Overview

Dataset statistics

Number of variables44
Number of observations3932
Missing cells56908
Missing cells (%)32.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory378.0 B

Variable types

Categorical15
Text7
DateTime4
Unsupported10
Numeric7
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18082/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (68.3%)Imbalance
여성종사자수 is highly imbalanced (68.3%)Imbalance
총인원 is highly imbalanced (68.3%)Imbalance
공장생산직종업원수 is highly imbalanced (62.5%)Imbalance
월세액 is highly imbalanced (85.7%)Imbalance
인허가취소일자 has 3932 (100.0%) missing valuesMissing
폐업일자 has 1143 (29.1%) missing valuesMissing
휴업시작일자 has 3932 (100.0%) missing valuesMissing
휴업종료일자 has 3932 (100.0%) missing valuesMissing
재개업일자 has 3932 (100.0%) missing valuesMissing
전화번호 has 2291 (58.3%) missing valuesMissing
소재지면적 has 679 (17.3%) missing valuesMissing
도로명주소 has 996 (25.3%) missing valuesMissing
도로명우편번호 has 1025 (26.1%) missing valuesMissing
업태구분명 has 3932 (100.0%) missing valuesMissing
좌표정보(X) has 60 (1.5%) missing valuesMissing
좌표정보(Y) has 60 (1.5%) missing valuesMissing
영업장주변구분명 has 3932 (100.0%) missing valuesMissing
등급구분명 has 3932 (100.0%) missing valuesMissing
공장사무직종업원수 has 2812 (71.5%) missing valuesMissing
공장판매직종업원수 has 2812 (71.5%) missing valuesMissing
보증액 has 3660 (93.1%) missing valuesMissing
다중이용업소여부 has 1011 (25.7%) missing valuesMissing
시설총규모 has 1011 (25.7%) missing valuesMissing
전통업소지정번호 has 3932 (100.0%) missing valuesMissing
전통업소주된음식 has 3932 (100.0%) missing valuesMissing
홈페이지 has 3932 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 45.76650365)Skewed
공장사무직종업원수 is highly skewed (γ1 = 24.04182241)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 1101 (28.0%) zerosZeros
공장판매직종업원수 has 1080 (27.5%) zerosZeros
보증액 has 264 (6.7%) zerosZeros
시설총규모 has 1974 (50.2%) zerosZeros

Reproduction

Analysis started2024-04-29 19:35:48.425982
Analysis finished2024-04-29 19:35:49.930529
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
3050000
3932 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3050000 3932
100.0%

Length

2024-04-30T04:35:49.991261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:50.067096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 3932
100.0%

관리번호
Text

UNIQUE 

Distinct3932
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
2024-04-30T04:35:50.218886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters86504
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

Unique3932 ?
Unique (%)100.0%

Sample

1st row3050000-134-2002-00001
2nd row3050000-134-2004-00001
3rd row3050000-134-2004-00002
4th row3050000-134-2004-00003
5th row3050000-134-2004-00004
ValueCountFrequency (%)
3050000-134-2002-00001 1
 
< 0.1%
3050000-134-2018-00099 1
 
< 0.1%
3050000-134-2018-00101 1
 
< 0.1%
3050000-134-2018-00102 1
 
< 0.1%
3050000-134-2018-00103 1
 
< 0.1%
3050000-134-2018-00104 1
 
< 0.1%
3050000-134-2018-00105 1
 
< 0.1%
3050000-134-2018-00106 1
 
< 0.1%
3050000-134-2018-00107 1
 
< 0.1%
3050000-134-2018-00108 1
 
< 0.1%
Other values (3922) 3922
99.7%
2024-04-30T04:35:50.486919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 36122
41.8%
- 11796
 
13.6%
3 9245
 
10.7%
1 8145
 
9.4%
2 6842
 
7.9%
4 5313
 
6.1%
5 5067
 
5.9%
9 1065
 
1.2%
7 988
 
1.1%
6 986
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74708
86.4%
Dash Punctuation 11796
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 36122
48.4%
3 9245
 
12.4%
1 8145
 
10.9%
2 6842
 
9.2%
4 5313
 
7.1%
5 5067
 
6.8%
9 1065
 
1.4%
7 988
 
1.3%
6 986
 
1.3%
8 935
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 11796
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86504
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 36122
41.8%
- 11796
 
13.6%
3 9245
 
10.7%
1 8145
 
9.4%
2 6842
 
7.9%
4 5313
 
6.1%
5 5067
 
5.9%
9 1065
 
1.2%
7 988
 
1.1%
6 986
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 36122
41.8%
- 11796
 
13.6%
3 9245
 
10.7%
1 8145
 
9.4%
2 6842
 
7.9%
4 5313
 
6.1%
5 5067
 
5.9%
9 1065
 
1.2%
7 988
 
1.1%
6 986
 
1.1%
Distinct2369
Distinct (%)60.2%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
Minimum2004-03-09 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T04:35:50.612271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:50.713816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
3
2789 
1
1143 

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 2789
70.9%
1 1143
29.1%

Length

2024-04-30T04:35:50.817026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:50.899839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2789
70.9%
1 1143
29.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
폐업
2789 
영업/정상
1143 

Length

Max length5
Median length2
Mean length2.8720753
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2789
70.9%
영업/정상 1143
29.1%

Length

2024-04-30T04:35:50.988552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:51.086490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2789
70.9%
영업/정상 1143
29.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
2
2789 
1
1143 

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 2789
70.9%
1 1143
29.1%

Length

2024-04-30T04:35:51.188436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:51.285521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2789
70.9%
1 1143
29.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
폐업
2789 
영업
1143 

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 2789
70.9%
영업 1143
29.1%

Length

2024-04-30T04:35:51.385248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:51.463399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2789
70.9%
영업 1143
29.1%

폐업일자
Date

MISSING 

Distinct1591
Distinct (%)57.0%
Missing1143
Missing (%)29.1%
Memory size30.8 KiB
Minimum2004-07-07 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T04:35:51.553440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:51.657345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB

전화번호
Text

MISSING 

Distinct1582
Distinct (%)96.4%
Missing2291
Missing (%)58.3%
Memory size30.8 KiB
2024-04-30T04:35:51.876662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.371725
Min length2

Characters and Unicode

Total characters17020
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

Unique1528 ?
Unique (%)93.1%

Sample

1st row02 9278935
2nd row02 9573090
3rd row0222443095
4th row0222137041
5th row02 9218613
ValueCountFrequency (%)
02 921
33.2%
070 28
 
1.0%
031 11
 
0.4%
960 10
 
0.4%
962 9
 
0.3%
959 8
 
0.3%
965 6
 
0.2%
966 6
 
0.2%
957 6
 
0.2%
967 5
 
0.2%
Other values (1654) 1763
63.6%
2024-04-30T04:35:52.232130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3595
21.1%
0 2746
16.1%
9 1555
9.1%
1460
8.6%
6 1316
 
7.7%
4 1143
 
6.7%
5 1098
 
6.5%
7 1081
 
6.4%
1 1065
 
6.3%
3 1062
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15560
91.4%
Space Separator 1460
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3595
23.1%
0 2746
17.6%
9 1555
10.0%
6 1316
 
8.5%
4 1143
 
7.3%
5 1098
 
7.1%
7 1081
 
6.9%
1 1065
 
6.8%
3 1062
 
6.8%
8 899
 
5.8%
Space Separator
ValueCountFrequency (%)
1460
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17020
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3595
21.1%
0 2746
16.1%
9 1555
9.1%
1460
8.6%
6 1316
 
7.7%
4 1143
 
6.7%
5 1098
 
6.5%
7 1081
 
6.4%
1 1065
 
6.3%
3 1062
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17020
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3595
21.1%
0 2746
16.1%
9 1555
9.1%
1460
8.6%
6 1316
 
7.7%
4 1143
 
6.7%
5 1098
 
6.5%
7 1081
 
6.4%
1 1065
 
6.3%
3 1062
 
6.2%

소재지면적
Text

MISSING 

Distinct920
Distinct (%)28.3%
Missing679
Missing (%)17.3%
Memory size30.8 KiB
2024-04-30T04:35:52.465451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.6898248
Min length3

Characters and Unicode

Total characters15256
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

Unique694 ?
Unique (%)21.3%

Sample

1st row85.02
2nd row24.57
3rd row207.24
4th row87.33
5th row5.56
ValueCountFrequency (%)
3.30 791
24.3%
6.60 167
 
5.1%
00 105
 
3.2%
33.00 90
 
2.8%
10.00 57
 
1.8%
16.50 45
 
1.4%
66.00 45
 
1.4%
3.00 43
 
1.3%
9.90 42
 
1.3%
26.40 39
 
1.2%
Other values (910) 1829
56.2%
2024-04-30T04:35:52.804168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4121
27.0%
. 3253
21.3%
3 2383
15.6%
1 976
 
6.4%
6 960
 
6.3%
2 833
 
5.5%
5 695
 
4.6%
4 603
 
4.0%
9 598
 
3.9%
8 487
 
3.2%
Other values (2) 347
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12001
78.7%
Other Punctuation 3255
 
21.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4121
34.3%
3 2383
19.9%
1 976
 
8.1%
6 960
 
8.0%
2 833
 
6.9%
5 695
 
5.8%
4 603
 
5.0%
9 598
 
5.0%
8 487
 
4.1%
7 345
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 3253
99.9%
, 2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 15256
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4121
27.0%
. 3253
21.3%
3 2383
15.6%
1 976
 
6.4%
6 960
 
6.3%
2 833
 
5.5%
5 695
 
4.6%
4 603
 
4.0%
9 598
 
3.9%
8 487
 
3.2%
Other values (2) 347
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15256
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4121
27.0%
. 3253
21.3%
3 2383
15.6%
1 976
 
6.4%
6 960
 
6.3%
2 833
 
5.5%
5 695
 
4.6%
4 603
 
4.0%
9 598
 
3.9%
8 487
 
3.2%
Other values (2) 347
 
2.3%
Distinct188
Distinct (%)4.8%
Missing14
Missing (%)0.4%
Memory size30.8 KiB
2024-04-30T04:35:53.112976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1531394
Min length6

Characters and Unicode

Total characters24108
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

Unique29 ?
Unique (%)0.7%

Sample

1st row130821
2nd row130817
3rd row130883
4th row130846
5th row130860
ValueCountFrequency (%)
130864 384
 
9.8%
130865 192
 
4.9%
130845 139
 
3.5%
130842 118
 
3.0%
130820 103
 
2.6%
130851 103
 
2.6%
130840 95
 
2.4%
130805 92
 
2.3%
130817 90
 
2.3%
130867 85
 
2.2%
Other values (178) 2517
64.2%
2024-04-30T04:35:53.673915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5169
21.4%
3 4622
19.2%
1 4562
18.9%
8 3886
16.1%
4 1414
 
5.9%
6 1129
 
4.7%
5 917
 
3.8%
7 788
 
3.3%
2 771
 
3.2%
- 600
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23508
97.5%
Dash Punctuation 600
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5169
22.0%
3 4622
19.7%
1 4562
19.4%
8 3886
16.5%
4 1414
 
6.0%
6 1129
 
4.8%
5 917
 
3.9%
7 788
 
3.4%
2 771
 
3.3%
9 250
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 600
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5169
21.4%
3 4622
19.2%
1 4562
18.9%
8 3886
16.1%
4 1414
 
5.9%
6 1129
 
4.7%
5 917
 
3.8%
7 788
 
3.3%
2 771
 
3.2%
- 600
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5169
21.4%
3 4622
19.2%
1 4562
18.9%
8 3886
16.1%
4 1414
 
5.9%
6 1129
 
4.7%
5 917
 
3.8%
7 788
 
3.3%
2 771
 
3.2%
- 600
 
2.5%
Distinct1850
Distinct (%)47.2%
Missing14
Missing (%)0.4%
Memory size30.8 KiB
2024-04-30T04:35:53.894342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length55
Mean length28.412455
Min length17

Characters and Unicode

Total characters111320
Distinct characters396
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

Unique1416 ?
Unique (%)36.1%

Sample

1st row서울특별시 동대문구 용두동 ***-***번지 (*층)(풍인*길 **)
2nd row서울특별시 동대문구 용두동 **-*번지
3rd row서울특별시 동대문구 답십리동 **-*번지
4th row서울특별시 동대문구 장안동 ***-*번지 외 *필지
5th row서울특별시 동대문구 제기동 ***-***번지
ValueCountFrequency (%)
서울특별시 3917
19.9%
동대문구 3916
19.9%
번지 2373
12.0%
1743
8.8%
장안동 945
 
4.8%
제기동 779
 
4.0%
625
 
3.2%
용두동 455
 
2.3%
답십리동 437
 
2.2%
전농동 385
 
2.0%
Other values (1144) 4124
20.9%
2024-04-30T04:35:54.245537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 21239
19.1%
18553
16.7%
8429
 
7.6%
4224
 
3.8%
4131
 
3.7%
4065
 
3.7%
3977
 
3.6%
3953
 
3.6%
3943
 
3.5%
3919
 
3.5%
Other values (386) 34887
31.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65764
59.1%
Other Punctuation 21380
 
19.2%
Space Separator 18553
 
16.7%
Dash Punctuation 3301
 
3.0%
Open Punctuation 821
 
0.7%
Close Punctuation 821
 
0.7%
Decimal Number 376
 
0.3%
Lowercase Letter 149
 
0.1%
Uppercase Letter 147
 
0.1%
Math Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8429
 
12.8%
4224
 
6.4%
4131
 
6.3%
4065
 
6.2%
3977
 
6.0%
3953
 
6.0%
3943
 
6.0%
3919
 
6.0%
3917
 
6.0%
2754
 
4.2%
Other values (326) 22452
34.1%
Lowercase Letter
ValueCountFrequency (%)
w 27
18.1%
e 23
15.4%
o 14
9.4%
r 11
 
7.4%
t 10
 
6.7%
a 7
 
4.7%
k 7
 
4.7%
s 7
 
4.7%
h 6
 
4.0%
n 6
 
4.0%
Other values (9) 31
20.8%
Uppercase Letter
ValueCountFrequency (%)
K 36
24.5%
S 30
20.4%
B 25
17.0%
A 15
10.2%
C 8
 
5.4%
T 7
 
4.8%
Y 6
 
4.1%
J 4
 
2.7%
X 3
 
2.0%
G 3
 
2.0%
Other values (8) 10
 
6.8%
Decimal Number
ValueCountFrequency (%)
1 74
19.7%
3 56
14.9%
2 44
11.7%
9 39
10.4%
7 30
8.0%
5 29
 
7.7%
0 27
 
7.2%
8 26
 
6.9%
4 26
 
6.9%
6 25
 
6.6%
Other Punctuation
ValueCountFrequency (%)
* 21239
99.3%
, 98
 
0.5%
. 19
 
0.1%
@ 17
 
0.1%
/ 4
 
< 0.1%
: 3
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 725
88.3%
[ 96
 
11.7%
Close Punctuation
ValueCountFrequency (%)
) 725
88.3%
] 96
 
11.7%
Space Separator
ValueCountFrequency (%)
18553
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3301
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65764
59.1%
Common 45260
40.7%
Latin 296
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8429
 
12.8%
4224
 
6.4%
4131
 
6.3%
4065
 
6.2%
3977
 
6.0%
3953
 
6.0%
3943
 
6.0%
3919
 
6.0%
3917
 
6.0%
2754
 
4.2%
Other values (326) 22452
34.1%
Latin
ValueCountFrequency (%)
K 36
 
12.2%
S 30
 
10.1%
w 27
 
9.1%
B 25
 
8.4%
e 23
 
7.8%
A 15
 
5.1%
o 14
 
4.7%
r 11
 
3.7%
t 10
 
3.4%
C 8
 
2.7%
Other values (27) 97
32.8%
Common
ValueCountFrequency (%)
* 21239
46.9%
18553
41.0%
- 3301
 
7.3%
( 725
 
1.6%
) 725
 
1.6%
, 98
 
0.2%
] 96
 
0.2%
[ 96
 
0.2%
1 74
 
0.2%
3 56
 
0.1%
Other values (13) 297
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65764
59.1%
ASCII 45556
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 21239
46.6%
18553
40.7%
- 3301
 
7.2%
( 725
 
1.6%
) 725
 
1.6%
, 98
 
0.2%
] 96
 
0.2%
[ 96
 
0.2%
1 74
 
0.2%
3 56
 
0.1%
Other values (50) 593
 
1.3%
Hangul
ValueCountFrequency (%)
8429
 
12.8%
4224
 
6.4%
4131
 
6.3%
4065
 
6.2%
3977
 
6.0%
3953
 
6.0%
3943
 
6.0%
3919
 
6.0%
3917
 
6.0%
2754
 
4.2%
Other values (326) 22452
34.1%

도로명주소
Text

MISSING 

Distinct1910
Distinct (%)65.1%
Missing996
Missing (%)25.3%
Memory size30.8 KiB
2024-04-30T04:35:54.498334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length55
Mean length36.336512
Min length22

Characters and Unicode

Total characters106684
Distinct characters390
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

Unique1478 ?
Unique (%)50.3%

Sample

1st row서울특별시 동대문구 천호대로**길 ** (용두동,(*층)(풍인*길 **))
2nd row서울특별시 동대문구 무학로**길 ** (용두동,원진빌딩 ***호)
3rd row서울특별시 동대문구 장한로**다길 ***-*, *층 (장안동)
4th row서울특별시 동대문구 무학로**길 ** (용두동)
5th row서울특별시 동대문구 사가정로**길 **-* (장안동,*층)
ValueCountFrequency (%)
2959
14.9%
서울특별시 2935
14.8%
동대문구 2934
14.8%
1492
 
7.5%
1267
 
6.4%
장안동 591
 
3.0%
제기동 473
 
2.4%
359
 
1.8%
답십리동 326
 
1.6%
용두동 293
 
1.5%
Other values (1249) 6204
31.3%
2024-04-30T04:35:54.873606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 17584
16.5%
16899
 
15.8%
6758
 
6.3%
, 3594
 
3.4%
3485
 
3.3%
3285
 
3.1%
3187
 
3.0%
( 3153
 
3.0%
) 3153
 
3.0%
3061
 
2.9%
Other values (380) 42525
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60772
57.0%
Other Punctuation 21193
 
19.9%
Space Separator 16899
 
15.8%
Open Punctuation 3199
 
3.0%
Close Punctuation 3199
 
3.0%
Decimal Number 608
 
0.6%
Dash Punctuation 515
 
0.5%
Uppercase Letter 208
 
0.2%
Lowercase Letter 79
 
0.1%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6758
 
11.1%
3485
 
5.7%
3285
 
5.4%
3187
 
5.2%
3061
 
5.0%
3029
 
5.0%
2993
 
4.9%
2989
 
4.9%
2935
 
4.8%
2935
 
4.8%
Other values (322) 26115
43.0%
Uppercase Letter
ValueCountFrequency (%)
B 58
27.9%
K 31
14.9%
S 29
13.9%
A 28
13.5%
C 13
 
6.2%
T 9
 
4.3%
Y 6
 
2.9%
G 6
 
2.9%
R 4
 
1.9%
U 3
 
1.4%
Other values (11) 21
 
10.1%
Lowercase Letter
ValueCountFrequency (%)
e 21
26.6%
w 12
15.2%
o 8
 
10.1%
r 8
 
10.1%
s 5
 
6.3%
a 5
 
6.3%
t 5
 
6.3%
l 5
 
6.3%
b 2
 
2.5%
h 2
 
2.5%
Other values (5) 6
 
7.6%
Decimal Number
ValueCountFrequency (%)
1 173
28.5%
2 108
17.8%
0 90
14.8%
4 51
 
8.4%
3 49
 
8.1%
5 44
 
7.2%
6 30
 
4.9%
9 24
 
3.9%
7 23
 
3.8%
8 16
 
2.6%
Other Punctuation
ValueCountFrequency (%)
* 17584
83.0%
, 3594
 
17.0%
. 7
 
< 0.1%
@ 7
 
< 0.1%
/ 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3153
98.6%
[ 46
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 3153
98.6%
] 46
 
1.4%
Space Separator
ValueCountFrequency (%)
16899
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 515
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60772
57.0%
Common 45625
42.8%
Latin 287
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6758
 
11.1%
3485
 
5.7%
3285
 
5.4%
3187
 
5.2%
3061
 
5.0%
3029
 
5.0%
2993
 
4.9%
2989
 
4.9%
2935
 
4.8%
2935
 
4.8%
Other values (322) 26115
43.0%
Latin
ValueCountFrequency (%)
B 58
20.2%
K 31
10.8%
S 29
10.1%
A 28
 
9.8%
e 21
 
7.3%
C 13
 
4.5%
w 12
 
4.2%
T 9
 
3.1%
o 8
 
2.8%
r 8
 
2.8%
Other values (26) 70
24.4%
Common
ValueCountFrequency (%)
* 17584
38.5%
16899
37.0%
, 3594
 
7.9%
( 3153
 
6.9%
) 3153
 
6.9%
- 515
 
1.1%
1 173
 
0.4%
2 108
 
0.2%
0 90
 
0.2%
4 51
 
0.1%
Other values (12) 305
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60772
57.0%
ASCII 45912
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 17584
38.3%
16899
36.8%
, 3594
 
7.8%
( 3153
 
6.9%
) 3153
 
6.9%
- 515
 
1.1%
1 173
 
0.4%
2 108
 
0.2%
0 90
 
0.2%
B 58
 
0.1%
Other values (48) 585
 
1.3%
Hangul
ValueCountFrequency (%)
6758
 
11.1%
3485
 
5.7%
3285
 
5.4%
3187
 
5.2%
3061
 
5.0%
3029
 
5.0%
2993
 
4.9%
2989
 
4.9%
2935
 
4.8%
2935
 
4.8%
Other values (322) 26115
43.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct236
Distinct (%)8.1%
Missing1025
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean2557.3165
Minimum2400
Maximum14284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2024-04-30T04:35:55.160984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2400
5-th percentile2435
Q12514
median2569
Q32594
95-th percentile2637.7
Maximum14284
Range11884
Interquartile range (IQR)80

Descriptive statistics

Standard deviation230.39073
Coefficient of variation (CV)0.090090818
Kurtosis2315.282
Mean2557.3165
Median Absolute Deviation (MAD)41
Skewness45.766504
Sum7434119
Variance53079.89
MonotonicityNot monotonic
2024-04-30T04:35:55.273750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2571 194
 
4.9%
2570 139
 
3.5%
2624 75
 
1.9%
2569 69
 
1.8%
2478 64
 
1.6%
2568 59
 
1.5%
2585 53
 
1.3%
2555 46
 
1.2%
2637 39
 
1.0%
2586 38
 
1.0%
Other values (226) 2131
54.2%
(Missing) 1025
26.1%
ValueCountFrequency (%)
2400 2
 
0.1%
2401 6
0.2%
2403 4
 
0.1%
2404 1
 
< 0.1%
2405 4
 
0.1%
2406 2
 
0.1%
2407 5
0.1%
2409 6
0.2%
2410 10
0.3%
2411 1
 
< 0.1%
ValueCountFrequency (%)
14284 1
 
< 0.1%
4926 1
 
< 0.1%
2646 3
 
0.1%
2645 16
0.4%
2644 29
0.7%
2643 25
0.6%
2642 5
 
0.1%
2641 6
 
0.2%
2640 11
 
0.3%
2639 29
0.7%
Distinct3698
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
2024-04-30T04:35:55.507601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length6.6197864
Min length1

Characters and Unicode

Total characters26029
Distinct characters809
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3542 ?
Unique (%)90.1%

Sample

1st row(주)팜스홀
2nd row물개건강원
3rd row미건의료기
4th row태영상사
5th row업레이어
ValueCountFrequency (%)
주식회사 87
 
1.9%
인셀덤 26
 
0.6%
세븐일레븐 25
 
0.5%
허브다이어트 24
 
0.5%
하이리빙 23
 
0.5%
gs25 21
 
0.5%
다이어트 18
 
0.4%
훼미리마트 18
 
0.4%
청량리점 16
 
0.3%
동대문점 12
 
0.3%
Other values (3935) 4375
94.2%
2024-04-30T04:35:55.878879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
915
 
3.5%
713
 
2.7%
) 702
 
2.7%
( 700
 
2.7%
626
 
2.4%
620
 
2.4%
553
 
2.1%
423
 
1.6%
419
 
1.6%
315
 
1.2%
Other values (799) 20043
77.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21957
84.4%
Uppercase Letter 839
 
3.2%
Space Separator 713
 
2.7%
Lowercase Letter 710
 
2.7%
Close Punctuation 703
 
2.7%
Open Punctuation 701
 
2.7%
Decimal Number 328
 
1.3%
Other Punctuation 60
 
0.2%
Dash Punctuation 15
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
915
 
4.2%
626
 
2.9%
620
 
2.8%
553
 
2.5%
423
 
1.9%
419
 
1.9%
315
 
1.4%
314
 
1.4%
281
 
1.3%
276
 
1.3%
Other values (723) 17215
78.4%
Uppercase Letter
ValueCountFrequency (%)
S 109
 
13.0%
G 91
 
10.8%
O 63
 
7.5%
E 47
 
5.6%
H 45
 
5.4%
N 45
 
5.4%
C 43
 
5.1%
A 41
 
4.9%
B 38
 
4.5%
I 35
 
4.2%
Other values (16) 282
33.6%
Lowercase Letter
ValueCountFrequency (%)
e 83
11.7%
o 78
11.0%
a 69
 
9.7%
n 57
 
8.0%
r 51
 
7.2%
l 43
 
6.1%
y 37
 
5.2%
t 37
 
5.2%
i 36
 
5.1%
h 29
 
4.1%
Other values (15) 190
26.8%
Decimal Number
ValueCountFrequency (%)
2 99
30.2%
5 78
23.8%
1 45
13.7%
0 31
 
9.5%
3 23
 
7.0%
4 23
 
7.0%
6 11
 
3.4%
8 10
 
3.0%
7 5
 
1.5%
9 3
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 25
41.7%
& 22
36.7%
, 5
 
8.3%
' 3
 
5.0%
# 2
 
3.3%
? 2
 
3.3%
/ 1
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 702
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 700
99.9%
[ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
= 1
33.3%
Space Separator
ValueCountFrequency (%)
713
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21943
84.3%
Common 2523
 
9.7%
Latin 1549
 
6.0%
Han 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
915
 
4.2%
626
 
2.9%
620
 
2.8%
553
 
2.5%
423
 
1.9%
419
 
1.9%
315
 
1.4%
314
 
1.4%
281
 
1.3%
276
 
1.3%
Other values (711) 17201
78.4%
Latin
ValueCountFrequency (%)
S 109
 
7.0%
G 91
 
5.9%
e 83
 
5.4%
o 78
 
5.0%
a 69
 
4.5%
O 63
 
4.1%
n 57
 
3.7%
r 51
 
3.3%
E 47
 
3.0%
H 45
 
2.9%
Other values (41) 856
55.3%
Common
ValueCountFrequency (%)
713
28.3%
) 702
27.8%
( 700
27.7%
2 99
 
3.9%
5 78
 
3.1%
1 45
 
1.8%
0 31
 
1.2%
. 25
 
1.0%
3 23
 
0.9%
4 23
 
0.9%
Other values (15) 84
 
3.3%
Han
ValueCountFrequency (%)
3
21.4%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (2) 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21943
84.3%
ASCII 4072
 
15.6%
CJK 14
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
915
 
4.2%
626
 
2.9%
620
 
2.8%
553
 
2.5%
423
 
1.9%
419
 
1.9%
315
 
1.4%
314
 
1.4%
281
 
1.3%
276
 
1.3%
Other values (711) 17201
78.4%
ASCII
ValueCountFrequency (%)
713
17.5%
) 702
17.2%
( 700
17.2%
S 109
 
2.7%
2 99
 
2.4%
G 91
 
2.2%
e 83
 
2.0%
o 78
 
1.9%
5 78
 
1.9%
a 69
 
1.7%
Other values (66) 1350
33.2%
CJK
ValueCountFrequency (%)
3
21.4%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (2) 2
14.3%
Distinct3752
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
Minimum2004-03-30 00:00:00
Maximum2024-04-24 16:54:08
2024-04-30T04:35:55.988755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:56.095811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
I
2608 
U
1324 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2608
66.3%
U 1324
33.7%

Length

2024-04-30T04:35:56.214488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:56.307193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2608
66.3%
u 1324
33.7%
Distinct1014
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-30T04:35:56.398909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:56.513854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1972
Distinct (%)50.9%
Missing60
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean204521.18
Minimum186566.14
Maximum207371.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2024-04-30T04:35:56.645806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum186566.14
5-th percentile202483.46
Q1203316.47
median204721.9
Q3205737.59
95-th percentile206307.01
Maximum207371.82
Range20805.676
Interquartile range (IQR)2421.1211

Descriptive statistics

Standard deviation1303.8156
Coefficient of variation (CV)0.0063749661
Kurtosis7.845324
Mean204521.18
Median Absolute Deviation (MAD)1185.9091
Skewness-0.81155316
Sum7.9190601 × 108
Variance1699935.1
MonotonicityNot monotonic
2024-04-30T04:35:56.768147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205787.106208763 99
 
2.5%
203075.098504907 71
 
1.8%
203347.517232661 64
 
1.6%
204081.282117393 52
 
1.3%
203434.377459802 29
 
0.7%
203403.019535366 29
 
0.7%
205271.704936121 27
 
0.7%
206101.9138443 27
 
0.7%
203356.957362754 25
 
0.6%
203397.282060237 25
 
0.6%
Other values (1962) 3424
87.1%
(Missing) 60
 
1.5%
ValueCountFrequency (%)
186566.141360856 1
 
< 0.1%
201998.969766069 1
 
< 0.1%
202012.621510207 3
0.1%
202013.401502902 1
 
< 0.1%
202014.988956307 2
0.1%
202033.014104401 1
 
< 0.1%
202033.22548938 1
 
< 0.1%
202036.453390905 2
0.1%
202042.827600608 3
0.1%
202056.394367168 2
0.1%
ValueCountFrequency (%)
207371.817832593 1
 
< 0.1%
206643.334997521 1
 
< 0.1%
206623.222570241 2
 
0.1%
206590.173910517 2
 
0.1%
206590.046202018 22
0.6%
206586.572428103 6
 
0.2%
206582.46704114 1
 
< 0.1%
206580.212542092 1
 
< 0.1%
206563.594687195 1
 
< 0.1%
206562.649224959 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1973
Distinct (%)51.0%
Missing60
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean452852.97
Minimum441737.13
Maximum455899.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2024-04-30T04:35:56.892183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441737.13
5-th percentile451191.35
Q1452185.68
median452863.3
Q3453314.14
95-th percentile454813.91
Maximum455899.98
Range14162.854
Interquartile range (IQR)1128.4593

Descriptive statistics

Standard deviation1025.1684
Coefficient of variation (CV)0.0022637996
Kurtosis3.539867
Mean452852.97
Median Absolute Deviation (MAD)580.69145
Skewness0.14762987
Sum1.7534467 × 109
Variance1050970.2
MonotonicityNot monotonic
2024-04-30T04:35:57.015767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451191.34653897 99
 
2.5%
452918.836458244 71
 
1.8%
453035.676205184 64
 
1.6%
453187.395154017 52
 
1.3%
452985.725419514 29
 
0.7%
452938.652905317 29
 
0.7%
452706.897879436 27
 
0.7%
452155.691148899 27
 
0.7%
452469.300221465 25
 
0.6%
453025.117728275 25
 
0.6%
Other values (1963) 3424
87.1%
(Missing) 60
 
1.5%
ValueCountFrequency (%)
441737.128038275 1
 
< 0.1%
450857.671867646 1
 
< 0.1%
450987.048392613 1
 
< 0.1%
450998.638678935 2
0.1%
451017.179310496 1
 
< 0.1%
451017.540622804 2
0.1%
451024.506229475 2
0.1%
451025.902075739 1
 
< 0.1%
451031.569748553 1
 
< 0.1%
451031.672241199 4
0.1%
ValueCountFrequency (%)
455899.982370316 2
 
0.1%
455830.821297367 1
 
< 0.1%
455813.713540339 1
 
< 0.1%
455808.419175247 1
 
< 0.1%
455803.028832488 1
 
< 0.1%
455801.638525525 5
0.1%
455797.417581881 1
 
< 0.1%
455752.082819335 1
 
< 0.1%
455710.688794955 1
 
< 0.1%
455681.221589435 1
 
< 0.1%

위생업태명
Categorical

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
영업장판매
1532 
<NA>
1011 
전자상거래(통신판매업)
688 
방문판매
343 
통신판매
 
146
Other values (7)
212 

Length

Max length14
Median length13
Mean length5.9699898
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row영업장판매
2nd row영업장판매
3rd row영업장판매
4th row전자상거래(통신판매업)
5th row통신판매

Common Values

ValueCountFrequency (%)
영업장판매 1532
39.0%
<NA> 1011
25.7%
전자상거래(통신판매업) 688
17.5%
방문판매 343
 
8.7%
통신판매 146
 
3.7%
다단계판매 127
 
3.2%
기타 건강기능식품일반판매업 45
 
1.1%
도매업(유통) 17
 
0.4%
기타(복합 등) 14
 
0.4%
전화권유판매 7
 
0.2%
Other values (2) 2
 
0.1%

Length

2024-04-30T04:35:57.136109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영업장판매 1532
38.4%
na 1011
25.3%
전자상거래(통신판매업 688
17.2%
방문판매 343
 
8.6%
통신판매 146
 
3.7%
다단계판매 127
 
3.2%
기타 45
 
1.1%
건강기능식품일반판매업 45
 
1.1%
도매업(유통 17
 
0.4%
기타(복합 14
 
0.4%
Other values (4) 23
 
0.6%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
<NA>
3706 
0
 
226

Length

Max length4
Median length4
Mean length3.8275687
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> 3706
94.3%
0 226
 
5.7%

Length

2024-04-30T04:35:57.248151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:57.338593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3706
94.3%
0 226
 
5.7%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
<NA>
3706 
0
 
226

Length

Max length4
Median length4
Mean length3.8275687
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> 3706
94.3%
0 226
 
5.7%

Length

2024-04-30T04:35:57.430150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:57.525271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3706
94.3%
0 226
 
5.7%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
<NA>
3472 
상수도전용
460 

Length

Max length5
Median length4
Mean length4.1169888
Min length4

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> 3472
88.3%
상수도전용 460
 
11.7%

Length

2024-04-30T04:35:57.624607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:57.723389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3472
88.3%
상수도전용 460
 
11.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
<NA>
3706 
0
 
226

Length

Max length4
Median length4
Mean length3.8275687
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> 3706
94.3%
0 226
 
5.7%

Length

2024-04-30T04:35:57.821652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:57.904427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3706
94.3%
0 226
 
5.7%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
<NA>
2812 
0
1118 
1
 
2

Length

Max length4
Median length4
Mean length3.145473
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2812
71.5%
0 1118
 
28.4%
1 2
 
0.1%

Length

2024-04-30T04:35:57.998739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:58.100265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2812
71.5%
0 1118
 
28.4%
1 2
 
0.1%

공장사무직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.7%
Missing2812
Missing (%)71.5%
Infinite0
Infinite (%)0.0%
Mean0.078571429
Minimum0
Maximum30
Zeros1101
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2024-04-30T04:35:58.170034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0195084
Coefficient of variation (CV)12.975562
Kurtosis674.55818
Mean0.078571429
Median Absolute Deviation (MAD)0
Skewness24.041822
Sum88
Variance1.0393974
MonotonicityNot monotonic
2024-04-30T04:35:58.247625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1101
 
28.0%
3 6
 
0.2%
2 4
 
0.1%
1 3
 
0.1%
4 3
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
30 1
 
< 0.1%
(Missing) 2812
71.5%
ValueCountFrequency (%)
0 1101
28.0%
1 3
 
0.1%
2 4
 
0.1%
3 6
 
0.2%
4 3
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
30 1
 
< 0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
4 3
 
0.1%
3 6
 
0.2%
2 4
 
0.1%
1 3
 
0.1%
0 1101
28.0%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.1%
Missing2812
Missing (%)71.5%
Infinite0
Infinite (%)0.0%
Mean0.20089286
Minimum0
Maximum30
Zeros1080
Zeros (%)27.5%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2024-04-30T04:35:58.331623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8701835
Coefficient of variation (CV)9.3093579
Kurtosis184.02007
Mean0.20089286
Median Absolute Deviation (MAD)0
Skewness13.037129
Sum225
Variance3.4975863
MonotonicityNot monotonic
2024-04-30T04:35:58.417562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 1080
 
27.5%
1 15
 
0.4%
2 10
 
0.3%
4 5
 
0.1%
30 2
 
0.1%
20 2
 
0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
28 1
 
< 0.1%
15 1
 
< 0.1%
Other values (2) 2
 
0.1%
(Missing) 2812
71.5%
ValueCountFrequency (%)
0 1080
27.5%
1 15
 
0.4%
2 10
 
0.3%
3 1
 
< 0.1%
4 5
 
0.1%
5 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
15 1
 
< 0.1%
20 2
 
0.1%
ValueCountFrequency (%)
30 2
 
0.1%
28 1
 
< 0.1%
20 2
 
0.1%
15 1
 
< 0.1%
10 1
 
< 0.1%
9 1
 
< 0.1%
5 1
 
< 0.1%
4 5
0.1%
3 1
 
< 0.1%
2 10
0.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
<NA>
2812 
0
1117 
5
 
1
1
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.145473
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2812
71.5%
0 1117
 
28.4%
5 1
 
< 0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%

Length

2024-04-30T04:35:58.520875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:58.608970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2812
71.5%
0 1117
 
28.4%
5 1
 
< 0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
<NA>
2140 
자가
1039 
임대
753 

Length

Max length4
Median length4
Mean length3.0885046
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2140
54.4%
자가 1039
26.4%
임대 753
 
19.2%

Length

2024-04-30T04:35:58.701974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:58.809514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2140
54.4%
자가 1039
26.4%
임대 753
 
19.2%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)2.9%
Missing3660
Missing (%)93.1%
Infinite0
Infinite (%)0.0%
Mean996323.53
Minimum0
Maximum1.8 × 108
Zeros264
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2024-04-30T04:35:58.900786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1.8 × 108
Range1.8 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11181329
Coefficient of variation (CV)11.222589
Kurtosis244.99217
Mean996323.53
Median Absolute Deviation (MAD)0
Skewness15.346304
Sum2.71 × 108
Variance1.2502213 × 1014
MonotonicityNot monotonic
2024-04-30T04:35:58.996650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 264
 
6.7%
10000000 2
 
0.1%
20000000 1
 
< 0.1%
30000000 1
 
< 0.1%
180000000 1
 
< 0.1%
5000000 1
 
< 0.1%
15000000 1
 
< 0.1%
1000000 1
 
< 0.1%
(Missing) 3660
93.1%
ValueCountFrequency (%)
0 264
6.7%
1000000 1
 
< 0.1%
5000000 1
 
< 0.1%
10000000 2
 
0.1%
15000000 1
 
< 0.1%
20000000 1
 
< 0.1%
30000000 1
 
< 0.1%
180000000 1
 
< 0.1%
ValueCountFrequency (%)
180000000 1
 
< 0.1%
30000000 1
 
< 0.1%
20000000 1
 
< 0.1%
15000000 1
 
< 0.1%
10000000 2
 
0.1%
5000000 1
 
< 0.1%
1000000 1
 
< 0.1%
0 264
6.7%

월세액
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
<NA>
3664 
0
 
264
1800000
 
1
200000
 
1
13500000
 
1

Length

Max length8
Median length4
Mean length3.8013733
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row1800000
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3664
93.2%
0 264
 
6.7%
1800000 1
 
< 0.1%
200000 1
 
< 0.1%
13500000 1
 
< 0.1%
150000 1
 
< 0.1%

Length

2024-04-30T04:35:59.109723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:59.219167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3664
93.2%
0 264
 
6.7%
1800000 1
 
< 0.1%
200000 1
 
< 0.1%
13500000 1
 
< 0.1%
150000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1011
Missing (%)25.7%
Memory size7.8 KiB
False
2921 
(Missing)
1011 
ValueCountFrequency (%)
False 2921
74.3%
(Missing) 1011
 
25.7%
2024-04-30T04:35:59.295635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct337
Distinct (%)11.5%
Missing1011
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean14.05861
Minimum0
Maximum990
Zeros1974
Zeros (%)50.2%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2024-04-30T04:35:59.379616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.3
95-th percentile83
Maximum990
Range990
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation45.717162
Coefficient of variation (CV)3.2518977
Kurtosis105.59205
Mean14.05861
Median Absolute Deviation (MAD)0
Skewness7.857015
Sum41065.2
Variance2090.0589
MonotonicityNot monotonic
2024-04-30T04:35:59.738590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1974
50.2%
3.3 238
 
6.1%
6.6 36
 
0.9%
10.0 33
 
0.8%
33.0 28
 
0.7%
3.0 20
 
0.5%
16.5 17
 
0.4%
9.9 15
 
0.4%
66.0 14
 
0.4%
30.0 14
 
0.4%
Other values (327) 532
 
13.5%
(Missing) 1011
25.7%
ValueCountFrequency (%)
0.0 1974
50.2%
1.0 12
 
0.3%
1.5 2
 
0.1%
2.0 9
 
0.2%
3.0 20
 
0.5%
3.3 238
 
6.1%
3.5 1
 
< 0.1%
4.0 2
 
0.1%
4.4 1
 
< 0.1%
4.71 1
 
< 0.1%
ValueCountFrequency (%)
990.0 1
 
< 0.1%
660.0 1
 
< 0.1%
495.0 1
 
< 0.1%
450.0 1
 
< 0.1%
438.55 1
 
< 0.1%
400.0 1
 
< 0.1%
396.0 1
 
< 0.1%
330.0 3
0.1%
307.18 1
 
< 0.1%
300.0 1
 
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3932
Missing (%)100.0%
Memory size34.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030500003050000-134-2002-0000120090309<NA>3폐업2폐업20191231<NA><NA><NA>02 927893585.02130821서울특별시 동대문구 용두동 ***-***번지 (*층)(풍인*길 **)서울특별시 동대문구 천호대로**길 ** (용두동,(*층)(풍인*길 **))2589(주)팜스홀2019-12-31 16:29:39U2020-01-02 02:40:00.0<NA>202704.736992452220.302938영업장판매<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0.0<NA><NA><NA>
130500003050000-134-2004-0000120040324<NA>3폐업2폐업20041221<NA><NA><NA>02 957309024.57130817서울특별시 동대문구 용두동 **-*번지<NA><NA>물개건강원2004-07-05 00:00:00I2018-08-31 23:59:59.0<NA>203270.898056452654.133214영업장판매<NA><NA><NA><NA><NA><NA>0020임대<NA><NA>N0.0<NA><NA><NA>
230500003050000-134-2004-0000220040324<NA>3폐업2폐업20040916<NA><NA><NA>0222443095207.24130883서울특별시 동대문구 답십리동 **-*번지<NA><NA>미건의료기2004-07-05 00:00:00I2018-08-31 23:59:59.0<NA>205033.87404452322.301296영업장판매<NA><NA><NA><NA><NA><NA>0020임대200000001800000N0.0<NA><NA><NA>
330500003050000-134-2004-0000320040325<NA>3폐업2폐업20040723<NA><NA><NA>022213704187.33130846서울특별시 동대문구 장안동 ***-*번지 외 *필지<NA><NA>태영상사2004-07-23 00:00:00I2018-08-31 23:59:59.0<NA>205931.813126451042.369316전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>0140임대<NA><NA>N0.0<NA><NA><NA>
430500003050000-134-2004-0000420040330<NA>3폐업2폐업20040707<NA><NA><NA>02 92186135.56130860서울특별시 동대문구 제기동 ***-***번지<NA><NA>업레이어2004-03-30 00:00:00I2018-08-31 23:59:59.0<NA>203125.548713454081.380093통신판매<NA><NA><NA><NA><NA><NA>0010임대<NA><NA>N0.0<NA><NA><NA>
530500003050000-134-2004-0000520040330<NA>3폐업2폐업20061113<NA><NA><NA>02 925818343.80130820서울특별시 동대문구 용두동 ***-***번지<NA><NA>수신물산 용두영업소2004-07-05 00:00:00I2018-08-31 23:59:59.0<NA>202893.485957452694.925255방문판매<NA><NA><NA><NA><NA><NA>0040<NA><NA><NA>N0.0<NA><NA><NA>
630500003050000-134-2004-0000620040309<NA>3폐업2폐업20150828<NA><NA><NA>02 9245822102.90130820서울특별시 동대문구 용두동 ***-**번지 원진빌딩 ***호서울특별시 동대문구 무학로**길 ** (용두동,원진빌딩 ***호)2585레이크우드 생명공학(주)2015-08-27 16:02:48I2018-08-31 23:59:59.0<NA>202805.715804452786.165629전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>0305임대30000000<NA>N0.0<NA><NA><NA>
730500003050000-134-2004-0000720040311<NA>3폐업2폐업20080911<NA><NA><NA>022242588418.69130851서울특별시 동대문구 전농동 ***-**번지<NA><NA>한미바이오텍2005-05-04 00:00:00I2018-08-31 23:59:59.0<NA>204765.522273453630.873363전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>0000임대10000000200000N0.0<NA><NA><NA>
830500003050000-134-2004-0000820040317<NA>3폐업2폐업20111228<NA><NA><NA>022246875113.00130805서울특별시 동대문구 답십리동 ***-*번지<NA><NA>하늘의원2011-11-24 10:21:49I2018-08-31 23:59:59.0<NA>204551.741974451706.003571영업장판매<NA><NA><NA><NA><NA><NA>0400임대18000000013500000N0.0<NA><NA><NA>
930500003050000-134-2004-000092004-03-31<NA>1영업/정상1영업<NA><NA><NA><NA>02 925353020.00130-841서울특별시 동대문구 장안동 ***-*서울특별시 동대문구 장한로**다길 ***-*, *층 (장안동)2640(주)대현에벤에셀2023-03-03 13:36:24U2022-12-03 00:05:00.0<NA>206246.844179451602.012441<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
392230500003050000-134-2024-000562024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-839서울특별시 동대문구 장안동 ***-** 삼성그린아파트서울특별시 동대문구 장한로**길 **, ***호 (장안동, 삼성그린아파트)2522상승인터네셔널2024-04-02 10:30:19I2023-12-04 00:04:00.0<NA>206455.710665452564.893434<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
392330500003050000-134-2024-000572024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>99.00130-867서울특별시 동대문구 청량리동 **-* 세종빌딩서울특별시 동대문구 제기로**길 **, *층 (청량리동)2488솔고 헬스케어2024-04-03 14:00:57I2023-12-04 00:05:00.0<NA>204282.878492453570.891988<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
392430500003050000-134-2024-000582024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA>02 96610756.60130-864서울특별시 동대문구 제기동 ***-** 한솔동의보감서울특별시 동대문구 왕산로 ***, 한솔동의보감 *층 **호 (제기동)2568자연건강상담센터2024-04-15 13:54:49U2023-12-03 23:07:00.0<NA>203075.098505452918.836458<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
392530500003050000-134-2024-000592024-04-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-030서울특별시 동대문구 답십리동 **** 한신 휴플러스 그린파크서울특별시 동대문구 답십리로**길 **, ***동 ****호 (답십리동, 한신 휴플러스 그린파크)2595건강기능상담웹2024-04-11 09:41:58I2023-12-03 23:03:00.0<NA>204325.608356452402.508039<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
392630500003050000-134-2024-000602024-04-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-060서울특별시 동대문구 제기동 **** 한신아파트서울특별시 동대문구 고산자로 ***, ***동 ****호 (제기동, 한신아파트)2467온리수2024-04-12 10:06:25I2023-12-03 23:04:00.0<NA>203388.646669454069.152284<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
392730500003050000-134-2024-000612024-04-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.00130-864서울특별시 동대문구 제기동 ****-*서울특별시 동대문구 약령중앙로 *-*, 지하*층 (제기동)2569서울한방협동조합2024-04-16 10:54:45I2023-12-03 23:08:00.0<NA>203160.859654452970.739422<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
392830500003050000-134-2024-000622024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-090서울특별시 동대문구 휘경동 *** 휘경에스케이뷰서울특별시 동대문구 휘경로 **, ***동 ****호 (휘경동, 휘경에스케이뷰)2434Dr.phil2024-04-17 17:33:41I2023-12-03 22:01:00.0<NA>205767.039551454592.910091<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
392930500003050000-134-2024-000632024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-100서울특별시 동대문구 장안동 ***-**서울특별시 동대문구 답십리로 ***, *층 (장안동)2623다비치안경 장안촬영소사거리점2024-04-18 13:27:42I2023-12-03 22:01:00.0<NA>205809.68423452251.809771<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
393030500003050000-134-2024-000642024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.40130-842서울특별시 동대문구 장안동 ***-*서울특별시 동대문구 한천로**길 **-*, *층 ***호 (장안동)2625씨앤에스메디칼(주)2024-04-23 14:17:11I2023-12-03 22:05:00.0<NA>205952.506671451814.91562<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
393130500003050000-134-2024-000652024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-840서울특별시 동대문구 장안동 *** 장안현대홈타운서울특별시 동대문구 장안벚꽃로 ***, ***동 ****호 (장안동, 장안현대홈타운)2638롤리웰리2024-04-24 11:04:56I2023-12-03 22:07:00.0<NA>206521.40532451940.11906<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>