Overview

Dataset statistics

Number of variables44
Number of observations4307
Missing cells48935
Missing cells (%)25.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory376.0 B

Variable types

Categorical18
Text7
DateTime4
Unsupported8
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18682/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (53.9%)Imbalance
등급구분명 is highly imbalanced (53.6%)Imbalance
총인원 is highly imbalanced (74.6%)Imbalance
본사종업원수 is highly imbalanced (74.2%)Imbalance
공장사무직종업원수 is highly imbalanced (74.2%)Imbalance
공장판매직종업원수 is highly imbalanced (74.2%)Imbalance
공장생산직종업원수 is highly imbalanced (74.2%)Imbalance
보증액 is highly imbalanced (74.2%)Imbalance
월세액 is highly imbalanced (74.2%)Imbalance
다중이용업소여부 is highly imbalanced (91.8%)Imbalance
인허가취소일자 has 4307 (100.0%) missing valuesMissing
폐업일자 has 1244 (28.9%) missing valuesMissing
휴업시작일자 has 4307 (100.0%) missing valuesMissing
휴업종료일자 has 4307 (100.0%) missing valuesMissing
재개업일자 has 4307 (100.0%) missing valuesMissing
전화번호 has 2333 (54.2%) missing valuesMissing
도로명주소 has 1573 (36.5%) missing valuesMissing
도로명우편번호 has 1596 (37.1%) missing valuesMissing
좌표정보(X) has 245 (5.7%) missing valuesMissing
좌표정보(Y) has 245 (5.7%) missing valuesMissing
남성종사자수 has 2725 (63.3%) missing valuesMissing
여성종사자수 has 2724 (63.2%) missing valuesMissing
건물소유구분명 has 4307 (100.0%) missing valuesMissing
다중이용업소여부 has 889 (20.6%) missing valuesMissing
시설총규모 has 889 (20.6%) missing valuesMissing
전통업소지정번호 has 4307 (100.0%) missing valuesMissing
전통업소주된음식 has 4307 (100.0%) missing valuesMissing
홈페이지 has 4307 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 45.67775934)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
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 1418 (32.9%) zerosZeros
여성종사자수 has 921 (21.4%) zerosZeros

Reproduction

Analysis started2024-05-11 01:38:54.198953
Analysis finished2024-05-11 01:38:57.389571
Duration3.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
3050000
4307 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 4307
100.0%

Length

2024-05-11T01:38:57.572532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:38:57.918437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 4307
100.0%

관리번호
Text

UNIQUE 

Distinct4307
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
2024-05-11T01:38:58.381310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters94754
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

Unique4307 ?
Unique (%)100.0%

Sample

1st row3050000-104-1965-09774
2nd row3050000-104-1967-09246
3rd row3050000-104-1968-09244
4th row3050000-104-1968-09253
5th row3050000-104-1968-09293
ValueCountFrequency (%)
3050000-104-1965-09774 1
 
< 0.1%
3050000-104-2017-00001 1
 
< 0.1%
3050000-104-2017-00017 1
 
< 0.1%
3050000-104-2016-00210 1
 
< 0.1%
3050000-104-2016-00211 1
 
< 0.1%
3050000-104-2016-00212 1
 
< 0.1%
3050000-104-2016-00213 1
 
< 0.1%
3050000-104-2016-00214 1
 
< 0.1%
3050000-104-2016-00215 1
 
< 0.1%
3050000-104-2016-00216 1
 
< 0.1%
Other values (4297) 4297
99.8%
2024-05-11T01:38:59.301298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40219
42.4%
- 12921
 
13.6%
1 10075
 
10.6%
3 5907
 
6.2%
4 5745
 
6.1%
5 5680
 
6.0%
2 5543
 
5.8%
9 4082
 
4.3%
8 1929
 
2.0%
6 1366
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81833
86.4%
Dash Punctuation 12921
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40219
49.1%
1 10075
 
12.3%
3 5907
 
7.2%
4 5745
 
7.0%
5 5680
 
6.9%
2 5543
 
6.8%
9 4082
 
5.0%
8 1929
 
2.4%
6 1366
 
1.7%
7 1287
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 12921
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 94754
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40219
42.4%
- 12921
 
13.6%
1 10075
 
10.6%
3 5907
 
6.2%
4 5745
 
6.1%
5 5680
 
6.0%
2 5543
 
5.8%
9 4082
 
4.3%
8 1929
 
2.0%
6 1366
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 94754
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40219
42.4%
- 12921
 
13.6%
1 10075
 
10.6%
3 5907
 
6.2%
4 5745
 
6.1%
5 5680
 
6.0%
2 5543
 
5.8%
9 4082
 
4.3%
8 1929
 
2.0%
6 1366
 
1.4%
Distinct3259
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
Minimum1965-11-20 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T01:38:59.744284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:39:00.223195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4307
Missing (%)100.0%
Memory size38.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
3
3063 
1
1244 

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 3063
71.1%
1 1244
28.9%

Length

2024-05-11T01:39:00.636970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:00.964695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3063
71.1%
1 1244
28.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
폐업
3063 
영업/정상
1244 

Length

Max length5
Median length2
Mean length2.8664964
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3063
71.1%
영업/정상 1244
28.9%

Length

2024-05-11T01:39:01.353958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:01.893078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3063
71.1%
영업/정상 1244
28.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
2
3063 
1
1244 

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 3063
71.1%
1 1244
28.9%

Length

2024-05-11T01:39:02.234890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:02.572518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3063
71.1%
1 1244
28.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
폐업
3063 
영업
1244 

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 3063
71.1%
영업 1244
28.9%

Length

2024-05-11T01:39:03.110252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:03.517288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3063
71.1%
영업 1244
28.9%

폐업일자
Date

MISSING 

Distinct2326
Distinct (%)75.9%
Missing1244
Missing (%)28.9%
Memory size33.8 KiB
Minimum1989-03-07 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T01:39:03.964940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:39:04.540272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4307
Missing (%)100.0%
Memory size38.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4307
Missing (%)100.0%
Memory size38.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4307
Missing (%)100.0%
Memory size38.0 KiB

전화번호
Text

MISSING 

Distinct1759
Distinct (%)89.1%
Missing2333
Missing (%)54.2%
Memory size33.8 KiB
2024-05-11T01:39:05.149774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.023303
Min length2

Characters and Unicode

Total characters19786
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

Unique1679 ?
Unique (%)85.1%

Sample

1st row0202123058
2nd row0209683602
3rd row02 9238282
4th row0202127659
5th row0209230870
ValueCountFrequency (%)
02 925
30.6%
0200000000 36
 
1.2%
0 30
 
1.0%
00000 28
 
0.9%
070 17
 
0.6%
031 13
 
0.4%
32848112 11
 
0.4%
959 9
 
0.3%
960 8
 
0.3%
969 7
 
0.2%
Other values (1806) 1937
64.1%
2024-05-11T01:39:06.196377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4106
20.8%
0 4033
20.4%
9 1768
8.9%
6 1533
 
7.7%
4 1439
 
7.3%
1357
 
6.9%
5 1170
 
5.9%
1 1165
 
5.9%
3 1149
 
5.8%
7 1094
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18429
93.1%
Space Separator 1357
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4106
22.3%
0 4033
21.9%
9 1768
9.6%
6 1533
 
8.3%
4 1439
 
7.8%
5 1170
 
6.3%
1 1165
 
6.3%
3 1149
 
6.2%
7 1094
 
5.9%
8 972
 
5.3%
Space Separator
ValueCountFrequency (%)
1357
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19786
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4106
20.8%
0 4033
20.4%
9 1768
8.9%
6 1533
 
7.7%
4 1439
 
7.3%
1357
 
6.9%
5 1170
 
5.9%
1 1165
 
5.9%
3 1149
 
5.8%
7 1094
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4106
20.8%
0 4033
20.4%
9 1768
8.9%
6 1533
 
7.7%
4 1439
 
7.3%
1357
 
6.9%
5 1170
 
5.9%
1 1165
 
5.9%
3 1149
 
5.8%
7 1094
 
5.5%
Distinct2118
Distinct (%)49.3%
Missing8
Missing (%)0.2%
Memory size33.8 KiB
2024-05-11T01:39:07.107717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9304489
Min length3

Characters and Unicode

Total characters21196
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

Unique1641 ?
Unique (%)38.2%

Sample

1st row78.06
2nd row74.76
3rd row193.55
4th row82.21
5th row129.67
ValueCountFrequency (%)
3.30 289
 
6.7%
6.60 119
 
2.8%
33.00 78
 
1.8%
10.00 72
 
1.7%
16.50 47
 
1.1%
20.00 47
 
1.1%
30.00 47
 
1.1%
26.40 45
 
1.0%
9.90 40
 
0.9%
15.00 32
 
0.7%
Other values (2108) 3483
81.0%
2024-05-11T01:39:08.359066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4299
20.3%
0 4271
20.2%
3 2012
9.5%
1 1835
8.7%
2 1691
 
8.0%
6 1504
 
7.1%
4 1302
 
6.1%
5 1176
 
5.5%
9 1109
 
5.2%
8 1035
 
4.9%
Other values (2) 962
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16896
79.7%
Other Punctuation 4300
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4271
25.3%
3 2012
11.9%
1 1835
10.9%
2 1691
 
10.0%
6 1504
 
8.9%
4 1302
 
7.7%
5 1176
 
7.0%
9 1109
 
6.6%
8 1035
 
6.1%
7 961
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 4299
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 21196
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4299
20.3%
0 4271
20.2%
3 2012
9.5%
1 1835
8.7%
2 1691
 
8.0%
6 1504
 
7.1%
4 1302
 
6.1%
5 1176
 
5.5%
9 1109
 
5.2%
8 1035
 
4.9%
Other values (2) 962
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21196
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4299
20.3%
0 4271
20.2%
3 2012
9.5%
1 1835
8.7%
2 1691
 
8.0%
6 1504
 
7.1%
4 1302
 
6.1%
5 1176
 
5.5%
9 1109
 
5.2%
8 1035
 
4.9%
Other values (2) 962
 
4.5%
Distinct187
Distinct (%)4.3%
Missing4
Missing (%)0.1%
Memory size33.8 KiB
2024-05-11T01:39:09.217697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1352545
Min length6

Characters and Unicode

Total characters26400
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

Unique28 ?
Unique (%)0.7%

Sample

1st row130857
2nd row130080
3rd row130812
4th row130859
5th row130820
ValueCountFrequency (%)
130851 324
 
7.5%
130872 277
 
6.4%
130840 160
 
3.7%
130876 118
 
2.7%
130831 118
 
2.7%
130817 111
 
2.6%
130842 87
 
2.0%
130805 87
 
2.0%
130864 86
 
2.0%
130859 81
 
1.9%
Other values (177) 2854
66.3%
2024-05-11T01:39:10.643387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5806
22.0%
1 5425
20.5%
3 5133
19.4%
8 4330
16.4%
7 1103
 
4.2%
2 1008
 
3.8%
5 1004
 
3.8%
4 893
 
3.4%
6 778
 
2.9%
- 582
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25818
97.8%
Dash Punctuation 582
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5806
22.5%
1 5425
21.0%
3 5133
19.9%
8 4330
16.8%
7 1103
 
4.3%
2 1008
 
3.9%
5 1004
 
3.9%
4 893
 
3.5%
6 778
 
3.0%
9 338
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 582
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26400
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5806
22.0%
1 5425
20.5%
3 5133
19.4%
8 4330
16.4%
7 1103
 
4.2%
2 1008
 
3.8%
5 1004
 
3.8%
4 893
 
3.4%
6 778
 
2.9%
- 582
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5806
22.0%
1 5425
20.5%
3 5133
19.4%
8 4330
16.4%
7 1103
 
4.2%
2 1008
 
3.8%
5 1004
 
3.8%
4 893
 
3.4%
6 778
 
2.9%
- 582
 
2.2%
Distinct3359
Distinct (%)78.1%
Missing4
Missing (%)0.1%
Memory size33.8 KiB
2024-05-11T01:39:11.407233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length49
Mean length25.72554
Min length15

Characters and Unicode

Total characters110697
Distinct characters361
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2845 ?
Unique (%)66.1%

Sample

1st row서울특별시 동대문구 전농동 496-1번지
2nd row서울특별시 동대문구 이문동 258-17번지
3rd row서울특별시 동대문구 신설동 101-7번지
4th row서울특별시 동대문구 전농동 655-30번지
5th row서울특별시 동대문구 용두동 119-15번지
ValueCountFrequency (%)
동대문구 4305
21.9%
서울특별시 4302
21.9%
장안동 857
 
4.4%
전농동 767
 
3.9%
답십리동 524
 
2.7%
이문동 422
 
2.1%
회기동 388
 
2.0%
휘경동 333
 
1.7%
용두동 320
 
1.6%
제기동 292
 
1.5%
Other values (3428) 7151
36.4%
2024-05-11T01:39:12.648934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18724
 
16.9%
8763
 
7.9%
4790
 
4.3%
4440
 
4.0%
4355
 
3.9%
4337
 
3.9%
4324
 
3.9%
4320
 
3.9%
4303
 
3.9%
4302
 
3.9%
Other values (351) 48039
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66192
59.8%
Decimal Number 20647
 
18.7%
Space Separator 18724
 
16.9%
Dash Punctuation 3936
 
3.6%
Close Punctuation 408
 
0.4%
Open Punctuation 408
 
0.4%
Uppercase Letter 168
 
0.2%
Other Punctuation 160
 
0.1%
Lowercase Letter 38
 
< 0.1%
Math Symbol 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8763
13.2%
4790
 
7.2%
4440
 
6.7%
4355
 
6.6%
4337
 
6.6%
4324
 
6.5%
4320
 
6.5%
4303
 
6.5%
4302
 
6.5%
3318
 
5.0%
Other values (305) 18940
28.6%
Uppercase Letter
ValueCountFrequency (%)
S 34
20.2%
K 32
19.0%
Y 12
 
7.1%
L 10
 
6.0%
E 8
 
4.8%
W 8
 
4.8%
C 7
 
4.2%
O 6
 
3.6%
T 6
 
3.6%
B 6
 
3.6%
Other values (11) 39
23.2%
Decimal Number
ValueCountFrequency (%)
1 4171
20.2%
3 2772
13.4%
2 2739
13.3%
5 1969
9.5%
4 1846
8.9%
6 1728
8.4%
0 1548
 
7.5%
9 1510
 
7.3%
8 1227
 
5.9%
7 1137
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
e 14
36.8%
t 6
15.8%
s 6
15.8%
l 6
15.8%
a 3
 
7.9%
w 3
 
7.9%
Other Punctuation
ValueCountFrequency (%)
, 155
96.9%
@ 2
 
1.2%
: 2
 
1.2%
& 1
 
0.6%
Space Separator
ValueCountFrequency (%)
18724
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3936
100.0%
Close Punctuation
ValueCountFrequency (%)
) 408
100.0%
Open Punctuation
ValueCountFrequency (%)
( 408
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66192
59.8%
Common 44299
40.0%
Latin 206
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8763
13.2%
4790
 
7.2%
4440
 
6.7%
4355
 
6.6%
4337
 
6.6%
4324
 
6.5%
4320
 
6.5%
4303
 
6.5%
4302
 
6.5%
3318
 
5.0%
Other values (305) 18940
28.6%
Latin
ValueCountFrequency (%)
S 34
16.5%
K 32
15.5%
e 14
 
6.8%
Y 12
 
5.8%
L 10
 
4.9%
E 8
 
3.9%
W 8
 
3.9%
C 7
 
3.4%
t 6
 
2.9%
s 6
 
2.9%
Other values (17) 69
33.5%
Common
ValueCountFrequency (%)
18724
42.3%
1 4171
 
9.4%
- 3936
 
8.9%
3 2772
 
6.3%
2 2739
 
6.2%
5 1969
 
4.4%
4 1846
 
4.2%
6 1728
 
3.9%
0 1548
 
3.5%
9 1510
 
3.4%
Other values (9) 3356
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66192
59.8%
ASCII 44505
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18724
42.1%
1 4171
 
9.4%
- 3936
 
8.8%
3 2772
 
6.2%
2 2739
 
6.2%
5 1969
 
4.4%
4 1846
 
4.1%
6 1728
 
3.9%
0 1548
 
3.5%
9 1510
 
3.4%
Other values (36) 3562
 
8.0%
Hangul
ValueCountFrequency (%)
8763
13.2%
4790
 
7.2%
4440
 
6.7%
4355
 
6.6%
4337
 
6.6%
4324
 
6.5%
4320
 
6.5%
4303
 
6.5%
4302
 
6.5%
3318
 
5.0%
Other values (305) 18940
28.6%

도로명주소
Text

MISSING 

Distinct2305
Distinct (%)84.3%
Missing1573
Missing (%)36.5%
Memory size33.8 KiB
2024-05-11T01:39:13.628805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length55
Mean length33.545721
Min length22

Characters and Unicode

Total characters91714
Distinct characters374
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2036 ?
Unique (%)74.5%

Sample

1st row서울특별시 동대문구 이문로 144 (이문동)
2nd row서울특별시 동대문구 왕산로 4 (신설동)
3rd row서울특별시 동대문구 답십리로 4 (용두동,(답십리길 4))
4th row서울특별시 동대문구 고산자로 391 (용두동)
5th row서울특별시 동대문구 고산자로 484 (제기동,(고산자로 240))
ValueCountFrequency (%)
동대문구 2737
 
15.3%
서울특별시 2733
 
15.3%
1층 1525
 
8.5%
장안동 508
 
2.8%
전농동 472
 
2.6%
왕산로 313
 
1.8%
답십리동 262
 
1.5%
회기동 258
 
1.4%
이문동 250
 
1.4%
휘경동 229
 
1.3%
Other values (1693) 8561
48.0%
2024-05-11T01:39:15.013529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15118
 
16.5%
5760
 
6.3%
1 4687
 
5.1%
3284
 
3.6%
3275
 
3.6%
, 3107
 
3.4%
2911
 
3.2%
( 2898
 
3.2%
) 2898
 
3.2%
2854
 
3.1%
Other values (364) 44922
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53885
58.8%
Space Separator 15118
 
16.5%
Decimal Number 13176
 
14.4%
Other Punctuation 3112
 
3.4%
Open Punctuation 2899
 
3.2%
Close Punctuation 2899
 
3.2%
Dash Punctuation 330
 
0.4%
Uppercase Letter 197
 
0.2%
Lowercase Letter 52
 
0.1%
Math Symbol 46
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5760
 
10.7%
3284
 
6.1%
3275
 
6.1%
2911
 
5.4%
2854
 
5.3%
2831
 
5.3%
2800
 
5.2%
2748
 
5.1%
2737
 
5.1%
2733
 
5.1%
Other values (306) 21952
40.7%
Uppercase Letter
ValueCountFrequency (%)
S 31
15.7%
K 28
14.2%
B 23
11.7%
Y 13
 
6.6%
L 10
 
5.1%
C 10
 
5.1%
E 9
 
4.6%
W 9
 
4.6%
A 8
 
4.1%
G 7
 
3.6%
Other values (11) 49
24.9%
Lowercase Letter
ValueCountFrequency (%)
e 16
30.8%
s 7
13.5%
l 7
13.5%
t 6
 
11.5%
a 4
 
7.7%
w 3
 
5.8%
i 1
 
1.9%
n 1
 
1.9%
r 1
 
1.9%
x 1
 
1.9%
Other values (5) 5
 
9.6%
Decimal Number
ValueCountFrequency (%)
1 4687
35.6%
2 2077
15.8%
3 1206
 
9.2%
0 1027
 
7.8%
4 1022
 
7.8%
6 775
 
5.9%
5 653
 
5.0%
8 615
 
4.7%
7 613
 
4.7%
9 501
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 3107
99.8%
@ 2
 
0.1%
& 1
 
< 0.1%
* 1
 
< 0.1%
. 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2898
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2898
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
15118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 330
100.0%
Math Symbol
ValueCountFrequency (%)
~ 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53885
58.8%
Common 37580
41.0%
Latin 249
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5760
 
10.7%
3284
 
6.1%
3275
 
6.1%
2911
 
5.4%
2854
 
5.3%
2831
 
5.3%
2800
 
5.2%
2748
 
5.1%
2737
 
5.1%
2733
 
5.1%
Other values (306) 21952
40.7%
Latin
ValueCountFrequency (%)
S 31
 
12.4%
K 28
 
11.2%
B 23
 
9.2%
e 16
 
6.4%
Y 13
 
5.2%
L 10
 
4.0%
C 10
 
4.0%
E 9
 
3.6%
W 9
 
3.6%
A 8
 
3.2%
Other values (26) 92
36.9%
Common
ValueCountFrequency (%)
15118
40.2%
1 4687
 
12.5%
, 3107
 
8.3%
( 2898
 
7.7%
) 2898
 
7.7%
2 2077
 
5.5%
3 1206
 
3.2%
0 1027
 
2.7%
4 1022
 
2.7%
6 775
 
2.1%
Other values (12) 2765
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53885
58.8%
ASCII 37829
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15118
40.0%
1 4687
 
12.4%
, 3107
 
8.2%
( 2898
 
7.7%
) 2898
 
7.7%
2 2077
 
5.5%
3 1206
 
3.2%
0 1027
 
2.7%
4 1022
 
2.7%
6 775
 
2.0%
Other values (48) 3014
 
8.0%
Hangul
ValueCountFrequency (%)
5760
 
10.7%
3284
 
6.1%
3275
 
6.1%
2911
 
5.4%
2854
 
5.3%
2831
 
5.3%
2800
 
5.2%
2748
 
5.1%
2737
 
5.1%
2733
 
5.1%
Other values (306) 21952
40.7%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct225
Distinct (%)8.3%
Missing1596
Missing (%)37.1%
Infinite0
Infinite (%)0.0%
Mean2537.1199
Minimum2400
Maximum14284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.0 KiB
2024-05-11T01:39:15.444464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2400
5-th percentile2428
Q12462
median2540
Q32586
95-th percentile2637
Maximum14284
Range11884
Interquartile range (IQR)124

Descriptive statistics

Standard deviation235.74955
Coefficient of variation (CV)0.092920148
Kurtosis2276.7159
Mean2537.1199
Median Absolute Deviation (MAD)56
Skewness45.677759
Sum6878132
Variance55577.852
MonotonicityNot monotonic
2024-05-11T01:39:15.907407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2555 185
 
4.3%
2453 88
 
2.0%
2637 56
 
1.3%
2447 56
 
1.3%
2454 46
 
1.1%
2624 43
 
1.0%
2452 41
 
1.0%
2594 37
 
0.9%
2446 34
 
0.8%
2565 33
 
0.8%
Other values (215) 2092
48.6%
(Missing) 1596
37.1%
ValueCountFrequency (%)
2400 2
 
< 0.1%
2401 1
 
< 0.1%
2402 1
 
< 0.1%
2403 4
 
0.1%
2405 7
0.2%
2406 10
0.2%
2407 6
0.1%
2408 1
 
< 0.1%
2409 10
0.2%
2410 3
 
0.1%
ValueCountFrequency (%)
14284 1
 
< 0.1%
2646 4
 
0.1%
2645 14
0.3%
2644 32
0.7%
2643 22
0.5%
2642 9
 
0.2%
2641 4
 
0.1%
2640 6
 
0.1%
2639 22
0.5%
2638 12
 
0.3%
Distinct3879
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
2024-05-11T01:39:16.598395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length7.0032505
Min length1

Characters and Unicode

Total characters30163
Distinct characters876
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3590 ?
Unique (%)83.4%

Sample

1st row파리
2nd row양지
3rd row동화다방
4th row새마을
5th row동아
ValueCountFrequency (%)
세븐일레븐 58
 
1.1%
씨유 38
 
0.7%
카페 36
 
0.7%
gs25 33
 
0.6%
장안점 26
 
0.5%
지에스25 25
 
0.5%
씨유(cu 24
 
0.4%
coffee 22
 
0.4%
경희대점 22
 
0.4%
청량리점 21
 
0.4%
Other values (4098) 5040
94.3%
2024-05-11T01:39:17.814584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1261
 
4.2%
1041
 
3.5%
847
 
2.8%
776
 
2.6%
706
 
2.3%
626
 
2.1%
) 570
 
1.9%
( 569
 
1.9%
530
 
1.8%
386
 
1.3%
Other values (866) 22851
75.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24714
81.9%
Lowercase Letter 1264
 
4.2%
Uppercase Letter 1201
 
4.0%
Space Separator 1041
 
3.5%
Decimal Number 699
 
2.3%
Close Punctuation 570
 
1.9%
Open Punctuation 569
 
1.9%
Other Punctuation 85
 
0.3%
Dash Punctuation 14
 
< 0.1%
Connector Punctuation 2
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1261
 
5.1%
847
 
3.4%
776
 
3.1%
706
 
2.9%
626
 
2.5%
530
 
2.1%
386
 
1.6%
349
 
1.4%
322
 
1.3%
312
 
1.3%
Other values (784) 18599
75.3%
Lowercase Letter
ValueCountFrequency (%)
e 227
18.0%
a 153
12.1%
o 115
 
9.1%
f 110
 
8.7%
n 65
 
5.1%
i 63
 
5.0%
l 62
 
4.9%
c 61
 
4.8%
t 60
 
4.7%
r 54
 
4.3%
Other values (16) 294
23.3%
Uppercase Letter
ValueCountFrequency (%)
C 178
14.8%
S 170
14.2%
G 132
11.0%
E 83
 
6.9%
U 80
 
6.7%
P 66
 
5.5%
O 56
 
4.7%
A 56
 
4.7%
F 52
 
4.3%
T 39
 
3.2%
Other values (16) 289
24.1%
Other Punctuation
ValueCountFrequency (%)
& 24
28.2%
. 20
23.5%
, 13
15.3%
' 10
11.8%
/ 6
 
7.1%
? 6
 
7.1%
2
 
2.4%
; 1
 
1.2%
% 1
 
1.2%
# 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
2 269
38.5%
5 210
30.0%
1 61
 
8.7%
3 35
 
5.0%
4 32
 
4.6%
9 29
 
4.1%
7 23
 
3.3%
0 20
 
2.9%
8 17
 
2.4%
6 3
 
0.4%
Modifier Symbol
ValueCountFrequency (%)
˚ 1
50.0%
` 1
50.0%
Space Separator
ValueCountFrequency (%)
1041
100.0%
Close Punctuation
ValueCountFrequency (%)
) 570
100.0%
Open Punctuation
ValueCountFrequency (%)
( 569
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24710
81.9%
Common 2984
 
9.9%
Latin 2465
 
8.2%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1261
 
5.1%
847
 
3.4%
776
 
3.1%
706
 
2.9%
626
 
2.5%
530
 
2.1%
386
 
1.6%
349
 
1.4%
322
 
1.3%
312
 
1.3%
Other values (780) 18595
75.3%
Latin
ValueCountFrequency (%)
e 227
 
9.2%
C 178
 
7.2%
S 170
 
6.9%
a 153
 
6.2%
G 132
 
5.4%
o 115
 
4.7%
f 110
 
4.5%
E 83
 
3.4%
U 80
 
3.2%
P 66
 
2.7%
Other values (42) 1151
46.7%
Common
ValueCountFrequency (%)
1041
34.9%
) 570
19.1%
( 569
19.1%
2 269
 
9.0%
5 210
 
7.0%
1 61
 
2.0%
3 35
 
1.2%
4 32
 
1.1%
9 29
 
1.0%
& 24
 
0.8%
Other values (20) 144
 
4.8%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24710
81.9%
ASCII 5445
 
18.1%
CJK 4
 
< 0.1%
None 2
 
< 0.1%
Punctuation 1
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1261
 
5.1%
847
 
3.4%
776
 
3.1%
706
 
2.9%
626
 
2.5%
530
 
2.1%
386
 
1.6%
349
 
1.4%
322
 
1.3%
312
 
1.3%
Other values (780) 18595
75.3%
ASCII
ValueCountFrequency (%)
1041
19.1%
) 570
 
10.5%
( 569
 
10.4%
2 269
 
4.9%
e 227
 
4.2%
5 210
 
3.9%
C 178
 
3.3%
S 170
 
3.1%
a 153
 
2.8%
G 132
 
2.4%
Other values (69) 1926
35.4%
None
ValueCountFrequency (%)
2
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%
Modifier Letters
ValueCountFrequency (%)
˚ 1
100.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct3470
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
Minimum1999-01-04 00:00:00
Maximum2024-05-08 15:07:11
2024-05-11T01:39:18.274925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:39:18.787452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
I
3042 
U
1265 

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 3042
70.6%
U 1265
29.4%

Length

2024-05-11T01:39:19.217042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:19.519423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3042
70.6%
u 1265
29.4%
Distinct1020
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T01:39:19.919999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:39:20.367951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct17
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
커피숍
940 
다방
883 
기타 휴게음식점
878 
일반조리판매
528 
편의점
416 
Other values (12)
662 

Length

Max length8
Median length6
Mean length4.3222661
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 940
21.8%
다방 883
20.5%
기타 휴게음식점 878
20.4%
일반조리판매 528
12.3%
편의점 416
9.7%
과자점 312
 
7.2%
패스트푸드 263
 
6.1%
백화점 26
 
0.6%
아이스크림 17
 
0.4%
전통찻집 12
 
0.3%
Other values (7) 32
 
0.7%

Length

2024-05-11T01:39:20.860435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 940
18.1%
다방 883
17.0%
기타 878
16.9%
휴게음식점 878
16.9%
일반조리판매 528
10.2%
편의점 416
8.0%
과자점 312
 
6.0%
패스트푸드 263
 
5.1%
백화점 26
 
0.5%
아이스크림 17
 
0.3%
Other values (8) 44
 
0.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2112
Distinct (%)52.0%
Missing245
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean204688.27
Minimum186566.14
Maximum206717.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.0 KiB
2024-05-11T01:39:21.279066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum186566.14
5-th percentile202483.32
Q1204081.28
median204846.38
Q3205531.93
95-th percentile206325.35
Maximum206717.46
Range20151.315
Interquartile range (IQR)1450.6508

Descriptive statistics

Standard deviation1159.5769
Coefficient of variation (CV)0.0056650872
Kurtosis13.958161
Mean204688.27
Median Absolute Deviation (MAD)765.10256
Skewness-1.361279
Sum8.3144375 × 108
Variance1344618.6
MonotonicityNot monotonic
2024-05-11T01:39:21.759670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204081.282117393 194
 
4.5%
203996.013917877 73
 
1.7%
204469.209049094 58
 
1.3%
203356.957362754 49
 
1.1%
206325.349431713 41
 
1.0%
205271.704936121 23
 
0.5%
206521.405320134 20
 
0.5%
203075.098504907 19
 
0.4%
204082.111844228 18
 
0.4%
204089.817117361 16
 
0.4%
Other values (2102) 3551
82.4%
(Missing) 245
 
5.7%
ValueCountFrequency (%)
186566.141360856 1
 
< 0.1%
201995.643218229 1
 
< 0.1%
202010.550405076 1
 
< 0.1%
202013.401502902 3
0.1%
202022.650035503 2
< 0.1%
202023.921749857 2
< 0.1%
202033.014104401 2
< 0.1%
202034.733564967 1
 
< 0.1%
202036.453390905 4
0.1%
202041.708509704 1
 
< 0.1%
ValueCountFrequency (%)
206717.456167249 7
0.2%
206713.730568115 3
 
0.1%
206637.16421148 1
 
< 0.1%
206590.046202018 8
0.2%
206586.572428103 3
 
0.1%
206574.561496753 1
 
< 0.1%
206573.59398246 1
 
< 0.1%
206562.649224959 2
 
< 0.1%
206560.736934242 1
 
< 0.1%
206546.935298263 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2112
Distinct (%)52.0%
Missing245
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean453136.29
Minimum441737.13
Maximum455917.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.0 KiB
2024-05-11T01:39:22.217390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441737.13
5-th percentile451440.24
Q1452319.78
median452986.95
Q3454119.84
95-th percentile454939.01
Maximum455917.55
Range14180.425
Interquartile range (IQR)1800.063

Descriptive statistics

Standard deviation1110.9097
Coefficient of variation (CV)0.0024516017
Kurtosis1.8954979
Mean453136.29
Median Absolute Deviation (MAD)789.52868
Skewness0.0107631
Sum1.8406396 × 109
Variance1234120.4
MonotonicityNot monotonic
2024-05-11T01:39:22.681283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453187.395154017 194
 
4.5%
453058.665828669 73
 
1.7%
454934.047367752 58
 
1.3%
452469.300221465 49
 
1.1%
452184.2101607 41
 
1.0%
452706.897879436 23
 
0.5%
451940.119059947 20
 
0.5%
452918.836458244 19
 
0.4%
452472.990548179 18
 
0.4%
453314.135663101 16
 
0.4%
Other values (2102) 3551
82.4%
(Missing) 245
 
5.7%
ValueCountFrequency (%)
441737.128038275 1
 
< 0.1%
450994.913744005 1
 
< 0.1%
451011.194201757 2
< 0.1%
451019.703974623 1
 
< 0.1%
451025.902075739 4
0.1%
451031.569748553 1
 
< 0.1%
451042.369315593 1
 
< 0.1%
451049.960154453 1
 
< 0.1%
451053.76563095 2
< 0.1%
451055.899298778 1
 
< 0.1%
ValueCountFrequency (%)
455917.552544887 1
 
< 0.1%
455899.982370316 6
0.1%
455797.417581881 1
 
< 0.1%
455790.631069022 2
 
< 0.1%
455771.62005247 1
 
< 0.1%
455735.644473957 1
 
< 0.1%
455722.995595154 1
 
< 0.1%
455714.48034047 3
0.1%
455710.688794955 1
 
< 0.1%
455707.422465374 1
 
< 0.1%

위생업태명
Categorical

Distinct17
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
889 
다방
877 
커피숍
669 
기타 휴게음식점
518 
일반조리판매
482 
Other values (12)
872 

Length

Max length8
Median length6
Mean length4.0596703
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 889
20.6%
다방 877
20.4%
커피숍 669
15.5%
기타 휴게음식점 518
12.0%
일반조리판매 482
11.2%
과자점 309
 
7.2%
편의점 267
 
6.2%
패스트푸드 237
 
5.5%
백화점 25
 
0.6%
전통찻집 8
 
0.2%
Other values (7) 26
 
0.6%

Length

2024-05-11T01:39:23.183939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 889
18.4%
다방 877
18.2%
커피숍 669
13.9%
기타 518
10.7%
휴게음식점 518
10.7%
일반조리판매 482
10.0%
과자점 309
 
6.4%
편의점 267
 
5.5%
패스트푸드 237
 
4.9%
백화점 25
 
0.5%
Other values (8) 34
 
0.7%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.4%
Missing2725
Missing (%)63.3%
Infinite0
Infinite (%)0.0%
Mean0.13084703
Minimum0
Maximum7
Zeros1418
Zeros (%)32.9%
Negative0
Negative (%)0.0%
Memory size38.0 KiB
2024-05-11T01:39:23.667912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.45819177
Coefficient of variation (CV)3.5017361
Kurtosis58.743308
Mean0.13084703
Median Absolute Deviation (MAD)0
Skewness6.0120878
Sum207
Variance0.2099397
MonotonicityNot monotonic
2024-05-11T01:39:24.069974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1418
32.9%
1 137
 
3.2%
2 19
 
0.4%
3 5
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
4 1
 
< 0.1%
(Missing) 2725
63.3%
ValueCountFrequency (%)
0 1418
32.9%
1 137
 
3.2%
2 19
 
0.4%
3 5
 
0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
3 5
 
0.1%
2 19
 
0.4%
1 137
 
3.2%
0 1418
32.9%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.4%
Missing2724
Missing (%)63.2%
Infinite0
Infinite (%)0.0%
Mean0.95514845
Minimum0
Maximum8
Zeros921
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size38.0 KiB
2024-05-11T01:39:24.665532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3044259
Coefficient of variation (CV)1.3656787
Kurtosis0.86512267
Mean0.95514845
Median Absolute Deviation (MAD)0
Skewness1.1626826
Sum1512
Variance1.7015269
MonotonicityNot monotonic
2024-05-11T01:39:25.226402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 921
 
21.4%
3 237
 
5.5%
2 203
 
4.7%
1 170
 
3.9%
4 44
 
1.0%
5 5
 
0.1%
8 3
 
0.1%
(Missing) 2724
63.2%
ValueCountFrequency (%)
0 921
21.4%
1 170
 
3.9%
2 203
 
4.7%
3 237
 
5.5%
4 44
 
1.0%
5 5
 
0.1%
8 3
 
0.1%
ValueCountFrequency (%)
8 3
 
0.1%
5 5
 
0.1%
4 44
 
1.0%
3 237
 
5.5%
2 203
 
4.7%
1 170
 
3.9%
0 921
21.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
3052 
기타
626 
주택가주변
428 
유흥업소밀집지역
 
105
아파트지역
 
33
Other values (3)
 
63

Length

Max length8
Median length4
Mean length3.9679591
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3052
70.9%
기타 626
 
14.5%
주택가주변 428
 
9.9%
유흥업소밀집지역 105
 
2.4%
아파트지역 33
 
0.8%
학교정화(상대) 30
 
0.7%
결혼예식장주변 19
 
0.4%
학교정화(절대) 14
 
0.3%

Length

2024-05-11T01:39:25.829749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:26.525454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3052
70.9%
기타 626
 
14.5%
주택가주변 428
 
9.9%
유흥업소밀집지역 105
 
2.4%
아파트지역 33
 
0.8%
학교정화(상대 30
 
0.7%
결혼예식장주변 19
 
0.4%
학교정화(절대 14
 
0.3%

등급구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
3063 
기타
663 
지도
458 
자율
 
55
 
42
Other values (2)
 
26

Length

Max length4
Median length4
Mean length3.4070118
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3063
71.1%
기타 663
 
15.4%
지도 458
 
10.6%
자율 55
 
1.3%
42
 
1.0%
24
 
0.6%
우수 2
 
< 0.1%

Length

2024-05-11T01:39:27.096096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:27.828978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3063
71.1%
기타 663
 
15.4%
지도 458
 
10.6%
자율 55
 
1.3%
42
 
1.0%
24
 
0.6%
우수 2
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
2837 
상수도전용
1468 
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length4
Mean length4.3468772
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2837
65.9%
상수도전용 1468
34.1%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

Length

2024-05-11T01:39:28.253001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:28.604043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2837
65.9%
상수도전용 1468
34.1%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
4124 
0
 
183

Length

Max length4
Median length4
Mean length3.8725331
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> 4124
95.8%
0 183
 
4.2%

Length

2024-05-11T01:39:29.058572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:29.402456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4124
95.8%
0 183
 
4.2%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
4120 
0
 
187

Length

Max length4
Median length4
Mean length3.8697469
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> 4120
95.7%
0 187
 
4.3%

Length

2024-05-11T01:39:29.735865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:30.132328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4120
95.7%
0 187
 
4.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
4120 
0
 
187

Length

Max length4
Median length4
Mean length3.8697469
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> 4120
95.7%
0 187
 
4.3%

Length

2024-05-11T01:39:30.474205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:30.798312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4120
95.7%
0 187
 
4.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
4120 
0
 
187

Length

Max length4
Median length4
Mean length3.8697469
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> 4120
95.7%
0 187
 
4.3%

Length

2024-05-11T01:39:31.187197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:31.542271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4120
95.7%
0 187
 
4.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
4120 
0
 
187

Length

Max length4
Median length4
Mean length3.8697469
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> 4120
95.7%
0 187
 
4.3%

Length

2024-05-11T01:39:31.928184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:32.309410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4120
95.7%
0 187
 
4.3%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4307
Missing (%)100.0%
Memory size38.0 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
4120 
0
 
187

Length

Max length4
Median length4
Mean length3.8697469
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> 4120
95.7%
0 187
 
4.3%

Length

2024-05-11T01:39:32.661257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:33.075789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4120
95.7%
0 187
 
4.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
<NA>
4120 
0
 
187

Length

Max length4
Median length4
Mean length3.8697469
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> 4120
95.7%
0 187
 
4.3%

Length

2024-05-11T01:39:33.551605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:39:33.913284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4120
95.7%
0 187
 
4.3%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing889
Missing (%)20.6%
Memory size8.5 KiB
False
3383 
True
 
35
(Missing)
889 
ValueCountFrequency (%)
False 3383
78.5%
True 35
 
0.8%
(Missing) 889
 
20.6%
2024-05-11T01:39:34.207648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct1859
Distinct (%)54.4%
Missing889
Missing (%)20.6%
Infinite0
Infinite (%)0.0%
Mean49.410462
Minimum0
Maximum1014
Zeros9
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size38.0 KiB
2024-05-11T01:39:34.663612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q116.385
median33
Q370.0425
95-th percentile139.881
Maximum1014
Range1014
Interquartile range (IQR)53.6575

Descriptive statistics

Standard deviation51.332485
Coefficient of variation (CV)1.0388991
Kurtosis42.028536
Mean49.410462
Median Absolute Deviation (MAD)23
Skewness3.81482
Sum168884.96
Variance2635.0241
MonotonicityNot monotonic
2024-05-11T01:39:35.192824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 157
 
3.6%
6.6 90
 
2.1%
33.0 60
 
1.4%
10.0 46
 
1.1%
16.5 39
 
0.9%
26.4 38
 
0.9%
30.0 35
 
0.8%
9.9 32
 
0.7%
20.0 30
 
0.7%
13.2 29
 
0.7%
Other values (1849) 2862
66.4%
(Missing) 889
 
20.6%
ValueCountFrequency (%)
0.0 9
0.2%
1.0 14
0.3%
1.2 1
 
< 0.1%
1.3 1
 
< 0.1%
1.5 2
 
< 0.1%
1.8 1
 
< 0.1%
2.0 17
0.4%
2.5 1
 
< 0.1%
2.56 1
 
< 0.1%
3.0 16
0.4%
ValueCountFrequency (%)
1014.0 1
< 0.1%
422.3 1
< 0.1%
389.68 1
< 0.1%
371.25 1
< 0.1%
353.3 1
< 0.1%
337.36 1
< 0.1%
337.08 1
< 0.1%
330.48 1
< 0.1%
330.0 1
< 0.1%
328.01 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4307
Missing (%)100.0%
Memory size38.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4307
Missing (%)100.0%
Memory size38.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4307
Missing (%)100.0%
Memory size38.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030500003050000-104-1965-0977419651120<NA>3폐업2폐업20150603<NA><NA><NA>020212305878.06130857서울특별시 동대문구 전농동 496-1번지<NA><NA>파리2015-06-03 09:50:15I2018-08-31 23:59:59.0다방<NA><NA>다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N78.06<NA><NA><NA>
130500003050000-104-1967-0924619671218<NA>3폐업2폐업20170116<NA><NA><NA>020968360274.76130080서울특별시 동대문구 이문동 258-17번지서울특별시 동대문구 이문로 144 (이문동)2414양지2017-01-13 17:02:56I2018-08-31 23:59:59.0다방205412.139993455222.365426다방02기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N74.76<NA><NA><NA>
230500003050000-104-1968-0924419680120<NA>3폐업2폐업20150727<NA><NA><NA>02 9238282193.55130812서울특별시 동대문구 신설동 101-7번지서울특별시 동대문구 왕산로 4 (신설동)2582동화다방1999-04-20 00:00:00I2018-08-31 23:59:59.0다방202056.089579452590.463014다방00결혼예식장주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N193.55<NA><NA><NA>
330500003050000-104-1968-0925319680725<NA>3폐업2폐업20051229<NA><NA><NA>020212765982.21130859서울특별시 동대문구 전농동 655-30번지<NA><NA>새마을1999-02-10 00:00:00I2018-08-31 23:59:59.0다방204444.480432452433.549643다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N82.21<NA><NA><NA>
430500003050000-104-1968-0929319680202<NA>3폐업2폐업20051017<NA><NA><NA>0209230870129.67130820서울특별시 동대문구 용두동 119-15번지<NA><NA>동아2001-09-29 00:00:00I2018-08-31 23:59:59.0다방202650.242826452714.465799다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N129.67<NA><NA><NA>
530500003050000-104-1968-0933919681228<NA>3폐업2폐업20190502<NA><NA><NA>020966689392.50130816서울특별시 동대문구 용두동 9-7번지 (답십리길 4)서울특별시 동대문구 답십리로 4 (용두동,(답십리길 4))2560화성2019-05-02 14:48:15U2019-05-04 02:40:00.0다방203701.438857452950.25665다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N92.5<NA><NA><NA>
630500003050000-104-1968-0962819681118<NA>3폐업2폐업20060605<NA><NA><NA>0202344543116.90130811서울특별시 동대문구 신설동 93-16번지<NA><NA>신호다방1999-12-18 00:00:00I2018-08-31 23:59:59.0다방202324.201887452370.69524다방00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N116.9<NA><NA><NA>
730500003050000-104-1969-0918219690210<NA>3폐업2폐업20100708<NA><NA><NA>0209668329131.20130870서울특별시 동대문구 청량리동 761-0번지 (왕산로 323)<NA><NA>제일2008-07-01 09:58:50I2018-08-31 23:59:59.0다방203803.484635453084.117645다방03유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N131.2<NA><NA><NA>
830500003050000-104-1969-0920419690605<NA>3폐업2폐업20120910<NA><NA><NA>0209628863119.00130816서울특별시 동대문구 용두동 9-2번지 (답십리길 10)<NA><NA>백궁2008-07-01 09:59:11I2018-08-31 23:59:59.0다방203729.036123452887.352617다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N119.0<NA><NA><NA>
930500003050000-104-1969-0926319691205<NA>1영업/정상1영업<NA><NA><NA><NA>02 4597469123.66130817서울특별시 동대문구 용두동 38-1번지서울특별시 동대문구 고산자로 391 (용두동)2566대동다방2020-05-12 11:09:36U2020-05-14 02:40:00.0다방203261.116619452486.964467다방00기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y123.66<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
429730500003050000-104-2024-000702024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-867서울특별시 동대문구 청량리동 224-2서울특별시 동대문구 약령시로21길 5, 1층 (청량리동)2484씨유 청량리경찰서점2024-04-25 11:23:09I2023-12-03 22:07:00.0편의점203900.727368453480.356786<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
429830500003050000-104-2024-000712024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.90130-883서울특별시 동대문구 답십리동 68-1서울특별시 동대문구 전농로 94, 1층 (답십리동)2538수수맛집2024-04-25 11:40:46I2023-12-03 22:07:00.0기타 휴게음식점205033.87404452322.301296<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
429930500003050000-104-2024-000722024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>66.00130-876서울특별시 동대문구 휘경동 267-9서울특별시 동대문구 망우로 61, 1층 (휘경동)2439벨라루체 카페2024-04-26 13:35:22I2023-12-03 22:08:00.0커피숍205226.126828454172.055738<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430030500003050000-104-2024-000732024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA>031 26854683.30130-851서울특별시 동대문구 전농동 591-53 청량리역,롯데백화점서울특별시 동대문구 왕산로 214, 청량리역,롯데백화점 3층 (전농동)2555(주)제이와이에스유통2024-04-29 09:26:40I2023-12-05 00:01:00.0기타 휴게음식점204081.282117453187.395154<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430130500003050000-104-2024-000742024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA>02695651013.30130-851서울특별시 동대문구 전농동 591-53 청량리역,롯데백화점서울특별시 동대문구 왕산로 214, 청량리역,롯데백화점 3층 (전농동)2555오시오카페2024-04-30 11:31:32I2023-12-05 00:02:00.0기타 휴게음식점204081.282117453187.395154<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430230500003050000-104-2024-000752024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>66.00130-835서울특별시 동대문구 장안동 94-30서울특별시 동대문구 사가정로25길 41, 1층 (장안동)2516배스킨라빈스 휘경주공점2024-05-01 09:29:22I2023-12-05 00:03:00.0아이스크림206166.922571453180.448622<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430330500003050000-104-2024-000762024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00130-827서울특별시 동대문구 이문동 256-136 이문동빌딩서울특별시 동대문구 이문로46길 22, 이문동빌딩 1층 (이문동)2412봄봄커머스2024-05-02 12:02:10I2023-12-05 00:04:00.0커피숍205521.208193455478.118027<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430430500003050000-104-2024-000772024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.44130-878서울특별시 동대문구 휘경동 286-84서울특별시 동대문구 망우로18가길 75, 1층 (휘경동)2498고래김밥2024-05-03 16:31:28I2023-12-05 00:05:00.0기타 휴게음식점205264.420561453852.79009<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430530500003050000-104-2024-000782024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.30130-756서울특별시 동대문구 답십리동 80 답십리청솔우성아파트서울특별시 동대문구 전농로10길 20, 1층 109호 (답십리동, 답십리청솔우성아파트)2536조이앤비 전농점2024-05-03 16:58:55I2023-12-05 00:05:00.0기타 휴게음식점205208.16745452466.868526<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430630500003050000-104-2024-000792024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.70130-844서울특별시 동대문구 장안동 432-13서울특별시 동대문구 천호대로83길 14, 1층 (장안동)2636샌드리지2024-05-08 10:18:07U2023-12-04 23:00:00.0기타 휴게음식점205652.108255451172.586412<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>