Overview

Dataset statistics

Number of variables44
Number of observations3607
Missing cells41210
Missing cells (%)26.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory377.0 B

Variable types

Categorical18
Text6
DateTime4
Unsupported8
Numeric7
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-18679/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (50.2%)Imbalance
등급구분명 is highly imbalanced (57.5%)Imbalance
총인원 is highly imbalanced (75.3%)Imbalance
본사종업원수 is highly imbalanced (74.9%)Imbalance
공장사무직종업원수 is highly imbalanced (74.9%)Imbalance
공장판매직종업원수 is highly imbalanced (74.9%)Imbalance
공장생산직종업원수 is highly imbalanced (74.9%)Imbalance
보증액 is highly imbalanced (74.9%)Imbalance
월세액 is highly imbalanced (74.9%)Imbalance
다중이용업소여부 is highly imbalanced (93.0%)Imbalance
인허가취소일자 has 3607 (100.0%) missing valuesMissing
폐업일자 has 1093 (30.3%) missing valuesMissing
휴업시작일자 has 3607 (100.0%) missing valuesMissing
휴업종료일자 has 3607 (100.0%) missing valuesMissing
재개업일자 has 3607 (100.0%) missing valuesMissing
전화번호 has 1895 (52.5%) missing valuesMissing
소재지면적 has 130 (3.6%) missing valuesMissing
도로명주소 has 1258 (34.9%) missing valuesMissing
도로명우편번호 has 1269 (35.2%) missing valuesMissing
좌표정보(X) has 115 (3.2%) missing valuesMissing
좌표정보(Y) has 115 (3.2%) missing valuesMissing
남성종사자수 has 2359 (65.4%) missing valuesMissing
여성종사자수 has 2356 (65.3%) missing valuesMissing
건물소유구분명 has 3607 (100.0%) missing valuesMissing
다중이용업소여부 has 882 (24.5%) missing valuesMissing
시설총규모 has 882 (24.5%) missing valuesMissing
전통업소지정번호 has 3607 (100.0%) missing valuesMissing
전통업소주된음식 has 3607 (100.0%) missing valuesMissing
홈페이지 has 3607 (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
남성종사자수 has 1085 (30.1%) zerosZeros
여성종사자수 has 795 (22.0%) zerosZeros

Reproduction

Analysis started2024-05-11 06:35:56.366034
Analysis finished2024-05-11 06:35:58.292267
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
3020000
3607 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 3607
100.0%

Length

2024-05-11T15:35:58.369349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:58.490403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 3607
100.0%

관리번호
Text

UNIQUE 

Distinct3607
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2024-05-11T15:35:58.703915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters79354
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

Unique3607 ?
Unique (%)100.0%

Sample

1st row3020000-104-1966-02732
2nd row3020000-104-1967-02566
3rd row3020000-104-1967-02622
4th row3020000-104-1967-02733
5th row3020000-104-1967-02779
ValueCountFrequency (%)
3020000-104-1966-02732 1
 
< 0.1%
3020000-104-2016-00070 1
 
< 0.1%
3020000-104-2017-00072 1
 
< 0.1%
3020000-104-2017-00061 1
 
< 0.1%
3020000-104-2017-00062 1
 
< 0.1%
3020000-104-2017-00063 1
 
< 0.1%
3020000-104-2017-00064 1
 
< 0.1%
3020000-104-2017-00065 1
 
< 0.1%
3020000-104-2017-00066 1
 
< 0.1%
3020000-104-2017-00067 1
 
< 0.1%
Other values (3597) 3597
99.7%
2024-05-11T15:35:59.129777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34694
43.7%
- 10821
 
13.6%
2 9125
 
11.5%
1 7760
 
9.8%
3 5115
 
6.4%
4 4873
 
6.1%
9 2244
 
2.8%
7 1273
 
1.6%
8 1256
 
1.6%
5 1116
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68533
86.4%
Dash Punctuation 10821
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34694
50.6%
2 9125
 
13.3%
1 7760
 
11.3%
3 5115
 
7.5%
4 4873
 
7.1%
9 2244
 
3.3%
7 1273
 
1.9%
8 1256
 
1.8%
5 1116
 
1.6%
6 1077
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 10821
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79354
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34694
43.7%
- 10821
 
13.6%
2 9125
 
11.5%
1 7760
 
9.8%
3 5115
 
6.4%
4 4873
 
6.1%
9 2244
 
2.8%
7 1273
 
1.6%
8 1256
 
1.6%
5 1116
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34694
43.7%
- 10821
 
13.6%
2 9125
 
11.5%
1 7760
 
9.8%
3 5115
 
6.4%
4 4873
 
6.1%
9 2244
 
2.8%
7 1273
 
1.6%
8 1256
 
1.6%
5 1116
 
1.4%

인허가일자
Date

Distinct2784
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
Minimum1966-12-20 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:35:59.309127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:59.480266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3607
Missing (%)100.0%
Memory size31.8 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
3
2514 
1
1093 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2514
69.7%
1 1093
30.3%

Length

2024-05-11T15:36:00.069297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:00.199486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2514
69.7%
1 1093
30.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
폐업
2514 
영업/정상
1093 

Length

Max length5
Median length2
Mean length2.9090657
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2514
69.7%
영업/정상 1093
30.3%

Length

2024-05-11T15:36:00.358587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:00.509307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2514
69.7%
영업/정상 1093
30.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2
2514 
1
1093 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 2514
69.7%
1 1093
30.3%

Length

2024-05-11T15:36:00.640400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:00.799461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2514
69.7%
1 1093
30.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
폐업
2514 
영업
1093 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2514
69.7%
영업 1093
30.3%

Length

2024-05-11T15:36:00.940522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:01.126522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2514
69.7%
영업 1093
30.3%

폐업일자
Date

MISSING 

Distinct1970
Distinct (%)78.4%
Missing1093
Missing (%)30.3%
Memory size28.3 KiB
Minimum1988-12-17 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:36:01.294374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:01.505051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3607
Missing (%)100.0%
Memory size31.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3607
Missing (%)100.0%
Memory size31.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3607
Missing (%)100.0%
Memory size31.8 KiB

전화번호
Text

MISSING 

Distinct1485
Distinct (%)86.7%
Missing1895
Missing (%)52.5%
Memory size28.3 KiB
2024-05-11T15:36:01.794747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9065421
Min length2

Characters and Unicode

Total characters16960
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

Unique1429 ?
Unique (%)83.5%

Sample

1st row02 7956111
2nd row02 7944344
3rd row0207951990
4th row0207133333
5th row0207137463
ValueCountFrequency (%)
02 1119
37.2%
0200000000 30
 
1.0%
070 29
 
1.0%
00000 23
 
0.8%
790 23
 
0.8%
797 20
 
0.7%
0 17
 
0.6%
794 17
 
0.6%
749 12
 
0.4%
795 11
 
0.4%
Other values (1538) 1705
56.7%
2024-05-11T15:36:02.255175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3626
21.4%
2 2621
15.5%
7 2220
13.1%
1679
9.9%
9 1287
 
7.6%
1 1163
 
6.9%
3 952
 
5.6%
5 936
 
5.5%
4 930
 
5.5%
8 821
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15281
90.1%
Space Separator 1679
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3626
23.7%
2 2621
17.2%
7 2220
14.5%
9 1287
 
8.4%
1 1163
 
7.6%
3 952
 
6.2%
5 936
 
6.1%
4 930
 
6.1%
8 821
 
5.4%
6 725
 
4.7%
Space Separator
ValueCountFrequency (%)
1679
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16960
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3626
21.4%
2 2621
15.5%
7 2220
13.1%
1679
9.9%
9 1287
 
7.6%
1 1163
 
6.9%
3 952
 
5.6%
5 936
 
5.5%
4 930
 
5.5%
8 821
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3626
21.4%
2 2621
15.5%
7 2220
13.1%
1679
9.9%
9 1287
 
7.6%
1 1163
 
6.9%
3 952
 
5.6%
5 936
 
5.5%
4 930
 
5.5%
8 821
 
4.8%

소재지면적
Real number (ℝ)

MISSING 

Distinct2048
Distinct (%)58.9%
Missing130
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean50.760966
Minimum0
Maximum1116.19
Zeros7
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-05-11T15:36:02.453269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q115.2
median33
Q365.36
95-th percentile152.41
Maximum1116.19
Range1116.19
Interquartile range (IQR)50.16

Descriptive statistics

Standard deviation61.441445
Coefficient of variation (CV)1.2104073
Kurtosis45.761083
Mean50.760966
Median Absolute Deviation (MAD)21.69
Skewness4.7599115
Sum176495.88
Variance3775.0511
MonotonicityNot monotonic
2024-05-11T15:36:02.653011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 135
 
3.7%
6.6 109
 
3.0%
10.0 59
 
1.6%
33.0 39
 
1.1%
9.9 32
 
0.9%
13.2 31
 
0.9%
26.4 27
 
0.7%
15.0 26
 
0.7%
16.5 25
 
0.7%
20.0 24
 
0.7%
Other values (2038) 2970
82.3%
(Missing) 130
 
3.6%
ValueCountFrequency (%)
0.0 7
0.2%
0.8 1
 
< 0.1%
1.0 1
 
< 0.1%
1.5 1
 
< 0.1%
1.89 1
 
< 0.1%
2.0 8
0.2%
2.04 1
 
< 0.1%
2.24 1
 
< 0.1%
2.25 1
 
< 0.1%
2.27 1
 
< 0.1%
ValueCountFrequency (%)
1116.19 1
< 0.1%
836.82 1
< 0.1%
591.0 1
< 0.1%
579.27 1
< 0.1%
520.0 1
< 0.1%
505.65 1
< 0.1%
486.0 1
< 0.1%
476.87 2
0.1%
455.12 1
< 0.1%
447.93 1
< 0.1%

소재지우편번호
Text

Distinct239
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2024-05-11T15:36:03.167303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1721652
Min length6

Characters and Unicode

Total characters22263
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

Unique45 ?
Unique (%)1.2%

Sample

1st row140011
2nd row140871
3rd row140160
4th row140847
5th row140100
ValueCountFrequency (%)
140780 203
 
5.6%
140-780 129
 
3.6%
140132 128
 
3.5%
140133 87
 
2.4%
140893 83
 
2.3%
140821 82
 
2.3%
140863 82
 
2.3%
140871 75
 
2.1%
140823 68
 
1.9%
140858 68
 
1.9%
Other values (229) 2602
72.1%
2024-05-11T15:36:03.862933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5075
22.8%
1 4728
21.2%
4 4003
18.0%
8 3018
13.6%
7 1037
 
4.7%
3 1016
 
4.6%
2 977
 
4.4%
9 765
 
3.4%
- 621
 
2.8%
6 576
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21642
97.2%
Dash Punctuation 621
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5075
23.4%
1 4728
21.8%
4 4003
18.5%
8 3018
13.9%
7 1037
 
4.8%
3 1016
 
4.7%
2 977
 
4.5%
9 765
 
3.5%
6 576
 
2.7%
5 447
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 621
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22263
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5075
22.8%
1 4728
21.2%
4 4003
18.0%
8 3018
13.6%
7 1037
 
4.7%
3 1016
 
4.6%
2 977
 
4.4%
9 765
 
3.4%
- 621
 
2.8%
6 576
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22263
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5075
22.8%
1 4728
21.2%
4 4003
18.0%
8 3018
13.6%
7 1037
 
4.7%
3 1016
 
4.6%
2 977
 
4.4%
9 765
 
3.4%
- 621
 
2.8%
6 576
 
2.6%

지번주소
Text

Distinct2958
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2024-05-11T15:36:04.245388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length26.611589
Min length14

Characters and Unicode

Total characters95988
Distinct characters377
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2666 ?
Unique (%)73.9%

Sample

1st row서울특별시 용산구 한강로1가 23-1번지
2nd row서울특별시 용산구 한강로2가 351-0번지
3rd row서울특별시 용산구 남영동 94-6번지
4th row서울특별시 용산구 원효로2가 86-8번지
5th row서울특별시 용산구 문배동 11-0번지
ValueCountFrequency (%)
용산구 3608
20.9%
서울특별시 3607
20.9%
지상1층 540
 
3.1%
한강로3가 522
 
3.0%
한남동 403
 
2.3%
이태원동 370
 
2.1%
한강로2가 294
 
1.7%
이촌동 220
 
1.3%
40-999 219
 
1.3%
용산역 196
 
1.1%
Other values (2887) 7317
42.3%
2024-05-11T15:36:04.831719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16345
 
17.0%
1 4412
 
4.6%
용 4241
 
4.4%
산 4204
 
4.4%
서 3748
 
3.9%
시 3655
 
3.8%
울 3646
 
3.8%
구 3619
 
3.8%
특 3609
 
3.8%
별 3609
 
3.8%
Other values (367) 44900
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55384
57.7%
Decimal Number 19249
 
20.1%
Space Separator 16345
 
17.0%
Dash Punctuation 3372
 
3.5%
Close Punctuation 690
 
0.7%
Open Punctuation 690
 
0.7%
Other Punctuation 116
 
0.1%
Uppercase Letter 109
 
0.1%
Lowercase Letter 27
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 4241
 
7.7%
산 4204
 
7.6%
서 3748
 
6.8%
시 3655
 
6.6%
울 3646
 
6.6%
구 3619
 
6.5%
특 3609
 
6.5%
별 3609
 
6.5%
지 3430
 
6.2%
동 2818
 
5.1%
Other values (316) 18805
34.0%
Uppercase Letter
ValueCountFrequency (%)
B 32
29.4%
A 10
 
9.2%
C 8
 
7.3%
D 8
 
7.3%
T 8
 
7.3%
K 6
 
5.5%
P 5
 
4.6%
Y 4
 
3.7%
N 4
 
3.7%
S 4
 
3.7%
Other values (11) 20
18.3%
Lowercase Letter
ValueCountFrequency (%)
c 4
14.8%
o 3
11.1%
i 3
11.1%
r 3
11.1%
e 3
11.1%
l 3
11.1%
t 2
7.4%
k 2
7.4%
s 1
 
3.7%
p 1
 
3.7%
Other values (2) 2
7.4%
Decimal Number
ValueCountFrequency (%)
1 4412
22.9%
2 2934
15.2%
3 2513
13.1%
9 1793
9.3%
0 1742
 
9.0%
4 1679
 
8.7%
6 1258
 
6.5%
5 1207
 
6.3%
7 906
 
4.7%
8 805
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 113
97.4%
. 2
 
1.7%
/ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
16345
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3372
100.0%
Close Punctuation
ValueCountFrequency (%)
) 690
100.0%
Open Punctuation
ValueCountFrequency (%)
( 690
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55384
57.7%
Common 40468
42.2%
Latin 136
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 4241
 
7.7%
산 4204
 
7.6%
서 3748
 
6.8%
시 3655
 
6.6%
울 3646
 
6.6%
구 3619
 
6.5%
특 3609
 
6.5%
별 3609
 
6.5%
지 3430
 
6.2%
동 2818
 
5.1%
Other values (316) 18805
34.0%
Latin
ValueCountFrequency (%)
B 32
23.5%
A 10
 
7.4%
C 8
 
5.9%
D 8
 
5.9%
T 8
 
5.9%
K 6
 
4.4%
P 5
 
3.7%
c 4
 
2.9%
Y 4
 
2.9%
N 4
 
2.9%
Other values (23) 47
34.6%
Common
ValueCountFrequency (%)
16345
40.4%
1 4412
 
10.9%
- 3372
 
8.3%
2 2934
 
7.3%
3 2513
 
6.2%
9 1793
 
4.4%
0 1742
 
4.3%
4 1679
 
4.1%
6 1258
 
3.1%
5 1207
 
3.0%
Other values (8) 3213
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55383
57.7%
ASCII 40604
42.3%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16345
40.3%
1 4412
 
10.9%
- 3372
 
8.3%
2 2934
 
7.2%
3 2513
 
6.2%
9 1793
 
4.4%
0 1742
 
4.3%
4 1679
 
4.1%
6 1258
 
3.1%
5 1207
 
3.0%
Other values (41) 3349
 
8.2%
Hangul
ValueCountFrequency (%)
용 4241
 
7.7%
산 4204
 
7.6%
서 3748
 
6.8%
시 3655
 
6.6%
울 3646
 
6.6%
구 3619
 
6.5%
특 3609
 
6.5%
별 3609
 
6.5%
지 3430
 
6.2%
동 2818
 
5.1%
Other values (315) 18804
34.0%
Compat Jamo
ValueCountFrequency (%)
ㅊ 1
100.0%

도로명주소
Text

MISSING 

Distinct2080
Distinct (%)88.5%
Missing1258
Missing (%)34.9%
Memory size28.3 KiB
2024-05-11T15:36:05.304193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length56
Mean length35.750106
Min length22

Characters and Unicode

Total characters83977
Distinct characters381
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

Unique1938 ?
Unique (%)82.5%

Sample

1st row서울특별시 용산구 한강대로80길 10 (남영동)
2nd row서울특별시 용산구 효창원로69길 4 (효창동)
3rd row서울특별시 용산구 이촌로18길 6 (이촌동)
4th row서울특별시 용산구 보광로 30 (보광동)
5th row서울특별시 용산구 한강대로 341 (갈월동)
ValueCountFrequency (%)
용산구 2350
 
14.9%
서울특별시 2349
 
14.9%
1층 801
 
5.1%
한강로3가 395
 
2.5%
55 298
 
1.9%
한강대로23길 291
 
1.8%
지상1층 274
 
1.7%
한남동 230
 
1.5%
이태원동 225
 
1.4%
한강대로 207
 
1.3%
Other values (1853) 8324
52.9%
2024-05-11T15:36:05.991579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13395
 
16.0%
1 3933
 
4.7%
로 3113
 
3.7%
용 2837
 
3.4%
산 2811
 
3.3%
, 2739
 
3.3%
) 2605
 
3.1%
( 2605
 
3.1%
서 2565
 
3.1%
2 2441
 
2.9%
Other values (371) 44933
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47494
56.6%
Decimal Number 14393
 
17.1%
Space Separator 13395
 
16.0%
Other Punctuation 2748
 
3.3%
Close Punctuation 2605
 
3.1%
Open Punctuation 2605
 
3.1%
Dash Punctuation 535
 
0.6%
Uppercase Letter 177
 
0.2%
Lowercase Letter 18
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 3113
 
6.6%
용 2837
 
6.0%
산 2811
 
5.9%
서 2565
 
5.4%
시 2395
 
5.0%
울 2394
 
5.0%
구 2358
 
5.0%
별 2352
 
5.0%
특 2351
 
5.0%
층 2214
 
4.7%
Other values (322) 22104
46.5%
Uppercase Letter
ValueCountFrequency (%)
B 74
41.8%
D 20
 
11.3%
C 17
 
9.6%
A 9
 
5.1%
F 7
 
4.0%
N 6
 
3.4%
H 6
 
3.4%
K 5
 
2.8%
S 5
 
2.8%
T 4
 
2.3%
Other values (11) 24
 
13.6%
Decimal Number
ValueCountFrequency (%)
1 3933
27.3%
2 2441
17.0%
3 1794
12.5%
5 1334
 
9.3%
4 1151
 
8.0%
0 1091
 
7.6%
7 906
 
6.3%
6 699
 
4.9%
9 543
 
3.8%
8 501
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
c 5
27.8%
e 3
16.7%
l 3
16.7%
i 2
 
11.1%
k 2
 
11.1%
t 1
 
5.6%
r 1
 
5.6%
o 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 2739
99.7%
& 5
 
0.2%
. 2
 
0.1%
? 1
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
13395
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2605
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2605
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 535
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47494
56.6%
Common 36288
43.2%
Latin 195
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 3113
 
6.6%
용 2837
 
6.0%
산 2811
 
5.9%
서 2565
 
5.4%
시 2395
 
5.0%
울 2394
 
5.0%
구 2358
 
5.0%
별 2352
 
5.0%
특 2351
 
5.0%
층 2214
 
4.7%
Other values (322) 22104
46.5%
Latin
ValueCountFrequency (%)
B 74
37.9%
D 20
 
10.3%
C 17
 
8.7%
A 9
 
4.6%
F 7
 
3.6%
N 6
 
3.1%
H 6
 
3.1%
K 5
 
2.6%
c 5
 
2.6%
S 5
 
2.6%
Other values (19) 41
21.0%
Common
ValueCountFrequency (%)
13395
36.9%
1 3933
 
10.8%
, 2739
 
7.5%
) 2605
 
7.2%
( 2605
 
7.2%
2 2441
 
6.7%
3 1794
 
4.9%
5 1334
 
3.7%
4 1151
 
3.2%
0 1091
 
3.0%
Other values (10) 3200
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47494
56.6%
ASCII 36483
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13395
36.7%
1 3933
 
10.8%
, 2739
 
7.5%
) 2605
 
7.1%
( 2605
 
7.1%
2 2441
 
6.7%
3 1794
 
4.9%
5 1334
 
3.7%
4 1151
 
3.2%
0 1091
 
3.0%
Other values (39) 3395
 
9.3%
Hangul
ValueCountFrequency (%)
로 3113
 
6.6%
용 2837
 
6.0%
산 2811
 
5.9%
서 2565
 
5.4%
시 2395
 
5.0%
울 2394
 
5.0%
구 2358
 
5.0%
별 2352
 
5.0%
특 2351
 
5.0%
층 2214
 
4.7%
Other values (322) 22104
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct124
Distinct (%)5.3%
Missing1269
Missing (%)35.2%
Infinite0
Infinite (%)0.0%
Mean4361.3426
Minimum4300
Maximum4428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-05-11T15:36:06.317125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4300
5-th percentile4309
Q14332
median4370
Q34385
95-th percentile4419
Maximum4428
Range128
Interquartile range (IQR)53

Descriptive statistics

Standard deviation34.579995
Coefficient of variation (CV)0.0079287499
Kurtosis-1.0092051
Mean4361.3426
Median Absolute Deviation (MAD)26
Skewness-0.060199195
Sum10196819
Variance1195.776
MonotonicityNot monotonic
2024-05-11T15:36:06.665485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4377 292
 
8.1%
4382 74
 
2.1%
4313 63
 
1.7%
4345 51
 
1.4%
4310 48
 
1.3%
4378 46
 
1.3%
4401 42
 
1.2%
4400 41
 
1.1%
4363 40
 
1.1%
4309 37
 
1.0%
Other values (114) 1604
44.5%
(Missing) 1269
35.2%
ValueCountFrequency (%)
4300 15
0.4%
4301 37
1.0%
4302 7
 
0.2%
4303 9
 
0.2%
4304 10
 
0.3%
4305 19
0.5%
4306 5
 
0.1%
4307 3
 
0.1%
4308 6
 
0.2%
4309 37
1.0%
ValueCountFrequency (%)
4428 8
 
0.2%
4427 25
0.7%
4426 28
0.8%
4425 8
 
0.2%
4424 9
 
0.2%
4423 19
0.5%
4422 3
 
0.1%
4420 11
 
0.3%
4419 26
0.7%
4418 3
 
0.1%

사업장명
Text

Distinct3308
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2024-05-11T15:36:07.178906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length28
Mean length7.2653174
Min length1

Characters and Unicode

Total characters26206
Distinct characters871
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3105 ?
Unique (%)86.1%

Sample

1st row동심
2nd row여백
3rd row귀향
4th row해림
5th row중원
ValueCountFrequency (%)
세븐일레븐 33
 
0.8%
씨유 27
 
0.6%
주식회사 19
 
0.4%
지에스25 19
 
0.4%
coffee 17
 
0.4%
리은푸드 17
 
0.4%
카페 16
 
0.4%
gs25 15
 
0.3%
용산아이파크몰점 15
 
0.3%
용산점 14
 
0.3%
Other values (3599) 4207
95.6%
2024-05-11T15:36:07.879849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 897
 
3.4%
이 839
 
3.2%
스 809
 
3.1%
793
 
3.0%
) 543
 
2.1%
( 542
 
2.1%
리 487
 
1.9%
산 401
 
1.5%
피 379
 
1.4%
용 369
 
1.4%
Other values (861) 20147
76.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20945
79.9%
Lowercase Letter 1579
 
6.0%
Uppercase Letter 1212
 
4.6%
Space Separator 793
 
3.0%
Close Punctuation 543
 
2.1%
Open Punctuation 542
 
2.1%
Decimal Number 484
 
1.8%
Other Punctuation 92
 
0.4%
Dash Punctuation 15
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 897
 
4.3%
이 839
 
4.0%
스 809
 
3.9%
리 487
 
2.3%
산 401
 
1.9%
피 379
 
1.8%
용 369
 
1.8%
아 329
 
1.6%
레 311
 
1.5%
커 307
 
1.5%
Other values (783) 15817
75.5%
Lowercase Letter
ValueCountFrequency (%)
e 247
15.6%
a 158
 
10.0%
o 149
 
9.4%
r 106
 
6.7%
i 95
 
6.0%
n 87
 
5.5%
f 85
 
5.4%
t 82
 
5.2%
s 77
 
4.9%
c 68
 
4.3%
Other values (16) 425
26.9%
Uppercase Letter
ValueCountFrequency (%)
C 120
 
9.9%
S 115
 
9.5%
A 92
 
7.6%
O 89
 
7.3%
E 83
 
6.8%
G 80
 
6.6%
R 68
 
5.6%
T 65
 
5.4%
L 59
 
4.9%
F 51
 
4.2%
Other values (16) 390
32.2%
Other Punctuation
ValueCountFrequency (%)
. 27
29.3%
& 22
23.9%
, 18
19.6%
' 10
 
10.9%
: 4
 
4.3%
? 4
 
4.3%
! 3
 
3.3%
/ 1
 
1.1%
% 1
 
1.1%
# 1
 
1.1%
Decimal Number
ValueCountFrequency (%)
2 170
35.1%
5 118
24.4%
1 55
 
11.4%
4 39
 
8.1%
3 28
 
5.8%
9 20
 
4.1%
0 20
 
4.1%
7 13
 
2.7%
6 11
 
2.3%
8 10
 
2.1%
Space Separator
ValueCountFrequency (%)
793
100.0%
Close Punctuation
ValueCountFrequency (%)
) 543
100.0%
Open Punctuation
ValueCountFrequency (%)
( 542
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20940
79.9%
Latin 2792
 
10.7%
Common 2469
 
9.4%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 897
 
4.3%
이 839
 
4.0%
스 809
 
3.9%
리 487
 
2.3%
산 401
 
1.9%
피 379
 
1.8%
용 369
 
1.8%
아 329
 
1.6%
레 311
 
1.5%
커 307
 
1.5%
Other values (778) 15812
75.5%
Latin
ValueCountFrequency (%)
e 247
 
8.8%
a 158
 
5.7%
o 149
 
5.3%
C 120
 
4.3%
S 115
 
4.1%
r 106
 
3.8%
i 95
 
3.4%
A 92
 
3.3%
O 89
 
3.2%
n 87
 
3.1%
Other values (43) 1534
54.9%
Common
ValueCountFrequency (%)
793
32.1%
) 543
22.0%
( 542
22.0%
2 170
 
6.9%
5 118
 
4.8%
1 55
 
2.2%
4 39
 
1.6%
3 28
 
1.1%
. 27
 
1.1%
& 22
 
0.9%
Other values (15) 132
 
5.3%
Han
ValueCountFrequency (%)
公 1
20.0%
金 1
20.0%
衣 1
20.0%
子 1
20.0%
家 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20938
79.9%
ASCII 5260
 
20.1%
CJK 4
 
< 0.1%
Compat Jamo 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 897
 
4.3%
이 839
 
4.0%
스 809
 
3.9%
리 487
 
2.3%
산 401
 
1.9%
피 379
 
1.8%
용 369
 
1.8%
아 329
 
1.6%
레 311
 
1.5%
커 307
 
1.5%
Other values (777) 15810
75.5%
ASCII
ValueCountFrequency (%)
793
 
15.1%
) 543
 
10.3%
( 542
 
10.3%
e 247
 
4.7%
2 170
 
3.2%
a 158
 
3.0%
o 149
 
2.8%
C 120
 
2.3%
5 118
 
2.2%
S 115
 
2.2%
Other values (67) 2305
43.8%
Compat Jamo
ValueCountFrequency (%)
ㅋ 2
100.0%
CJK
ValueCountFrequency (%)
公 1
25.0%
衣 1
25.0%
子 1
25.0%
家 1
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
金 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정일자
Date

Distinct2858
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
Minimum1999-03-30 00:00:00
Maximum2024-05-09 15:27:17
2024-05-11T15:36:08.120914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:08.356640image/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 size28.3 KiB
I
2435 
U
1172 

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 2435
67.5%
U 1172
32.5%

Length

2024-05-11T15:36:08.585362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:08.754065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2435
67.5%
u 1172
32.5%

데이터갱신일자
Date

Distinct925
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:36:08.935669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:09.156241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct17
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
커피숍
1056 
기타 휴게음식점
854 
다방
502 
일반조리판매
415 
편의점
296 
Other values (12)
484 

Length

Max length8
Median length6
Mean length4.5162185
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 1056
29.3%
기타 휴게음식점 854
23.7%
다방 502
13.9%
일반조리판매 415
 
11.5%
편의점 296
 
8.2%
과자점 230
 
6.4%
패스트푸드 146
 
4.0%
철도역구내 47
 
1.3%
아이스크림 29
 
0.8%
푸드트럭 9
 
0.2%
Other values (7) 23
 
0.6%

Length

2024-05-11T15:36:09.387369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1056
23.7%
기타 854
19.1%
휴게음식점 854
19.1%
다방 502
11.3%
일반조리판매 415
 
9.3%
편의점 296
 
6.6%
과자점 230
 
5.2%
패스트푸드 146
 
3.3%
철도역구내 47
 
1.1%
아이스크림 29
 
0.7%
Other values (8) 32
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1766
Distinct (%)50.6%
Missing115
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean197837.94
Minimum195266.36
Maximum201070.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-05-11T15:36:09.619362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195266.36
5-th percentile196292.45
Q1196812.97
median197416.5
Q3198930.08
95-th percentile200415.97
Maximum201070.19
Range5803.8254
Interquartile range (IQR)2117.1149

Descriptive statistics

Standard deviation1304.5705
Coefficient of variation (CV)0.0065941369
Kurtosis-0.63578888
Mean197837.94
Median Absolute Deviation (MAD)654.42438
Skewness0.71750884
Sum6.9085009 × 108
Variance1701904.1
MonotonicityNot monotonic
2024-05-11T15:36:09.832366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196762.077394917 324
 
9.0%
197373.839856311 42
 
1.2%
196370.746398773 29
 
0.8%
197811.954980013 21
 
0.6%
198622.89264988 19
 
0.5%
196813.258497258 19
 
0.5%
196831.461759469 19
 
0.5%
198236.296378418 18
 
0.5%
200437.601967198 18
 
0.5%
197071.403205622 16
 
0.4%
Other values (1756) 2967
82.3%
(Missing) 115
 
3.2%
ValueCountFrequency (%)
195266.362355276 1
 
< 0.1%
195462.432724897 1
 
< 0.1%
195544.606275448 4
 
0.1%
195547.140326252 10
0.3%
195550.858625514 1
 
< 0.1%
195556.853873045 2
 
0.1%
195563.535062555 2
 
0.1%
195565.493588098 1
 
< 0.1%
195580.091935429 1
 
< 0.1%
195593.749840213 1
 
< 0.1%
ValueCountFrequency (%)
201070.187785081 2
 
0.1%
201033.050326 1
 
< 0.1%
201030.206402172 1
 
< 0.1%
201015.713148163 1
 
< 0.1%
200999.320513425 2
 
0.1%
200955.892430557 1
 
< 0.1%
200896.20841088 1
 
< 0.1%
200846.604536733 1
 
< 0.1%
200837.136549128 5
0.1%
200831.699356882 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1766
Distinct (%)50.6%
Missing115
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean448204.74
Minimum445891.89
Maximum450296.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-05-11T15:36:10.078521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445891.89
5-th percentile446521.05
Q1447480.04
median448055.05
Q3448985.2
95-th percentile449934.16
Maximum450296.59
Range4404.7002
Interquartile range (IQR)1505.1634

Descriptive statistics

Standard deviation958.05357
Coefficient of variation (CV)0.0021375355
Kurtosis-0.49424446
Mean448204.74
Median Absolute Deviation (MAD)582.79189
Skewness0.12280118
Sum1.565131 × 109
Variance917866.64
MonotonicityNot monotonic
2024-05-11T15:36:10.332671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447480.039577359 324
 
9.0%
450014.537949042 42
 
1.2%
447841.698787531 29
 
0.8%
446248.255892098 21
 
0.6%
446114.155238838 19
 
0.5%
447881.970772064 19
 
0.5%
449320.370380461 19
 
0.5%
446262.544080318 18
 
0.5%
448269.566304924 18
 
0.5%
447073.62284187 16
 
0.4%
Other values (1756) 2967
82.3%
(Missing) 115
 
3.2%
ValueCountFrequency (%)
445891.889050955 10
0.3%
446114.125235545 6
 
0.2%
446114.155238838 19
0.5%
446185.244544796 1
 
< 0.1%
446196.846273533 2
 
0.1%
446201.315141801 3
 
0.1%
446202.36502252 9
0.2%
446243.198701013 2
 
0.1%
446248.255892098 21
0.6%
446252.339785985 3
 
0.1%
ValueCountFrequency (%)
450296.589217562 1
 
< 0.1%
450290.442701448 4
0.1%
450288.561776513 2
 
0.1%
450286.425859673 1
 
< 0.1%
450278.758007272 5
0.1%
450272.711607398 1
 
< 0.1%
450267.741912848 1
 
< 0.1%
450252.766196402 1
 
< 0.1%
450247.06018934 1
 
< 0.1%
450239.515008707 3
0.1%

위생업태명
Categorical

Distinct18
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
882 
커피숍
694 
기타 휴게음식점
567 
다방
499 
일반조리판매
345 
Other values (13)
620 

Length

Max length8
Median length6
Mean length4.2808428
Min length2

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 882
24.5%
커피숍 694
19.2%
기타 휴게음식점 567
15.7%
다방 499
13.8%
일반조리판매 345
 
9.6%
과자점 229
 
6.3%
편의점 188
 
5.2%
패스트푸드 134
 
3.7%
철도역구내 32
 
0.9%
아이스크림 15
 
0.4%
Other values (8) 22
 
0.6%

Length

2024-05-11T15:36:10.551927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 882
21.1%
커피숍 694
16.6%
기타 567
13.6%
휴게음식점 567
13.6%
다방 499
12.0%
일반조리판매 345
 
8.3%
과자점 229
 
5.5%
편의점 188
 
4.5%
패스트푸드 134
 
3.2%
철도역구내 32
 
0.8%
Other values (9) 37
 
0.9%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing2359
Missing (%)65.4%
Infinite0
Infinite (%)0.0%
Mean0.17708333
Minimum0
Maximum5
Zeros1085
Zeros (%)30.1%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-05-11T15:36:10.730221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.51587826
Coefficient of variation (CV)2.9131949
Kurtosis16.38323
Mean0.17708333
Median Absolute Deviation (MAD)0
Skewness3.6259069
Sum221
Variance0.26613038
MonotonicityNot monotonic
2024-05-11T15:36:10.910151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1085
30.1%
1 118
 
3.3%
2 35
 
1.0%
3 8
 
0.2%
4 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 2359
65.4%
ValueCountFrequency (%)
0 1085
30.1%
1 118
 
3.3%
2 35
 
1.0%
3 8
 
0.2%
4 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 1
 
< 0.1%
3 8
 
0.2%
2 35
 
1.0%
1 118
 
3.3%
0 1085
30.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing2356
Missing (%)65.3%
Infinite0
Infinite (%)0.0%
Mean0.75539568
Minimum0
Maximum5
Zeros795
Zeros (%)22.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-05-11T15:36:11.140262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1465256
Coefficient of variation (CV)1.5177815
Kurtosis0.88968099
Mean0.75539568
Median Absolute Deviation (MAD)0
Skewness1.3525812
Sum945
Variance1.3145209
MonotonicityNot monotonic
2024-05-11T15:36:11.727298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 795
 
22.0%
2 181
 
5.0%
1 139
 
3.9%
3 109
 
3.0%
4 18
 
0.5%
5 9
 
0.2%
(Missing) 2356
65.3%
ValueCountFrequency (%)
0 795
22.0%
1 139
 
3.9%
2 181
 
5.0%
3 109
 
3.0%
4 18
 
0.5%
5 9
 
0.2%
ValueCountFrequency (%)
5 9
 
0.2%
4 18
 
0.5%
3 109
 
3.0%
2 181
 
5.0%
1 139
 
3.9%
0 795
22.0%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
2518 
기타
629 
주택가주변
 
238
유흥업소밀집지역
 
125
아파트지역
 
64
Other values (2)
 
33

Length

Max length8
Median length4
Mean length3.9101747
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2518
69.8%
기타 629
 
17.4%
주택가주변 238
 
6.6%
유흥업소밀집지역 125
 
3.5%
아파트지역 64
 
1.8%
학교정화(상대) 30
 
0.8%
학교정화(절대) 3
 
0.1%

Length

2024-05-11T15:36:11.959914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:12.167245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2518
69.8%
기타 629
 
17.4%
주택가주변 238
 
6.6%
유흥업소밀집지역 125
 
3.5%
아파트지역 64
 
1.8%
학교정화(상대 30
 
0.8%
학교정화(절대 3
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
2736 
기타
344 
지도
320 
자율
 
101
갑
 
52
Other values (3)
 
54

Length

Max length4
Median length4
Mean length3.4909897
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2736
75.9%
기타 344
 
9.5%
지도 320
 
8.9%
자율 101
 
2.8%
갑 52
 
1.4%
을 42
 
1.2%
관리 7
 
0.2%
우수 5
 
0.1%

Length

2024-05-11T15:36:12.409126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:12.667990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2736
75.9%
기타 344
 
9.5%
지도 320
 
8.9%
자율 101
 
2.8%
갑 52
 
1.4%
을 42
 
1.2%
관리 7
 
0.2%
우수 5
 
0.1%

급수시설구분명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
2030 
상수도전용
1562 
상수도(음용)지하수(주방용)겸용
 
14
지하수전용
 
1

Length

Max length17
Median length4
Mean length4.4837815
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2030
56.3%
상수도전용 1562
43.3%
상수도(음용)지하수(주방용)겸용 14
 
0.4%
지하수전용 1
 
< 0.1%

Length

2024-05-11T15:36:12.951441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:13.183355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2030
56.3%
상수도전용 1562
43.3%
상수도(음용)지하수(주방용)겸용 14
 
0.4%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3459 
0
 
148

Length

Max length4
Median length4
Mean length3.876906
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> 3459
95.9%
0 148
 
4.1%

Length

2024-05-11T15:36:13.435189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:13.632382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3459
95.9%
0 148
 
4.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3456 
0
 
151

Length

Max length4
Median length4
Mean length3.8744109
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> 3456
95.8%
0 151
 
4.2%

Length

2024-05-11T15:36:13.828043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:14.049966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3456
95.8%
0 151
 
4.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3456 
0
 
151

Length

Max length4
Median length4
Mean length3.8744109
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> 3456
95.8%
0 151
 
4.2%

Length

2024-05-11T15:36:14.244207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:14.436359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3456
95.8%
0 151
 
4.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3456 
0
 
151

Length

Max length4
Median length4
Mean length3.8744109
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> 3456
95.8%
0 151
 
4.2%

Length

2024-05-11T15:36:14.729135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:14.978136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3456
95.8%
0 151
 
4.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3456 
0
 
151

Length

Max length4
Median length4
Mean length3.8744109
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> 3456
95.8%
0 151
 
4.2%

Length

2024-05-11T15:36:15.216191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:15.443417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3456
95.8%
0 151
 
4.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3607
Missing (%)100.0%
Memory size31.8 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3456 
0
 
151

Length

Max length4
Median length4
Mean length3.8744109
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> 3456
95.8%
0 151
 
4.2%

Length

2024-05-11T15:36:15.646693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:15.851845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3456
95.8%
0 151
 
4.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3456 
0
 
151

Length

Max length4
Median length4
Mean length3.8744109
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> 3456
95.8%
0 151
 
4.2%

Length

2024-05-11T15:36:16.118599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:16.352047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3456
95.8%
0 151
 
4.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing882
Missing (%)24.5%
Memory size7.2 KiB
False
2702 
True
 
23
(Missing)
882 
ValueCountFrequency (%)
False 2702
74.9%
True 23
 
0.6%
(Missing) 882
 
24.5%
2024-05-11T15:36:16.524390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct1717
Distinct (%)63.0%
Missing882
Missing (%)24.5%
Infinite0
Infinite (%)0.0%
Mean49.415064
Minimum0
Maximum591
Zeros36
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2024-05-11T15:36:16.723948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.78
Q116
median33.06
Q365.72
95-th percentile145.764
Maximum591
Range591
Interquartile range (IQR)49.72

Descriptive statistics

Standard deviation52.235291
Coefficient of variation (CV)1.0570722
Kurtosis14.591645
Mean49.415064
Median Absolute Deviation (MAD)21.51
Skewness2.9471482
Sum134656.05
Variance2728.5257
MonotonicityNot monotonic
2024-05-11T15:36:16.968216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.6 87
 
2.4%
3.3 75
 
2.1%
10.0 39
 
1.1%
0.0 36
 
1.0%
33.0 32
 
0.9%
9.9 27
 
0.7%
26.4 26
 
0.7%
13.2 25
 
0.7%
16.5 23
 
0.6%
15.0 19
 
0.5%
Other values (1707) 2336
64.8%
(Missing) 882
 
24.5%
ValueCountFrequency (%)
0.0 36
1.0%
0.8 1
 
< 0.1%
2.0 2
 
0.1%
2.04 1
 
< 0.1%
2.25 1
 
< 0.1%
2.27 1
 
< 0.1%
2.5 1
 
< 0.1%
2.83 2
 
0.1%
2.88 1
 
< 0.1%
3.0 10
 
0.3%
ValueCountFrequency (%)
591.0 1
< 0.1%
476.87 1
< 0.1%
455.12 1
< 0.1%
436.08 1
< 0.1%
429.0 1
< 0.1%
412.5 2
0.1%
339.45 1
< 0.1%
322.22 1
< 0.1%
320.0 1
< 0.1%
313.5 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3607
Missing (%)100.0%
Memory size31.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3607
Missing (%)100.0%
Memory size31.8 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3607
Missing (%)100.0%
Memory size31.8 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030200003020000-104-1966-0273219661220<NA>3폐업2폐업19950502<NA><NA><NA>02 7956111121.59140011서울특별시 용산구 한강로1가 23-1번지<NA><NA>동심2001-09-27 00:00:00I2018-08-31 23:59:59.0다방197716.472188448132.036097다방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N121.59<NA><NA><NA>
130200003020000-104-1967-0256619671223<NA>3폐업2폐업20130527<NA><NA><NA>02 7944344135.68140871서울특별시 용산구 한강로2가 351-0번지<NA><NA>여백2004-09-13 00:00:00I2018-08-31 23:59:59.0다방196920.867478447381.325491다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N135.68<NA><NA><NA>
230200003020000-104-1967-0262219671011<NA>1영업/정상1영업<NA><NA><NA><NA>020795199095.52140160서울특별시 용산구 남영동 94-6번지서울특별시 용산구 한강대로80길 10 (남영동)4352귀향2004-09-13 00:00:00I2018-08-31 23:59:59.0다방197577.022277448914.646283다방02유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N95.52<NA><NA><NA>
330200003020000-104-1967-0273319671011<NA>3폐업2폐업20051229<NA><NA><NA>020713333350.9140847서울특별시 용산구 원효로2가 86-8번지<NA><NA>해림2004-09-13 00:00:00I2018-08-31 23:59:59.0다방196577.544734448075.781249다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N50.9<NA><NA><NA>
430200003020000-104-1967-0277919671010<NA>3폐업2폐업20030716<NA><NA><NA>0207137463120.12140100서울특별시 용산구 문배동 11-0번지<NA><NA>중원2001-09-27 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N120.12<NA><NA><NA>
530200003020000-104-1967-0281019671011<NA>3폐업2폐업19941103<NA><NA><NA>020712576577.01140847서울특별시 용산구 원효로2가 3-15번지<NA><NA>우리2001-09-27 00:00:00I2018-08-31 23:59:59.0다방196892.836559448355.376118다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N77.01<NA><NA><NA>
630200003020000-104-1967-0281519671228<NA>3폐업2폐업19951019<NA><NA><NA>020795241246.62140882서울특별시 용산구 한강로3가 61-0번지<NA><NA>선향2001-09-27 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N46.62<NA><NA><NA>
730200003020000-104-1967-0287619671010<NA>3폐업2폐업19940907<NA><NA><NA>0207145544109.09140821서울특별시 용산구 동자동 43-66번지<NA><NA>역전2001-09-27 00:00:00I2018-08-31 23:59:59.0다방197472.030892450252.766196다방02유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N109.09<NA><NA><NA>
830200003020000-104-1967-0288519671011<NA>3폐업2폐업19931015<NA><NA><NA>02 713766262.89140111서울특별시 용산구 원효로1가 133-11번지<NA><NA>은하2001-09-27 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방04주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N62.89<NA><NA><NA>
930200003020000-104-1967-0291319671011<NA>3폐업2폐업19920421<NA><NA><NA>020793047448.4140160서울특별시 용산구 남영동 84-8번지<NA><NA>성남2001-09-27 00:00:00I2018-08-31 23:59:59.0다방197552.160288448884.57297다방02기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N48.4<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
359730200003020000-104-2024-000652024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>222.42140-892서울특별시 용산구 한남동 683-130서울특별시 용산구 이태원로 254, 2층 (한남동)4400플디 한남점(plated)2024-04-30 14:52:28U2023-12-05 00:02:00.0기타 휴게음식점200034.203421448331.69664<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
359830200003020000-104-2024-000662024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.44140-012서울특별시 용산구 한강로2가 426 용산 베르디움 프렌즈서울특별시 용산구 백범로99길 40, 102동 109호 (한강로2가, 용산 베르디움 프렌즈)4375코르츠(korz)2024-04-26 14:58:37I2023-12-03 22:08:00.0커피숍197414.574509448137.721887<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
359930200003020000-104-2024-000672024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0140-133서울특별시 용산구 청파동3가 111-9 캠퍼스프라자서울특별시 용산구 청파로47길 49, 캠퍼스프라자 지하1층 (청파동3가)4313브라비pc카페(Bravi pc cafe)2024-04-29 13:47:18I2023-12-05 00:01:00.0기타 휴게음식점197059.739244449146.256652<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
360030200003020000-104-2024-000682024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>7.24140-012서울특별시 용산구 한강로2가 422 래미안용산 더 센트럴서울특별시 용산구 한강대로 95, 지하1층 B126호 (한강로2가, 래미안용산 더 센트럴)4378금밥집2024-04-30 15:43:55I2023-12-05 00:02:00.0기타 휴게음식점197011.737529447430.100251<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
360130200003020000-104-2024-000692024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA>022039158849.55140-777서울특별시 용산구 한강로2가 424 아모레퍼시픽서울특별시 용산구 한강대로 100, 아모레퍼시픽 지하1층 B106-4호 (한강로2가)4386나레이션(Narration)2024-04-30 16:00:54I2023-12-05 00:02:00.0기타 휴게음식점197158.923648447399.964398<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
360230200003020000-104-2024-000702024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>140-780서울특별시 용산구 한강로3가 40-999 용산역서울특별시 용산구 한강대로23길 55, 용산역 7층 (한강로3가)4377감동푸드2024-04-30 17:27:28I2023-12-05 00:02:00.0기타 휴게음식점196762.077395447480.039577<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
360330200003020000-104-2024-000712024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>140-780서울특별시 용산구 한강로3가 40-999 용산역서울특별시 용산구 한강대로23길 55, 용산역 7층 (한강로3가)4377주바른2024-05-01 13:27:27I2023-12-05 00:03:00.0기타 휴게음식점196762.077395447480.039577<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
360430200003020000-104-2024-000722024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>140-210서울특별시 용산구 한남동 829 나인원 한남서울특별시 용산구 한남대로 91, B2층 (한남동, 나인원 한남)4401달콤한위로2024-05-03 13:35:32I2023-12-05 00:08:00.0기타 휴게음식점200231.538141448226.481351<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
360530200003020000-104-2024-000732024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>83.17140-780서울특별시 용산구 한강로3가 40-999 용산역서울특별시 용산구 한강대로23길 55, 용산역 6층 (한강로3가)4377구슬스2024-05-07 11:57:26I2023-12-05 00:09:00.0아이스크림196762.077395447480.039577<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
360630200003020000-104-2024-000742024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>140-780서울특별시 용산구 한강로3가 40-999 용산역서울특별시 용산구 한강대로23길 55, 용산역 7층 (한강로3가)4377모구야미 매교역점2024-05-09 15:15:06I2023-12-04 23:01:00.0기타 휴게음식점196762.077395447480.039577<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>