서초동 1576-7번지 이화빌딩 1층<NA><NA>뚜레쥬르2006-11-15 00:00:00I2018-08-31 23:59:59.0제과점영업201165.849569443142.702976제과점영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N86.1<NA><NA><NA>
46832200003220000-121-2023-000472023-04-27<NA>3폐업2폐업2023-05-31<NA><NA><NA>02 517 9346<NA>135-902서울특별시 강남구 압구정동 494 갤러리아백화점서울특별시 강남구 압구정로 343, 갤러리아백화점 지하1층 (압구정동)6008베시 더 스콘(한시적)2023-06-01 04:15:10U2022-12-06 00:03:00.0제과점영업203470.848439447369.579852<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
576031000003100000-121-2018-0000320180315<NA>3폐업2폐업20220816<NA><NA><NA><NA>27.30139861서울특별시 노원구 중계동 364-19 삼부프라자서울특별시 노원구 한글비석로 242, 삼부프라자 1층 118호 (중계동)1734식빵이 맛있는 집 네모(노원 은행사거리점)2022-08-16 11:27:55U2021-12-07 23:08:00.0제과점영업206722.537202460773.320554<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
708831300003130000-121-2000-0000420000719<NA>3폐업2폐업20130829<NA><NA><NA>02 335206243.24121807서울특별시 마포구 노고산동 49-31번지<NA><NA>하나로베이커리2013-09-23 16:45:32I2018-08-31 23:59:59.0제과점영업194020.023177450426.583344제과점영업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.24<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
554730900003090000-121-1999-0487319991122<NA>3폐업2폐업20141124<NA><NA><NA>02 990252755.80132030서울특별시 도봉구 쌍문동 192-4번지서울특별시 도봉구 해등로 200 (쌍문동)1385던킨도너츠2014-10-31 16:28:56I2018-08-31 23:59:59.0제과점영업202978.715323461768.035208제과점영업22아파트지역자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N55.8<NA><NA><NA>
1122332100003210000-121-2015-0003020150917<NA>3폐업2폐업20180929<NA><NA><NA><NA>33.00137830서울특별시 서초구 방배동 796-28번지 1층서울특별시 서초구 동광로 75, 1층 (방배동)6584식빵학개론2018-09-28 10:47:06U2018-09-28 23:59:59.0제과점영업199100.858117443429.869829제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N33.0<NA><NA><NA>
1032732000003200000-121-2008-0000120080228<NA>3폐업2폐업20110901<NA><NA><NA><NA>75.00151892서울특별시 관악구 신림동 1433-86번지 지상1층<NA><NA>파리바게뜨신림본점2008-02-28 15:26:02I2018-08-31 23:59:59.0제과점영업193550.979729442458.424808제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N75.0<NA><NA><NA>
225630400003040000-121-2019-0001220190708<NA>3폐업2폐업20220411<NA><NA><NA><NA>38.83143723서울특별시 광진구 구의동 199-18 구의동삼성쉐르빌서울특별시 광진구 구의강변로 106, 지하1층 지하107호 (구의동, 구의동삼성쉐르빌)5117일릴리2022-04-11 16:09:11U2021-12-03 23:03:00.0제과점영업208310.37226448631.437595<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
619931200003120000-121-2010-0001420101025<NA>3폐업2폐업20220809<NA><NA><NA>02 394 8497154.38120859서울특별시 서대문구 홍제동 172-5 1동서울특별시 서대문구 통일로 437, 1동 1층 (홍제동)3646미정2022-08-09 16:51:10U2021-12-07 23:02:00.0제과점영업195048.257103453949.306565<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
229532200003220000-121-2022-0005720220602<NA>3폐업2폐업20220702<NA><NA><NA><NA><NA>135724서울특별시 강남구 압구정동 429 현대백화점본점서울특별시 강남구 압구정로 165, 현대백화점 본점 지하1층 식품관 (압구정동)6001탄탈라이즈 르네테르 커피(한시적)2022-07-03 04:15:13U2021-12-07 00:05:00.0제과점영업202358.505687447232.955698<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
214432400003240000-121-2022-0001120220324<NA>3폐업2폐업20220407<NA><NA><NA><NA><NA>134779서울특별시 강동구 천호동 572 현대백화점서울특별시 강동구 천호대로 1005, 현대백화점 지2층 (천호동)5328더블유스타일도넛 강남점 한시적영업2022-04-08 04:15:10U2021-12-03 23:02:00.0제과점영업210929.919694448537.406728<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413430500003050000-121-2011-0000920110614<NA>1영업/정상1영업<NA><NA><NA><NA>02 969172185.00130817서울특별시 동대문구 용두동 27-4번지 1층서울특별시 동대문구 고산자로 410, 1층 (용두동)2560파리바게뜨(동대문구청점)2017-02-13 11:44:59I2018-08-31 23:59:59.0제과점영업203343.611551452663.381465제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N85.0<NA><NA><NA>
380030400003040000-121-2007-0001820071002<NA>3폐업2폐업20160901<NA><NA><NA><NA><NA>143701서울특별시 광진구 화양동 1번지 건국대학교기숙사 쿨하우스드림홀 B103호서울특별시 광진구 능동로 120 (화양동)5029브랑제리 르와르2013-12-30 15:06:43I2018-08-31 23:59:59.0제과점영업206445.881092448922.881688제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N66.08<NA><NA><NA>
625931100003110000-121-2010-0001220100618<NA>3폐업2폐업20150210<NA><NA><NA>02 72860111.50122906서울특별시 은평구 응암동 90-1번지 이마트내 지상1층서울특별시 은평구 은평로 111 (응암동, 이마트내 지상1층)3461데이앤데이 은평점42013-04-02 16:59:28I2018-08-31 23:59:59.0제과점영업192882.837727455340.540564제과점영업<NA><NA>학교정화(상대)자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N1.5<NA><NA><NA>