Overview

Dataset statistics

Number of variables44
Number of observations2618
Missing cells28180
Missing cells (%)24.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory964.0 KiB
Average record size in memory377.1 B

Variable types

Categorical19
Text6
DateTime4
Unsupported8
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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-18694/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
남성종사자수 is highly imbalanced (54.6%)Imbalance
영업장주변구분명 is highly imbalanced (69.7%)Imbalance
등급구분명 is highly imbalanced (65.9%)Imbalance
급수시설구분명 is highly imbalanced (52.0%)Imbalance
총인원 is highly imbalanced (67.4%)Imbalance
본사종업원수 is highly imbalanced (67.4%)Imbalance
공장사무직종업원수 is highly imbalanced (67.4%)Imbalance
공장판매직종업원수 is highly imbalanced (67.4%)Imbalance
공장생산직종업원수 is highly imbalanced (67.4%)Imbalance
보증액 is highly imbalanced (67.4%)Imbalance
월세액 is highly imbalanced (67.4%)Imbalance
다중이용업소여부 is highly imbalanced (93.8%)Imbalance
인허가취소일자 has 2618 (100.0%) missing valuesMissing
폐업일자 has 971 (37.1%) missing valuesMissing
휴업시작일자 has 2618 (100.0%) missing valuesMissing
휴업종료일자 has 2618 (100.0%) missing valuesMissing
재개업일자 has 2618 (100.0%) missing valuesMissing
전화번호 has 1573 (60.1%) missing valuesMissing
소재지면적 has 28 (1.1%) missing valuesMissing
도로명주소 has 645 (24.6%) missing valuesMissing
도로명우편번호 has 654 (25.0%) missing valuesMissing
좌표정보(X) has 53 (2.0%) missing valuesMissing
좌표정보(Y) has 53 (2.0%) missing valuesMissing
여성종사자수 has 1849 (70.6%) missing valuesMissing
건물소유구분명 has 2618 (100.0%) missing valuesMissing
다중이용업소여부 has 702 (26.8%) missing valuesMissing
시설총규모 has 702 (26.8%) missing valuesMissing
전통업소지정번호 has 2618 (100.0%) missing valuesMissing
전통업소주된음식 has 2618 (100.0%) missing valuesMissing
홈페이지 has 2618 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
여성종사자수 has 482 (18.4%) zerosZeros

Reproduction

Analysis started2024-05-11 05:56:25.750112
Analysis finished2024-05-11 05:56:28.084397
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
3170000
2618 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 2618
100.0%

Length

2024-05-11T14:56:28.183021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:28.328227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 2618
100.0%

관리번호
Text

UNIQUE 

Distinct2618
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
2024-05-11T14:56:28.550705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters57596
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

Unique2618 ?
Unique (%)100.0%

Sample

1st row3170000-104-1970-00230
2nd row3170000-104-1970-00397
3rd row3170000-104-1972-00130
4th row3170000-104-1973-00198
5th row3170000-104-1973-00403
ValueCountFrequency (%)
3170000-104-1970-00230 1
 
< 0.1%
3170000-104-2018-00122 1
 
< 0.1%
3170000-104-2018-00105 1
 
< 0.1%
3170000-104-2018-00106 1
 
< 0.1%
3170000-104-2018-00114 1
 
< 0.1%
3170000-104-2018-00107 1
 
< 0.1%
3170000-104-2018-00108 1
 
< 0.1%
3170000-104-2018-00109 1
 
< 0.1%
3170000-104-2018-00110 1
 
< 0.1%
3170000-104-2018-00111 1
 
< 0.1%
Other values (2608) 2608
99.6%
2024-05-11T14:56:29.020325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23647
41.1%
1 8315
 
14.4%
- 7854
 
13.6%
2 3832
 
6.7%
3 3570
 
6.2%
4 3406
 
5.9%
7 3322
 
5.8%
9 1250
 
2.2%
8 893
 
1.6%
5 757
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49742
86.4%
Dash Punctuation 7854
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23647
47.5%
1 8315
 
16.7%
2 3832
 
7.7%
3 3570
 
7.2%
4 3406
 
6.8%
7 3322
 
6.7%
9 1250
 
2.5%
8 893
 
1.8%
5 757
 
1.5%
6 750
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7854
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57596
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23647
41.1%
1 8315
 
14.4%
- 7854
 
13.6%
2 3832
 
6.7%
3 3570
 
6.2%
4 3406
 
5.9%
7 3322
 
5.8%
9 1250
 
2.2%
8 893
 
1.6%
5 757
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23647
41.1%
1 8315
 
14.4%
- 7854
 
13.6%
2 3832
 
6.7%
3 3570
 
6.2%
4 3406
 
5.9%
7 3322
 
5.8%
9 1250
 
2.2%
8 893
 
1.6%
5 757
 
1.3%

인허가일자
Date

Distinct2098
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
Minimum1970-08-20 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:56:29.223405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:29.402564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
3
1647 
1
971 

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 1647
62.9%
1 971
37.1%

Length

2024-05-11T14:56:29.593358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:29.777126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1647
62.9%
1 971
37.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
폐업
1647 
영업/정상
971 

Length

Max length5
Median length2
Mean length3.1126814
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1647
62.9%
영업/정상 971
37.1%

Length

2024-05-11T14:56:29.972145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:30.148867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1647
62.9%
영업/정상 971
37.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
2
1647 
1
971 

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 1647
62.9%
1 971
37.1%

Length

2024-05-11T14:56:30.337615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:30.607021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1647
62.9%
1 971
37.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
폐업
1647 
영업
971 

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 1647
62.9%
영업 971
37.1%

Length

2024-05-11T14:56:30.808855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:30.979933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1647
62.9%
영업 971
37.1%

폐업일자
Date

MISSING 

Distinct1348
Distinct (%)81.8%
Missing971
Missing (%)37.1%
Memory size20.6 KiB
Minimum1993-09-20 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:56:31.176707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:31.383768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

전화번호
Text

MISSING 

Distinct965
Distinct (%)92.3%
Missing1573
Missing (%)60.1%
Memory size20.6 KiB
2024-05-11T14:56:31.768890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.148325
Min length2

Characters and Unicode

Total characters10605
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

Unique933 ?
Unique (%)89.3%

Sample

1st row02
2nd row0208550921
3rd row02
4th row02 8025119
5th row0208070303
ValueCountFrequency (%)
02 693
36.7%
070 19
 
1.0%
808 11
 
0.6%
858 9
 
0.5%
803 9
 
0.5%
0200000000 8
 
0.4%
802 7
 
0.4%
866 7
 
0.4%
031 6
 
0.3%
859 6
 
0.3%
Other values (1004) 1115
59.0%
2024-05-11T14:56:32.559381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2271
21.4%
2 1677
15.8%
8 1300
12.3%
1070
10.1%
6 683
 
6.4%
5 675
 
6.4%
9 615
 
5.8%
3 610
 
5.8%
1 580
 
5.5%
7 577
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9535
89.9%
Space Separator 1070
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2271
23.8%
2 1677
17.6%
8 1300
13.6%
6 683
 
7.2%
5 675
 
7.1%
9 615
 
6.4%
3 610
 
6.4%
1 580
 
6.1%
7 577
 
6.1%
4 547
 
5.7%
Space Separator
ValueCountFrequency (%)
1070
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10605
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2271
21.4%
2 1677
15.8%
8 1300
12.3%
1070
10.1%
6 683
 
6.4%
5 675
 
6.4%
9 615
 
5.8%
3 610
 
5.8%
1 580
 
5.5%
7 577
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10605
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2271
21.4%
2 1677
15.8%
8 1300
12.3%
1070
10.1%
6 683
 
6.4%
5 675
 
6.4%
9 615
 
5.8%
3 610
 
5.8%
1 580
 
5.5%
7 577
 
5.4%

소재지면적
Real number (ℝ)

MISSING 

Distinct1613
Distinct (%)62.3%
Missing28
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean43.505606
Minimum0.25
Maximum530
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-05-11T14:56:33.108122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.25
5-th percentile3.3
Q113.2
median30
Q359.8525
95-th percentile124.5435
Maximum530
Range529.75
Interquartile range (IQR)46.6525

Descriptive statistics

Standard deviation46.176558
Coefficient of variation (CV)1.0613933
Kurtosis16.518017
Mean43.505606
Median Absolute Deviation (MAD)20.675
Skewness3.0326777
Sum112679.52
Variance2132.2745
MonotonicityNot monotonic
2024-05-11T14:56:33.373946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 220
 
8.4%
3.0 38
 
1.5%
33.0 37
 
1.4%
6.6 36
 
1.4%
9.9 33
 
1.3%
10.0 23
 
0.9%
30.0 19
 
0.7%
4.0 14
 
0.5%
13.2 14
 
0.5%
20.0 14
 
0.5%
Other values (1603) 2142
81.8%
(Missing) 28
 
1.1%
ValueCountFrequency (%)
0.25 1
 
< 0.1%
0.4 3
0.1%
0.5 2
0.1%
0.61 1
 
< 0.1%
0.75 1
 
< 0.1%
0.79 1
 
< 0.1%
0.85 1
 
< 0.1%
1.0 4
0.2%
1.02 1
 
< 0.1%
1.04 1
 
< 0.1%
ValueCountFrequency (%)
530.0 1
< 0.1%
468.13 1
< 0.1%
445.36 1
< 0.1%
412.5 1
< 0.1%
359.48 1
< 0.1%
348.19 1
< 0.1%
304.8 1
< 0.1%
284.15 1
< 0.1%
280.53 1
< 0.1%
279.43 1
< 0.1%

소재지우편번호
Text

Distinct140
Distinct (%)5.4%
Missing3
Missing (%)0.1%
Memory size20.6 KiB
2024-05-11T14:56:33.810939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1736138
Min length6

Characters and Unicode

Total characters16144
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

Unique20 ?
Unique (%)0.8%

Sample

1st row153864
2nd row153806
3rd row153813
4th row153841
5th row153858
ValueCountFrequency (%)
153801 287
 
11.0%
153803 218
 
8.3%
153813 172
 
6.6%
153864 106
 
4.1%
153858 92
 
3.5%
153-803 83
 
3.2%
153010 82
 
3.1%
153-801 77
 
2.9%
153857 57
 
2.2%
153802 55
 
2.1%
Other values (130) 1386
53.0%
2024-05-11T14:56:34.577220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3549
22.0%
3 3431
21.3%
5 3116
19.3%
8 2493
15.4%
0 1283
 
7.9%
6 462
 
2.9%
- 454
 
2.8%
2 419
 
2.6%
4 379
 
2.3%
7 347
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15690
97.2%
Dash Punctuation 454
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3549
22.6%
3 3431
21.9%
5 3116
19.9%
8 2493
15.9%
0 1283
 
8.2%
6 462
 
2.9%
2 419
 
2.7%
4 379
 
2.4%
7 347
 
2.2%
9 211
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 454
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16144
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3549
22.0%
3 3431
21.3%
5 3116
19.3%
8 2493
15.4%
0 1283
 
7.9%
6 462
 
2.9%
- 454
 
2.8%
2 419
 
2.6%
4 379
 
2.3%
7 347
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16144
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3549
22.0%
3 3431
21.3%
5 3116
19.3%
8 2493
15.4%
0 1283
 
7.9%
6 462
 
2.9%
- 454
 
2.8%
2 419
 
2.6%
4 379
 
2.3%
7 347
 
2.1%

지번주소
Text

Distinct2260
Distinct (%)86.4%
Missing3
Missing (%)0.1%
Memory size20.6 KiB
2024-05-11T14:56:35.172080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length29.286424
Min length17

Characters and Unicode

Total characters76584
Distinct characters366
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

Unique2038 ?
Unique (%)77.9%

Sample

1st row서울특별시 금천구 시흥동 994-12번지 지하1층 (시흥대로 464)
2nd row서울특별시 금천구 독산동 144-23번지
3rd row서울특별시 금천구 독산동 331-4번지
4th row서울특별시 금천구 시흥동 831-6번지
5th row서울특별시 금천구 시흥동 883-11번지
ValueCountFrequency (%)
금천구 2617
18.5%
서울특별시 2615
18.5%
독산동 901
 
6.4%
가산동 894
 
6.3%
시흥동 821
 
5.8%
지상1층 537
 
3.8%
1층 163
 
1.2%
지하1층 148
 
1.0%
가산 53
 
0.4%
291-7번지 51
 
0.4%
Other values (2417) 5336
37.7%
2024-05-11T14:56:35.977625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13208
 
17.2%
1 4106
 
5.4%
시 3604
 
4.7%
천 2789
 
3.6%
금 2784
 
3.6%
동 2758
 
3.6%
울 2692
 
3.5%
구 2634
 
3.4%
서 2629
 
3.4%
별 2618
 
3.4%
Other values (356) 36762
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43974
57.4%
Decimal Number 15755
 
20.6%
Space Separator 13208
 
17.2%
Dash Punctuation 2430
 
3.2%
Uppercase Letter 556
 
0.7%
Close Punctuation 264
 
0.3%
Open Punctuation 263
 
0.3%
Other Punctuation 115
 
0.2%
Lowercase Letter 15
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3604
 
8.2%
천 2789
 
6.3%
금 2784
 
6.3%
동 2758
 
6.3%
울 2692
 
6.1%
구 2634
 
6.0%
서 2629
 
6.0%
별 2618
 
6.0%
특 2615
 
5.9%
지 2512
 
5.7%
Other values (305) 16339
37.2%
Uppercase Letter
ValueCountFrequency (%)
B 132
23.7%
T 60
10.8%
A 41
 
7.4%
S 40
 
7.2%
I 39
 
7.0%
C 27
 
4.9%
L 24
 
4.3%
J 24
 
4.3%
W 20
 
3.6%
Y 19
 
3.4%
Other values (14) 130
23.4%
Decimal Number
ValueCountFrequency (%)
1 4106
26.1%
0 1732
11.0%
2 1730
11.0%
9 1477
 
9.4%
3 1298
 
8.2%
8 1187
 
7.5%
5 1175
 
7.5%
4 1159
 
7.4%
6 962
 
6.1%
7 929
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
e 5
33.3%
i 2
 
13.3%
c 2
 
13.3%
l 2
 
13.3%
v 1
 
6.7%
x 1
 
6.7%
t 1
 
6.7%
s 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 111
96.5%
' 2
 
1.7%
& 1
 
0.9%
. 1
 
0.9%
Space Separator
ValueCountFrequency (%)
13208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2430
100.0%
Close Punctuation
ValueCountFrequency (%)
) 264
100.0%
Open Punctuation
ValueCountFrequency (%)
( 263
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43974
57.4%
Common 32039
41.8%
Latin 571
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3604
 
8.2%
천 2789
 
6.3%
금 2784
 
6.3%
동 2758
 
6.3%
울 2692
 
6.1%
구 2634
 
6.0%
서 2629
 
6.0%
별 2618
 
6.0%
특 2615
 
5.9%
지 2512
 
5.7%
Other values (305) 16339
37.2%
Latin
ValueCountFrequency (%)
B 132
23.1%
T 60
10.5%
A 41
 
7.2%
S 40
 
7.0%
I 39
 
6.8%
C 27
 
4.7%
L 24
 
4.2%
J 24
 
4.2%
W 20
 
3.5%
Y 19
 
3.3%
Other values (22) 145
25.4%
Common
ValueCountFrequency (%)
13208
41.2%
1 4106
 
12.8%
- 2430
 
7.6%
0 1732
 
5.4%
2 1730
 
5.4%
9 1477
 
4.6%
3 1298
 
4.1%
8 1187
 
3.7%
5 1175
 
3.7%
4 1159
 
3.6%
Other values (9) 2537
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43974
57.4%
ASCII 32610
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13208
40.5%
1 4106
 
12.6%
- 2430
 
7.5%
0 1732
 
5.3%
2 1730
 
5.3%
9 1477
 
4.5%
3 1298
 
4.0%
8 1187
 
3.6%
5 1175
 
3.6%
4 1159
 
3.6%
Other values (41) 3108
 
9.5%
Hangul
ValueCountFrequency (%)
시 3604
 
8.2%
천 2789
 
6.3%
금 2784
 
6.3%
동 2758
 
6.3%
울 2692
 
6.1%
구 2634
 
6.0%
서 2629
 
6.0%
별 2618
 
6.0%
특 2615
 
5.9%
지 2512
 
5.7%
Other values (305) 16339
37.2%

도로명주소
Text

MISSING 

Distinct1799
Distinct (%)91.2%
Missing645
Missing (%)24.6%
Memory size20.6 KiB
2024-05-11T14:56:36.551062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length57
Mean length37.994932
Min length22

Characters and Unicode

Total characters74964
Distinct characters361
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

Unique1678 ?
Unique (%)85.0%

Sample

1st row서울특별시 금천구 시흥대로 211 (시흥동)
2nd row서울특별시 금천구 독산로 42 (시흥동,지하1층 (독산동길 327))
3rd row서울특별시 금천구 시흥대로142길 52 (독산동)
4th row서울특별시 금천구 시흥대로 405 (독산동)
5th row서울특별시 금천구 시흥대로 149 (시흥동,지상2층 (시흥대로 536))
ValueCountFrequency (%)
서울특별시 1973
 
14.1%
금천구 1973
 
14.1%
가산동 703
 
5.0%
지상1층 681
 
4.9%
독산동 603
 
4.3%
1층 505
 
3.6%
시흥동 486
 
3.5%
시흥대로 296
 
2.1%
가산디지털1로 241
 
1.7%
벚꽃로 135
 
1.0%
Other values (1569) 6424
45.8%
2024-05-11T14:56:37.305729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12062
 
16.1%
1 4508
 
6.0%
시 3130
 
4.2%
, 2519
 
3.4%
산 2456
 
3.3%
금 2240
 
3.0%
동 2142
 
2.9%
천 2105
 
2.8%
( 2084
 
2.8%
) 2084
 
2.8%
Other values (351) 39634
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43170
57.6%
Decimal Number 12228
 
16.3%
Space Separator 12062
 
16.1%
Other Punctuation 2522
 
3.4%
Open Punctuation 2084
 
2.8%
Close Punctuation 2084
 
2.8%
Uppercase Letter 553
 
0.7%
Dash Punctuation 241
 
0.3%
Lowercase Letter 17
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3130
 
7.3%
산 2456
 
5.7%
금 2240
 
5.2%
동 2142
 
5.0%
천 2105
 
4.9%
울 2058
 
4.8%
서 2005
 
4.6%
로 1993
 
4.6%
구 1986
 
4.6%
별 1973
 
4.6%
Other values (300) 21082
48.8%
Uppercase Letter
ValueCountFrequency (%)
B 112
20.3%
T 62
11.2%
A 41
 
7.4%
I 37
 
6.7%
S 36
 
6.5%
C 28
 
5.1%
L 28
 
5.1%
W 21
 
3.8%
J 21
 
3.8%
Y 21
 
3.8%
Other values (14) 146
26.4%
Decimal Number
ValueCountFrequency (%)
1 4508
36.9%
2 1545
 
12.6%
0 1236
 
10.1%
3 1044
 
8.5%
4 739
 
6.0%
6 698
 
5.7%
5 685
 
5.6%
9 652
 
5.3%
8 566
 
4.6%
7 555
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 5
29.4%
x 2
 
11.8%
l 2
 
11.8%
i 2
 
11.8%
c 2
 
11.8%
y 1
 
5.9%
v 1
 
5.9%
t 1
 
5.9%
s 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 2519
99.9%
' 2
 
0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12062
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2084
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2084
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 241
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43170
57.6%
Common 31224
41.7%
Latin 570
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3130
 
7.3%
산 2456
 
5.7%
금 2240
 
5.2%
동 2142
 
5.0%
천 2105
 
4.9%
울 2058
 
4.8%
서 2005
 
4.6%
로 1993
 
4.6%
구 1986
 
4.6%
별 1973
 
4.6%
Other values (300) 21082
48.8%
Latin
ValueCountFrequency (%)
B 112
19.6%
T 62
 
10.9%
A 41
 
7.2%
I 37
 
6.5%
S 36
 
6.3%
C 28
 
4.9%
L 28
 
4.9%
W 21
 
3.7%
J 21
 
3.7%
Y 21
 
3.7%
Other values (23) 163
28.6%
Common
ValueCountFrequency (%)
12062
38.6%
1 4508
 
14.4%
, 2519
 
8.1%
( 2084
 
6.7%
) 2084
 
6.7%
2 1545
 
4.9%
0 1236
 
4.0%
3 1044
 
3.3%
4 739
 
2.4%
6 698
 
2.2%
Other values (8) 2705
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43170
57.6%
ASCII 31794
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12062
37.9%
1 4508
 
14.2%
, 2519
 
7.9%
( 2084
 
6.6%
) 2084
 
6.6%
2 1545
 
4.9%
0 1236
 
3.9%
3 1044
 
3.3%
4 739
 
2.3%
6 698
 
2.2%
Other values (41) 3275
 
10.3%
Hangul
ValueCountFrequency (%)
시 3130
 
7.3%
산 2456
 
5.7%
금 2240
 
5.2%
동 2142
 
5.0%
천 2105
 
4.9%
울 2058
 
4.8%
서 2005
 
4.6%
로 1993
 
4.6%
구 1986
 
4.6%
별 1973
 
4.6%
Other values (300) 21082
48.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct150
Distinct (%)7.6%
Missing654
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean8566.4939
Minimum8500
Maximum8657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-05-11T14:56:37.550927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8500
5-th percentile8503
Q18514
median8568
Q38608
95-th percentile8644
Maximum8657
Range157
Interquartile range (IQR)94

Descriptive statistics

Standard deviation48.66377
Coefficient of variation (CV)0.0056807102
Kurtosis-1.3709022
Mean8566.4939
Median Absolute Deviation (MAD)48
Skewness0.16058569
Sum16824594
Variance2368.1625
MonotonicityNot monotonic
2024-05-11T14:56:37.821948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8511 96
 
3.7%
8584 75
 
2.9%
8608 73
 
2.8%
8503 56
 
2.1%
8514 48
 
1.8%
8507 46
 
1.8%
8512 42
 
1.6%
8506 42
 
1.6%
8513 40
 
1.5%
8594 38
 
1.5%
Other values (140) 1408
53.8%
(Missing) 654
25.0%
ValueCountFrequency (%)
8500 9
 
0.3%
8501 26
1.0%
8502 19
 
0.7%
8503 56
2.1%
8504 16
 
0.6%
8505 33
1.3%
8506 42
1.6%
8507 46
1.8%
8508 1
 
< 0.1%
8509 1
 
< 0.1%
ValueCountFrequency (%)
8657 5
 
0.2%
8656 19
0.7%
8655 2
 
0.1%
8654 9
0.3%
8653 3
 
0.1%
8652 10
0.4%
8651 10
0.4%
8649 8
0.3%
8647 1
 
< 0.1%
8646 2
 
0.1%

사업장명
Text

Distinct2444
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
2024-05-11T14:56:38.358615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length25
Mean length8.0213904
Min length1

Characters and Unicode

Total characters21000
Distinct characters748
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2300 ?
Unique (%)87.9%

Sample

1st row프로포즈커피숍
2nd row수정
3rd row수연
4th row은다실
5th row응접실
ValueCountFrequency (%)
씨유 91
 
2.3%
세븐일레븐 73
 
1.9%
카페 46
 
1.2%
gs25 37
 
1.0%
금천점 29
 
0.7%
가산점 28
 
0.7%
커피 22
 
0.6%
이마트24 22
 
0.6%
독산점 19
 
0.5%
cafe 18
 
0.5%
Other values (2666) 3507
90.1%
2024-05-11T14:56:39.154151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1275
 
6.1%
점 942
 
4.5%
스 632
 
3.0%
산 558
 
2.7%
가 428
 
2.0%
피 410
 
2.0%
이 395
 
1.9%
커 330
 
1.6%
) 327
 
1.6%
( 327
 
1.6%
Other values (738) 15376
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16470
78.4%
Space Separator 1275
 
6.1%
Uppercase Letter 1204
 
5.7%
Lowercase Letter 787
 
3.7%
Decimal Number 525
 
2.5%
Close Punctuation 328
 
1.6%
Open Punctuation 328
 
1.6%
Other Punctuation 59
 
0.3%
Dash Punctuation 20
 
0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 942
 
5.7%
스 632
 
3.8%
산 558
 
3.4%
가 428
 
2.6%
피 410
 
2.5%
이 395
 
2.4%
커 330
 
2.0%
리 310
 
1.9%
천 269
 
1.6%
금 265
 
1.6%
Other values (663) 11931
72.4%
Uppercase Letter
ValueCountFrequency (%)
C 160
13.3%
S 134
 
11.1%
G 115
 
9.6%
E 83
 
6.9%
O 74
 
6.1%
A 70
 
5.8%
P 67
 
5.6%
F 60
 
5.0%
U 57
 
4.7%
T 48
 
4.0%
Other values (16) 336
27.9%
Lowercase Letter
ValueCountFrequency (%)
e 151
19.2%
f 85
10.8%
a 85
10.8%
o 70
8.9%
c 54
 
6.9%
t 43
 
5.5%
s 37
 
4.7%
r 33
 
4.2%
i 31
 
3.9%
l 30
 
3.8%
Other values (13) 168
21.3%
Decimal Number
ValueCountFrequency (%)
2 191
36.4%
5 136
25.9%
1 57
 
10.9%
4 36
 
6.9%
0 28
 
5.3%
3 22
 
4.2%
9 19
 
3.6%
7 14
 
2.7%
6 11
 
2.1%
8 11
 
2.1%
Other Punctuation
ValueCountFrequency (%)
& 23
39.0%
, 13
22.0%
. 9
 
15.3%
' 5
 
8.5%
＆ 4
 
6.8%
? 2
 
3.4%
/ 2
 
3.4%
; 1
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 327
99.7%
] 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 327
99.7%
[ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Symbol
ValueCountFrequency (%)
℉ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16464
78.4%
Common 2539
 
12.1%
Latin 1991
 
9.5%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 942
 
5.7%
스 632
 
3.8%
산 558
 
3.4%
가 428
 
2.6%
피 410
 
2.5%
이 395
 
2.4%
커 330
 
2.0%
리 310
 
1.9%
천 269
 
1.6%
금 265
 
1.6%
Other values (657) 11925
72.4%
Latin
ValueCountFrequency (%)
C 160
 
8.0%
e 151
 
7.6%
S 134
 
6.7%
G 115
 
5.8%
f 85
 
4.3%
a 85
 
4.3%
E 83
 
4.2%
O 74
 
3.7%
o 70
 
3.5%
A 70
 
3.5%
Other values (39) 964
48.4%
Common
ValueCountFrequency (%)
1275
50.2%
) 327
 
12.9%
( 327
 
12.9%
2 191
 
7.5%
5 136
 
5.4%
1 57
 
2.2%
4 36
 
1.4%
0 28
 
1.1%
& 23
 
0.9%
3 22
 
0.9%
Other values (16) 117
 
4.6%
Han
ValueCountFrequency (%)
面 1
16.7%
姐 1
16.7%
妹 1
16.7%
食 1
16.7%
喜 1
16.7%
人 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16464
78.4%
ASCII 4525
 
21.5%
CJK 6
 
< 0.1%
None 4
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1275
28.2%
) 327
 
7.2%
( 327
 
7.2%
2 191
 
4.2%
C 160
 
3.5%
e 151
 
3.3%
5 136
 
3.0%
S 134
 
3.0%
G 115
 
2.5%
f 85
 
1.9%
Other values (63) 1624
35.9%
Hangul
ValueCountFrequency (%)
점 942
 
5.7%
스 632
 
3.8%
산 558
 
3.4%
가 428
 
2.6%
피 410
 
2.5%
이 395
 
2.4%
커 330
 
2.0%
리 310
 
1.9%
천 269
 
1.6%
금 265
 
1.6%
Other values (657) 11925
72.4%
None
ValueCountFrequency (%)
＆ 4
100.0%
CJK
ValueCountFrequency (%)
面 1
16.7%
姐 1
16.7%
妹 1
16.7%
食 1
16.7%
喜 1
16.7%
人 1
16.7%
Letterlike Symbols
ValueCountFrequency (%)
℉ 1
100.0%

최종수정일자
Date

Distinct2411
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
Minimum1999-03-26 00:00:00
Maximum2024-05-09 16:32:39
2024-05-11T14:56:39.393135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:39.594848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
I
1658 
U
959 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 1658
63.3%
U 959
36.6%
D 1
 
< 0.1%

Length

2024-05-11T14:56:39.814259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:39.986386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1658
63.3%
u 959
36.6%
d 1
 
< 0.1%

데이터갱신일자
Date

Distinct907
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:56:40.209640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:56:40.845932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct15
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
커피숍
861 
일반조리판매
547 
편의점
368 
다방
363 
기타 휴게음식점
275 
Other values (10)
204 

Length

Max length8
Median length6
Mean length4.1485867
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 861
32.9%
일반조리판매 547
20.9%
편의점 368
14.1%
다방 363
13.9%
기타 휴게음식점 275
 
10.5%
패스트푸드 142
 
5.4%
푸드트럭 16
 
0.6%
아이스크림 15
 
0.6%
철도역구내 10
 
0.4%
과자점 6
 
0.2%
Other values (5) 15
 
0.6%

Length

2024-05-11T14:56:41.043833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 861
29.8%
일반조리판매 547
18.9%
편의점 368
12.7%
다방 363
12.5%
기타 275
 
9.5%
휴게음식점 275
 
9.5%
패스트푸드 142
 
4.9%
푸드트럭 16
 
0.6%
아이스크림 15
 
0.5%
철도역구내 10
 
0.3%
Other values (6) 21
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1132
Distinct (%)44.1%
Missing53
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean190725.94
Minimum188870.64
Maximum192754.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-05-11T14:56:41.288188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum188870.64
5-th percentile189364.1
Q1189997.46
median190862.97
Q3191352.95
95-th percentile191880.44
Maximum192754.35
Range3883.7101
Interquartile range (IQR)1355.4946

Descriptive statistics

Standard deviation819.71316
Coefficient of variation (CV)0.0042978589
Kurtosis-0.89773772
Mean190725.94
Median Absolute Deviation (MAD)605.45581
Skewness-0.25023783
Sum4.8921202 × 108
Variance671929.66
MonotonicityNot monotonic
2024-05-11T14:56:41.531689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190809.507840375 64
 
2.4%
190119.463375612 46
 
1.8%
190704.904312713 37
 
1.4%
191152.432649234 37
 
1.4%
189538.020935968 34
 
1.3%
191226.287379467 32
 
1.2%
189943.234285288 28
 
1.1%
189722.178532426 26
 
1.0%
189997.455663258 25
 
1.0%
190858.649482406 24
 
0.9%
Other values (1122) 2212
84.5%
(Missing) 53
 
2.0%
ValueCountFrequency (%)
188870.636085641 1
 
< 0.1%
188882.169962717 1
 
< 0.1%
188927.953883941 1
 
< 0.1%
188968.189711073 1
 
< 0.1%
188974.800556597 1
 
< 0.1%
188979.225789508 1
 
< 0.1%
188981.555267121 1
 
< 0.1%
189016.465808265 2
0.1%
189021.226992181 3
0.1%
189031.670933573 3
0.1%
ValueCountFrequency (%)
192754.34619252 4
0.2%
192742.326147617 2
 
0.1%
192513.506810363 1
 
< 0.1%
192421.424581433 4
0.2%
192389.33175809 1
 
< 0.1%
192368.43764933 6
0.2%
192365.151762912 1
 
< 0.1%
192361.460767692 1
 
< 0.1%
192350.237217477 4
0.2%
192345.047518967 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1132
Distinct (%)44.1%
Missing53
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean440523.71
Minimum436888.77
Maximum442636.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-05-11T14:56:41.749870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436888.77
5-th percentile438436.11
Q1439267.71
median440769.18
Q3441685.99
95-th percentile442139.51
Maximum442636.32
Range5747.5466
Interquartile range (IQR)2418.2711

Descriptive statistics

Standard deviation1292.717
Coefficient of variation (CV)0.0029345004
Kurtosis-0.90776611
Mean440523.71
Median Absolute Deviation (MAD)1015.0652
Skewness-0.4753454
Sum1.1299433 × 109
Variance1671117.3
MonotonicityNot monotonic
2024-05-11T14:56:41.945343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
440728.382273075 64
 
2.4%
441716.684586176 46
 
1.8%
440940.384414334 37
 
1.4%
438865.160717275 37
 
1.4%
441982.427934953 34
 
1.3%
437914.06299827 32
 
1.2%
441784.247518723 28
 
1.1%
441920.972770099 26
 
1.0%
441687.841171831 25
 
1.0%
440808.541334678 24
 
0.9%
Other values (1122) 2212
84.5%
(Missing) 53
 
2.0%
ValueCountFrequency (%)
436888.773525926 2
0.1%
436893.312157815 1
 
< 0.1%
436897.466167682 1
 
< 0.1%
436909.870493711 1
 
< 0.1%
436946.358720615 4
0.2%
436946.60407049 2
0.1%
437199.30787957 1
 
< 0.1%
437280.574150819 3
0.1%
437299.637939286 1
 
< 0.1%
437560.573323753 1
 
< 0.1%
ValueCountFrequency (%)
442636.320100968 5
0.2%
442585.933234852 4
0.2%
442569.300676147 6
0.2%
442562.722742062 6
0.2%
442553.141302572 1
 
< 0.1%
442542.727581637 1
 
< 0.1%
442497.377672482 1
 
< 0.1%
442493.020182986 3
 
0.1%
442480.099547579 1
 
< 0.1%
442478.356256941 9
0.3%

위생업태명
Categorical

Distinct14
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
702 
커피숍
521 
일반조리판매
458 
다방
358 
편의점
225 
Other values (9)
354 

Length

Max length8
Median length6
Mean length4.1409473
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 702
26.8%
커피숍 521
19.9%
일반조리판매 458
17.5%
다방 358
13.7%
편의점 225
 
8.6%
기타 휴게음식점 198
 
7.6%
패스트푸드 118
 
4.5%
아이스크림 11
 
0.4%
푸드트럭 10
 
0.4%
과자점 6
 
0.2%
Other values (4) 11
 
0.4%

Length

2024-05-11T14:56:42.179441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 702
24.9%
커피숍 521
18.5%
일반조리판매 458
16.3%
다방 358
12.7%
편의점 225
 
8.0%
기타 198
 
7.0%
휴게음식점 198
 
7.0%
패스트푸드 118
 
4.2%
아이스크림 11
 
0.4%
푸드트럭 10
 
0.4%
Other values (5) 17
 
0.6%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
1841 
0
590 
1
 
155
2
 
24
5
 
5

Length

Max length4
Median length4
Mean length3.1096257
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row2
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
<NA> 1841
70.3%
0 590
 
22.5%
1 155
 
5.9%
2 24
 
0.9%
5 5
 
0.2%
3 3
 
0.1%

Length

2024-05-11T14:56:42.402647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:42.620010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1841
70.3%
0 590
 
22.5%
1 155
 
5.9%
2 24
 
0.9%
5 5
 
0.2%
3 3
 
0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.9%
Missing1849
Missing (%)70.6%
Infinite0
Infinite (%)0.0%
Mean0.92587776
Minimum0
Maximum6
Zeros482
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-05-11T14:56:42.799748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4283108
Coefficient of variation (CV)1.5426559
Kurtosis1.0881948
Mean0.92587776
Median Absolute Deviation (MAD)0
Skewness1.4317567
Sum712
Variance2.0400717
MonotonicityNot monotonic
2024-05-11T14:56:42.993503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 482
 
18.4%
3 86
 
3.3%
1 81
 
3.1%
2 67
 
2.6%
4 32
 
1.2%
5 15
 
0.6%
6 6
 
0.2%
(Missing) 1849
70.6%
ValueCountFrequency (%)
0 482
18.4%
1 81
 
3.1%
2 67
 
2.6%
3 86
 
3.3%
4 32
 
1.2%
5 15
 
0.6%
6 6
 
0.2%
ValueCountFrequency (%)
6 6
 
0.2%
5 15
 
0.6%
4 32
 
1.2%
3 86
 
3.3%
2 67
 
2.6%
1 81
 
3.1%
0 482
18.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
2177 
기타
318 
주택가주변
 
93
유흥업소밀집지역
 
14
아파트지역
 
14
Other values (2)
 
2

Length

Max length8
Median length4
Mean length3.8220015
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2177
83.2%
기타 318
 
12.1%
주택가주변 93
 
3.6%
유흥업소밀집지역 14
 
0.5%
아파트지역 14
 
0.5%
결혼예식장주변 1
 
< 0.1%
학교정화(상대) 1
 
< 0.1%

Length

2024-05-11T14:56:43.198864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:43.369659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2177
83.2%
기타 318
 
12.1%
주택가주변 93
 
3.6%
유흥업소밀집지역 14
 
0.5%
아파트지역 14
 
0.5%
결혼예식장주변 1
 
< 0.1%
학교정화(상대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
2197 
을
 
184
지도
 
98
기타
 
85
자율
 
38
Other values (2)
 
16

Length

Max length4
Median length4
Mean length3.6035141
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2197
83.9%
을 184
 
7.0%
지도 98
 
3.7%
기타 85
 
3.2%
자율 38
 
1.5%
갑 12
 
0.5%
우수 4
 
0.2%

Length

2024-05-11T14:56:43.596813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:43.762291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2197
83.9%
을 184
 
7.0%
지도 98
 
3.7%
기타 85
 
3.2%
자율 38
 
1.5%
갑 12
 
0.5%
우수 4
 
0.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
1660 
상수도전용
955 
지하수전용
 
2
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.3705118
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1660
63.4%
상수도전용 955
36.5%
지하수전용 2
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-05-11T14:56:43.953296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:44.161569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1660
63.4%
상수도전용 955
36.5%
지하수전용 2
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
2462 
0
 
156

Length

Max length4
Median length4
Mean length3.8212376
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> 2462
94.0%
0 156
 
6.0%

Length

2024-05-11T14:56:44.363557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:44.504025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
94.0%
0 156
 
6.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
2462 
0
 
156

Length

Max length4
Median length4
Mean length3.8212376
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> 2462
94.0%
0 156
 
6.0%

Length

2024-05-11T14:56:44.678562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:44.849866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
94.0%
0 156
 
6.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
2462 
0
 
156

Length

Max length4
Median length4
Mean length3.8212376
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> 2462
94.0%
0 156
 
6.0%

Length

2024-05-11T14:56:45.029518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:45.206834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
94.0%
0 156
 
6.0%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
2462 
0
 
156

Length

Max length4
Median length4
Mean length3.8212376
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> 2462
94.0%
0 156
 
6.0%

Length

2024-05-11T14:56:45.386310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:45.557616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
94.0%
0 156
 
6.0%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
2462 
0
 
156

Length

Max length4
Median length4
Mean length3.8212376
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> 2462
94.0%
0 156
 
6.0%

Length

2024-05-11T14:56:45.810460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:45.981924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
94.0%
0 156
 
6.0%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
2462 
0
 
156

Length

Max length4
Median length4
Mean length3.8212376
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> 2462
94.0%
0 156
 
6.0%

Length

2024-05-11T14:56:46.188972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:46.352168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
94.0%
0 156
 
6.0%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
<NA>
2462 
0
 
156

Length

Max length4
Median length4
Mean length3.8212376
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> 2462
94.0%
0 156
 
6.0%

Length

2024-05-11T14:56:46.533850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:46.721274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
94.0%
0 156
 
6.0%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing702
Missing (%)26.8%
Memory size5.2 KiB
False
1902 
True
 
14
(Missing)
702 
ValueCountFrequency (%)
False 1902
72.7%
True 14
 
0.5%
(Missing) 702
 
26.8%
2024-05-11T14:56:46.859759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct1322
Distinct (%)69.0%
Missing702
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean42.884243
Minimum0
Maximum530
Zeros24
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2024-05-11T14:56:47.043852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q113.2
median29.64
Q362.53
95-th percentile115.585
Maximum530
Range530
Interquartile range (IQR)49.33

Descriptive statistics

Standard deviation43.031326
Coefficient of variation (CV)1.0034298
Kurtosis17.27945
Mean42.884243
Median Absolute Deviation (MAD)20.99
Skewness2.8319082
Sum82166.21
Variance1851.695
MonotonicityNot monotonic
2024-05-11T14:56:47.327624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 115
 
4.4%
3.0 30
 
1.1%
6.6 29
 
1.1%
0.0 24
 
0.9%
33.0 22
 
0.8%
9.9 21
 
0.8%
10.0 14
 
0.5%
16.5 10
 
0.4%
30.0 10
 
0.4%
4.0 10
 
0.4%
Other values (1312) 1631
62.3%
(Missing) 702
26.8%
ValueCountFrequency (%)
0.0 24
0.9%
0.25 1
 
< 0.1%
0.4 3
 
0.1%
0.5 1
 
< 0.1%
0.61 1
 
< 0.1%
0.75 1
 
< 0.1%
0.79 1
 
< 0.1%
0.85 1
 
< 0.1%
1.0 3
 
0.1%
1.04 1
 
< 0.1%
ValueCountFrequency (%)
530.0 1
< 0.1%
468.13 1
< 0.1%
304.8 1
< 0.1%
280.53 1
< 0.1%
279.43 1
< 0.1%
261.92 1
< 0.1%
257.86 1
< 0.1%
252.39 1
< 0.1%
248.8 1
< 0.1%
243.9 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2618
Missing (%)100.0%
Memory size23.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031700003170000-104-1970-0023019701106<NA>3폐업2폐업20120430<NA><NA><NA>02137.7153864서울특별시 금천구 시흥동 994-12번지 지하1층 (시흥대로 464)<NA><NA>프로포즈커피숍2011-10-31 12:20:40I2018-08-31 23:59:59.0다방191131.648026439063.152473다방04기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N137.7<NA><NA><NA>
131700003170000-104-1970-0039719700820<NA>3폐업2폐업20030220<NA><NA><NA>0208550921112.33153806서울특별시 금천구 독산동 144-23번지<NA><NA>수정2005-08-22 00:00:00I2018-08-31 23:59:59.0다방190777.422167441613.844605다방24기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N112.33<NA><NA><NA>
231700003170000-104-1972-0013019720825<NA>3폐업2폐업20000426<NA><NA><NA>0299.44153813서울특별시 금천구 독산동 331-4번지<NA><NA>수연2000-04-26 00:00:00I2018-08-31 23:59:59.0다방190556.878611440604.776753다방12기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N99.44<NA><NA><NA>
331700003170000-104-1973-0019819731011<NA>3폐업2폐업19971008<NA><NA><NA>02 802511983.18153841서울특별시 금천구 시흥동 831-6번지<NA><NA>은다실2005-08-22 00:00:00I2018-08-31 23:59:59.0다방191823.02685438834.378061다방00주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N83.18<NA><NA><NA>
431700003170000-104-1973-0040319730509<NA>3폐업2폐업20030220<NA><NA><NA>0208070303126.32153858서울특별시 금천구 시흥동 883-11번지<NA><NA>응접실2005-08-22 00:00:00I2018-08-31 23:59:59.0다방191203.246076439087.640568다방16유흥업소밀집지역을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N126.32<NA><NA><NA>
531700003170000-104-1974-0018119741120<NA>3폐업2폐업20000309<NA><NA><NA>02106.0153858서울특별시 금천구 시흥동 883-7번지<NA><NA>썬2001-09-21 00:00:00I2018-08-31 23:59:59.0다방191197.770239439125.639918다방15기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N106.0<NA><NA><NA>
631700003170000-104-1974-0039819741205<NA>3폐업2폐업20070115<NA><NA><NA>0208056954129.23153829서울특별시 금천구 독산동 1009-74번지<NA><NA>다모아2007-01-15 00:00:00I2018-08-31 23:59:59.0다방190826.067032440219.136513다방24기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N129.23<NA><NA><NA>
731700003170000-104-1975-0039619750511<NA>3폐업2폐업20021220<NA><NA><NA>0208568200105.49153823서울특별시 금천구 독산동 967-9번지<NA><NA>유창2005-08-22 00:00:00I2018-08-31 23:59:59.0다방190999.108992441526.689933다방13기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N105.49<NA><NA><NA>
831700003170000-104-1976-0009419760901<NA>3폐업2폐업19990911<NA><NA><NA>02 856180890.47153806서울특별시 금천구 독산동 146-1번지<NA><NA>VAN(벤)1999-09-14 00:00:00I2018-08-31 23:59:59.0다방190923.96368441510.743691다방12기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N90.47<NA><NA><NA>
931700003170000-104-1976-0009719760806<NA>3폐업2폐업19980108<NA><NA><NA>02 856877291.12153800서울특별시 금천구 가산동 42-32번지<NA><NA>소금창고커피숍2005-08-22 00:00:00I2018-08-31 23:59:59.0다방189592.005791442206.954607다방02기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N91.12<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
260831700003170000-104-2024-000342024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0153-801서울특별시 금천구 가산동 219-5 가산테라타워서울특별시 금천구 디지털로10길 78, 가산테라타워 1층 114호 (가산동)8517GS25가산테라타워점2024-04-15 16:41:42I2023-12-03 23:07:00.0커피숍190185.054136441381.452927<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
260931700003170000-104-2024-000352024-04-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.0153-864서울특별시 금천구 시흥동 994-8서울특별시 금천구 시흥대로61길 5, 1호 (시흥동)8632미소마트2024-04-16 15:10:21I2023-12-03 23:08:00.0커피숍191103.758271439103.0362<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261031700003170000-104-2024-000362024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3153-825서울특별시 금천구 독산동 978-20서울특별시 금천구 독산로93길 12, 1층 일부호 (독산동)8542씨유 금천반수공원점2024-04-25 17:06:49I2023-12-03 22:07:00.0편의점191317.655684441321.651723<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261131700003170000-104-2024-000372024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>82.22153-806서울특별시 금천구 독산동 148-30서울특별시 금천구 시흥대로139길 36, 101호 (독산동)8533데일리 브레드2024-04-29 10:45:35I2023-12-05 00:01:00.0커피숍190719.577046441207.159262<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261231700003170000-104-2024-000382024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>43.1153-856서울특별시 금천구 시흥동 838-2서울특별시 금천구 독산로 69, 1층 (시흥동)8627전가당2024-04-29 10:56:05I2023-12-05 00:01:00.0기타 휴게음식점191606.939761439051.383272<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261331700003170000-104-2024-000392024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>34.0153-806서울특별시 금천구 독산동 148-1서울특별시 금천구 시흥대로149길 63, 호암아크빌 1층 (독산동)8533D149632024-04-30 09:34:27I2023-12-05 00:02:00.0커피숍190614.660766441396.627159<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261431700003170000-104-2024-000402024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>52.18153-803서울특별시 금천구 가산동 673서울특별시 금천구 가산디지털1로 16, 에이피타워 1층 116-R호 (가산동)8591더벤티 가산AP타워점2024-04-30 11:47:31I2023-12-05 00:02:00.0커피숍190021.956927440609.209534<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261531700003170000-104-2024-000412024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>146.08153-813서울특별시 금천구 독산동 291-1 현대지식산업센터서울특별시 금천구 두산로 70, 현대지식산업센터 제티135호 (독산동)8584파머스포케 독산점2024-05-02 13:36:37I2023-12-05 00:04:00.0커피숍190694.880295440764.426278<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261631700003170000-104-2024-000422024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>52.33153-803서울특별시 금천구 가산동 371-41 가산 SK V1 CENTER서울특별시 금천구 가산디지털1로 171, 가산 SK V1 CENTER 105호 (가산동)8503샐러디 가산디지털단지점2024-05-08 11:39:43I2023-12-04 23:00:00.0커피숍189378.332494442066.998665<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261731700003170000-104-2024-000432024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>94.6153-803서울특별시 금천구 가산동 459-14서울특별시 금천구 가산디지털2로 144, 1층 104호 (가산동)8503설빙 금천가산점2024-05-09 14:52:46I2023-12-04 23:01:00.0커피숍189262.863258442093.310518<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>