Overview

Dataset statistics

Number of variables44
Number of observations4411
Missing cells46411
Missing cells (%)23.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory377.0 B

Variable types

Categorical20
Text6
DateTime4
Unsupported8
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author광진구
URLhttps://data.seoul.go.kr/dataList/OA-18681/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
남성종사자수 is highly imbalanced (64.9%)Imbalance
여성종사자수 is highly imbalanced (63.9%)Imbalance
영업장주변구분명 is highly imbalanced (64.2%)Imbalance
등급구분명 is highly imbalanced (58.8%)Imbalance
총인원 is highly imbalanced (73.4%)Imbalance
본사종업원수 is highly imbalanced (73.2%)Imbalance
공장사무직종업원수 is highly imbalanced (73.2%)Imbalance
공장판매직종업원수 is highly imbalanced (73.2%)Imbalance
공장생산직종업원수 is highly imbalanced (73.2%)Imbalance
보증액 is highly imbalanced (73.2%)Imbalance
월세액 is highly imbalanced (73.2%)Imbalance
다중이용업소여부 is highly imbalanced (90.4%)Imbalance
인허가취소일자 has 4411 (100.0%) missing valuesMissing
폐업일자 has 1347 (30.5%) missing valuesMissing
휴업시작일자 has 4411 (100.0%) missing valuesMissing
휴업종료일자 has 4411 (100.0%) missing valuesMissing
재개업일자 has 4411 (100.0%) missing valuesMissing
전화번호 has 2389 (54.2%) missing valuesMissing
소재지면적 has 2265 (51.3%) missing valuesMissing
도로명주소 has 1344 (30.5%) missing valuesMissing
도로명우편번호 has 1365 (30.9%) missing valuesMissing
좌표정보(X) has 118 (2.7%) missing valuesMissing
좌표정보(Y) has 118 (2.7%) missing valuesMissing
건물소유구분명 has 4411 (100.0%) missing valuesMissing
다중이용업소여부 has 1087 (24.6%) missing valuesMissing
시설총규모 has 1087 (24.6%) missing valuesMissing
전통업소지정번호 has 4411 (100.0%) missing valuesMissing
전통업소주된음식 has 4411 (100.0%) missing valuesMissing
홈페이지 has 4411 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 59 (1.3%) zerosZeros

Reproduction

Analysis started2024-05-11 00:37:41.531884
Analysis finished2024-05-11 00:37:46.015608
Duration4.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
3040000
4411 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3040000
2nd row3040000
3rd row3040000
4th row3040000
5th row3040000

Common Values

ValueCountFrequency (%)
3040000 4411
100.0%

Length

2024-05-11T00:37:46.253123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:37:46.632604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3040000 4411
100.0%

관리번호
Text

UNIQUE 

Distinct4411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
2024-05-11T00:37:47.232236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters97042
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

Unique4411 ?
Unique (%)100.0%

Sample

1st row3040000-104-1974-07701
2nd row3040000-104-1974-07762
3rd row3040000-104-1976-07603
4th row3040000-104-1976-07610
5th row3040000-104-1976-07612
ValueCountFrequency (%)
3040000-104-1974-07701 1
 
< 0.1%
3040000-104-2017-00193 1
 
< 0.1%
3040000-104-2017-00187 1
 
< 0.1%
3040000-104-2017-00188 1
 
< 0.1%
3040000-104-2017-00189 1
 
< 0.1%
3040000-104-2017-00190 1
 
< 0.1%
3040000-104-2018-00013 1
 
< 0.1%
3040000-104-2017-00191 1
 
< 0.1%
3040000-104-2017-00194 1
 
< 0.1%
3040000-104-2018-00012 1
 
< 0.1%
Other values (4401) 4401
99.8%
2024-05-11T00:37:48.417960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41976
43.3%
- 13233
 
13.6%
4 10192
 
10.5%
1 10059
 
10.4%
2 6321
 
6.5%
3 5935
 
6.1%
9 2813
 
2.9%
7 1965
 
2.0%
8 1864
 
1.9%
6 1395
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83809
86.4%
Dash Punctuation 13233
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41976
50.1%
4 10192
 
12.2%
1 10059
 
12.0%
2 6321
 
7.5%
3 5935
 
7.1%
9 2813
 
3.4%
7 1965
 
2.3%
8 1864
 
2.2%
6 1395
 
1.7%
5 1289
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 13233
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97042
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41976
43.3%
- 13233
 
13.6%
4 10192
 
10.5%
1 10059
 
10.4%
2 6321
 
6.5%
3 5935
 
6.1%
9 2813
 
2.9%
7 1965
 
2.0%
8 1864
 
1.9%
6 1395
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97042
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41976
43.3%
- 13233
 
13.6%
4 10192
 
10.5%
1 10059
 
10.4%
2 6321
 
6.5%
3 5935
 
6.1%
9 2813
 
2.9%
7 1965
 
2.0%
8 1864
 
1.9%
6 1395
 
1.4%

인허가일자
Date

Distinct3191
Distinct (%)72.3%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
Minimum1974-03-01 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T00:37:48.925595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:37:49.388917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4411
Missing (%)100.0%
Memory size38.9 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
3
3064 
1
1347 

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 3064
69.5%
1 1347
30.5%

Length

2024-05-11T00:37:49.903781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:37:50.315130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3064
69.5%
1 1347
30.5%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
폐업
3064 
영업/정상
1347 

Length

Max length5
Median length2
Mean length2.9161188
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3064
69.5%
영업/정상 1347
30.5%

Length

2024-05-11T00:37:50.814413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:37:51.168013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3064
69.5%
영업/정상 1347
30.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
2
3064 
1
1347 

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 3064
69.5%
1 1347
30.5%

Length

2024-05-11T00:37:51.561045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:37:52.086120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3064
69.5%
1 1347
30.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
폐업
3064 
영업
1347 

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 3064
69.5%
영업 1347
30.5%

Length

2024-05-11T00:37:52.508113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:37:52.951988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3064
69.5%
영업 1347
30.5%

폐업일자
Date

MISSING 

Distinct2266
Distinct (%)74.0%
Missing1347
Missing (%)30.5%
Memory size34.6 KiB
Minimum1987-11-04 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T00:37:53.489113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:37:54.059383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4411
Missing (%)100.0%
Memory size38.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4411
Missing (%)100.0%
Memory size38.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4411
Missing (%)100.0%
Memory size38.9 KiB

전화번호
Text

MISSING 

Distinct1804
Distinct (%)89.2%
Missing2389
Missing (%)54.2%
Memory size34.6 KiB
2024-05-11T00:37:55.061685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9866469
Min length2

Characters and Unicode

Total characters20193
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

Unique1701 ?
Unique (%)84.1%

Sample

1st row02 4666678
2nd row02 4461818
3rd row02 4669209
4th row02 00000
5th row02 00000
ValueCountFrequency (%)
02 1477
40.5%
0 32
 
0.9%
00000 23
 
0.6%
0220241050 16
 
0.4%
070 9
 
0.2%
031 9
 
0.2%
02447 8
 
0.2%
0200000000 7
 
0.2%
4525955 7
 
0.2%
444 7
 
0.2%
Other values (1869) 2050
56.2%
2024-05-11T00:37:56.481283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3499
17.3%
2 3292
16.3%
4 3014
14.9%
1803
8.9%
5 1636
8.1%
6 1493
7.4%
3 1188
 
5.9%
7 1143
 
5.7%
1 1096
 
5.4%
8 1042
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18390
91.1%
Space Separator 1803
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3499
19.0%
2 3292
17.9%
4 3014
16.4%
5 1636
8.9%
6 1493
8.1%
3 1188
 
6.5%
7 1143
 
6.2%
1 1096
 
6.0%
8 1042
 
5.7%
9 987
 
5.4%
Space Separator
ValueCountFrequency (%)
1803
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3499
17.3%
2 3292
16.3%
4 3014
14.9%
1803
8.9%
5 1636
8.1%
6 1493
7.4%
3 1188
 
5.9%
7 1143
 
5.7%
1 1096
 
5.4%
8 1042
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3499
17.3%
2 3292
16.3%
4 3014
14.9%
1803
8.9%
5 1636
8.1%
6 1493
7.4%
3 1188
 
5.9%
7 1143
 
5.7%
1 1096
 
5.4%
8 1042
 
5.2%

소재지면적
Real number (ℝ)

MISSING 

Distinct976
Distinct (%)45.5%
Missing2265
Missing (%)51.3%
Infinite0
Infinite (%)0.0%
Mean43.630904
Minimum0
Maximum834
Zeros25
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size38.9 KiB
2024-05-11T00:37:56.993439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q110
median26.44
Q349.5
95-th percentile150.045
Maximum834
Range834
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation60.903336
Coefficient of variation (CV)1.3958761
Kurtosis32.633793
Mean43.630904
Median Absolute Deviation (MAD)18.09
Skewness4.5416896
Sum93631.92
Variance3709.2163
MonotonicityNot monotonic
2024-05-11T00:37:57.487645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.6 253
 
5.7%
3.3 102
 
2.3%
33.0 47
 
1.1%
30.0 46
 
1.0%
20.0 39
 
0.9%
25.0 30
 
0.7%
0.0 25
 
0.6%
18.0 22
 
0.5%
9.9 21
 
0.5%
26.4 20
 
0.5%
Other values (966) 1541
34.9%
(Missing) 2265
51.3%
ValueCountFrequency (%)
0.0 25
0.6%
1.3 2
 
< 0.1%
1.5 1
 
< 0.1%
1.6 1
 
< 0.1%
1.8 1
 
< 0.1%
1.98 1
 
< 0.1%
2.0 1
 
< 0.1%
2.04 1
 
< 0.1%
2.08 1
 
< 0.1%
2.38 1
 
< 0.1%
ValueCountFrequency (%)
834.0 1
< 0.1%
675.04 1
< 0.1%
627.82 1
< 0.1%
528.56 1
< 0.1%
467.0 1
< 0.1%
451.55 1
< 0.1%
429.75 1
< 0.1%
426.24 1
< 0.1%
398.68 1
< 0.1%
393.7 1
< 0.1%

소재지우편번호
Text

Distinct229
Distinct (%)5.2%
Missing2
Missing (%)< 0.1%
Memory size34.6 KiB
2024-05-11T00:37:58.219511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1596734
Min length6

Characters and Unicode

Total characters27158
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 (%)0.7%

Sample

1st row143839
2nd row143826
3rd row143842
4th row143915
5th row143915
ValueCountFrequency (%)
143914 246
 
5.6%
143758 201
 
4.6%
143915 141
 
3.2%
143841 124
 
2.8%
143847 121
 
2.7%
143826 100
 
2.3%
143200 86
 
2.0%
143840 81
 
1.8%
143819 80
 
1.8%
143916 75
 
1.7%
Other values (219) 3154
71.5%
2024-05-11T00:37:59.404796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5920
21.8%
4 5500
20.3%
3 4982
18.3%
8 3547
13.1%
9 1590
 
5.9%
2 1106
 
4.1%
7 1049
 
3.9%
0 963
 
3.5%
5 912
 
3.4%
6 885
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26454
97.4%
Dash Punctuation 704
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5920
22.4%
4 5500
20.8%
3 4982
18.8%
8 3547
13.4%
9 1590
 
6.0%
2 1106
 
4.2%
7 1049
 
4.0%
0 963
 
3.6%
5 912
 
3.4%
6 885
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 704
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27158
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5920
21.8%
4 5500
20.3%
3 4982
18.3%
8 3547
13.1%
9 1590
 
5.9%
2 1106
 
4.1%
7 1049
 
3.9%
0 963
 
3.5%
5 912
 
3.4%
6 885
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5920
21.8%
4 5500
20.3%
3 4982
18.3%
8 3547
13.1%
9 1590
 
5.9%
2 1106
 
4.1%
7 1049
 
3.9%
0 963
 
3.5%
5 912
 
3.4%
6 885
 
3.3%

지번주소
Text

Distinct3754
Distinct (%)85.1%
Missing1
Missing (%)< 0.1%
Memory size34.6 KiB
2024-05-11T00:37:59.973722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length25.127438
Min length14

Characters and Unicode

Total characters110812
Distinct characters373
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3343 ?
Unique (%)75.8%

Sample

1st row서울특별시 광진구 군자동 102-32번지
2nd row서울특별시 광진구 구의동 252-16번지
3rd row서울특별시 광진구 자양동 36-30번지
4th row서울특별시 광진구 화양동 111-5번지
5th row서울특별시 광진구 화양동 111-49번지
ValueCountFrequency (%)
서울특별시 4411
20.8%
광진구 4410
20.8%
자양동 1274
 
6.0%
1층 1184
 
5.6%
구의동 936
 
4.4%
중곡동 756
 
3.6%
화양동 712
 
3.4%
군자동 297
 
1.4%
광장동 254
 
1.2%
지하1층 193
 
0.9%
Other values (3598) 6802
32.0%
2024-05-11T00:38:00.859759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20066
18.1%
구 5392
 
4.9%
1 5379
 
4.9%
광 4738
 
4.3%
동 4577
 
4.1%
시 4501
 
4.1%
진 4471
 
4.0%
서 4427
 
4.0%
울 4419
 
4.0%
별 4411
 
4.0%
Other values (363) 48431
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63605
57.4%
Decimal Number 21963
 
19.8%
Space Separator 20066
 
18.1%
Dash Punctuation 4027
 
3.6%
Open Punctuation 420
 
0.4%
Close Punctuation 420
 
0.4%
Uppercase Letter 146
 
0.1%
Other Punctuation 132
 
0.1%
Lowercase Letter 16
 
< 0.1%
Math Symbol 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 5392
 
8.5%
광 4738
 
7.4%
동 4577
 
7.2%
시 4501
 
7.1%
진 4471
 
7.0%
서 4427
 
7.0%
울 4419
 
6.9%
별 4411
 
6.9%
특 4411
 
6.9%
지 3178
 
5.0%
Other values (310) 19080
30.0%
Uppercase Letter
ValueCountFrequency (%)
B 36
24.7%
A 29
19.9%
C 21
14.4%
D 21
14.4%
S 9
 
6.2%
K 5
 
3.4%
P 3
 
2.1%
U 3
 
2.1%
M 2
 
1.4%
F 2
 
1.4%
Other values (10) 15
10.3%
Lowercase Letter
ValueCountFrequency (%)
e 3
18.8%
a 3
18.8%
p 2
12.5%
r 1
 
6.2%
w 1
 
6.2%
o 1
 
6.2%
t 1
 
6.2%
c 1
 
6.2%
s 1
 
6.2%
l 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 5379
24.5%
2 3816
17.4%
3 2118
 
9.6%
4 2073
 
9.4%
5 1864
 
8.5%
6 1683
 
7.7%
7 1530
 
7.0%
0 1474
 
6.7%
8 1063
 
4.8%
9 963
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 123
93.2%
? 4
 
3.0%
/ 3
 
2.3%
. 2
 
1.5%
Letter Number
ValueCountFrequency (%)
Ⅲ 2
50.0%
Ⅰ 1
25.0%
Ⅱ 1
25.0%
Space Separator
ValueCountFrequency (%)
20066
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4027
100.0%
Open Punctuation
ValueCountFrequency (%)
( 420
100.0%
Close Punctuation
ValueCountFrequency (%)
) 420
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63603
57.4%
Common 47041
42.5%
Latin 166
 
0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 5392
 
8.5%
광 4738
 
7.4%
동 4577
 
7.2%
시 4501
 
7.1%
진 4471
 
7.0%
서 4427
 
7.0%
울 4419
 
6.9%
별 4411
 
6.9%
특 4411
 
6.9%
지 3178
 
5.0%
Other values (309) 19078
30.0%
Latin
ValueCountFrequency (%)
B 36
21.7%
A 29
17.5%
C 21
12.7%
D 21
12.7%
S 9
 
5.4%
K 5
 
3.0%
P 3
 
1.8%
U 3
 
1.8%
e 3
 
1.8%
a 3
 
1.8%
Other values (24) 33
19.9%
Common
ValueCountFrequency (%)
20066
42.7%
1 5379
 
11.4%
- 4027
 
8.6%
2 3816
 
8.1%
3 2118
 
4.5%
4 2073
 
4.4%
5 1864
 
4.0%
6 1683
 
3.6%
7 1530
 
3.3%
0 1474
 
3.1%
Other values (9) 3011
 
6.4%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63603
57.4%
ASCII 47203
42.6%
Number Forms 4
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20066
42.5%
1 5379
 
11.4%
- 4027
 
8.5%
2 3816
 
8.1%
3 2118
 
4.5%
4 2073
 
4.4%
5 1864
 
3.9%
6 1683
 
3.6%
7 1530
 
3.2%
0 1474
 
3.1%
Other values (40) 3173
 
6.7%
Hangul
ValueCountFrequency (%)
구 5392
 
8.5%
광 4738
 
7.4%
동 4577
 
7.2%
시 4501
 
7.1%
진 4471
 
7.0%
서 4427
 
7.0%
울 4419
 
6.9%
별 4411
 
6.9%
특 4411
 
6.9%
지 3178
 
5.0%
Other values (309) 19078
30.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 2
50.0%
Ⅰ 1
25.0%
Ⅱ 1
25.0%
CJK
ValueCountFrequency (%)
內 2
100.0%

도로명주소
Text

MISSING 

Distinct2565
Distinct (%)83.6%
Missing1344
Missing (%)30.5%
Memory size34.6 KiB
2024-05-11T00:38:01.452535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length58
Mean length31.762634
Min length21

Characters and Unicode

Total characters97416
Distinct characters371
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2252 ?
Unique (%)73.4%

Sample

1st row서울특별시 광진구 동일로 174 (화양동)
2nd row서울특별시 광진구 뚝섬로 503 (자양동)
3rd row서울특별시 광진구 용마산로 66 (중곡동)
4th row서울특별시 광진구 뚝섬로 672 (자양동)
5th row서울특별시 광진구 아차산로 399, 지하1층 (구의동)
ValueCountFrequency (%)
서울특별시 3068
 
15.6%
광진구 3067
 
15.6%
1층 1819
 
9.3%
자양동 848
 
4.3%
구의동 584
 
3.0%
중곡동 494
 
2.5%
능동로 477
 
2.4%
화양동 412
 
2.1%
아차산로 285
 
1.5%
지하1층 228
 
1.2%
Other values (1802) 8350
42.5%
2024-05-11T00:38:02.603724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16569
 
17.0%
1 5036
 
5.2%
동 4058
 
4.2%
구 3834
 
3.9%
광 3694
 
3.8%
( 3250
 
3.3%
) 3250
 
3.3%
, 3206
 
3.3%
시 3148
 
3.2%
진 3125
 
3.2%
Other values (361) 48246
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55480
57.0%
Space Separator 16569
 
17.0%
Decimal Number 15189
 
15.6%
Open Punctuation 3250
 
3.3%
Close Punctuation 3250
 
3.3%
Other Punctuation 3213
 
3.3%
Dash Punctuation 283
 
0.3%
Uppercase Letter 138
 
0.1%
Lowercase Letter 22
 
< 0.1%
Math Symbol 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4058
 
7.3%
구 3834
 
6.9%
광 3694
 
6.7%
시 3148
 
5.7%
진 3125
 
5.6%
로 3083
 
5.6%
서 3083
 
5.6%
울 3074
 
5.5%
별 3068
 
5.5%
특 3068
 
5.5%
Other values (307) 22245
40.1%
Uppercase Letter
ValueCountFrequency (%)
B 48
34.8%
A 24
17.4%
C 15
 
10.9%
S 11
 
8.0%
D 10
 
7.2%
I 3
 
2.2%
K 3
 
2.2%
U 3
 
2.2%
G 3
 
2.2%
P 3
 
2.2%
Other values (11) 15
 
10.9%
Lowercase Letter
ValueCountFrequency (%)
b 6
27.3%
e 3
13.6%
a 3
13.6%
p 2
 
9.1%
c 1
 
4.5%
s 1
 
4.5%
z 1
 
4.5%
l 1
 
4.5%
t 1
 
4.5%
o 1
 
4.5%
Other values (2) 2
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 5036
33.2%
2 2140
14.1%
0 1370
 
9.0%
3 1359
 
8.9%
5 1156
 
7.6%
6 1004
 
6.6%
4 985
 
6.5%
9 757
 
5.0%
7 725
 
4.8%
8 657
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 3206
99.8%
. 3
 
0.1%
? 2
 
0.1%
/ 2
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
16569
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3250
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3250
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 283
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55478
56.9%
Common 41774
42.9%
Latin 162
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4058
 
7.3%
구 3834
 
6.9%
광 3694
 
6.7%
시 3148
 
5.7%
진 3125
 
5.6%
로 3083
 
5.6%
서 3083
 
5.6%
울 3074
 
5.5%
별 3068
 
5.5%
특 3068
 
5.5%
Other values (306) 22243
40.1%
Latin
ValueCountFrequency (%)
B 48
29.6%
A 24
14.8%
C 15
 
9.3%
S 11
 
6.8%
D 10
 
6.2%
b 6
 
3.7%
I 3
 
1.9%
K 3
 
1.9%
e 3
 
1.9%
U 3
 
1.9%
Other values (25) 36
22.2%
Common
ValueCountFrequency (%)
16569
39.7%
1 5036
 
12.1%
( 3250
 
7.8%
) 3250
 
7.8%
, 3206
 
7.7%
2 2140
 
5.1%
0 1370
 
3.3%
3 1359
 
3.3%
5 1156
 
2.8%
6 1004
 
2.4%
Other values (9) 3434
 
8.2%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55478
56.9%
ASCII 41934
43.0%
CJK 2
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16569
39.5%
1 5036
 
12.0%
( 3250
 
7.8%
) 3250
 
7.8%
, 3206
 
7.6%
2 2140
 
5.1%
0 1370
 
3.3%
3 1359
 
3.2%
5 1156
 
2.8%
6 1004
 
2.4%
Other values (42) 3594
 
8.6%
Hangul
ValueCountFrequency (%)
동 4058
 
7.3%
구 3834
 
6.9%
광 3694
 
6.7%
시 3148
 
5.7%
진 3125
 
5.6%
로 3083
 
5.6%
서 3083
 
5.6%
울 3074
 
5.5%
별 3068
 
5.5%
특 3068
 
5.5%
Other values (306) 22243
40.1%
CJK
ValueCountFrequency (%)
內 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct205
Distinct (%)6.7%
Missing1365
Missing (%)30.9%
Infinite0
Infinite (%)0.0%
Mean5016.3296
Minimum4900
Maximum5119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.9 KiB
2024-05-11T00:38:02.998981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4900
5-th percentile4913
Q14974
median5018
Q35065
95-th percentile5112
Maximum5119
Range219
Interquartile range (IQR)91

Descriptive statistics

Standard deviation57.780802
Coefficient of variation (CV)0.011518542
Kurtosis-0.84400608
Mean5016.3296
Median Absolute Deviation (MAD)47
Skewness-0.17856369
Sum15279740
Variance3338.621
MonotonicityNot monotonic
2024-05-11T00:38:03.257757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5065 210
 
4.8%
5116 95
 
2.2%
4991 66
 
1.5%
5009 46
 
1.0%
5011 45
 
1.0%
5073 45
 
1.0%
5017 41
 
0.9%
5072 41
 
0.9%
4969 37
 
0.8%
5006 37
 
0.8%
Other values (195) 2383
54.0%
(Missing) 1365
30.9%
ValueCountFrequency (%)
4900 4
 
0.1%
4901 1
 
< 0.1%
4902 14
 
0.3%
4903 11
 
0.2%
4904 8
 
0.2%
4905 4
 
0.1%
4906 12
 
0.3%
4907 7
 
0.2%
4908 35
0.8%
4909 14
 
0.3%
ValueCountFrequency (%)
5119 14
 
0.3%
5118 7
 
0.2%
5117 24
 
0.5%
5116 95
2.2%
5115 2
 
< 0.1%
5113 6
 
0.1%
5112 10
 
0.2%
5110 4
 
0.1%
5106 3
 
0.1%
5105 6
 
0.1%

사업장명
Text

Distinct4048
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
2024-05-11T00:38:03.928815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length7.2772614
Min length1

Characters and Unicode

Total characters32100
Distinct characters900
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3796 ?
Unique (%)86.1%

Sample

1st row인화
2nd row황태자
3rd row수정
4th row판도라
5th row오두막
ValueCountFrequency (%)
세븐일레븐 35
 
0.7%
coffee 31
 
0.6%
건대점 26
 
0.5%
자양점 24
 
0.5%
지에스25 17
 
0.3%
구의점 17
 
0.3%
카페 14
 
0.3%
이마트 14
 
0.3%
이마트24 13
 
0.2%
건대스타시티점 13
 
0.2%
Other values (4269) 5024
96.1%
2024-05-11T00:38:04.956209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 1346
 
4.2%
스 1027
 
3.2%
818
 
2.5%
이 775
 
2.4%
) 712
 
2.2%
( 711
 
2.2%
피 638
 
2.0%
리 531
 
1.7%
커 519
 
1.6%
대 451
 
1.4%
Other values (890) 24572
76.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26126
81.4%
Lowercase Letter 1447
 
4.5%
Uppercase Letter 1384
 
4.3%
Space Separator 818
 
2.5%
Decimal Number 784
 
2.4%
Close Punctuation 713
 
2.2%
Open Punctuation 712
 
2.2%
Other Punctuation 86
 
0.3%
Dash Punctuation 20
 
0.1%
Connector Punctuation 3
 
< 0.1%
Other values (4) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1346
 
5.2%
스 1027
 
3.9%
이 775
 
3.0%
피 638
 
2.4%
리 531
 
2.0%
커 519
 
2.0%
대 451
 
1.7%
자 432
 
1.7%
카 361
 
1.4%
페 341
 
1.3%
Other values (806) 19705
75.4%
Uppercase Letter
ValueCountFrequency (%)
C 171
12.4%
S 160
 
11.6%
G 130
 
9.4%
E 117
 
8.5%
O 85
 
6.1%
A 81
 
5.9%
F 67
 
4.8%
T 58
 
4.2%
U 57
 
4.1%
R 51
 
3.7%
Other values (16) 407
29.4%
Lowercase Letter
ValueCountFrequency (%)
e 255
17.6%
o 146
10.1%
a 124
 
8.6%
f 109
 
7.5%
n 95
 
6.6%
i 89
 
6.2%
c 82
 
5.7%
t 80
 
5.5%
s 69
 
4.8%
r 54
 
3.7%
Other values (15) 344
23.8%
Other Punctuation
ValueCountFrequency (%)
& 32
37.2%
. 22
25.6%
' 12
 
14.0%
? 6
 
7.0%
, 4
 
4.7%
？ 2
 
2.3%
! 2
 
2.3%
: 2
 
2.3%
/ 2
 
2.3%
; 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
2 281
35.8%
5 211
26.9%
1 65
 
8.3%
4 64
 
8.2%
3 47
 
6.0%
9 37
 
4.7%
7 28
 
3.6%
0 27
 
3.4%
8 17
 
2.2%
6 7
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 712
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 711
99.9%
[ 1
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
Space Separator
ValueCountFrequency (%)
818
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Math Symbol
ValueCountFrequency (%)
× 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26118
81.4%
Common 3140
 
9.8%
Latin 2834
 
8.8%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1346
 
5.2%
스 1027
 
3.9%
이 775
 
3.0%
피 638
 
2.4%
리 531
 
2.0%
커 519
 
2.0%
대 451
 
1.7%
자 432
 
1.7%
카 361
 
1.4%
페 341
 
1.3%
Other values (799) 19697
75.4%
Latin
ValueCountFrequency (%)
e 255
 
9.0%
C 171
 
6.0%
S 160
 
5.6%
o 146
 
5.2%
G 130
 
4.6%
a 124
 
4.4%
E 117
 
4.1%
f 109
 
3.8%
n 95
 
3.4%
i 89
 
3.1%
Other values (43) 1438
50.7%
Common
ValueCountFrequency (%)
818
26.1%
) 712
22.7%
( 711
22.6%
2 281
 
8.9%
5 211
 
6.7%
1 65
 
2.1%
4 64
 
2.0%
3 47
 
1.5%
9 37
 
1.2%
& 32
 
1.0%
Other values (21) 162
 
5.2%
Han
ValueCountFrequency (%)
愛 2
25.0%
酸 1
12.5%
米 1
12.5%
宋 1
12.5%
有 1
12.5%
多 1
12.5%
淸 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26116
81.4%
ASCII 5966
 
18.6%
CJK 8
 
< 0.1%
None 4
 
< 0.1%
Number Forms 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 1346
 
5.2%
스 1027
 
3.9%
이 775
 
3.0%
피 638
 
2.4%
리 531
 
2.0%
커 519
 
2.0%
대 451
 
1.7%
자 432
 
1.7%
카 361
 
1.4%
페 341
 
1.3%
Other values (797) 19695
75.4%
ASCII
ValueCountFrequency (%)
818
 
13.7%
) 712
 
11.9%
( 711
 
11.9%
2 281
 
4.7%
e 255
 
4.3%
5 211
 
3.5%
C 171
 
2.9%
S 160
 
2.7%
o 146
 
2.4%
G 130
 
2.2%
Other values (69) 2371
39.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
None
ValueCountFrequency (%)
× 2
50.0%
？ 2
50.0%
CJK
ValueCountFrequency (%)
愛 2
25.0%
酸 1
12.5%
米 1
12.5%
宋 1
12.5%
有 1
12.5%
多 1
12.5%
淸 1
12.5%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅡ 1
50.0%
ㅋ 1
50.0%

최종수정일자
Date

Distinct3662
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
Minimum1999-09-06 00:00:00
Maximum2024-05-08 17:45:44
2024-05-11T00:38:05.346584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:38:06.065643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
I
2803 
U
1608 

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 2803
63.5%
U 1608
36.5%

Length

2024-05-11T00:38:06.430655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:06.714709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2803
63.5%
u 1608
36.5%

데이터갱신일자
Date

Distinct1123
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T00:38:07.064217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:38:07.470294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct19
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
커피숍
1234 
일반조리판매
956 
기타 휴게음식점
647 
다방
459 
편의점
449 
Other values (14)
666 

Length

Max length8
Median length7
Mean length4.4101111
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 1234
28.0%
일반조리판매 956
21.7%
기타 휴게음식점 647
14.7%
다방 459
 
10.4%
편의점 449
 
10.2%
과자점 304
 
6.9%
패스트푸드 246
 
5.6%
푸드트럭 26
 
0.6%
백화점 25
 
0.6%
유원지 19
 
0.4%
Other values (9) 46
 
1.0%

Length

2024-05-11T00:38:07.863702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1234
24.4%
일반조리판매 956
18.9%
기타 648
12.8%
휴게음식점 647
12.8%
다방 459
 
9.1%
편의점 449
 
8.9%
과자점 304
 
6.0%
패스트푸드 246
 
4.9%
푸드트럭 26
 
0.5%
백화점 25
 
0.5%
Other values (9) 64
 
1.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2108
Distinct (%)49.1%
Missing118
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean207065.69
Minimum205276.78
Maximum209775.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.9 KiB
2024-05-11T00:38:08.210412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum205276.78
5-th percentile205843.14
Q1206246.31
median207057.12
Q3207691.92
95-th percentile208729.17
Maximum209775.27
Range4498.4834
Interquartile range (IQR)1445.6088

Descriptive statistics

Standard deviation919.94493
Coefficient of variation (CV)0.0044427686
Kurtosis-0.22275834
Mean207065.69
Median Absolute Deviation (MAD)733.15564
Skewness0.5445942
Sum8.88933 × 108
Variance846298.67
MonotonicityNot monotonic
2024-05-11T00:38:08.735765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206217.434726027 161
 
3.6%
208394.416382167 119
 
2.7%
206349.675048285 80
 
1.8%
206445.881091692 39
 
0.9%
205930.90842787 35
 
0.8%
207138.865762508 31
 
0.7%
206479.980833988 25
 
0.6%
208558.286631653 20
 
0.5%
206031.196548172 20
 
0.5%
206107.775163579 20
 
0.5%
Other values (2098) 3743
84.9%
(Missing) 118
 
2.7%
ValueCountFrequency (%)
205276.784422761 2
< 0.1%
205310.285709458 1
< 0.1%
205329.672408805 1
< 0.1%
205335.7201455 2
< 0.1%
205347.861121036 2
< 0.1%
205356.778041972 1
< 0.1%
205359.546199006 2
< 0.1%
205390.463339147 1
< 0.1%
205391.382375241 1
< 0.1%
205404.102971486 2
< 0.1%
ValueCountFrequency (%)
209775.267831522 5
0.1%
209766.973555533 7
0.2%
209734.218553133 5
0.1%
209704.152516892 5
0.1%
209681.727602854 1
 
< 0.1%
209679.58447051 3
0.1%
209637.078215509 3
0.1%
209602.113978282 2
 
< 0.1%
209589.042548422 3
0.1%
209587.408592767 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2108
Distinct (%)49.1%
Missing118
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean449218.45
Minimum447345.67
Maximum452134.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.9 KiB
2024-05-11T00:38:09.086611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447345.67
5-th percentile447709.28
Q1448396.94
median448954.33
Q3449968.08
95-th percentile451332.13
Maximum452134.45
Range4788.7779
Interquartile range (IQR)1571.1401

Descriptive statistics

Standard deviation1095.0095
Coefficient of variation (CV)0.002437588
Kurtosis-0.4864648
Mean449218.45
Median Absolute Deviation (MAD)701.20634
Skewness0.59678736
Sum1.9284948 × 109
Variance1199045.8
MonotonicityNot monotonic
2024-05-11T00:38:09.533313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448506.218743834 161
 
3.6%
448165.279999905 119
 
2.7%
448396.939704285 80
 
1.8%
448922.881688102 39
 
0.9%
447507.969485782 35
 
0.8%
449705.690586932 31
 
0.7%
449827.630945538 25
 
0.6%
448353.905156369 20
 
0.5%
448731.099217371 20
 
0.5%
449029.342177779 20
 
0.5%
Other values (2098) 3743
84.9%
(Missing) 118
 
2.7%
ValueCountFrequency (%)
447345.67489312 2
 
< 0.1%
447352.88652766 14
0.3%
447372.650718356 1
 
< 0.1%
447374.008518853 1
 
< 0.1%
447379.671524405 2
 
< 0.1%
447382.310354354 1
 
< 0.1%
447396.733663032 3
 
0.1%
447399.697266999 1
 
< 0.1%
447404.717192681 1
 
< 0.1%
447413.748434959 1
 
< 0.1%
ValueCountFrequency (%)
452134.45276901 2
< 0.1%
452121.121578344 1
< 0.1%
452112.360344615 1
< 0.1%
452108.545091879 1
< 0.1%
452106.544784594 2
< 0.1%
452094.741574905 1
< 0.1%
452089.198171901 1
< 0.1%
452083.35613137 1
< 0.1%
452078.304729585 1
< 0.1%
452070.118445356 1
< 0.1%

위생업태명
Categorical

Distinct20
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
1087 
일반조리판매
807 
커피숍
733 
다방
455 
기타 휴게음식점
432 
Other values (15)
897 

Length

Max length8
Median length7
Mean length4.2876899
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1087
24.6%
일반조리판매 807
18.3%
커피숍 733
16.6%
다방 455
10.3%
기타 휴게음식점 432
 
9.8%
편의점 303
 
6.9%
과자점 303
 
6.9%
패스트푸드 205
 
4.6%
백화점 20
 
0.5%
푸드트럭 18
 
0.4%
Other values (10) 48
 
1.1%

Length

2024-05-11T00:38:10.000362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1087
22.4%
일반조리판매 807
16.7%
커피숍 733
15.1%
다방 455
9.4%
기타 433
 
8.9%
휴게음식점 432
 
8.9%
편의점 303
 
6.3%
과자점 303
 
6.3%
패스트푸드 205
 
4.2%
백화점 20
 
0.4%
Other values (10) 65
 
1.3%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
3274 
0
1083 
1
 
40
2
 
10
3
 
3

Length

Max length4
Median length4
Mean length3.226706
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row0
3rd row0
4th row0
5th row2

Common Values

ValueCountFrequency (%)
<NA> 3274
74.2%
0 1083
 
24.6%
1 40
 
0.9%
2 10
 
0.2%
3 3
 
0.1%
4 1
 
< 0.1%

Length

2024-05-11T00:38:10.422179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:10.784634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3274
74.2%
0 1083
 
24.6%
1 40
 
0.9%
2 10
 
0.2%
3 3
 
0.1%
4 1
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
3375 
0
936 
2
 
39
3
 
37
1
 
20

Length

Max length4
Median length4
Mean length3.2953979
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row3
5th row2

Common Values

ValueCountFrequency (%)
<NA> 3375
76.5%
0 936
 
21.2%
2 39
 
0.9%
3 37
 
0.8%
1 20
 
0.5%
4 4
 
0.1%

Length

2024-05-11T00:38:11.297500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:11.662963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3375
76.5%
0 936
 
21.2%
2 39
 
0.9%
3 37
 
0.8%
1 20
 
0.5%
4 4
 
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
3411 
주택가주변
680 
기타
 
224
아파트지역
 
62
유흥업소밀집지역
 
19
Other values (3)
 
15

Length

Max length8
Median length4
Mean length4.0949898
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3411
77.3%
주택가주변 680
 
15.4%
기타 224
 
5.1%
아파트지역 62
 
1.4%
유흥업소밀집지역 19
 
0.4%
결혼예식장주변 11
 
0.2%
학교정화(절대) 3
 
0.1%
학교정화(상대) 1
 
< 0.1%

Length

2024-05-11T00:38:12.095840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:12.595734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3411
77.3%
주택가주변 680
 
15.4%
기타 224
 
5.1%
아파트지역 62
 
1.4%
유흥업소밀집지역 19
 
0.4%
결혼예식장주변 11
 
0.2%
학교정화(절대 3
 
0.1%
학교정화(상대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
3462 
기타
619 
을
 
193
지도
 
88
갑
 
35

Length

Max length4
Median length4
Mean length3.5180231
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3462
78.5%
기타 619
 
14.0%
을 193
 
4.4%
지도 88
 
2.0%
갑 35
 
0.8%
자율 14
 
0.3%

Length

2024-05-11T00:38:13.038435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:13.403530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3462
78.5%
기타 619
 
14.0%
을 193
 
4.4%
지도 88
 
2.0%
갑 35
 
0.8%
자율 14
 
0.3%

급수시설구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
3090 
상수도전용
1320 
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.302199
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3090
70.1%
상수도전용 1320
29.9%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-05-11T00:38:13.865955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:14.419854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3090
70.1%
상수도전용 1320
29.9%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
4211 
0
 
200

Length

Max length4
Median length4
Mean length3.8639764
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> 4211
95.5%
0 200
 
4.5%

Length

2024-05-11T00:38:14.890364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:15.255798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4211
95.5%
0 200
 
4.5%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
4209 
0
 
202

Length

Max length4
Median length4
Mean length3.8626162
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> 4209
95.4%
0 202
 
4.6%

Length

2024-05-11T00:38:15.616186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:15.975588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4209
95.4%
0 202
 
4.6%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
4209 
0
 
202

Length

Max length4
Median length4
Mean length3.8626162
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> 4209
95.4%
0 202
 
4.6%

Length

2024-05-11T00:38:16.345236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:16.724130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4209
95.4%
0 202
 
4.6%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
4209 
0
 
202

Length

Max length4
Median length4
Mean length3.8626162
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> 4209
95.4%
0 202
 
4.6%

Length

2024-05-11T00:38:17.182130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:17.576909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4209
95.4%
0 202
 
4.6%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
4209 
0
 
202

Length

Max length4
Median length4
Mean length3.8626162
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> 4209
95.4%
0 202
 
4.6%

Length

2024-05-11T00:38:18.003541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:18.327918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4209
95.4%
0 202
 
4.6%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4411
Missing (%)100.0%
Memory size38.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
4209 
0
 
202

Length

Max length4
Median length4
Mean length3.8626162
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> 4209
95.4%
0 202
 
4.6%

Length

2024-05-11T00:38:18.728047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:19.060011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4209
95.4%
0 202
 
4.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
<NA>
4209 
0
 
202

Length

Max length4
Median length4
Mean length3.8626162
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> 4209
95.4%
0 202
 
4.6%

Length

2024-05-11T00:38:19.434491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:19.811785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4209
95.4%
0 202
 
4.6%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing1087
Missing (%)24.6%
Memory size8.7 KiB
False
3283 
True
 
41
(Missing)
1087 
ValueCountFrequency (%)
False 3283
74.4%
True 41
 
0.9%
(Missing) 1087
 
24.6%
2024-05-11T00:38:20.077021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct1771
Distinct (%)53.3%
Missing1087
Missing (%)24.6%
Infinite0
Infinite (%)0.0%
Mean45.518433
Minimum0
Maximum881.81
Zeros59
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size38.9 KiB
2024-05-11T00:38:20.430495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q114.55
median28.3
Q359.71
95-th percentile129.5
Maximum881.81
Range881.81
Interquartile range (IQR)45.16

Descriptive statistics

Standard deviation56.264051
Coefficient of variation (CV)1.2360718
Kurtosis41.433293
Mean45.518433
Median Absolute Deviation (MAD)19.3
Skewness4.7307499
Sum151303.27
Variance3165.6434
MonotonicityNot monotonic
2024-05-11T00:38:20.892674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.6 217
 
4.9%
3.3 118
 
2.7%
0.0 59
 
1.3%
33.0 51
 
1.2%
16.5 48
 
1.1%
30.0 42
 
1.0%
9.9 38
 
0.9%
20.0 35
 
0.8%
26.4 27
 
0.6%
25.0 25
 
0.6%
Other values (1761) 2664
60.4%
(Missing) 1087
24.6%
ValueCountFrequency (%)
0.0 59
1.3%
0.14 1
 
< 0.1%
0.45 1
 
< 0.1%
0.76 1
 
< 0.1%
1.0 1
 
< 0.1%
1.05 1
 
< 0.1%
1.3 1
 
< 0.1%
1.44 1
 
< 0.1%
1.5 1
 
< 0.1%
1.53 4
 
0.1%
ValueCountFrequency (%)
881.81 1
< 0.1%
834.0 1
< 0.1%
627.82 1
< 0.1%
518.34 1
< 0.1%
500.0 1
< 0.1%
475.71 1
< 0.1%
468.6 1
< 0.1%
446.73 1
< 0.1%
429.75 1
< 0.1%
426.24 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4411
Missing (%)100.0%
Memory size38.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4411
Missing (%)100.0%
Memory size38.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4411
Missing (%)100.0%
Memory size38.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030400003040000-104-1974-0770119740301<NA>3폐업2폐업20000930<NA><NA><NA>02 4666678<NA>143839서울특별시 광진구 군자동 102-32번지<NA><NA>인화2001-11-29 00:00:00I2018-08-31 23:59:59.0다방206266.119712450011.265138다방<NA><NA>주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N74.74<NA><NA><NA>
130400003040000-104-1974-0776219740301<NA>3폐업2폐업19941007<NA><NA><NA>02 4461818<NA>143826서울특별시 광진구 구의동 252-16번지<NA><NA>황태자2001-11-29 00:00:00I2018-08-31 23:59:59.0다방207342.766107448444.754635다방00주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N172.82<NA><NA><NA>
230400003040000-104-1976-0760319760205<NA>3폐업2폐업19891109<NA><NA><NA>02 4669209<NA>143842서울특별시 광진구 자양동 36-30번지<NA><NA>수정2001-11-29 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방00기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N77.5<NA><NA><NA>
330400003040000-104-1976-0761019760205<NA>3폐업2폐업19920714<NA><NA><NA>02 00000<NA>143915서울특별시 광진구 화양동 111-5번지<NA><NA>판도라2001-11-29 00:00:00I2018-08-31 23:59:59.0다방206279.821132449481.157001다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.36<NA><NA><NA>
430400003040000-104-1976-0761219761230<NA>3폐업2폐업19930820<NA><NA><NA>02 00000<NA>143915서울특별시 광진구 화양동 111-49번지<NA><NA>오두막2001-11-29 00:00:00I2018-08-31 23:59:59.0다방206254.165297449493.752555다방22주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N189.02<NA><NA><NA>
530400003040000-104-1976-0761519760205<NA>3폐업2폐업20000811<NA><NA><NA>0200000000<NA>143915서울특별시 광진구 화양동 168-2번지<NA><NA>에스페로2001-11-29 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방12주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630400003040000-104-1976-0774719761101<NA>3폐업2폐업19990625<NA><NA><NA>02 4672561<NA>143904서울특별시 광진구 중곡동 245-39번지<NA><NA>영2001-11-29 00:00:00I2018-08-31 23:59:59.0다방206932.729539451161.083521다방<NA><NA>주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N76.48<NA><NA><NA>
730400003040000-104-1976-0779019761231<NA>3폐업2폐업20000217<NA><NA><NA>02 4630015<NA>143846서울특별시 광진구 자양동 236-76번지<NA><NA>종2001-11-29 00:00:00I2018-08-31 23:59:59.0다방205520.920308448279.862521다방<NA><NA>주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N91.02<NA><NA><NA>
830400003040000-104-1976-0782819760205<NA>3폐업2폐업19960918<NA><NA><NA>02 4462109<NA>143890서울특별시 광진구 중곡동 116-6번지<NA><NA>능2001-11-29 00:00:00I2018-08-31 23:59:59.0다방207731.485258450196.465106다방03주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N100.38<NA><NA><NA>
930400003040000-104-1977-0761919770127<NA>3폐업2폐업19960419<NA><NA><NA>02 4444149<NA>143824서울특별시 광진구 구의동 236-53번지<NA><NA>길2001-11-29 00:00:00I2018-08-31 23:59:59.0다방207400.608063448930.683212다방04주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N106.2<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
440130400003040000-104-2024-000692024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.0143-901서울특별시 광진구 중곡동 192-54서울특별시 광진구 동일로72길 53, 1층 가운데호 (중곡동)4907빅보스 후르츠2024-04-26 10:47:15I2023-12-03 22:08:00.0기타 휴게음식점207051.523405451446.211634<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
440230400003040000-104-2024-000702024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3143-845서울특별시 광진구 자양동 97-5 뚝섬 2호 매점서울특별시 광진구 강변북로 2210, 뚝섬 2호 매점 (자양동)5097씨유(CU)한강르네상스 뚝섬2호점2024-04-26 11:26:19I2023-12-03 22:08:00.0편의점205607.186172447642.163715<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
440330400003040000-104-2024-000712024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>102.52143-889서울특별시 광진구 중곡동 107-40서울특별시 광진구 영화사로 51, 제1동 제1층 101호 (중곡동)4947굿띵(Good Thing)2024-04-29 13:37:14I2023-12-05 00:01:00.0커피숍208094.585958450390.016216<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
440430400003040000-104-2024-000722024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.9143-190서울특별시 광진구 자양동 861 자양 호반써밋서울특별시 광진구 능동로 69, 상가동 1층 121호 (자양동, 자양 호반써밋)5074영미화김밥건대점2024-04-29 14:42:55I2023-12-05 00:01:00.0기타 휴게음식점206014.599715448359.99046<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
440530400003040000-104-2024-000732024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3143-888서울특별시 광진구 중곡동 98-22서울특별시 광진구 자양로53길 70, 1층 (중곡동)4951이마트24 중곡사랑2024-04-29 14:47:35I2023-12-05 00:01:00.0편의점207969.487408450408.82353<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
440630400003040000-104-2024-000742024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.7143-758서울특별시 광진구 자양동 227-342 롯데백화점서울특별시 광진구 능동로 92, 롯데백화점 지하1층 (자양동)5065몽슈슈 롯데백화점 건대스타시티점2024-05-01 10:58:33I2023-12-05 00:03:00.0기타 휴게음식점206217.434726448506.218744<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
440730400003040000-104-2024-000752024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0143-915서울특별시 광진구 화양동 111-161서울특별시 광진구 능동로19길 36, 5층 (화양동)5009히어로보드게임카페 어린이대공원점2024-05-02 10:30:05I2023-12-05 00:04:00.0커피숍206276.769586449466.36074<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
440830400003040000-104-2024-000762024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.0143-915서울특별시 광진구 화양동 16-43서울특별시 광진구 능동로13길 84, 1층 일부호 (화양동)5012요거트아이스크림의 정석 건대점2024-05-03 15:59:11I2023-12-05 00:05:00.0아이스크림206007.800552449234.773599<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
440930400003040000-104-2024-000772024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.0143-843서울특별시 광진구 자양동 48-36서울특별시 광진구 뚝섬로32길 29, 2층 201호 (자양동)5085커피보이즈2024-05-07 14:36:57I2023-12-05 00:09:00.0커피숍205848.046243448004.406386<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
441030400003040000-104-2024-000782024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3143-846서울특별시 광진구 자양동 236 507-8호서울특별시 광진구 뚝섬로 471, 1층 507, 508호 (자양동)5080씨유(CU) 자양롯데캐슬정문점2024-05-07 16:54:15I2023-12-05 00:09:00.0편의점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>