Overview

Dataset statistics

Number of variables44
Number of observations5636
Missing cells64569
Missing cells (%)26.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 MiB
Average record size in memory376.0 B

Variable types

Categorical18
Text7
DateTime4
Unsupported8
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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-18692/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (68.5%)Imbalance
등급구분명 is highly imbalanced (62.5%)Imbalance
급수시설구분명 is highly imbalanced (55.5%)Imbalance
총인원 is highly imbalanced (65.2%)Imbalance
본사종업원수 is highly imbalanced (64.5%)Imbalance
공장사무직종업원수 is highly imbalanced (64.5%)Imbalance
공장판매직종업원수 is highly imbalanced (64.5%)Imbalance
공장생산직종업원수 is highly imbalanced (64.5%)Imbalance
보증액 is highly imbalanced (64.5%)Imbalance
월세액 is highly imbalanced (64.5%)Imbalance
다중이용업소여부 is highly imbalanced (92.6%)Imbalance
인허가취소일자 has 5636 (100.0%) missing valuesMissing
폐업일자 has 1985 (35.2%) missing valuesMissing
휴업시작일자 has 5636 (100.0%) missing valuesMissing
휴업종료일자 has 5636 (100.0%) missing valuesMissing
재개업일자 has 5636 (100.0%) missing valuesMissing
전화번호 has 2537 (45.0%) missing valuesMissing
소재지면적 has 127 (2.3%) missing valuesMissing
도로명주소 has 1356 (24.1%) missing valuesMissing
도로명우편번호 has 1390 (24.7%) missing valuesMissing
좌표정보(X) has 331 (5.9%) missing valuesMissing
좌표정보(Y) has 331 (5.9%) missing valuesMissing
남성종사자수 has 4182 (74.2%) missing valuesMissing
여성종사자수 has 4146 (73.6%) missing valuesMissing
건물소유구분명 has 5636 (100.0%) missing valuesMissing
다중이용업소여부 has 1547 (27.4%) missing valuesMissing
시설총규모 has 1547 (27.4%) missing valuesMissing
전통업소지정번호 has 5636 (100.0%) missing valuesMissing
전통업소주된음식 has 5636 (100.0%) missing valuesMissing
홈페이지 has 5636 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 63.87752914)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
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 1097 (19.5%) zerosZeros
여성종사자수 has 736 (13.1%) zerosZeros
시설총규모 has 108 (1.9%) zerosZeros

Reproduction

Analysis started2024-05-11 06:42:36.210629
Analysis finished2024-05-11 06:42:39.657818
Duration3.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
3150000
5636 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 5636
100.0%

Length

2024-05-11T15:42:39.750297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:39.891161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 5636
100.0%

관리번호
Text

UNIQUE 

Distinct5636
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
2024-05-11T15:42:40.157931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters123992
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

Unique5636 ?
Unique (%)100.0%

Sample

1st row3150000-104-1966-07235
2nd row3150000-104-1970-07143
3rd row3150000-104-1970-07169
4th row3150000-104-1971-07152
5th row3150000-104-1971-07201
ValueCountFrequency (%)
3150000-104-1966-07235 1
 
< 0.1%
3150000-104-2018-00042 1
 
< 0.1%
3150000-104-2018-00283 1
 
< 0.1%
3150000-104-2018-00282 1
 
< 0.1%
3150000-104-2018-00281 1
 
< 0.1%
3150000-104-2018-00280 1
 
< 0.1%
3150000-104-2018-00279 1
 
< 0.1%
3150000-104-2018-00278 1
 
< 0.1%
3150000-104-2018-00277 1
 
< 0.1%
3150000-104-2018-00276 1
 
< 0.1%
Other values (5626) 5626
99.8%
2024-05-11T15:42:40.671672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48567
39.2%
1 18260
 
14.7%
- 16908
 
13.6%
2 9055
 
7.3%
3 7919
 
6.4%
4 7289
 
5.9%
5 7198
 
5.8%
9 3160
 
2.5%
7 1979
 
1.6%
8 1965
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 107084
86.4%
Dash Punctuation 16908
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48567
45.4%
1 18260
 
17.1%
2 9055
 
8.5%
3 7919
 
7.4%
4 7289
 
6.8%
5 7198
 
6.7%
9 3160
 
3.0%
7 1979
 
1.8%
8 1965
 
1.8%
6 1692
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 16908
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123992
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48567
39.2%
1 18260
 
14.7%
- 16908
 
13.6%
2 9055
 
7.3%
3 7919
 
6.4%
4 7289
 
5.9%
5 7198
 
5.8%
9 3160
 
2.5%
7 1979
 
1.6%
8 1965
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123992
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48567
39.2%
1 18260
 
14.7%
- 16908
 
13.6%
2 9055
 
7.3%
3 7919
 
6.4%
4 7289
 
5.9%
5 7198
 
5.8%
9 3160
 
2.5%
7 1979
 
1.6%
8 1965
 
1.6%
Distinct3604
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
Minimum1966-10-28 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:42:40.933929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:41.168669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5636
Missing (%)100.0%
Memory size49.7 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
3
3651 
1
1985 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 3651
64.8%
1 1985
35.2%

Length

2024-05-11T15:42:41.360725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:41.480718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3651
64.8%
1 1985
35.2%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
폐업
3651 
영업/정상
1985 

Length

Max length5
Median length2
Mean length3.0566004
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3651
64.8%
영업/정상 1985
35.2%

Length

2024-05-11T15:42:41.615229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:41.742942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3651
64.8%
영업/정상 1985
35.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
2
3651 
1
1985 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 3651
64.8%
1 1985
35.2%

Length

2024-05-11T15:42:41.879974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:41.999407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3651
64.8%
1 1985
35.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
폐업
3651 
영업
1985 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3651
64.8%
영업 1985
35.2%

Length

2024-05-11T15:42:42.128806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:42.240008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3651
64.8%
영업 1985
35.2%

폐업일자
Date

MISSING 

Distinct2622
Distinct (%)71.8%
Missing1985
Missing (%)35.2%
Memory size44.2 KiB
Minimum1977-01-07 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:42:42.379582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:42.563375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5636
Missing (%)100.0%
Memory size49.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5636
Missing (%)100.0%
Memory size49.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5636
Missing (%)100.0%
Memory size49.7 KiB

전화번호
Text

MISSING 

Distinct2850
Distinct (%)92.0%
Missing2537
Missing (%)45.0%
Memory size44.2 KiB
2024-05-11T15:42:42.879921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9767667
Min length2

Characters and Unicode

Total characters30918
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

Unique2737 ?
Unique (%)88.3%

Sample

1st row0206054744
2nd row0206645266
3rd row0206620786
4th row02 6647377
5th row0206053317
ValueCountFrequency (%)
02 686
 
18.1%
0232848111 22
 
0.6%
0200000000 16
 
0.4%
00000 12
 
0.3%
0 11
 
0.3%
070 10
 
0.3%
528 8
 
0.2%
0226608000 8
 
0.2%
7130 7
 
0.2%
0221661052 6
 
0.2%
Other values (2864) 3000
79.2%
2024-05-11T15:42:43.429896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6136
19.8%
2 5932
19.2%
6 4971
16.1%
3 2232
 
7.2%
5 2027
 
6.6%
1 1914
 
6.2%
7 1807
 
5.8%
9 1744
 
5.6%
8 1710
 
5.5%
4 1635
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30108
97.4%
Space Separator 810
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6136
20.4%
2 5932
19.7%
6 4971
16.5%
3 2232
 
7.4%
5 2027
 
6.7%
1 1914
 
6.4%
7 1807
 
6.0%
9 1744
 
5.8%
8 1710
 
5.7%
4 1635
 
5.4%
Space Separator
ValueCountFrequency (%)
810
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30918
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6136
19.8%
2 5932
19.2%
6 4971
16.1%
3 2232
 
7.2%
5 2027
 
6.6%
1 1914
 
6.2%
7 1807
 
5.8%
9 1744
 
5.6%
8 1710
 
5.5%
4 1635
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30918
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6136
19.8%
2 5932
19.2%
6 4971
16.1%
3 2232
 
7.2%
5 2027
 
6.6%
1 1914
 
6.2%
7 1807
 
5.8%
9 1744
 
5.6%
8 1710
 
5.5%
4 1635
 
5.3%

소재지면적
Text

MISSING 

Distinct2622
Distinct (%)47.6%
Missing127
Missing (%)2.3%
Memory size44.2 KiB
2024-05-11T15:42:43.921496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.9061536
Min length3

Characters and Unicode

Total characters27028
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

Unique1930 ?
Unique (%)35.0%

Sample

1st row62.00
2nd row65.25
3rd row16.07
4th row74.16
5th row64.40
ValueCountFrequency (%)
3.30 449
 
8.2%
6.60 175
 
3.2%
33.00 113
 
2.1%
30.00 73
 
1.3%
10.00 60
 
1.1%
26.40 49
 
0.9%
9.90 46
 
0.8%
20.00 41
 
0.7%
25.00 37
 
0.7%
15.00 35
 
0.6%
Other values (2612) 4431
80.4%
2024-05-11T15:42:44.668173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5509
20.4%
0 4967
18.4%
3 2995
11.1%
2 2279
8.4%
1 2079
 
7.7%
6 1872
 
6.9%
4 1776
 
6.6%
5 1658
 
6.1%
8 1378
 
5.1%
9 1358
 
5.0%
Other values (2) 1157
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21518
79.6%
Other Punctuation 5510
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4967
23.1%
3 2995
13.9%
2 2279
10.6%
1 2079
9.7%
6 1872
 
8.7%
4 1776
 
8.3%
5 1658
 
7.7%
8 1378
 
6.4%
9 1358
 
6.3%
7 1156
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 5509
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 27028
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5509
20.4%
0 4967
18.4%
3 2995
11.1%
2 2279
8.4%
1 2079
 
7.7%
6 1872
 
6.9%
4 1776
 
6.6%
5 1658
 
6.1%
8 1378
 
5.1%
9 1358
 
5.0%
Other values (2) 1157
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27028
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5509
20.4%
0 4967
18.4%
3 2995
11.1%
2 2279
8.4%
1 2079
 
7.7%
6 1872
 
6.9%
4 1776
 
6.6%
5 1658
 
6.1%
8 1378
 
5.1%
9 1358
 
5.0%
Other values (2) 1157
 
4.3%
Distinct250
Distinct (%)4.4%
Missing1
Missing (%)< 0.1%
Memory size44.2 KiB
2024-05-11T15:42:45.093256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1872227
Min length6

Characters and Unicode

Total characters34865
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

Unique29 ?
Unique (%)0.5%

Sample

1st row157250
2nd row157853
3rd row157884
4th row157851
5th row157250
ValueCountFrequency (%)
157210 535
 
9.5%
157-210 313
 
5.6%
157930 267
 
4.7%
157220 181
 
3.2%
157840 149
 
2.6%
157280 130
 
2.3%
157846 100
 
1.8%
157884 97
 
1.7%
157928 82
 
1.5%
157918 81
 
1.4%
Other values (240) 3700
65.7%
2024-05-11T15:42:45.951711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7448
21.4%
7 6341
18.2%
5 6297
18.1%
8 3730
10.7%
0 3028
8.7%
2 2347
 
6.7%
9 1771
 
5.1%
3 1127
 
3.2%
- 1055
 
3.0%
4 999
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33810
97.0%
Dash Punctuation 1055
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7448
22.0%
7 6341
18.8%
5 6297
18.6%
8 3730
11.0%
0 3028
9.0%
2 2347
 
6.9%
9 1771
 
5.2%
3 1127
 
3.3%
4 999
 
3.0%
6 722
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 1055
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34865
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7448
21.4%
7 6341
18.2%
5 6297
18.1%
8 3730
10.7%
0 3028
8.7%
2 2347
 
6.7%
9 1771
 
5.1%
3 1127
 
3.2%
- 1055
 
3.0%
4 999
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34865
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7448
21.4%
7 6341
18.2%
5 6297
18.1%
8 3730
10.7%
0 3028
8.7%
2 2347
 
6.7%
9 1771
 
5.1%
3 1127
 
3.2%
- 1055
 
3.0%
4 999
 
2.9%
Distinct5063
Distinct (%)89.8%
Missing1
Missing (%)< 0.1%
Memory size44.2 KiB
2024-05-11T15:42:46.337016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length53
Mean length31.371961
Min length17

Characters and Unicode

Total characters176781
Distinct characters478
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4715 ?
Unique (%)83.7%

Sample

1st row서울특별시 강서구 과해동 48-27번지
2nd row서울특별시 강서구 방화동 620-50번지
3rd row서울특별시 강서구 화곡동 362-84번지
4th row서울특별시 강서구 방화동 598-146번지
5th row서울특별시 강서구 과해동 72-33번지
ValueCountFrequency (%)
서울특별시 5635
16.6%
강서구 5635
16.6%
1층 2493
 
7.3%
화곡동 1759
 
5.2%
지상 1592
 
4.7%
등촌동 861
 
2.5%
마곡동 848
 
2.5%
방화동 814
 
2.4%
내발산동 418
 
1.2%
가양동 344
 
1.0%
Other values (4926) 13522
39.9%
2024-05-11T15:42:46.848362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31401
 
17.8%
11572
 
6.5%
1 10025
 
5.7%
6280
 
3.6%
6197
 
3.5%
5904
 
3.3%
5821
 
3.3%
5708
 
3.2%
5646
 
3.2%
5638
 
3.2%
Other values (468) 82589
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 98984
56.0%
Decimal Number 35430
 
20.0%
Space Separator 31401
 
17.8%
Dash Punctuation 5177
 
2.9%
Close Punctuation 2333
 
1.3%
Open Punctuation 2332
 
1.3%
Uppercase Letter 519
 
0.3%
Other Punctuation 348
 
0.2%
Math Symbol 149
 
0.1%
Letter Number 73
 
< 0.1%
Other values (2) 35
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11572
 
11.7%
6280
 
6.3%
6197
 
6.3%
5904
 
6.0%
5821
 
5.9%
5708
 
5.8%
5646
 
5.7%
5638
 
5.7%
5635
 
5.7%
3559
 
3.6%
Other values (402) 37024
37.4%
Uppercase Letter
ValueCountFrequency (%)
B 135
26.0%
A 89
17.1%
C 52
 
10.0%
N 46
 
8.9%
G 33
 
6.4%
M 19
 
3.7%
S 19
 
3.7%
F 15
 
2.9%
K 13
 
2.5%
W 12
 
2.3%
Other values (16) 86
16.6%
Lowercase Letter
ValueCountFrequency (%)
e 8
23.5%
k 5
14.7%
s 4
11.8%
o 3
 
8.8%
n 3
 
8.8%
y 2
 
5.9%
a 2
 
5.9%
g 1
 
2.9%
b 1
 
2.9%
h 1
 
2.9%
Other values (4) 4
11.8%
Decimal Number
ValueCountFrequency (%)
1 10025
28.3%
0 3852
 
10.9%
2 3718
 
10.5%
7 3012
 
8.5%
6 2896
 
8.2%
3 2696
 
7.6%
4 2531
 
7.1%
8 2388
 
6.7%
9 2245
 
6.3%
5 2067
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 338
97.1%
. 4
 
1.1%
/ 2
 
0.6%
& 2
 
0.6%
@ 1
 
0.3%
' 1
 
0.3%
Letter Number
ValueCountFrequency (%)
42
57.5%
24
32.9%
5
 
6.8%
2
 
2.7%
Space Separator
ValueCountFrequency (%)
31401
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5177
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2333
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2332
100.0%
Math Symbol
ValueCountFrequency (%)
~ 149
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 98984
56.0%
Common 77171
43.7%
Latin 626
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11572
 
11.7%
6280
 
6.3%
6197
 
6.3%
5904
 
6.0%
5821
 
5.9%
5708
 
5.8%
5646
 
5.7%
5638
 
5.7%
5635
 
5.7%
3559
 
3.6%
Other values (402) 37024
37.4%
Latin
ValueCountFrequency (%)
B 135
21.6%
A 89
14.2%
C 52
 
8.3%
N 46
 
7.3%
42
 
6.7%
G 33
 
5.3%
24
 
3.8%
M 19
 
3.0%
S 19
 
3.0%
F 15
 
2.4%
Other values (34) 152
24.3%
Common
ValueCountFrequency (%)
31401
40.7%
1 10025
 
13.0%
- 5177
 
6.7%
0 3852
 
5.0%
2 3718
 
4.8%
7 3012
 
3.9%
6 2896
 
3.8%
3 2696
 
3.5%
4 2531
 
3.3%
8 2388
 
3.1%
Other values (12) 9475
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 98984
56.0%
ASCII 77724
44.0%
Number Forms 73
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31401
40.4%
1 10025
 
12.9%
- 5177
 
6.7%
0 3852
 
5.0%
2 3718
 
4.8%
7 3012
 
3.9%
6 2896
 
3.7%
3 2696
 
3.5%
4 2531
 
3.3%
8 2388
 
3.1%
Other values (52) 10028
 
12.9%
Hangul
ValueCountFrequency (%)
11572
 
11.7%
6280
 
6.3%
6197
 
6.3%
5904
 
6.0%
5821
 
5.9%
5708
 
5.8%
5646
 
5.7%
5638
 
5.7%
5635
 
5.7%
3559
 
3.6%
Other values (402) 37024
37.4%
Number Forms
ValueCountFrequency (%)
42
57.5%
24
32.9%
5
 
6.8%
2
 
2.7%

도로명주소
Text

MISSING 

Distinct3789
Distinct (%)88.5%
Missing1356
Missing (%)24.1%
Memory size44.2 KiB
2024-05-11T15:42:47.254718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length58
Mean length38.443458
Min length22

Characters and Unicode

Total characters164538
Distinct characters480
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3477 ?
Unique (%)81.2%

Sample

1st row서울특별시 강서구 방화동로 65, 지하 1층 (방화동, 2동)
2nd row서울특별시 강서구 방화동로 119 (방화동)
3rd row서울특별시 강서구 양천로 606 (등촌동)
4th row서울특별시 강서구 방화동로 92 (방화동)
5th row서울특별시 강서구 방화동로 49, 지하1층 (방화동, 1동)
ValueCountFrequency (%)
서울특별시 4280
 
13.1%
강서구 4280
 
13.1%
1층 3128
 
9.6%
화곡동 1138
 
3.5%
마곡동 842
 
2.6%
등촌동 629
 
1.9%
방화동 571
 
1.7%
1동 551
 
1.7%
양천로 396
 
1.2%
강서로 351
 
1.1%
Other values (2709) 16584
50.6%
2024-05-11T15:42:47.899716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28484
 
17.3%
9705
 
5.9%
1 9699
 
5.9%
, 6581
 
4.0%
6460
 
3.9%
5310
 
3.2%
) 4472
 
2.7%
( 4470
 
2.7%
4468
 
2.7%
4355
 
2.6%
Other values (470) 80534
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92341
56.1%
Space Separator 28484
 
17.3%
Decimal Number 26877
 
16.3%
Other Punctuation 6587
 
4.0%
Close Punctuation 4472
 
2.7%
Open Punctuation 4470
 
2.7%
Uppercase Letter 540
 
0.3%
Dash Punctuation 492
 
0.3%
Math Symbol 167
 
0.1%
Letter Number 73
 
< 0.1%
Other values (2) 35
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9705
 
10.5%
6460
 
7.0%
5310
 
5.8%
4468
 
4.8%
4355
 
4.7%
4291
 
4.6%
4285
 
4.6%
4280
 
4.6%
4134
 
4.5%
4099
 
4.4%
Other values (405) 40954
44.4%
Uppercase Letter
ValueCountFrequency (%)
B 150
27.8%
A 90
16.7%
C 52
 
9.6%
N 47
 
8.7%
G 31
 
5.7%
M 20
 
3.7%
F 19
 
3.5%
S 18
 
3.3%
Y 14
 
2.6%
X 14
 
2.6%
Other values (16) 85
15.7%
Lowercase Letter
ValueCountFrequency (%)
e 8
23.5%
k 4
11.8%
n 3
 
8.8%
o 3
 
8.8%
s 3
 
8.8%
y 2
 
5.9%
a 2
 
5.9%
g 2
 
5.9%
f 1
 
2.9%
m 1
 
2.9%
Other values (5) 5
14.7%
Decimal Number
ValueCountFrequency (%)
1 9699
36.1%
2 3169
 
11.8%
3 2528
 
9.4%
0 2466
 
9.2%
4 1992
 
7.4%
5 1813
 
6.7%
6 1710
 
6.4%
8 1249
 
4.6%
7 1240
 
4.6%
9 1011
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 6581
99.9%
. 3
 
< 0.1%
& 2
 
< 0.1%
' 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
42
57.5%
24
32.9%
5
 
6.8%
2
 
2.7%
Space Separator
ValueCountFrequency (%)
28484
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4472
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4470
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 492
100.0%
Math Symbol
ValueCountFrequency (%)
~ 167
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92340
56.1%
Common 71550
43.5%
Latin 647
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9705
 
10.5%
6460
 
7.0%
5310
 
5.8%
4468
 
4.8%
4355
 
4.7%
4291
 
4.6%
4285
 
4.6%
4280
 
4.6%
4134
 
4.5%
4099
 
4.4%
Other values (404) 40953
44.4%
Latin
ValueCountFrequency (%)
B 150
23.2%
A 90
13.9%
C 52
 
8.0%
N 47
 
7.3%
42
 
6.5%
G 31
 
4.8%
24
 
3.7%
M 20
 
3.1%
F 19
 
2.9%
S 18
 
2.8%
Other values (35) 154
23.8%
Common
ValueCountFrequency (%)
28484
39.8%
1 9699
 
13.6%
, 6581
 
9.2%
) 4472
 
6.3%
( 4470
 
6.2%
2 3169
 
4.4%
3 2528
 
3.5%
0 2466
 
3.4%
4 1992
 
2.8%
5 1813
 
2.5%
Other values (10) 5876
 
8.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92339
56.1%
ASCII 72124
43.8%
Number Forms 73
 
< 0.1%
Compat Jamo 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28484
39.5%
1 9699
 
13.4%
, 6581
 
9.1%
) 4472
 
6.2%
( 4470
 
6.2%
2 3169
 
4.4%
3 2528
 
3.5%
0 2466
 
3.4%
4 1992
 
2.8%
5 1813
 
2.5%
Other values (51) 6450
 
8.9%
Hangul
ValueCountFrequency (%)
9705
 
10.5%
6460
 
7.0%
5310
 
5.8%
4468
 
4.8%
4355
 
4.7%
4291
 
4.6%
4285
 
4.6%
4280
 
4.6%
4134
 
4.5%
4099
 
4.4%
Other values (403) 40952
44.3%
Number Forms
ValueCountFrequency (%)
42
57.5%
24
32.9%
5
 
6.8%
2
 
2.7%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct285
Distinct (%)6.7%
Missing1390
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean7656.4211
Minimum7502
Maximum7811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.7 KiB
2024-05-11T15:42:48.096945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7502
5-th percentile7505
Q17571
median7639
Q37752
95-th percentile7803
Maximum7811
Range309
Interquartile range (IQR)181

Descriptive statistics

Standard deviation98.950699
Coefficient of variation (CV)0.012923884
Kurtosis-1.3387053
Mean7656.4211
Median Absolute Deviation (MAD)85
Skewness0.081843355
Sum32509164
Variance9791.2408
MonotonicityNot monotonic
2024-05-11T15:42:48.303714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7505 242
 
4.3%
7788 135
 
2.4%
7803 114
 
2.0%
7802 81
 
1.4%
7639 73
 
1.3%
7567 68
 
1.2%
7532 67
 
1.2%
7631 63
 
1.1%
7807 56
 
1.0%
7584 56
 
1.0%
Other values (275) 3291
58.4%
(Missing) 1390
24.7%
ValueCountFrequency (%)
7502 2
 
< 0.1%
7503 3
 
0.1%
7504 5
 
0.1%
7505 242
4.3%
7506 6
 
0.1%
7508 2
 
< 0.1%
7509 8
 
0.1%
7510 35
 
0.6%
7511 17
 
0.3%
7512 3
 
0.1%
ValueCountFrequency (%)
7811 1
 
< 0.1%
7809 2
 
< 0.1%
7808 16
 
0.3%
7807 56
1.0%
7806 49
0.9%
7805 5
 
0.1%
7804 15
 
0.3%
7803 114
2.0%
7802 81
1.4%
7801 55
1.0%
Distinct5230
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
2024-05-11T15:42:48.696249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length29
Mean length7.9006388
Min length1

Characters and Unicode

Total characters44528
Distinct characters928
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4934 ?
Unique (%)87.5%

Sample

1st row다린
2nd row코보다방
3rd row
4th row샘다방
5th row
ValueCountFrequency (%)
씨유 139
 
1.7%
세븐일레븐 124
 
1.5%
카페 105
 
1.3%
마곡점 70
 
0.9%
지에스25 65
 
0.8%
gs25 62
 
0.8%
커피 49
 
0.6%
coffee 43
 
0.5%
화곡점 37
 
0.5%
메가엠지씨커피 33
 
0.4%
Other values (5451) 7457
91.1%
2024-05-11T15:42:49.171122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2550
 
5.7%
1981
 
4.4%
1316
 
3.0%
934
 
2.1%
890
 
2.0%
733
 
1.6%
) 728
 
1.6%
( 713
 
1.6%
675
 
1.5%
647
 
1.5%
Other values (918) 33361
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35326
79.3%
Space Separator 2550
 
5.7%
Uppercase Letter 2077
 
4.7%
Lowercase Letter 1890
 
4.2%
Decimal Number 1072
 
2.4%
Close Punctuation 731
 
1.6%
Open Punctuation 716
 
1.6%
Other Punctuation 144
 
0.3%
Dash Punctuation 15
 
< 0.1%
Math Symbol 4
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1981
 
5.6%
1316
 
3.7%
934
 
2.6%
890
 
2.5%
733
 
2.1%
675
 
1.9%
647
 
1.8%
626
 
1.8%
560
 
1.6%
497
 
1.4%
Other values (832) 26467
74.9%
Lowercase Letter
ValueCountFrequency (%)
e 341
18.0%
a 199
10.5%
o 162
 
8.6%
f 157
 
8.3%
n 118
 
6.2%
r 103
 
5.4%
i 103
 
5.4%
c 100
 
5.3%
t 93
 
4.9%
s 74
 
3.9%
Other values (16) 440
23.3%
Uppercase Letter
ValueCountFrequency (%)
C 278
13.4%
S 242
11.7%
G 187
 
9.0%
E 167
 
8.0%
P 116
 
5.6%
O 115
 
5.5%
A 110
 
5.3%
F 105
 
5.1%
T 97
 
4.7%
N 83
 
4.0%
Other values (15) 577
27.8%
Other Punctuation
ValueCountFrequency (%)
& 43
29.9%
. 27
18.8%
' 23
16.0%
, 22
15.3%
? 15
 
10.4%
/ 6
 
4.2%
: 3
 
2.1%
# 2
 
1.4%
1
 
0.7%
1
 
0.7%
Decimal Number
ValueCountFrequency (%)
2 357
33.3%
5 280
26.1%
1 90
 
8.4%
9 87
 
8.1%
3 62
 
5.8%
4 58
 
5.4%
0 56
 
5.2%
8 41
 
3.8%
7 23
 
2.1%
6 18
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 728
99.6%
] 2
 
0.3%
1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 713
99.6%
[ 2
 
0.3%
1
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 2
50.0%
< 1
25.0%
> 1
25.0%
Space Separator
ValueCountFrequency (%)
2550
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35317
79.3%
Common 5235
 
11.8%
Latin 3967
 
8.9%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1981
 
5.6%
1316
 
3.7%
934
 
2.6%
890
 
2.5%
733
 
2.1%
675
 
1.9%
647
 
1.8%
626
 
1.8%
560
 
1.6%
497
 
1.4%
Other values (823) 26458
74.9%
Latin
ValueCountFrequency (%)
e 341
 
8.6%
C 278
 
7.0%
S 242
 
6.1%
a 199
 
5.0%
G 187
 
4.7%
E 167
 
4.2%
o 162
 
4.1%
f 157
 
4.0%
n 118
 
3.0%
P 116
 
2.9%
Other values (41) 2000
50.4%
Common
ValueCountFrequency (%)
2550
48.7%
) 728
 
13.9%
( 713
 
13.6%
2 357
 
6.8%
5 280
 
5.3%
1 90
 
1.7%
9 87
 
1.7%
3 62
 
1.2%
4 58
 
1.1%
0 56
 
1.1%
Other values (25) 254
 
4.9%
Han
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35313
79.3%
ASCII 9197
 
20.7%
CJK 9
 
< 0.1%
None 5
 
< 0.1%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2550
27.7%
) 728
 
7.9%
( 713
 
7.8%
2 357
 
3.9%
e 341
 
3.7%
5 280
 
3.0%
C 278
 
3.0%
S 242
 
2.6%
a 199
 
2.2%
G 187
 
2.0%
Other values (71) 3322
36.1%
Hangul
ValueCountFrequency (%)
1981
 
5.6%
1316
 
3.7%
934
 
2.6%
890
 
2.5%
733
 
2.1%
675
 
1.9%
647
 
1.8%
626
 
1.8%
560
 
1.6%
497
 
1.4%
Other values (820) 26454
74.9%
Compat Jamo
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
CJK
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
None
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
° 1
20.0%
Distinct4963
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
Minimum1999-07-05 00:00:00
Maximum2024-05-09 15:21:09
2024-05-11T15:42:49.343822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:49.520166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
I
3210 
U
2426 

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 3210
57.0%
U 2426
43.0%

Length

2024-05-11T15:42:50.083435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:50.212629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3210
57.0%
u 2426
43.0%
Distinct1284
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:42:50.358293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:50.540697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
커피숍
2074 
일반조리판매
1050 
편의점
592 
기타 휴게음식점
519 
과자점
468 
Other values (12)
933 

Length

Max length8
Median length3
Mean length4.126863
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 2074
36.8%
일반조리판매 1050
18.6%
편의점 592
 
10.5%
기타 휴게음식점 519
 
9.2%
과자점 468
 
8.3%
패스트푸드 425
 
7.5%
다방 366
 
6.5%
아이스크림 34
 
0.6%
키즈카페 21
 
0.4%
공항 18
 
0.3%
Other values (7) 69
 
1.2%

Length

2024-05-11T15:42:50.772944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 2074
33.7%
일반조리판매 1050
17.1%
편의점 592
 
9.6%
기타 519
 
8.4%
휴게음식점 519
 
8.4%
과자점 468
 
7.6%
패스트푸드 425
 
6.9%
다방 366
 
5.9%
아이스크림 34
 
0.6%
키즈카페 21
 
0.3%
Other values (8) 87
 
1.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2395
Distinct (%)45.1%
Missing331
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean185689.76
Minimum181881.23
Maximum189200.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.7 KiB
2024-05-11T15:42:50.992487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum181881.23
5-th percentile182860.66
Q1184623.2
median185821
Q3186805.8
95-th percentile188012.26
Maximum189200.15
Range7318.9131
Interquartile range (IQR)2182.6058

Descriptive statistics

Standard deviation1618.8386
Coefficient of variation (CV)0.0087179748
Kurtosis-0.65114999
Mean185689.76
Median Absolute Deviation (MAD)1078.2376
Skewness-0.31826213
Sum9.8508418 × 108
Variance2620638.6
MonotonicityNot monotonic
2024-05-11T15:42:51.234331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
182524.823835629 191
 
3.4%
187119.948165892 87
 
1.5%
187761.194273879 63
 
1.1%
186687.131804431 59
 
1.0%
185824.428508883 54
 
1.0%
182974.850127567 35
 
0.6%
186501.233192961 28
 
0.5%
187952.560027898 24
 
0.4%
186786.622461585 23
 
0.4%
186966.036176588 23
 
0.4%
Other values (2385) 4718
83.7%
(Missing) 331
 
5.9%
ValueCountFrequency (%)
181881.234660314 5
 
0.1%
182086.388313239 2
 
< 0.1%
182141.205465089 21
0.4%
182154.410343287 2
 
< 0.1%
182193.232383262 1
 
< 0.1%
182289.835592654 3
 
0.1%
182293.357671337 2
 
< 0.1%
182364.55474538 1
 
< 0.1%
182479.713774504 1
 
< 0.1%
182482.786036202 1
 
< 0.1%
ValueCountFrequency (%)
189200.147733153 1
 
< 0.1%
189172.250232972 1
 
< 0.1%
189152.269637156 1
 
< 0.1%
189145.455894355 1
 
< 0.1%
189124.441211963 2
 
< 0.1%
189105.201587182 2
 
< 0.1%
189102.277524848 1
 
< 0.1%
189098.806779959 8
0.1%
189066.642961645 1
 
< 0.1%
189037.964421932 2
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2389
Distinct (%)45.0%
Missing331
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean450199.44
Minimum447239.55
Maximum455223.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.7 KiB
2024-05-11T15:42:51.473707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447239.55
5-th percentile447712.72
Q1449171.6
median450446.74
Q3451299.05
95-th percentile452247.39
Maximum455223.86
Range7984.3025
Interquartile range (IQR)2127.4502

Descriptive statistics

Standard deviation1417.562
Coefficient of variation (CV)0.0031487422
Kurtosis-0.71925846
Mean450199.44
Median Absolute Deviation (MAD)991.50924
Skewness-0.3284433
Sum2.388308 × 109
Variance2009481.9
MonotonicityNot monotonic
2024-05-11T15:42:51.743515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451438.25089679 191
 
3.4%
450691.593173724 87
 
1.5%
450640.214509068 63
 
1.1%
451342.773451086 59
 
1.0%
450866.252126246 54
 
1.0%
450419.684560487 35
 
0.6%
451485.251875922 28
 
0.5%
450562.020225978 24
 
0.4%
450297.70265223 23
 
0.4%
451047.287263879 23
 
0.4%
Other values (2379) 4718
83.7%
(Missing) 331
 
5.9%
ValueCountFrequency (%)
447239.554007375 1
 
< 0.1%
447293.252713899 1
 
< 0.1%
447297.791614934 1
 
< 0.1%
447316.214981355 1
 
< 0.1%
447324.010715124 1
 
< 0.1%
447326.774511162 1
 
< 0.1%
447329.136662979 1
 
< 0.1%
447332.105309799 1
 
< 0.1%
447359.949619626 4
0.1%
447360.27075665 4
0.1%
ValueCountFrequency (%)
455223.856535527 3
0.1%
454178.034489148 1
 
< 0.1%
453877.559518012 1
 
< 0.1%
453626.099540967 1
 
< 0.1%
453468.096258454 2
 
< 0.1%
453178.305694113 4
0.1%
453175.087759747 1
 
< 0.1%
453174.899157458 5
0.1%
453050.733807442 4
0.1%
453018.037256925 3
0.1%

위생업태명
Categorical

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
1547 
커피숍
1211 
일반조리판매
851 
과자점
467 
편의점
386 
Other values (12)
1174 

Length

Max length8
Median length6
Mean length4.1130234
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1547
27.4%
커피숍 1211
21.5%
일반조리판매 851
15.1%
과자점 467
 
8.3%
편의점 386
 
6.8%
패스트푸드 370
 
6.6%
다방 362
 
6.4%
기타 휴게음식점 343
 
6.1%
아이스크림 21
 
0.4%
공항 18
 
0.3%
Other values (7) 60
 
1.1%

Length

2024-05-11T15:42:51.999636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1547
25.9%
커피숍 1211
20.3%
일반조리판매 851
14.2%
과자점 467
 
7.8%
편의점 386
 
6.5%
패스트푸드 370
 
6.2%
다방 362
 
6.1%
기타 343
 
5.7%
휴게음식점 343
 
5.7%
아이스크림 21
 
0.4%
Other values (8) 78
 
1.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.8%
Missing4182
Missing (%)74.2%
Infinite0
Infinite (%)0.0%
Mean0.38651994
Minimum0
Maximum13
Zeros1097
Zeros (%)19.5%
Negative0
Negative (%)0.0%
Memory size49.7 KiB
2024-05-11T15:42:52.220491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.97694546
Coefficient of variation (CV)2.5275422
Kurtosis57.438162
Mean0.38651994
Median Absolute Deviation (MAD)0
Skewness6.0120807
Sum562
Variance0.95442243
MonotonicityNot monotonic
2024-05-11T15:42:52.490885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 1097
 
19.5%
1 252
 
4.5%
2 65
 
1.2%
3 21
 
0.4%
4 10
 
0.2%
5 2
 
< 0.1%
6 2
 
< 0.1%
12 2
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 4182
74.2%
ValueCountFrequency (%)
0 1097
19.5%
1 252
 
4.5%
2 65
 
1.2%
3 21
 
0.4%
4 10
 
0.2%
5 2
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
12 2
 
< 0.1%
ValueCountFrequency (%)
13 1
 
< 0.1%
12 2
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
4 10
 
0.2%
3 21
 
0.4%
2 65
 
1.2%
1 252
4.5%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)0.9%
Missing4146
Missing (%)73.6%
Infinite0
Infinite (%)0.0%
Mean1.0241611
Minimum0
Maximum20
Zeros736
Zeros (%)13.1%
Negative0
Negative (%)0.0%
Memory size49.7 KiB
2024-05-11T15:42:52.683180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5060055
Coefficient of variation (CV)1.4704772
Kurtosis32.240103
Mean1.0241611
Median Absolute Deviation (MAD)1
Skewness3.9268765
Sum1526
Variance2.2680525
MonotonicityNot monotonic
2024-05-11T15:42:52.903556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 736
 
13.1%
1 332
 
5.9%
2 221
 
3.9%
3 148
 
2.6%
4 32
 
0.6%
5 5
 
0.1%
6 4
 
0.1%
7 3
 
0.1%
10 3
 
0.1%
9 2
 
< 0.1%
Other values (4) 4
 
0.1%
(Missing) 4146
73.6%
ValueCountFrequency (%)
0 736
13.1%
1 332
5.9%
2 221
 
3.9%
3 148
 
2.6%
4 32
 
0.6%
5 5
 
0.1%
6 4
 
0.1%
7 3
 
0.1%
9 2
 
< 0.1%
10 3
 
0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
11 1
 
< 0.1%
10 3
 
0.1%
9 2
 
< 0.1%
7 3
 
0.1%
6 4
 
0.1%
5 5
 
0.1%
4 32
0.6%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
4651 
주택가주변
533 
기타
 
320
아파트지역
 
81
유흥업소밀집지역
 
37
Other values (3)
 
14

Length

Max length8
Median length4
Mean length4.0306955
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4651
82.5%
주택가주변 533
 
9.5%
기타 320
 
5.7%
아파트지역 81
 
1.4%
유흥업소밀집지역 37
 
0.7%
학교정화(상대) 5
 
0.1%
결혼예식장주변 5
 
0.1%
학교정화(절대) 4
 
0.1%

Length

2024-05-11T15:42:53.111508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:53.285921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4651
82.5%
주택가주변 533
 
9.5%
기타 320
 
5.7%
아파트지역 81
 
1.4%
유흥업소밀집지역 37
 
0.7%
학교정화(상대 5
 
0.1%
결혼예식장주변 5
 
0.1%
학교정화(절대 4
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
4633 
기타
 
400
지도
 
251
자율
 
197
 
80
Other values (2)
 
75

Length

Max length4
Median length4
Mean length3.6199432
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4633
82.2%
기타 400
 
7.1%
지도 251
 
4.5%
자율 197
 
3.5%
80
 
1.4%
56
 
1.0%
우수 19
 
0.3%

Length

2024-05-11T15:42:53.495505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:53.668104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4633
82.2%
기타 400
 
7.1%
지도 251
 
4.5%
자율 197
 
3.5%
80
 
1.4%
56
 
1.0%
우수 19
 
0.3%

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
상수도전용
3236 
<NA>
2367 
지하수전용
 
27
상수도(음용)지하수(주방용)겸용
 
5
간이상수도
 
1

Length

Max length17
Median length5
Mean length4.5906671
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 3236
57.4%
<NA> 2367
42.0%
지하수전용 27
 
0.5%
상수도(음용)지하수(주방용)겸용 5
 
0.1%
간이상수도 1
 
< 0.1%

Length

2024-05-11T15:42:53.856445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:54.002934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 3236
57.4%
na 2367
42.0%
지하수전용 27
 
0.5%
상수도(음용)지하수(주방용)겸용 5
 
0.1%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
5268 
0
 
368

Length

Max length4
Median length4
Mean length3.8041164
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> 5268
93.5%
0 368
 
6.5%

Length

2024-05-11T15:42:54.176269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:54.292005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5268
93.5%
0 368
 
6.5%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
5258 
0
 
378

Length

Max length4
Median length4
Mean length3.7987935
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> 5258
93.3%
0 378
 
6.7%

Length

2024-05-11T15:42:54.431427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:54.614847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5258
93.3%
0 378
 
6.7%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
5258 
0
 
378

Length

Max length4
Median length4
Mean length3.7987935
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> 5258
93.3%
0 378
 
6.7%

Length

2024-05-11T15:42:54.758134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:54.866808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5258
93.3%
0 378
 
6.7%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
5258 
0
 
378

Length

Max length4
Median length4
Mean length3.7987935
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> 5258
93.3%
0 378
 
6.7%

Length

2024-05-11T15:42:55.009051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:55.154691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5258
93.3%
0 378
 
6.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
5258 
0
 
378

Length

Max length4
Median length4
Mean length3.7987935
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> 5258
93.3%
0 378
 
6.7%

Length

2024-05-11T15:42:55.306301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:55.439805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5258
93.3%
0 378
 
6.7%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5636
Missing (%)100.0%
Memory size49.7 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
5258 
0
 
378

Length

Max length4
Median length4
Mean length3.7987935
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> 5258
93.3%
0 378
 
6.7%

Length

2024-05-11T15:42:55.569011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:55.698650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5258
93.3%
0 378
 
6.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
<NA>
5258 
0
 
378

Length

Max length4
Median length4
Mean length3.7987935
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> 5258
93.3%
0 378
 
6.7%

Length

2024-05-11T15:42:55.820239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:55.956916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5258
93.3%
0 378
 
6.7%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1547
Missing (%)27.4%
Memory size11.1 KiB
False
4052 
True
 
37
(Missing)
1547 
ValueCountFrequency (%)
False 4052
71.9%
True 37
 
0.7%
(Missing) 1547
 
27.4%
2024-05-11T15:42:56.066756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct2119
Distinct (%)51.8%
Missing1547
Missing (%)27.4%
Infinite0
Infinite (%)0.0%
Mean70.635559
Minimum0
Maximum111010.51
Zeros108
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size49.7 KiB
2024-05-11T15:42:56.217738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q114
median30
Q356.18
95-th percentile130.384
Maximum111010.51
Range111010.51
Interquartile range (IQR)42.18

Descriptive statistics

Standard deviation1735.9566
Coefficient of variation (CV)24.576242
Kurtosis4083.2182
Mean70.635559
Median Absolute Deviation (MAD)20
Skewness63.877529
Sum288828.8
Variance3013545.2
MonotonicityNot monotonic
2024-05-11T15:42:56.421795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 294
 
5.2%
6.6 118
 
2.1%
0.0 108
 
1.9%
33.0 79
 
1.4%
10.0 46
 
0.8%
26.4 41
 
0.7%
30.0 39
 
0.7%
9.9 36
 
0.6%
25.0 29
 
0.5%
16.5 29
 
0.5%
Other values (2109) 3270
58.0%
(Missing) 1547
27.4%
ValueCountFrequency (%)
0.0 108
1.9%
0.49 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 1
 
< 0.1%
1.3 1
 
< 0.1%
1.5 3
 
0.1%
1.89 1
 
< 0.1%
1.9 1
 
< 0.1%
2.0 7
 
0.1%
2.2 1
 
< 0.1%
ValueCountFrequency (%)
111010.51 1
< 0.1%
414.71 1
< 0.1%
387.0 1
< 0.1%
363.0 1
< 0.1%
355.77 1
< 0.1%
345.12 1
< 0.1%
341.89 1
< 0.1%
339.49 1
< 0.1%
330.22 1
< 0.1%
324.53 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5636
Missing (%)100.0%
Memory size49.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5636
Missing (%)100.0%
Memory size49.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5636
Missing (%)100.0%
Memory size49.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031500003150000-104-1966-0723519661028<NA>3폐업2폐업19941226<NA><NA><NA>020605474462.00157250서울특별시 강서구 과해동 48-27번지<NA><NA>다린2002-07-30 00:00:00I2018-08-31 23:59:59.0과자점<NA><NA>과자점03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N62.0<NA><NA><NA>
131500003150000-104-1970-0714319701119<NA>3폐업2폐업19900807<NA><NA><NA>020664526665.25157853서울특별시 강서구 방화동 620-50번지<NA><NA>코보다방2002-07-30 00:00:00I2018-08-31 23:59:59.0과자점182974.746871451121.648101과자점02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N65.25<NA><NA><NA>
231500003150000-104-1970-0716919700216<NA>3폐업2폐업20000306<NA><NA><NA>020662078616.07157884서울특별시 강서구 화곡동 362-84번지<NA><NA>2001-09-28 00:00:00I2018-08-31 23:59:59.0다방185642.804833448020.429847다방13주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.07<NA><NA><NA>
331500003150000-104-1971-0715219711123<NA>3폐업2폐업20021007<NA><NA><NA>02 664737774.16157851서울특별시 강서구 방화동 598-146번지<NA><NA>샘다방2000-07-21 00:00:00I2018-08-31 23:59:59.0다방183375.296606451710.62201다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N74.16<NA><NA><NA>
431500003150000-104-1971-0720119711209<NA>3폐업2폐업19900219<NA><NA><NA>020605331764.40157250서울특별시 강서구 과해동 72-33번지<NA><NA>2002-07-30 00:00:00I2018-08-31 23:59:59.0과자점<NA><NA>과자점02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N64.4<NA><NA><NA>
531500003150000-104-1972-0697319720323<NA>3폐업2폐업19981024<NA><NA><NA>02 554566519.35157822서울특별시 강서구 과해동 274번지<NA><NA>국내선B스넥2002-07-30 00:00:00I2018-08-31 23:59:59.0과자점<NA><NA>과자점11기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N19.35<NA><NA><NA>
631500003150000-104-1972-0724219720126<NA>3폐업2폐업19910105<NA><NA><NA>0206022851103.35157871서울특별시 강서구 화곡동 98-60번지<NA><NA>화성2002-07-30 00:00:00I2018-08-31 23:59:59.0과자점186156.556156448925.225988과자점04주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N103.35<NA><NA><NA>
731500003150000-104-1973-0717819730728<NA>3폐업2폐업19910212<NA><NA><NA>0206620990100.10157852서울특별시 강서구 방화동 609-38번지<NA><NA>수정2002-07-30 00:00:00I2018-08-31 23:59:59.0과자점183305.351014451440.599238과자점02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N100.1<NA><NA><NA>
831500003150000-104-1975-0006019750215<NA>3폐업2폐업19901101<NA><NA><NA>0206022564103.80157884서울특별시 강서구 화곡동 370-103번지<NA><NA>한일2002-07-29 00:00:00I2018-08-31 23:59:59.0과자점185623.258753448056.909742과자점02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N103.8<NA><NA><NA>
931500003150000-104-1975-0850919750313<NA>3폐업2폐업19990910<NA><NA><NA>02 6521318125.08157863서울특별시 강서구 염창동 275-1번지<NA><NA>화천2010-07-08 15:32:08I2018-08-31 23:59:59.0다방188222.331439449759.066577다방03주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N125.08<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
562631500003150000-104-2024-000962024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>47.95157-210서울특별시 강서구 마곡동 773-2 마곡지엠지타워서울특별시 강서구 마곡중앙6로 16, 마곡지엠지타워 1층 109호 (마곡동)7801메가엠지씨커피 마곡GMG타워점2024-04-23 14:53:04I2023-12-03 22:05:00.0커피숍184824.275824450916.757856<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
562731500003150000-104-2024-000972024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>44.84157-210서울특별시 강서구 마곡동 774-12 마커스빌딩서울특별시 강서구 마곡동로 55, 마커스빌딩 1층 102 일부호 (마곡동)7802블루샥 마곡점2024-04-24 09:38:23I2023-12-03 22:06:00.0커피숍185177.843493450877.710686<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
562831500003150000-104-2024-000982024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA>0707797626230.00157-829서울특별시 강서구 내발산동 678-11서울특별시 강서구 공항대로36길 129, 1층 일부호 (내발산동)7632빠인파인2024-04-25 14:19:41I2023-12-03 22:07:00.0커피숍185418.868989450071.0306<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
562931500003150000-104-2024-000992024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.00157-280서울특별시 강서구 내발산동 675-14서울특별시 강서구 우장산로6길 80, 1층 일부호 (내발산동)7681마이요거트립 우장산점2024-04-26 15:30:49I2023-12-03 22:08:00.0일반조리판매185569.653333450124.593453<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
563031500003150000-104-2024-001002024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA>023773111474.69157-210서울특별시 강서구 마곡동 812 LG아트센터 서울 및 LG디스커버리랩 서울서울특별시 강서구 마곡중앙로 136, LG아트센터 서울 및 LG디스커버리랩 서울 1층 (마곡동)7789코펠라 아트센터2호점2024-04-26 16:07:52I2023-12-03 22:08:00.0커피숍185118.204839451739.731418<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
563131500003150000-104-2024-001012024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30157-930서울특별시 강서구 등촌동 689 NC 강서점서울특별시 강서구 강서로56길 17, NC 강서점 지하 1층 (등촌동)7584족발요리집 NC강서점2024-04-30 16:31:09I2023-12-05 00:02:00.0일반조리판매185824.428509450866.252126<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
563231500003150000-104-2024-001022024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.59157-840서울특별시 강서구 등촌동 639-11 홈플러스강서점앤본사사옥 2층서울특별시 강서구 화곡로 398, 홈플러스강서점앤본사사옥 2층 (등촌동)7567돈가스분식2024-05-01 16:44:21I2023-12-05 00:03:00.0일반조리판매187119.948166450691.593174<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
563331500003150000-104-2024-001032024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.60157-861서울특별시 강서구 염창동 244-15 세우빌딩 1층 8호서울특별시 강서구 양천로69길 19, 세우빌딩 1층 8호 (염창동)7544GS25 염창빌리지점2024-05-07 11:24:23I2023-12-05 00:09:00.0편의점188508.502581450136.973259<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
563431500003150000-104-2024-001042024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>206.87157-210서울특별시 강서구 마곡동 793-7 매그넘793 1층 101,102,103,104호서울특별시 강서구 강서로 401, 매그넘793 1층 101,102,103,104호 (마곡동)7794투썸플레이스 강서발산점2024-05-08 11:34:10I2023-12-04 23:00:00.0커피숍185685.044366451042.187907<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
563531500003150000-104-2024-001052024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>157-210서울특별시 강서구 마곡동 811-5 마곡어울림공원서울특별시 강서구 양천로 291, 마곡어울림공원 (마곡동)7520티오르카페2024-05-09 13:25:26I2023-12-04 23:01:00.0커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>