Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells107916
Missing cells (%)24.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory383.0 B

Variable types

Categorical18
Text8
DateTime4
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
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18676/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
총인원 is highly imbalanced (84.3%)Imbalance
본사종업원수 is highly imbalanced (84.3%)Imbalance
공장사무직종업원수 is highly imbalanced (84.3%)Imbalance
공장판매직종업원수 is highly imbalanced (84.3%)Imbalance
공장생산직종업원수 is highly imbalanced (84.3%)Imbalance
보증액 is highly imbalanced (84.3%)Imbalance
월세액 is highly imbalanced (84.3%)Imbalance
다중이용업소여부 is highly imbalanced (91.2%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1799 (18.0%) 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 2875 (28.7%) missing valuesMissing
도로명주소 has 5986 (59.9%) missing valuesMissing
도로명우편번호 has 6038 (60.4%) missing valuesMissing
좌표정보(X) has 320 (3.2%) missing valuesMissing
좌표정보(Y) has 320 (3.2%) missing valuesMissing
남성종사자수 has 3903 (39.0%) missing valuesMissing
여성종사자수 has 3846 (38.5%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1390 (13.9%) missing valuesMissing
시설총규모 has 1390 (13.9%) missing valuesMissing
전통업소지정번호 has 9997 (> 99.9%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 41.34975213)Skewed
여성종사자수 is highly skewed (γ1 = 43.81196837)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 4914 (49.1%) zerosZeros
여성종사자수 has 4329 (43.3%) zerosZeros

Reproduction

Analysis started2024-04-17 23:26:35.294779
Analysis finished2024-04-17 23:26:37.965001
Duration2.67 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
3240000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 10000
100.0%

Length

2024-04-18T08:26:38.024116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:38.135208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T08:26:38.289989image/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 row3240000-101-2020-00095
2nd row3240000-101-2014-00257
3rd row3240000-101-2000-11537
4th row3240000-101-1984-08261
5th row3240000-101-2005-00481
ValueCountFrequency (%)
3240000-101-2020-00095 1
 
< 0.1%
3240000-101-1984-00747 1
 
< 0.1%
3240000-101-1995-07446 1
 
< 0.1%
3240000-101-2023-00236 1
 
< 0.1%
3240000-101-2014-00095 1
 
< 0.1%
3240000-101-2020-00210 1
 
< 0.1%
3240000-101-1993-08582 1
 
< 0.1%
3240000-101-1998-10066 1
 
< 0.1%
3240000-101-2019-00394 1
 
< 0.1%
3240000-101-1993-03513 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-18T08:26:38.591040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76562
34.8%
1 33657
15.3%
- 30000
 
13.6%
2 22199
 
10.1%
3 15610
 
7.1%
4 14177
 
6.4%
9 11521
 
5.2%
8 4711
 
2.1%
6 3976
 
1.8%
7 3900
 
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 76562
40.3%
1 33657
17.7%
2 22199
 
11.7%
3 15610
 
8.2%
4 14177
 
7.5%
9 11521
 
6.1%
8 4711
 
2.5%
6 3976
 
2.1%
7 3900
 
2.1%
5 3687
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76562
34.8%
1 33657
15.3%
- 30000
 
13.6%
2 22199
 
10.1%
3 15610
 
7.1%
4 14177
 
6.4%
9 11521
 
5.2%
8 4711
 
2.1%
6 3976
 
1.8%
7 3900
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76562
34.8%
1 33657
15.3%
- 30000
 
13.6%
2 22199
 
10.1%
3 15610
 
7.1%
4 14177
 
6.4%
9 11521
 
5.2%
8 4711
 
2.1%
6 3976
 
1.8%
7 3900
 
1.8%
Distinct6249
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1904-08-08 00:00:00
Maximum2024-04-16 00:00:00
2024-04-18T08:26:38.728458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T08:26:38.858163image/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
8201 
1
1799 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 8201
82.0%
1 1799
 
18.0%

Length

2024-04-18T08:26:38.982824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:39.069207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8201
82.0%
1 1799
 
18.0%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8201 
영업/정상
1799 

Length

Max length5
Median length2
Mean length2.5397
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8201
82.0%
영업/정상 1799
 
18.0%

Length

2024-04-18T08:26:39.164589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:39.258214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8201
82.0%
영업/정상 1799
 
18.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8201 
1
1799 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 8201
82.0%
1 1799
 
18.0%

Length

2024-04-18T08:26:39.349930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:39.456041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8201
82.0%
1 1799
 
18.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8201 
영업
1799 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8201
82.0%
영업 1799
 
18.0%

Length

2024-04-18T08:26:39.558367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:39.644494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8201
82.0%
영업 1799
 
18.0%

폐업일자
Date

MISSING 

Distinct4532
Distinct (%)55.3%
Missing1799
Missing (%)18.0%
Memory size156.2 KiB
Minimum1990-01-25 00:00:00
Maximum2024-04-16 00:00:00
2024-04-18T08:26:39.762625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T08:26:39.928982image/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 

Distinct5756
Distinct (%)80.8%
Missing2875
Missing (%)28.7%
Memory size156.2 KiB
2024-04-18T08:26:40.253559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.4286316
Min length2

Characters and Unicode

Total characters67179
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

Unique5574 ?
Unique (%)78.2%

Sample

1st row02 429 5658
2nd row02 4852093
3rd row02
4th row02
5th row02 4769409
ValueCountFrequency (%)
02 5477
42.5%
0201768800 128
 
1.0%
0200000000 128
 
1.0%
00000 68
 
0.5%
0 68
 
0.5%
470 66
 
0.5%
428 53
 
0.4%
488 52
 
0.4%
477 51
 
0.4%
471 42
 
0.3%
Other values (5739) 6757
52.4%
2024-04-18T08:26:40.675686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13108
19.5%
2 11400
17.0%
4 8931
13.3%
7151
10.6%
7 5809
8.6%
8 5528
8.2%
3 3283
 
4.9%
6 3178
 
4.7%
1 3038
 
4.5%
5 2934
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60028
89.4%
Space Separator 7151
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13108
21.8%
2 11400
19.0%
4 8931
14.9%
7 5809
9.7%
8 5528
9.2%
3 3283
 
5.5%
6 3178
 
5.3%
1 3038
 
5.1%
5 2934
 
4.9%
9 2819
 
4.7%
Space Separator
ValueCountFrequency (%)
7151
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67179
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13108
19.5%
2 11400
17.0%
4 8931
13.3%
7151
10.6%
7 5809
8.6%
8 5528
8.2%
3 3283
 
4.9%
6 3178
 
4.7%
1 3038
 
4.5%
5 2934
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67179
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13108
19.5%
2 11400
17.0%
4 8931
13.3%
7151
10.6%
7 5809
8.6%
8 5528
8.2%
3 3283
 
4.9%
6 3178
 
4.7%
1 3038
 
4.5%
5 2934
 
4.4%
Distinct4165
Distinct (%)41.9%
Missing52
Missing (%)0.5%
Memory size156.2 KiB
2024-04-18T08:26:41.034035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1099719
Min length3

Characters and Unicode

Total characters50834
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

Unique2831 ?
Unique (%)28.5%

Sample

1st row22.00
2nd row37.24
3rd row20.00
4th row15.40
5th row264.00
ValueCountFrequency (%)
26.40 345
 
3.5%
23.10 179
 
1.8%
33.00 164
 
1.6%
29.70 133
 
1.3%
30.00 124
 
1.2%
66.00 112
 
1.1%
19.80 96
 
1.0%
49.50 85
 
0.9%
39.60 71
 
0.7%
26.00 70
 
0.7%
Other values (4155) 8569
86.1%
2024-04-18T08:26:41.507700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9948
19.6%
0 8435
16.6%
2 5752
11.3%
1 4301
8.5%
3 3812
 
7.5%
4 3769
 
7.4%
6 3512
 
6.9%
5 3213
 
6.3%
9 2872
 
5.6%
8 2820
 
5.5%
Other values (2) 2400
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40882
80.4%
Other Punctuation 9952
 
19.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8435
20.6%
2 5752
14.1%
1 4301
10.5%
3 3812
9.3%
4 3769
9.2%
6 3512
8.6%
5 3213
 
7.9%
9 2872
 
7.0%
8 2820
 
6.9%
7 2396
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 9948
> 99.9%
, 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 50834
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9948
19.6%
0 8435
16.6%
2 5752
11.3%
1 4301
8.5%
3 3812
 
7.5%
4 3769
 
7.4%
6 3512
 
6.9%
5 3213
 
6.3%
9 2872
 
5.6%
8 2820
 
5.5%
Other values (2) 2400
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50834
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9948
19.6%
0 8435
16.6%
2 5752
11.3%
1 4301
8.5%
3 3812
 
7.5%
4 3769
 
7.4%
6 3512
 
6.9%
5 3213
 
6.3%
9 2872
 
5.6%
8 2820
 
5.5%
Other values (2) 2400
 
4.7%
Distinct184
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T08:26:41.860904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0894
Min length6

Characters and Unicode

Total characters60894
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)0.2%

Sample

1st row134866
2nd row134825
3rd row134810
4th row134880
5th row134874
ValueCountFrequency (%)
134830 416
 
4.2%
134867 391
 
3.9%
134864 365
 
3.6%
134814 340
 
3.4%
134840 330
 
3.3%
134859 293
 
2.9%
134874 278
 
2.8%
134880 264
 
2.6%
134871 241
 
2.4%
134846 231
 
2.3%
Other values (174) 6851
68.5%
2024-04-18T08:26:42.318655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 13096
21.5%
1 12517
20.6%
3 11542
19.0%
8 10939
18.0%
0 2929
 
4.8%
7 2612
 
4.3%
6 2359
 
3.9%
5 1695
 
2.8%
2 1305
 
2.1%
9 1006
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60000
98.5%
Dash Punctuation 894
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 13096
21.8%
1 12517
20.9%
3 11542
19.2%
8 10939
18.2%
0 2929
 
4.9%
7 2612
 
4.4%
6 2359
 
3.9%
5 1695
 
2.8%
2 1305
 
2.2%
9 1006
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 894
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60894
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 13096
21.5%
1 12517
20.6%
3 11542
19.0%
8 10939
18.0%
0 2929
 
4.8%
7 2612
 
4.3%
6 2359
 
3.9%
5 1695
 
2.8%
2 1305
 
2.1%
9 1006
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 13096
21.5%
1 12517
20.6%
3 11542
19.0%
8 10939
18.0%
0 2929
 
4.8%
7 2612
 
4.3%
6 2359
 
3.9%
5 1695
 
2.8%
2 1305
 
2.1%
9 1006
 
1.7%
Distinct6516
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T08:26:42.618201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length74
Mean length23.2553
Min length14

Characters and Unicode

Total characters232553
Distinct characters354
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4757 ?
Unique (%)47.6%

Sample

1st row서울특별시 강동구 천호동 224-58번지
2nd row서울특별시 강동구 명일동 46-1 명성프라자 104호
3rd row서울특별시 강동구 길동 330-15번지
4th row서울특별시 강동구 길동 394-3번지
5th row서울특별시 강동구 천호동 469-1번지 7층
ValueCountFrequency (%)
서울특별시 10000
23.1%
강동구 10000
23.1%
천호동 2688
 
6.2%
성내동 2536
 
5.9%
길동 1503
 
3.5%
암사동 1062
 
2.5%
명일동 885
 
2.0%
1층 523
 
1.2%
둔촌동 502
 
1.2%
고덕동 404
 
0.9%
Other values (5864) 13125
30.4%
2024-04-18T08:26:43.089623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41624
17.9%
20328
 
8.7%
10253
 
4.4%
10052
 
4.3%
10031
 
4.3%
10020
 
4.3%
10011
 
4.3%
10002
 
4.3%
10000
 
4.3%
- 9399
 
4.0%
Other values (344) 90833
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133720
57.5%
Decimal Number 46661
 
20.1%
Space Separator 41624
 
17.9%
Dash Punctuation 9399
 
4.0%
Close Punctuation 384
 
0.2%
Open Punctuation 384
 
0.2%
Other Punctuation 236
 
0.1%
Uppercase Letter 123
 
0.1%
Math Symbol 12
 
< 0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20328
15.2%
10253
 
7.7%
10052
 
7.5%
10031
 
7.5%
10020
 
7.5%
10011
 
7.5%
10002
 
7.5%
10000
 
7.5%
8287
 
6.2%
7975
 
6.0%
Other values (299) 26761
20.0%
Uppercase Letter
ValueCountFrequency (%)
B 33
26.8%
A 14
11.4%
U 11
 
8.9%
K 10
 
8.1%
D 8
 
6.5%
F 7
 
5.7%
P 6
 
4.9%
M 5
 
4.1%
H 4
 
3.3%
S 4
 
3.3%
Other values (8) 21
17.1%
Decimal Number
ValueCountFrequency (%)
1 8541
18.3%
4 7317
15.7%
3 6058
13.0%
2 5793
12.4%
5 4523
9.7%
0 3778
8.1%
9 2760
 
5.9%
7 2675
 
5.7%
8 2635
 
5.6%
6 2581
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
l 2
22.2%
s 2
22.2%
a 1
11.1%
e 1
11.1%
w 1
11.1%
q 1
11.1%
k 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 221
93.6%
. 12
 
5.1%
@ 2
 
0.8%
/ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
41624
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9399
100.0%
Close Punctuation
ValueCountFrequency (%)
) 384
100.0%
Open Punctuation
ValueCountFrequency (%)
( 384
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133720
57.5%
Common 98701
42.4%
Latin 132
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20328
15.2%
10253
 
7.7%
10052
 
7.5%
10031
 
7.5%
10020
 
7.5%
10011
 
7.5%
10002
 
7.5%
10000
 
7.5%
8287
 
6.2%
7975
 
6.0%
Other values (299) 26761
20.0%
Latin
ValueCountFrequency (%)
B 33
25.0%
A 14
10.6%
U 11
 
8.3%
K 10
 
7.6%
D 8
 
6.1%
F 7
 
5.3%
P 6
 
4.5%
M 5
 
3.8%
H 4
 
3.0%
S 4
 
3.0%
Other values (15) 30
22.7%
Common
ValueCountFrequency (%)
41624
42.2%
- 9399
 
9.5%
1 8541
 
8.7%
4 7317
 
7.4%
3 6058
 
6.1%
2 5793
 
5.9%
5 4523
 
4.6%
0 3778
 
3.8%
9 2760
 
2.8%
7 2675
 
2.7%
Other values (10) 6233
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133720
57.5%
ASCII 98833
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41624
42.1%
- 9399
 
9.5%
1 8541
 
8.6%
4 7317
 
7.4%
3 6058
 
6.1%
2 5793
 
5.9%
5 4523
 
4.6%
0 3778
 
3.8%
9 2760
 
2.8%
7 2675
 
2.7%
Other values (35) 6365
 
6.4%
Hangul
ValueCountFrequency (%)
20328
15.2%
10253
 
7.7%
10052
 
7.5%
10031
 
7.5%
10020
 
7.5%
10011
 
7.5%
10002
 
7.5%
10000
 
7.5%
8287
 
6.2%
7975
 
6.0%
Other values (299) 26761
20.0%

도로명주소
Text

MISSING 

Distinct3606
Distinct (%)89.8%
Missing5986
Missing (%)59.9%
Memory size156.2 KiB
2024-04-18T08:26:43.370581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length53
Mean length31.032885
Min length21

Characters and Unicode

Total characters124566
Distinct characters335
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

Unique3296 ?
Unique (%)82.1%

Sample

1st row서울특별시 강동구 상암로 119-1, 1층 102호 (천호동)
2nd row서울특별시 강동구 고덕로 256, 104호 (명일동, 명성프라자)
3rd row서울특별시 강동구 구천면로 140 (천호동,7층)
4th row서울특별시 강동구 천호대로158길 14 (성내동)
5th row서울특별시 강동구 상암로63길 48 (명일동)
ValueCountFrequency (%)
서울특별시 4014
 
16.4%
강동구 4014
 
16.4%
1층 1517
 
6.2%
천호동 967
 
4.0%
성내동 852
 
3.5%
길동 515
 
2.1%
암사동 350
 
1.4%
명일동 304
 
1.2%
구천면로 242
 
1.0%
101호 239
 
1.0%
Other values (2107) 11420
46.7%
2024-04-18T08:26:43.779652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20435
 
16.4%
8502
 
6.8%
1 7107
 
5.7%
4434
 
3.6%
4292
 
3.4%
( 4185
 
3.4%
) 4185
 
3.4%
4068
 
3.3%
4029
 
3.2%
4028
 
3.2%
Other values (325) 59301
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70099
56.3%
Decimal Number 21702
 
17.4%
Space Separator 20435
 
16.4%
Open Punctuation 4185
 
3.4%
Close Punctuation 4185
 
3.4%
Other Punctuation 3385
 
2.7%
Dash Punctuation 409
 
0.3%
Uppercase Letter 140
 
0.1%
Math Symbol 16
 
< 0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8502
 
12.1%
4434
 
6.3%
4292
 
6.1%
4068
 
5.8%
4029
 
5.7%
4028
 
5.7%
4015
 
5.7%
4014
 
5.7%
3883
 
5.5%
3174
 
4.5%
Other values (279) 25660
36.6%
Uppercase Letter
ValueCountFrequency (%)
B 56
40.0%
A 13
 
9.3%
U 11
 
7.9%
K 8
 
5.7%
M 7
 
5.0%
D 7
 
5.0%
P 5
 
3.6%
G 4
 
2.9%
H 4
 
2.9%
I 4
 
2.9%
Other values (10) 21
 
15.0%
Decimal Number
ValueCountFrequency (%)
1 7107
32.7%
2 2493
 
11.5%
0 2281
 
10.5%
3 1918
 
8.8%
5 1562
 
7.2%
4 1516
 
7.0%
7 1333
 
6.1%
6 1245
 
5.7%
9 1133
 
5.2%
8 1114
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
s 3
30.0%
l 2
20.0%
a 1
 
10.0%
g 1
 
10.0%
w 1
 
10.0%
e 1
 
10.0%
k 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 3380
99.9%
@ 2
 
0.1%
. 2
 
0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
20435
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4185
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 409
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70099
56.3%
Common 54317
43.6%
Latin 150
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8502
 
12.1%
4434
 
6.3%
4292
 
6.1%
4068
 
5.8%
4029
 
5.7%
4028
 
5.7%
4015
 
5.7%
4014
 
5.7%
3883
 
5.5%
3174
 
4.5%
Other values (279) 25660
36.6%
Latin
ValueCountFrequency (%)
B 56
37.3%
A 13
 
8.7%
U 11
 
7.3%
K 8
 
5.3%
M 7
 
4.7%
D 7
 
4.7%
P 5
 
3.3%
G 4
 
2.7%
H 4
 
2.7%
I 4
 
2.7%
Other values (17) 31
20.7%
Common
ValueCountFrequency (%)
20435
37.6%
1 7107
 
13.1%
( 4185
 
7.7%
) 4185
 
7.7%
, 3380
 
6.2%
2 2493
 
4.6%
0 2281
 
4.2%
3 1918
 
3.5%
5 1562
 
2.9%
4 1516
 
2.8%
Other values (9) 5255
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70099
56.3%
ASCII 54467
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20435
37.5%
1 7107
 
13.0%
( 4185
 
7.7%
) 4185
 
7.7%
, 3380
 
6.2%
2 2493
 
4.6%
0 2281
 
4.2%
3 1918
 
3.5%
5 1562
 
2.9%
4 1516
 
2.8%
Other values (36) 5405
 
9.9%
Hangul
ValueCountFrequency (%)
8502
 
12.1%
4434
 
6.3%
4292
 
6.1%
4068
 
5.8%
4029
 
5.7%
4028
 
5.7%
4015
 
5.7%
4014
 
5.7%
3883
 
5.5%
3174
 
4.5%
Other values (279) 25660
36.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct197
Distinct (%)5.0%
Missing6038
Missing (%)60.4%
Infinite0
Infinite (%)0.0%
Mean5323.32
Minimum5200
Maximum5415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T08:26:43.925308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5200
5-th percentile5225.05
Q15272.25
median5329
Q35370
95-th percentile5405
Maximum5415
Range215
Interquartile range (IQR)97.75

Descriptive statistics

Standard deviation55.799041
Coefficient of variation (CV)0.010482
Kurtosis-0.9541137
Mean5323.32
Median Absolute Deviation (MAD)46
Skewness-0.28345379
Sum21090994
Variance3113.533
MonotonicityNot monotonic
2024-04-18T08:26:44.044321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5328 117
 
1.2%
5353 99
 
1.0%
5405 96
 
1.0%
5269 88
 
0.9%
5257 82
 
0.8%
5329 80
 
0.8%
5404 78
 
0.8%
5222 73
 
0.7%
5335 71
 
0.7%
5373 60
 
0.6%
Other values (187) 3118
31.2%
(Missing) 6038
60.4%
ValueCountFrequency (%)
5200 3
 
< 0.1%
5201 4
 
< 0.1%
5203 12
 
0.1%
5204 6
 
0.1%
5205 1
 
< 0.1%
5207 1
 
< 0.1%
5210 1
 
< 0.1%
5211 47
0.5%
5212 1
 
< 0.1%
5213 2
 
< 0.1%
ValueCountFrequency (%)
5415 10
 
0.1%
5413 1
 
< 0.1%
5411 2
 
< 0.1%
5409 5
 
0.1%
5408 43
0.4%
5407 21
 
0.2%
5406 29
 
0.3%
5405 96
1.0%
5404 78
0.8%
5403 21
 
0.2%
Distinct8556
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T08:26:44.381823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length5.3515
Min length1

Characters and Unicode

Total characters53515
Distinct characters1069
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7730 ?
Unique (%)77.3%

Sample

1st row야미분식(Yami)
2nd row피자헤븐 고덕역점
3rd row쎈스호프
4th row새샘물
5th row스타씨티
ValueCountFrequency (%)
천호점 101
 
0.9%
강동점 69
 
0.6%
길동점 53
 
0.5%
전주식당 30
 
0.3%
한시적영업 29
 
0.3%
암사점 27
 
0.2%
명일점 24
 
0.2%
고덕점 23
 
0.2%
김밥천국 20
 
0.2%
카페 16
 
0.1%
Other values (8991) 11117
96.6%
2024-04-18T08:26:44.846792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1512
 
2.8%
1267
 
2.4%
1025
 
1.9%
962
 
1.8%
920
 
1.7%
806
 
1.5%
771
 
1.4%
761
 
1.4%
744
 
1.4%
723
 
1.4%
Other values (1059) 44024
82.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48895
91.4%
Space Separator 1512
 
2.8%
Lowercase Letter 914
 
1.7%
Uppercase Letter 811
 
1.5%
Decimal Number 492
 
0.9%
Close Punctuation 367
 
0.7%
Open Punctuation 364
 
0.7%
Other Punctuation 147
 
0.3%
Dash Punctuation 11
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1267
 
2.6%
1025
 
2.1%
962
 
2.0%
920
 
1.9%
806
 
1.6%
771
 
1.6%
761
 
1.6%
744
 
1.5%
723
 
1.5%
614
 
1.3%
Other values (981) 40302
82.4%
Lowercase Letter
ValueCountFrequency (%)
e 146
16.0%
o 89
 
9.7%
a 78
 
8.5%
i 61
 
6.7%
r 57
 
6.2%
t 54
 
5.9%
n 50
 
5.5%
l 45
 
4.9%
c 43
 
4.7%
f 39
 
4.3%
Other values (16) 252
27.6%
Uppercase Letter
ValueCountFrequency (%)
A 76
 
9.4%
C 64
 
7.9%
B 62
 
7.6%
O 60
 
7.4%
H 46
 
5.7%
E 44
 
5.4%
S 36
 
4.4%
N 34
 
4.2%
T 34
 
4.2%
F 34
 
4.2%
Other values (16) 321
39.6%
Decimal Number
ValueCountFrequency (%)
1 90
18.3%
2 75
15.2%
0 67
13.6%
9 60
12.2%
3 53
10.8%
8 45
9.1%
5 36
 
7.3%
4 32
 
6.5%
7 17
 
3.5%
6 17
 
3.5%
Other Punctuation
ValueCountFrequency (%)
& 47
32.0%
. 43
29.3%
, 26
17.7%
? 11
 
7.5%
' 7
 
4.8%
! 7
 
4.8%
% 2
 
1.4%
/ 2
 
1.4%
1
 
0.7%
@ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
1512
100.0%
Close Punctuation
ValueCountFrequency (%)
) 367
100.0%
Open Punctuation
ValueCountFrequency (%)
( 364
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48859
91.3%
Common 2894
 
5.4%
Latin 1726
 
3.2%
Han 36
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1267
 
2.6%
1025
 
2.1%
962
 
2.0%
920
 
1.9%
806
 
1.6%
771
 
1.6%
761
 
1.6%
744
 
1.5%
723
 
1.5%
614
 
1.3%
Other values (953) 40266
82.4%
Latin
ValueCountFrequency (%)
e 146
 
8.5%
o 89
 
5.2%
a 78
 
4.5%
A 76
 
4.4%
C 64
 
3.7%
B 62
 
3.6%
i 61
 
3.5%
O 60
 
3.5%
r 57
 
3.3%
t 54
 
3.1%
Other values (43) 979
56.7%
Han
ValueCountFrequency (%)
5
 
13.9%
3
 
8.3%
2
 
5.6%
2
 
5.6%
1
 
2.8%
1
 
2.8%
1
 
2.8%
1
 
2.8%
1
 
2.8%
1
 
2.8%
Other values (18) 18
50.0%
Common
ValueCountFrequency (%)
1512
52.2%
) 367
 
12.7%
( 364
 
12.6%
1 90
 
3.1%
2 75
 
2.6%
0 67
 
2.3%
9 60
 
2.1%
3 53
 
1.8%
& 47
 
1.6%
8 45
 
1.6%
Other values (15) 214
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48857
91.3%
ASCII 4618
 
8.6%
CJK 35
 
0.1%
Compat Jamo 2
 
< 0.1%
Punctuation 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1512
32.7%
) 367
 
7.9%
( 364
 
7.9%
e 146
 
3.2%
1 90
 
1.9%
o 89
 
1.9%
a 78
 
1.7%
A 76
 
1.6%
2 75
 
1.6%
0 67
 
1.5%
Other values (66) 1754
38.0%
Hangul
ValueCountFrequency (%)
1267
 
2.6%
1025
 
2.1%
962
 
2.0%
920
 
1.9%
806
 
1.6%
771
 
1.6%
761
 
1.6%
744
 
1.5%
723
 
1.5%
614
 
1.3%
Other values (951) 40264
82.4%
CJK
ValueCountFrequency (%)
5
 
14.3%
3
 
8.6%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (17) 17
48.6%
Punctuation
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct6552
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-07 00:00:00
Maximum2024-04-16 15:26:16
2024-04-18T08:26:44.975721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T08:26:45.115518image/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
7867 
U
2133 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7867
78.7%
U 2133
 
21.3%

Length

2024-04-18T08:26:45.256184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:45.343334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7867
78.7%
u 2133
 
21.3%
Distinct1154
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-18T08:26:45.429506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T08:26:45.557477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4058 
분식
2283 
호프/통닭
1011 
경양식
600 
기타
505 
Other values (19)
1543 

Length

Max length15
Median length2
Mean length2.8469
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row분식
2nd row통닭(치킨)
3rd row호프/통닭
4th row분식
5th row호프/통닭

Common Values

ValueCountFrequency (%)
한식 4058
40.6%
분식 2283
22.8%
호프/통닭 1011
 
10.1%
경양식 600
 
6.0%
기타 505
 
5.1%
정종/대포집/소주방 317
 
3.2%
일식 298
 
3.0%
중국식 285
 
2.9%
통닭(치킨) 237
 
2.4%
까페 86
 
0.9%
Other values (14) 320
 
3.2%

Length

2024-04-18T08:26:45.692990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4058
40.6%
분식 2283
22.8%
호프/통닭 1011
 
10.1%
경양식 600
 
6.0%
기타 505
 
5.1%
정종/대포집/소주방 317
 
3.2%
일식 298
 
3.0%
중국식 285
 
2.9%
통닭(치킨 237
 
2.4%
까페 86
 
0.9%
Other values (14) 320
 
3.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3809
Distinct (%)39.3%
Missing320
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean212060.62
Minimum210480.77
Maximum216037.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T08:26:45.813823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210480.77
5-th percentile210862.3
Q1211281.42
median211840.76
Q3212544.27
95-th percentile214696.19
Maximum216037.21
Range5556.4376
Interquartile range (IQR)1262.8534

Descriptive statistics

Standard deviation1038.5114
Coefficient of variation (CV)0.0048972383
Kurtosis1.8089735
Mean212060.62
Median Absolute Deviation (MAD)602.09952
Skewness1.3575947
Sum2.0527468 × 109
Variance1078505.9
MonotonicityNot monotonic
2024-04-18T08:26:45.938866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210929.919693661 44
 
0.4%
210931.643485 41
 
0.4%
213493.90717524 35
 
0.4%
211279.030241561 30
 
0.3%
212172.828537488 29
 
0.3%
212334.9584644 28
 
0.3%
213048.692179757 25
 
0.2%
211863.996107162 25
 
0.2%
210970.75707265 25
 
0.2%
212081.019857419 22
 
0.2%
Other values (3799) 9376
93.8%
(Missing) 320
 
3.2%
ValueCountFrequency (%)
210480.767564873 1
 
< 0.1%
210558.095600946 4
 
< 0.1%
210567.056218374 1
 
< 0.1%
210567.072509045 1
 
< 0.1%
210573.186608263 1
 
< 0.1%
210575.541535172 10
0.1%
210579.764835208 2
 
< 0.1%
210589.447298199 1
 
< 0.1%
210599.252168998 1
 
< 0.1%
210607.529826692 1
 
< 0.1%
ValueCountFrequency (%)
216037.205176194 1
< 0.1%
216029.388021 1
< 0.1%
216006.293465612 1
< 0.1%
215958.498951055 2
< 0.1%
215951.989631069 1
< 0.1%
215888.898816 1
< 0.1%
215875.024969 2
< 0.1%
215849.976239044 1
< 0.1%
215774.281326864 1
< 0.1%
215772.159219333 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3809
Distinct (%)39.3%
Missing320
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean448773.72
Minimum446598.59
Maximum452797.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T08:26:46.083258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446598.59
5-th percentile447167.06
Q1447990.73
median448661.11
Q3449619.73
95-th percentile450559.23
Maximum452797.96
Range6199.3724
Interquartile range (IQR)1629.0068

Descriptive statistics

Standard deviation1047.0571
Coefficient of variation (CV)0.0023331516
Kurtosis-0.42661746
Mean448773.72
Median Absolute Deviation (MAD)817.62076
Skewness0.2690426
Sum4.3441296 × 109
Variance1096328.6
MonotonicityNot monotonic
2024-04-18T08:26:46.212636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448537.406728283 44
 
0.4%
448522.079827 41
 
0.4%
450038.847319845 35
 
0.4%
448548.819716671 30
 
0.3%
448321.330153611 29
 
0.3%
450346.790651613 28
 
0.3%
450124.105734971 25
 
0.2%
447092.251026265 25
 
0.2%
448713.31669728 25
 
0.2%
448209.124823551 22
 
0.2%
Other values (3799) 9376
93.8%
(Missing) 320
 
3.2%
ValueCountFrequency (%)
446598.591776331 4
 
< 0.1%
446680.303498539 9
0.1%
446699.196101461 8
0.1%
446719.053565685 1
 
< 0.1%
446748.493341691 11
0.1%
446755.547655259 2
 
< 0.1%
446761.604007505 2
 
< 0.1%
446766.631391106 1
 
< 0.1%
446777.558590088 1
 
< 0.1%
446778.592045172 1
 
< 0.1%
ValueCountFrequency (%)
452797.964140486 1
 
< 0.1%
452758.558082703 1
 
< 0.1%
452742.267264252 1
 
< 0.1%
452305.723682264 1
 
< 0.1%
452302.694269798 1
 
< 0.1%
452269.014454429 3
< 0.1%
452247.431947179 2
< 0.1%
452233.685440247 1
 
< 0.1%
452213.416817557 1
 
< 0.1%
452195.587817951 1
 
< 0.1%

위생업태명
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3468 
분식
2168 
<NA>
1390 
호프/통닭
877 
경양식
518 
Other values (20)
1579 

Length

Max length15
Median length2
Mean length3.0103
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row분식
2nd row<NA>
3rd row호프/통닭
4th row분식
5th row호프/통닭

Common Values

ValueCountFrequency (%)
한식 3468
34.7%
분식 2168
21.7%
<NA> 1390
13.9%
호프/통닭 877
 
8.8%
경양식 518
 
5.2%
정종/대포집/소주방 298
 
3.0%
기타 281
 
2.8%
중국식 236
 
2.4%
일식 222
 
2.2%
통닭(치킨) 220
 
2.2%
Other values (15) 322
 
3.2%

Length

2024-04-18T08:26:46.388556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3468
34.7%
분식 2168
21.7%
na 1390
13.9%
호프/통닭 877
 
8.8%
경양식 518
 
5.2%
정종/대포집/소주방 298
 
3.0%
기타 281
 
2.8%
중국식 236
 
2.4%
일식 222
 
2.2%
통닭(치킨 220
 
2.2%
Other values (15) 322
 
3.2%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct10
Distinct (%)0.2%
Missing3903
Missing (%)39.0%
Infinite0
Infinite (%)0.0%
Mean0.28489421
Minimum0
Maximum93
Zeros4914
Zeros (%)49.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T08:26:46.490178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum93
Range93
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.9028289
Coefficient of variation (CV)6.6790717
Kurtosis1921.1826
Mean0.28489421
Median Absolute Deviation (MAD)0
Skewness41.349752
Sum1737
Variance3.6207577
MonotonicityNot monotonic
2024-04-18T08:26:46.588079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 4914
49.1%
1 961
 
9.6%
2 152
 
1.5%
3 47
 
0.5%
4 15
 
0.1%
7 3
 
< 0.1%
5 2
 
< 0.1%
92 1
 
< 0.1%
55 1
 
< 0.1%
93 1
 
< 0.1%
(Missing) 3903
39.0%
ValueCountFrequency (%)
0 4914
49.1%
1 961
 
9.6%
2 152
 
1.5%
3 47
 
0.5%
4 15
 
0.1%
5 2
 
< 0.1%
7 3
 
< 0.1%
55 1
 
< 0.1%
92 1
 
< 0.1%
93 1
 
< 0.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
92 1
 
< 0.1%
55 1
 
< 0.1%
7 3
 
< 0.1%
5 2
 
< 0.1%
4 15
 
0.1%
3 47
 
0.5%
2 152
 
1.5%
1 961
 
9.6%
0 4914
49.1%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct10
Distinct (%)0.2%
Missing3846
Missing (%)38.5%
Infinite0
Infinite (%)0.0%
Mean0.41355216
Minimum0
Maximum93
Zeros4329
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T08:26:46.681119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum93
Range93
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8078737
Coefficient of variation (CV)4.3715735
Kurtosis2235.4243
Mean0.41355216
Median Absolute Deviation (MAD)0
Skewness43.811968
Sum2545
Variance3.2684072
MonotonicityNot monotonic
2024-04-18T08:26:46.778841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 4329
43.3%
1 1419
 
14.2%
2 320
 
3.2%
3 58
 
0.6%
4 14
 
0.1%
5 6
 
0.1%
6 3
 
< 0.1%
93 2
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
(Missing) 3846
38.5%
ValueCountFrequency (%)
0 4329
43.3%
1 1419
 
14.2%
2 320
 
3.2%
3 58
 
0.6%
4 14
 
0.1%
5 6
 
0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
93 2
 
< 0.1%
ValueCountFrequency (%)
93 2
 
< 0.1%
8 1
 
< 0.1%
7 2
 
< 0.1%
6 3
 
< 0.1%
5 6
 
0.1%
4 14
 
0.1%
3 58
 
0.6%
2 320
 
3.2%
1 1419
 
14.2%
0 4329
43.3%
Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4950 
주택가주변
3485 
기타
883 
유흥업소밀집지역
 
463
아파트지역
 
191
Other values (4)
 
28

Length

Max length8
Median length7
Mean length4.3861
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4950
49.5%
주택가주변 3485
34.8%
기타 883
 
8.8%
유흥업소밀집지역 463
 
4.6%
아파트지역 191
 
1.9%
결혼예식장주변 11
 
0.1%
학교정화(상대) 10
 
0.1%
학교정화(절대) 6
 
0.1%
주택가?嶺? 1
 
< 0.1%

Length

2024-04-18T08:26:46.900076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:47.008879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4950
49.5%
주택가주변 3485
34.8%
기타 883
 
8.8%
유흥업소밀집지역 463
 
4.6%
아파트지역 191
 
1.9%
결혼예식장주변 11
 
0.1%
학교정화(상대 10
 
0.1%
학교정화(절대 6
 
0.1%
주택가?嶺 1
 
< 0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4951 
기타
2116 
자율
1862 
지도
 
486
 
460
Other values (3)
 
125

Length

Max length4
Median length2
Mean length2.9357
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4951
49.5%
기타 2116
21.2%
자율 1862
 
18.6%
지도 486
 
4.9%
460
 
4.6%
85
 
0.9%
관리 26
 
0.3%
우수 14
 
0.1%

Length

2024-04-18T08:26:47.128435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:47.236120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4951
49.5%
기타 2116
21.2%
자율 1862
 
18.6%
지도 486
 
4.9%
460
 
4.6%
85
 
0.9%
관리 26
 
0.3%
우수 14
 
0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
5287 
<NA>
4677 
상수도(음용)지하수(주방용)겸용
 
20
지하수전용
 
16

Length

Max length17
Median length5
Mean length4.5563
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 5287
52.9%
<NA> 4677
46.8%
상수도(음용)지하수(주방용)겸용 20
 
0.2%
지하수전용 16
 
0.2%

Length

2024-04-18T08:26:47.371659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:47.469604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 5287
52.9%
na 4677
46.8%
상수도(음용)지하수(주방용)겸용 20
 
0.2%
지하수전용 16
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9772 
0
 
228

Length

Max length4
Median length4
Mean length3.9316
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> 9772
97.7%
0 228
 
2.3%

Length

2024-04-18T08:26:47.578566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:47.667423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9772
97.7%
0 228
 
2.3%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9772 
0
 
228

Length

Max length4
Median length4
Mean length3.9316
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> 9772
97.7%
0 228
 
2.3%

Length

2024-04-18T08:26:47.759508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:47.858368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9772
97.7%
0 228
 
2.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9772 
0
 
228

Length

Max length4
Median length4
Mean length3.9316
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> 9772
97.7%
0 228
 
2.3%

Length

2024-04-18T08:26:47.959282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:48.057627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9772
97.7%
0 228
 
2.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9772 
0
 
228

Length

Max length4
Median length4
Mean length3.9316
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> 9772
97.7%
0 228
 
2.3%

Length

2024-04-18T08:26:48.156087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:48.248490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9772
97.7%
0 228
 
2.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9772 
0
 
228

Length

Max length4
Median length4
Mean length3.9316
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> 9772
97.7%
0 228
 
2.3%

Length

2024-04-18T08:26:48.356371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:48.470940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9772
97.7%
0 228
 
2.3%

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>
9772 
0
 
228

Length

Max length4
Median length4
Mean length3.9316
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> 9772
97.7%
0 228
 
2.3%

Length

2024-04-18T08:26:48.577094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:48.686872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9772
97.7%
0 228
 
2.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9772 
0
 
228

Length

Max length4
Median length4
Mean length3.9316
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> 9772
97.7%
0 228
 
2.3%

Length

2024-04-18T08:26:48.793209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T08:26:48.881753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9772
97.7%
0 228
 
2.3%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1390
Missing (%)13.9%
Memory size97.7 KiB
False
8515 
True
 
95
(Missing)
1390 
ValueCountFrequency (%)
False 8515
85.2%
True 95
 
0.9%
(Missing) 1390
 
13.9%
2024-04-18T08:26:48.956799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct3744
Distinct (%)43.5%
Missing1390
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean56.022466
Minimum0
Maximum1479.18
Zeros30
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T08:26:49.699897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q123.6225
median32.78
Q365.9975
95-th percentile159.091
Maximum1479.18
Range1479.18
Interquartile range (IQR)42.375

Descriptive statistics

Standard deviation68.412653
Coefficient of variation (CV)1.2211646
Kurtosis63.579608
Mean56.022466
Median Absolute Deviation (MAD)12.845
Skewness5.9260192
Sum482353.43
Variance4680.2911
MonotonicityNot monotonic
2024-04-18T08:26:49.863749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.4 325
 
3.2%
23.1 175
 
1.8%
29.7 130
 
1.3%
33.0 127
 
1.3%
66.0 96
 
1.0%
19.8 93
 
0.9%
30.0 91
 
0.9%
49.5 69
 
0.7%
39.6 67
 
0.7%
24.0 63
 
0.6%
Other values (3734) 7374
73.7%
(Missing) 1390
 
13.9%
ValueCountFrequency (%)
0.0 30
0.3%
2.82 1
 
< 0.1%
3.3 2
 
< 0.1%
4.17 1
 
< 0.1%
4.68 1
 
< 0.1%
4.75 1
 
< 0.1%
5.0 1
 
< 0.1%
5.46 1
 
< 0.1%
6.0 1
 
< 0.1%
6.23 1
 
< 0.1%
ValueCountFrequency (%)
1479.18 1
< 0.1%
1227.87 1
< 0.1%
1041.5 1
< 0.1%
978.46 1
< 0.1%
855.68 1
< 0.1%
825.0 1
< 0.1%
785.76 1
< 0.1%
762.46 1
< 0.1%
750.48 1
< 0.1%
729.94 1
< 0.1%
Distinct3
Distinct (%)100.0%
Missing9997
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-18T08:26:49.962345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length2.3333333
Min length1

Characters and Unicode

Total characters7
Distinct characters3
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 row9
2nd row-----
3rd row+
ValueCountFrequency (%)
2
66.7%
9 1
33.3%
2024-04-18T08:26:50.218832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5
71.4%
9 1
 
14.3%
+ 1
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Dash Punctuation 5
71.4%
Decimal Number 1
 
14.3%
Math Symbol 1
 
14.3%

Most frequent character per category

Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Decimal Number
ValueCountFrequency (%)
9 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 5
71.4%
9 1
 
14.3%
+ 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5
71.4%
9 1
 
14.3%
+ 1
 
14.3%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
2022532400003240000-101-2020-0009520200312<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.00134866서울특별시 강동구 천호동 224-58번지서울특별시 강동구 상암로 119-1, 1층 102호 (천호동)5309야미분식(Yami)2020-03-12 16:14:15I2020-03-14 00:23:22.0분식211952.587213449393.507301분식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N22.0<NA><NA><NA>
1781032400003240000-101-2014-0025720140808<NA>3폐업2폐업20221208<NA><NA><NA>02 429 565837.24134825서울특별시 강동구 명일동 46-1 명성프라자 104호서울특별시 강동구 고덕로 256, 104호 (명일동, 명성프라자)5269피자헤븐 고덕역점2022-12-08 10:12:19U2021-11-01 23:00:00.0통닭(치킨)213545.481603450269.254821<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
960432400003240000-101-2000-1153720000519<NA>3폐업2폐업20051208<NA><NA><NA>02 485209320.00134810서울특별시 강동구 길동 330-15번지<NA><NA>쎈스호프2003-03-24 00:00:00I2018-08-31 23:59:59.0호프/통닭212778.616004448932.723109호프/통닭00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N20.0<NA><NA><NA>
56132400003240000-101-1984-0826119840218<NA>3폐업2폐업20010827<NA><NA><NA>0215.40134880서울특별시 강동구 길동 394-3번지<NA><NA>새샘물2002-06-05 00:00:00I2018-08-31 23:59:59.0분식212399.142107448376.401564분식10기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N15.4<NA><NA><NA>
1376532400003240000-101-2005-0048120051111<NA>3폐업2폐업20170529<NA><NA><NA><NA>264.00134874서울특별시 강동구 천호동 469-1번지 7층서울특별시 강동구 구천면로 140 (천호동,7층)5247스타씨티2017-05-29 12:02:22I2018-08-31 23:59:59.0호프/통닭210575.541535448896.628722호프/통닭00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N264.0<NA><NA><NA>
861932400003240000-101-1999-0373519991021<NA>3폐업2폐업19991021<NA><NA><NA>0224.50134859서울특별시 강동구 암사동 493-0번지<NA><NA>응 거기1999-10-21 00:00:00I2018-08-31 23:59:59.0분식211536.015639449892.2849분식00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N24.5<NA><NA><NA>
311332400003240000-101-1992-0212319920108<NA>3폐업2폐업19971119<NA><NA><NA>02 476940917.78134861서울특별시 강동구 천호동 21-196번지<NA><NA>촌집식당2002-06-05 00:00:00I2018-08-31 23:59:59.0한식212180.633608449243.348323한식01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N17.78<NA><NA><NA>
1592132400003240000-101-2010-002202010-06-08<NA>1영업/정상1영업<NA><NA><NA><NA>02 471 791162.16134-840서울특별시 강동구 성내동 50-25서울특별시 강동구 천호대로158길 14 (성내동)5379쭈꾸미포차2023-10-26 17:46:36U2022-10-30 22:08:00.0한식211093.200677448301.882443<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1751132400003240000-101-2013-0036620131125<NA>3폐업2폐업20210818<NA><NA><NA>02 3426097160.00134826서울특별시 강동구 명일동 86서울특별시 강동구 상암로63길 48 (명일동)5271남한산성2021-08-18 14:57:15U2021-08-20 02:40:00.0한식213558.971026449613.04285한식00<NA><NA><NA>00000<NA>00N60.0<NA><NA><NA>
628032400003240000-101-1996-0584519961108<NA>3폐업2폐업20010317<NA><NA><NA>02 476138454.12134866서울특별시 강동구 천호동 243-3번지<NA><NA>길민속주점2001-03-17 00:00:00I2018-08-31 23:59:59.0정종/대포집/소주방212005.141394449656.437086정종/대포집/소주방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N54.12<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
105432400003240000-101-1987-0213419870214<NA>3폐업2폐업20171026<NA><NA><NA>02 488040533.00134890서울특별시 강동구 성내동 433-14번지 1층서울특별시 강동구 양재대로89길 69, 1층 (성내동)5406페리카나치킨2017-10-26 10:42:11I2018-08-31 23:59:59.0통닭(치킨)211574.627259447234.590196통닭(치킨)00주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N33.0<NA><NA><NA>
1824932400003240000-101-2015-0027620150903<NA>3폐업2폐업20200122<NA><NA><NA><NA>172.98134843서울특별시 강동구 성내동 378-18번지서울특별시 강동구 천호대로176길 13, 지1층 (성내동)5373별이 빛나는 밤에2020-01-30 11:39:39U2020-02-01 02:40:00.0라이브카페211980.125475447952.156334라이브카페<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Y172.98<NA><NA><NA>
939132400003240000-101-2000-1128120000128<NA>3폐업2폐업20011130<NA><NA><NA>02152.00134814서울특별시 강동구 길동 457-4번지<NA><NA>토요일오후2001-11-30 00:00:00I2018-08-31 23:59:59.0경양식212060.935103448068.174635경양식00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N152.0<NA><NA><NA>
515932400003240000-101-1994-0994819940926<NA>3폐업2폐업20171117<NA><NA><NA>02 481897994.62134830서울특별시 강동구 명일동 312-66번지서울특별시 강동구 고덕로38길 63 (명일동)5257원조쌈밥2017-11-17 10:48:02I2018-08-31 23:59:59.0한식212540.988392449945.912392한식00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N94.62<NA><NA><NA>
672432400003240000-101-1996-0990719960412<NA>3폐업2폐업19980401<NA><NA><NA>02 019.42134808서울특별시 강동구 길동 87-0번지<NA><NA>해림회집2002-06-05 00:00:00I2018-08-31 23:59:59.0일식212900.560816448872.407937일식<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N19.42<NA><NA><NA>
2059632400003240000-101-2020-0046620201127<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.44134890서울특별시 강동구 성내동 431-17서울특별시 강동구 강동대로53길 93, 104호 (성내동)5406돈가스만뷔페2022-12-19 16:00:47U2021-11-01 22:01:00.0뷔페식211667.428786447195.197383<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1161132400003240000-101-2002-1379520020917<NA>3폐업2폐업20030516<NA><NA><NA><NA><NA>134857서울특별시 강동구 암사동 463-7번지<NA><NA>까치네식당2002-09-17 00:00:00I2018-08-31 23:59:59.0한식211321.146576450029.761421한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
694732400003240000-101-1997-0114419970617<NA>3폐업2폐업19980925<NA><NA><NA>02 486296117.67134811서울특별시 강동구 길동 337-10번지<NA><NA>장평식당2002-06-05 00:00:00I2018-08-31 23:59:59.0한식212577.517934448939.125832한식<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N17.67<NA><NA><NA>
706532400003240000-101-1997-0577919970526<NA>3폐업2폐업19980805<NA><NA><NA>02 476248723.80134884서울특별시 강동구 성내동 420-19번지<NA><NA>이즈2002-06-05 00:00:00I2018-08-31 23:59:59.0정종/대포집/소주방211548.412647447509.818582정종/대포집/소주방<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.8<NA><NA><NA>
1921932400003240000-101-2018-0000320180103<NA>1영업/정상1영업<NA><NA><NA><NA>02 471228645.00134818서울특별시 강동구 둔촌동 98-83번지서울특별시 강동구 진황도로61길 48-4, 지하1층 (둔촌동)5369청수식당2018-01-03 09:43:29I2018-08-31 23:59:59.0한식212812.436697447347.558712한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N45.0<NA><NA><NA>