Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells89180
Missing cells (%)20.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 MiB
Average record size in memory382.0 B

Variable types

Categorical20
Text7
DateTime3
Unsupported7
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-18664/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
급수시설구분명 is highly imbalanced (54.4%)Imbalance
총인원 is highly imbalanced (74.7%)Imbalance
본사종업원수 is highly imbalanced (74.7%)Imbalance
공장사무직종업원수 is highly imbalanced (74.7%)Imbalance
공장판매직종업원수 is highly imbalanced (74.7%)Imbalance
공장생산직종업원수 is highly imbalanced (74.7%)Imbalance
보증액 is highly imbalanced (74.7%)Imbalance
월세액 is highly imbalanced (74.7%)Imbalance
다중이용업소여부 is highly imbalanced (83.1%)Imbalance
전통업소지정번호 is highly imbalanced (91.5%)Imbalance
전통업소주된음식 is highly imbalanced (88.3%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2081 (20.8%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 3184 (31.8%) missing valuesMissing
도로명주소 has 5439 (54.4%) missing valuesMissing
도로명우편번호 has 5531 (55.3%) missing valuesMissing
좌표정보(X) has 911 (9.1%) missing valuesMissing
좌표정보(Y) has 911 (9.1%) missing valuesMissing
남성종사자수 has 3956 (39.6%) missing valuesMissing
여성종사자수 has 3933 (39.3%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1558 (15.6%) missing valuesMissing
시설총규모 has 1558 (15.6%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 43.64996812)Skewed
여성종사자수 is highly skewed (γ1 = 21.23909667)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
소재지면적 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
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 4550 (45.5%) zerosZeros
여성종사자수 has 3835 (38.4%) zerosZeros

Reproduction

Analysis started2024-04-17 19:12:19.178250
Analysis finished2024-04-17 19:12:21.197430
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3120000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 10000
100.0%

Length

2024-04-18T04:12:21.244157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:21.308106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T04:12:21.444220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3120000-101-2003-00342
2nd row3120000-101-1993-06248
3rd row3120000-101-2021-00301
4th row3120000-101-1993-06171
5th row3120000-101-1992-07349
ValueCountFrequency (%)
3120000-101-2003-00342 1
 
< 0.1%
3120000-101-2021-00156 1
 
< 0.1%
3120000-101-2020-00147 1
 
< 0.1%
3120000-101-2023-00183 1
 
< 0.1%
3120000-101-1991-04697 1
 
< 0.1%
3120000-101-1991-03627 1
 
< 0.1%
3120000-101-2018-00252 1
 
< 0.1%
3120000-101-1991-06330 1
 
< 0.1%
3120000-101-1992-05494 1
 
< 0.1%
3120000-101-1992-07033 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-18T04:12:21.696380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 78381
35.6%
1 42391
19.3%
- 30000
 
13.6%
2 21854
 
9.9%
3 14794
 
6.7%
9 11634
 
5.3%
8 4606
 
2.1%
4 4189
 
1.9%
5 4077
 
1.9%
7 4070
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 78381
41.3%
1 42391
22.3%
2 21854
 
11.5%
3 14794
 
7.8%
9 11634
 
6.1%
8 4606
 
2.4%
4 4189
 
2.2%
5 4077
 
2.1%
7 4070
 
2.1%
6 4004
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 78381
35.6%
1 42391
19.3%
- 30000
 
13.6%
2 21854
 
9.9%
3 14794
 
6.7%
9 11634
 
5.3%
8 4606
 
2.1%
4 4189
 
1.9%
5 4077
 
1.9%
7 4070
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 78381
35.6%
1 42391
19.3%
- 30000
 
13.6%
2 21854
 
9.9%
3 14794
 
6.7%
9 11634
 
5.3%
8 4606
 
2.1%
4 4189
 
1.9%
5 4077
 
1.9%
7 4070
 
1.8%
Distinct6274
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1903-10-20 00:00:00
Maximum2024-04-15 00:00:00
2024-04-18T04:12:21.803782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:12:21.904393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
7919 
1
2081 

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 7919
79.2%
1 2081
 
20.8%

Length

2024-04-18T04:12:22.003237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:22.070265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7919
79.2%
1 2081
 
20.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7919 
영업/정상
2081 

Length

Max length5
Median length2
Mean length2.6243
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7919
79.2%
영업/정상 2081
 
20.8%

Length

2024-04-18T04:12:22.146269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:22.216831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7919
79.2%
영업/정상 2081
 
20.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7919 
1
2081 

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 7919
79.2%
1 2081
 
20.8%

Length

2024-04-18T04:12:22.287603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:22.355054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7919
79.2%
1 2081
 
20.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7919 
영업
2081 

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 7919
79.2%
영업 2081
 
20.8%

Length

2024-04-18T04:12:22.424699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:22.492916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7919
79.2%
영업 2081
 
20.8%

폐업일자
Date

MISSING 

Distinct4514
Distinct (%)57.0%
Missing2081
Missing (%)20.8%
Memory size156.2 KiB
Minimum1988-12-06 00:00:00
Maximum2024-04-16 00:00:00
2024-04-18T04:12:22.571837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:12:22.679508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct6273
Distinct (%)92.0%
Missing3184
Missing (%)31.8%
Memory size156.2 KiB
2024-04-18T04:12:22.961177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.221538
Min length2

Characters and Unicode

Total characters69670
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6074 ?
Unique (%)89.1%

Sample

1st row0203921097
2nd row0203924763
3rd row0203338752
4th row0203942672
5th row0203745036
ValueCountFrequency (%)
02 4026
33.3%
0200000000 166
 
1.4%
363 63
 
0.5%
365 56
 
0.5%
313 54
 
0.4%
0 52
 
0.4%
312 51
 
0.4%
394 48
 
0.4%
393 46
 
0.4%
070 45
 
0.4%
Other values (6252) 7473
61.9%
2024-04-18T04:12:23.340355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14377
20.6%
2 11470
16.5%
3 10834
15.6%
6776
9.7%
6 4221
 
6.1%
7 4161
 
6.0%
9 3900
 
5.6%
1 3803
 
5.5%
5 3607
 
5.2%
4 3468
 
5.0%
Other values (2) 3053
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62893
90.3%
Space Separator 6776
 
9.7%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14377
22.9%
2 11470
18.2%
3 10834
17.2%
6 4221
 
6.7%
7 4161
 
6.6%
9 3900
 
6.2%
1 3803
 
6.0%
5 3607
 
5.7%
4 3468
 
5.5%
8 3052
 
4.9%
Space Separator
ValueCountFrequency (%)
6776
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14377
20.6%
2 11470
16.5%
3 10834
15.6%
6776
9.7%
6 4221
 
6.1%
7 4161
 
6.0%
9 3900
 
5.6%
1 3803
 
5.5%
5 3607
 
5.2%
4 3468
 
5.0%
Other values (2) 3053
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14377
20.6%
2 11470
16.5%
3 10834
15.6%
6776
9.7%
6 4221
 
6.1%
7 4161
 
6.0%
9 3900
 
5.6%
1 3803
 
5.5%
5 3607
 
5.2%
4 3468
 
5.0%
Other values (2) 3053
 
4.4%

소재지면적
Unsupported

REJECTED  UNSUPPORTED 

Missing74
Missing (%)0.7%
Memory size156.2 KiB
Distinct184
Distinct (%)1.8%
Missing22
Missing (%)0.2%
Memory size156.2 KiB
2024-04-18T04:12:23.596879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0962117
Min length6

Characters and Unicode

Total characters60828
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

Unique21 ?
Unique (%)0.2%

Sample

1st row120853
2nd row120808
3rd row120816
4th row120833
5th row120834
ValueCountFrequency (%)
120834 1017
 
10.2%
120833 585
 
5.9%
120808 512
 
5.1%
120805 437
 
4.4%
120857 334
 
3.3%
120809 316
 
3.2%
120825 297
 
3.0%
120807 286
 
2.9%
120848 274
 
2.7%
120100 271
 
2.7%
Other values (174) 5649
56.6%
2024-04-18T04:12:23.936611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15246
25.1%
1 12493
20.5%
2 11669
19.2%
8 9382
15.4%
3 3401
 
5.6%
4 2428
 
4.0%
5 2056
 
3.4%
7 1277
 
2.1%
6 1019
 
1.7%
- 960
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59868
98.4%
Dash Punctuation 960
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15246
25.5%
1 12493
20.9%
2 11669
19.5%
8 9382
15.7%
3 3401
 
5.7%
4 2428
 
4.1%
5 2056
 
3.4%
7 1277
 
2.1%
6 1019
 
1.7%
9 897
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 960
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60828
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15246
25.1%
1 12493
20.5%
2 11669
19.2%
8 9382
15.4%
3 3401
 
5.6%
4 2428
 
4.0%
5 2056
 
3.4%
7 1277
 
2.1%
6 1019
 
1.7%
- 960
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60828
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15246
25.1%
1 12493
20.5%
2 11669
19.2%
8 9382
15.4%
3 3401
 
5.6%
4 2428
 
4.0%
5 2056
 
3.4%
7 1277
 
2.1%
6 1019
 
1.7%
- 960
 
1.6%
Distinct7319
Distinct (%)73.4%
Missing22
Missing (%)0.2%
Memory size156.2 KiB
2024-04-18T04:12:24.182223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length64
Mean length25.684005
Min length15

Characters and Unicode

Total characters256275
Distinct characters343
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

Unique5802 ?
Unique (%)58.1%

Sample

1st row서울특별시 서대문구 홍제동 90-15번지 (지상1층)
2nd row서울특별시 서대문구 대현동 34-35번지
3rd row서울특별시 서대문구 북가좌동 371-12 국제빌딩
4th row서울특별시 서대문구 창천동 18-35번지
5th row서울특별시 서대문구 창천동 52-147번지
ValueCountFrequency (%)
서울특별시 9977
22.2%
서대문구 9975
22.2%
창천동 2097
 
4.7%
남가좌동 1550
 
3.4%
홍제동 1140
 
2.5%
대현동 962
 
2.1%
홍은동 950
 
2.1%
연희동 870
 
1.9%
북가좌동 803
 
1.8%
지상1층 793
 
1.8%
Other values (6204) 15892
35.3%
2024-04-18T04:12:24.731147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43341
 
16.9%
19977
 
7.8%
11185
 
4.4%
1 10740
 
4.2%
10015
 
3.9%
9995
 
3.9%
9991
 
3.9%
9985
 
3.9%
9979
 
3.9%
9977
 
3.9%
Other values (333) 111090
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150512
58.7%
Decimal Number 48879
 
19.1%
Space Separator 43341
 
16.9%
Dash Punctuation 9634
 
3.8%
Close Punctuation 1277
 
0.5%
Open Punctuation 1276
 
0.5%
Other Punctuation 871
 
0.3%
Uppercase Letter 407
 
0.2%
Math Symbol 51
 
< 0.1%
Lowercase Letter 25
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
19977
13.3%
11185
 
7.4%
10015
 
6.7%
9995
 
6.6%
9991
 
6.6%
9985
 
6.6%
9979
 
6.6%
9977
 
6.6%
9752
 
6.5%
9270
 
6.2%
Other values (286) 40386
26.8%
Uppercase Letter
ValueCountFrequency (%)
D 67
16.5%
C 65
16.0%
B 64
15.7%
M 64
15.7%
A 36
8.8%
E 14
 
3.4%
T 14
 
3.4%
S 12
 
2.9%
O 10
 
2.5%
R 10
 
2.5%
Other values (11) 51
12.5%
Decimal Number
ValueCountFrequency (%)
1 10740
22.0%
2 7469
15.3%
3 6749
13.8%
4 4380
9.0%
5 4356
8.9%
0 3625
 
7.4%
9 2979
 
6.1%
6 2974
 
6.1%
7 2922
 
6.0%
8 2685
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 842
96.7%
. 13
 
1.5%
@ 12
 
1.4%
: 2
 
0.2%
/ 2
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
e 19
76.0%
a 2
 
8.0%
b 2
 
8.0%
x 1
 
4.0%
l 1
 
4.0%
Space Separator
ValueCountFrequency (%)
43341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9634
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1277
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1276
100.0%
Math Symbol
ValueCountFrequency (%)
~ 51
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150510
58.7%
Common 105329
41.1%
Latin 434
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
19977
13.3%
11185
 
7.4%
10015
 
6.7%
9995
 
6.6%
9991
 
6.6%
9985
 
6.6%
9979
 
6.6%
9977
 
6.6%
9752
 
6.5%
9270
 
6.2%
Other values (284) 40384
26.8%
Latin
ValueCountFrequency (%)
D 67
15.4%
C 65
15.0%
B 64
14.7%
M 64
14.7%
A 36
8.3%
e 19
 
4.4%
E 14
 
3.2%
T 14
 
3.2%
S 12
 
2.8%
O 10
 
2.3%
Other values (17) 69
15.9%
Common
ValueCountFrequency (%)
43341
41.1%
1 10740
 
10.2%
- 9634
 
9.1%
2 7469
 
7.1%
3 6749
 
6.4%
4 4380
 
4.2%
5 4356
 
4.1%
0 3625
 
3.4%
9 2979
 
2.8%
6 2974
 
2.8%
Other values (10) 9082
 
8.6%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150510
58.7%
ASCII 105761
41.3%
Number Forms 2
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43341
41.0%
1 10740
 
10.2%
- 9634
 
9.1%
2 7469
 
7.1%
3 6749
 
6.4%
4 4380
 
4.1%
5 4356
 
4.1%
0 3625
 
3.4%
9 2979
 
2.8%
6 2974
 
2.8%
Other values (36) 9514
 
9.0%
Hangul
ValueCountFrequency (%)
19977
13.3%
11185
 
7.4%
10015
 
6.7%
9995
 
6.6%
9991
 
6.6%
9985
 
6.6%
9979
 
6.6%
9977
 
6.6%
9752
 
6.5%
9270
 
6.2%
Other values (284) 40384
26.8%
Number Forms
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct4032
Distinct (%)88.4%
Missing5439
Missing (%)54.4%
Memory size156.2 KiB
2024-04-18T04:12:24.949867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length61
Mean length31.363517
Min length22

Characters and Unicode

Total characters143049
Distinct characters352
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

Unique3643 ?
Unique (%)79.9%

Sample

1st row서울특별시 서대문구 수색로 144, 국제빌딩 지1층 106,107호 (북가좌동)
2nd row서울특별시 서대문구 증가로10길 50, 2층 (남가좌동)
3rd row서울특별시 서대문구 홍제내길 142 (홍제동)
4th row서울특별시 서대문구 독립문로 66, 1층 (냉천동)
5th row서울특별시 서대문구 가좌로 100 (홍은동,(지상1층))
ValueCountFrequency (%)
서울특별시 4560
 
16.7%
서대문구 4558
 
16.7%
1층 1432
 
5.3%
창천동 893
 
3.3%
홍제동 470
 
1.7%
남가좌동 468
 
1.7%
연희동 461
 
1.7%
홍은동 399
 
1.5%
2층 358
 
1.3%
대현동 339
 
1.2%
Other values (2112) 13305
48.8%
2024-04-18T04:12:25.287490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22690
 
15.9%
9263
 
6.5%
1 6072
 
4.2%
5641
 
3.9%
) 5025
 
3.5%
( 5025
 
3.5%
4679
 
3.3%
4676
 
3.3%
4643
 
3.2%
4579
 
3.2%
Other values (342) 70756
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85192
59.6%
Space Separator 22690
 
15.9%
Decimal Number 19449
 
13.6%
Close Punctuation 5025
 
3.5%
Open Punctuation 5025
 
3.5%
Other Punctuation 4072
 
2.8%
Dash Punctuation 1060
 
0.7%
Uppercase Letter 437
 
0.3%
Math Symbol 72
 
0.1%
Lowercase Letter 25
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9263
 
10.9%
5641
 
6.6%
4679
 
5.5%
4676
 
5.5%
4643
 
5.5%
4579
 
5.4%
4566
 
5.4%
4563
 
5.4%
4560
 
5.4%
4009
 
4.7%
Other values (295) 34013
39.9%
Uppercase Letter
ValueCountFrequency (%)
B 83
19.0%
C 77
17.6%
D 73
16.7%
M 72
16.5%
A 36
8.2%
E 13
 
3.0%
T 11
 
2.5%
S 10
 
2.3%
I 9
 
2.1%
O 9
 
2.1%
Other values (12) 44
10.1%
Decimal Number
ValueCountFrequency (%)
1 6072
31.2%
2 3029
15.6%
3 2071
 
10.6%
4 1493
 
7.7%
0 1436
 
7.4%
5 1419
 
7.3%
7 1192
 
6.1%
6 991
 
5.1%
8 921
 
4.7%
9 825
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 20
80.0%
b 2
 
8.0%
l 1
 
4.0%
x 1
 
4.0%
a 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 4060
99.7%
. 10
 
0.2%
/ 1
 
< 0.1%
? 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
22690
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5025
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5025
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1060
100.0%
Math Symbol
ValueCountFrequency (%)
~ 72
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85192
59.6%
Common 57393
40.1%
Latin 464
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9263
 
10.9%
5641
 
6.6%
4679
 
5.5%
4676
 
5.5%
4643
 
5.5%
4579
 
5.4%
4566
 
5.4%
4563
 
5.4%
4560
 
5.4%
4009
 
4.7%
Other values (295) 34013
39.9%
Latin
ValueCountFrequency (%)
B 83
17.9%
C 77
16.6%
D 73
15.7%
M 72
15.5%
A 36
7.8%
e 20
 
4.3%
E 13
 
2.8%
T 11
 
2.4%
S 10
 
2.2%
I 9
 
1.9%
Other values (18) 60
12.9%
Common
ValueCountFrequency (%)
22690
39.5%
1 6072
 
10.6%
) 5025
 
8.8%
( 5025
 
8.8%
, 4060
 
7.1%
2 3029
 
5.3%
3 2071
 
3.6%
4 1493
 
2.6%
0 1436
 
2.5%
5 1419
 
2.5%
Other values (9) 5073
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85192
59.6%
ASCII 57855
40.4%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22690
39.2%
1 6072
 
10.5%
) 5025
 
8.7%
( 5025
 
8.7%
, 4060
 
7.0%
2 3029
 
5.2%
3 2071
 
3.6%
4 1493
 
2.6%
0 1436
 
2.5%
5 1419
 
2.5%
Other values (36) 5535
 
9.6%
Hangul
ValueCountFrequency (%)
9263
 
10.9%
5641
 
6.6%
4679
 
5.5%
4676
 
5.5%
4643
 
5.5%
4579
 
5.4%
4566
 
5.4%
4563
 
5.4%
4560
 
5.4%
4009
 
4.7%
Other values (295) 34013
39.9%
Number Forms
ValueCountFrequency (%)
2
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct175
Distinct (%)3.9%
Missing5531
Missing (%)55.3%
Infinite0
Infinite (%)0.0%
Mean3719.373
Minimum3600
Maximum10383
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T04:12:25.395232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3600
5-th percentile3619
Q13672
median3722
Q33774
95-th percentile3789
Maximum10383
Range6783
Interquartile range (IQR)102

Descriptive statistics

Standard deviation114.8854
Coefficient of variation (CV)0.030888379
Kurtosis2533.7506
Mean3719.373
Median Absolute Deviation (MAD)52
Skewness43.649968
Sum16621878
Variance13198.656
MonotonicityNot monotonic
2024-04-18T04:12:25.519593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3789 274
 
2.7%
3788 252
 
2.5%
3766 218
 
2.2%
3777 162
 
1.6%
3712 124
 
1.2%
3665 123
 
1.2%
3776 114
 
1.1%
3787 106
 
1.1%
3735 98
 
1.0%
3707 92
 
0.9%
Other values (165) 2906
29.1%
(Missing) 5531
55.3%
ValueCountFrequency (%)
3600 7
 
0.1%
3601 4
 
< 0.1%
3602 18
 
0.2%
3603 7
 
0.1%
3604 11
 
0.1%
3605 49
0.5%
3606 5
 
0.1%
3607 4
 
< 0.1%
3610 6
 
0.1%
3611 14
 
0.1%
ValueCountFrequency (%)
10383 1
 
< 0.1%
4056 1
 
< 0.1%
4031 1
 
< 0.1%
3791 6
 
0.1%
3790 2
 
< 0.1%
3789 274
2.7%
3788 252
2.5%
3787 106
 
1.1%
3786 13
 
0.1%
3785 32
 
0.3%
Distinct8656
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T04:12:25.719995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length5.2902
Min length1

Characters and Unicode

Total characters52902
Distinct characters1116
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7815 ?
Unique (%)78.1%

Sample

1st row제이제이돈돈
2nd row카니발
3rd row성영에프엔디 마포점
4th row효성
5th row레넌호프
ValueCountFrequency (%)
신촌점 112
 
0.9%
전주식당 30
 
0.3%
이대점 29
 
0.2%
실내포장마차 27
 
0.2%
명지대점 26
 
0.2%
연희점 26
 
0.2%
홍제점 26
 
0.2%
식당 23
 
0.2%
카페 22
 
0.2%
서대문점 17
 
0.1%
Other values (9318) 11483
97.1%
2024-04-18T04:12:26.016982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1823
 
3.4%
1269
 
2.4%
1029
 
1.9%
958
 
1.8%
865
 
1.6%
770
 
1.5%
697
 
1.3%
) 586
 
1.1%
( 584
 
1.1%
579
 
1.1%
Other values (1106) 43742
82.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46453
87.8%
Space Separator 1823
 
3.4%
Lowercase Letter 1567
 
3.0%
Uppercase Letter 1123
 
2.1%
Close Punctuation 586
 
1.1%
Open Punctuation 584
 
1.1%
Decimal Number 562
 
1.1%
Other Punctuation 164
 
0.3%
Dash Punctuation 31
 
0.1%
Letter Number 5
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1269
 
2.7%
1029
 
2.2%
958
 
2.1%
865
 
1.9%
770
 
1.7%
697
 
1.5%
579
 
1.2%
567
 
1.2%
537
 
1.2%
530
 
1.1%
Other values (1026) 38652
83.2%
Lowercase Letter
ValueCountFrequency (%)
e 219
14.0%
a 164
 
10.5%
o 147
 
9.4%
i 117
 
7.5%
r 95
 
6.1%
n 93
 
5.9%
l 78
 
5.0%
f 65
 
4.1%
s 62
 
4.0%
t 59
 
3.8%
Other values (16) 468
29.9%
Uppercase Letter
ValueCountFrequency (%)
C 98
 
8.7%
E 82
 
7.3%
O 82
 
7.3%
B 82
 
7.3%
A 81
 
7.2%
T 65
 
5.8%
M 64
 
5.7%
N 58
 
5.2%
R 52
 
4.6%
I 49
 
4.4%
Other values (16) 410
36.5%
Decimal Number
ValueCountFrequency (%)
2 123
21.9%
1 118
21.0%
0 65
11.6%
3 49
 
8.7%
4 49
 
8.7%
9 48
 
8.5%
5 37
 
6.6%
6 29
 
5.2%
8 23
 
4.1%
7 21
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 54
32.9%
& 44
26.8%
, 29
17.7%
! 12
 
7.3%
' 9
 
5.5%
? 8
 
4.9%
: 4
 
2.4%
# 2
 
1.2%
% 1
 
0.6%
/ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
1823
100.0%
Close Punctuation
ValueCountFrequency (%)
) 586
100.0%
Open Punctuation
ValueCountFrequency (%)
( 584
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Letter Number
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46423
87.8%
Common 3754
 
7.1%
Latin 2695
 
5.1%
Han 30
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1269
 
2.7%
1029
 
2.2%
958
 
2.1%
865
 
1.9%
770
 
1.7%
697
 
1.5%
579
 
1.2%
567
 
1.2%
537
 
1.2%
530
 
1.1%
Other values (1000) 38622
83.2%
Latin
ValueCountFrequency (%)
e 219
 
8.1%
a 164
 
6.1%
o 147
 
5.5%
i 117
 
4.3%
C 98
 
3.6%
r 95
 
3.5%
n 93
 
3.5%
E 82
 
3.0%
O 82
 
3.0%
B 82
 
3.0%
Other values (43) 1516
56.3%
Common
ValueCountFrequency (%)
1823
48.6%
) 586
 
15.6%
( 584
 
15.6%
2 123
 
3.3%
1 118
 
3.1%
0 65
 
1.7%
. 54
 
1.4%
3 49
 
1.3%
4 49
 
1.3%
9 48
 
1.3%
Other values (17) 255
 
6.8%
Han
ValueCountFrequency (%)
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
1
 
3.3%
1
 
3.3%
1
 
3.3%
1
 
3.3%
1
 
3.3%
1
 
3.3%
Other values (16) 16
53.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46421
87.7%
ASCII 6443
 
12.2%
CJK 29
 
0.1%
Number Forms 5
 
< 0.1%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1823
28.3%
) 586
 
9.1%
( 584
 
9.1%
e 219
 
3.4%
a 164
 
2.5%
o 147
 
2.3%
2 123
 
1.9%
1 118
 
1.8%
i 117
 
1.8%
C 98
 
1.5%
Other values (68) 2464
38.2%
Hangul
ValueCountFrequency (%)
1269
 
2.7%
1029
 
2.2%
958
 
2.1%
865
 
1.9%
770
 
1.7%
697
 
1.5%
579
 
1.2%
567
 
1.2%
537
 
1.2%
530
 
1.1%
Other values (999) 38620
83.2%
Number Forms
ValueCountFrequency (%)
5
100.0%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
1
 
3.4%
Other values (15) 15
51.7%
None
ValueCountFrequency (%)
² 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Distinct6448
Distinct (%)64.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T04:12:26.256316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length18.9999
Min length18

Characters and Unicode

Total characters189999
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5900 ?
Unique (%)59.0%

Sample

1st row2004-06-21 00:00:00
2nd row2001-09-30 00:00:00
3rd row2022-03-14 17:11:24
4th row2001-09-30 00:00:00
5th row2000-05-12 00:00:00
ValueCountFrequency (%)
00:00:00 4729
 
23.6%
2001-09-30 1834
 
9.2%
2004-01-27 121
 
0.6%
2004-01-26 89
 
0.4%
2002-02-28 57
 
0.3%
2002-02-27 45
 
0.2%
2002-02-18 43
 
0.2%
2002-02-19 40
 
0.2%
2002-02-22 40
 
0.2%
2010-02-05 39
 
0.2%
Other values (8311) 12963
64.8%
2024-04-18T04:12:26.590701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 60925
32.1%
2 22586
 
11.9%
1 20501
 
10.8%
- 20000
 
10.5%
: 20000
 
10.5%
10000
 
5.3%
3 8678
 
4.6%
9 6260
 
3.3%
4 5870
 
3.1%
5 5245
 
2.8%
Other values (3) 9934
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 139999
73.7%
Dash Punctuation 20000
 
10.5%
Other Punctuation 20000
 
10.5%
Space Separator 10000
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60925
43.5%
2 22586
 
16.1%
1 20501
 
14.6%
3 8678
 
6.2%
9 6260
 
4.5%
4 5870
 
4.2%
5 5245
 
3.7%
7 3406
 
2.4%
6 3295
 
2.4%
8 3233
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%
Other Punctuation
ValueCountFrequency (%)
: 20000
100.0%
Space Separator
ValueCountFrequency (%)
10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 189999
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 60925
32.1%
2 22586
 
11.9%
1 20501
 
10.8%
- 20000
 
10.5%
: 20000
 
10.5%
10000
 
5.3%
3 8678
 
4.6%
9 6260
 
3.3%
4 5870
 
3.1%
5 5245
 
2.8%
Other values (3) 9934
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 189999
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 60925
32.1%
2 22586
 
11.9%
1 20501
 
10.8%
- 20000
 
10.5%
: 20000
 
10.5%
10000
 
5.3%
3 8678
 
4.6%
9 6260
 
3.3%
4 5870
 
3.1%
5 5245
 
2.8%
Other values (3) 9934
 
5.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7252 
U
2748 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7252
72.5%
U 2748
 
27.5%

Length

2024-04-18T04:12:26.698841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:26.766609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7252
72.5%
u 2748
 
27.5%
Distinct1261
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-18T04:12:26.845827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:12:26.945682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3748 
분식
1522 
경양식
1438 
정종/대포집/소주방
978 
기타
681 
Other values (21)
1633 

Length

Max length15
Median length2
Mean length3.2821
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row경양식
3rd row한식
4th row경양식
5th row분식

Common Values

ValueCountFrequency (%)
한식 3748
37.5%
분식 1522
15.2%
경양식 1438
 
14.4%
정종/대포집/소주방 978
 
9.8%
기타 681
 
6.8%
호프/통닭 545
 
5.5%
일식 306
 
3.1%
중국식 281
 
2.8%
통닭(치킨) 148
 
1.5%
까페 121
 
1.2%
Other values (16) 232
 
2.3%

Length

2024-04-18T04:12:27.047534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3748
37.5%
분식 1522
15.2%
경양식 1438
 
14.4%
정종/대포집/소주방 978
 
9.8%
기타 681
 
6.8%
호프/통닭 545
 
5.5%
일식 306
 
3.1%
중국식 281
 
2.8%
통닭(치킨 148
 
1.5%
까페 121
 
1.2%
Other values (16) 232
 
2.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3505
Distinct (%)38.6%
Missing911
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean194412.85
Minimum177915.68
Maximum197170.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T04:12:27.140168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum177915.68
5-th percentile192280.46
Q1193522.08
median194395.37
Q3195159.58
95-th percentile196752.76
Maximum197170.64
Range19254.957
Interquartile range (IQR)1637.5

Descriptive statistics

Standard deviation1251.9013
Coefficient of variation (CV)0.0064393961
Kurtosis2.8389191
Mean194412.85
Median Absolute Deviation (MAD)786.88723
Skewness-0.23469603
Sum1.7670184 × 109
Variance1567257
MonotonicityNot monotonic
2024-04-18T04:12:27.245367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194265.067639805 116
 
1.2%
194584.959249312 35
 
0.4%
192672.067512964 29
 
0.3%
196801.661639204 25
 
0.2%
194955.406353595 23
 
0.2%
192344.544098471 23
 
0.2%
195063.820722531 20
 
0.2%
191559.918118738 18
 
0.2%
192478.126428725 17
 
0.2%
195643.865636259 17
 
0.2%
Other values (3495) 8766
87.7%
(Missing) 911
 
9.1%
ValueCountFrequency (%)
177915.685 1
 
< 0.1%
191497.867040904 1
 
< 0.1%
191500.393722857 1
 
< 0.1%
191505.706772766 1
 
< 0.1%
191513.171871672 2
< 0.1%
191513.605808387 1
 
< 0.1%
191518.681259249 1
 
< 0.1%
191519.132033814 2
< 0.1%
191540.260492627 1
 
< 0.1%
191552.612967645 4
< 0.1%
ValueCountFrequency (%)
197170.642282034 1
 
< 0.1%
197147.394631349 4
 
< 0.1%
197144.015440398 17
0.2%
197121.041523674 1
 
< 0.1%
197096.672275034 2
 
< 0.1%
197092.765305706 1
 
< 0.1%
197088.194167189 1
 
< 0.1%
197085.338267982 1
 
< 0.1%
197078.51446791 2
 
< 0.1%
197073.021981074 4
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3503
Distinct (%)38.5%
Missing911
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean452060.06
Minimum450329.33
Maximum463452.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T04:12:27.357246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450329.33
5-th percentile450501.17
Q1450689.14
median451704.44
Q3453203.05
95-th percentile454624.55
Maximum463452.84
Range13123.507
Interquartile range (IQR)2513.9132

Descriptive statistics

Standard deviation1433.3206
Coefficient of variation (CV)0.0031706419
Kurtosis-0.56730021
Mean452060.06
Median Absolute Deviation (MAD)1085.1793
Skewness0.59349177
Sum4.1087739 × 109
Variance2054407.9
MonotonicityNot monotonic
2024-04-18T04:12:27.464209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450433.691021245 116
 
1.2%
451381.585492051 36
 
0.4%
452221.960661496 29
 
0.3%
451267.809661546 25
 
0.2%
452002.278744736 23
 
0.2%
450620.463748751 23
 
0.2%
450597.874088644 20
 
0.2%
452563.291844785 18
 
0.2%
451976.482254131 17
 
0.2%
450576.385496383 17
 
0.2%
Other values (3493) 8765
87.6%
(Missing) 911
 
9.1%
ValueCountFrequency (%)
450329.327525435 1
 
< 0.1%
450371.790065047 1
 
< 0.1%
450375.488731434 1
 
< 0.1%
450378.207939919 1
 
< 0.1%
450379.614037537 2
 
< 0.1%
450387.139950052 4
< 0.1%
450387.943584382 2
 
< 0.1%
450388.329359668 8
0.1%
450391.53849739 7
0.1%
450392.774100774 8
0.1%
ValueCountFrequency (%)
463452.835 1
< 0.1%
455755.483684061 1
< 0.1%
455735.363417848 1
< 0.1%
455710.429910779 1
< 0.1%
455689.567479919 2
< 0.1%
455616.624014493 1
< 0.1%
455565.505109819 2
< 0.1%
455557.444744824 1
< 0.1%
455521.138091877 1
< 0.1%
455484.478875325 2
< 0.1%

위생업태명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3108 
<NA>
1559 
분식
1432 
경양식
1276 
정종/대포집/소주방
929 
Other values (21)
1696 

Length

Max length15
Median length2
Mean length3.4548
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row경양식
3rd row한식
4th row경양식
5th row분식

Common Values

ValueCountFrequency (%)
한식 3108
31.1%
<NA> 1559
15.6%
분식 1432
14.3%
경양식 1276
12.8%
정종/대포집/소주방 929
 
9.3%
호프/통닭 415
 
4.2%
기타 412
 
4.1%
중국식 222
 
2.2%
일식 220
 
2.2%
통닭(치킨) 135
 
1.4%
Other values (16) 292
 
2.9%

Length

2024-04-18T04:12:27.575031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3108
31.1%
na 1559
15.6%
분식 1432
14.3%
경양식 1276
12.8%
정종/대포집/소주방 929
 
9.3%
호프/통닭 415
 
4.2%
기타 412
 
4.1%
중국식 222
 
2.2%
일식 220
 
2.2%
통닭(치킨 135
 
1.4%
Other values (16) 292
 
2.9%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.2%
Missing3956
Missing (%)39.6%
Infinite0
Infinite (%)0.0%
Mean0.35473197
Minimum0
Maximum15
Zeros4550
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T04:12:27.679991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.75311199
Coefficient of variation (CV)2.1230452
Kurtosis32.843638
Mean0.35473197
Median Absolute Deviation (MAD)0
Skewness3.7307067
Sum2144
Variance0.56717767
MonotonicityNot monotonic
2024-04-18T04:12:27.763612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 4550
45.5%
1 1045
 
10.4%
2 321
 
3.2%
3 86
 
0.9%
4 29
 
0.3%
5 7
 
0.1%
6 3
 
< 0.1%
15 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
(Missing) 3956
39.6%
ValueCountFrequency (%)
0 4550
45.5%
1 1045
 
10.4%
2 321
 
3.2%
3 86
 
0.9%
4 29
 
0.3%
5 7
 
0.1%
6 3
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
6 3
 
< 0.1%
5 7
 
0.1%
4 29
 
0.3%
3 86
 
0.9%
2 321
 
3.2%
1 1045
 
10.4%
0 4550
45.5%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct10
Distinct (%)0.2%
Missing3933
Missing (%)39.3%
Infinite0
Infinite (%)0.0%
Mean0.5309049
Minimum0
Maximum54
Zeros3835
Zeros (%)38.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T04:12:27.847294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum54
Range54
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0770632
Coefficient of variation (CV)2.028731
Kurtosis1004.1159
Mean0.5309049
Median Absolute Deviation (MAD)0
Skewness21.239097
Sum3221
Variance1.1600652
MonotonicityNot monotonic
2024-04-18T04:12:27.927731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 3835
38.4%
1 1521
 
15.2%
2 570
 
5.7%
3 95
 
0.9%
4 24
 
0.2%
5 12
 
0.1%
6 4
 
< 0.1%
7 3
 
< 0.1%
10 2
 
< 0.1%
54 1
 
< 0.1%
(Missing) 3933
39.3%
ValueCountFrequency (%)
0 3835
38.4%
1 1521
 
15.2%
2 570
 
5.7%
3 95
 
0.9%
4 24
 
0.2%
5 12
 
0.1%
6 4
 
< 0.1%
7 3
 
< 0.1%
10 2
 
< 0.1%
54 1
 
< 0.1%
ValueCountFrequency (%)
54 1
 
< 0.1%
10 2
 
< 0.1%
7 3
 
< 0.1%
6 4
 
< 0.1%
5 12
 
0.1%
4 24
 
0.2%
3 95
 
0.9%
2 570
 
5.7%
1 1521
 
15.2%
0 3835
38.4%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5316 
주택가주변
2270 
기타
1200 
유흥업소밀집지역
999 
학교정화(상대)
 
100
Other values (3)
 
115

Length

Max length8
Median length4
Mean length4.452
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5316
53.2%
주택가주변 2270
22.7%
기타 1200
 
12.0%
유흥업소밀집지역 999
 
10.0%
학교정화(상대) 100
 
1.0%
아파트지역 65
 
0.7%
학교정화(절대) 39
 
0.4%
결혼예식장주변 11
 
0.1%

Length

2024-04-18T04:12:28.022514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:28.120658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5316
53.2%
주택가주변 2270
22.7%
기타 1200
 
12.0%
유흥업소밀집지역 999
 
10.0%
학교정화(상대 100
 
1.0%
아파트지역 65
 
0.7%
학교정화(절대 39
 
0.4%
결혼예식장주변 11
 
0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5384 
기타
1692 
1286 
자율
669 
지도
600 
Other values (3)
 
369

Length

Max length4
Median length4
Mean length2.9142
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5384
53.8%
기타 1692
 
16.9%
1286
 
12.9%
자율 669
 
6.7%
지도 600
 
6.0%
340
 
3.4%
관리 19
 
0.2%
우수 10
 
0.1%

Length

2024-04-18T04:12:28.237800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:28.344923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5384
53.8%
기타 1692
 
16.9%
1286
 
12.9%
자율 669
 
6.7%
지도 600
 
6.0%
340
 
3.4%
관리 19
 
0.2%
우수 10
 
0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
5652 
<NA>
4248 
상수도(음용)지하수(주방용)겸용
 
97
간이상수도
 
2
지하수전용
 
1

Length

Max length17
Median length5
Mean length4.6916
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 5652
56.5%
<NA> 4248
42.5%
상수도(음용)지하수(주방용)겸용 97
 
1.0%
간이상수도 2
 
< 0.1%
지하수전용 1
 
< 0.1%

Length

2024-04-18T04:12:28.437357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:28.516396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 5652
56.5%
na 4248
42.5%
상수도(음용)지하수(주방용)겸용 97
 
1.0%
간이상수도 2
 
< 0.1%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9577 
0
 
423

Length

Max length4
Median length4
Mean length3.8731
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9577
95.8%
0 423
 
4.2%

Length

2024-04-18T04:12:28.605906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:28.678129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9577
95.8%
0 423
 
4.2%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9577 
0
 
423

Length

Max length4
Median length4
Mean length3.8731
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9577
95.8%
0 423
 
4.2%

Length

2024-04-18T04:12:28.753405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:28.824847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9577
95.8%
0 423
 
4.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9577 
0
 
423

Length

Max length4
Median length4
Mean length3.8731
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9577
95.8%
0 423
 
4.2%

Length

2024-04-18T04:12:28.902269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:28.975004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9577
95.8%
0 423
 
4.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9577 
0
 
423

Length

Max length4
Median length4
Mean length3.8731
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9577
95.8%
0 423
 
4.2%

Length

2024-04-18T04:12:29.051992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:29.123964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9577
95.8%
0 423
 
4.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9577 
0
 
423

Length

Max length4
Median length4
Mean length3.8731
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9577
95.8%
0 423
 
4.2%

Length

2024-04-18T04:12:29.205491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:29.278811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9577
95.8%
0 423
 
4.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9577 
0
 
423

Length

Max length4
Median length4
Mean length3.8731
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9577
95.8%
0 423
 
4.2%

Length

2024-04-18T04:12:29.358579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:29.432567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9577
95.8%
0 423
 
4.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9577 
0
 
423

Length

Max length4
Median length4
Mean length3.8731
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9577
95.8%
0 423
 
4.2%

Length

2024-04-18T04:12:29.509417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:29.580600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9577
95.8%
0 423
 
4.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1558
Missing (%)15.6%
Memory size97.7 KiB
False
8231 
True
 
211
(Missing)
1558 
ValueCountFrequency (%)
False 8231
82.3%
True 211
 
2.1%
(Missing) 1558
 
15.6%
2024-04-18T04:12:29.649111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct4352
Distinct (%)51.6%
Missing1558
Missing (%)15.6%
Infinite0
Infinite (%)0.0%
Mean64.944415
Minimum0
Maximum1709.57
Zeros89
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T04:12:29.729865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.22
Q125.385
median42.9
Q377
95-th percentile176.7325
Maximum1709.57
Range1709.57
Interquartile range (IQR)51.615

Descriptive statistics

Standard deviation84.995119
Coefficient of variation (CV)1.3087364
Kurtosis89.998598
Mean64.944415
Median Absolute Deviation (MAD)21.17
Skewness7.2799707
Sum548260.75
Variance7224.1703
MonotonicityNot monotonic
2024-04-18T04:12:29.832929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.4 164
 
1.6%
33.0 117
 
1.2%
23.1 108
 
1.1%
0.0 89
 
0.9%
29.7 85
 
0.9%
16.5 78
 
0.8%
19.8 77
 
0.8%
66.0 57
 
0.6%
30.0 49
 
0.5%
13.2 43
 
0.4%
Other values (4342) 7575
75.8%
(Missing) 1558
 
15.6%
ValueCountFrequency (%)
0.0 89
0.9%
3.12 1
 
< 0.1%
3.5 1
 
< 0.1%
3.78 1
 
< 0.1%
3.8 1
 
< 0.1%
4.52 1
 
< 0.1%
4.76 1
 
< 0.1%
4.95 1
 
< 0.1%
5.04 1
 
< 0.1%
5.07 1
 
< 0.1%
ValueCountFrequency (%)
1709.57 1
< 0.1%
1643.27 1
< 0.1%
1634.84 1
< 0.1%
1356.06 2
< 0.1%
1296.5 1
< 0.1%
1291.83 1
< 0.1%
1183.8 1
< 0.1%
1060.0 1
< 0.1%
1056.0 1
< 0.1%
961.02 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9619 
00032
 
376
.
 
1
00096
 
1
07725
 
1
Other values (2)
 
2

Length

Max length5
Median length4
Mean length4.0373
Min length1

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9619
96.2%
00032 376
 
3.8%
. 1
 
< 0.1%
00096 1
 
< 0.1%
07725 1
 
< 0.1%
1
 
< 0.1%
07299 1
 
< 0.1%

Length

2024-04-18T04:12:29.941318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:30.267059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9619
96.2%
00032 376
 
3.8%
1
 
< 0.1%
00096 1
 
< 0.1%
07725 1
 
< 0.1%
07299 1
 
< 0.1%

전통업소주된음식
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9621 
갈비탕
 
377
000000
 
1
한식
 
1

Length

Max length6
Median length4
Mean length3.9623
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9621
96.2%
갈비탕 377
 
3.8%
000000 1
 
< 0.1%
한식 1
 
< 0.1%

Length

2024-04-18T04:12:30.365787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:12:30.450083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9621
96.2%
갈비탕 377
 
3.8%
000000 1
 
< 0.1%
한식 1
 
< 0.1%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
985431200003120000-101-2003-0034220031002<NA>3폐업2폐업20051031<NA><NA><NA><NA>75.90120853서울특별시 서대문구 홍제동 90-15번지 (지상1층)<NA><NA>제이제이돈돈2004-06-21 00:00:00I2018-08-31 23:59:59.0한식195488.609925453407.138857한식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N75.9<NA><NA><NA>
374231200003120000-101-1993-0624819931018<NA>3폐업2폐업19940526<NA><NA><NA>020392109769.75120808서울특별시 서대문구 대현동 34-35번지<NA><NA>카니발2001-09-30 00:00:00I2018-08-31 23:59:59.0경양식194997.451099450781.690034경양식11유흥업소밀집지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N69.75<NA><NA><NA>
1625031200003120000-101-2021-0030120210906<NA>3폐업2폐업20220314<NA><NA><NA><NA>26.40120816서울특별시 서대문구 북가좌동 371-12 국제빌딩서울특별시 서대문구 수색로 144, 국제빌딩 지1층 106,107호 (북가좌동)3714성영에프엔디 마포점2022-03-14 17:11:24U2022-03-16 02:40:00.0한식191559.918119452563.291845한식00<NA><NA><NA>00000<NA>00N26.4<NA><NA><NA>
372931200003120000-101-1993-0617119930506<NA>3폐업2폐업20050317<NA><NA><NA>020392476329.75120833서울특별시 서대문구 창천동 18-35번지<NA><NA>효성2001-09-30 00:00:00I2018-08-31 23:59:59.0경양식194369.076829450430.870126경양식11기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.75<NA><NA><NA>
324231200003120000-101-1992-0734919921228<NA>3폐업2폐업20000508<NA><NA><NA>020333875245.00120834서울특별시 서대문구 창천동 52-147번지<NA><NA>레넌호프2000-05-12 00:00:00I2018-08-31 23:59:59.0분식194193.699542450679.830562분식11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N45.0<NA><NA><NA>
1418231200003120000-101-2016-0011420160428<NA>3폐업2폐업20190829<NA><NA><NA><NA>80.35120806서울특별시 서대문구 남가좌동 325-2번지 2층서울특별시 서대문구 증가로10길 50, 2층 (남가좌동)3665마이클잭슨2019-08-29 20:52:25U2019-08-31 02:40:00.0호프/통닭193286.753535452988.305541호프/통닭<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N80.35<NA><NA><NA>
735731200003120000-101-1999-0915019990406<NA>1영업/정상1영업<NA><NA><NA><NA>020394267269.39120861서울특별시 서대문구 홍제동 334-23서울특별시 서대문구 홍제내길 142 (홍제동)3640오서방들깨나드리2021-08-12 16:42:57U2021-08-14 02:40:00.0한식194373.760074454006.10918한식00주택가주변기타상수도전용00000<NA>00N69.39<NA><NA><NA>
1632031200003120000-101-2021-0037120211109<NA>1영업/정상1영업<NA><NA><NA><NA><NA>68.08120050서울특별시 서대문구 냉천동 34 1층서울특별시 서대문구 독립문로 66, 1층 (냉천동)3745프랭크버거 냉천점2022-11-23 16:45:41U2021-10-31 22:05:00.0경양식196742.104096451655.294843<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
559431200003120000-101-1996-0752819961021<NA>3폐업2폐업19990319<NA><NA><NA>020374503621.17120847서울특별시 서대문구 홍은동 274-114번지<NA><NA>유나분식2004-01-27 00:00:00I2018-08-31 23:59:59.0분식194267.555594453136.162455분식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N21.17<NA><NA><NA>
9131200003120000-101-1976-0362319761218<NA>3폐업2폐업20010210<NA><NA><NA>020324441328.43120825서울특별시 서대문구 연희동 188-69번지<NA><NA>일성집2001-09-30 00:00:00I2018-08-31 23:59:59.0한식193761.529828451630.094981한식12기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.4300032갈비탕<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
971831200003120000-101-2003-0020320030702<NA>3폐업2폐업20040224<NA><NA><NA><NA>23.10120856서울특별시 서대문구 홍제동 217-2번지<NA><NA>청실홍실2003-07-02 00:00:00I2018-08-31 23:59:59.0한식195229.090583454049.944027한식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.1<NA><NA><NA>
1694731200003120000-101-2023-002092023-06-14<NA>1영업/정상1영업<NA><NA><NA><NA>026449847687.74120-806서울특별시 서대문구 남가좌동 324-20서울특별시 서대문구 거북골로 27, 2층 (남가좌동)3665피슈마라홍탕 명지대점2023-06-14 10:56:19I2022-12-05 23:07:00.0중국식193263.496217453055.317642<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1703031200003120000-101-2023-002932023-08-04<NA>1영업/정상1영업<NA><NA><NA><NA>0222278425368.63120-140서울특별시 서대문구 신촌동 134 세브란스병원서울특별시 서대문구 연세로 50-1, 세브란스병원 본관 3층 (신촌동)3722프레시박스 세브란스병원점2023-08-04 13:37:54I2022-12-08 00:06:00.0기타194584.959249451381.585492<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1456431200003120000-101-2017-0015620170525<NA>3폐업2폐업20190626<NA><NA><NA><NA>60.00120810서울특별시 서대문구 북가좌동 3-31번지 1층서울특별시 서대문구 증가로12나길 63-1, 1층 (북가좌동)3671바른먹거리2019-06-26 14:59:27U2019-06-28 02:40:00.0한식192944.69801453257.381604한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N60.0<NA><NA><NA>
786831200003120000-101-2000-0492920000928<NA>3폐업2폐업20060508<NA><NA><NA>02 393490126.40120050서울특별시 서대문구 냉천동 141-0번지<NA><NA>푸른분식2002-02-26 00:00:00I2018-08-31 23:59:59.0분식<NA><NA>분식00주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N26.4<NA><NA><NA>
385131200003120000-101-1993-0714519931207<NA>3폐업2폐업19940621<NA><NA><NA>020308537084.10120807서울특별시 서대문구 남가좌동 344-32번지<NA><NA>천야2001-09-30 00:00:00I2018-08-31 23:59:59.0분식193061.360577452827.956933분식11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N84.1<NA><NA><NA>
1182631200003120000-101-2009-0009020090507<NA>3폐업2폐업20090824<NA><NA><NA>02 372 54849.00120807서울특별시 서대문구 남가좌동 342-1번지 (지상1층)<NA><NA>서서마차2009-07-28 10:00:39I2018-08-31 23:59:59.0분식193228.13576452938.097902분식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N9.0<NA><NA><NA>
1575831200003120000-101-2020-0017320200707<NA>3폐업2폐업20220627<NA><NA><NA><NA>65.52120818서울특별시 서대문구 북아현동 183-1 정원아리솔서울특별시 서대문구 북아현로 83, 지1층 (북아현동, 정원아리솔)3762자연미가2022-06-27 13:03:06U2021-12-05 22:09:00.0한식195829.077803451307.919538<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1453531200003120000-101-2017-0012720170428<NA>3폐업2폐업20190520<NA><NA><NA><NA>26.00120809서울특별시 서대문구 대현동 101-12번지 지하1층서울특별시 서대문구 신촌역로 6, 지하1층 (대현동)3766신촌싸닭2019-05-20 12:24:35U2019-05-22 02:40:00.0호프/통닭194904.027279450560.372751호프/통닭<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N26.0<NA><NA><NA>
1088831200003120000-101-2006-0006120060317<NA>3폐업2폐업20200605<NA><NA><NA>02 312 8277250.00120833서울특별시 서대문구 창천동 18-5번지서울특별시 서대문구 명물길 6, 3층 (창천동)3777호랑이왕돈까스2020-06-05 09:45:58U2020-06-07 02:40:00.0호프/통닭194398.900504450561.690367호프/통닭00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N250.0<NA><NA><NA>