Overview

Dataset statistics

Number of variables44
Number of observations5169
Missing cells56266
Missing cells (%)24.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 MiB
Average record size in memory377.0 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-18677/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (57.7%)Imbalance
등급구분명 is highly imbalanced (51.7%)Imbalance
급수시설구분명 is highly imbalanced (50.2%)Imbalance
총인원 is highly imbalanced (75.5%)Imbalance
본사종업원수 is highly imbalanced (75.1%)Imbalance
공장사무직종업원수 is highly imbalanced (75.1%)Imbalance
공장판매직종업원수 is highly imbalanced (75.1%)Imbalance
공장생산직종업원수 is highly imbalanced (75.1%)Imbalance
보증액 is highly imbalanced (75.1%)Imbalance
월세액 is highly imbalanced (75.1%)Imbalance
다중이용업소여부 is highly imbalanced (93.8%)Imbalance
전통업소지정번호 is highly imbalanced (99.7%)Imbalance
인허가취소일자 has 5169 (100.0%) missing valuesMissing
폐업일자 has 1770 (34.2%) missing valuesMissing
휴업시작일자 has 5169 (100.0%) missing valuesMissing
휴업종료일자 has 5169 (100.0%) missing valuesMissing
재개업일자 has 5169 (100.0%) missing valuesMissing
전화번호 has 2485 (48.1%) missing valuesMissing
소재지면적 has 3278 (63.4%) missing valuesMissing
도로명주소 has 1922 (37.2%) missing valuesMissing
도로명우편번호 has 1952 (37.8%) missing valuesMissing
좌표정보(X) has 320 (6.2%) missing valuesMissing
좌표정보(Y) has 320 (6.2%) missing valuesMissing
남성종사자수 has 3121 (60.4%) missing valuesMissing
여성종사자수 has 3113 (60.2%) missing valuesMissing
건물소유구분명 has 5169 (100.0%) missing valuesMissing
다중이용업소여부 has 893 (17.3%) missing valuesMissing
시설총규모 has 893 (17.3%) missing valuesMissing
전통업소주된음식 has 5169 (100.0%) missing valuesMissing
홈페이지 has 5169 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 29.07961913)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 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 1817 (35.2%) zerosZeros
여성종사자수 has 1161 (22.5%) zerosZeros
시설총규모 has 76 (1.5%) zerosZeros

Reproduction

Analysis started2024-05-11 06:51:23.802360
Analysis finished2024-05-11 06:51:26.158155
Duration2.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
3000000
5169 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 5169
100.0%

Length

2024-05-11T15:51:26.258121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:26.426521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 5169
100.0%

관리번호
Text

UNIQUE 

Distinct5169
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
2024-05-11T15:51:26.691792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters113718
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

Unique5169 ?
Unique (%)100.0%

Sample

1st row3000000-104-1964-09227
2nd row3000000-104-1965-09174
3rd row3000000-104-1965-09216
4th row3000000-104-1965-09601
5th row3000000-104-1966-09238
ValueCountFrequency (%)
3000000-104-1964-09227 1
 
< 0.1%
3000000-104-2015-00211 1
 
< 0.1%
3000000-104-2015-00189 1
 
< 0.1%
3000000-104-2015-00188 1
 
< 0.1%
3000000-104-2015-00187 1
 
< 0.1%
3000000-104-2015-00186 1
 
< 0.1%
3000000-104-2015-00185 1
 
< 0.1%
3000000-104-2015-00184 1
 
< 0.1%
3000000-104-2015-00191 1
 
< 0.1%
3000000-104-2015-00183 1
 
< 0.1%
Other values (5159) 5159
99.8%
2024-05-11T15:51:27.231711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 53499
47.0%
- 15507
 
13.6%
1 12243
 
10.8%
3 6994
 
6.2%
4 6883
 
6.1%
2 6597
 
5.8%
9 4743
 
4.2%
8 2284
 
2.0%
7 1717
 
1.5%
6 1670
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98211
86.4%
Dash Punctuation 15507
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53499
54.5%
1 12243
 
12.5%
3 6994
 
7.1%
4 6883
 
7.0%
2 6597
 
6.7%
9 4743
 
4.8%
8 2284
 
2.3%
7 1717
 
1.7%
6 1670
 
1.7%
5 1581
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 15507
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 113718
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 53499
47.0%
- 15507
 
13.6%
1 12243
 
10.8%
3 6994
 
6.2%
4 6883
 
6.1%
2 6597
 
5.8%
9 4743
 
4.2%
8 2284
 
2.0%
7 1717
 
1.5%
6 1670
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113718
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 53499
47.0%
- 15507
 
13.6%
1 12243
 
10.8%
3 6994
 
6.2%
4 6883
 
6.1%
2 6597
 
5.8%
9 4743
 
4.2%
8 2284
 
2.0%
7 1717
 
1.5%
6 1670
 
1.5%

인허가일자
Date

Distinct3860
Distinct (%)74.7%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
Minimum1964-12-03 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:51:27.468033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:51:27.740343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5169
Missing (%)100.0%
Memory size45.6 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
3
3399 
1
1770 

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 3399
65.8%
1 1770
34.2%

Length

2024-05-11T15:51:27.949064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:28.107387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3399
65.8%
1 1770
34.2%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
폐업
3399 
영업/정상
1770 

Length

Max length5
Median length2
Mean length3.027278
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3399
65.8%
영업/정상 1770
34.2%

Length

2024-05-11T15:51:28.307242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:28.460186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3399
65.8%
영업/정상 1770
34.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
2
3399 
1
1770 

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 3399
65.8%
1 1770
34.2%

Length

2024-05-11T15:51:28.610717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:28.741399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3399
65.8%
1 1770
34.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
폐업
3399 
영업
1770 

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 3399
65.8%
영업 1770
34.2%

Length

2024-05-11T15:51:28.875701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:29.025631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3399
65.8%
영업 1770
34.2%

폐업일자
Date

MISSING 

Distinct2558
Distinct (%)75.3%
Missing1770
Missing (%)34.2%
Memory size40.5 KiB
Minimum1987-07-14 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T15:51:29.177516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:51:29.399862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5169
Missing (%)100.0%
Memory size45.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5169
Missing (%)100.0%
Memory size45.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5169
Missing (%)100.0%
Memory size45.6 KiB

전화번호
Text

MISSING 

Distinct2479
Distinct (%)92.4%
Missing2485
Missing (%)48.1%
Memory size40.5 KiB
2024-05-11T15:51:29.767743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.419523
Min length2

Characters and Unicode

Total characters27966
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

Unique2400 ?
Unique (%)89.4%

Sample

1st row0202674693
2nd row0207255360
3rd row0207633064
4th row02 7636226
5th row0202654710
ValueCountFrequency (%)
02 1625
33.8%
0200000000 43
 
0.9%
070 43
 
0.9%
766 21
 
0.4%
741 20
 
0.4%
722 19
 
0.4%
32848120 18
 
0.4%
00000 18
 
0.4%
737 18
 
0.4%
742 17
 
0.4%
Other values (2583) 2962
61.7%
2024-05-11T15:51:30.793534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5488
19.6%
2 4952
17.7%
7 3248
11.6%
2785
10.0%
3 2453
8.8%
6 1860
 
6.7%
4 1716
 
6.1%
5 1561
 
5.6%
1 1442
 
5.2%
8 1247
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25181
90.0%
Space Separator 2785
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5488
21.8%
2 4952
19.7%
7 3248
12.9%
3 2453
9.7%
6 1860
 
7.4%
4 1716
 
6.8%
5 1561
 
6.2%
1 1442
 
5.7%
8 1247
 
5.0%
9 1214
 
4.8%
Space Separator
ValueCountFrequency (%)
2785
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27966
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5488
19.6%
2 4952
17.7%
7 3248
11.6%
2785
10.0%
3 2453
8.8%
6 1860
 
6.7%
4 1716
 
6.1%
5 1561
 
5.6%
1 1442
 
5.2%
8 1247
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27966
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5488
19.6%
2 4952
17.7%
7 3248
11.6%
2785
10.0%
3 2453
8.8%
6 1860
 
6.7%
4 1716
 
6.1%
5 1561
 
5.6%
1 1442
 
5.2%
8 1247
 
4.5%

소재지면적
Real number (ℝ)

MISSING 

Distinct1082
Distinct (%)57.2%
Missing3278
Missing (%)63.4%
Infinite0
Infinite (%)0.0%
Mean56.341835
Minimum1.2
Maximum628.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.6 KiB
2024-05-11T15:51:31.154015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.2
5-th percentile3.3
Q113.105
median30
Q360.515
95-th percentile230.765
Maximum628.56
Range627.36
Interquartile range (IQR)47.41

Descriptive statistics

Standard deviation79.380827
Coefficient of variation (CV)1.4089145
Kurtosis11.269303
Mean56.341835
Median Absolute Deviation (MAD)20
Skewness3.0916298
Sum106542.41
Variance6301.3157
MonotonicityNot monotonic
2024-05-11T15:51:31.675394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 118
 
2.3%
10.0 51
 
1.0%
6.6 43
 
0.8%
9.0 40
 
0.8%
20.0 24
 
0.5%
33.0 23
 
0.4%
30.0 22
 
0.4%
3.0 22
 
0.4%
16.5 21
 
0.4%
13.2 17
 
0.3%
Other values (1072) 1510
29.2%
(Missing) 3278
63.4%
ValueCountFrequency (%)
1.2 1
 
< 0.1%
1.5 1
 
< 0.1%
2.0 2
 
< 0.1%
2.4 1
 
< 0.1%
2.73 1
 
< 0.1%
3.0 22
 
0.4%
3.3 118
2.3%
3.6 1
 
< 0.1%
4.0 5
 
0.1%
4.56 1
 
< 0.1%
ValueCountFrequency (%)
628.56 1
< 0.1%
598.08 1
< 0.1%
550.9 1
< 0.1%
537.18 1
< 0.1%
530.68 1
< 0.1%
512.83 1
< 0.1%
486.06 1
< 0.1%
479.78 1
< 0.1%
476.21 1
< 0.1%
449.98 1
< 0.1%

소재지우편번호
Text

Distinct319
Distinct (%)6.2%
Missing8
Missing (%)0.2%
Memory size40.5 KiB
2024-05-11T15:51:32.988658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1178066
Min length6

Characters and Unicode

Total characters31574
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

Unique60 ?
Unique (%)1.2%

Sample

1st row110430
2nd row110160
3rd row110840
4th row110843
5th row110430
ValueCountFrequency (%)
110111 192
 
3.7%
110522 173
 
3.4%
110809 163
 
3.2%
110122 117
 
2.3%
110130 115
 
2.2%
110300 110
 
2.1%
110530 97
 
1.9%
110320 89
 
1.7%
110420 87
 
1.7%
110524 84
 
1.6%
Other values (309) 3934
76.2%
2024-05-11T15:51:33.811460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12731
40.3%
0 8686
27.5%
2 2230
 
7.1%
8 1726
 
5.5%
3 1447
 
4.6%
4 1305
 
4.1%
5 1073
 
3.4%
6 721
 
2.3%
7 626
 
2.0%
- 608
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30966
98.1%
Dash Punctuation 608
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12731
41.1%
0 8686
28.1%
2 2230
 
7.2%
8 1726
 
5.6%
3 1447
 
4.7%
4 1305
 
4.2%
5 1073
 
3.5%
6 721
 
2.3%
7 626
 
2.0%
9 421
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 608
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31574
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12731
40.3%
0 8686
27.5%
2 2230
 
7.1%
8 1726
 
5.5%
3 1447
 
4.6%
4 1305
 
4.1%
5 1073
 
3.4%
6 721
 
2.3%
7 626
 
2.0%
- 608
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31574
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12731
40.3%
0 8686
27.5%
2 2230
 
7.1%
8 1726
 
5.5%
3 1447
 
4.6%
4 1305
 
4.1%
5 1073
 
3.4%
6 721
 
2.3%
7 626
 
2.0%
- 608
 
1.9%

지번주소
Text

Distinct4520
Distinct (%)87.6%
Missing8
Missing (%)0.2%
Memory size40.5 KiB
2024-05-11T15:51:34.304759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length49
Mean length23.976555
Min length14

Characters and Unicode

Total characters123743
Distinct characters402
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4039 ?
Unique (%)78.3%

Sample

1st row서울특별시 종로구 장사동 147-2번지
2nd row서울특별시 종로구 공평동 119-0번지
3rd row서울특별시 종로구 창신동 154-1번지 지상2층
4th row서울특별시 종로구 창신동 696-1번지
5th row서울특별시 종로구 장사동 212번지
ValueCountFrequency (%)
서울특별시 5161
21.4%
종로구 5161
21.4%
1층 617
 
2.6%
지상1층 375
 
1.6%
창신동 272
 
1.1%
숭인동 230
 
1.0%
관철동 212
 
0.9%
동숭동 202
 
0.8%
지하1층 198
 
0.8%
명륜2가 194
 
0.8%
Other values (3676) 11524
47.7%
2024-05-11T15:51:35.125644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23142
18.7%
1 6558
 
5.3%
로 6073
 
4.9%
종 5890
 
4.8%
서 5337
 
4.3%
구 5234
 
4.2%
시 5214
 
4.2%
울 5212
 
4.2%
별 5164
 
4.2%
특 5162
 
4.2%
Other values (392) 50757
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73948
59.8%
Space Separator 23142
 
18.7%
Decimal Number 21705
 
17.5%
Dash Punctuation 3804
 
3.1%
Open Punctuation 295
 
0.2%
Close Punctuation 295
 
0.2%
Uppercase Letter 235
 
0.2%
Other Punctuation 171
 
0.1%
Lowercase Letter 88
 
0.1%
Math Symbol 59
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 6073
 
8.2%
종 5890
 
8.0%
서 5337
 
7.2%
구 5234
 
7.1%
시 5214
 
7.1%
울 5212
 
7.0%
별 5164
 
7.0%
특 5162
 
7.0%
지 4878
 
6.6%
동 4419
 
6.0%
Other values (335) 21365
28.9%
Uppercase Letter
ValueCountFrequency (%)
B 74
31.5%
D 23
 
9.8%
A 22
 
9.4%
T 19
 
8.1%
S 12
 
5.1%
K 12
 
5.1%
G 12
 
5.1%
C 9
 
3.8%
L 9
 
3.8%
M 7
 
3.0%
Other values (12) 36
15.3%
Lowercase Letter
ValueCountFrequency (%)
e 16
18.2%
r 15
17.0%
o 15
17.0%
w 12
13.6%
c 6
 
6.8%
n 6
 
6.8%
t 5
 
5.7%
b 3
 
3.4%
a 3
 
3.4%
d 2
 
2.3%
Other values (4) 5
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 6558
30.2%
2 3297
15.2%
3 2036
 
9.4%
0 1898
 
8.7%
4 1719
 
7.9%
5 1541
 
7.1%
6 1353
 
6.2%
8 1261
 
5.8%
7 1072
 
4.9%
9 970
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 142
83.0%
. 21
 
12.3%
/ 6
 
3.5%
& 1
 
0.6%
@ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
23142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3804
100.0%
Open Punctuation
ValueCountFrequency (%)
( 295
100.0%
Close Punctuation
ValueCountFrequency (%)
) 295
100.0%
Math Symbol
ValueCountFrequency (%)
~ 59
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73948
59.8%
Common 49471
40.0%
Latin 324
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 6073
 
8.2%
종 5890
 
8.0%
서 5337
 
7.2%
구 5234
 
7.1%
시 5214
 
7.1%
울 5212
 
7.0%
별 5164
 
7.0%
특 5162
 
7.0%
지 4878
 
6.6%
동 4419
 
6.0%
Other values (335) 21365
28.9%
Latin
ValueCountFrequency (%)
B 74
22.8%
D 23
 
7.1%
A 22
 
6.8%
T 19
 
5.9%
e 16
 
4.9%
r 15
 
4.6%
o 15
 
4.6%
S 12
 
3.7%
w 12
 
3.7%
K 12
 
3.7%
Other values (27) 104
32.1%
Common
ValueCountFrequency (%)
23142
46.8%
1 6558
 
13.3%
- 3804
 
7.7%
2 3297
 
6.7%
3 2036
 
4.1%
0 1898
 
3.8%
4 1719
 
3.5%
5 1541
 
3.1%
6 1353
 
2.7%
8 1261
 
2.5%
Other values (10) 2862
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73948
59.8%
ASCII 49794
40.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23142
46.5%
1 6558
 
13.2%
- 3804
 
7.6%
2 3297
 
6.6%
3 2036
 
4.1%
0 1898
 
3.8%
4 1719
 
3.5%
5 1541
 
3.1%
6 1353
 
2.7%
8 1261
 
2.5%
Other values (46) 3185
 
6.4%
Hangul
ValueCountFrequency (%)
로 6073
 
8.2%
종 5890
 
8.0%
서 5337
 
7.2%
구 5234
 
7.1%
시 5214
 
7.1%
울 5212
 
7.0%
별 5164
 
7.0%
특 5162
 
7.0%
지 4878
 
6.6%
동 4419
 
6.0%
Other values (335) 21365
28.9%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명주소
Text

MISSING 

Distinct2957
Distinct (%)91.1%
Missing1922
Missing (%)37.2%
Memory size40.5 KiB
2024-05-11T15:51:35.599014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length62
Mean length31.218971
Min length20

Characters and Unicode

Total characters101368
Distinct characters407
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2743 ?
Unique (%)84.5%

Sample

1st row서울특별시 종로구 종로 313-1 (창신동,지상2층)
2nd row서울특별시 종로구 새문안로5길 19 (당주동,지하1층 1호)
3rd row서울특별시 종로구 종로 138-1 (종로3가,(지하 1층))
4th row서울특별시 종로구 종로 222 (종로5가,(1층))
5th row서울특별시 종로구 새문안로5길 11-7 (당주동)
ValueCountFrequency (%)
서울특별시 3247
 
15.8%
종로구 3246
 
15.8%
1층 1417
 
6.9%
종로 326
 
1.6%
지하1층 250
 
1.2%
지상1층 163
 
0.8%
2층 163
 
0.8%
창신동 130
 
0.6%
동숭동 123
 
0.6%
대학로 105
 
0.5%
Other values (2295) 11341
55.3%
2024-05-11T15:51:36.291602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17270
 
17.0%
로 6377
 
6.3%
1 5434
 
5.4%
종 4304
 
4.2%
) 3410
 
3.4%
( 3410
 
3.4%
서 3379
 
3.3%
울 3302
 
3.3%
구 3299
 
3.3%
시 3296
 
3.3%
Other values (397) 47887
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57867
57.1%
Space Separator 17270
 
17.0%
Decimal Number 15092
 
14.9%
Close Punctuation 3410
 
3.4%
Open Punctuation 3410
 
3.4%
Other Punctuation 3284
 
3.2%
Dash Punctuation 621
 
0.6%
Uppercase Letter 246
 
0.2%
Lowercase Letter 89
 
0.1%
Math Symbol 78
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 6377
 
11.0%
종 4304
 
7.4%
서 3379
 
5.8%
울 3302
 
5.7%
구 3299
 
5.7%
시 3296
 
5.7%
특 3248
 
5.6%
별 3247
 
5.6%
동 3158
 
5.5%
층 2741
 
4.7%
Other values (339) 21516
37.2%
Uppercase Letter
ValueCountFrequency (%)
B 97
39.4%
A 24
 
9.8%
D 24
 
9.8%
T 15
 
6.1%
G 12
 
4.9%
K 10
 
4.1%
S 10
 
4.1%
M 9
 
3.7%
C 8
 
3.3%
L 8
 
3.3%
Other values (12) 29
 
11.8%
Lowercase Letter
ValueCountFrequency (%)
e 17
19.1%
r 14
15.7%
o 14
15.7%
w 11
12.4%
c 6
 
6.7%
n 6
 
6.7%
t 6
 
6.7%
a 4
 
4.5%
i 3
 
3.4%
d 2
 
2.2%
Other values (4) 6
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 5434
36.0%
2 2175
14.4%
3 1542
 
10.2%
4 1094
 
7.2%
5 1076
 
7.1%
0 1012
 
6.7%
6 811
 
5.4%
9 659
 
4.4%
7 652
 
4.3%
8 637
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 3252
99.0%
. 27
 
0.8%
? 2
 
0.1%
& 1
 
< 0.1%
@ 1
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
17270
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3410
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3410
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 621
100.0%
Math Symbol
ValueCountFrequency (%)
~ 78
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57866
57.1%
Common 43165
42.6%
Latin 336
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 6377
 
11.0%
종 4304
 
7.4%
서 3379
 
5.8%
울 3302
 
5.7%
구 3299
 
5.7%
시 3296
 
5.7%
특 3248
 
5.6%
별 3247
 
5.6%
동 3158
 
5.5%
층 2741
 
4.7%
Other values (338) 21515
37.2%
Latin
ValueCountFrequency (%)
B 97
28.9%
A 24
 
7.1%
D 24
 
7.1%
e 17
 
5.1%
T 15
 
4.5%
r 14
 
4.2%
o 14
 
4.2%
G 12
 
3.6%
w 11
 
3.3%
K 10
 
3.0%
Other values (27) 98
29.2%
Common
ValueCountFrequency (%)
17270
40.0%
1 5434
 
12.6%
) 3410
 
7.9%
( 3410
 
7.9%
, 3252
 
7.5%
2 2175
 
5.0%
3 1542
 
3.6%
4 1094
 
2.5%
5 1076
 
2.5%
0 1012
 
2.3%
Other values (11) 3490
 
8.1%
Han
ValueCountFrequency (%)
慣 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57866
57.1%
ASCII 43500
42.9%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17270
39.7%
1 5434
 
12.5%
) 3410
 
7.8%
( 3410
 
7.8%
, 3252
 
7.5%
2 2175
 
5.0%
3 1542
 
3.5%
4 1094
 
2.5%
5 1076
 
2.5%
0 1012
 
2.3%
Other values (47) 3825
 
8.8%
Hangul
ValueCountFrequency (%)
로 6377
 
11.0%
종 4304
 
7.4%
서 3379
 
5.8%
울 3302
 
5.7%
구 3299
 
5.7%
시 3296
 
5.7%
특 3248
 
5.6%
별 3247
 
5.6%
동 3158
 
5.5%
층 2741
 
4.7%
Other values (338) 21515
37.2%
CJK
ValueCountFrequency (%)
慣 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct190
Distinct (%)5.9%
Missing1952
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean3108.6354
Minimum3000
Maximum3198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.6 KiB
2024-05-11T15:51:36.507206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000
5-th percentile3015
Q13059
median3114
Q33158
95-th percentile3191
Maximum3198
Range198
Interquartile range (IQR)99

Descriptive statistics

Standard deviation56.844236
Coefficient of variation (CV)0.018285913
Kurtosis-1.2338676
Mean3108.6354
Median Absolute Deviation (MAD)50
Skewness-0.10418601
Sum10000480
Variance3231.2672
MonotonicityNot monotonic
2024-05-11T15:51:36.752429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3086 95
 
1.8%
3173 66
 
1.3%
3157 65
 
1.3%
3053 61
 
1.2%
3189 56
 
1.1%
3190 51
 
1.0%
3133 45
 
0.9%
3077 44
 
0.9%
3139 43
 
0.8%
3036 43
 
0.8%
Other values (180) 2648
51.2%
(Missing) 1952
37.8%
ValueCountFrequency (%)
3000 2
 
< 0.1%
3001 16
0.3%
3003 13
0.3%
3004 27
0.5%
3005 2
 
< 0.1%
3006 5
 
0.1%
3007 9
 
0.2%
3008 23
0.4%
3009 16
0.3%
3010 6
 
0.1%
ValueCountFrequency (%)
3198 26
0.5%
3197 14
 
0.3%
3196 7
 
0.1%
3195 34
0.7%
3194 10
 
0.2%
3193 13
 
0.3%
3192 40
0.8%
3191 37
0.7%
3190 51
1.0%
3189 56
1.1%

사업장명
Text

Distinct4758
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
2024-05-11T15:51:37.185188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length7.1329077
Min length1

Characters and Unicode

Total characters36870
Distinct characters943
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4493 ?
Unique (%)86.9%

Sample

1st row청수
2nd row태을
3rd row봉다방
4th row길
5th row장미
ValueCountFrequency (%)
카페 121
 
1.6%
세븐일레븐 70
 
0.9%
씨유 68
 
0.9%
gs25 57
 
0.8%
커피 52
 
0.7%
대학로점 49
 
0.6%
스타벅스 44
 
0.6%
종로점 39
 
0.5%
광화문점 34
 
0.5%
coffee 33
 
0.4%
Other values (5320) 6987
92.5%
2024-05-11T15:51:37.805071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2391
 
6.5%
점 1277
 
3.5%
스 1093
 
3.0%
로 758
 
2.1%
) 715
 
1.9%
( 702
 
1.9%
이 688
 
1.9%
리 626
 
1.7%
피 617
 
1.7%
커 572
 
1.6%
Other values (933) 27431
74.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28326
76.8%
Space Separator 2391
 
6.5%
Lowercase Letter 2119
 
5.7%
Uppercase Letter 1750
 
4.7%
Close Punctuation 715
 
1.9%
Decimal Number 708
 
1.9%
Open Punctuation 702
 
1.9%
Other Punctuation 121
 
0.3%
Dash Punctuation 30
 
0.1%
Connector Punctuation 4
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1277
 
4.5%
스 1093
 
3.9%
로 758
 
2.7%
이 688
 
2.4%
리 626
 
2.2%
피 617
 
2.2%
커 572
 
2.0%
종 501
 
1.8%
카 451
 
1.6%
페 423
 
1.5%
Other values (852) 21320
75.3%
Uppercase Letter
ValueCountFrequency (%)
C 189
 
10.8%
S 169
 
9.7%
E 134
 
7.7%
G 133
 
7.6%
A 115
 
6.6%
O 110
 
6.3%
F 78
 
4.5%
L 76
 
4.3%
B 75
 
4.3%
M 73
 
4.2%
Other values (16) 598
34.2%
Lowercase Letter
ValueCountFrequency (%)
e 374
17.6%
a 217
10.2%
o 203
9.6%
f 153
 
7.2%
n 132
 
6.2%
r 126
 
5.9%
t 111
 
5.2%
i 106
 
5.0%
c 105
 
5.0%
s 94
 
4.4%
Other values (15) 498
23.5%
Other Punctuation
ValueCountFrequency (%)
. 43
35.5%
& 30
24.8%
' 14
 
11.6%
, 9
 
7.4%
? 6
 
5.0%
/ 5
 
4.1%
# 5
 
4.1%
: 4
 
3.3%
! 2
 
1.7%
＆ 1
 
0.8%
Other values (2) 2
 
1.7%
Decimal Number
ValueCountFrequency (%)
2 226
31.9%
5 160
22.6%
1 91
12.9%
3 65
 
9.2%
0 38
 
5.4%
4 34
 
4.8%
7 32
 
4.5%
9 29
 
4.1%
8 25
 
3.5%
6 8
 
1.1%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
= 1
33.3%
Space Separator
ValueCountFrequency (%)
2391
100.0%
Close Punctuation
ValueCountFrequency (%)
) 715
100.0%
Open Punctuation
ValueCountFrequency (%)
( 702
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28308
76.8%
Common 4674
 
12.7%
Latin 3870
 
10.5%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1277
 
4.5%
스 1093
 
3.9%
로 758
 
2.7%
이 688
 
2.4%
리 626
 
2.2%
피 617
 
2.2%
커 572
 
2.0%
종 501
 
1.8%
카 451
 
1.6%
페 423
 
1.5%
Other values (837) 21302
75.3%
Latin
ValueCountFrequency (%)
e 374
 
9.7%
a 217
 
5.6%
o 203
 
5.2%
C 189
 
4.9%
S 169
 
4.4%
f 153
 
4.0%
E 134
 
3.5%
G 133
 
3.4%
n 132
 
3.4%
r 126
 
3.3%
Other values (42) 2040
52.7%
Common
ValueCountFrequency (%)
2391
51.2%
) 715
 
15.3%
( 702
 
15.0%
2 226
 
4.8%
5 160
 
3.4%
1 91
 
1.9%
3 65
 
1.4%
. 43
 
0.9%
0 38
 
0.8%
4 34
 
0.7%
Other values (19) 209
 
4.5%
Han
ValueCountFrequency (%)
桃 2
 
11.1%
笑 2
 
11.1%
空 2
 
11.1%
美 1
 
5.6%
間 1
 
5.6%
茶 1
 
5.6%
味 1
 
5.6%
米 1
 
5.6%
悟 1
 
5.6%
禪 1
 
5.6%
Other values (5) 5
27.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28308
76.8%
ASCII 8542
 
23.2%
CJK 17
 
< 0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2391
28.0%
) 715
 
8.4%
( 702
 
8.2%
e 374
 
4.4%
2 226
 
2.6%
a 217
 
2.5%
o 203
 
2.4%
C 189
 
2.2%
S 169
 
2.0%
5 160
 
1.9%
Other values (69) 3196
37.4%
Hangul
ValueCountFrequency (%)
점 1277
 
4.5%
스 1093
 
3.9%
로 758
 
2.7%
이 688
 
2.4%
리 626
 
2.2%
피 617
 
2.2%
커 572
 
2.0%
종 501
 
1.8%
카 451
 
1.6%
페 423
 
1.5%
Other values (837) 21302
75.3%
CJK
ValueCountFrequency (%)
桃 2
11.8%
笑 2
11.8%
空 2
11.8%
美 1
 
5.9%
間 1
 
5.9%
味 1
 
5.9%
米 1
 
5.9%
悟 1
 
5.9%
禪 1
 
5.9%
甫 1
 
5.9%
Other values (4) 4
23.5%
None
ValueCountFrequency (%)
＆ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
茶 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정일자
Date

Distinct3963
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
Minimum1999-01-07 00:00:00
Maximum2024-05-09 17:07:27
2024-05-11T15:51:38.017560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:51:38.248758image/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 size40.5 KiB
I
3723 
U
1446 

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 3723
72.0%
U 1446
 
28.0%

Length

2024-05-11T15:51:38.433584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:38.546216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3723
72.0%
u 1446
 
28.0%

데이터갱신일자
Date

Distinct1100
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:51:38.691429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:51:38.873742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
커피숍
1621 
다방
1209 
기타 휴게음식점
933 
일반조리판매
339 
과자점
301 
Other values (11)
766 

Length

Max length8
Median length6
Mean length4.0239892
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 1621
31.4%
다방 1209
23.4%
기타 휴게음식점 933
18.0%
일반조리판매 339
 
6.6%
과자점 301
 
5.8%
패스트푸드 278
 
5.4%
편의점 237
 
4.6%
전통찻집 147
 
2.8%
푸드트럭 63
 
1.2%
아이스크림 22
 
0.4%
Other values (6) 19
 
0.4%

Length

2024-05-11T15:51:39.060827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1621
26.6%
다방 1209
19.8%
기타 933
15.3%
휴게음식점 933
15.3%
일반조리판매 339
 
5.6%
과자점 301
 
4.9%
패스트푸드 278
 
4.6%
편의점 237
 
3.9%
전통찻집 147
 
2.4%
푸드트럭 63
 
1.0%
Other values (7) 41
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2687
Distinct (%)55.4%
Missing320
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean198880.29
Minimum195852.33
Maximum201966.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.6 KiB
2024-05-11T15:51:39.298860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195852.33
5-th percentile196733.25
Q1197841.42
median198746.8
Q3199954.04
95-th percentile201285.65
Maximum201966.26
Range6113.9369
Interquartile range (IQR)2112.623

Descriptive statistics

Standard deviation1355.9794
Coefficient of variation (CV)0.0068180684
Kurtosis-0.5991216
Mean198880.29
Median Absolute Deviation (MAD)1083.0753
Skewness0.13876824
Sum9.6437053 × 108
Variance1838680.2
MonotonicityNot monotonic
2024-05-11T15:51:39.490342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198150.300374121 49
 
0.9%
197567.849954354 32
 
0.6%
197650.653736722 27
 
0.5%
198286.311784052 26
 
0.5%
198504.772723631 23
 
0.4%
197804.357783157 22
 
0.4%
199045.043602772 20
 
0.4%
198068.926781947 19
 
0.4%
195960.546025512 19
 
0.4%
198324.653631679 19
 
0.4%
Other values (2677) 4593
88.9%
(Missing) 320
 
6.2%
ValueCountFrequency (%)
195852.325400317 1
 
< 0.1%
195960.546025512 19
0.4%
195981.007689291 1
 
< 0.1%
195998.140762432 3
 
0.1%
196010.602015955 1
 
< 0.1%
196023.58999141 1
 
< 0.1%
196036.761890225 3
 
0.1%
196047.812876606 1
 
< 0.1%
196048.079358067 1
 
< 0.1%
196065.157232057 3
 
0.1%
ValueCountFrequency (%)
201966.262330671 1
 
< 0.1%
201962.62904341 2
< 0.1%
201960.304346071 1
 
< 0.1%
201958.489788275 1
 
< 0.1%
201949.750623535 2
< 0.1%
201949.65163583 1
 
< 0.1%
201949.270716491 2
< 0.1%
201948.560407436 3
0.1%
201946.86632604 2
< 0.1%
201940.504033308 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2687
Distinct (%)55.4%
Missing320
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean452790.01
Minimum451543.63
Maximum457226.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.6 KiB
2024-05-11T15:51:39.742643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451543.63
5-th percentile451876.48
Q1452103.71
median452439
Q3453203.27
95-th percentile455417.43
Maximum457226.31
Range5682.683
Interquartile range (IQR)1099.5622

Descriptive statistics

Standard deviation1015.888
Coefficient of variation (CV)0.0022436184
Kurtosis4.4471808
Mean452790.01
Median Absolute Deviation (MAD)425.59321
Skewness2.0215938
Sum2.1955787 × 109
Variance1032028.4
MonotonicityNot monotonic
2024-05-11T15:51:39.965615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452019.212642931 49
 
0.9%
452567.159554494 31
 
0.6%
452368.519288991 27
 
0.5%
452091.444332546 26
 
0.5%
452018.161511911 23
 
0.4%
452216.539274871 22
 
0.4%
451939.677286976 20
 
0.4%
452087.030190231 19
 
0.4%
455612.122672739 19
 
0.4%
452252.812389497 19
 
0.4%
Other values (2677) 4594
88.9%
(Missing) 320
 
6.2%
ValueCountFrequency (%)
451543.629004831 5
0.1%
451596.900364676 1
 
< 0.1%
451653.730410822 1
 
< 0.1%
451658.76871749 4
 
0.1%
451664.399383222 1
 
< 0.1%
451670.158825331 2
 
< 0.1%
451678.787536538 4
 
0.1%
451682.368379486 11
0.2%
451683.728773742 2
 
< 0.1%
451727.374746801 3
 
0.1%
ValueCountFrequency (%)
457226.312037034 1
 
< 0.1%
457224.745016553 1
 
< 0.1%
457195.671211601 1
 
< 0.1%
457071.513223747 1
 
< 0.1%
457064.384905993 2
< 0.1%
457061.730282515 1
 
< 0.1%
457060.224383785 1
 
< 0.1%
457042.274454745 1
 
< 0.1%
457038.315149761 1
 
< 0.1%
457023.752164733 4
0.1%

위생업태명
Categorical

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
커피숍
1205 
다방
1190 
<NA>
893 
기타 휴게음식점
675 
일반조리판매
302 
Other values (12)
904 

Length

Max length8
Median length6
Mean length3.9050106
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 1205
23.3%
다방 1190
23.0%
<NA> 893
17.3%
기타 휴게음식점 675
13.1%
일반조리판매 302
 
5.8%
과자점 301
 
5.8%
패스트푸드 254
 
4.9%
편의점 172
 
3.3%
전통찻집 115
 
2.2%
푸드트럭 39
 
0.8%
Other values (7) 23
 
0.4%

Length

2024-05-11T15:51:40.180217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1205
20.6%
다방 1190
20.4%
na 893
15.3%
기타 675
11.6%
휴게음식점 675
11.6%
일반조리판매 302
 
5.2%
과자점 301
 
5.2%
패스트푸드 254
 
4.3%
편의점 172
 
2.9%
전통찻집 115
 
2.0%
Other values (8) 62
 
1.1%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.4%
Missing3121
Missing (%)60.4%
Infinite0
Infinite (%)0.0%
Mean0.18798828
Minimum0
Maximum46
Zeros1817
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size45.6 KiB
2024-05-11T15:51:40.341918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum46
Range46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1928431
Coefficient of variation (CV)6.3453057
Kurtosis1076.0403
Mean0.18798828
Median Absolute Deviation (MAD)0
Skewness29.079619
Sum385
Variance1.4228747
MonotonicityNot monotonic
2024-05-11T15:51:40.514136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 1817
35.2%
1 175
 
3.4%
2 29
 
0.6%
3 15
 
0.3%
4 6
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
15 1
 
< 0.1%
46 1
 
< 0.1%
(Missing) 3121
60.4%
ValueCountFrequency (%)
0 1817
35.2%
1 175
 
3.4%
2 29
 
0.6%
3 15
 
0.3%
4 6
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
15 1
 
< 0.1%
46 1
 
< 0.1%
ValueCountFrequency (%)
46 1
 
< 0.1%
15 1
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
4 6
 
0.1%
3 15
 
0.3%
2 29
 
0.6%
1 175
 
3.4%
0 1817
35.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.5%
Missing3113
Missing (%)60.2%
Infinite0
Infinite (%)0.0%
Mean0.92607004
Minimum0
Maximum14
Zeros1161
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size45.6 KiB
2024-05-11T15:51:40.673782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum14
Range14
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2700485
Coefficient of variation (CV)1.3714389
Kurtosis7.6488994
Mean0.92607004
Median Absolute Deviation (MAD)0
Skewness1.8022698
Sum1904
Variance1.6130232
MonotonicityNot monotonic
2024-05-11T15:51:40.840321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 1161
 
22.5%
2 413
 
8.0%
1 235
 
4.5%
3 190
 
3.7%
4 40
 
0.8%
5 7
 
0.1%
6 4
 
0.1%
7 2
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
(Missing) 3113
60.2%
ValueCountFrequency (%)
0 1161
22.5%
1 235
 
4.5%
2 413
 
8.0%
3 190
 
3.7%
4 40
 
0.8%
5 7
 
0.1%
6 4
 
0.1%
7 2
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
14 1
 
< 0.1%
10 1
 
< 0.1%
8 2
 
< 0.1%
7 2
 
< 0.1%
6 4
 
0.1%
5 7
 
0.1%
4 40
 
0.8%
3 190
3.7%
2 413
8.0%
1 235
4.5%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
3330 
기타
1516 
유흥업소밀집지역
 
168
주택가주변
 
128
학교정화(상대)
 
17
Other values (3)
 
10

Length

Max length8
Median length4
Mean length3.5865738
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3330
64.4%
기타 1516
29.3%
유흥업소밀집지역 168
 
3.3%
주택가주변 128
 
2.5%
학교정화(상대) 17
 
0.3%
학교정화(절대) 5
 
0.1%
아파트지역 4
 
0.1%
결혼예식장주변 1
 
< 0.1%

Length

2024-05-11T15:51:41.114322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:41.316788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3330
64.4%
기타 1516
29.3%
유흥업소밀집지역 168
 
3.3%
주택가주변 128
 
2.5%
학교정화(상대 17
 
0.3%
학교정화(절대 5
 
0.1%
아파트지역 4
 
0.1%
결혼예식장주변 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
3528 
기타
751 
갑
594 
자율
 
218
을
 
42
Other values (3)
 
36

Length

Max length4
Median length4
Mean length3.2420197
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3528
68.3%
기타 751
 
14.5%
갑 594
 
11.5%
자율 218
 
4.2%
을 42
 
0.8%
지도 15
 
0.3%
우수 11
 
0.2%
관리 10
 
0.2%

Length

2024-05-11T15:51:41.540258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:41.762379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3528
68.3%
기타 751
 
14.5%
갑 594
 
11.5%
자율 218
 
4.2%
을 42
 
0.8%
지도 15
 
0.3%
우수 11
 
0.2%
관리 10
 
0.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
3093 
상수도전용
2063 
상수도(음용)지하수(주방용)겸용
 
11
간이상수도
 
2

Length

Max length17
Median length4
Mean length4.4271619
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3093
59.8%
상수도전용 2063
39.9%
상수도(음용)지하수(주방용)겸용 11
 
0.2%
간이상수도 2
 
< 0.1%

Length

2024-05-11T15:51:41.995185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:42.194044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3093
59.8%
상수도전용 2063
39.9%
상수도(음용)지하수(주방용)겸용 11
 
0.2%
간이상수도 2
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
4959 
0
 
210

Length

Max length4
Median length4
Mean length3.8781196
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> 4959
95.9%
0 210
 
4.1%

Length

2024-05-11T15:51:42.411868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:42.609822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4959
95.9%
0 210
 
4.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
4955 
0
 
214

Length

Max length4
Median length4
Mean length3.875798
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> 4955
95.9%
0 214
 
4.1%

Length

2024-05-11T15:51:43.155439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:43.342990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4955
95.9%
0 214
 
4.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
4955 
0
 
214

Length

Max length4
Median length4
Mean length3.875798
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> 4955
95.9%
0 214
 
4.1%

Length

2024-05-11T15:51:43.519540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:43.693689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4955
95.9%
0 214
 
4.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
4955 
0
 
214

Length

Max length4
Median length4
Mean length3.875798
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> 4955
95.9%
0 214
 
4.1%

Length

2024-05-11T15:51:43.892647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:44.098644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4955
95.9%
0 214
 
4.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
4955 
0
 
214

Length

Max length4
Median length4
Mean length3.875798
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> 4955
95.9%
0 214
 
4.1%

Length

2024-05-11T15:51:44.303413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:44.492765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4955
95.9%
0 214
 
4.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5169
Missing (%)100.0%
Memory size45.6 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
4955 
0
 
214

Length

Max length4
Median length4
Mean length3.875798
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> 4955
95.9%
0 214
 
4.1%

Length

2024-05-11T15:51:44.650451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:44.805269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4955
95.9%
0 214
 
4.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
4955 
0
 
214

Length

Max length4
Median length4
Mean length3.875798
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> 4955
95.9%
0 214
 
4.1%

Length

2024-05-11T15:51:44.972002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:45.141743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4955
95.9%
0 214
 
4.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing893
Missing (%)17.3%
Memory size10.2 KiB
False
4245 
True
 
31
(Missing)
893 
ValueCountFrequency (%)
False 4245
82.1%
True 31
 
0.6%
(Missing) 893
 
17.3%
2024-05-11T15:51:45.267877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct2617
Distinct (%)61.2%
Missing893
Missing (%)17.3%
Infinite0
Infinite (%)0.0%
Mean58.405334
Minimum0
Maximum1096.62
Zeros76
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size45.6 KiB
2024-05-11T15:51:45.450305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q116
median37.98
Q376.005
95-th percentile180.535
Maximum1096.62
Range1096.62
Interquartile range (IQR)60.005

Descriptive statistics

Standard deviation67.540935
Coefficient of variation (CV)1.1564172
Kurtosis24.766108
Mean58.405334
Median Absolute Deviation (MAD)26.415
Skewness3.5381223
Sum249741.21
Variance4561.7779
MonotonicityNot monotonic
2024-05-11T15:51:45.672776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 111
 
2.1%
0.0 76
 
1.5%
6.6 71
 
1.4%
10.0 70
 
1.4%
33.0 43
 
0.8%
9.0 42
 
0.8%
16.5 37
 
0.7%
15.0 33
 
0.6%
9.9 32
 
0.6%
13.2 30
 
0.6%
Other values (2607) 3731
72.2%
(Missing) 893
 
17.3%
ValueCountFrequency (%)
0.0 76
1.5%
1.3 1
 
< 0.1%
1.5 3
 
0.1%
1.6 1
 
< 0.1%
1.65 1
 
< 0.1%
2.0 11
 
0.2%
2.24 1
 
< 0.1%
2.3 1
 
< 0.1%
2.36 1
 
< 0.1%
2.4 2
 
< 0.1%
ValueCountFrequency (%)
1096.62 1
< 0.1%
695.47 1
< 0.1%
628.56 1
< 0.1%
582.26 1
< 0.1%
565.0 1
< 0.1%
537.87 1
< 0.1%
537.18 1
< 0.1%
530.68 1
< 0.1%
527.08 1
< 0.1%
496.3 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.5 KiB
<NA>
5168 
0
 
1

Length

Max length4
Median length4
Mean length3.9994196
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5168
> 99.9%
0 1
 
< 0.1%

Length

2024-05-11T15:51:45.909968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:46.073433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5168
> 99.9%
0 1
 
< 0.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5169
Missing (%)100.0%
Memory size45.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5169
Missing (%)100.0%
Memory size45.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030000003000000-104-1964-0922719641203<NA>3폐업2폐업19920618<NA><NA><NA>0202674693<NA>110430서울특별시 종로구 장사동 147-2번지<NA><NA>청수2002-07-15 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방01기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N2.4<NA><NA><NA>
130000003000000-104-1965-0917419651030<NA>3폐업2폐업19941201<NA><NA><NA>0207255360<NA>110160서울특별시 종로구 공평동 119-0번지<NA><NA>태을2001-11-20 00:00:00I2018-08-31 23:59:59.0다방198432.497187452113.670898다방01기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N56.62<NA><NA><NA>
230000003000000-104-1965-0921619651010<NA>3폐업2폐업20120323<NA><NA><NA>0207633064<NA>110840서울특별시 종로구 창신동 154-1번지 지상2층서울특별시 종로구 종로 313-1 (창신동,지상2층)3105봉다방2012-03-12 13:27:09I2018-08-31 23:59:59.0다방201040.562597452226.799878다방01기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N58.3<NA><NA><NA>
330000003000000-104-1965-0960119651223<NA>3폐업2폐업19960430<NA><NA><NA>02 7636226<NA>110843서울특별시 종로구 창신동 696-1번지<NA><NA>길2001-09-29 00:00:00I2018-08-31 23:59:59.0다방200811.925354452162.569488다방04기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N119.72<NA><NA><NA>
430000003000000-104-1966-0923819661014<NA>3폐업2폐업19930804<NA><NA><NA>0202654710<NA>110430서울특별시 종로구 장사동 212번지<NA><NA>장미2002-07-15 00:00:00I2018-08-31 23:59:59.0다방199333.563376451884.604411다방01기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N76.12<NA><NA><NA>
530000003000000-104-1966-0925919660720<NA>3폐업2폐업20060609<NA><NA><NA>0209582020<NA>110827서울특별시 종로구 숭인동 1243-0번지<NA><NA>돌2001-09-29 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방10기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N108.8<NA><NA><NA>
630000003000000-104-1966-0931719660716<NA>3폐업2폐업19961002<NA><NA><NA>02 7350698<NA>110061서울특별시 종로구 신문로1가 25-0번지<NA><NA>시티파크2001-09-29 00:00:00I2018-08-31 23:59:59.0다방197680.78008452016.543891다방02기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N104.68<NA><NA><NA>
730000003000000-104-1966-0973319661205<NA>3폐업2폐업20020507<NA><NA><NA>0202656858<NA>110420서울특별시 종로구 관수동 120번지<NA><NA>호2001-12-27 00:00:00I2018-08-31 23:59:59.0과자점<NA><NA>과자점01기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830000003000000-104-1966-0977519661231<NA>3폐업2폐업20130909<NA><NA><NA>0207642370<NA>110370서울특별시 종로구 묘동 60-1번지<NA><NA>백궁2001-12-27 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방04기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N131.46<NA><NA><NA>
930000003000000-104-1967-0877719671109<NA>3폐업2폐업20021022<NA><NA><NA>0209477611<NA>110827서울특별시 종로구 숭인동 1243-0번지<NA><NA>(주)롯데리아신설점2001-09-29 00:00:00I2018-08-31 23:59:59.0과자점<NA><NA>과자점12기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N129.38<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
515930000003000000-104-2024-000572024-04-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>38.79110-320서울특별시 종로구 낙원동 211 젬누리빌딩서울특별시 종로구 수표로 115-1, 젬누리빌딩 1층 1호 (낙원동)3140빽다방 종로3가낙원점2024-04-16 14:20:42I2023-12-03 23:08:00.0커피숍198960.877015452149.495588<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
516030000003000000-104-2024-000582024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>58.19110-250서울특별시 종로구 재동 25-2서울특별시 종로구 북촌로5길 3, 지상 1층 (재동)3060이오이2024-04-18 17:29:40I2023-12-03 22:00:00.0커피숍198578.052244452984.933442<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
516130000003000000-104-2024-000592024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0110-524서울특별시 종로구 명륜4가 187 이화빌딩서울특별시 종로구 창경궁로 236, 이화빌딩 5층 (명륜4가)3079스틸시리즈PC방2024-04-24 13:45:20I2023-12-03 22:06:00.0기타 휴게음식점199821.627625453360.147414<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
516230000003000000-104-2024-000602024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.46110-524서울특별시 종로구 명륜4가 113-1 대학로스타시티빌딩서울특별시 종로구 대학로11길 23, 대학로스타시티빌딩 제1층 제105호 (명륜4가)3079요거트 아이스크림의 정석 대학로점2024-04-24 14:04:27I2023-12-03 22:06:00.0아이스크림199972.881432453308.674807<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
516330000003000000-104-2024-000612024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>110-821서울특별시 종로구 세종로 80-1 세종로지하주차장 지상 세종로공원 푸드존 일대서울특별시 종로구 세종대로 지하 189, 지상 세종로공원 푸드존 일대 (세종로)3172보끄보끄2024-04-24 14:38:05I2023-12-03 22:06:00.0푸드트럭197802.707703452342.759829<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
516430000003000000-104-2024-000622024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>268.56110-522서울특별시 종로구 명륜2가 24-5서울특별시 종로구 대명길 6 (명륜2가)3077투썸플레이스 혜화대명로점2024-04-25 14:03:39I2023-12-03 22:07:00.0커피숍200024.959536453496.248461<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
516530000003000000-104-2024-000632024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3110-126서울특별시 종로구 종로6가 203-3서울특별시 종로구 율곡로29길 10, 지상 1층 (종로6가)3099효지티부2024-05-03 14:25:38I2023-12-05 00:05:00.0커피숍200584.538189452411.33549<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
516630000003000000-104-2024-000642024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA>02 379 811223.0110-847서울특별시 종로구 평창동 321-2서울특별시 종로구 평창문화로 43-1, 지상 1층 (평창동)3008유캔두잇 평창동점2024-05-07 14:53:25I2023-12-05 00:09:00.0커피숍196937.164919455902.559351<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
516730000003000000-104-2024-000652024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>198.41110-756서울특별시 종로구 적선동 80 적선현대빌딩서울특별시 종로구 사직로 130, 적선현대빌딩 지상 1층 2호 (적선동)3170오커쇼어2024-05-09 11:45:29I2023-12-04 23:01:00.0커피숍197567.849954452567.159554<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
516830000003000000-104-2024-000662024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA>02 738101013.0110-240서울특별시 종로구 안국동 175-3서울특별시 종로구 율곡로 39, 안국빌딩 신관1층 (안국동)3061서울동행상회2024-05-09 17:07:27I2023-12-04 23:01:00.0기타 휴게음식점198507.43712452641.178442<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>