Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells110757
Missing cells (%)25.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 MiB
Average record size in memory382.0 B

Variable types

Categorical18
Text9
DateTime4
Unsupported6
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
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-18654/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
전통업소주된음식 has constant value ""Constant
총인원 is highly imbalanced (76.8%)Imbalance
본사종업원수 is highly imbalanced (76.8%)Imbalance
공장사무직종업원수 is highly imbalanced (76.8%)Imbalance
공장판매직종업원수 is highly imbalanced (76.8%)Imbalance
공장생산직종업원수 is highly imbalanced (76.8%)Imbalance
보증액 is highly imbalanced (76.8%)Imbalance
월세액 is highly imbalanced (76.8%)Imbalance
다중이용업소여부 is highly imbalanced (85.5%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 3376 (33.8%) 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 4095 (40.9%) missing valuesMissing
소재지면적 has 121 (1.2%) missing valuesMissing
도로명주소 has 4174 (41.7%) missing valuesMissing
도로명우편번호 has 4204 (42.0%) missing valuesMissing
좌표정보(X) has 374 (3.7%) missing valuesMissing
좌표정보(Y) has 374 (3.7%) missing valuesMissing
남성종사자수 has 5140 (51.4%) missing valuesMissing
여성종사자수 has 5133 (51.3%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1885 (18.9%) missing valuesMissing
시설총규모 has 1885 (18.9%) missing valuesMissing
전통업소지정번호 has 9997 (> 99.9%) missing valuesMissing
전통업소주된음식 has 9999 (> 99.9%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 3849 (38.5%) zerosZeros
여성종사자수 has 3333 (33.3%) zerosZeros

Reproduction

Analysis started2024-04-06 11:04:41.516200
Analysis finished2024-04-06 11:04:46.166785
Duration4.65 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
3020000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3020000 10000
100.0%

Length

2024-04-06T20:04:46.263264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:46.394846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T20:04:46.686981image/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 row3020000-101-2015-00327
2nd row3020000-101-1996-04084
3rd row3020000-101-2014-00458
4th row3020000-101-2003-00285
5th row3020000-101-1996-04087
ValueCountFrequency (%)
3020000-101-2015-00327 1
 
< 0.1%
3020000-101-2019-00120 1
 
< 0.1%
3020000-101-2003-00111 1
 
< 0.1%
3020000-101-2010-00070 1
 
< 0.1%
3020000-101-2012-00308 1
 
< 0.1%
3020000-101-2016-00406 1
 
< 0.1%
3020000-101-1994-04390 1
 
< 0.1%
3020000-101-1999-02287 1
 
< 0.1%
3020000-101-2017-00104 1
 
< 0.1%
3020000-101-1993-07161 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-06T20:04:47.269953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89878
40.9%
1 32087
 
14.6%
- 30000
 
13.6%
2 23009
 
10.5%
3 14574
 
6.6%
9 9338
 
4.2%
4 4607
 
2.1%
8 4286
 
1.9%
5 4135
 
1.9%
7 4132
 
1.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89878
47.3%
1 32087
 
16.9%
2 23009
 
12.1%
3 14574
 
7.7%
9 9338
 
4.9%
4 4607
 
2.4%
8 4286
 
2.3%
5 4135
 
2.2%
7 4132
 
2.2%
6 3954
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89878
40.9%
1 32087
 
14.6%
- 30000
 
13.6%
2 23009
 
10.5%
3 14574
 
6.6%
9 9338
 
4.2%
4 4607
 
2.1%
8 4286
 
1.9%
5 4135
 
1.9%
7 4132
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89878
40.9%
1 32087
 
14.6%
- 30000
 
13.6%
2 23009
 
10.5%
3 14574
 
6.6%
9 9338
 
4.2%
4 4607
 
2.1%
8 4286
 
1.9%
5 4135
 
1.9%
7 4132
 
1.9%
Distinct6113
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1904-08-08 00:00:00
Maximum2024-04-04 00:00:00
2024-04-06T20:04:47.577868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:04:47.820992image/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
6624 
1
3376 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 6624
66.2%
1 3376
33.8%

Length

2024-04-06T20:04:48.053419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:48.209738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 6624
66.2%
1 3376
33.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
6624 
영업/정상
3376 

Length

Max length5
Median length2
Mean length3.0128
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6624
66.2%
영업/정상 3376
33.8%

Length

2024-04-06T20:04:48.376458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:48.580891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6624
66.2%
영업/정상 3376
33.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
6624 
1
3376 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 6624
66.2%
1 3376
33.8%

Length

2024-04-06T20:04:48.857150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:49.001768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6624
66.2%
1 3376
33.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
6624 
영업
3376 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6624
66.2%
영업 3376
33.8%

Length

2024-04-06T20:04:49.158922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:04:49.301574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6624
66.2%
영업 3376
33.8%

폐업일자
Date

MISSING 

Distinct4007
Distinct (%)60.5%
Missing3376
Missing (%)33.8%
Memory size156.2 KiB
Minimum1984-08-08 00:00:00
Maximum2024-04-04 00:00:00
2024-04-06T20:04:49.515087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:04:49.796521image/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 

Distinct5087
Distinct (%)86.1%
Missing4095
Missing (%)40.9%
Memory size156.2 KiB
2024-04-06T20:04:50.380707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.746486
Min length1

Characters and Unicode

Total characters57553
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

Unique4911 ?
Unique (%)83.2%

Sample

1st row02 7903264
2nd row02 3933493
3rd row02 7978307
4th row02 7030133
5th row02 7983318
ValueCountFrequency (%)
02 4097
39.3%
0200000000 131
 
1.3%
0 92
 
0.9%
790 70
 
0.7%
794 60
 
0.6%
00000 59
 
0.6%
070 54
 
0.5%
792 53
 
0.5%
749 50
 
0.5%
793 43
 
0.4%
Other values (5142) 5725
54.9%
2024-04-06T20:04:51.193335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12006
20.9%
2 8938
15.5%
7 7908
13.7%
5626
9.8%
9 5051
8.8%
1 3500
 
6.1%
3 3225
 
5.6%
5 3034
 
5.3%
4 3013
 
5.2%
8 2732
 
4.7%
Other values (2) 2520
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51926
90.2%
Space Separator 5626
 
9.8%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12006
23.1%
2 8938
17.2%
7 7908
15.2%
9 5051
9.7%
1 3500
 
6.7%
3 3225
 
6.2%
5 3034
 
5.8%
4 3013
 
5.8%
8 2732
 
5.3%
6 2519
 
4.9%
Space Separator
ValueCountFrequency (%)
5626
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57553
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12006
20.9%
2 8938
15.5%
7 7908
13.7%
5626
9.8%
9 5051
8.8%
1 3500
 
6.1%
3 3225
 
5.6%
5 3034
 
5.3%
4 3013
 
5.2%
8 2732
 
4.7%
Other values (2) 2520
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57553
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12006
20.9%
2 8938
15.5%
7 7908
13.7%
5626
9.8%
9 5051
8.8%
1 3500
 
6.1%
3 3225
 
5.6%
5 3034
 
5.3%
4 3013
 
5.2%
8 2732
 
4.7%
Other values (2) 2520
 
4.4%

소재지면적
Text

MISSING 

Distinct5360
Distinct (%)54.3%
Missing121
Missing (%)1.2%
Memory size156.2 KiB
2024-04-06T20:04:51.784990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1619597
Min length3

Characters and Unicode

Total characters50995
Distinct characters12
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

Unique3517 ?
Unique (%)35.6%

Sample

1st row163.32
2nd row60.46
3rd row29.70
4th row28.90
5th row30.90
ValueCountFrequency (%)
33.00 83
 
0.8%
26.40 58
 
0.6%
30.00 53
 
0.5%
49.50 48
 
0.5%
20.00 45
 
0.5%
16.50 39
 
0.4%
60.00 38
 
0.4%
50.00 34
 
0.3%
19.80 33
 
0.3%
66.00 32
 
0.3%
Other values (5350) 9416
95.3%
2024-04-06T20:04:52.659470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9879
19.4%
0 6750
13.2%
2 4890
9.6%
1 4653
9.1%
3 4186
8.2%
4 3955
7.8%
5 3780
 
7.4%
6 3611
 
7.1%
8 3238
 
6.3%
9 3092
 
6.1%
Other values (2) 2961
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41097
80.6%
Other Punctuation 9898
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6750
16.4%
2 4890
11.9%
1 4653
11.3%
3 4186
10.2%
4 3955
9.6%
5 3780
9.2%
6 3611
8.8%
8 3238
7.9%
9 3092
7.5%
7 2942
7.2%
Other Punctuation
ValueCountFrequency (%)
. 9879
99.8%
, 19
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 50995
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9879
19.4%
0 6750
13.2%
2 4890
9.6%
1 4653
9.1%
3 4186
8.2%
4 3955
7.8%
5 3780
 
7.4%
6 3611
 
7.1%
8 3238
 
6.3%
9 3092
 
6.1%
Other values (2) 2961
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50995
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9879
19.4%
0 6750
13.2%
2 4890
9.6%
1 4653
9.1%
3 4186
8.2%
4 3955
7.8%
5 3780
 
7.4%
6 3611
 
7.1%
8 3238
 
6.3%
9 3092
 
6.1%
Other values (2) 2961
 
5.8%
Distinct257
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T20:04:53.215303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1225
Min length6

Characters and Unicode

Total characters61225
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

Unique28 ?
Unique (%)0.3%

Sample

1st row140857
2nd row140823
3rd row140823
4th row140821
5th row140871
ValueCountFrequency (%)
140863 436
 
4.4%
140858 363
 
3.6%
140887 300
 
3.0%
140861 296
 
3.0%
140823 255
 
2.5%
140893 245
 
2.5%
140871 230
 
2.3%
140780 217
 
2.2%
140132 216
 
2.2%
140160 214
 
2.1%
Other values (247) 7228
72.3%
2024-04-06T20:04:54.083944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13081
21.4%
1 13080
21.4%
4 11168
18.2%
8 9489
15.5%
3 2830
 
4.6%
2 2509
 
4.1%
7 2299
 
3.8%
6 2052
 
3.4%
9 1997
 
3.3%
5 1495
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60000
98.0%
Dash Punctuation 1225
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13081
21.8%
1 13080
21.8%
4 11168
18.6%
8 9489
15.8%
3 2830
 
4.7%
2 2509
 
4.2%
7 2299
 
3.8%
6 2052
 
3.4%
9 1997
 
3.3%
5 1495
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 1225
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61225
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13081
21.4%
1 13080
21.4%
4 11168
18.2%
8 9489
15.5%
3 2830
 
4.6%
2 2509
 
4.1%
7 2299
 
3.8%
6 2052
 
3.4%
9 1997
 
3.3%
5 1495
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61225
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13081
21.4%
1 13080
21.4%
4 11168
18.2%
8 9489
15.5%
3 2830
 
4.6%
2 2509
 
4.1%
7 2299
 
3.8%
6 2052
 
3.4%
9 1997
 
3.3%
5 1495
 
2.4%
Distinct7967
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T20:04:54.540302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length51
Mean length26.0174
Min length14

Characters and Unicode

Total characters260174
Distinct characters379
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6712 ?
Unique (%)67.1%

Sample

1st row서울특별시 용산구 이태원동 225-5번지 지상1층
2nd row서울특별시 용산구 보광동 243-3번지
3rd row서울특별시 용산구 보광동 253-44번지 지상1층
4th row서울특별시 용산구 동자동 43-205번지 2층 201호
5th row서울특별시 용산구 한강로2가 337-1번지
ValueCountFrequency (%)
서울특별시 10000
21.5%
용산구 10000
21.5%
지상1층 2064
 
4.4%
이태원동 1811
 
3.9%
한남동 1464
 
3.2%
한강로2가 807
 
1.7%
한강로3가 788
 
1.7%
보광동 454
 
1.0%
용산동2가 449
 
1.0%
지하1층 442
 
1.0%
Other values (5969) 18184
39.1%
2024-04-06T20:04:55.636578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44491
 
17.1%
1 12836
 
4.9%
11043
 
4.2%
10881
 
4.2%
10863
 
4.2%
10322
 
4.0%
10078
 
3.9%
10049
 
3.9%
10007
 
3.8%
10004
 
3.8%
Other values (369) 119600
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148618
57.1%
Decimal Number 51765
 
19.9%
Space Separator 44491
 
17.1%
Dash Punctuation 9461
 
3.6%
Close Punctuation 2580
 
1.0%
Open Punctuation 2580
 
1.0%
Other Punctuation 450
 
0.2%
Uppercase Letter 204
 
0.1%
Lowercase Letter 18
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11043
 
7.4%
10881
 
7.3%
10863
 
7.3%
10322
 
6.9%
10078
 
6.8%
10049
 
6.8%
10007
 
6.7%
10004
 
6.7%
10000
 
6.7%
8149
 
5.5%
Other values (319) 47222
31.8%
Uppercase Letter
ValueCountFrequency (%)
B 80
39.2%
A 28
 
13.7%
C 16
 
7.8%
D 13
 
6.4%
K 7
 
3.4%
S 7
 
3.4%
R 7
 
3.4%
T 6
 
2.9%
L 6
 
2.9%
P 6
 
2.9%
Other values (8) 28
 
13.7%
Lowercase Letter
ValueCountFrequency (%)
e 3
16.7%
c 3
16.7%
l 2
11.1%
u 2
11.1%
n 2
11.1%
k 1
 
5.6%
m 1
 
5.6%
s 1
 
5.6%
b 1
 
5.6%
i 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 12836
24.8%
2 8915
17.2%
3 6534
12.6%
4 4368
 
8.4%
6 4044
 
7.8%
5 3557
 
6.9%
0 3466
 
6.7%
9 2872
 
5.5%
7 2784
 
5.4%
8 2389
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 411
91.3%
. 29
 
6.4%
@ 3
 
0.7%
/ 3
 
0.7%
& 3
 
0.7%
' 1
 
0.2%
Space Separator
ValueCountFrequency (%)
44491
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9461
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2580
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2580
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 148618
57.1%
Common 111334
42.8%
Latin 222
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11043
 
7.4%
10881
 
7.3%
10863
 
7.3%
10322
 
6.9%
10078
 
6.8%
10049
 
6.8%
10007
 
6.7%
10004
 
6.7%
10000
 
6.7%
8149
 
5.5%
Other values (319) 47222
31.8%
Latin
ValueCountFrequency (%)
B 80
36.0%
A 28
 
12.6%
C 16
 
7.2%
D 13
 
5.9%
K 7
 
3.2%
S 7
 
3.2%
R 7
 
3.2%
T 6
 
2.7%
L 6
 
2.7%
P 6
 
2.7%
Other values (19) 46
20.7%
Common
ValueCountFrequency (%)
44491
40.0%
1 12836
 
11.5%
- 9461
 
8.5%
2 8915
 
8.0%
3 6534
 
5.9%
4 4368
 
3.9%
6 4044
 
3.6%
5 3557
 
3.2%
0 3466
 
3.1%
9 2872
 
2.6%
Other values (11) 10790
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148618
57.1%
ASCII 111556
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44491
39.9%
1 12836
 
11.5%
- 9461
 
8.5%
2 8915
 
8.0%
3 6534
 
5.9%
4 4368
 
3.9%
6 4044
 
3.6%
5 3557
 
3.2%
0 3466
 
3.1%
9 2872
 
2.6%
Other values (40) 11012
 
9.9%
Hangul
ValueCountFrequency (%)
11043
 
7.4%
10881
 
7.3%
10863
 
7.3%
10322
 
6.9%
10078
 
6.8%
10049
 
6.8%
10007
 
6.7%
10004
 
6.7%
10000
 
6.7%
8149
 
5.5%
Other values (319) 47222
31.8%

도로명주소
Text

MISSING 

Distinct5303
Distinct (%)91.0%
Missing4174
Missing (%)41.7%
Memory size156.2 KiB
2024-04-06T20:04:56.151363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length59
Mean length34.327326
Min length21

Characters and Unicode

Total characters199991
Distinct characters375
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4921 ?
Unique (%)84.5%

Sample

1st row서울특별시 용산구 회나무로 33, 지상1층 (이태원동)
2nd row서울특별시 용산구 보광로24길 13, 지상1층 (보광동)
3rd row서울특별시 용산구 한강대로 405, 2층 201호 (동자동)
4th row서울특별시 용산구 우사단로14길 3, 1층 (이태원동)
5th row서울특별시 용산구 청파로89길 43, 1층 (서계동)
ValueCountFrequency (%)
서울특별시 5826
 
15.9%
용산구 5826
 
15.9%
1층 1632
 
4.5%
이태원동 1160
 
3.2%
한남동 753
 
2.1%
지상1층 725
 
2.0%
지하1층 435
 
1.2%
2층 432
 
1.2%
한강대로 370
 
1.0%
한강로3가 364
 
1.0%
Other values (3091) 19103
52.2%
2024-04-06T20:04:57.016320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30808
 
15.4%
1 10219
 
5.1%
7142
 
3.6%
( 6961
 
3.5%
) 6961
 
3.5%
, 6662
 
3.3%
6566
 
3.3%
6479
 
3.2%
6297
 
3.1%
2 6233
 
3.1%
Other values (365) 105663
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111658
55.8%
Decimal Number 34557
 
17.3%
Space Separator 30808
 
15.4%
Open Punctuation 6961
 
3.5%
Close Punctuation 6961
 
3.5%
Other Punctuation 6680
 
3.3%
Dash Punctuation 1964
 
1.0%
Uppercase Letter 322
 
0.2%
Lowercase Letter 53
 
< 0.1%
Math Symbol 27
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7142
 
6.4%
6566
 
5.9%
6479
 
5.8%
6297
 
5.6%
5905
 
5.3%
5880
 
5.3%
5831
 
5.2%
5831
 
5.2%
5830
 
5.2%
5672
 
5.1%
Other values (309) 50225
45.0%
Uppercase Letter
ValueCountFrequency (%)
B 155
48.1%
A 37
 
11.5%
C 26
 
8.1%
D 20
 
6.2%
R 13
 
4.0%
K 10
 
3.1%
F 8
 
2.5%
L 7
 
2.2%
S 7
 
2.2%
T 6
 
1.9%
Other values (10) 33
 
10.2%
Lowercase Letter
ValueCountFrequency (%)
b 20
37.7%
c 8
 
15.1%
l 5
 
9.4%
i 3
 
5.7%
k 3
 
5.7%
e 3
 
5.7%
n 2
 
3.8%
p 2
 
3.8%
a 1
 
1.9%
s 1
 
1.9%
Other values (5) 5
 
9.4%
Decimal Number
ValueCountFrequency (%)
1 10219
29.6%
2 6233
18.0%
3 3572
 
10.3%
4 2926
 
8.5%
0 2450
 
7.1%
5 2411
 
7.0%
6 1966
 
5.7%
7 1913
 
5.5%
8 1436
 
4.2%
9 1431
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 6662
99.7%
. 12
 
0.2%
& 2
 
< 0.1%
/ 2
 
< 0.1%
? 1
 
< 0.1%
' 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
30808
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6961
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6961
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1964
100.0%
Math Symbol
ValueCountFrequency (%)
~ 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111658
55.8%
Common 87958
44.0%
Latin 375
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7142
 
6.4%
6566
 
5.9%
6479
 
5.8%
6297
 
5.6%
5905
 
5.3%
5880
 
5.3%
5831
 
5.2%
5831
 
5.2%
5830
 
5.2%
5672
 
5.1%
Other values (309) 50225
45.0%
Latin
ValueCountFrequency (%)
B 155
41.3%
A 37
 
9.9%
C 26
 
6.9%
D 20
 
5.3%
b 20
 
5.3%
R 13
 
3.5%
K 10
 
2.7%
c 8
 
2.1%
F 8
 
2.1%
L 7
 
1.9%
Other values (25) 71
18.9%
Common
ValueCountFrequency (%)
30808
35.0%
1 10219
 
11.6%
( 6961
 
7.9%
) 6961
 
7.9%
, 6662
 
7.6%
2 6233
 
7.1%
3 3572
 
4.1%
4 2926
 
3.3%
0 2450
 
2.8%
5 2411
 
2.7%
Other values (11) 8755
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111658
55.8%
ASCII 88333
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30808
34.9%
1 10219
 
11.6%
( 6961
 
7.9%
) 6961
 
7.9%
, 6662
 
7.5%
2 6233
 
7.1%
3 3572
 
4.0%
4 2926
 
3.3%
0 2450
 
2.8%
5 2411
 
2.7%
Other values (46) 9130
 
10.3%
Hangul
ValueCountFrequency (%)
7142
 
6.4%
6566
 
5.9%
6479
 
5.8%
6297
 
5.6%
5905
 
5.3%
5880
 
5.3%
5831
 
5.2%
5831
 
5.2%
5830
 
5.2%
5672
 
5.1%
Other values (309) 50225
45.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct126
Distinct (%)2.2%
Missing4204
Missing (%)42.0%
Infinite0
Infinite (%)0.0%
Mean4365.9862
Minimum4300
Maximum4428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:04:57.311247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4300
5-th percentile4310
Q14342
median4369
Q34392
95-th percentile4419
Maximum4428
Range128
Interquartile range (IQR)50

Descriptive statistics

Standard deviation33.66008
Coefficient of variation (CV)0.0077096168
Kurtosis-1.0383082
Mean4365.9862
Median Absolute Deviation (MAD)26
Skewness-0.12008965
Sum25305256
Variance1133.001
MonotonicityNot monotonic
2024-04-06T20:04:57.688135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4382 256
 
2.6%
4391 231
 
2.3%
4345 197
 
2.0%
4400 191
 
1.9%
4350 183
 
1.8%
4377 154
 
1.5%
4352 137
 
1.4%
4419 136
 
1.4%
4337 124
 
1.2%
4363 123
 
1.2%
Other values (116) 4064
40.6%
(Missing) 4204
42.0%
ValueCountFrequency (%)
4300 43
0.4%
4301 56
0.6%
4302 15
 
0.1%
4303 19
 
0.2%
4304 18
 
0.2%
4305 36
0.4%
4306 5
 
0.1%
4307 7
 
0.1%
4308 6
 
0.1%
4309 70
0.7%
ValueCountFrequency (%)
4428 12
 
0.1%
4427 45
 
0.4%
4426 36
 
0.4%
4425 12
 
0.1%
4424 20
 
0.2%
4423 53
 
0.5%
4420 34
 
0.3%
4419 136
1.4%
4418 5
 
0.1%
4417 21
 
0.2%
Distinct8829
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T20:04:58.397634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length41
Mean length5.7884
Min length1

Characters and Unicode

Total characters57884
Distinct characters1156
Distinct categories14 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8079 ?
Unique (%)80.8%

Sample

1st row남산케미스트리
2nd row고전민속촌
3rd row코코로
4th row야미철판볶음밥
5th row으뜸매기매운탕
ValueCountFrequency (%)
용산점 46
 
0.4%
이태원점 36
 
0.3%
주식회사 25
 
0.2%
한남 25
 
0.2%
용산아이파크몰점 23
 
0.2%
전주식당 21
 
0.2%
한남점 20
 
0.2%
coffee 19
 
0.2%
이태원 19
 
0.2%
16
 
0.1%
Other values (9568) 11260
97.8%
2024-04-06T20:04:59.370705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1556
 
2.7%
1515
 
2.6%
1228
 
2.1%
1099
 
1.9%
) 1062
 
1.8%
( 1059
 
1.8%
896
 
1.5%
778
 
1.3%
768
 
1.3%
500
 
0.9%
Other values (1146) 47423
81.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46425
80.2%
Lowercase Letter 3871
 
6.7%
Uppercase Letter 3072
 
5.3%
Space Separator 1515
 
2.6%
Close Punctuation 1063
 
1.8%
Open Punctuation 1059
 
1.8%
Decimal Number 645
 
1.1%
Other Punctuation 190
 
0.3%
Dash Punctuation 25
 
< 0.1%
Letter Number 7
 
< 0.1%
Other values (4) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1556
 
3.4%
1228
 
2.6%
1099
 
2.4%
896
 
1.9%
778
 
1.7%
768
 
1.7%
500
 
1.1%
495
 
1.1%
489
 
1.1%
486
 
1.0%
Other values (1059) 38130
82.1%
Lowercase Letter
ValueCountFrequency (%)
e 484
12.5%
o 393
 
10.2%
a 366
 
9.5%
i 270
 
7.0%
r 251
 
6.5%
n 241
 
6.2%
t 217
 
5.6%
s 211
 
5.5%
l 203
 
5.2%
u 157
 
4.1%
Other values (16) 1078
27.8%
Uppercase Letter
ValueCountFrequency (%)
A 280
 
9.1%
E 249
 
8.1%
O 244
 
7.9%
S 211
 
6.9%
B 187
 
6.1%
T 187
 
6.1%
N 165
 
5.4%
R 154
 
5.0%
I 154
 
5.0%
L 150
 
4.9%
Other values (16) 1091
35.5%
Decimal Number
ValueCountFrequency (%)
2 123
19.1%
1 112
17.4%
3 72
11.2%
9 65
10.1%
0 59
9.1%
4 55
8.5%
5 46
 
7.1%
8 45
 
7.0%
7 36
 
5.6%
6 32
 
5.0%
Other Punctuation
ValueCountFrequency (%)
& 58
30.5%
. 49
25.8%
' 28
14.7%
? 23
 
12.1%
, 20
 
10.5%
: 3
 
1.6%
/ 3
 
1.6%
@ 2
 
1.1%
# 2
 
1.1%
! 2
 
1.1%
Math Symbol
ValueCountFrequency (%)
+ 2
33.3%
> 1
16.7%
< 1
16.7%
× 1
16.7%
~ 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 1062
99.9%
] 1
 
0.1%
Letter Number
ValueCountFrequency (%)
6
85.7%
1
 
14.3%
Space Separator
ValueCountFrequency (%)
1515
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1059
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Other Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46403
80.2%
Latin 6950
 
12.0%
Common 4508
 
7.8%
Han 21
 
< 0.1%
Hiragana 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1556
 
3.4%
1228
 
2.6%
1099
 
2.4%
896
 
1.9%
778
 
1.7%
768
 
1.7%
500
 
1.1%
495
 
1.1%
489
 
1.1%
486
 
1.0%
Other values (1038) 38108
82.1%
Latin
ValueCountFrequency (%)
e 484
 
7.0%
o 393
 
5.7%
a 366
 
5.3%
A 280
 
4.0%
i 270
 
3.9%
r 251
 
3.6%
E 249
 
3.6%
O 244
 
3.5%
n 241
 
3.5%
t 217
 
3.1%
Other values (44) 3955
56.9%
Common
ValueCountFrequency (%)
1515
33.6%
) 1062
23.6%
( 1059
23.5%
2 123
 
2.7%
1 112
 
2.5%
3 72
 
1.6%
9 65
 
1.4%
0 59
 
1.3%
& 58
 
1.3%
4 55
 
1.2%
Other values (22) 328
 
7.3%
Han
ValueCountFrequency (%)
2
 
9.5%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
Other values (10) 10
47.6%
Hiragana
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46402
80.2%
ASCII 11449
 
19.8%
CJK 21
 
< 0.1%
Number Forms 8
 
< 0.1%
None 2
 
< 0.1%
Hiragana 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1556
 
3.4%
1228
 
2.6%
1099
 
2.4%
896
 
1.9%
778
 
1.7%
768
 
1.7%
500
 
1.1%
495
 
1.1%
489
 
1.1%
486
 
1.0%
Other values (1037) 38107
82.1%
ASCII
ValueCountFrequency (%)
1515
 
13.2%
) 1062
 
9.3%
( 1059
 
9.2%
e 484
 
4.2%
o 393
 
3.4%
a 366
 
3.2%
A 280
 
2.4%
i 270
 
2.4%
r 251
 
2.2%
E 249
 
2.2%
Other values (72) 5520
48.2%
Number Forms
ValueCountFrequency (%)
6
75.0%
1
 
12.5%
1
 
12.5%
CJK
ValueCountFrequency (%)
2
 
9.5%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
Other values (10) 10
47.6%
None
ValueCountFrequency (%)
1
50.0%
× 1
50.0%
Hiragana
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct7082
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-09 00:00:00
Maximum2024-04-04 16:42:00
2024-04-06T20:04:59.599818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:04:59.850038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6938 
U
3062 

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 6938
69.4%
U 3062
30.6%

Length

2024-04-06T20:05:00.081014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:00.235251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6938
69.4%
u 3062
30.6%
Distinct1463
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T20:05:00.415982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:05:00.665687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3589 
경양식
1723 
기타
1539 
분식
1249 
일식
441 
Other values (22)
1459 

Length

Max length15
Median length2
Mean length2.9004
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row호프/통닭
2nd row분식
3rd row분식
4th row한식
5th row분식

Common Values

ValueCountFrequency (%)
한식 3589
35.9%
경양식 1723
17.2%
기타 1539
15.4%
분식 1249
 
12.5%
일식 441
 
4.4%
호프/통닭 351
 
3.5%
외국음식전문점(인도,태국등) 316
 
3.2%
중국식 234
 
2.3%
까페 176
 
1.8%
정종/대포집/소주방 105
 
1.1%
Other values (17) 277
 
2.8%

Length

2024-04-06T20:05:00.895324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3589
35.9%
경양식 1723
17.2%
기타 1539
15.4%
분식 1249
 
12.5%
일식 441
 
4.4%
호프/통닭 351
 
3.5%
외국음식전문점(인도,태국등 316
 
3.2%
중국식 234
 
2.3%
까페 176
 
1.8%
정종/대포집/소주방 105
 
1.1%
Other values (17) 277
 
2.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3986
Distinct (%)41.4%
Missing374
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean198204.72
Minimum195086.36
Maximum201202.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:05:01.064841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195086.36
5-th percentile196370.75
Q1197063.84
median197719.58
Q3199432.7
95-th percentile200460.53
Maximum201202.31
Range6115.9504
Interquartile range (IQR)2368.8546

Descriptive statistics

Standard deviation1364.3023
Coefficient of variation (CV)0.0068832987
Kurtosis-1.227818
Mean198204.72
Median Absolute Deviation (MAD)1081.6796
Skewness0.24712166
Sum1.9079186 × 109
Variance1861320.7
MonotonicityNot monotonic
2024-04-06T20:05:01.336055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196762.077394917 195
 
1.9%
197373.839856311 45
 
0.4%
196370.746398773 45
 
0.4%
196893.277042114 42
 
0.4%
196610.663839509 35
 
0.4%
198236.296378418 25
 
0.2%
197158.923647874 23
 
0.2%
200455.14401596 23
 
0.2%
200571.725921493 22
 
0.2%
197514.145785647 22
 
0.2%
Other values (3976) 9149
91.5%
(Missing) 374
 
3.7%
ValueCountFrequency (%)
195086.35935132 2
 
< 0.1%
195125.34321485 1
 
< 0.1%
195141.076716711 1
 
< 0.1%
195266.362355276 1
 
< 0.1%
195544.606275448 3
< 0.1%
195547.140326252 5
0.1%
195549.831263238 2
 
< 0.1%
195556.853873045 1
 
< 0.1%
195563.535062555 2
 
< 0.1%
195563.788982635 1
 
< 0.1%
ValueCountFrequency (%)
201202.309752621 1
 
< 0.1%
201079.965314031 1
 
< 0.1%
201070.187785081 3
< 0.1%
201062.189654534 1
 
< 0.1%
201015.713148163 1
 
< 0.1%
201013.819447755 1
 
< 0.1%
200980.035948688 1
 
< 0.1%
200955.892430557 2
 
< 0.1%
200954.990156608 2
 
< 0.1%
200949.791234436 5
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3985
Distinct (%)41.4%
Missing374
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean448233.13
Minimum445090.1
Maximum450296.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:05:01.597669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445090.1
5-th percentile446924.42
Q1447732.67
median448067.25
Q3448821.33
95-th percentile449884.95
Maximum450296.59
Range5206.4853
Interquartile range (IQR)1088.6541

Descriptive statistics

Standard deviation867.92039
Coefficient of variation (CV)0.0019363147
Kurtosis-0.18841176
Mean448233.13
Median Absolute Deviation (MAD)512.44173
Skewness0.23643325
Sum4.3146922 × 109
Variance753285.8
MonotonicityNot monotonic
2024-04-06T20:05:01.867265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447480.039577359 195
 
1.9%
450014.537949042 45
 
0.4%
447841.698787531 45
 
0.4%
447852.583272453 42
 
0.4%
447742.348636253 35
 
0.4%
446262.544080318 25
 
0.2%
447399.964398158 23
 
0.2%
447866.831310941 23
 
0.2%
447793.924058853 22
 
0.2%
448264.322314594 22
 
0.2%
Other values (3975) 9149
91.5%
(Missing) 374
 
3.7%
ValueCountFrequency (%)
445090.103903473 1
 
< 0.1%
445891.889050955 1
 
< 0.1%
446114.125235545 1
 
< 0.1%
446114.155238838 19
0.2%
446178.85892605 5
 
0.1%
446185.244544796 3
 
< 0.1%
446194.350546744 3
 
< 0.1%
446196.846273533 3
 
< 0.1%
446201.315141801 7
 
0.1%
446202.36502252 13
0.1%
ValueCountFrequency (%)
450296.589217562 2
 
< 0.1%
450290.442701448 3
< 0.1%
450288.561776513 5
0.1%
450286.425859673 1
 
< 0.1%
450278.758007272 5
0.1%
450273.633824628 2
 
< 0.1%
450273.618205183 1
 
< 0.1%
450272.711607398 2
 
< 0.1%
450272.315459538 3
< 0.1%
450267.741912848 2
 
< 0.1%

위생업태명
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3075 
<NA>
1886 
경양식
1369 
분식
1181 
기타
1039 
Other values (20)
1450 

Length

Max length15
Median length2
Mean length2.9662
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row호프/통닭
2nd row분식
3rd row분식
4th row한식
5th row분식

Common Values

ValueCountFrequency (%)
한식 3075
30.8%
<NA> 1886
18.9%
경양식 1369
13.7%
분식 1181
 
11.8%
기타 1039
 
10.4%
일식 332
 
3.3%
호프/통닭 291
 
2.9%
중국식 188
 
1.9%
까페 163
 
1.6%
외국음식전문점(인도,태국등) 135
 
1.4%
Other values (15) 341
 
3.4%

Length

2024-04-06T20:05:02.102387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3075
30.8%
na 1886
18.9%
경양식 1369
13.7%
분식 1181
 
11.8%
기타 1039
 
10.4%
일식 332
 
3.3%
호프/통닭 291
 
2.9%
중국식 188
 
1.9%
까페 163
 
1.6%
외국음식전문점(인도,태국등 135
 
1.4%
Other values (15) 341
 
3.4%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.1%
Missing5140
Missing (%)51.4%
Infinite0
Infinite (%)0.0%
Mean0.28374486
Minimum0
Maximum10
Zeros3849
Zeros (%)38.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:05:02.297944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.64184146
Coefficient of variation (CV)2.2620373
Kurtosis18.399362
Mean0.28374486
Median Absolute Deviation (MAD)0
Skewness3.1972185
Sum1379
Variance0.41196045
MonotonicityNot monotonic
2024-04-06T20:05:02.503142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 3849
38.5%
1 732
 
7.3%
2 214
 
2.1%
3 52
 
0.5%
4 7
 
0.1%
5 5
 
0.1%
10 1
 
< 0.1%
(Missing) 5140
51.4%
ValueCountFrequency (%)
0 3849
38.5%
1 732
 
7.3%
2 214
 
2.1%
3 52
 
0.5%
4 7
 
0.1%
5 5
 
0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
5 5
 
0.1%
4 7
 
0.1%
3 52
 
0.5%
2 214
 
2.1%
1 732
 
7.3%
0 3849
38.5%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.2%
Missing5133
Missing (%)51.3%
Infinite0
Infinite (%)0.0%
Mean0.48387097
Minimum0
Maximum10
Zeros3333
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:05:02.679282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8289218
Coefficient of variation (CV)1.7131051
Kurtosis6.8976687
Mean0.48387097
Median Absolute Deviation (MAD)0
Skewness2.0568453
Sum2355
Variance0.68711136
MonotonicityNot monotonic
2024-04-06T20:05:02.859642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3333
33.3%
1 881
 
8.8%
2 524
 
5.2%
3 107
 
1.1%
4 13
 
0.1%
5 6
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 5133
51.3%
ValueCountFrequency (%)
0 3333
33.3%
1 881
 
8.8%
2 524
 
5.2%
3 107
 
1.1%
4 13
 
0.1%
5 6
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 6
 
0.1%
4 13
 
0.1%
3 107
 
1.1%
2 524
 
5.2%
1 881
 
8.8%
0 3333
33.3%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5540 
기타
2310 
주택가주변
1419 
유흥업소밀집지역
 
451
아파트지역
 
164
Other values (3)
 
116

Length

Max length8
Median length4
Mean length3.9225
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5540
55.4%
기타 2310
23.1%
주택가주변 1419
 
14.2%
유흥업소밀집지역 451
 
4.5%
아파트지역 164
 
1.6%
학교정화(상대) 98
 
1.0%
학교정화(절대) 12
 
0.1%
결혼예식장주변 6
 
0.1%

Length

2024-04-06T20:05:03.040364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:03.211481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5540
55.4%
기타 2310
23.1%
주택가주변 1419
 
14.2%
유흥업소밀집지역 451
 
4.5%
아파트지역 164
 
1.6%
학교정화(상대 98
 
1.0%
학교정화(절대 12
 
0.1%
결혼예식장주변 6
 
0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6195 
기타
1710 
지도
1151 
자율
 
520
 
273
Other values (3)
 
151

Length

Max length4
Median length4
Mean length3.2032
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6195
62.0%
기타 1710
 
17.1%
지도 1151
 
11.5%
자율 520
 
5.2%
273
 
2.7%
85
 
0.9%
관리 60
 
0.6%
우수 6
 
0.1%

Length

2024-04-06T20:05:03.423382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:03.612153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6195
62.0%
기타 1710
 
17.1%
지도 1151
 
11.5%
자율 520
 
5.2%
273
 
2.7%
85
 
0.9%
관리 60
 
0.6%
우수 6
 
0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
5645 
<NA>
4321 
상수도(음용)지하수(주방용)겸용
 
32
지하수전용
 
2

Length

Max length17
Median length5
Mean length4.6063
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 5645
56.5%
<NA> 4321
43.2%
상수도(음용)지하수(주방용)겸용 32
 
0.3%
지하수전용 2
 
< 0.1%

Length

2024-04-06T20:05:03.858903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:04.029207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 5645
56.5%
na 4321
43.2%
상수도(음용)지하수(주방용)겸용 32
 
0.3%
지하수전용 2
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9622 
0
 
378

Length

Max length4
Median length4
Mean length3.8866
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> 9622
96.2%
0 378
 
3.8%

Length

2024-04-06T20:05:04.202528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:04.379750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9622
96.2%
0 378
 
3.8%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9622 
0
 
378

Length

Max length4
Median length4
Mean length3.8866
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> 9622
96.2%
0 378
 
3.8%

Length

2024-04-06T20:05:04.594294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:04.762228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9622
96.2%
0 378
 
3.8%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9622 
0
 
378

Length

Max length4
Median length4
Mean length3.8866
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> 9622
96.2%
0 378
 
3.8%

Length

2024-04-06T20:05:04.940352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:05.098822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9622
96.2%
0 378
 
3.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9622 
0
 
378

Length

Max length4
Median length4
Mean length3.8866
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> 9622
96.2%
0 378
 
3.8%

Length

2024-04-06T20:05:05.261476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:05.404366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9622
96.2%
0 378
 
3.8%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9622 
0
 
378

Length

Max length4
Median length4
Mean length3.8866
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> 9622
96.2%
0 378
 
3.8%

Length

2024-04-06T20:05:05.574306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:05.738867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9622
96.2%
0 378
 
3.8%

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>
9622 
0
 
378

Length

Max length4
Median length4
Mean length3.8866
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> 9622
96.2%
0 378
 
3.8%

Length

2024-04-06T20:05:05.910748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:06.092528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9622
96.2%
0 378
 
3.8%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9622 
0
 
378

Length

Max length4
Median length4
Mean length3.8866
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> 9622
96.2%
0 378
 
3.8%

Length

2024-04-06T20:05:06.333970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:06.503414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9622
96.2%
0 378
 
3.8%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1885
Missing (%)18.9%
Memory size97.7 KiB
False
7947 
True
 
168
(Missing)
1885 
ValueCountFrequency (%)
False 7947
79.5%
True 168
 
1.7%
(Missing) 1885
 
18.9%
2024-04-06T20:05:06.634174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct4643
Distinct (%)57.2%
Missing1885
Missing (%)18.9%
Infinite0
Infinite (%)0.0%
Mean68.945739
Minimum0
Maximum4252.33
Zeros84
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:05:06.813118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.26
Q126.4
median44.04
Q378.5
95-th percentile189.622
Maximum4252.33
Range4252.33
Interquartile range (IQR)52.1

Descriptive statistics

Standard deviation113.68925
Coefficient of variation (CV)1.648967
Kurtosis530.05811
Mean68.945739
Median Absolute Deviation (MAD)21.15
Skewness17.374394
Sum559494.67
Variance12925.245
MonotonicityNot monotonic
2024-04-06T20:05:07.413765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 84
 
0.8%
33.0 68
 
0.7%
26.4 53
 
0.5%
49.5 43
 
0.4%
30.0 36
 
0.4%
16.5 36
 
0.4%
20.0 36
 
0.4%
19.8 31
 
0.3%
23.1 28
 
0.3%
18.0 28
 
0.3%
Other values (4633) 7672
76.7%
(Missing) 1885
 
18.9%
ValueCountFrequency (%)
0.0 84
0.8%
1.0 1
 
< 0.1%
3.0 1
 
< 0.1%
3.3 1
 
< 0.1%
3.49 1
 
< 0.1%
3.91 1
 
< 0.1%
4.61 1
 
< 0.1%
4.62 1
 
< 0.1%
4.67 1
 
< 0.1%
5.54 1
 
< 0.1%
ValueCountFrequency (%)
4252.33 2
< 0.1%
3014.79 1
< 0.1%
1624.28 1
< 0.1%
1478.3 1
< 0.1%
1256.56 1
< 0.1%
1251.44 1
< 0.1%
1249.0 1
< 0.1%
1190.0 1
< 0.1%
1168.98 1
< 0.1%
1142.49 1
< 0.1%
Distinct3
Distinct (%)100.0%
Missing9997
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-06T20:05:07.561292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length1
Mean length2
Min length1

Characters and Unicode

Total characters6
Distinct characters6
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

Unique3 ?
Unique (%)100.0%

Sample

1st row`
2nd row;
3rd row5236
ValueCountFrequency (%)
2
66.7%
5236 1
33.3%
2024-04-06T20:05:07.946970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
` 1
16.7%
; 1
16.7%
5 1
16.7%
2 1
16.7%
3 1
16.7%
6 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
66.7%
Modifier Symbol 1
 
16.7%
Other Punctuation 1
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1
25.0%
2 1
25.0%
3 1
25.0%
6 1
25.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Punctuation
ValueCountFrequency (%)
; 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
` 1
16.7%
; 1
16.7%
5 1
16.7%
2 1
16.7%
3 1
16.7%
6 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
` 1
16.7%
; 1
16.7%
5 1
16.7%
2 1
16.7%
3 1
16.7%
6 1
16.7%

전통업소주된음식
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-06T20:05:08.097609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row한식
ValueCountFrequency (%)
한식 1
100.0%
2024-04-06T20:05:08.428200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1064730200003020000-101-2015-0032720150717<NA>1영업/정상1영업<NA><NA><NA><NA><NA>163.32140857서울특별시 용산구 이태원동 225-5번지 지상1층서울특별시 용산구 회나무로 33, 지상1층 (이태원동)4344남산케미스트리2018-06-12 13:30:58I2018-08-31 23:59:59.0호프/통닭199080.030031448618.736803호프/통닭<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N163.32<NA><NA><NA>
401130200003020000-101-1996-0408419960919<NA>3폐업2폐업19980912<NA><NA><NA>02 790326460.46140823서울특별시 용산구 보광동 243-3번지<NA><NA>고전민속촌2001-09-27 00:00:00I2018-08-31 23:59:59.0분식199743.601603447467.085734분식<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N60.46<NA><NA><NA>
1030430200003020000-101-2014-0045820141217<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.70140823서울특별시 용산구 보광동 253-44번지 지상1층서울특별시 용산구 보광로24길 13, 지상1층 (보광동)4414코코로2016-04-07 12:49:23I2018-08-31 23:59:59.0분식199904.464181447370.195239분식<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.7<NA><NA><NA>
689630200003020000-101-2003-0028520031125<NA>3폐업2폐업20180615<NA><NA><NA>02 393349328.90140821서울특별시 용산구 동자동 43-205번지 2층 201호서울특별시 용산구 한강대로 405, 2층 201호 (동자동)4320야미철판볶음밥2018-06-15 09:59:42I2018-08-31 23:59:59.0한식197373.839856450014.537949한식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.9<NA><NA><NA>
401430200003020000-101-1996-0408719960923<NA>3폐업2폐업19971209<NA><NA><NA>02 797830730.90140871서울특별시 용산구 한강로2가 337-1번지<NA><NA>으뜸매기매운탕2001-09-27 00:00:00I2018-08-31 23:59:59.0분식197010.451032447447.03737분식<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N30.9<NA><NA><NA>
1234930200003020000-101-2018-0041020181005<NA>3폐업2폐업20201221<NA><NA><NA><NA>211.60140858서울특별시 용산구 이태원동 126-16 1층서울특별시 용산구 우사단로14길 3, 1층 (이태원동)4405요술집(요리가 있는 술집)2020-12-21 09:45:30U2020-12-23 02:40:00.0경양식199563.353058447985.100399경양식<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N211.6<NA><NA><NA>
1422530200003020000-101-2022-0028320220617<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.10140827서울특별시 용산구 서계동 25서울특별시 용산구 청파로89길 43, 1층 (서계동)4302세올2022-06-17 15:59:21I2021-12-05 23:09:00.0기타196976.195602450094.939121<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
652230200003020000-101-2002-0032420021007<NA>3폐업2폐업20090313<NA><NA><NA>02 703013347.85140848서울특별시 용산구 원효로3가 58-1번지 (지상1층)<NA><NA>쉼터김밥2008-06-17 09:43:58I2018-08-31 23:59:59.0분식196230.759299448007.462945분식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N47.85<NA><NA><NA>
52730200003020000-101-1984-0127919840107<NA>3폐업2폐업20190514<NA><NA><NA>02 798331835.70140858서울특별시 용산구 이태원동 136-5번지 (지상1층)서울특별시 용산구 우사단로14길 8 (이태원동,(지상1층))4405예스2019-05-14 10:59:01U2019-05-16 02:40:00.0기타199586.156519447965.086938기타02유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N35.7<NA><NA><NA>
1277130200003020000-101-2019-0031720190923<NA>3폐업2폐업20211018<NA><NA><NA><NA>35.00140889서울특별시 용산구 한남동 106-2서울특별시 용산구 독서당로 29-1, 1층 101호 (한남동)4410카페1062021-10-18 11:52:34U2021-10-20 02:40:00.0기타200580.663402447655.891219기타00<NA><NA><NA>00000<NA>00N35.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1066530200003020000-101-2015-003452015-07-28<NA>1영업/정상1영업<NA><NA><NA><NA>02 790114043.93140-863서울특별시 용산구 이태원동 57-12서울특별시 용산구 이태원로 143-7, 1층 (이태원동)4351구석탱이2023-07-17 12:37:42U2022-12-06 23:09:00.0경양식199003.844878448030.306459<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
261530200003020000-101-1993-0005619931027<NA>3폐업2폐업19940915<NA><NA><NA>020793395867.34140861서울특별시 용산구 이태원동 639-4번지<NA><NA>미도리2004-01-16 00:00:00I2018-08-31 23:59:59.0한식<NA><NA>한식12학교정화(상대)기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N67.34<NA><NA><NA>
1462530200003020000-101-2023-001102023-04-05<NA>3폐업2폐업2023-08-01<NA><NA><NA><NA>11.00140-830서울특별시 용산구 서계동 263-4서울특별시 용산구 만리재로 152-1, 1층 (서계동)4302비에뜨반미 서울역점2023-08-01 11:54:14U2022-12-08 00:03:00.0외국음식전문점(인도,태국등)196746.599253450029.99214<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1398930200003020000-101-2022-000462022-02-04<NA>3폐업2폐업2023-04-03<NA><NA><NA>02 749270372.70140-861서울특별시 용산구 이태원동 704서울특별시 용산구 녹사평대로54길 7, 지하 1층 (이태원동)4343맥파이 이태원지점2023-04-03 11:18:43U2022-12-04 00:05:00.0외국음식전문점(인도,태국등)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
882330200003020000-101-2011-0001020110117<NA>1영업/정상1영업<NA><NA><NA><NA><NA>19.38140821서울특별시 용산구 동자동 23-27번지 지상1층서울특별시 용산구 한강대로104길 38-3 (동자동, 23-27 지상1층)4333신촌원조식당2016-07-11 09:52:44I2018-08-31 23:59:59.0한식197679.243849449779.651127한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N19.38<NA><NA><NA>
1484830200003020000-101-2023-003342023-08-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.89140-898서울특별시 용산구 효창동 242-1서울특별시 용산구 백범로 282, 1층 (효창동)4355갈비본가 직화구이 전문점2023-08-25 09:35:23I2022-12-07 22:07:00.0한식196424.662655448589.283928<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
185130200003020000-101-1990-0169919900116<NA>3폐업2폐업19961211<NA><NA><NA>020795837429.93140823서울특별시 용산구 보광동 259-1번지<NA><NA>다정2001-09-27 00:00:00I2018-08-31 23:59:59.0한식199860.819809447348.10087한식02기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.93<NA><NA><NA>
61030200003020000-101-1984-0606519840706<NA>3폐업2폐업20060829<NA><NA><NA>02 712362940.85140846서울특별시 용산구 원효로1가 27-6번지<NA><NA>원미옥2004-09-06 00:00:00I2018-08-31 23:59:59.0한식<NA><NA>한식11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.85<NA><NA><NA>
1008730200003020000-101-2014-0024120140725<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.98140911서울특별시 용산구 한남동 756-10번지서울특별시 용산구 우사단로10길 67, 1층 (한남동)4408이드(EID)2014-08-14 14:06:05I2018-08-31 23:59:59.0한식199856.901392447793.491946한식<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N26.0<NA><NA><NA>
148330200003020000-101-1988-0522919881227<NA>3폐업2폐업19960612<NA><NA><NA>02 798613968.43140823서울특별시 용산구 보광동 260-12번지<NA><NA>투달리2001-09-27 00:00:00I2018-08-31 23:59:59.0일식199862.580109447278.462642일식12기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N68.43<NA><NA><NA>