Overview

Dataset statistics

Number of variables44
Number of observations2969
Missing cells39285
Missing cells (%)30.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory379.0 B

Variable types

Categorical17
Text6
DateTime4
Unsupported10
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-18083/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (65.0%)Imbalance
여성종사자수 is highly imbalanced (65.0%)Imbalance
급수시설구분명 is highly imbalanced (92.1%)Imbalance
총인원 is highly imbalanced (65.2%)Imbalance
본사종업원수 is highly imbalanced (66.5%)Imbalance
공장사무직종업원수 is highly imbalanced (73.3%)Imbalance
공장생산직종업원수 is highly imbalanced (66.5%)Imbalance
보증액 is highly imbalanced (73.9%)Imbalance
월세액 is highly imbalanced (73.9%)Imbalance
인허가취소일자 has 2969 (100.0%) missing valuesMissing
폐업일자 has 854 (28.8%) missing valuesMissing
휴업시작일자 has 2969 (100.0%) missing valuesMissing
휴업종료일자 has 2969 (100.0%) missing valuesMissing
재개업일자 has 2969 (100.0%) missing valuesMissing
전화번호 has 1790 (60.3%) missing valuesMissing
소재지면적 has 1624 (54.7%) missing valuesMissing
도로명주소 has 432 (14.6%) missing valuesMissing
도로명우편번호 has 462 (15.6%) missing valuesMissing
업태구분명 has 2969 (100.0%) missing valuesMissing
영업장주변구분명 has 2969 (100.0%) missing valuesMissing
등급구분명 has 2969 (100.0%) missing valuesMissing
공장판매직종업원수 has 2609 (87.9%) missing valuesMissing
다중이용업소여부 has 884 (29.8%) missing valuesMissing
시설총규모 has 884 (29.8%) missing valuesMissing
전통업소지정번호 has 2969 (100.0%) missing valuesMissing
전통업소주된음식 has 2969 (100.0%) missing valuesMissing
홈페이지 has 2969 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 26.88683194)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
소재지면적 has 263 (8.9%) zerosZeros
공장판매직종업원수 has 332 (11.2%) zerosZeros
시설총규모 has 1943 (65.4%) zerosZeros

Reproduction

Analysis started2024-05-11 07:48:27.193908
Analysis finished2024-05-11 07:48:31.599180
Duration4.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
3060000
2969 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 2969
100.0%

Length

2024-05-11T07:48:31.916256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:32.276587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 2969
100.0%

관리번호
Text

UNIQUE 

Distinct2969
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
2024-05-11T07:48:32.899233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters65318
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

Unique2969 ?
Unique (%)100.0%

Sample

1st row3060000-134-2004-00001
2nd row3060000-134-2004-00003
3rd row3060000-134-2004-00004
4th row3060000-134-2004-00005
5th row3060000-134-2004-00006
ValueCountFrequency (%)
3060000-134-2004-00001 1
 
< 0.1%
3060000-134-2020-00032 1
 
< 0.1%
3060000-134-2020-00023 1
 
< 0.1%
3060000-134-2020-00044 1
 
< 0.1%
3060000-134-2020-00024 1
 
< 0.1%
3060000-134-2020-00025 1
 
< 0.1%
3060000-134-2020-00027 1
 
< 0.1%
3060000-134-2020-00028 1
 
< 0.1%
3060000-134-2020-00029 1
 
< 0.1%
3060000-134-2020-00030 1
 
< 0.1%
Other values (2959) 2959
99.7%
2024-05-11T07:48:34.171644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27453
42.0%
- 8907
 
13.6%
3 6943
 
10.6%
1 5998
 
9.2%
2 5327
 
8.2%
4 4037
 
6.2%
6 3689
 
5.6%
5 791
 
1.2%
9 759
 
1.2%
7 742
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56411
86.4%
Dash Punctuation 8907
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27453
48.7%
3 6943
 
12.3%
1 5998
 
10.6%
2 5327
 
9.4%
4 4037
 
7.2%
6 3689
 
6.5%
5 791
 
1.4%
9 759
 
1.3%
7 742
 
1.3%
8 672
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 8907
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27453
42.0%
- 8907
 
13.6%
3 6943
 
10.6%
1 5998
 
9.2%
2 5327
 
8.2%
4 4037
 
6.2%
6 3689
 
5.6%
5 791
 
1.2%
9 759
 
1.2%
7 742
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27453
42.0%
- 8907
 
13.6%
3 6943
 
10.6%
1 5998
 
9.2%
2 5327
 
8.2%
4 4037
 
6.2%
6 3689
 
5.6%
5 791
 
1.2%
9 759
 
1.2%
7 742
 
1.1%

인허가일자
Date

Distinct1981
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
Minimum2004-04-06 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T07:48:34.824101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:48:35.352426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
3
2115 
1
854 

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 2115
71.2%
1 854
28.8%

Length

2024-05-11T07:48:35.920127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:36.269392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2115
71.2%
1 854
28.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
폐업
2115 
영업/정상
854 

Length

Max length5
Median length2
Mean length2.8629168
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2115
71.2%
영업/정상 854
28.8%

Length

2024-05-11T07:48:36.707929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:37.082645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2115
71.2%
영업/정상 854
28.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
2
2115 
1
854 

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 2115
71.2%
1 854
28.8%

Length

2024-05-11T07:48:37.614350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:37.993899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2115
71.2%
1 854
28.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
폐업
2115 
영업
854 

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 2115
71.2%
영업 854
28.8%

Length

2024-05-11T07:48:38.427391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:38.793392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2115
71.2%
영업 854
28.8%

폐업일자
Date

MISSING 

Distinct1353
Distinct (%)64.0%
Missing854
Missing (%)28.8%
Memory size23.3 KiB
Minimum2004-05-10 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T07:48:39.292518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:48:39.782333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

전화번호
Text

MISSING 

Distinct1129
Distinct (%)95.8%
Missing1790
Missing (%)60.3%
Memory size23.3 KiB
2024-05-11T07:48:40.846204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.877863
Min length7

Characters and Unicode

Total characters12825
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

Unique1089 ?
Unique (%)92.4%

Sample

1st row02 4360066
2nd row0222079000
3rd row02 4928801
4th row0222094675
5th row02 4943111
ValueCountFrequency (%)
02 853
34.8%
070 71
 
2.9%
432 27
 
1.1%
434 26
 
1.1%
433 21
 
0.9%
492 18
 
0.7%
438 18
 
0.7%
491 18
 
0.7%
435 16
 
0.7%
437 15
 
0.6%
Other values (1208) 1369
55.8%
2024-05-11T07:48:42.319898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2097
16.4%
0 2027
15.8%
1756
13.7%
4 1303
10.2%
3 1089
8.5%
9 923
7.2%
7 869
6.8%
8 744
 
5.8%
1 710
 
5.5%
5 677
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11069
86.3%
Space Separator 1756
 
13.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2097
18.9%
0 2027
18.3%
4 1303
11.8%
3 1089
9.8%
9 923
8.3%
7 869
7.9%
8 744
 
6.7%
1 710
 
6.4%
5 677
 
6.1%
6 630
 
5.7%
Space Separator
ValueCountFrequency (%)
1756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12825
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2097
16.4%
0 2027
15.8%
1756
13.7%
4 1303
10.2%
3 1089
8.5%
9 923
7.2%
7 869
6.8%
8 744
 
5.8%
1 710
 
5.5%
5 677
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2097
16.4%
0 2027
15.8%
1756
13.7%
4 1303
10.2%
3 1089
8.5%
9 923
7.2%
7 869
6.8%
8 744
 
5.8%
1 710
 
5.5%
5 677
 
5.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct384
Distinct (%)28.6%
Missing1624
Missing (%)54.7%
Infinite0
Infinite (%)0.0%
Mean41.227799
Minimum0
Maximum990
Zeros263
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size26.2 KiB
2024-05-11T07:48:42.951040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median13.2
Q342
95-th percentile164
Maximum990
Range990
Interquartile range (IQR)39

Descriptive statistics

Standard deviation79.763948
Coefficient of variation (CV)1.9347127
Kurtosis40.653048
Mean41.227799
Median Absolute Deviation (MAD)13.2
Skewness5.1295245
Sum55451.39
Variance6362.2874
MonotonicityNot monotonic
2024-05-11T07:48:43.482109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 263
 
8.9%
3.3 109
 
3.7%
3.0 88
 
3.0%
10.0 58
 
2.0%
33.0 51
 
1.7%
6.6 36
 
1.2%
5.0 20
 
0.7%
26.4 20
 
0.7%
16.5 18
 
0.6%
19.8 17
 
0.6%
Other values (374) 665
22.4%
(Missing) 1624
54.7%
ValueCountFrequency (%)
0.0 263
8.9%
0.5 7
 
0.2%
1.0 3
 
0.1%
1.3 1
 
< 0.1%
1.65 2
 
0.1%
1.92 1
 
< 0.1%
2.0 9
 
0.3%
2.19 1
 
< 0.1%
2.3 1
 
< 0.1%
3.0 88
 
3.0%
ValueCountFrequency (%)
990.0 1
< 0.1%
987.0 1
< 0.1%
660.0 1
< 0.1%
628.14 1
< 0.1%
585.0 1
< 0.1%
495.0 2
0.1%
479.28 1
< 0.1%
475.0 1
< 0.1%
460.25 1
< 0.1%
450.0 1
< 0.1%

소재지우편번호
Text

Distinct208
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
2024-05-11T07:48:44.577579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1882789
Min length6

Characters and Unicode

Total characters18373
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

Unique32 ?
Unique (%)1.1%

Sample

1st row131875
2nd row131875
3rd row131875
4th row131867
5th row131829
ValueCountFrequency (%)
131848 89
 
3.0%
131865 71
 
2.4%
131881 71
 
2.4%
131816 70
 
2.4%
131859 60
 
2.0%
131802 59
 
2.0%
131809 58
 
2.0%
131817 58
 
2.0%
131813 57
 
1.9%
131810 57
 
1.9%
Other values (198) 2319
78.1%
2024-05-11T07:48:46.224256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6787
36.9%
3 3400
18.5%
8 3310
18.0%
2 895
 
4.9%
7 735
 
4.0%
0 704
 
3.8%
6 681
 
3.7%
5 650
 
3.5%
- 559
 
3.0%
4 338
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17814
97.0%
Dash Punctuation 559
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6787
38.1%
3 3400
19.1%
8 3310
18.6%
2 895
 
5.0%
7 735
 
4.1%
0 704
 
4.0%
6 681
 
3.8%
5 650
 
3.6%
4 338
 
1.9%
9 314
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 559
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18373
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6787
36.9%
3 3400
18.5%
8 3310
18.0%
2 895
 
4.9%
7 735
 
4.0%
0 704
 
3.8%
6 681
 
3.7%
5 650
 
3.5%
- 559
 
3.0%
4 338
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6787
36.9%
3 3400
18.5%
8 3310
18.0%
2 895
 
4.9%
7 735
 
4.0%
0 704
 
3.8%
6 681
 
3.7%
5 650
 
3.5%
- 559
 
3.0%
4 338
 
1.8%

지번주소
Text

Distinct1169
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
2024-05-11T07:48:47.003267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length24.749411
Min length15

Characters and Unicode

Total characters73481
Distinct characters406
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique914 ?
Unique (%)30.8%

Sample

1st row서울특별시 중랑구 중화동 ***-**번지
2nd row서울특별시 중랑구 중화동 ***-**번지
3rd row서울특별시 중랑구 중화동 ***-**번지
4th row서울특별시 중랑구 신내동 ***-**번지
5th row서울특별시 중랑구 면목동 ***-*번지
ValueCountFrequency (%)
서울특별시 2969
21.2%
중랑구 2968
21.2%
번지 1693
12.1%
1226
8.7%
면목동 1018
 
7.3%
묵동 412
 
2.9%
상봉동 392
 
2.8%
신내동 386
 
2.8%
중화동 382
 
2.7%
망우동 381
 
2.7%
Other values (782) 2194
15.6%
2024-05-11T07:48:48.345999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 14526
19.8%
12889
17.5%
중 3392
 
4.6%
동 3245
 
4.4%
시 3028
 
4.1%
랑 2997
 
4.1%
울 2990
 
4.1%
서 2983
 
4.1%
구 2972
 
4.0%
별 2970
 
4.0%
Other values (396) 21489
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43037
58.6%
Other Punctuation 14553
 
19.8%
Space Separator 12889
 
17.5%
Dash Punctuation 2331
 
3.2%
Decimal Number 274
 
0.4%
Uppercase Letter 233
 
0.3%
Open Punctuation 71
 
0.1%
Close Punctuation 71
 
0.1%
Lowercase Letter 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 3392
 
7.9%
동 3245
 
7.5%
시 3028
 
7.0%
랑 2997
 
7.0%
울 2990
 
6.9%
서 2983
 
6.9%
구 2972
 
6.9%
별 2970
 
6.9%
특 2969
 
6.9%
지 1841
 
4.3%
Other values (345) 13650
31.7%
Uppercase Letter
ValueCountFrequency (%)
T 27
11.6%
G 26
11.2%
S 25
10.7%
E 24
10.3%
B 22
9.4%
W 21
9.0%
O 21
9.0%
R 21
9.0%
A 12
5.2%
L 7
 
3.0%
Other values (10) 27
11.6%
Lowercase Letter
ValueCountFrequency (%)
e 6
27.3%
h 3
13.6%
t 2
 
9.1%
n 2
 
9.1%
s 1
 
4.5%
y 1
 
4.5%
l 1
 
4.5%
i 1
 
4.5%
a 1
 
4.5%
c 1
 
4.5%
Other values (3) 3
13.6%
Decimal Number
ValueCountFrequency (%)
1 55
20.1%
2 45
16.4%
3 31
11.3%
4 28
10.2%
0 26
9.5%
6 23
8.4%
8 19
 
6.9%
7 17
 
6.2%
9 16
 
5.8%
5 14
 
5.1%
Other Punctuation
ValueCountFrequency (%)
* 14526
99.8%
@ 16
 
0.1%
, 7
 
< 0.1%
. 4
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12889
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2331
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43036
58.6%
Common 30189
41.1%
Latin 255
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 3392
 
7.9%
동 3245
 
7.5%
시 3028
 
7.0%
랑 2997
 
7.0%
울 2990
 
6.9%
서 2983
 
6.9%
구 2972
 
6.9%
별 2970
 
6.9%
특 2969
 
6.9%
지 1841
 
4.3%
Other values (344) 13649
31.7%
Latin
ValueCountFrequency (%)
T 27
10.6%
G 26
10.2%
S 25
9.8%
E 24
9.4%
B 22
8.6%
W 21
8.2%
O 21
8.2%
R 21
8.2%
A 12
 
4.7%
L 7
 
2.7%
Other values (23) 49
19.2%
Common
ValueCountFrequency (%)
* 14526
48.1%
12889
42.7%
- 2331
 
7.7%
( 71
 
0.2%
) 71
 
0.2%
1 55
 
0.2%
2 45
 
0.1%
3 31
 
0.1%
4 28
 
0.1%
0 26
 
0.1%
Other values (8) 116
 
0.4%
Han
ValueCountFrequency (%)
休 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43036
58.6%
ASCII 30444
41.4%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 14526
47.7%
12889
42.3%
- 2331
 
7.7%
( 71
 
0.2%
) 71
 
0.2%
1 55
 
0.2%
2 45
 
0.1%
3 31
 
0.1%
4 28
 
0.1%
T 27
 
0.1%
Other values (41) 370
 
1.2%
Hangul
ValueCountFrequency (%)
중 3392
 
7.9%
동 3245
 
7.5%
시 3028
 
7.0%
랑 2997
 
7.0%
울 2990
 
6.9%
서 2983
 
6.9%
구 2972
 
6.9%
별 2970
 
6.9%
특 2969
 
6.9%
지 1841
 
4.3%
Other values (344) 13649
31.7%
CJK
ValueCountFrequency (%)
休 1
100.0%

도로명주소
Text

MISSING 

Distinct1736
Distinct (%)68.4%
Missing432
Missing (%)14.6%
Memory size23.3 KiB
2024-05-11T07:48:49.244416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length53
Mean length34.207331
Min length21

Characters and Unicode

Total characters86784
Distinct characters422
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

Unique1424 ?
Unique (%)56.1%

Sample

1st row서울특별시 중랑구 동일로***길 **-* (중화동)
2nd row서울특별시 중랑구 동일로***길 ** (중화동)
3rd row서울특별시 중랑구 겸재로 *** (면목동)
4th row서울특별시 중랑구 봉화산로 *** (신내동,(관상복합청사 ***호))
5th row서울특별시 중랑구 신내로 *** (신내동,디아뜨갤러리상가 *층***호)
ValueCountFrequency (%)
2600
15.6%
서울특별시 2537
15.2%
중랑구 2536
15.2%
호 1075
 
6.4%
면목동 838
 
5.0%
층 740
 
4.4%
동 358
 
2.1%
상봉동 322
 
1.9%
묵동 318
 
1.9%
망우동 298
 
1.8%
Other values (1022) 5053
30.3%
2024-05-11T07:48:50.502754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 15586
18.0%
14139
16.3%
동 3617
 
4.2%
중 3111
 
3.6%
, 2865
 
3.3%
랑 2720
 
3.1%
시 2606
 
3.0%
) 2568
 
3.0%
( 2568
 
3.0%
울 2558
 
2.9%
Other values (412) 34446
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47700
55.0%
Other Punctuation 18464
 
21.3%
Space Separator 14139
 
16.3%
Close Punctuation 2568
 
3.0%
Open Punctuation 2568
 
3.0%
Dash Punctuation 554
 
0.6%
Decimal Number 429
 
0.5%
Uppercase Letter 335
 
0.4%
Lowercase Letter 24
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3617
 
7.6%
중 3111
 
6.5%
랑 2720
 
5.7%
시 2606
 
5.5%
울 2558
 
5.4%
서 2551
 
5.3%
로 2550
 
5.3%
구 2540
 
5.3%
별 2538
 
5.3%
특 2537
 
5.3%
Other values (359) 20372
42.7%
Uppercase Letter
ValueCountFrequency (%)
B 62
18.5%
A 45
13.4%
S 31
9.3%
T 28
8.4%
R 27
8.1%
E 26
7.8%
G 25
7.5%
O 24
 
7.2%
W 23
 
6.9%
C 14
 
4.2%
Other values (10) 30
9.0%
Lowercase Letter
ValueCountFrequency (%)
e 6
25.0%
h 3
12.5%
t 2
 
8.3%
c 2
 
8.3%
n 2
 
8.3%
s 1
 
4.2%
y 1
 
4.2%
l 1
 
4.2%
i 1
 
4.2%
r 1
 
4.2%
Other values (4) 4
16.7%
Decimal Number
ValueCountFrequency (%)
1 104
24.2%
0 79
18.4%
2 69
16.1%
3 39
 
9.1%
5 34
 
7.9%
4 32
 
7.5%
9 23
 
5.4%
6 20
 
4.7%
7 20
 
4.7%
8 9
 
2.1%
Other Punctuation
ValueCountFrequency (%)
* 15586
84.4%
, 2865
 
15.5%
@ 8
 
< 0.1%
. 5
 
< 0.1%
Space Separator
ValueCountFrequency (%)
14139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2568
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2568
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 554
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47699
55.0%
Common 38725
44.6%
Latin 359
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3617
 
7.6%
중 3111
 
6.5%
랑 2720
 
5.7%
시 2606
 
5.5%
울 2558
 
5.4%
서 2551
 
5.3%
로 2550
 
5.3%
구 2540
 
5.3%
별 2538
 
5.3%
특 2537
 
5.3%
Other values (358) 20371
42.7%
Latin
ValueCountFrequency (%)
B 62
17.3%
A 45
12.5%
S 31
8.6%
T 28
7.8%
R 27
7.5%
E 26
7.2%
G 25
7.0%
O 24
 
6.7%
W 23
 
6.4%
C 14
 
3.9%
Other values (24) 54
15.0%
Common
ValueCountFrequency (%)
* 15586
40.2%
14139
36.5%
, 2865
 
7.4%
) 2568
 
6.6%
( 2568
 
6.6%
- 554
 
1.4%
1 104
 
0.3%
0 79
 
0.2%
2 69
 
0.2%
3 39
 
0.1%
Other values (9) 154
 
0.4%
Han
ValueCountFrequency (%)
休 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47699
55.0%
ASCII 39084
45.0%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 15586
39.9%
14139
36.2%
, 2865
 
7.3%
) 2568
 
6.6%
( 2568
 
6.6%
- 554
 
1.4%
1 104
 
0.3%
0 79
 
0.2%
2 69
 
0.2%
B 62
 
0.2%
Other values (43) 490
 
1.3%
Hangul
ValueCountFrequency (%)
동 3617
 
7.6%
중 3111
 
6.5%
랑 2720
 
5.7%
시 2606
 
5.5%
울 2558
 
5.4%
서 2551
 
5.3%
로 2550
 
5.3%
구 2540
 
5.3%
별 2538
 
5.3%
특 2537
 
5.3%
Other values (358) 20371
42.7%
CJK
ValueCountFrequency (%)
休 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct255
Distinct (%)10.2%
Missing462
Missing (%)15.6%
Infinite0
Infinite (%)0.0%
Mean2124.5281
Minimum2001
Maximum7332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.2 KiB
2024-05-11T07:48:51.061397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2012.3
Q12057
median2121
Q32178
95-th percentile2246
Maximum7332
Range5331
Interquartile range (IQR)121

Descriptive statistics

Standard deviation128.03275
Coefficient of variation (CV)0.060264089
Kurtosis1091.8765
Mean2124.5281
Median Absolute Deviation (MAD)61
Skewness26.886832
Sum5326192
Variance16392.386
MonotonicityNot monotonic
2024-05-11T07:48:51.522530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2076 58
 
2.0%
2054 36
 
1.2%
2055 35
 
1.2%
2024 31
 
1.0%
2033 31
 
1.0%
2086 28
 
0.9%
2155 28
 
0.9%
2067 27
 
0.9%
2122 26
 
0.9%
2087 25
 
0.8%
Other values (245) 2182
73.5%
(Missing) 462
 
15.6%
ValueCountFrequency (%)
2001 1
 
< 0.1%
2002 7
 
0.2%
2003 7
 
0.2%
2004 12
0.4%
2005 6
 
0.2%
2006 12
0.4%
2007 19
0.6%
2008 13
0.4%
2009 11
0.4%
2010 13
0.4%
ValueCountFrequency (%)
7332 1
 
< 0.1%
2263 2
 
0.1%
2262 1
 
< 0.1%
2260 3
 
0.1%
2259 10
0.3%
2258 12
0.4%
2257 8
0.3%
2256 6
 
0.2%
2255 18
0.6%
2253 10
0.3%

사업장명
Text

Distinct2737
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
2024-05-11T07:48:52.119243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length23
Mean length6.5422701
Min length2

Characters and Unicode

Total characters19424
Distinct characters768
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2593 ?
Unique (%)87.3%

Sample

1st row이엠에스네츄럴(주)
2nd row신용사업부
3rd row비젼명가(중화점)
4th row드림애드텍
5th row태롬코리아 유통
ValueCountFrequency (%)
주식회사 51
 
1.4%
세븐일레븐 29
 
0.8%
허브다이어트 25
 
0.7%
인셀덤 22
 
0.6%
다이어트 13
 
0.4%
하이리빙 12
 
0.3%
애터미 12
 
0.3%
상봉점 12
 
0.3%
코리아 11
 
0.3%
유니베라 10
 
0.3%
Other values (2918) 3377
94.5%
2024-05-11T07:48:53.316131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 818
 
4.2%
606
 
3.1%
스 543
 
2.8%
) 368
 
1.9%
( 364
 
1.9%
리 352
 
1.8%
점 328
 
1.7%
트 328
 
1.7%
어 275
 
1.4%
주 266
 
1.4%
Other values (758) 15176
78.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16660
85.8%
Uppercase Letter 646
 
3.3%
Space Separator 606
 
3.1%
Lowercase Letter 448
 
2.3%
Close Punctuation 369
 
1.9%
Open Punctuation 365
 
1.9%
Decimal Number 271
 
1.4%
Other Punctuation 49
 
0.3%
Dash Punctuation 9
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 818
 
4.9%
스 543
 
3.3%
리 352
 
2.1%
점 328
 
2.0%
트 328
 
2.0%
어 275
 
1.7%
주 266
 
1.6%
아 262
 
1.6%
다 231
 
1.4%
에 224
 
1.3%
Other values (684) 13033
78.2%
Uppercase Letter
ValueCountFrequency (%)
S 76
 
11.8%
A 40
 
6.2%
E 39
 
6.0%
G 37
 
5.7%
H 36
 
5.6%
O 36
 
5.6%
N 35
 
5.4%
L 34
 
5.3%
B 33
 
5.1%
I 31
 
4.8%
Other values (16) 249
38.5%
Lowercase Letter
ValueCountFrequency (%)
e 54
12.1%
o 41
 
9.2%
n 38
 
8.5%
i 38
 
8.5%
a 36
 
8.0%
s 29
 
6.5%
r 25
 
5.6%
l 24
 
5.4%
t 21
 
4.7%
y 16
 
3.6%
Other values (15) 126
28.1%
Decimal Number
ValueCountFrequency (%)
2 80
29.5%
5 66
24.4%
4 26
 
9.6%
0 23
 
8.5%
1 21
 
7.7%
3 16
 
5.9%
9 13
 
4.8%
6 11
 
4.1%
8 9
 
3.3%
7 6
 
2.2%
Other Punctuation
ValueCountFrequency (%)
& 21
42.9%
. 18
36.7%
, 4
 
8.2%
' 3
 
6.1%
? 2
 
4.1%
! 1
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 368
99.7%
」 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 364
99.7%
「 1
 
0.3%
Space Separator
ValueCountFrequency (%)
606
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16657
85.8%
Common 1670
 
8.6%
Latin 1094
 
5.6%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 818
 
4.9%
스 543
 
3.3%
리 352
 
2.1%
점 328
 
2.0%
트 328
 
2.0%
어 275
 
1.7%
주 266
 
1.6%
아 262
 
1.6%
다 231
 
1.4%
에 224
 
1.3%
Other values (682) 13030
78.2%
Latin
ValueCountFrequency (%)
S 76
 
6.9%
e 54
 
4.9%
o 41
 
3.7%
A 40
 
3.7%
E 39
 
3.6%
n 38
 
3.5%
i 38
 
3.5%
G 37
 
3.4%
H 36
 
3.3%
a 36
 
3.3%
Other values (41) 659
60.2%
Common
ValueCountFrequency (%)
606
36.3%
) 368
22.0%
( 364
21.8%
2 80
 
4.8%
5 66
 
4.0%
4 26
 
1.6%
0 23
 
1.4%
& 21
 
1.3%
1 21
 
1.3%
. 18
 
1.1%
Other values (13) 77
 
4.6%
Han
ValueCountFrequency (%)
美 2
66.7%
米 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16657
85.8%
ASCII 2762
 
14.2%
CJK 3
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 818
 
4.9%
스 543
 
3.3%
리 352
 
2.1%
점 328
 
2.0%
트 328
 
2.0%
어 275
 
1.7%
주 266
 
1.6%
아 262
 
1.6%
다 231
 
1.4%
에 224
 
1.3%
Other values (682) 13030
78.2%
ASCII
ValueCountFrequency (%)
606
21.9%
) 368
 
13.3%
( 364
 
13.2%
2 80
 
2.9%
S 76
 
2.8%
5 66
 
2.4%
e 54
 
2.0%
o 41
 
1.5%
A 40
 
1.4%
E 39
 
1.4%
Other values (62) 1028
37.2%
CJK
ValueCountFrequency (%)
美 2
66.7%
米 1
33.3%
None
ValueCountFrequency (%)
」 1
50.0%
「 1
50.0%

최종수정일자
Date

Distinct2814
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
Minimum2004-04-07 00:00:00
Maximum2024-05-09 10:46:40
2024-05-11T07:48:53.738941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:48:54.215352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
I
2013 
U
956 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2013
67.8%
U 956
32.2%

Length

2024-05-11T07:48:54.669013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:54.998418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2013
67.8%
u 956
32.2%

데이터갱신일자
Date

Distinct850
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T07:48:55.491001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:48:56.122945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

좌표정보(X)
Real number (ℝ)

Distinct1782
Distinct (%)60.6%
Missing28
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean207638.54
Minimum193619.04
Maximum209931.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.2 KiB
2024-05-11T07:48:56.593641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum193619.04
5-th percentile206558.83
Q1206967.4
median207598.86
Q3208231.36
95-th percentile208961.69
Maximum209931.17
Range16312.129
Interquartile range (IQR)1263.9541

Descriptive statistics

Standard deviation820.33004
Coefficient of variation (CV)0.0039507601
Kurtosis28.051937
Mean207638.54
Median Absolute Deviation (MAD)631.45421
Skewness-1.3303578
Sum6.1066494 × 108
Variance672941.38
MonotonicityNot monotonic
2024-05-11T07:48:57.127081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208295.099818379 41
 
1.4%
207923.745922676 25
 
0.8%
207163.791145804 24
 
0.8%
207605.319631481 23
 
0.8%
206974.095837709 20
 
0.7%
208136.908729599 17
 
0.6%
207990.479257211 16
 
0.5%
208294.31154469 15
 
0.5%
207982.810825453 15
 
0.5%
208536.163679365 15
 
0.5%
Other values (1772) 2730
92.0%
(Missing) 28
 
0.9%
ValueCountFrequency (%)
193619.043536672 1
< 0.1%
206221.462480638 1
< 0.1%
206221.834183749 1
< 0.1%
206232.501463747 1
< 0.1%
206246.235023787 1
< 0.1%
206248.888273932 1
< 0.1%
206259.152361542 1
< 0.1%
206261.052582648 1
< 0.1%
206285.912434623 2
0.1%
206290.445840268 1
< 0.1%
ValueCountFrequency (%)
209931.172836 11
0.4%
209856.1161416 1
 
< 0.1%
209797.760188391 1
 
< 0.1%
209723.67417621 1
 
< 0.1%
209666.65304044 1
 
< 0.1%
209660.753885948 1
 
< 0.1%
209658.815531957 1
 
< 0.1%
209646.142554388 6
0.2%
209638.584054523 2
 
0.1%
209625.385161432 3
 
0.1%

좌표정보(Y)
Real number (ℝ)

Distinct1782
Distinct (%)60.6%
Missing28
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean454950.84
Minimum446463.95
Maximum457702.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.2 KiB
2024-05-11T07:48:57.652064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446463.95
5-th percentile452819.14
Q1454084.64
median454990.44
Q3455850.94
95-th percentile457087.08
Maximum457702.63
Range11238.684
Interquartile range (IQR)1766.3003

Descriptive statistics

Standard deviation1270.3659
Coefficient of variation (CV)0.0027923147
Kurtosis-0.06159397
Mean454950.84
Median Absolute Deviation (MAD)888.10711
Skewness-0.17721118
Sum1.3380104 × 109
Variance1613829.5
MonotonicityNot monotonic
2024-05-11T07:48:58.556540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456014.999180519 41
 
1.4%
455090.718335439 25
 
0.8%
454984.412728653 24
 
0.8%
454476.402983363 23
 
0.8%
454601.381554597 20
 
0.7%
455433.855855917 17
 
0.6%
457183.637796144 16
 
0.5%
455843.287574845 15
 
0.5%
454980.023827024 15
 
0.5%
456379.478717154 15
 
0.5%
Other values (1772) 2730
92.0%
(Missing) 28
 
0.9%
ValueCountFrequency (%)
446463.947431693 1
< 0.1%
452092.784532468 1
< 0.1%
452098.766989799 2
0.1%
452112.148887923 1
< 0.1%
452121.046249861 1
< 0.1%
452127.637523483 1
< 0.1%
452129.969287997 1
< 0.1%
452134.332757901 1
< 0.1%
452142.620856563 2
0.1%
452164.135638838 1
< 0.1%
ValueCountFrequency (%)
457702.631123 1
 
< 0.1%
457500.72629784 1
 
< 0.1%
457462.766652935 2
 
0.1%
457446.479605 11
0.4%
457438.909754748 1
 
< 0.1%
457386.267609574 1
 
< 0.1%
457380.933864584 5
0.2%
457360.684721982 1
 
< 0.1%
457349.190526051 1
 
< 0.1%
457341.679969126 1
 
< 0.1%

위생업태명
Categorical

Distinct11
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
영업장판매
1103 
<NA>
884 
전자상거래(통신판매업)
483 
방문판매
240 
통신판매
166 
Other values (6)
 
93

Length

Max length14
Median length12
Mean length5.7271809
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업장판매 1103
37.2%
<NA> 884
29.8%
전자상거래(통신판매업) 483
16.3%
방문판매 240
 
8.1%
통신판매 166
 
5.6%
다단계판매 79
 
2.7%
기타 건강기능식품일반판매업 6
 
0.2%
전화권유판매 3
 
0.1%
도매업(유통) 3
 
0.1%
기타(복합 등) 1
 
< 0.1%

Length

2024-05-11T07:48:59.092872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영업장판매 1103
37.1%
na 884
29.7%
전자상거래(통신판매업 483
16.2%
방문판매 240
 
8.1%
통신판매 166
 
5.6%
다단계판매 79
 
2.7%
기타 6
 
0.2%
건강기능식품일반판매업 6
 
0.2%
전화권유판매 3
 
0.1%
도매업(유통 3
 
0.1%
Other values (3) 3
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
2774 
0
 
195

Length

Max length4
Median length4
Mean length3.802964
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> 2774
93.4%
0 195
 
6.6%

Length

2024-05-11T07:48:59.610303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:59.946069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2774
93.4%
0 195
 
6.6%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
2774 
0
 
195

Length

Max length4
Median length4
Mean length3.802964
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> 2774
93.4%
0 195
 
6.6%

Length

2024-05-11T07:49:00.338283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:49:00.838159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2774
93.4%
0 195
 
6.6%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
2940 
상수도전용
 
29

Length

Max length5
Median length4
Mean length4.0097676
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> 2940
99.0%
상수도전용 29
 
1.0%

Length

2024-05-11T07:49:01.381423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:49:01.792586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2940
99.0%
상수도전용 29
 
1.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
2775 
0
 
194

Length

Max length4
Median length4
Mean length3.8039744
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> 2775
93.5%
0 194
 
6.5%

Length

2024-05-11T07:49:02.374083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:49:02.834689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2775
93.5%
0 194
 
6.5%

본사종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
2615 
0
353 
85
 
1

Length

Max length4
Median length4
Mean length3.6426406
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> 2615
88.1%
0 353
 
11.9%
85 1
 
< 0.1%

Length

2024-05-11T07:49:03.452865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:49:03.926835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2615
88.1%
0 353
 
11.9%
85 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
2615 
0
352 
33
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.6426406
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> 2615
88.1%
0 352
 
11.9%
33 1
 
< 0.1%
2 1
 
< 0.1%

Length

2024-05-11T07:49:04.562959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:49:05.034127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2615
88.1%
0 352
 
11.9%
33 1
 
< 0.1%
2 1
 
< 0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.7%
Missing2609
Missing (%)87.9%
Infinite0
Infinite (%)0.0%
Mean0.20555556
Minimum0
Maximum20
Zeros332
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size26.2 KiB
2024-05-11T07:49:05.573652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2067462
Coefficient of variation (CV)5.8706573
Kurtosis203.87271
Mean0.20555556
Median Absolute Deviation (MAD)0
Skewness12.940536
Sum74
Variance1.4562365
MonotonicityNot monotonic
2024-05-11T07:49:06.211771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 332
 
11.2%
2 13
 
0.4%
1 9
 
0.3%
3 3
 
0.1%
5 2
 
0.1%
20 1
 
< 0.1%
(Missing) 2609
87.9%
ValueCountFrequency (%)
0 332
11.2%
1 9
 
0.3%
2 13
 
0.4%
3 3
 
0.1%
5 2
 
0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
5 2
 
0.1%
3 3
 
0.1%
2 13
 
0.4%
1 9
 
0.3%
0 332
11.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
2615 
0
353 
2
 
1

Length

Max length4
Median length4
Mean length3.6423038
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> 2615
88.1%
0 353
 
11.9%
2 1
 
< 0.1%

Length

2024-05-11T07:49:06.690537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:49:07.294485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2615
88.1%
0 353
 
11.9%
2 1
 
< 0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
1980 
자가
562 
임대
427 

Length

Max length4
Median length4
Mean length3.3337824
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> 1980
66.7%
자가 562
 
18.9%
임대 427
 
14.4%

Length

2024-05-11T07:49:08.079474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:49:08.535116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1980
66.7%
자가 562
 
18.9%
임대 427
 
14.4%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
2725 
0
 
243
38602100
 
1

Length

Max length8
Median length4
Mean length3.75581
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> 2725
91.8%
0 243
 
8.2%
38602100 1
 
< 0.1%

Length

2024-05-11T07:49:08.976952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:49:09.301704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2725
91.8%
0 243
 
8.2%
38602100 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
<NA>
2725 
0
 
243
3860210
 
1

Length

Max length7
Median length4
Mean length3.7554732
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> 2725
91.8%
0 243
 
8.2%
3860210 1
 
< 0.1%

Length

2024-05-11T07:49:09.850064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:49:10.201367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2725
91.8%
0 243
 
8.2%
3860210 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing884
Missing (%)29.8%
Memory size5.9 KiB
False
2085 
(Missing)
884 
ValueCountFrequency (%)
False 2085
70.2%
(Missing) 884
29.8%
2024-05-11T07:49:10.475983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct77
Distinct (%)3.7%
Missing884
Missing (%)29.8%
Infinite0
Infinite (%)0.0%
Mean3.3734197
Minimum0
Maximum297.52
Zeros1943
Zeros (%)65.4%
Negative0
Negative (%)0.0%
Memory size26.2 KiB
2024-05-11T07:49:10.849446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.6
Maximum297.52
Range297.52
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19.124514
Coefficient of variation (CV)5.6691772
Kurtosis82.007872
Mean3.3734197
Median Absolute Deviation (MAD)0
Skewness8.1286063
Sum7033.58
Variance365.74703
MonotonicityNot monotonic
2024-05-11T07:49:11.424458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1943
65.4%
3.3 32
 
1.1%
6.6 7
 
0.2%
33.0 6
 
0.2%
10.0 5
 
0.2%
99.0 5
 
0.2%
50.0 4
 
0.1%
9.9 3
 
0.1%
19.8 3
 
0.1%
66.0 2
 
0.1%
Other values (67) 75
 
2.5%
(Missing) 884
29.8%
ValueCountFrequency (%)
0.0 1943
65.4%
3.0 2
 
0.1%
3.3 32
 
1.1%
6.0 1
 
< 0.1%
6.6 7
 
0.2%
9.0 1
 
< 0.1%
9.9 3
 
0.1%
10.0 5
 
0.2%
15.0 2
 
0.1%
16.5 2
 
0.1%
ValueCountFrequency (%)
297.52 1
< 0.1%
264.0 1
< 0.1%
228.23 1
< 0.1%
210.0 1
< 0.1%
201.35 1
< 0.1%
181.0 1
< 0.1%
165.0 1
< 0.1%
148.0 1
< 0.1%
137.85 1
< 0.1%
136.0 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2969
Missing (%)100.0%
Memory size26.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030600003060000-134-2004-0000120040406<NA>3폐업2폐업20160121<NA><NA><NA>02 4360066<NA>131875서울특별시 중랑구 중화동 ***-**번지서울특별시 중랑구 동일로***길 **-* (중화동)2047이엠에스네츄럴(주)2007-04-09 00:00:00I2018-08-31 23:59:59.0<NA>207026.563406455807.538589방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
130600003060000-134-2004-0000320040407<NA>3폐업2폐업20161207<NA><NA><NA>0222079000<NA>131875서울특별시 중랑구 중화동 ***-**번지서울특별시 중랑구 동일로***길 ** (중화동)2050신용사업부2004-04-07 00:00:00I2018-08-31 23:59:59.0<NA>206977.524227455758.379541방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230600003060000-134-2004-0000420040407<NA>3폐업2폐업20100503<NA><NA><NA>02 4928801<NA>131875서울특별시 중랑구 중화동 ***-**번지<NA><NA>비젼명가(중화점)2004-04-07 00:00:00I2018-08-31 23:59:59.0<NA>207110.520133455500.972163방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330600003060000-134-2004-0000520040407<NA>3폐업2폐업20040512<NA><NA><NA><NA><NA>131867서울특별시 중랑구 신내동 ***-**번지<NA><NA>드림애드텍2004-04-07 00:00:00I2018-08-31 23:59:59.0<NA>208432.147531456140.06921방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430600003060000-134-2004-0000620040407<NA>3폐업2폐업20070920<NA><NA><NA>0222094675<NA>131829서울특별시 중랑구 면목동 ***-*번지<NA><NA>태롬코리아 유통2004-04-07 00:00:00I2018-08-31 23:59:59.0<NA>207530.687243452649.921915방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530600003060000-134-2004-0000720040407<NA>3폐업2폐업20071001<NA><NA><NA>02 4943111<NA>131809서울특별시 중랑구 망우동 ***-*번지 사다리빌딩*층<NA><NA>생그린동부지사2005-08-26 00:00:00I2018-08-31 23:59:59.0<NA>208766.661881455118.157244방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630600003060000-134-2004-0000820040407<NA>3폐업2폐업20170323<NA><NA><NA>02 4320275<NA>131821서울특별시 중랑구 면목동 ***-*번지서울특별시 중랑구 겸재로 *** (면목동)2216오투바이오2004-04-07 00:00:00I2018-08-31 23:59:59.0<NA>207205.900557453852.775443방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730600003060000-134-2004-0000920040407<NA>3폐업2폐업20060203<NA><NA><NA>02 4914245<NA>131858서울특별시 중랑구 상봉동 **-*번지 한일써너스빌***동****호<NA><NA>제우스2004-04-07 00:00:00I2018-08-31 23:59:59.0<NA>207982.810825454980.023827방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830600003060000-134-2004-0001020040406<NA>3폐업2폐업20090625<NA><NA><NA>02 4338200<NA>131880서울특별시 중랑구 중화동 ***-**번지 성심빌딩 *층<NA><NA>이엠에스네츄럴2007-04-09 00:00:00I2018-08-31 23:59:59.0<NA>206956.392279455196.971911방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930600003060000-134-2004-0001120040412<NA>3폐업2폐업20181116<NA><NA><NA>0234217707<NA>131865서울특별시 중랑구 신내동 ***번지 (관상복합청사 ***호)서울특별시 중랑구 봉화산로 *** (신내동,(관상복합청사 ***호))2076유니베라2018-11-16 15:27:45U2018-11-18 02:36:47.0<NA>208245.979899455993.576503방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
295930600003060000-134-2024-000572024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA>02 22071357<NA>131-831서울특별시 중랑구 면목동 ***-* 농협서울특별시 중랑구 사가정로 *** (면목동)2228다비치안경 사가정역점2024-04-22 13:51:36I2023-12-03 22:04:00.0<NA>207564.382907453207.051708<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296030600003060000-134-2024-000582024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-861서울특별시 중랑구 상봉동 ***-**서울특별시 중랑구 동일로 ***, *층 (상봉동)2122바이크랜드2024-04-22 13:54:52I2023-12-03 22:04:00.0<NA>206986.454175454678.651641<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296130600003060000-134-2024-000592024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA>02 9711222<NA>131-849서울특별시 중랑구 묵동 ***-*서울특별시 중랑구 동일로 ***, *층 (묵동)2039다비치안경 먹골역점2024-04-25 11:01:35I2023-12-03 22:07:00.0<NA>206842.344164456352.321407<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296230600003060000-134-2024-000602024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-775서울특별시 중랑구 묵동 *** 금호어울림아파트서울특별시 중랑구 공릉로*길 **, ***동 ****호 (묵동, 금호어울림아파트)2036냥글댕글2024-04-30 16:07:25I2023-12-05 00:02:00.0<NA>206997.618789456713.095863<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296330600003060000-134-2024-000612024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 433 9485<NA>131-810서울특별시 중랑구 망우동 ***-**서울특별시 중랑구 망우로 ***, *층 ***호 (망우동)2072다비치안경 보청기 망우점2024-04-30 17:28:53I2023-12-05 00:02:00.0<NA>208661.161795455280.403063<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296430600003060000-134-2024-000622024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA>02 4351330<NA>131-871서울특별시 중랑구 신내동 ***-*서울특별시 중랑구 신내로 **, *층 (신내동)2076커브스 신내클럽2024-05-02 13:57:59I2023-12-05 00:04:00.0<NA>208329.316274455923.228873<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296530600003060000-134-2024-000632024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3131-828서울특별시 중랑구 면목동 ***-**서울특별시 중랑구 면목로**길 **, *층 (면목동)2252러블리(LOVELY)2024-05-02 15:45:45I2023-12-05 00:04:00.0<NA>207690.327471452971.460388<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296630600003060000-134-2024-000642024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-821서울특별시 중랑구 면목동 ***-*서울특별시 중랑구 동일로**나길 ** (면목동)2223대큐레이션2024-05-03 11:23:17I2023-12-05 00:05:00.0<NA>207221.01371453568.131691<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296730600003060000-134-2024-000652024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-876서울특별시 중랑구 중화동 ***-** 청원다미소아파트서울특별시 중랑구 동일로***길 **, ***호 (중화동, 청원다미소아파트)2051인셀덤퀸2024-05-07 16:06:15I2023-12-05 00:09:00.0<NA>206994.15405455522.929612<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
296830600003060000-134-2024-000662024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3131-824서울특별시 중랑구 면목동 ***-**서울특별시 중랑구 중랑천로 *, *층 (면목동)2133아라마켓2024-05-08 14:45:51I2023-12-04 23:00:00.0<NA>206581.080218453739.983185<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>