Overview

Dataset statistics

Number of variables44
Number of observations3475
Missing cells37171
Missing cells (%)24.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory375.0 B

Variable types

Categorical19
Text8
DateTime4
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-18696/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
전통업소지정번호 has constant value ""Constant
남성종사자수 is highly imbalanced (50.4%)Imbalance
영업장주변구분명 is highly imbalanced (54.0%)Imbalance
등급구분명 is highly imbalanced (59.2%)Imbalance
총인원 is highly imbalanced (70.6%)Imbalance
본사종업원수 is highly imbalanced (70.4%)Imbalance
공장사무직종업원수 is highly imbalanced (70.4%)Imbalance
공장판매직종업원수 is highly imbalanced (70.4%)Imbalance
공장생산직종업원수 is highly imbalanced (70.4%)Imbalance
보증액 is highly imbalanced (70.4%)Imbalance
월세액 is highly imbalanced (70.4%)Imbalance
다중이용업소여부 is highly imbalanced (89.7%)Imbalance
인허가취소일자 has 3475 (100.0%) missing valuesMissing
폐업일자 has 1061 (30.5%) missing valuesMissing
휴업시작일자 has 3475 (100.0%) missing valuesMissing
휴업종료일자 has 3475 (100.0%) missing valuesMissing
재개업일자 has 3475 (100.0%) missing valuesMissing
전화번호 has 1816 (52.3%) missing valuesMissing
소재지면적 has 59 (1.7%) missing valuesMissing
도로명주소 has 1118 (32.2%) missing valuesMissing
도로명우편번호 has 1141 (32.8%) missing valuesMissing
좌표정보(X) has 185 (5.3%) missing valuesMissing
좌표정보(Y) has 185 (5.3%) missing valuesMissing
여성종사자수 has 2313 (66.6%) missing valuesMissing
건물소유구분명 has 3475 (100.0%) missing valuesMissing
다중이용업소여부 has 716 (20.6%) missing valuesMissing
시설총규모 has 716 (20.6%) missing valuesMissing
전통업소지정번호 has 3474 (> 99.9%) missing valuesMissing
전통업소주된음식 has 3475 (100.0%) missing valuesMissing
홈페이지 has 3475 (100.0%) missing valuesMissing
여성종사자수 is highly skewed (γ1 = 27.22242143)Skewed
시설총규모 is highly skewed (γ1 = 52.47620803)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
여성종사자수 has 665 (19.1%) zerosZeros
시설총규모 has 60 (1.7%) zerosZeros

Reproduction

Analysis started2024-05-11 08:03:42.954628
Analysis finished2024-05-11 08:03:46.514499
Duration3.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
3190000
3475 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 3475
100.0%

Length

2024-05-11T08:03:46.895008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:47.457576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 3475
100.0%

관리번호
Text

UNIQUE 

Distinct3475
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2024-05-11T08:03:48.077396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters76450
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

Unique3475 ?
Unique (%)100.0%

Sample

1st row3190000-104-1969-01192
2nd row3190000-104-1970-01074
3rd row3190000-104-1970-01116
4th row3190000-104-1970-01156
5th row3190000-104-1970-01183
ValueCountFrequency (%)
3190000-104-1969-01192 1
 
< 0.1%
3190000-104-2017-00006 1
 
< 0.1%
3190000-104-2017-00019 1
 
< 0.1%
3190000-104-2016-00217 1
 
< 0.1%
3190000-104-2016-00218 1
 
< 0.1%
3190000-104-2016-00219 1
 
< 0.1%
3190000-104-2016-00220 1
 
< 0.1%
3190000-104-2016-00221 1
 
< 0.1%
3190000-104-2017-00001 1
 
< 0.1%
3190000-104-2017-00002 1
 
< 0.1%
Other values (3465) 3465
99.7%
2024-05-11T08:03:49.538231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 30057
39.3%
1 11740
 
15.4%
- 10425
 
13.6%
9 5841
 
7.6%
3 4789
 
6.3%
4 4681
 
6.1%
2 4628
 
6.1%
8 1158
 
1.5%
7 1073
 
1.4%
5 1033
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66025
86.4%
Dash Punctuation 10425
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30057
45.5%
1 11740
 
17.8%
9 5841
 
8.8%
3 4789
 
7.3%
4 4681
 
7.1%
2 4628
 
7.0%
8 1158
 
1.8%
7 1073
 
1.6%
5 1033
 
1.6%
6 1025
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 10425
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76450
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 30057
39.3%
1 11740
 
15.4%
- 10425
 
13.6%
9 5841
 
7.6%
3 4789
 
6.3%
4 4681
 
6.1%
2 4628
 
6.1%
8 1158
 
1.5%
7 1073
 
1.4%
5 1033
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 30057
39.3%
1 11740
 
15.4%
- 10425
 
13.6%
9 5841
 
7.6%
3 4789
 
6.3%
4 4681
 
6.1%
2 4628
 
6.1%
8 1158
 
1.5%
7 1073
 
1.4%
5 1033
 
1.4%
Distinct2668
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
Minimum1969-03-19 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T08:03:50.405449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:03:51.309449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3475
Missing (%)100.0%
Memory size30.7 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
3
2414 
1
1061 

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 2414
69.5%
1 1061
30.5%

Length

2024-05-11T08:03:51.883224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:52.330215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2414
69.5%
1 1061
30.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
폐업
2414 
영업/정상
1061 

Length

Max length5
Median length2
Mean length2.9159712
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2414
69.5%
영업/정상 1061
30.5%

Length

2024-05-11T08:03:52.915656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:53.424542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2414
69.5%
영업/정상 1061
30.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2
2414 
1
1061 

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 2414
69.5%
1 1061
30.5%

Length

2024-05-11T08:03:53.845722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:54.301528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2414
69.5%
1 1061
30.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
폐업
2414 
영업
1061 

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 2414
69.5%
영업 1061
30.5%

Length

2024-05-11T08:03:54.909235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:55.294076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2414
69.5%
영업 1061
30.5%

폐업일자
Date

MISSING 

Distinct1854
Distinct (%)76.8%
Missing1061
Missing (%)30.5%
Memory size27.3 KiB
Minimum1989-03-08 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T08:03:55.764423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:03:56.304794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3475
Missing (%)100.0%
Memory size30.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3475
Missing (%)100.0%
Memory size30.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3475
Missing (%)100.0%
Memory size30.7 KiB

전화번호
Text

MISSING 

Distinct1550
Distinct (%)93.4%
Missing1816
Missing (%)52.3%
Memory size27.3 KiB
2024-05-11T08:03:57.136040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.173599
Min length2

Characters and Unicode

Total characters16878
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

Unique1489 ?
Unique (%)89.8%

Sample

1st row02 8159356
2nd row02 8141228
3rd row02 8158409
4th row02 8155225
5th row02 8156824
ValueCountFrequency (%)
02 1171
37.4%
070 36
 
1.1%
825 14
 
0.4%
812 13
 
0.4%
532 11
 
0.4%
822 11
 
0.4%
826 11
 
0.4%
823 10
 
0.3%
813 9
 
0.3%
02812 9
 
0.3%
Other values (1633) 1836
58.6%
2024-05-11T08:03:58.409989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3046
18.0%
0 2844
16.9%
8 1908
11.3%
1776
10.5%
5 1323
7.8%
1 1264
7.5%
3 1135
 
6.7%
7 997
 
5.9%
4 962
 
5.7%
9 820
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15102
89.5%
Space Separator 1776
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3046
20.2%
0 2844
18.8%
8 1908
12.6%
5 1323
8.8%
1 1264
8.4%
3 1135
 
7.5%
7 997
 
6.6%
4 962
 
6.4%
9 820
 
5.4%
6 803
 
5.3%
Space Separator
ValueCountFrequency (%)
1776
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16878
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3046
18.0%
0 2844
16.9%
8 1908
11.3%
1776
10.5%
5 1323
7.8%
1 1264
7.5%
3 1135
 
6.7%
7 997
 
5.9%
4 962
 
5.7%
9 820
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16878
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3046
18.0%
0 2844
16.9%
8 1908
11.3%
1776
10.5%
5 1323
7.8%
1 1264
7.5%
3 1135
 
6.7%
7 997
 
5.9%
4 962
 
5.7%
9 820
 
4.9%

소재지면적
Text

MISSING 

Distinct1876
Distinct (%)54.9%
Missing59
Missing (%)1.7%
Memory size27.3 KiB
2024-05-11T08:03:59.405363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.8773419
Min length3

Characters and Unicode

Total characters16661
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

Unique1459 ?
Unique (%)42.7%

Sample

1st row51.67
2nd row117.15
3rd row92.64
4th row61.28
5th row65.96
ValueCountFrequency (%)
3.30 191
 
5.6%
6.60 124
 
3.6%
33.00 42
 
1.2%
10.00 38
 
1.1%
9.90 35
 
1.0%
3.00 33
 
1.0%
20.00 32
 
0.9%
23.00 31
 
0.9%
16.50 30
 
0.9%
13.20 28
 
0.8%
Other values (1866) 2832
82.9%
2024-05-11T08:04:00.804266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3416
20.5%
0 3058
18.4%
3 1587
9.5%
2 1498
9.0%
1 1478
8.9%
6 1268
 
7.6%
5 1003
 
6.0%
4 993
 
6.0%
9 813
 
4.9%
8 809
 
4.9%
Other values (2) 738
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13244
79.5%
Other Punctuation 3417
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3058
23.1%
3 1587
12.0%
2 1498
11.3%
1 1478
11.2%
6 1268
9.6%
5 1003
 
7.6%
4 993
 
7.5%
9 813
 
6.1%
8 809
 
6.1%
7 737
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 3416
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 16661
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3416
20.5%
0 3058
18.4%
3 1587
9.5%
2 1498
9.0%
1 1478
8.9%
6 1268
 
7.6%
5 1003
 
6.0%
4 993
 
6.0%
9 813
 
4.9%
8 809
 
4.9%
Other values (2) 738
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16661
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3416
20.5%
0 3058
18.4%
3 1587
9.5%
2 1498
9.0%
1 1478
8.9%
6 1268
 
7.6%
5 1003
 
6.0%
4 993
 
6.0%
9 813
 
4.9%
8 809
 
4.9%
Other values (2) 738
 
4.4%
Distinct170
Distinct (%)4.9%
Missing31
Missing (%)0.9%
Memory size27.3 KiB
2024-05-11T08:04:01.567960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1355981
Min length6

Characters and Unicode

Total characters21131
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 (%)0.8%

Sample

1st row156030
2nd row156839
3rd row156813
4th row156803
5th row156806
ValueCountFrequency (%)
156030 245
 
7.1%
156800 211
 
6.1%
156816 181
 
5.3%
156801 150
 
4.4%
156861 105
 
3.0%
156811 80
 
2.3%
156826 79
 
2.3%
156824 78
 
2.3%
156815 78
 
2.3%
156821 70
 
2.0%
Other values (160) 2167
62.9%
2024-05-11T08:04:03.065788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4683
22.2%
6 4036
19.1%
5 3918
18.5%
8 3126
14.8%
0 2079
9.8%
3 896
 
4.2%
2 609
 
2.9%
4 552
 
2.6%
- 467
 
2.2%
7 458
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20664
97.8%
Dash Punctuation 467
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4683
22.7%
6 4036
19.5%
5 3918
19.0%
8 3126
15.1%
0 2079
10.1%
3 896
 
4.3%
2 609
 
2.9%
4 552
 
2.7%
7 458
 
2.2%
9 307
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 467
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21131
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4683
22.2%
6 4036
19.1%
5 3918
18.5%
8 3126
14.8%
0 2079
9.8%
3 896
 
4.2%
2 609
 
2.9%
4 552
 
2.6%
- 467
 
2.2%
7 458
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21131
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4683
22.2%
6 4036
19.1%
5 3918
18.5%
8 3126
14.8%
0 2079
9.8%
3 896
 
4.2%
2 609
 
2.9%
4 552
 
2.6%
- 467
 
2.2%
7 458
 
2.2%
Distinct2796
Distinct (%)81.2%
Missing31
Missing (%)0.9%
Memory size27.3 KiB
2024-05-11T08:04:03.782307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length44
Mean length24.004355
Min length13

Characters and Unicode

Total characters82671
Distinct characters343
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

Unique2351 ?
Unique (%)68.3%

Sample

1st row서울특별시 동작구 상도동 701-3번지
2nd row서울특별시 동작구 상도동 187-1번지
3rd row서울특별시 동작구 본동 399-3번지
4th row서울특별시 동작구 노량진동 240-27번지
5th row서울특별시 동작구 노량진동 307-159번지
ValueCountFrequency (%)
서울특별시 3446
22.4%
동작구 3444
22.4%
사당동 969
 
6.3%
상도동 698
 
4.5%
노량진동 587
 
3.8%
신대방동 410
 
2.7%
흑석동 306
 
2.0%
1층 272
 
1.8%
대방동 249
 
1.6%
상도1동 137
 
0.9%
Other values (2842) 4839
31.5%
2024-05-11T08:04:05.211498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14599
17.7%
7062
 
8.5%
1 3932
 
4.8%
3495
 
4.2%
3484
 
4.2%
3466
 
4.2%
3462
 
4.2%
3454
 
4.2%
3451
 
4.2%
3451
 
4.2%
Other values (333) 32815
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48253
58.4%
Decimal Number 16340
 
19.8%
Space Separator 14599
 
17.7%
Dash Punctuation 3081
 
3.7%
Close Punctuation 129
 
0.2%
Open Punctuation 129
 
0.2%
Uppercase Letter 60
 
0.1%
Other Punctuation 58
 
0.1%
Lowercase Letter 20
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7062
14.6%
3495
 
7.2%
3484
 
7.2%
3466
 
7.2%
3462
 
7.2%
3454
 
7.2%
3451
 
7.2%
3451
 
7.2%
2251
 
4.7%
2084
 
4.3%
Other values (286) 12593
26.1%
Lowercase Letter
ValueCountFrequency (%)
e 4
20.0%
t 2
10.0%
y 2
10.0%
a 2
10.0%
s 1
 
5.0%
w 1
 
5.0%
h 1
 
5.0%
u 1
 
5.0%
b 1
 
5.0%
k 1
 
5.0%
Other values (4) 4
20.0%
Uppercase Letter
ValueCountFrequency (%)
B 20
33.3%
A 12
20.0%
D 6
 
10.0%
R 5
 
8.3%
T 5
 
8.3%
P 3
 
5.0%
J 2
 
3.3%
H 2
 
3.3%
C 2
 
3.3%
I 1
 
1.7%
Other values (2) 2
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 3932
24.1%
2 2089
12.8%
3 1922
11.8%
0 1445
 
8.8%
4 1424
 
8.7%
5 1311
 
8.0%
6 1227
 
7.5%
9 1033
 
6.3%
7 1024
 
6.3%
8 933
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 49
84.5%
& 4
 
6.9%
? 2
 
3.4%
. 1
 
1.7%
/ 1
 
1.7%
@ 1
 
1.7%
Space Separator
ValueCountFrequency (%)
14599
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3081
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48253
58.4%
Common 34338
41.5%
Latin 80
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7062
14.6%
3495
 
7.2%
3484
 
7.2%
3466
 
7.2%
3462
 
7.2%
3454
 
7.2%
3451
 
7.2%
3451
 
7.2%
2251
 
4.7%
2084
 
4.3%
Other values (286) 12593
26.1%
Latin
ValueCountFrequency (%)
B 20
25.0%
A 12
15.0%
D 6
 
7.5%
R 5
 
6.2%
T 5
 
6.2%
e 4
 
5.0%
P 3
 
3.8%
J 2
 
2.5%
H 2
 
2.5%
t 2
 
2.5%
Other values (16) 19
23.8%
Common
ValueCountFrequency (%)
14599
42.5%
1 3932
 
11.5%
- 3081
 
9.0%
2 2089
 
6.1%
3 1922
 
5.6%
0 1445
 
4.2%
4 1424
 
4.1%
5 1311
 
3.8%
6 1227
 
3.6%
9 1033
 
3.0%
Other values (11) 2275
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48253
58.4%
ASCII 34418
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14599
42.4%
1 3932
 
11.4%
- 3081
 
9.0%
2 2089
 
6.1%
3 1922
 
5.6%
0 1445
 
4.2%
4 1424
 
4.1%
5 1311
 
3.8%
6 1227
 
3.6%
9 1033
 
3.0%
Other values (37) 2355
 
6.8%
Hangul
ValueCountFrequency (%)
7062
14.6%
3495
 
7.2%
3484
 
7.2%
3466
 
7.2%
3462
 
7.2%
3454
 
7.2%
3451
 
7.2%
3451
 
7.2%
2251
 
4.7%
2084
 
4.3%
Other values (286) 12593
26.1%

도로명주소
Text

MISSING 

Distinct2173
Distinct (%)92.2%
Missing1118
Missing (%)32.2%
Memory size27.3 KiB
2024-05-11T08:04:06.088208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length57
Mean length32.336445
Min length21

Characters and Unicode

Total characters76217
Distinct characters350
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

Unique2013 ?
Unique (%)85.4%

Sample

1st row서울특별시 동작구 흑석로 109-2 (흑석동)
2nd row서울특별시 동작구 장승배기로 71 (상도동)
3rd row서울특별시 동작구 장승배기로 139 (노량진동)
4th row서울특별시 동작구 흑석로 101-7 (흑석동)
5th row서울특별시 동작구 상도로 372 (상도동,외2필지)
ValueCountFrequency (%)
서울특별시 2357
 
15.7%
동작구 2357
 
15.7%
1층 1081
 
7.2%
사당동 613
 
4.1%
상도동 452
 
3.0%
노량진동 340
 
2.3%
신대방동 269
 
1.8%
지하1층 183
 
1.2%
상도로 183
 
1.2%
흑석동 183
 
1.2%
Other values (1495) 7005
46.6%
2024-05-11T08:04:07.566512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12675
 
16.6%
5305
 
7.0%
1 4081
 
5.4%
2742
 
3.6%
) 2455
 
3.2%
( 2455
 
3.2%
2432
 
3.2%
, 2424
 
3.2%
2415
 
3.2%
2371
 
3.1%
Other values (340) 36862
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44375
58.2%
Space Separator 12675
 
16.6%
Decimal Number 11443
 
15.0%
Close Punctuation 2455
 
3.2%
Open Punctuation 2455
 
3.2%
Other Punctuation 2432
 
3.2%
Dash Punctuation 239
 
0.3%
Uppercase Letter 126
 
0.2%
Lowercase Letter 13
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5305
 
12.0%
2742
 
6.2%
2432
 
5.5%
2415
 
5.4%
2371
 
5.3%
2367
 
5.3%
2364
 
5.3%
2364
 
5.3%
2216
 
5.0%
1868
 
4.2%
Other values (296) 17931
40.4%
Uppercase Letter
ValueCountFrequency (%)
B 84
66.7%
A 11
 
8.7%
D 7
 
5.6%
C 6
 
4.8%
T 4
 
3.2%
R 3
 
2.4%
X 2
 
1.6%
P 2
 
1.6%
Y 2
 
1.6%
I 1
 
0.8%
Other values (4) 4
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 4081
35.7%
2 1725
15.1%
3 1033
 
9.0%
0 995
 
8.7%
4 752
 
6.6%
6 672
 
5.9%
5 632
 
5.5%
7 543
 
4.7%
8 533
 
4.7%
9 477
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
38.5%
o 1
 
7.7%
t 1
 
7.7%
s 1
 
7.7%
k 1
 
7.7%
a 1
 
7.7%
j 1
 
7.7%
g 1
 
7.7%
n 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 2424
99.7%
. 3
 
0.1%
& 2
 
0.1%
/ 1
 
< 0.1%
? 1
 
< 0.1%
@ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12675
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2455
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2455
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 239
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44375
58.2%
Common 31703
41.6%
Latin 139
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5305
 
12.0%
2742
 
6.2%
2432
 
5.5%
2415
 
5.4%
2371
 
5.3%
2367
 
5.3%
2364
 
5.3%
2364
 
5.3%
2216
 
5.0%
1868
 
4.2%
Other values (296) 17931
40.4%
Latin
ValueCountFrequency (%)
B 84
60.4%
A 11
 
7.9%
D 7
 
5.0%
C 6
 
4.3%
e 5
 
3.6%
T 4
 
2.9%
R 3
 
2.2%
X 2
 
1.4%
P 2
 
1.4%
Y 2
 
1.4%
Other values (13) 13
 
9.4%
Common
ValueCountFrequency (%)
12675
40.0%
1 4081
 
12.9%
) 2455
 
7.7%
( 2455
 
7.7%
, 2424
 
7.6%
2 1725
 
5.4%
3 1033
 
3.3%
0 995
 
3.1%
4 752
 
2.4%
6 672
 
2.1%
Other values (11) 2436
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44375
58.2%
ASCII 31842
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12675
39.8%
1 4081
 
12.8%
) 2455
 
7.7%
( 2455
 
7.7%
, 2424
 
7.6%
2 1725
 
5.4%
3 1033
 
3.2%
0 995
 
3.1%
4 752
 
2.4%
6 672
 
2.1%
Other values (34) 2575
 
8.1%
Hangul
ValueCountFrequency (%)
5305
 
12.0%
2742
 
6.2%
2432
 
5.5%
2415
 
5.4%
2371
 
5.3%
2367
 
5.3%
2364
 
5.3%
2364
 
5.3%
2216
 
5.0%
1868
 
4.2%
Other values (296) 17931
40.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct167
Distinct (%)7.2%
Missing1141
Missing (%)32.8%
Infinite0
Infinite (%)0.0%
Mean6987.2159
Minimum6586
Maximum7075
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2024-05-11T08:04:08.155164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6586
5-th percentile6910
Q16938
median6997
Q37027
95-th percentile7069
Maximum7075
Range489
Interquartile range (IQR)89

Descriptive statistics

Standard deviation51.838911
Coefficient of variation (CV)0.0074191082
Kurtosis0.23615722
Mean6987.2159
Median Absolute Deviation (MAD)43
Skewness-0.26067541
Sum16308162
Variance2687.2727
MonotonicityNot monotonic
2024-05-11T08:04:08.594364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7008 129
 
3.7%
6922 75
 
2.2%
7071 67
 
1.9%
6913 66
 
1.9%
7013 56
 
1.6%
7025 55
 
1.6%
7027 52
 
1.5%
7015 51
 
1.5%
7010 44
 
1.3%
6910 44
 
1.3%
Other values (157) 1695
48.8%
(Missing) 1141
32.8%
ValueCountFrequency (%)
6586 1
 
< 0.1%
6900 19
0.5%
6901 2
 
0.1%
6902 22
0.6%
6904 11
0.3%
6905 4
 
0.1%
6906 6
 
0.2%
6907 6
 
0.2%
6908 10
0.3%
6909 6
 
0.2%
ValueCountFrequency (%)
7075 1
 
< 0.1%
7074 4
 
0.1%
7073 2
 
0.1%
7072 16
 
0.5%
7071 67
1.9%
7070 12
 
0.3%
7069 16
 
0.5%
7068 11
 
0.3%
7067 16
 
0.5%
7065 3
 
0.1%
Distinct3253
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2024-05-11T08:04:09.482144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length7.6756835
Min length1

Characters and Unicode

Total characters26673
Distinct characters834
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

Unique3082 ?
Unique (%)88.7%

Sample

1st row로타리다방
2nd row지성다방
3rd row커피하우스
4th row아씨
5th row
ValueCountFrequency (%)
씨유 66
 
1.4%
세븐일레븐 63
 
1.3%
카페 42
 
0.9%
노량진점 40
 
0.8%
coffee 32
 
0.7%
중앙대점 29
 
0.6%
사당점 28
 
0.6%
이수역점 26
 
0.5%
cafe 25
 
0.5%
상도점 23
 
0.5%
Other values (3493) 4405
92.2%
2024-05-11T08:04:11.106767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1306
 
4.9%
1112
 
4.2%
742
 
2.8%
632
 
2.4%
568
 
2.1%
( 465
 
1.7%
) 464
 
1.7%
457
 
1.7%
438
 
1.6%
364
 
1.4%
Other values (824) 20125
75.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20814
78.0%
Uppercase Letter 1530
 
5.7%
Lowercase Letter 1360
 
5.1%
Space Separator 1306
 
4.9%
Decimal Number 635
 
2.4%
Open Punctuation 465
 
1.7%
Close Punctuation 464
 
1.7%
Other Punctuation 75
 
0.3%
Dash Punctuation 15
 
0.1%
Modifier Symbol 5
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1112
 
5.3%
742
 
3.6%
632
 
3.0%
568
 
2.7%
457
 
2.2%
438
 
2.1%
364
 
1.7%
323
 
1.6%
309
 
1.5%
306
 
1.5%
Other values (748) 15563
74.8%
Lowercase Letter
ValueCountFrequency (%)
e 232
17.1%
o 146
10.7%
a 133
 
9.8%
f 113
 
8.3%
r 73
 
5.4%
c 72
 
5.3%
i 67
 
4.9%
n 65
 
4.8%
s 64
 
4.7%
t 62
 
4.6%
Other values (15) 333
24.5%
Uppercase Letter
ValueCountFrequency (%)
C 202
13.2%
S 180
11.8%
G 141
 
9.2%
E 123
 
8.0%
P 109
 
7.1%
O 91
 
5.9%
F 76
 
5.0%
T 71
 
4.6%
A 69
 
4.5%
R 54
 
3.5%
Other values (15) 414
27.1%
Decimal Number
ValueCountFrequency (%)
2 209
32.9%
5 178
28.0%
1 54
 
8.5%
3 48
 
7.6%
0 38
 
6.0%
4 38
 
6.0%
9 33
 
5.2%
6 15
 
2.4%
7 13
 
2.0%
8 9
 
1.4%
Other Punctuation
ValueCountFrequency (%)
& 26
34.7%
. 20
26.7%
' 11
14.7%
, 11
14.7%
/ 3
 
4.0%
? 2
 
2.7%
: 1
 
1.3%
# 1
 
1.3%
Space Separator
ValueCountFrequency (%)
1306
100.0%
Open Punctuation
ValueCountFrequency (%)
( 465
100.0%
Close Punctuation
ValueCountFrequency (%)
) 464
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20807
78.0%
Common 2968
 
11.1%
Latin 2891
 
10.8%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1112
 
5.3%
742
 
3.6%
632
 
3.0%
568
 
2.7%
457
 
2.2%
438
 
2.1%
364
 
1.7%
323
 
1.6%
309
 
1.5%
306
 
1.5%
Other values (742) 15556
74.8%
Latin
ValueCountFrequency (%)
e 232
 
8.0%
C 202
 
7.0%
S 180
 
6.2%
o 146
 
5.1%
G 141
 
4.9%
a 133
 
4.6%
E 123
 
4.3%
f 113
 
3.9%
P 109
 
3.8%
O 91
 
3.1%
Other values (41) 1421
49.2%
Common
ValueCountFrequency (%)
1306
44.0%
( 465
 
15.7%
) 464
 
15.6%
2 209
 
7.0%
5 178
 
6.0%
1 54
 
1.8%
3 48
 
1.6%
0 38
 
1.3%
4 38
 
1.3%
9 33
 
1.1%
Other values (15) 135
 
4.5%
Han
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20804
78.0%
ASCII 5856
 
22.0%
CJK 7
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Letterlike Symbols 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1306
22.3%
( 465
 
7.9%
) 464
 
7.9%
e 232
 
4.0%
2 209
 
3.6%
C 202
 
3.4%
S 180
 
3.1%
5 178
 
3.0%
o 146
 
2.5%
G 141
 
2.4%
Other values (64) 2333
39.8%
Hangul
ValueCountFrequency (%)
1112
 
5.3%
742
 
3.6%
632
 
3.0%
568
 
2.7%
457
 
2.2%
438
 
2.1%
364
 
1.7%
323
 
1.6%
309
 
1.5%
306
 
1.5%
Other values (739) 15553
74.8%
CJK
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Letterlike Symbols
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct2838
Distinct (%)81.7%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
Minimum1999-03-03 00:00:00
Maximum2024-05-09 16:28:23
2024-05-11T08:04:11.688088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:04:12.143746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
I
2194 
U
1281 

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 2194
63.1%
U 1281
36.9%

Length

2024-05-11T08:04:12.707531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:13.047066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2194
63.1%
u 1281
36.9%
Distinct930
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T08:04:13.397008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:04:13.808297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct15
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
커피숍
1050 
일반조리판매
626 
기타 휴게음식점
481 
다방
394 
편의점
388 
Other values (10)
536 

Length

Max length8
Median length6
Mean length4.2635971
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 1050
30.2%
일반조리판매 626
18.0%
기타 휴게음식점 481
13.8%
다방 394
 
11.3%
편의점 388
 
11.2%
과자점 263
 
7.6%
패스트푸드 199
 
5.7%
철도역구내 25
 
0.7%
아이스크림 18
 
0.5%
푸드트럭 8
 
0.2%
Other values (5) 23
 
0.7%

Length

2024-05-11T08:04:14.276291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1050
26.5%
일반조리판매 626
15.8%
기타 481
12.2%
휴게음식점 481
12.2%
다방 394
 
10.0%
편의점 388
 
9.8%
과자점 263
 
6.6%
패스트푸드 199
 
5.0%
철도역구내 25
 
0.6%
아이스크림 18
 
0.5%
Other values (6) 31
 
0.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1766
Distinct (%)53.7%
Missing185
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean195570.08
Minimum191484.23
Maximum199391.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2024-05-11T08:04:14.686771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191484.23
5-th percentile192842.81
Q1194158.66
median195212.13
Q3197456.12
95-th percentile198290.86
Maximum199391.45
Range7907.2177
Interquartile range (IQR)3297.4583

Descriptive statistics

Standard deviation1860.7171
Coefficient of variation (CV)0.0095143243
Kurtosis-1.0685567
Mean195570.08
Median Absolute Deviation (MAD)1435.4465
Skewness-0.0086068049
Sum6.4342555 × 108
Variance3462268.3
MonotonicityNot monotonic
2024-05-11T08:04:15.167528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198303.527071078 41
 
1.2%
196122.678608319 29
 
0.8%
193218.36400997 25
 
0.7%
193279.599095483 23
 
0.7%
194772.975405476 20
 
0.6%
193896.384765772 18
 
0.5%
191691.678396263 16
 
0.5%
195079.265528912 16
 
0.5%
197802.054854046 15
 
0.4%
193153.177033349 15
 
0.4%
Other values (1756) 3072
88.4%
(Missing) 185
 
5.3%
ValueCountFrequency (%)
191484.231170935 1
 
< 0.1%
191544.278295685 1
 
< 0.1%
191555.354381759 1
 
< 0.1%
191585.298671366 1
 
< 0.1%
191647.259479634 1
 
< 0.1%
191673.025374635 1
 
< 0.1%
191682.980173893 1
 
< 0.1%
191688.979039976 1
 
< 0.1%
191691.678396263 16
0.5%
191705.34451018 1
 
< 0.1%
ValueCountFrequency (%)
199391.448910937 1
 
< 0.1%
198410.178061993 1
 
< 0.1%
198371.098321744 2
0.1%
198369.365881805 2
0.1%
198366.483082717 2
0.1%
198364.235287192 3
0.1%
198362.996258131 2
0.1%
198354.350098982 1
 
< 0.1%
198353.622717679 1
 
< 0.1%
198341.017757812 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1765
Distinct (%)53.6%
Missing185
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean443985.85
Minimum441569.06
Maximum445912.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2024-05-11T08:04:15.649770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441569.06
5-th percentile442017.93
Q1442854.86
median444101.28
Q3445038.84
95-th percentile445664.8
Maximum445912.39
Range4343.3302
Interquartile range (IQR)2183.9858

Descriptive statistics

Standard deviation1215.0955
Coefficient of variation (CV)0.0027367887
Kurtosis-1.1966468
Mean443985.85
Median Absolute Deviation (MAD)1051.013
Skewness-0.19808147
Sum1.4607135 × 109
Variance1476457
MonotonicityNot monotonic
2024-05-11T08:04:16.079227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442742.422887932 41
 
1.2%
444705.530165147 29
 
0.8%
443239.581054145 25
 
0.7%
443230.418234155 23
 
0.7%
445623.080168564 20
 
0.6%
444196.484790728 18
 
0.5%
442818.113681285 16
 
0.5%
445413.288375132 16
 
0.5%
443049.47147487 15
 
0.4%
443251.121433059 15
 
0.4%
Other values (1755) 3072
88.4%
(Missing) 185
 
5.3%
ValueCountFrequency (%)
441569.058208929 1
 
< 0.1%
441569.362995612 1
 
< 0.1%
441577.448324663 2
 
0.1%
441581.838470649 1
 
< 0.1%
441582.949309562 8
0.2%
441588.861462309 1
 
< 0.1%
441606.177364885 1
 
< 0.1%
441621.408468674 1
 
< 0.1%
441622.478200576 1
 
< 0.1%
441632.166495668 1
 
< 0.1%
ValueCountFrequency (%)
445912.388377 1
 
< 0.1%
445901.413432497 6
0.2%
445897.817620227 1
 
< 0.1%
445836.993606646 1
 
< 0.1%
445823.500892497 9
0.3%
445790.549860682 4
0.1%
445767.132034396 1
 
< 0.1%
445764.45259219 1
 
< 0.1%
445764.166038984 4
0.1%
445761.720381251 5
0.1%

위생업태명
Categorical

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
716 
커피숍
713 
일반조리판매
530 
다방
393 
기타 휴게음식점
352 
Other values (11)
771 

Length

Max length8
Median length6
Mean length4.1847482
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 716
20.6%
커피숍 713
20.5%
일반조리판매 530
15.3%
다방 393
11.3%
기타 휴게음식점 352
10.1%
편의점 271
 
7.8%
과자점 261
 
7.5%
패스트푸드 177
 
5.1%
철도역구내 25
 
0.7%
아이스크림 13
 
0.4%
Other values (6) 24
 
0.7%

Length

2024-05-11T08:04:16.772243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 716
18.7%
커피숍 713
18.6%
일반조리판매 530
13.8%
다방 393
10.3%
기타 352
9.2%
휴게음식점 352
9.2%
편의점 271
 
7.1%
과자점 261
 
6.8%
패스트푸드 177
 
4.6%
철도역구내 25
 
0.7%
Other values (7) 37
 
1.0%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
2319 
0
855 
1
 
218
2
 
71
3
 
11

Length

Max length4
Median length4
Mean length3.0020144
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row1
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 2319
66.7%
0 855
 
24.6%
1 218
 
6.3%
2 71
 
2.0%
3 11
 
0.3%
4 1
 
< 0.1%

Length

2024-05-11T08:04:17.259709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:17.756374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2319
66.7%
0 855
 
24.6%
1 218
 
6.3%
2 71
 
2.0%
3 11
 
0.3%
4 1
 
< 0.1%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.7%
Missing2313
Missing (%)66.6%
Infinite0
Infinite (%)0.0%
Mean0.86316695
Minimum0
Maximum94
Zeros665
Zeros (%)19.1%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2024-05-11T08:04:18.215243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum94
Range94
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.9502396
Coefficient of variation (CV)3.4179246
Kurtosis857.07616
Mean0.86316695
Median Absolute Deviation (MAD)0
Skewness27.222421
Sum1003
Variance8.7039135
MonotonicityNot monotonic
2024-05-11T08:04:18.546350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 665
 
19.1%
1 223
 
6.4%
2 167
 
4.8%
3 83
 
2.4%
4 17
 
0.5%
5 5
 
0.1%
94 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 2313
66.6%
ValueCountFrequency (%)
0 665
19.1%
1 223
 
6.4%
2 167
 
4.8%
3 83
 
2.4%
4 17
 
0.5%
5 5
 
0.1%
10 1
 
< 0.1%
94 1
 
< 0.1%
ValueCountFrequency (%)
94 1
 
< 0.1%
10 1
 
< 0.1%
5 5
 
0.1%
4 17
 
0.5%
3 83
 
2.4%
2 167
 
4.8%
1 223
 
6.4%
0 665
19.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
2453 
주택가주변
618 
기타
311 
아파트지역
 
48
유흥업소밀집지역
 
30
Other values (2)
 
15

Length

Max length8
Median length4
Mean length4.0644604
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2453
70.6%
주택가주변 618
 
17.8%
기타 311
 
8.9%
아파트지역 48
 
1.4%
유흥업소밀집지역 30
 
0.9%
학교정화(상대) 10
 
0.3%
학교정화(절대) 5
 
0.1%

Length

2024-05-11T08:04:18.907604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:19.259861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2453
70.6%
주택가주변 618
 
17.8%
기타 311
 
8.9%
아파트지역 48
 
1.4%
유흥업소밀집지역 30
 
0.9%
학교정화(상대 10
 
0.3%
학교정화(절대 5
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
2590 
기타
592 
지도
 
115
자율
 
70
 
61
Other values (3)
 
47

Length

Max length4
Median length4
Mean length3.4710791
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2590
74.5%
기타 592
 
17.0%
지도 115
 
3.3%
자율 70
 
2.0%
61
 
1.8%
관리 38
 
1.1%
7
 
0.2%
우수 2
 
0.1%

Length

2024-05-11T08:04:19.765499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:20.184741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2590
74.5%
기타 592
 
17.0%
지도 115
 
3.3%
자율 70
 
2.0%
61
 
1.8%
관리 38
 
1.1%
7
 
0.2%
우수 2
 
0.1%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
1747 
상수도전용
1708 
상수도(음용)지하수(주방용)겸용
 
19
간이상수도
 
1

Length

Max length17
Median length4
Mean length4.5628777
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1747
50.3%
상수도전용 1708
49.2%
상수도(음용)지하수(주방용)겸용 19
 
0.5%
간이상수도 1
 
< 0.1%

Length

2024-05-11T08:04:20.754462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:21.175266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1747
50.3%
상수도전용 1708
49.2%
상수도(음용)지하수(주방용)겸용 19
 
0.5%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
3295 
0
 
180

Length

Max length4
Median length4
Mean length3.8446043
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> 3295
94.8%
0 180
 
5.2%

Length

2024-05-11T08:04:21.847586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:22.411643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3295
94.8%
0 180
 
5.2%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
3293 
0
 
182

Length

Max length4
Median length4
Mean length3.8428777
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> 3293
94.8%
0 182
 
5.2%

Length

2024-05-11T08:04:23.096084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:23.596592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3293
94.8%
0 182
 
5.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
3293 
0
 
182

Length

Max length4
Median length4
Mean length3.8428777
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> 3293
94.8%
0 182
 
5.2%

Length

2024-05-11T08:04:24.258957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:24.759053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3293
94.8%
0 182
 
5.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
3293 
0
 
182

Length

Max length4
Median length4
Mean length3.8428777
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> 3293
94.8%
0 182
 
5.2%

Length

2024-05-11T08:04:25.108556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:25.451228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3293
94.8%
0 182
 
5.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
3293 
0
 
182

Length

Max length4
Median length4
Mean length3.8428777
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> 3293
94.8%
0 182
 
5.2%

Length

2024-05-11T08:04:25.830690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:26.140262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3293
94.8%
0 182
 
5.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3475
Missing (%)100.0%
Memory size30.7 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
3293 
0
 
182

Length

Max length4
Median length4
Mean length3.8428777
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> 3293
94.8%
0 182
 
5.2%

Length

2024-05-11T08:04:26.534003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:26.993530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3293
94.8%
0 182
 
5.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
<NA>
3293 
0
 
182

Length

Max length4
Median length4
Mean length3.8428777
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> 3293
94.8%
0 182
 
5.2%

Length

2024-05-11T08:04:27.604478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:04:28.069134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3293
94.8%
0 182
 
5.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing716
Missing (%)20.6%
Memory size6.9 KiB
False
2722 
True
 
37
(Missing)
716 
ValueCountFrequency (%)
False 2722
78.3%
True 37
 
1.1%
(Missing) 716
 
20.6%
2024-05-11T08:04:28.435602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1626
Distinct (%)58.9%
Missing716
Missing (%)20.6%
Infinite0
Infinite (%)0.0%
Mean81.075027
Minimum0
Maximum111113.52
Zeros60
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2024-05-11T08:04:28.779641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q112.925
median25
Q350.84
95-th percentile127.311
Maximum111113.52
Range111113.52
Interquartile range (IQR)37.915

Descriptive statistics

Standard deviation2115.2877
Coefficient of variation (CV)26.090497
Kurtosis2755.4927
Mean81.075027
Median Absolute Deviation (MAD)15.6
Skewness52.476208
Sum223686
Variance4474442.2
MonotonicityNot monotonic
2024-05-11T08:04:29.351948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 120
 
3.5%
6.6 91
 
2.6%
0.0 60
 
1.7%
9.9 29
 
0.8%
10.0 27
 
0.8%
33.0 27
 
0.8%
3.0 26
 
0.7%
13.2 25
 
0.7%
23.0 25
 
0.7%
20.0 22
 
0.6%
Other values (1616) 2307
66.4%
(Missing) 716
 
20.6%
ValueCountFrequency (%)
0.0 60
1.7%
1.0 2
 
0.1%
1.4 1
 
< 0.1%
1.5 1
 
< 0.1%
1.54 1
 
< 0.1%
1.6 1
 
< 0.1%
1.76 1
 
< 0.1%
2.0 6
 
0.2%
2.18 1
 
< 0.1%
2.2 2
 
0.1%
ValueCountFrequency (%)
111113.52 1
< 0.1%
982.03 1
< 0.1%
865.19 1
< 0.1%
568.0 1
< 0.1%
456.95 2
0.1%
427.02 2
0.1%
407.48 1
< 0.1%
388.4 1
< 0.1%
345.85 1
< 0.1%
331.2 1
< 0.1%

전통업소지정번호
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3474
Missing (%)> 99.9%
Memory size27.3 KiB
2024-05-11T08:04:29.649076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row.
ValueCountFrequency (%)
1
100.0%
2024-05-11T08:04:30.502004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 1
100.0%

Most frequent character per category

Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1
100.0%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3475
Missing (%)100.0%
Memory size30.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3475
Missing (%)100.0%
Memory size30.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031900003190000-104-1969-0119219690319<NA>3폐업2폐업20000306<NA><NA><NA>02 815935651.67156030서울특별시 동작구 상도동 701-3번지<NA><NA>로타리다방2000-03-08 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방02주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N51.67<NA><NA><NA>
131900003190000-104-1970-0107419701001<NA>3폐업2폐업20080822<NA><NA><NA>02 8141228117.15156839서울특별시 동작구 상도동 187-1번지<NA><NA>지성다방2000-03-27 00:00:00I2018-08-31 23:59:59.0다방194284.301857444582.34538다방12주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N117.15<NA><NA><NA>
231900003190000-104-1970-0111619700103<NA>3폐업2폐업20080812<NA><NA><NA>02 815840992.64156813서울특별시 동작구 본동 399-3번지<NA><NA>커피하우스2002-10-17 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방12유흥업소밀집지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N92.64<NA><NA><NA>
331900003190000-104-1970-0115619701028<NA>3폐업2폐업19951130<NA><NA><NA>02 815522561.28156803서울특별시 동작구 노량진동 240-27번지<NA><NA>아씨2001-09-29 00:00:00I2018-08-31 23:59:59.0다방194625.122879445440.650665다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N61.28<NA><NA><NA>
431900003190000-104-1970-0118319700309<NA>3폐업2폐업19971110<NA><NA><NA>02 815682465.96156806서울특별시 동작구 노량진동 307-159번지<NA><NA>2001-09-29 00:00:00I2018-08-31 23:59:59.0다방194617.585163445158.723576다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N65.96<NA><NA><NA>
531900003190000-104-1970-0139819700730<NA>3폐업2폐업19941114<NA><NA><NA>02081553715.25156030서울특별시 동작구 상도동 105-1번지<NA><NA>풍성2002-01-05 00:00:00I2018-08-31 23:59:59.0과자점<NA><NA>과자점02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N5.25<NA><NA><NA>
631900003190000-104-1970-0141419700831<NA>3폐업2폐업19920103<NA><NA><NA>020814414164.08156800서울특별시 동작구 노량진동 62-11번지<NA><NA>은좌2001-09-29 00:00:00I2018-08-31 23:59:59.0다방194675.267546445680.282422다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N64.08<NA><NA><NA>
731900003190000-104-1970-0157619700126<NA>3폐업2폐업19970828<NA><NA><NA>02 815027681.74156800서울특별시 동작구 노량진동 28-6번지<NA><NA>로얄제과점2001-09-29 00:00:00I2018-08-31 23:59:59.0과자점194256.864829445650.173147과자점14유흥업소밀집지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N81.74<NA><NA><NA>
831900003190000-104-1971-0126319710820<NA>3폐업2폐업19970508<NA><NA><NA>02 8158741130.06156800서울특별시 동작구 노량진동 13-29번지<NA><NA>한냉다방2001-09-29 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N130.06<NA><NA><NA>
931900003190000-104-1971-0138919711214<NA>3폐업2폐업19920610<NA><NA><NA>0208330523141.83156811서울특별시 동작구 대방동 405-1번지<NA><NA>랑랑2001-09-29 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방04주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N141.83<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
346531900003190000-104-2024-000332024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA>023280800234.51156-800서울특별시 동작구 노량진동 72-10서울특별시 동작구 노량진로16길 12-14, 1층 (노량진동)6922카페로아(cafe roa)2024-04-09 15:28:24I2023-12-03 23:01:00.0커피숍194920.794468445656.069651<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
346631900003190000-104-2024-000342024-04-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>69.22156-848서울특별시 동작구 신대방동 362-29서울특별시 동작구 여의대방로24길 24, 1층 (신대방동)7056컴포즈커피 보라매중앙점2024-04-12 10:40:18I2023-12-03 23:04:00.0커피숍192991.480776443965.263237<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
346731900003190000-104-2024-000352024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>51.17156-838서울특별시 동작구 상도동 180-2서울특별시 동작구 장승배기로 71, 1층 (상도동)6956빽다방 장승배기역점2024-04-15 16:21:19I2023-12-03 23:07:00.0커피숍194553.678319444641.743174<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
346831900003190000-104-2024-000362024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00156-755서울특별시 동작구 흑석동 224-1 중앙대학교병원 정문 앞 광장서울특별시 동작구 흑석로 102, 중앙대학교병원 정문 앞 광장 (흑석동)6973대디피자2024-04-15 14:04:33I2023-12-03 23:07:00.0푸드트럭196469.839777444981.937931<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
346931900003190000-104-2024-000372024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30156-832서울특별시 동작구 상도동 363-164서울특별시 동작구 상도로15길 131, B102, B103호 (상도동)6937세븐일레븐 동작휴엔하임점2024-04-18 14:58:22I2023-12-03 22:00:00.0편의점194443.209845444754.236227<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
347031900003190000-104-2024-000382024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30156-080서울특별시 동작구 동작동 55-21 고영빌딩서울특별시 동작구 동작대로 189, 고영빌딩 1층 102호 (동작동)6995이마트24 동작정금마을점2024-04-19 09:21:47I2023-12-03 22:01:00.0편의점198369.365882443497.2833<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
347131900003190000-104-2024-000392024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.00156-838서울특별시 동작구 상도동 204-74서울특별시 동작구 장승배기로 44-1, 1층 (상도동)6963온니떡방2024-04-19 16:25:00I2023-12-03 22:01:00.0떡카페194706.525394444413.366684<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
347231900003190000-104-2024-000402024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30156-030서울특별시 동작구 상도동 502-4서울특별시 동작구 사당로 18, 1층 (상도동)7027세븐일레븐 숭실대중앙점2024-04-30 14:42:54I2023-12-05 00:02:00.0편의점196060.844546443669.316318<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
347331900003190000-104-2024-000412024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>140.96156-816서울특별시 동작구 사당동 147-53 골든시네마타워서울특별시 동작구 동작대로 89, 골든시네마타워 1층 105, 106호 (사당동)7013스템커피 이수역점2024-05-03 11:34:53I2023-12-05 00:05:00.0커피숍198295.843258442507.699069<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
347431900003190000-104-2024-000422024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.49156-836서울특별시 동작구 상도1동 428-4서울특별시 동작구 상도로41길 24, 1층 (상도1동)6970테디의 오후(Teddy`s Afternoon)2024-05-07 15:23:06I2023-12-05 00:09:00.0커피숍195550.510681444421.828521<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>