Overview

Dataset statistics

Number of variables44
Number of observations4087
Missing cells64910
Missing cells (%)36.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory378.0 B

Variable types

Categorical14
Text7
DateTime4
Unsupported10
Numeric8
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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-18097/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (69.8%)Imbalance
여성종사자수 is highly imbalanced (69.8%)Imbalance
급수시설구분명 is highly imbalanced (56.2%)Imbalance
총인원 is highly imbalanced (70.0%)Imbalance
본사종업원수 is highly imbalanced (71.6%)Imbalance
공장생산직종업원수 is highly imbalanced (71.8%)Imbalance
인허가취소일자 has 4087 (100.0%) missing valuesMissing
폐업일자 has 1002 (24.5%) missing valuesMissing
휴업시작일자 has 4087 (100.0%) missing valuesMissing
휴업종료일자 has 4087 (100.0%) missing valuesMissing
재개업일자 has 4087 (100.0%) missing valuesMissing
전화번호 has 2396 (58.6%) missing valuesMissing
소재지면적 has 2438 (59.7%) missing valuesMissing
소재지우편번호 has 120 (2.9%) missing valuesMissing
지번주소 has 120 (2.9%) missing valuesMissing
도로명주소 has 873 (21.4%) missing valuesMissing
도로명우편번호 has 890 (21.8%) missing valuesMissing
업태구분명 has 4087 (100.0%) missing valuesMissing
영업장주변구분명 has 4087 (100.0%) missing valuesMissing
등급구분명 has 4087 (100.0%) missing valuesMissing
공장사무직종업원수 has 3302 (80.8%) missing valuesMissing
공장판매직종업원수 has 3270 (80.0%) missing valuesMissing
보증액 has 3603 (88.2%) missing valuesMissing
월세액 has 3654 (89.4%) missing valuesMissing
다중이용업소여부 has 1147 (28.1%) missing valuesMissing
시설총규모 has 1147 (28.1%) missing valuesMissing
전통업소지정번호 has 4087 (100.0%) missing valuesMissing
전통업소주된음식 has 4087 (100.0%) missing valuesMissing
홈페이지 has 4087 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = -39.26242127)Skewed
시설총규모 is highly skewed (γ1 = 24.19723398)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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 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
공장사무직종업원수 has 669 (16.4%) zerosZeros
공장판매직종업원수 has 604 (14.8%) zerosZeros
보증액 has 279 (6.8%) zerosZeros
월세액 has 278 (6.8%) zerosZeros
시설총규모 has 2924 (71.5%) zerosZeros

Reproduction

Analysis started2024-04-29 19:36:24.613758
Analysis finished2024-04-29 19:36:26.064229
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
3200000
4087 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 4087
100.0%

Length

2024-04-30T04:36:26.124272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:26.214283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 4087
100.0%

관리번호
Text

UNIQUE 

Distinct4087
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
2024-04-30T04:36:26.367926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters89914
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

Unique4087 ?
Unique (%)100.0%

Sample

1st row3200000-134-2004-00001
2nd row3200000-134-2004-00002
3rd row3200000-134-2004-00003
4th row3200000-134-2004-00004
5th row3200000-134-2004-00005
ValueCountFrequency (%)
3200000-134-2004-00001 1
 
< 0.1%
3200000-134-2019-00060 1
 
< 0.1%
3200000-134-2019-00062 1
 
< 0.1%
3200000-134-2019-00063 1
 
< 0.1%
3200000-134-2019-00064 1
 
< 0.1%
3200000-134-2019-00065 1
 
< 0.1%
3200000-134-2019-00066 1
 
< 0.1%
3200000-134-2019-00067 1
 
< 0.1%
3200000-134-2019-00068 1
 
< 0.1%
3200000-134-2019-00069 1
 
< 0.1%
Other values (4077) 4077
99.8%
2024-04-30T04:36:26.651466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37221
41.4%
- 12261
 
13.6%
2 11387
 
12.7%
3 9661
 
10.7%
1 8574
 
9.5%
4 5543
 
6.2%
9 1145
 
1.3%
5 1091
 
1.2%
6 1026
 
1.1%
7 1016
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77653
86.4%
Dash Punctuation 12261
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37221
47.9%
2 11387
 
14.7%
3 9661
 
12.4%
1 8574
 
11.0%
4 5543
 
7.1%
9 1145
 
1.5%
5 1091
 
1.4%
6 1026
 
1.3%
7 1016
 
1.3%
8 989
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 12261
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 89914
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37221
41.4%
- 12261
 
13.6%
2 11387
 
12.7%
3 9661
 
10.7%
1 8574
 
9.5%
4 5543
 
6.2%
9 1145
 
1.3%
5 1091
 
1.2%
6 1026
 
1.1%
7 1016
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89914
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37221
41.4%
- 12261
 
13.6%
2 11387
 
12.7%
3 9661
 
10.7%
1 8574
 
9.5%
4 5543
 
6.2%
9 1145
 
1.3%
5 1091
 
1.2%
6 1026
 
1.1%
7 1016
 
1.1%
Distinct2443
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
Minimum2004-03-08 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T04:36:26.805982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:36:26.928948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
3
3085 
1
1002 

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 3085
75.5%
1 1002
 
24.5%

Length

2024-04-30T04:36:27.045427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:27.139140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3085
75.5%
1 1002
 
24.5%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
폐업
3085 
영업/정상
1002 

Length

Max length5
Median length2
Mean length2.7355028
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3085
75.5%
영업/정상 1002
 
24.5%

Length

2024-04-30T04:36:27.239455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:27.327419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3085
75.5%
영업/정상 1002
 
24.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
2
3085 
1
1002 

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 3085
75.5%
1 1002
 
24.5%

Length

2024-04-30T04:36:27.417841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:27.512978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3085
75.5%
1 1002
 
24.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
폐업
3085 
영업
1002 

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 3085
75.5%
영업 1002
 
24.5%

Length

2024-04-30T04:36:27.600440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:27.675692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3085
75.5%
영업 1002
 
24.5%

폐업일자
Date

MISSING 

Distinct1848
Distinct (%)59.9%
Missing1002
Missing (%)24.5%
Memory size32.1 KiB
Minimum2004-07-06 00:00:00
Maximum2024-04-23 00:00:00
2024-04-30T04:36:27.779481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:36:27.894175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB

전화번호
Text

MISSING 

Distinct1608
Distinct (%)95.1%
Missing2396
Missing (%)58.6%
Memory size32.1 KiB
2024-04-30T04:36:28.151399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.540509
Min length6

Characters and Unicode

Total characters17824
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

Unique1546 ?
Unique (%)91.4%

Sample

1st row02 8557091
2nd row02 8788482
3rd row02 5210705
4th row02 8663173
5th row02 8845637
ValueCountFrequency (%)
02 1239
36.9%
070 41
 
1.2%
883 21
 
0.6%
882 19
 
0.6%
877 16
 
0.5%
875 14
 
0.4%
878 12
 
0.4%
871 11
 
0.3%
031 10
 
0.3%
873 10
 
0.3%
Other values (1726) 1968
58.6%
2024-04-30T04:36:28.512393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2965
16.6%
8 2677
15.0%
2 2626
14.7%
1997
11.2%
7 1532
8.6%
5 1333
7.5%
3 1067
 
6.0%
6 990
 
5.6%
1 930
 
5.2%
4 882
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15827
88.8%
Space Separator 1997
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2965
18.7%
8 2677
16.9%
2 2626
16.6%
7 1532
9.7%
5 1333
8.4%
3 1067
 
6.7%
6 990
 
6.3%
1 930
 
5.9%
4 882
 
5.6%
9 825
 
5.2%
Space Separator
ValueCountFrequency (%)
1997
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17824
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2965
16.6%
8 2677
15.0%
2 2626
14.7%
1997
11.2%
7 1532
8.6%
5 1333
7.5%
3 1067
 
6.0%
6 990
 
5.6%
1 930
 
5.2%
4 882
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17824
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2965
16.6%
8 2677
15.0%
2 2626
14.7%
1997
11.2%
7 1532
8.6%
5 1333
7.5%
3 1067
 
6.0%
6 990
 
5.6%
1 930
 
5.2%
4 882
 
4.9%

소재지면적
Text

MISSING 

Distinct665
Distinct (%)40.3%
Missing2438
Missing (%)59.7%
Memory size32.1 KiB
2024-04-30T04:36:28.761977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0485143
Min length3

Characters and Unicode

Total characters8325
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

Unique503 ?
Unique (%)30.5%

Sample

1st row112.19
2nd row95.00
3rd row168.48
4th row59.77
5th row24.00
ValueCountFrequency (%)
00 75
 
4.5%
33.00 69
 
4.2%
3.30 57
 
3.5%
66.00 35
 
2.1%
6.60 34
 
2.1%
26.40 29
 
1.8%
23.10 29
 
1.8%
16.50 28
 
1.7%
10.00 27
 
1.6%
99.00 26
 
1.6%
Other values (655) 1240
75.2%
2024-04-30T04:36:29.098354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2316
27.8%
. 1649
19.8%
1 700
 
8.4%
3 658
 
7.9%
2 625
 
7.5%
6 513
 
6.2%
5 456
 
5.5%
9 437
 
5.2%
4 391
 
4.7%
8 321
 
3.9%
Other values (2) 259
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6673
80.2%
Other Punctuation 1652
 
19.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2316
34.7%
1 700
 
10.5%
3 658
 
9.9%
2 625
 
9.4%
6 513
 
7.7%
5 456
 
6.8%
9 437
 
6.5%
4 391
 
5.9%
8 321
 
4.8%
7 256
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 1649
99.8%
, 3
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 8325
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2316
27.8%
. 1649
19.8%
1 700
 
8.4%
3 658
 
7.9%
2 625
 
7.5%
6 513
 
6.2%
5 456
 
5.5%
9 437
 
5.2%
4 391
 
4.7%
8 321
 
3.9%
Other values (2) 259
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2316
27.8%
. 1649
19.8%
1 700
 
8.4%
3 658
 
7.9%
2 625
 
7.5%
6 513
 
6.2%
5 456
 
5.5%
9 437
 
5.2%
4 391
 
4.7%
8 321
 
3.9%
Other values (2) 259
 
3.1%

소재지우편번호
Text

MISSING 

Distinct276
Distinct (%)7.0%
Missing120
Missing (%)2.9%
Memory size32.1 KiB
2024-04-30T04:36:29.395051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1865389
Min length6

Characters and Unicode

Total characters24542
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

Unique49 ?
Unique (%)1.2%

Sample

1st row151874
2nd row151832
3rd row151802
4th row151903
5th row151803
ValueCountFrequency (%)
151050 143
 
3.6%
151015 102
 
2.6%
151890 96
 
2.4%
151836 95
 
2.4%
151832 90
 
2.3%
151800 77
 
1.9%
151830 64
 
1.6%
151843 64
 
1.6%
151849 60
 
1.5%
151891 58
 
1.5%
Other values (266) 3118
78.6%
2024-04-30T04:36:29.801954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8723
35.5%
5 4916
20.0%
8 3659
14.9%
0 1622
 
6.6%
9 1122
 
4.6%
3 903
 
3.7%
2 885
 
3.6%
7 759
 
3.1%
- 740
 
3.0%
4 686
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23802
97.0%
Dash Punctuation 740
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8723
36.6%
5 4916
20.7%
8 3659
15.4%
0 1622
 
6.8%
9 1122
 
4.7%
3 903
 
3.8%
2 885
 
3.7%
7 759
 
3.2%
4 686
 
2.9%
6 527
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 740
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24542
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8723
35.5%
5 4916
20.0%
8 3659
14.9%
0 1622
 
6.6%
9 1122
 
4.6%
3 903
 
3.7%
2 885
 
3.6%
7 759
 
3.1%
- 740
 
3.0%
4 686
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24542
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8723
35.5%
5 4916
20.0%
8 3659
14.9%
0 1622
 
6.6%
9 1122
 
4.6%
3 903
 
3.7%
2 885
 
3.6%
7 759
 
3.1%
- 740
 
3.0%
4 686
 
2.8%

지번주소
Text

MISSING 

Distinct1523
Distinct (%)38.4%
Missing120
Missing (%)2.9%
Memory size32.1 KiB
2024-04-30T04:36:30.066077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length25.725485
Min length17

Characters and Unicode

Total characters102053
Distinct characters408
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1232 ?
Unique (%)31.1%

Sample

1st row서울특별시 관악구 신림동 ***-*번지 성원빌딩 *층
2nd row서울특별시 관악구 봉천동 ****-*번지
3rd row서울특별시 관악구 남현동 ****-**번지 인성빌딩*층
4th row서울특별시 관악구 신림동 ****-*번지 새한빌딩 ***호
5th row서울특별시 관악구 봉천동 **-**번지
ValueCountFrequency (%)
서울특별시 3967
21.3%
관악구 3961
21.3%
번지 2349
12.6%
봉천동 1895
10.2%
신림동 1856
10.0%
1547
 
8.3%
398
 
2.1%
382
 
2.1%
남현동 211
 
1.1%
80
 
0.4%
Other values (1107) 1970
10.6%
2024-04-30T04:36:30.461320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 22141
21.7%
17256
16.9%
4199
 
4.1%
4145
 
4.1%
4134
 
4.1%
4018
 
3.9%
4005
 
3.9%
4002
 
3.9%
3989
 
3.9%
3970
 
3.9%
Other values (398) 30194
29.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58054
56.9%
Other Punctuation 22177
 
21.7%
Space Separator 17256
 
16.9%
Dash Punctuation 3616
 
3.5%
Decimal Number 469
 
0.5%
Open Punctuation 166
 
0.2%
Close Punctuation 166
 
0.2%
Uppercase Letter 102
 
0.1%
Lowercase Letter 40
 
< 0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4199
 
7.2%
4145
 
7.1%
4134
 
7.1%
4018
 
6.9%
4005
 
6.9%
4002
 
6.9%
3989
 
6.9%
3970
 
6.8%
3968
 
6.8%
2653
 
4.6%
Other values (345) 18971
32.7%
Uppercase Letter
ValueCountFrequency (%)
B 38
37.3%
A 17
16.7%
S 9
 
8.8%
D 7
 
6.9%
T 6
 
5.9%
C 5
 
4.9%
J 4
 
3.9%
G 3
 
2.9%
W 2
 
2.0%
I 2
 
2.0%
Other values (7) 9
 
8.8%
Lowercase Letter
ValueCountFrequency (%)
e 19
47.5%
o 3
 
7.5%
w 3
 
7.5%
r 3
 
7.5%
i 3
 
7.5%
z 2
 
5.0%
t 1
 
2.5%
b 1
 
2.5%
s 1
 
2.5%
k 1
 
2.5%
Other values (3) 3
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 109
23.2%
2 56
11.9%
3 46
9.8%
0 44
9.4%
6 41
 
8.7%
4 40
 
8.5%
5 39
 
8.3%
7 37
 
7.9%
9 29
 
6.2%
8 28
 
6.0%
Other Punctuation
ValueCountFrequency (%)
* 22141
99.8%
, 14
 
0.1%
@ 8
 
< 0.1%
/ 7
 
< 0.1%
. 7
 
< 0.1%
Letter Number
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
= 1
33.3%
Space Separator
ValueCountFrequency (%)
17256
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3616
100.0%
Open Punctuation
ValueCountFrequency (%)
( 166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58053
56.9%
Common 43853
43.0%
Latin 146
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4199
 
7.2%
4145
 
7.1%
4134
 
7.1%
4018
 
6.9%
4005
 
6.9%
4002
 
6.9%
3989
 
6.9%
3970
 
6.8%
3968
 
6.8%
2653
 
4.6%
Other values (344) 18970
32.7%
Latin
ValueCountFrequency (%)
B 38
26.0%
e 19
13.0%
A 17
11.6%
S 9
 
6.2%
D 7
 
4.8%
T 6
 
4.1%
C 5
 
3.4%
J 4
 
2.7%
o 3
 
2.1%
w 3
 
2.1%
Other values (22) 35
24.0%
Common
ValueCountFrequency (%)
* 22141
50.5%
17256
39.3%
- 3616
 
8.2%
( 166
 
0.4%
) 166
 
0.4%
1 109
 
0.2%
2 56
 
0.1%
3 46
 
0.1%
0 44
 
0.1%
6 41
 
0.1%
Other values (11) 212
 
0.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58053
56.9%
ASCII 43995
43.1%
Number Forms 4
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 22141
50.3%
17256
39.2%
- 3616
 
8.2%
( 166
 
0.4%
) 166
 
0.4%
1 109
 
0.2%
2 56
 
0.1%
3 46
 
0.1%
0 44
 
0.1%
6 41
 
0.1%
Other values (41) 354
 
0.8%
Hangul
ValueCountFrequency (%)
4199
 
7.2%
4145
 
7.1%
4134
 
7.1%
4018
 
6.9%
4005
 
6.9%
4002
 
6.9%
3989
 
6.9%
3970
 
6.8%
3968
 
6.8%
2653
 
4.6%
Other values (344) 18970
32.7%
Number Forms
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
CJK
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct2103
Distinct (%)65.4%
Missing873
Missing (%)21.4%
Memory size32.1 KiB
2024-04-30T04:36:30.716033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length55
Mean length33.081518
Min length21

Characters and Unicode

Total characters106324
Distinct characters428
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1707 ?
Unique (%)53.1%

Sample

1st row서울특별시 관악구 관악로 *** (봉천동)
2nd row서울특별시 관악구 시흥대로 *** (신림동,광안빌딩 *층)
3rd row서울특별시 관악구 조원로 **, ***호 (신림동, 강남빌딩)
4th row서울특별시 관악구 은천로*길 **-* (봉천동)
5th row서울특별시 관악구 신림로59길 23, 삼모스포렉스 1011호 (신림동)
ValueCountFrequency (%)
서울특별시 3214
15.6%
관악구 3210
15.6%
3147
15.3%
1453
 
7.1%
신림동 1417
 
6.9%
봉천동 1372
 
6.7%
889
 
4.3%
남부순환로 388
 
1.9%
286
 
1.4%
남부순환로***길 200
 
1.0%
Other values (1372) 4964
24.2%
2024-04-30T04:36:31.273872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 18169
17.1%
17333
16.3%
3713
 
3.5%
3700
 
3.5%
3619
 
3.4%
, 3433
 
3.2%
3313
 
3.1%
) 3272
 
3.1%
( 3272
 
3.1%
3269
 
3.1%
Other values (418) 43231
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59355
55.8%
Other Punctuation 21619
 
20.3%
Space Separator 17333
 
16.3%
Close Punctuation 3272
 
3.1%
Open Punctuation 3272
 
3.1%
Decimal Number 622
 
0.6%
Dash Punctuation 534
 
0.5%
Uppercase Letter 216
 
0.2%
Lowercase Letter 94
 
0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3713
 
6.3%
3700
 
6.2%
3619
 
6.1%
3313
 
5.6%
3269
 
5.5%
3256
 
5.5%
3252
 
5.5%
3217
 
5.4%
3215
 
5.4%
2505
 
4.2%
Other values (358) 26296
44.3%
Uppercase Letter
ValueCountFrequency (%)
B 102
47.2%
A 31
 
14.4%
C 13
 
6.0%
S 9
 
4.2%
W 6
 
2.8%
E 6
 
2.8%
R 6
 
2.8%
D 6
 
2.8%
I 5
 
2.3%
T 5
 
2.3%
Other values (10) 27
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 23
24.5%
o 21
22.3%
b 16
17.0%
n 6
 
6.4%
i 5
 
5.3%
r 5
 
5.3%
m 4
 
4.3%
w 3
 
3.2%
z 2
 
2.1%
g 2
 
2.1%
Other values (6) 7
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 139
22.3%
0 104
16.7%
2 94
15.1%
3 65
10.5%
4 52
 
8.4%
5 49
 
7.9%
6 35
 
5.6%
7 34
 
5.5%
8 25
 
4.0%
9 25
 
4.0%
Other Punctuation
ValueCountFrequency (%)
* 18169
84.0%
, 3433
 
15.9%
@ 5
 
< 0.1%
. 5
 
< 0.1%
# 5
 
< 0.1%
/ 2
 
< 0.1%
Letter Number
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
= 1
33.3%
Space Separator
ValueCountFrequency (%)
17333
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3272
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3272
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 534
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59354
55.8%
Common 46655
43.9%
Latin 314
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3713
 
6.3%
3700
 
6.2%
3619
 
6.1%
3313
 
5.6%
3269
 
5.5%
3256
 
5.5%
3252
 
5.5%
3217
 
5.4%
3215
 
5.4%
2505
 
4.2%
Other values (357) 26295
44.3%
Latin
ValueCountFrequency (%)
B 102
32.5%
A 31
 
9.9%
e 23
 
7.3%
o 21
 
6.7%
b 16
 
5.1%
C 13
 
4.1%
S 9
 
2.9%
W 6
 
1.9%
E 6
 
1.9%
R 6
 
1.9%
Other values (28) 81
25.8%
Common
ValueCountFrequency (%)
* 18169
38.9%
17333
37.2%
, 3433
 
7.4%
) 3272
 
7.0%
( 3272
 
7.0%
- 534
 
1.1%
1 139
 
0.3%
0 104
 
0.2%
2 94
 
0.2%
3 65
 
0.1%
Other values (12) 240
 
0.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59353
55.8%
ASCII 46965
44.2%
Number Forms 4
 
< 0.1%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 18169
38.7%
17333
36.9%
, 3433
 
7.3%
) 3272
 
7.0%
( 3272
 
7.0%
- 534
 
1.1%
1 139
 
0.3%
0 104
 
0.2%
B 102
 
0.2%
2 94
 
0.2%
Other values (48) 513
 
1.1%
Hangul
ValueCountFrequency (%)
3713
 
6.3%
3700
 
6.2%
3619
 
6.1%
3313
 
5.6%
3269
 
5.5%
3256
 
5.5%
3252
 
5.5%
3217
 
5.4%
3215
 
5.4%
2505
 
4.2%
Other values (356) 26294
44.3%
Number Forms
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
CJK
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct163
Distinct (%)5.1%
Missing890
Missing (%)21.8%
Infinite0
Infinite (%)0.0%
Mean8773.3988
Minimum1449
Maximum8866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.0 KiB
2024-04-30T04:36:31.389684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1449
5-th percentile8707
Q18746
median8775
Q38806
95-th percentile8854
Maximum8866
Range7417
Interquartile range (IQR)60

Descriptive statistics

Standard deviation148.92855
Coefficient of variation (CV)0.016975012
Kurtosis1857.5941
Mean8773.3988
Median Absolute Deviation (MAD)30
Skewness-39.262421
Sum28048556
Variance22179.712
MonotonicityNot monotonic
2024-04-30T04:36:31.507914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8793 76
 
1.9%
8754 63
 
1.5%
8774 60
 
1.5%
8787 59
 
1.4%
8708 56
 
1.4%
8788 52
 
1.3%
8786 48
 
1.2%
8846 48
 
1.2%
8750 47
 
1.1%
8758 45
 
1.1%
Other values (153) 2643
64.7%
(Missing) 890
 
21.8%
ValueCountFrequency (%)
1449 1
 
< 0.1%
6651 1
 
< 0.1%
6919 1
 
< 0.1%
7009 1
 
< 0.1%
8700 18
0.4%
8701 34
0.8%
8702 21
0.5%
8703 19
0.5%
8704 23
0.6%
8705 20
0.5%
ValueCountFrequency (%)
8866 2
 
< 0.1%
8865 19
0.5%
8864 23
0.6%
8863 8
 
0.2%
8862 19
0.5%
8861 9
 
0.2%
8860 8
 
0.2%
8859 21
0.5%
8858 13
0.3%
8857 5
 
0.1%
Distinct3811
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
2024-04-30T04:36:31.774338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length28
Mean length6.9464155
Min length1

Characters and Unicode

Total characters28390
Distinct characters832
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3661 ?
Unique (%)89.6%

Sample

1st row쓰리제이팜(주)
2nd row솔고헬스케어
3rd row(주)코리즈
4th row포르탈에쎄코리아(주)
5th row플로라
ValueCountFrequency (%)
주식회사 94
 
1.8%
gs25 79
 
1.5%
허브다이어트 60
 
1.2%
세븐일레븐 36
 
0.7%
다이어트 29
 
0.6%
인셀덤 26
 
0.5%
허브 23
 
0.4%
관악점 21
 
0.4%
아리따움 17
 
0.3%
신림점 17
 
0.3%
Other values (4112) 4767
92.2%
2024-04-30T04:36:32.171644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1135
 
4.0%
1083
 
3.8%
740
 
2.6%
) 646
 
2.3%
( 636
 
2.2%
572
 
2.0%
509
 
1.8%
487
 
1.7%
419
 
1.5%
380
 
1.3%
Other values (822) 21783
76.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23772
83.7%
Space Separator 1083
 
3.8%
Uppercase Letter 954
 
3.4%
Lowercase Letter 753
 
2.7%
Close Punctuation 647
 
2.3%
Open Punctuation 637
 
2.2%
Decimal Number 458
 
1.6%
Other Punctuation 63
 
0.2%
Dash Punctuation 20
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1135
 
4.8%
740
 
3.1%
572
 
2.4%
509
 
2.1%
487
 
2.0%
419
 
1.8%
380
 
1.6%
326
 
1.4%
315
 
1.3%
311
 
1.3%
Other values (747) 18578
78.2%
Uppercase Letter
ValueCountFrequency (%)
S 165
17.3%
G 143
15.0%
O 58
 
6.1%
A 52
 
5.5%
B 51
 
5.3%
C 50
 
5.2%
N 43
 
4.5%
I 42
 
4.4%
H 38
 
4.0%
M 34
 
3.6%
Other values (15) 278
29.1%
Lowercase Letter
ValueCountFrequency (%)
e 97
12.9%
a 65
 
8.6%
o 63
 
8.4%
r 58
 
7.7%
t 57
 
7.6%
i 55
 
7.3%
n 52
 
6.9%
l 36
 
4.8%
y 32
 
4.2%
m 31
 
4.1%
Other values (15) 207
27.5%
Decimal Number
ValueCountFrequency (%)
2 157
34.3%
5 136
29.7%
1 39
 
8.5%
4 37
 
8.1%
3 29
 
6.3%
0 17
 
3.7%
9 16
 
3.5%
6 13
 
2.8%
8 11
 
2.4%
7 3
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 34
54.0%
& 17
27.0%
, 8
 
12.7%
' 2
 
3.2%
# 1
 
1.6%
! 1
 
1.6%
Math Symbol
ValueCountFrequency (%)
< 1
33.3%
> 1
33.3%
~ 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 646
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 636
99.8%
[ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1083
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23769
83.7%
Common 2911
 
10.3%
Latin 1707
 
6.0%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1135
 
4.8%
740
 
3.1%
572
 
2.4%
509
 
2.1%
487
 
2.0%
419
 
1.8%
380
 
1.6%
326
 
1.4%
315
 
1.3%
311
 
1.3%
Other values (745) 18575
78.1%
Latin
ValueCountFrequency (%)
S 165
 
9.7%
G 143
 
8.4%
e 97
 
5.7%
a 65
 
3.8%
o 63
 
3.7%
O 58
 
3.4%
r 58
 
3.4%
t 57
 
3.3%
i 55
 
3.2%
A 52
 
3.0%
Other values (40) 894
52.4%
Common
ValueCountFrequency (%)
1083
37.2%
) 646
22.2%
( 636
21.8%
2 157
 
5.4%
5 136
 
4.7%
1 39
 
1.3%
4 37
 
1.3%
. 34
 
1.2%
3 29
 
1.0%
- 20
 
0.7%
Other values (15) 94
 
3.2%
Han
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23767
83.7%
ASCII 4618
 
16.3%
CJK 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1135
 
4.8%
740
 
3.1%
572
 
2.4%
509
 
2.1%
487
 
2.0%
419
 
1.8%
380
 
1.6%
326
 
1.4%
315
 
1.3%
311
 
1.3%
Other values (744) 18573
78.1%
ASCII
ValueCountFrequency (%)
1083
23.5%
) 646
14.0%
( 636
13.8%
S 165
 
3.6%
2 157
 
3.4%
G 143
 
3.1%
5 136
 
2.9%
e 97
 
2.1%
a 65
 
1.4%
o 63
 
1.4%
Other values (65) 1427
30.9%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
2
66.7%
1
33.3%
Distinct3915
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
Minimum2004-04-30 00:00:00
Maximum2024-04-24 14:44:12
2024-04-30T04:36:32.293018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:36:32.415538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
I
2548 
U
1539 

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 2548
62.3%
U 1539
37.7%

Length

2024-04-30T04:36:32.522987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:32.612126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2548
62.3%
u 1539
37.7%
Distinct999
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-30T04:36:32.704087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:36:32.832829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB

좌표정보(X)
Real number (ℝ)

Distinct2559
Distinct (%)63.2%
Missing39
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean194611.89
Minimum191084.94
Maximum202625.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.0 KiB
2024-04-30T04:36:32.953349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191084.94
5-th percentile192106.4
Q1193415.29
median194497.19
Q3195864.86
95-th percentile197557.94
Maximum202625.59
Range11540.651
Interquartile range (IQR)2449.5682

Descriptive statistics

Standard deviation1650.8835
Coefficient of variation (CV)0.0084829528
Kurtosis-0.49024412
Mean194611.89
Median Absolute Deviation (MAD)1198.734
Skewness0.21943814
Sum7.8778893 × 108
Variance2725416.3
MonotonicityNot monotonic
2024-04-30T04:36:33.059620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
195563.161650411 43
 
1.1%
193301.885808714 32
 
0.8%
195588.796492288 32
 
0.8%
192012.500669524 21
 
0.5%
196257.833652996 21
 
0.5%
194879.596231677 21
 
0.5%
196350.708293561 19
 
0.5%
195999.574887132 18
 
0.4%
195045.515107949 18
 
0.4%
193746.833837509 17
 
0.4%
Other values (2549) 3806
93.1%
(Missing) 39
 
1.0%
ValueCountFrequency (%)
191084.937997691 1
 
< 0.1%
191139.258430167 1
 
< 0.1%
191161.849432287 1
 
< 0.1%
191182.370774349 1
 
< 0.1%
191204.884621244 2
< 0.1%
191210.00657717 1
 
< 0.1%
191210.078732513 3
0.1%
191215.879312952 1
 
< 0.1%
191223.827173065 1
 
< 0.1%
191234.651997803 1
 
< 0.1%
ValueCountFrequency (%)
202625.589439164 1
 
< 0.1%
201213.808274052 1
 
< 0.1%
198811.570875592 1
 
< 0.1%
198675.092821991 1
 
< 0.1%
198449.002171 2
 
< 0.1%
198400.38041053 2
 
< 0.1%
198392.240810292 2
 
< 0.1%
198374.473281221 1
 
< 0.1%
198333.938333729 1
 
< 0.1%
198315.174254041 5
0.1%

좌표정보(Y)
Real number (ℝ)

Distinct2559
Distinct (%)63.2%
Missing39
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean441999.11
Minimum439023.17
Maximum460395.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.0 KiB
2024-04-30T04:36:33.174714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile440569.47
Q1441485.32
median442114.37
Q3442543.98
95-th percentile443064.44
Maximum460395.26
Range21372.089
Interquartile range (IQR)1058.661

Descriptive statistics

Standard deviation843.75965
Coefficient of variation (CV)0.0019089623
Kurtosis61.232527
Mean441999.11
Median Absolute Deviation (MAD)530.69307
Skewness2.5769766
Sum1.7892124 × 109
Variance711930.34
MonotonicityNot monotonic
2024-04-30T04:36:33.297711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443064.437566493 43
 
1.1%
443151.561302292 32
 
0.8%
442098.372819317 32
 
0.8%
441885.529640794 21
 
0.5%
443341.379446435 21
 
0.5%
442483.131081868 21
 
0.5%
442532.440501316 19
 
0.5%
443044.700996218 18
 
0.4%
443011.455007816 18
 
0.4%
442510.775085572 17
 
0.4%
Other values (2549) 3806
93.1%
(Missing) 39
 
1.0%
ValueCountFrequency (%)
439023.167125842 11
0.3%
439663.585570958 16
0.4%
439787.715563055 3
 
0.1%
439809.669640911 1
 
< 0.1%
439816.999224208 3
 
0.1%
439825.822160271 1
 
< 0.1%
439837.316813139 4
 
0.1%
439853.488919065 6
 
0.1%
439874.240349546 1
 
< 0.1%
439885.315238411 1
 
< 0.1%
ValueCountFrequency (%)
460395.256601978 1
 
< 0.1%
451518.870744569 1
 
< 0.1%
449897.213071289 1
 
< 0.1%
445023.088850366 1
 
< 0.1%
443547.049696825 11
0.3%
443437.692580028 1
 
< 0.1%
443415.023170772 1
 
< 0.1%
443369.161080189 4
 
0.1%
443360.266507676 1
 
< 0.1%
443347.669199144 1
 
< 0.1%

위생업태명
Categorical

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
영업장판매
1434 
<NA>
1147 
전자상거래(통신판매업)
631 
방문판매
347 
통신판매
280 
Other values (6)
248 

Length

Max length14
Median length12
Mean length5.6569611
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row영업장판매
2nd row영업장판매
3rd row통신판매
4th row통신판매
5th row영업장판매

Common Values

ValueCountFrequency (%)
영업장판매 1434
35.1%
<NA> 1147
28.1%
전자상거래(통신판매업) 631
15.4%
방문판매 347
 
8.5%
통신판매 280
 
6.9%
다단계판매 229
 
5.6%
전화권유판매 12
 
0.3%
기타(복합 등) 2
 
< 0.1%
도매업(유통) 2
 
< 0.1%
기타 건강기능식품일반판매업 2
 
< 0.1%

Length

2024-04-30T04:36:33.417692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영업장판매 1434
35.1%
na 1147
28.0%
전자상거래(통신판매업 631
15.4%
방문판매 347
 
8.5%
통신판매 280
 
6.8%
다단계판매 229
 
5.6%
전화권유판매 12
 
0.3%
기타(복합 2
 
< 0.1%
2
 
< 0.1%
도매업(유통 2
 
< 0.1%
Other values (3) 5
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
<NA>
3867 
0
 
220

Length

Max length4
Median length4
Mean length3.8385124
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> 3867
94.6%
0 220
 
5.4%

Length

2024-04-30T04:36:33.514151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:33.600911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3867
94.6%
0 220
 
5.4%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
<NA>
3867 
0
 
220

Length

Max length4
Median length4
Mean length3.8385124
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> 3867
94.6%
0 220
 
5.4%

Length

2024-04-30T04:36:33.691140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:33.789082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3867
94.6%
0 220
 
5.4%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
<NA>
3717 
상수도전용
 
370

Length

Max length5
Median length4
Mean length4.090531
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3717
90.9%
상수도전용 370
 
9.1%

Length

2024-04-30T04:36:33.898064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:34.035959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3717
90.9%
상수도전용 370
 
9.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
<NA>
3869 
0
 
218

Length

Max length4
Median length4
Mean length3.8399804
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> 3869
94.7%
0 218
 
5.3%

Length

2024-04-30T04:36:34.176260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:34.315712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3869
94.7%
0 218
 
5.3%

본사종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
<NA>
3313 
0
758 
1
 
9
2
 
4
3
 
2

Length

Max length4
Median length4
Mean length3.4318571
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3313
81.1%
0 758
 
18.5%
1 9
 
0.2%
2 4
 
0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-30T04:36:34.454775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:34.568402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3313
81.1%
0 758
 
18.5%
1 9
 
0.2%
2 4
 
0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)1.8%
Missing3302
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean0.44713376
Minimum0
Maximum50
Zeros669
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size36.0 KiB
2024-04-30T04:36:34.662443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum50
Range50
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4322598
Coefficient of variation (CV)5.4396694
Kurtosis242.15952
Mean0.44713376
Median Absolute Deviation (MAD)0
Skewness13.680979
Sum351
Variance5.9158878
MonotonicityNot monotonic
2024-04-30T04:36:34.759809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 669
 
16.4%
1 69
 
1.7%
2 15
 
0.4%
3 9
 
0.2%
4 7
 
0.2%
5 5
 
0.1%
8 3
 
0.1%
9 2
 
< 0.1%
13 1
 
< 0.1%
18 1
 
< 0.1%
Other values (4) 4
 
0.1%
(Missing) 3302
80.8%
ValueCountFrequency (%)
0 669
16.4%
1 69
 
1.7%
2 15
 
0.4%
3 9
 
0.2%
4 7
 
0.2%
5 5
 
0.1%
6 1
 
< 0.1%
8 3
 
0.1%
9 2
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
50 1
 
< 0.1%
26 1
 
< 0.1%
18 1
 
< 0.1%
17 1
 
< 0.1%
13 1
 
< 0.1%
9 2
 
< 0.1%
8 3
0.1%
6 1
 
< 0.1%
5 5
0.1%
4 7
0.2%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)2.4%
Missing3270
Missing (%)80.0%
Infinite0
Infinite (%)0.0%
Mean1.4381885
Minimum0
Maximum100
Zeros604
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size36.0 KiB
2024-04-30T04:36:34.868360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum100
Range100
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.6377863
Coefficient of variation (CV)4.6153799
Kurtosis145.66831
Mean1.4381885
Median Absolute Deviation (MAD)0
Skewness10.982046
Sum1175
Variance44.060207
MonotonicityNot monotonic
2024-04-30T04:36:34.961268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 604
 
14.8%
1 87
 
2.1%
2 38
 
0.9%
3 21
 
0.5%
5 13
 
0.3%
10 12
 
0.3%
4 11
 
0.3%
20 8
 
0.2%
6 4
 
0.1%
8 4
 
0.1%
Other values (10) 15
 
0.4%
(Missing) 3270
80.0%
ValueCountFrequency (%)
0 604
14.8%
1 87
 
2.1%
2 38
 
0.9%
3 21
 
0.5%
4 11
 
0.3%
5 13
 
0.3%
6 4
 
0.1%
8 4
 
0.1%
9 1
 
< 0.1%
10 12
 
0.3%
ValueCountFrequency (%)
100 2
 
< 0.1%
80 1
 
< 0.1%
48 1
 
< 0.1%
30 1
 
< 0.1%
26 1
 
< 0.1%
20 8
0.2%
15 4
0.1%
14 1
 
< 0.1%
13 1
 
< 0.1%
12 2
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
<NA>
3326 
0
744 
1
 
12
4
 
2
3
 
2

Length

Max length4
Median length4
Mean length3.4413996
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3326
81.4%
0 744
 
18.2%
1 12
 
0.3%
4 2
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-30T04:36:35.062634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:35.163725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3326
81.4%
0 744
 
18.2%
1 12
 
0.3%
4 2
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
<NA>
2793 
임대
906 
자가
388 

Length

Max length4
Median length4
Mean length3.3667727
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2793
68.3%
임대 906
 
22.2%
자가 388
 
9.5%

Length

2024-04-30T04:36:35.284691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:36:35.402425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2793
68.3%
임대 906
 
22.2%
자가 388
 
9.5%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct57
Distinct (%)11.8%
Missing3603
Missing (%)88.2%
Infinite0
Infinite (%)0.0%
Mean28735888
Minimum0
Maximum1.4 × 109
Zeros279
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size36.0 KiB
2024-04-30T04:36:35.512698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q320000000
95-th percentile1.4925 × 108
Maximum1.4 × 109
Range1.4 × 109
Interquartile range (IQR)20000000

Descriptive statistics

Standard deviation1.0216282 × 108
Coefficient of variation (CV)3.5552345
Kurtosis102.51365
Mean28735888
Median Absolute Deviation (MAD)0
Skewness9.0238069
Sum1.390817 × 1010
Variance1.0437242 × 1016
MonotonicityNot monotonic
2024-04-30T04:36:35.837401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 279
 
6.8%
20000000 28
 
0.7%
10000000 19
 
0.5%
5000000 15
 
0.4%
30000000 12
 
0.3%
50000000 11
 
0.3%
15000000 11
 
0.3%
40000000 9
 
0.2%
100000000 7
 
0.2%
3000000 6
 
0.1%
Other values (47) 87
 
2.1%
(Missing) 3603
88.2%
ValueCountFrequency (%)
0 279
6.8%
1000000 4
 
0.1%
1500000 1
 
< 0.1%
2000000 2
 
< 0.1%
3000000 6
 
0.1%
3500000 1
 
< 0.1%
4000000 1
 
< 0.1%
4500000 1
 
< 0.1%
5000000 15
 
0.4%
5500000 1
 
< 0.1%
ValueCountFrequency (%)
1400000000 1
 
< 0.1%
1170000000 1
 
< 0.1%
600000000 1
 
< 0.1%
500000000 2
< 0.1%
400000000 1
 
< 0.1%
360000000 1
 
< 0.1%
300000000 1
 
< 0.1%
250000000 1
 
< 0.1%
200000000 3
0.1%
180000000 2
< 0.1%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct62
Distinct (%)14.3%
Missing3654
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean576115.47
Minimum0
Maximum11000000
Zeros278
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size36.0 KiB
2024-04-30T04:36:35.952576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3600000
95-th percentile2500000
Maximum11000000
Range11000000
Interquartile range (IQR)600000

Descriptive statistics

Standard deviation1364612.4
Coefficient of variation (CV)2.3686439
Kurtosis21.9896
Mean576115.47
Median Absolute Deviation (MAD)0
Skewness4.2371222
Sum2.49458 × 108
Variance1.862167 × 1012
MonotonicityNot monotonic
2024-04-30T04:36:36.068303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 278
 
6.8%
200000 10
 
0.2%
1500000 9
 
0.2%
1100000 7
 
0.2%
500000 7
 
0.2%
700000 6
 
0.1%
2000000 6
 
0.1%
600000 5
 
0.1%
300000 5
 
0.1%
800000 5
 
0.1%
Other values (52) 95
 
2.3%
(Missing) 3654
89.4%
ValueCountFrequency (%)
0 278
6.8%
100000 2
 
< 0.1%
150000 2
 
< 0.1%
200000 10
 
0.2%
240000 1
 
< 0.1%
250000 2
 
< 0.1%
270000 1
 
< 0.1%
300000 5
 
0.1%
330000 2
 
< 0.1%
350000 1
 
< 0.1%
ValueCountFrequency (%)
11000000 1
 
< 0.1%
9500000 1
 
< 0.1%
8800000 1
 
< 0.1%
8000000 3
0.1%
7700000 1
 
< 0.1%
5850000 1
 
< 0.1%
5000000 2
< 0.1%
4000000 2
< 0.1%
3702000 1
 
< 0.1%
3500000 3
0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1147
Missing (%)28.1%
Memory size8.1 KiB
False
2940 
(Missing)
1147 
ValueCountFrequency (%)
False 2940
71.9%
(Missing) 1147
 
28.1%
2024-04-30T04:36:36.157344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct15
Distinct (%)0.5%
Missing1147
Missing (%)28.1%
Infinite0
Infinite (%)0.0%
Mean0.53070748
Minimum0
Maximum326.7
Zeros2924
Zeros (%)71.5%
Negative0
Negative (%)0.0%
Memory size36.0 KiB
2024-04-30T04:36:36.228179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum326.7
Range326.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.275674
Coefficient of variation (CV)19.362217
Kurtosis638.50935
Mean0.53070748
Median Absolute Deviation (MAD)0
Skewness24.197234
Sum1560.28
Variance105.58947
MonotonicityNot monotonic
2024-04-30T04:36:36.317441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 2924
71.5%
3.3 2
 
< 0.1%
25.0 2
 
< 0.1%
255.78 1
 
< 0.1%
148.0 1
 
< 0.1%
77.4 1
 
< 0.1%
31.32 1
 
< 0.1%
326.7 1
 
< 0.1%
97.06 1
 
< 0.1%
175.0 1
 
< 0.1%
Other values (5) 5
 
0.1%
(Missing) 1147
 
28.1%
ValueCountFrequency (%)
0.0 2924
71.5%
3.3 2
 
< 0.1%
20.55 1
 
< 0.1%
23.87 1
 
< 0.1%
25.0 2
 
< 0.1%
31.32 1
 
< 0.1%
33.0 1
 
< 0.1%
65.0 1
 
< 0.1%
77.4 1
 
< 0.1%
97.06 1
 
< 0.1%
ValueCountFrequency (%)
326.7 1
< 0.1%
255.78 1
< 0.1%
250.0 1
< 0.1%
175.0 1
< 0.1%
148.0 1
< 0.1%
97.06 1
< 0.1%
77.4 1
< 0.1%
65.0 1
< 0.1%
33.0 1
< 0.1%
31.32 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4087
Missing (%)100.0%
Memory size36.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032000003200000-134-2004-0000120040308<NA>3폐업2폐업20050201<NA><NA><NA>02 8557091112.19151874서울특별시 관악구 신림동 ***-*번지 성원빌딩 *층<NA><NA>쓰리제이팜(주)2004-05-10 00:00:00I2018-08-31 23:59:59.0<NA>192299.203878442496.61787영업장판매<NA><NA><NA><NA>상수도전용<NA>0141임대<NA><NA>N0.0<NA><NA><NA>
132000003200000-134-2004-0000220040318<NA>3폐업2폐업20070820<NA><NA><NA>02 878848295.00151832서울특별시 관악구 봉천동 ****-*번지<NA><NA>솔고헬스케어2005-08-11 00:00:00I2018-08-31 23:59:59.0<NA>196937.086446441297.226107영업장판매<NA><NA><NA><NA>상수도전용<NA>0010임대<NA><NA>N0.0<NA><NA><NA>
232000003200000-134-2004-0000320040326<NA>3폐업2폐업20090206<NA><NA><NA>02 5210705168.48151802서울특별시 관악구 남현동 ****-**번지 인성빌딩*층<NA><NA>(주)코리즈2004-04-30 00:00:00I2018-08-31 23:59:59.0<NA>197771.766609441556.215397통신판매<NA><NA><NA><NA>상수도전용<NA>01300임대<NA><NA>N0.0<NA><NA><NA>
332000003200000-134-2004-0000420040327<NA>3폐업2폐업20120207<NA><NA><NA>02 866317359.77151903서울특별시 관악구 신림동 ****-*번지 새한빌딩 ***호<NA><NA>포르탈에쎄코리아(주)2004-07-23 00:00:00I2018-08-31 23:59:59.0<NA>191530.450376442338.484748통신판매<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
432000003200000-134-2004-0000520040403<NA>3폐업2폐업20151218<NA><NA><NA>02 884563724.00151803서울특별시 관악구 봉천동 **-**번지서울특별시 관악구 관악로 *** (봉천동)8732플로라2015-12-18 13:04:13I2018-08-31 23:59:59.0<NA>196241.814296442914.386485영업장판매<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
532000003200000-134-2004-0000620040413<NA>3폐업2폐업20150127<NA><NA><NA>02 856616122.00151902서울특별시 관악구 신림동 ****번지 광안빌딩 *층서울특별시 관악구 시흥대로 *** (신림동,광안빌딩 *층)8700성지한의원2004-05-10 00:00:00I2018-08-31 23:59:59.0<NA>191376.602184442456.748277영업장판매<NA><NA><NA><NA>상수도전용<NA>0010임대<NA><NA>N0.0<NA><NA><NA>
632000003200000-134-2004-0000720040416<NA>3폐업2폐업20101123<NA><NA><NA>023285007723.15151050서울특별시 관악구 봉천동 ****번지 두산아파트A상가 ***호<NA><NA>웰빙라이프2010-03-22 21:24:58I2018-08-31 23:59:59.0<NA>194879.596232442483.131082영업장판매<NA><NA><NA><NA>상수도전용<NA>0010임대<NA><NA>N0.0<NA><NA><NA>
732000003200000-134-2004-0000920040419<NA>3폐업2폐업20180816<NA><NA><NA>02 859008919.00151903서울특별시 관악구 신림동 ****번지 강남빌딩 ***호서울특별시 관악구 조원로 **, ***호 (신림동, 강남빌딩)8769한미내추럴월드2018-08-16 15:45:50I2018-08-31 23:59:59.0<NA>191494.217232442341.131995방문판매<NA><NA><NA><NA>상수도전용<NA>01200임대<NA><NA>N0.0<NA><NA><NA>
832000003200000-134-2004-0001020040419<NA>3폐업2폐업20070327<NA><NA><NA>02 8594470139.31151903서울특별시 관악구 신림동 ****-*번지 강남빌딩***<NA><NA>주식회사 종근당건강에쓰비내츄럴2004-06-04 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA>방문판매<NA><NA><NA><NA>상수도전용<NA>01200임대<NA><NA>N0.0<NA><NA><NA>
932000003200000-134-2004-0001120040511<NA>3폐업2폐업20150527<NA><NA><NA>02 885917910.34151827서울특별시 관악구 봉천동 ***-**번지서울특별시 관악구 은천로*길 **-* (봉천동)8749국제건강가족동호회.비알엠연구소2014-01-02 16:05:58I2018-08-31 23:59:59.0<NA>194385.944814442641.820181영업장판매<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
407732000003200000-134-2024-000642024-04-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>151-869서울특별시 관악구 신림동 ****-**서울특별시 관악구 신원로*길 **-**, *층 (신림동)8774하비비엘(Habb-L)2024-04-11 15:33:30I2023-12-03 23:03:00.0<NA>193433.41481442144.360544<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
407832000003200000-134-2024-000652024-04-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>151-822서울특별시 관악구 봉천동 ***-** 운경하우스서울특별시 관악구 봉천로**나길 **, 운경하우스 ***호 (봉천동)8745드림 프로젝트2024-04-11 15:46:04I2023-12-03 23:03:00.0<NA>195598.164131442320.897545<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
407932000003200000-134-2024-000662024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>151-826서울특별시 관악구 봉천동 ***-**서울특별시 관악구 국회단지*길 **, ***호 (봉천동)8716유영리테일2024-04-15 09:03:25I2023-12-03 23:07:00.0<NA>194771.864922442704.079284<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
408032000003200000-134-2024-000672024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>151-872서울특별시 관악구 신림동 ***-**서울특별시 관악구 남부순환로***길 **, ***호 (신림동)8762앤드앤츠(andants)2024-04-17 15:40:22I2023-12-03 23:09:00.0<NA>192588.332013442377.875247<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
408132000003200000-134-2024-000682024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>77.55151-813서울특별시 관악구 봉천동 **-*서울특별시 관악구 남부순환로***길 **-*, 지하*층 (봉천동)8740예예점핑2024-04-17 17:51:43I2023-12-03 23:09:00.0<NA>196297.32216442048.760199<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
408232000003200000-134-2024-000692024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30151-892서울특별시 관악구 신림동 ****-*서울특별시 관악구 신림로 ***, *, *층 (신림동)8760다비치안경(신림점)2024-04-22 13:18:03I2023-12-03 22:04:00.0<NA>193637.45133442741.110638<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
408332000003200000-134-2024-000702024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.00151-848서울특별시 관악구 봉천동 ****-** GTI 빌딩서울특별시 관악구 남부순환로 ****, GTI 빌딩 ***호 (봉천동)8789주식회사 미나헬쓰웨이2024-04-23 11:41:08I2023-12-03 22:05:00.0<NA>196304.542171441820.178149<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
408432000003200000-134-2024-000712024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>151-895서울특별시 관악구 신림동 ****-*서울특별시 관악구 호암로**길 *, *층 ***호 (신림동)8812뉴지엄랩2024-04-24 09:41:50I2023-12-03 22:06:00.0<NA>194052.406287440860.610546<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
408532000003200000-134-2024-000722024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>151-814서울특별시 관악구 봉천동 ****-**서울특별시 관악구 인헌길 **, ***호 (봉천동)8795영스토어2024-04-24 14:33:08I2023-12-03 22:06:00.0<NA>197004.34269441280.579706<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
408632000003200000-134-2024-000732024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>151-832서울특별시 관악구 봉천동 ****-**서울특별시 관악구 인헌*길 *, *층 (봉천동)8793지니2024-04-24 14:44:12I2023-12-03 22:06:00.0<NA>196964.694092441452.928724<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>