Overview

Dataset statistics

Number of variables44
Number of observations3497
Missing cells47268
Missing cells (%)30.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory377.0 B

Variable types

Categorical17
Text8
DateTime4
Unsupported9
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-18087/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
홈페이지 has constant value ""Constant
남성종사자수 is highly imbalanced (60.0%)Imbalance
여성종사자수 is highly imbalanced (60.0%)Imbalance
급수시설구분명 is highly imbalanced (93.7%)Imbalance
총인원 is highly imbalanced (60.0%)Imbalance
본사종업원수 is highly imbalanced (64.9%)Imbalance
공장사무직종업원수 is highly imbalanced (74.8%)Imbalance
공장생산직종업원수 is highly imbalanced (65.0%)Imbalance
보증액 is highly imbalanced (79.6%)Imbalance
월세액 is highly imbalanced (74.5%)Imbalance
인허가취소일자 has 3497 (100.0%) missing valuesMissing
폐업일자 has 1283 (36.7%) missing valuesMissing
휴업시작일자 has 3497 (100.0%) missing valuesMissing
휴업종료일자 has 3497 (100.0%) missing valuesMissing
재개업일자 has 3497 (100.0%) missing valuesMissing
전화번호 has 2435 (69.6%) missing valuesMissing
소재지면적 has 2027 (58.0%) missing valuesMissing
도로명주소 has 678 (19.4%) missing valuesMissing
도로명우편번호 has 695 (19.9%) missing valuesMissing
업태구분명 has 3497 (100.0%) missing valuesMissing
좌표정보(X) has 43 (1.2%) missing valuesMissing
좌표정보(Y) has 43 (1.2%) missing valuesMissing
영업장주변구분명 has 3497 (100.0%) missing valuesMissing
등급구분명 has 3497 (100.0%) missing valuesMissing
공장판매직종업원수 has 3025 (86.5%) missing valuesMissing
다중이용업소여부 has 1001 (28.6%) missing valuesMissing
시설총규모 has 1001 (28.6%) missing valuesMissing
전통업소지정번호 has 3497 (100.0%) missing valuesMissing
전통업소주된음식 has 3497 (100.0%) missing valuesMissing
홈페이지 has 3496 (> 99.9%) missing valuesMissing
공장판매직종업원수 is highly skewed (γ1 = 20.46133503)Skewed
시설총규모 is highly skewed (γ1 = 25.26613854)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
공장판매직종업원수 has 444 (12.7%) zerosZeros
시설총규모 has 2488 (71.1%) zerosZeros

Reproduction

Analysis started2024-05-11 00:47:03.584578
Analysis finished2024-05-11 00:47:07.437376
Duration3.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
3100000
3497 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 3497
100.0%

Length

2024-05-11T00:47:07.696404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:08.027435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 3497
100.0%

관리번호
Text

UNIQUE 

Distinct3497
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
2024-05-11T00:47:08.592732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters76934
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

Unique3497 ?
Unique (%)100.0%

Sample

1st row3100000-134-2004-00001
2nd row3100000-134-2004-00002
3rd row3100000-134-2004-00003
4th row3100000-134-2004-00004
5th row3100000-134-2004-00005
ValueCountFrequency (%)
3100000-134-2004-00001 1
 
< 0.1%
3100000-134-2020-00002 1
 
< 0.1%
3100000-134-2019-00168 1
 
< 0.1%
3100000-134-2019-00169 1
 
< 0.1%
3100000-134-2020-00017 1
 
< 0.1%
3100000-134-2019-00170 1
 
< 0.1%
3100000-134-2019-00171 1
 
< 0.1%
3100000-134-2019-00172 1
 
< 0.1%
3100000-134-2019-00173 1
 
< 0.1%
3100000-134-2019-00174 1
 
< 0.1%
Other values (3487) 3487
99.7%
2024-05-11T00:47:09.695695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 32035
41.6%
1 10590
 
13.8%
- 10491
 
13.6%
3 8327
 
10.8%
2 6297
 
8.2%
4 4901
 
6.4%
9 911
 
1.2%
5 907
 
1.2%
6 852
 
1.1%
7 823
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66443
86.4%
Dash Punctuation 10491
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 32035
48.2%
1 10590
 
15.9%
3 8327
 
12.5%
2 6297
 
9.5%
4 4901
 
7.4%
9 911
 
1.4%
5 907
 
1.4%
6 852
 
1.3%
7 823
 
1.2%
8 800
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 10491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76934
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 32035
41.6%
1 10590
 
13.8%
- 10491
 
13.6%
3 8327
 
10.8%
2 6297
 
8.2%
4 4901
 
6.4%
9 911
 
1.2%
5 907
 
1.2%
6 852
 
1.1%
7 823
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 32035
41.6%
1 10590
 
13.8%
- 10491
 
13.6%
3 8327
 
10.8%
2 6297
 
8.2%
4 4901
 
6.4%
9 911
 
1.2%
5 907
 
1.2%
6 852
 
1.1%
7 823
 
1.1%
Distinct2179
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
Minimum2004-03-30 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T00:47:10.155459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:47:10.640745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3497
Missing (%)100.0%
Memory size30.9 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
3
2214 
1
1283 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 2214
63.3%
1 1283
36.7%

Length

2024-05-11T00:47:11.180327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:11.540236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2214
63.3%
1 1283
36.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
폐업
2214 
영업/정상
1283 

Length

Max length5
Median length2
Mean length3.1006577
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row폐업
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 2214
63.3%
영업/정상 1283
36.7%

Length

2024-05-11T00:47:11.892796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:12.240565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2214
63.3%
영업/정상 1283
36.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
2
2214 
1
1283 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 2214
63.3%
1 1283
36.7%

Length

2024-05-11T00:47:12.613002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:12.950863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2214
63.3%
1 1283
36.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
폐업
2214 
영업
1283 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2214
63.3%
영업 1283
36.7%

Length

2024-05-11T00:47:13.449061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:13.838121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2214
63.3%
영업 1283
36.7%

폐업일자
Date

MISSING 

Distinct1519
Distinct (%)68.6%
Missing1283
Missing (%)36.7%
Memory size27.4 KiB
Minimum2004-07-27 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T00:47:14.620317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:47:15.278157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3497
Missing (%)100.0%
Memory size30.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3497
Missing (%)100.0%
Memory size30.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3497
Missing (%)100.0%
Memory size30.9 KiB

전화번호
Text

MISSING 

Distinct1019
Distinct (%)96.0%
Missing2435
Missing (%)69.6%
Memory size27.4 KiB
2024-05-11T00:47:16.156615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.175141
Min length7

Characters and Unicode

Total characters11868
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

Unique979 ?
Unique (%)92.2%

Sample

1st row02 9345990
2nd row02 986 2080
3rd row02 9501310
4th row0220910011
5th row02 9491991
ValueCountFrequency (%)
02 839
34.4%
070 84
 
3.4%
930 26
 
1.1%
932 22
 
0.9%
939 19
 
0.8%
934 17
 
0.7%
951 17
 
0.7%
931 17
 
0.7%
937 16
 
0.7%
936 14
 
0.6%
Other values (1115) 1366
56.1%
2024-05-11T00:47:17.740860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1903
16.0%
0 1893
16.0%
2 1686
14.2%
9 1290
10.9%
3 990
8.3%
7 883
7.4%
1 726
 
6.1%
5 691
 
5.8%
8 661
 
5.6%
4 611
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9965
84.0%
Space Separator 1903
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1893
19.0%
2 1686
16.9%
9 1290
12.9%
3 990
9.9%
7 883
8.9%
1 726
 
7.3%
5 691
 
6.9%
8 661
 
6.6%
4 611
 
6.1%
6 534
 
5.4%
Space Separator
ValueCountFrequency (%)
1903
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11868
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1903
16.0%
0 1893
16.0%
2 1686
14.2%
9 1290
10.9%
3 990
8.3%
7 883
7.4%
1 726
 
6.1%
5 691
 
5.8%
8 661
 
5.6%
4 611
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11868
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1903
16.0%
0 1893
16.0%
2 1686
14.2%
9 1290
10.9%
3 990
8.3%
7 883
7.4%
1 726
 
6.1%
5 691
 
5.8%
8 661
 
5.6%
4 611
 
5.1%

소재지면적
Text

MISSING 

Distinct510
Distinct (%)34.7%
Missing2027
Missing (%)58.0%
Memory size27.4 KiB
2024-05-11T00:47:19.150625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.4312925
Min length3

Characters and Unicode

Total characters6514
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

Unique383 ?
Unique (%)26.1%

Sample

1st row277.51
2nd row57.40
3rd row200.00
4th row60.00
5th row3.30
ValueCountFrequency (%)
00 312
21.2%
3.30 179
 
12.2%
0.00 42
 
2.9%
10.00 38
 
2.6%
33.00 32
 
2.2%
6.60 30
 
2.0%
3.00 17
 
1.2%
9.90 16
 
1.1%
16.50 14
 
1.0%
20.00 14
 
1.0%
Other values (500) 776
52.8%
2024-05-11T00:47:21.260214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2033
31.2%
. 1470
22.6%
3 697
 
10.7%
1 444
 
6.8%
2 378
 
5.8%
6 342
 
5.3%
9 280
 
4.3%
5 256
 
3.9%
4 240
 
3.7%
8 199
 
3.1%
Other values (2) 175
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5043
77.4%
Other Punctuation 1471
 
22.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2033
40.3%
3 697
 
13.8%
1 444
 
8.8%
2 378
 
7.5%
6 342
 
6.8%
9 280
 
5.6%
5 256
 
5.1%
4 240
 
4.8%
8 199
 
3.9%
7 174
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 1470
99.9%
, 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 6514
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2033
31.2%
. 1470
22.6%
3 697
 
10.7%
1 444
 
6.8%
2 378
 
5.8%
6 342
 
5.3%
9 280
 
4.3%
5 256
 
3.9%
4 240
 
3.7%
8 199
 
3.1%
Other values (2) 175
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6514
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2033
31.2%
. 1470
22.6%
3 697
 
10.7%
1 444
 
6.8%
2 378
 
5.8%
6 342
 
5.3%
9 280
 
4.3%
5 256
 
3.9%
4 240
 
3.7%
8 199
 
3.1%
Other values (2) 175
 
2.7%
Distinct279
Distinct (%)8.1%
Missing34
Missing (%)1.0%
Memory size27.4 KiB
2024-05-11T00:47:22.477895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1770141
Min length6

Characters and Unicode

Total characters21391
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

Unique75 ?
Unique (%)2.2%

Sample

1st row139872
2nd row139871
3rd row139942
4th row139830
5th row139861
ValueCountFrequency (%)
139200 211
 
6.1%
139240 184
 
5.3%
139837 113
 
3.3%
139816 96
 
2.8%
139800 88
 
2.5%
139838 83
 
2.4%
139-200 73
 
2.1%
139804 70
 
2.0%
139860 68
 
2.0%
139863 64
 
1.8%
Other values (269) 2413
69.7%
2024-05-11T00:47:24.081454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4234
19.8%
3 4207
19.7%
9 3946
18.4%
8 2762
12.9%
0 1751
8.2%
2 1195
 
5.6%
4 754
 
3.5%
7 701
 
3.3%
6 690
 
3.2%
- 613
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20778
97.1%
Dash Punctuation 613
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4234
20.4%
3 4207
20.2%
9 3946
19.0%
8 2762
13.3%
0 1751
8.4%
2 1195
 
5.8%
4 754
 
3.6%
7 701
 
3.4%
6 690
 
3.3%
5 538
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 613
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21391
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4234
19.8%
3 4207
19.7%
9 3946
18.4%
8 2762
12.9%
0 1751
8.2%
2 1195
 
5.6%
4 754
 
3.5%
7 701
 
3.3%
6 690
 
3.2%
- 613
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21391
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4234
19.8%
3 4207
19.7%
9 3946
18.4%
8 2762
12.9%
0 1751
8.2%
2 1195
 
5.6%
4 754
 
3.5%
7 701
 
3.3%
6 690
 
3.2%
- 613
 
2.9%
Distinct1965
Distinct (%)56.7%
Missing34
Missing (%)1.0%
Memory size27.4 KiB
2024-05-11T00:47:24.969947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length42
Mean length28.275772
Min length16

Characters and Unicode

Total characters97919
Distinct characters395
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

Unique1560 ?
Unique (%)45.0%

Sample

1st row서울특별시 노원구 하계동 ***-*번지
2nd row서울특별시 노원구 하계동 ***-*번지
3rd row서울특별시 노원구 상계동 ***-*번지
4th row서울특별시 노원구 상계동 ***-*번지 광일B/D ***호
5th row서울특별시 노원구 중계동 ***-**번지
ValueCountFrequency (%)
서울특별시 3463
18.8%
노원구 3462
18.8%
번지 1927
10.4%
1698
9.2%
상계동 1614
8.7%
845
 
4.6%
중계동 629
 
3.4%
공릉동 595
 
3.2%
월계동 395
 
2.1%
344
 
1.9%
Other values (1149) 3477
18.8%
2024-05-11T00:47:26.401300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 19733
20.2%
16996
17.4%
4029
 
4.1%
3586
 
3.7%
3536
 
3.6%
3532
 
3.6%
3488
 
3.6%
3488
 
3.6%
3477
 
3.6%
3464
 
3.5%
Other values (385) 32590
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58113
59.3%
Other Punctuation 20095
 
20.5%
Space Separator 16996
 
17.4%
Dash Punctuation 2140
 
2.2%
Decimal Number 254
 
0.3%
Uppercase Letter 126
 
0.1%
Close Punctuation 83
 
0.1%
Open Punctuation 83
 
0.1%
Lowercase Letter 27
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4029
 
6.9%
3586
 
6.2%
3536
 
6.1%
3532
 
6.1%
3488
 
6.0%
3488
 
6.0%
3477
 
6.0%
3464
 
6.0%
3463
 
6.0%
3327
 
5.7%
Other values (330) 22723
39.1%
Uppercase Letter
ValueCountFrequency (%)
B 27
21.4%
A 22
17.5%
S 19
15.1%
E 11
8.7%
C 6
 
4.8%
G 6
 
4.8%
K 5
 
4.0%
T 4
 
3.2%
J 4
 
3.2%
I 3
 
2.4%
Other values (11) 19
15.1%
Lowercase Letter
ValueCountFrequency (%)
n 10
37.0%
a 3
 
11.1%
g 2
 
7.4%
h 2
 
7.4%
i 2
 
7.4%
l 1
 
3.7%
z 1
 
3.7%
b 1
 
3.7%
y 1
 
3.7%
t 1
 
3.7%
Other values (3) 3
 
11.1%
Decimal Number
ValueCountFrequency (%)
1 42
16.5%
2 35
13.8%
3 32
12.6%
5 28
11.0%
0 27
10.6%
7 21
8.3%
4 20
7.9%
6 20
7.9%
9 17
6.7%
8 12
 
4.7%
Other Punctuation
ValueCountFrequency (%)
* 19733
98.2%
@ 223
 
1.1%
, 135
 
0.7%
? 2
 
< 0.1%
. 1
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
16996
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2140
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58113
59.3%
Common 39653
40.5%
Latin 153
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4029
 
6.9%
3586
 
6.2%
3536
 
6.1%
3532
 
6.1%
3488
 
6.0%
3488
 
6.0%
3477
 
6.0%
3464
 
6.0%
3463
 
6.0%
3327
 
5.7%
Other values (330) 22723
39.1%
Latin
ValueCountFrequency (%)
B 27
17.6%
A 22
14.4%
S 19
12.4%
E 11
 
7.2%
n 10
 
6.5%
C 6
 
3.9%
G 6
 
3.9%
K 5
 
3.3%
T 4
 
2.6%
J 4
 
2.6%
Other values (24) 39
25.5%
Common
ValueCountFrequency (%)
* 19733
49.8%
16996
42.9%
- 2140
 
5.4%
@ 223
 
0.6%
, 135
 
0.3%
) 83
 
0.2%
( 83
 
0.2%
1 42
 
0.1%
2 35
 
0.1%
3 32
 
0.1%
Other values (11) 151
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58113
59.3%
ASCII 39806
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 19733
49.6%
16996
42.7%
- 2140
 
5.4%
@ 223
 
0.6%
, 135
 
0.3%
) 83
 
0.2%
( 83
 
0.2%
1 42
 
0.1%
2 35
 
0.1%
3 32
 
0.1%
Other values (45) 304
 
0.8%
Hangul
ValueCountFrequency (%)
4029
 
6.9%
3586
 
6.2%
3536
 
6.1%
3532
 
6.1%
3488
 
6.0%
3488
 
6.0%
3477
 
6.0%
3464
 
6.0%
3463
 
6.0%
3327
 
5.7%
Other values (330) 22723
39.1%

도로명주소
Text

MISSING 

Distinct2009
Distinct (%)71.3%
Missing678
Missing (%)19.4%
Memory size27.4 KiB
2024-05-11T00:47:27.061156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length65
Mean length40.566158
Min length21

Characters and Unicode

Total characters114356
Distinct characters397
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

Unique1675 ?
Unique (%)59.4%

Sample

1st row서울특별시 노원구 공릉로**길 ** (하계동)
2nd row서울특별시 노원구 공릉로**가길 ** (하계동)
3rd row서울특별시 노원구 한글비석로 *** (중계동)
4th row서울특별시 노원구 동일로 **** (상계동)
5th row서울특별시 노원구 상계로*길 **, 사용빌딩 *층 전체호 (상계동)
ValueCountFrequency (%)
3120
14.8%
서울특별시 2819
13.4%
노원구 2818
13.4%
1894
 
9.0%
상계동 1290
 
6.1%
1026
 
4.9%
748
 
3.6%
중계동 489
 
2.3%
공릉동 474
 
2.2%
동일로***길 407
 
1.9%
Other values (1311) 5984
28.4%
2024-05-11T00:47:28.288542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 23410
20.5%
18255
16.0%
5247
 
4.6%
, 4356
 
3.8%
3404
 
3.0%
3199
 
2.8%
3171
 
2.8%
) 2879
 
2.5%
( 2878
 
2.5%
2874
 
2.5%
Other values (387) 44683
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61257
53.6%
Other Punctuation 27828
24.3%
Space Separator 18255
 
16.0%
Close Punctuation 2879
 
2.5%
Open Punctuation 2878
 
2.5%
Dash Punctuation 578
 
0.5%
Decimal Number 464
 
0.4%
Uppercase Letter 179
 
0.2%
Lowercase Letter 34
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5247
 
8.6%
3404
 
5.6%
3199
 
5.2%
3171
 
5.2%
2874
 
4.7%
2844
 
4.6%
2843
 
4.6%
2836
 
4.6%
2833
 
4.6%
2820
 
4.6%
Other values (332) 29186
47.6%
Uppercase Letter
ValueCountFrequency (%)
B 72
40.2%
A 19
 
10.6%
S 16
 
8.9%
E 12
 
6.7%
C 9
 
5.0%
T 6
 
3.4%
K 6
 
3.4%
G 6
 
3.4%
D 6
 
3.4%
H 4
 
2.2%
Other values (12) 23
 
12.8%
Lowercase Letter
ValueCountFrequency (%)
n 10
29.4%
a 4
 
11.8%
h 3
 
8.8%
b 3
 
8.8%
s 2
 
5.9%
i 2
 
5.9%
e 2
 
5.9%
g 2
 
5.9%
l 1
 
2.9%
m 1
 
2.9%
Other values (4) 4
 
11.8%
Decimal Number
ValueCountFrequency (%)
1 90
19.4%
0 81
17.5%
2 59
12.7%
4 55
11.9%
3 48
10.3%
5 34
 
7.3%
6 28
 
6.0%
7 28
 
6.0%
9 23
 
5.0%
8 18
 
3.9%
Other Punctuation
ValueCountFrequency (%)
* 23410
84.1%
, 4356
 
15.7%
@ 58
 
0.2%
. 4
 
< 0.1%
Space Separator
ValueCountFrequency (%)
18255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2879
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2878
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 578
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61257
53.6%
Common 52886
46.2%
Latin 213
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5247
 
8.6%
3404
 
5.6%
3199
 
5.2%
3171
 
5.2%
2874
 
4.7%
2844
 
4.6%
2843
 
4.6%
2836
 
4.6%
2833
 
4.6%
2820
 
4.6%
Other values (332) 29186
47.6%
Latin
ValueCountFrequency (%)
B 72
33.8%
A 19
 
8.9%
S 16
 
7.5%
E 12
 
5.6%
n 10
 
4.7%
C 9
 
4.2%
T 6
 
2.8%
K 6
 
2.8%
G 6
 
2.8%
D 6
 
2.8%
Other values (26) 51
23.9%
Common
ValueCountFrequency (%)
* 23410
44.3%
18255
34.5%
, 4356
 
8.2%
) 2879
 
5.4%
( 2878
 
5.4%
- 578
 
1.1%
1 90
 
0.2%
0 81
 
0.2%
2 59
 
0.1%
@ 58
 
0.1%
Other values (9) 242
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61257
53.6%
ASCII 53099
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 23410
44.1%
18255
34.4%
, 4356
 
8.2%
) 2879
 
5.4%
( 2878
 
5.4%
- 578
 
1.1%
1 90
 
0.2%
0 81
 
0.2%
B 72
 
0.1%
2 59
 
0.1%
Other values (45) 441
 
0.8%
Hangul
ValueCountFrequency (%)
5247
 
8.6%
3404
 
5.6%
3199
 
5.2%
3171
 
5.2%
2874
 
4.7%
2844
 
4.6%
2843
 
4.6%
2836
 
4.6%
2833
 
4.6%
2820
 
4.6%
Other values (332) 29186
47.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct290
Distinct (%)10.3%
Missing695
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1746.4165
Minimum1600
Maximum2129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2024-05-11T00:47:28.731532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1600
5-th percentile1617
Q11675
median1743
Q31827
95-th percentile1901
Maximum2129
Range529
Interquartile range (IQR)152

Descriptive statistics

Standard deviation89.617074
Coefficient of variation (CV)0.051314835
Kurtosis-1.0273731
Mean1746.4165
Median Absolute Deviation (MAD)74
Skewness0.23667388
Sum4893459
Variance8031.2199
MonotonicityNot monotonic
2024-05-11T00:47:29.320890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1695 76
 
2.2%
1684 45
 
1.3%
1634 42
 
1.2%
1783 38
 
1.1%
1662 35
 
1.0%
1604 35
 
1.0%
1913 33
 
0.9%
1849 32
 
0.9%
1693 32
 
0.9%
1751 32
 
0.9%
Other values (280) 2402
68.7%
(Missing) 695
 
19.9%
ValueCountFrequency (%)
1600 2
 
0.1%
1601 4
 
0.1%
1603 4
 
0.1%
1604 35
1.0%
1605 3
 
0.1%
1606 11
 
0.3%
1607 8
 
0.2%
1608 7
 
0.2%
1609 9
 
0.3%
1610 17
0.5%
ValueCountFrequency (%)
2129 1
 
< 0.1%
1914 19
0.5%
1913 33
0.9%
1911 9
 
0.3%
1910 3
 
0.1%
1909 20
0.6%
1907 4
 
0.1%
1906 20
0.6%
1905 6
 
0.2%
1904 6
 
0.2%
Distinct3162
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
2024-05-11T00:47:30.156895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length6.8470117
Min length2

Characters and Unicode

Total characters23944
Distinct characters783
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

Unique3015 ?
Unique (%)86.2%

Sample

1st row하계 판매점
2nd row하계성모의원
3rd row노원내과의원
4th row생그린 상계지사
5th row케어샵한양재활의학과점
ValueCountFrequency (%)
주식회사 65
 
1.4%
gs25 44
 
1.0%
다이어트 37
 
0.8%
하이리빙 35
 
0.8%
노원점 33
 
0.7%
한국암웨이 26
 
0.6%
허브 24
 
0.5%
허벌라이프 22
 
0.5%
주)하이리빙 21
 
0.5%
아모레 20
 
0.4%
Other values (3431) 4208
92.8%
2024-05-11T00:47:31.628179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1064
 
4.4%
1041
 
4.3%
588
 
2.5%
483
 
2.0%
) 482
 
2.0%
( 480
 
2.0%
468
 
2.0%
400
 
1.7%
373
 
1.6%
334
 
1.4%
Other values (773) 18231
76.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20286
84.7%
Space Separator 1041
 
4.3%
Uppercase Letter 690
 
2.9%
Lowercase Letter 576
 
2.4%
Close Punctuation 482
 
2.0%
Open Punctuation 480
 
2.0%
Decimal Number 317
 
1.3%
Other Punctuation 56
 
0.2%
Dash Punctuation 14
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1064
 
5.2%
588
 
2.9%
483
 
2.4%
468
 
2.3%
400
 
2.0%
373
 
1.8%
334
 
1.6%
331
 
1.6%
285
 
1.4%
262
 
1.3%
Other values (699) 15698
77.4%
Uppercase Letter
ValueCountFrequency (%)
S 111
16.1%
G 85
12.3%
O 40
 
5.8%
B 39
 
5.7%
E 38
 
5.5%
I 36
 
5.2%
L 35
 
5.1%
A 33
 
4.8%
N 33
 
4.8%
H 28
 
4.1%
Other values (16) 212
30.7%
Lowercase Letter
ValueCountFrequency (%)
e 73
12.7%
n 50
 
8.7%
a 48
 
8.3%
o 45
 
7.8%
i 45
 
7.8%
t 38
 
6.6%
r 37
 
6.4%
l 30
 
5.2%
s 23
 
4.0%
m 22
 
3.8%
Other values (15) 165
28.6%
Decimal Number
ValueCountFrequency (%)
2 88
27.8%
5 82
25.9%
1 34
 
10.7%
4 28
 
8.8%
0 24
 
7.6%
6 19
 
6.0%
3 15
 
4.7%
9 14
 
4.4%
7 8
 
2.5%
8 5
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 23
41.1%
& 21
37.5%
, 4
 
7.1%
? 3
 
5.4%
# 2
 
3.6%
! 2
 
3.6%
' 1
 
1.8%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
= 1
50.0%
Space Separator
ValueCountFrequency (%)
1041
100.0%
Close Punctuation
ValueCountFrequency (%)
) 482
100.0%
Open Punctuation
ValueCountFrequency (%)
( 480
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20286
84.7%
Common 2392
 
10.0%
Latin 1266
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1064
 
5.2%
588
 
2.9%
483
 
2.4%
468
 
2.3%
400
 
2.0%
373
 
1.8%
334
 
1.6%
331
 
1.6%
285
 
1.4%
262
 
1.3%
Other values (699) 15698
77.4%
Latin
ValueCountFrequency (%)
S 111
 
8.8%
G 85
 
6.7%
e 73
 
5.8%
n 50
 
3.9%
a 48
 
3.8%
o 45
 
3.6%
i 45
 
3.6%
O 40
 
3.2%
B 39
 
3.1%
E 38
 
3.0%
Other values (41) 692
54.7%
Common
ValueCountFrequency (%)
1041
43.5%
) 482
20.2%
( 480
20.1%
2 88
 
3.7%
5 82
 
3.4%
1 34
 
1.4%
4 28
 
1.2%
0 24
 
1.0%
. 23
 
1.0%
& 21
 
0.9%
Other values (13) 89
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20286
84.7%
ASCII 3658
 
15.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1064
 
5.2%
588
 
2.9%
483
 
2.4%
468
 
2.3%
400
 
2.0%
373
 
1.8%
334
 
1.6%
331
 
1.6%
285
 
1.4%
262
 
1.3%
Other values (699) 15698
77.4%
ASCII
ValueCountFrequency (%)
1041
28.5%
) 482
13.2%
( 480
13.1%
S 111
 
3.0%
2 88
 
2.4%
G 85
 
2.3%
5 82
 
2.2%
e 73
 
2.0%
n 50
 
1.4%
a 48
 
1.3%
Other values (64) 1118
30.6%
Distinct3291
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
Minimum2004-03-30 00:00:00
Maximum2024-05-09 14:29:05
2024-05-11T00:47:32.141653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:47:32.658120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
I
2317 
U
1180 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2317
66.3%
U 1180
33.7%

Length

2024-05-11T00:47:33.286770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:33.733563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2317
66.3%
u 1180
33.7%
Distinct1011
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T00:47:34.476282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:47:35.098823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3497
Missing (%)100.0%
Memory size30.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1260
Distinct (%)36.5%
Missing43
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean205905.67
Minimum203719.16
Maximum209361.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2024-05-11T00:47:35.825038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203719.16
5-th percentile204619.14
Q1205296.39
median205934.91
Q3206532.25
95-th percentile207207.92
Maximum209361.21
Range5642.0455
Interquartile range (IQR)1235.8578

Descriptive statistics

Standard deviation816.88021
Coefficient of variation (CV)0.0039672546
Kurtosis-0.47417166
Mean205905.67
Median Absolute Deviation (MAD)624.71111
Skewness0.089038023
Sum7.1119818 × 108
Variance667293.28
MonotonicityNot monotonic
2024-05-11T00:47:36.314282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205320.28476675 50
 
1.4%
205984.15211292 40
 
1.1%
204670.573678123 38
 
1.1%
205994.811815848 36
 
1.0%
204855.557180678 36
 
1.0%
204846.017230075 31
 
0.9%
205601.066015629 25
 
0.7%
206356.052509483 24
 
0.7%
205264.637477558 24
 
0.7%
205227.342971697 24
 
0.7%
Other values (1250) 3126
89.4%
(Missing) 43
 
1.2%
ValueCountFrequency (%)
203719.161728968 3
0.1%
203762.973030298 1
 
< 0.1%
203786.584663472 1
 
< 0.1%
203811.52282877 2
 
0.1%
203839.989956111 3
0.1%
203850.736659357 2
 
0.1%
203904.660962669 1
 
< 0.1%
203920.549325193 6
0.2%
203951.168595124 1
 
< 0.1%
203982.774049825 2
 
0.1%
ValueCountFrequency (%)
209361.207272368 1
 
< 0.1%
209288.472624641 1
 
< 0.1%
209234.634090964 1
 
< 0.1%
209221.923150049 1
 
< 0.1%
208078.24388168 1
 
< 0.1%
208029.693383403 1
 
< 0.1%
208014.393680914 4
0.1%
207979.147006636 2
0.1%
207918.320414714 1
 
< 0.1%
207890.554378503 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1260
Distinct (%)36.5%
Missing43
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean460601.73
Minimum454312.59
Maximum465103.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2024-05-11T00:47:36.829798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum454312.59
5-th percentile457427.4
Q1458563.41
median460965.51
Q3462133.69
95-th percentile463663.2
Maximum465103.76
Range10791.163
Interquartile range (IQR)3570.2797

Descriptive statistics

Standard deviation2009.9943
Coefficient of variation (CV)0.0043638445
Kurtosis-1.1215401
Mean460601.73
Median Absolute Deviation (MAD)1599.5491
Skewness-0.11749378
Sum1.5909184 × 109
Variance4040077.2
MonotonicityNot monotonic
2024-05-11T00:47:37.418126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461419.881795004 50
 
1.4%
457275.799282625 40
 
1.1%
462933.316362013 38
 
1.1%
459502.645279682 36
 
1.0%
464199.048415229 36
 
1.0%
462293.140879558 31
 
0.9%
459233.675551946 25
 
0.7%
463287.58273428 24
 
0.7%
462298.014627148 24
 
0.7%
461827.579520796 24
 
0.7%
Other values (1250) 3126
89.4%
(Missing) 43
 
1.2%
ValueCountFrequency (%)
454312.592613837 1
 
< 0.1%
456930.30571679 3
0.1%
456954.147370611 5
0.1%
456962.107796844 1
 
< 0.1%
456994.517426262 2
 
0.1%
456996.048176249 1
 
< 0.1%
457008.271220657 1
 
< 0.1%
457025.976372498 1
 
< 0.1%
457027.279189504 1
 
< 0.1%
457030.063028682 1
 
< 0.1%
ValueCountFrequency (%)
465103.755134816 2
 
0.1%
464964.284423079 1
 
< 0.1%
464922.213107238 1
 
< 0.1%
464849.968985063 2
 
0.1%
464636.126839194 1
 
< 0.1%
464508.952781941 7
 
0.2%
464356.527197506 4
 
0.1%
464346.663669239 4
 
0.1%
464208.305428933 11
 
0.3%
464199.048415229 36
1.0%

위생업태명
Categorical

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
영업장판매
1109 
<NA>
1001 
전자상거래(통신판매업)
696 
방문판매
261 
통신판매
203 
Other values (6)
227 

Length

Max length14
Median length12
Mean length6.0134401
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업장판매 1109
31.7%
<NA> 1001
28.6%
전자상거래(통신판매업) 696
19.9%
방문판매 261
 
7.5%
통신판매 203
 
5.8%
다단계판매 188
 
5.4%
도매업(유통) 21
 
0.6%
기타 건강기능식품일반판매업 9
 
0.3%
전화권유판매 6
 
0.2%
기타(복합 등) 2
 
0.1%

Length

2024-05-11T00:47:38.069125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영업장판매 1109
31.6%
na 1001
28.5%
전자상거래(통신판매업 696
19.8%
방문판매 261
 
7.4%
통신판매 203
 
5.8%
다단계판매 188
 
5.4%
도매업(유통 21
 
0.6%
기타 9
 
0.3%
건강기능식품일반판매업 9
 
0.3%
전화권유판매 6
 
0.2%
Other values (3) 5
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
3219 
0
 
278

Length

Max length4
Median length4
Mean length3.7615099
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> 3219
92.1%
0 278
 
7.9%

Length

2024-05-11T00:47:38.599083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:39.215445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3219
92.1%
0 278
 
7.9%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
3219 
0
 
278

Length

Max length4
Median length4
Mean length3.7615099
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> 3219
92.1%
0 278
 
7.9%

Length

2024-05-11T00:47:40.007521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:40.492368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3219
92.1%
0 278
 
7.9%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3497
Missing (%)100.0%
Memory size30.9 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3497
Missing (%)100.0%
Memory size30.9 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
3471 
상수도전용
 
26

Length

Max length5
Median length4
Mean length4.0074349
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> 3471
99.3%
상수도전용 26
 
0.7%

Length

2024-05-11T00:47:41.120744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:41.820363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3471
99.3%
상수도전용 26
 
0.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
3219 
0
 
278

Length

Max length4
Median length4
Mean length3.7615099
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> 3219
92.1%
0 278
 
7.9%

Length

2024-05-11T00:47:42.288374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:42.627218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3219
92.1%
0 278
 
7.9%

본사종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
3048 
0
448 
1
 
1

Length

Max length4
Median length4
Mean length3.6148127
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3048
87.2%
0 448
 
12.8%
1 1
 
< 0.1%

Length

2024-05-11T00:47:42.965974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:43.298540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3048
87.2%
0 448
 
12.8%
1 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
3040 
0
446 
1
 
7
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.6079497
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3040
86.9%
0 446
 
12.8%
1 7
 
0.2%
2 3
 
0.1%
3 1
 
< 0.1%

Length

2024-05-11T00:47:43.782770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:44.318944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3040
86.9%
0 446
 
12.8%
1 7
 
0.2%
2 3
 
0.1%
3 1
 
< 0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct6
Distinct (%)1.3%
Missing3025
Missing (%)86.5%
Infinite0
Infinite (%)0.0%
Mean0.20338983
Minimum0
Maximum50
Zeros444
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2024-05-11T00:47:44.775789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum50
Range50
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.3451964
Coefficient of variation (CV)11.530549
Kurtosis434.18063
Mean0.20338983
Median Absolute Deviation (MAD)0
Skewness20.461335
Sum96
Variance5.499946
MonotonicityNot monotonic
2024-05-11T00:47:45.195708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 444
 
12.7%
1 15
 
0.4%
2 9
 
0.3%
5 2
 
0.1%
3 1
 
< 0.1%
50 1
 
< 0.1%
(Missing) 3025
86.5%
ValueCountFrequency (%)
0 444
12.7%
1 15
 
0.4%
2 9
 
0.3%
3 1
 
< 0.1%
5 2
 
0.1%
50 1
 
< 0.1%
ValueCountFrequency (%)
50 1
 
< 0.1%
5 2
 
0.1%
3 1
 
< 0.1%
2 9
 
0.3%
1 15
 
0.4%
0 444
12.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
3049 
0
447 
1
 
1

Length

Max length4
Median length4
Mean length3.6156706
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3049
87.2%
0 447
 
12.8%
1 1
 
< 0.1%

Length

2024-05-11T00:47:45.665641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:46.080306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3049
87.2%
0 447
 
12.8%
1 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
2393 
자가
771 
임대
333 

Length

Max length4
Median length4
Mean length3.3686017
Min length2

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> 2393
68.4%
자가 771
 
22.0%
임대 333
 
9.5%

Length

2024-05-11T00:47:46.883525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:47.217052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2393
68.4%
자가 771
 
22.0%
임대 333
 
9.5%

보증액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
3217 
0
 
278
10000000
 
1
1000000
 
1

Length

Max length8
Median length4
Mean length3.7635116
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3217
92.0%
0 278
 
7.9%
10000000 1
 
< 0.1%
1000000 1
 
< 0.1%

Length

2024-05-11T00:47:47.563402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:47.995133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3217
92.0%
0 278
 
7.9%
10000000 1
 
< 0.1%
1000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.4 KiB
<NA>
3218 
0
 
278
1100000
 
1

Length

Max length7
Median length4
Mean length3.7623677
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3218
92.0%
0 278
 
7.9%
1100000 1
 
< 0.1%

Length

2024-05-11T00:47:48.438708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:47:48.784916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3218
92.0%
0 278
 
7.9%
1100000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1001
Missing (%)28.6%
Memory size7.0 KiB
False
2496 
(Missing)
1001 
ValueCountFrequency (%)
False 2496
71.4%
(Missing) 1001
28.6%
2024-05-11T00:47:49.120896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.4%
Missing1001
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean0.23350962
Minimum0
Maximum163
Zeros2488
Zeros (%)71.1%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2024-05-11T00:47:49.389610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum163
Range163
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.4081892
Coefficient of variation (CV)23.160456
Kurtosis666.3145
Mean0.23350962
Median Absolute Deviation (MAD)0
Skewness25.266139
Sum582.84
Variance29.24851
MonotonicityNot monotonic
2024-05-11T00:47:49.941619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 2488
71.1%
6.0 1
 
< 0.1%
1.0 1
 
< 0.1%
3.3 1
 
< 0.1%
128.0 1
 
< 0.1%
80.03 1
 
< 0.1%
163.0 1
 
< 0.1%
142.0 1
 
< 0.1%
59.51 1
 
< 0.1%
(Missing) 1001
28.6%
ValueCountFrequency (%)
0.0 2488
71.1%
1.0 1
 
< 0.1%
3.3 1
 
< 0.1%
6.0 1
 
< 0.1%
59.51 1
 
< 0.1%
80.03 1
 
< 0.1%
128.0 1
 
< 0.1%
142.0 1
 
< 0.1%
163.0 1
 
< 0.1%
ValueCountFrequency (%)
163.0 1
 
< 0.1%
142.0 1
 
< 0.1%
128.0 1
 
< 0.1%
80.03 1
 
< 0.1%
59.51 1
 
< 0.1%
6.0 1
 
< 0.1%
3.3 1
 
< 0.1%
1.0 1
 
< 0.1%
0.0 2488
71.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3497
Missing (%)100.0%
Memory size30.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3497
Missing (%)100.0%
Memory size30.9 KiB

홈페이지
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3496
Missing (%)> 99.9%
Memory size27.4 KiB
2024-05-11T00:47:50.436704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowwww.dietld.com
ValueCountFrequency (%)
www.dietld.com 1
100.0%
2024-05-11T00:47:51.326544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 3
21.4%
. 2
14.3%
d 2
14.3%
i 1
 
7.1%
e 1
 
7.1%
t 1
 
7.1%
l 1
 
7.1%
c 1
 
7.1%
o 1
 
7.1%
m 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12
85.7%
Other Punctuation 2
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 3
25.0%
d 2
16.7%
i 1
 
8.3%
e 1
 
8.3%
t 1
 
8.3%
l 1
 
8.3%
c 1
 
8.3%
o 1
 
8.3%
m 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
85.7%
Common 2
 
14.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 3
25.0%
d 2
16.7%
i 1
 
8.3%
e 1
 
8.3%
t 1
 
8.3%
l 1
 
8.3%
c 1
 
8.3%
o 1
 
8.3%
m 1
 
8.3%
Common
ValueCountFrequency (%)
. 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 3
21.4%
. 2
14.3%
d 2
14.3%
i 1
 
7.1%
e 1
 
7.1%
t 1
 
7.1%
l 1
 
7.1%
c 1
 
7.1%
o 1
 
7.1%
m 1
 
7.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-134-2004-0000120040330<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139872서울특별시 노원구 하계동 ***-*번지서울특별시 노원구 공릉로**길 ** (하계동)1830하계 판매점2004-03-30 00:00:00I2018-08-31 23:59:59.0<NA>206156.733065459169.464921영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131000003100000-134-2004-0000220040420<NA>3폐업2폐업20190530<NA><NA><NA><NA><NA>139871서울특별시 노원구 하계동 ***-*번지서울특별시 노원구 공릉로**가길 ** (하계동)1809하계성모의원2019-05-30 10:44:58U2019-06-01 02:40:00.0<NA>206357.322437459324.819871영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231000003100000-134-2004-0000320040430<NA>3폐업2폐업20120821<NA><NA><NA><NA><NA>139942서울특별시 노원구 상계동 ***-*번지<NA><NA>노원내과의원2004-04-30 00:00:00I2018-08-31 23:59:59.0<NA>205255.038443461244.575306영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331000003100000-134-2004-0000420040503<NA>3폐업2폐업20090601<NA><NA><NA><NA><NA>139830서울특별시 노원구 상계동 ***-*번지 광일B/D ***호<NA><NA>생그린 상계지사2004-05-03 00:00:00I2018-08-31 23:59:59.0<NA>205193.005088461226.819159방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431000003100000-134-2004-0000520040504<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139861서울특별시 노원구 중계동 ***-**번지서울특별시 노원구 한글비석로 *** (중계동)1734케어샵한양재활의학과점2004-05-04 00:00:00I2018-08-31 23:59:59.0<NA>206726.35691460848.731778영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531000003100000-134-2004-0000620040514<NA>3폐업2폐업20090731<NA><NA><NA><NA><NA>139865서울특별시 노원구 중계동 ***번지<NA><NA>(주)한바람2004-05-14 00:00:00I2018-08-31 23:59:59.0<NA>205931.05327459884.197208영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631000003100000-134-2004-0000720040515<NA>3폐업2폐업20060111<NA><NA><NA><NA><NA>139240서울특별시 노원구 공릉동 ***-**번지<NA><NA>아모레 노원(특)2004-05-15 00:00:00I2018-08-31 23:59:59.0<NA>206388.862349457966.641016방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731000003100000-134-2004-000082004-05-15<NA>3폐업2폐업2023-03-28<NA><NA><NA>02 9345990<NA>139-831서울특별시 노원구 상계동 ***-*서울특별시 노원구 동일로 **** (상계동)1767아모레퍼시픽 중계특약점2023-03-28 10:11:57U2022-12-02 21:00:00.0<NA>205400.870654460681.679133<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
831000003100000-134-2004-0000920040519<NA>1영업/정상1영업<NA><NA><NA><NA><NA>277.51139818서울특별시 노원구 상계동 ***-* 사용빌딩서울특별시 노원구 상계로*길 **, 사용빌딩 *층 전체호 (상계동)1685아모레 상계특약점2021-12-23 10:40:27U2021-12-25 02:40:00.0<NA>205764.669442461769.075044방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931000003100000-134-2004-0001020040519<NA>3폐업2폐업20070122<NA><NA><NA><NA><NA>139831서울특별시 노원구 상계동 ***-*번지<NA><NA>코리아나 중계영업소2007-05-11 00:00:00I2018-08-31 23:59:59.0<NA>205391.41389460703.536575방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
348731000003100000-134-2024-000642024-04-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-942서울특별시 노원구 상계동 ***-* 상계주공*단지아파트 *단지상가동 ***호서울특별시 노원구 동일로 ****, *단지상가동 ***호 (상계동, 상계주공*단지아파트)1762북서울건강생활2024-04-16 13:34:59I2023-12-03 23:08:00.0<NA>205280.620693461113.539047<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
348831000003100000-134-2024-000652024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA>02 935 1357<NA>139-831서울특별시 노원구 상계동 ***-* 랑은빌딩서울특별시 노원구 동일로 ****, 랑은빌딩 *층 (상계동)1763다비치안경2024-04-19 10:03:58I2023-12-03 22:01:00.0<NA>205332.845625460914.857563<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
348931000003100000-134-2024-000662024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-815서울특별시 노원구 상계동 ***-***서울특별시 노원구 상계로**길 **, 지층 (상계동)1682아임슬리핑몰2024-04-23 13:57:49I2023-12-03 22:05:00.0<NA>206095.984425461955.875257<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
349031000003100000-134-2024-000672024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>729.00139-832서울특별시 노원구 상계동 ***-*서울특별시 노원구 동일로 ****, *,*층 (상계동)1751365mc2024-04-25 15:52:02I2023-12-03 22:07:00.0<NA>205346.193804461188.389276<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
349131000003100000-134-2024-000682024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-895서울특별시 노원구 상계동 **** 상계*차중앙하이츠아파트서울특별시 노원구 노원로 ***, 상계*차중앙하이츠아파트 지층 B***~B***호 (상계동)17033H지압침대 노원센터2024-04-26 16:25:19I2023-12-03 22:08:00.0<NA>205958.283359461400.10882<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
349231000003100000-134-2024-000692024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-957서울특별시 노원구 월계동 *** 현대아파트 ***동 ****호서울특별시 노원구 석계로 **, ***동 ****호 (월계동, 현대아파트)1901테이크잇미상점2024-05-02 16:02:16U2023-12-05 00:04:00.0<NA>205455.618699457358.731978<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
349331000003100000-134-2024-000702024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA>02 936 212220.00139-816서울특별시 노원구 상계동 ***-** 메디아이산부인과서울특별시 노원구 노원로 ***, 메디아이산부인과 *층 (상계동)1696메디아이2024-05-02 13:45:05I2023-12-05 00:04:00.0<NA>205845.013423461572.838655<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
349431000003100000-134-2024-000712024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-705서울특별시 노원구 상계동 **** 청솔상계양우아파트 ***동 ***호서울특별시 노원구 노원로**길 **, ***동 ***호 (상계동, 청솔상계양우아파트)1702코프2024-05-07 09:20:47I2023-12-05 00:09:00.0<NA>206214.174557461485.285072<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
349531000003100000-134-2024-000722024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-814서울특별시 노원구 상계동 ***-*** 신생하이빌 ***호서울특별시 노원구 한글비석로**길 **, ***호 (상계동, 신생하이빌)1659감상마트2024-05-07 13:22:43I2023-12-05 00:09:00.0<NA>206318.784461462404.286581<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
349631000003100000-134-2024-000732024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-741서울특별시 노원구 상계동 **** 극동아파트서울특별시 노원구 동일로***길 **, ***동 ****호 (상계동, 극동아파트)1626비타팜2024-05-09 14:16:32I2023-12-04 23:01:00.0<NA>204982.667824463884.895276<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>