Overview

Dataset statistics

Number of variables44
Number of observations426
Missing cells3766
Missing cells (%)20.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory156.1 KiB
Average record size in memory375.3 B

Variable types

Categorical22
Text7
DateTime4
Unsupported7
Numeric3
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-18192/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (76.0%)Imbalance
여성종사자수 is highly imbalanced (80.4%)Imbalance
영업장주변구분명 is highly imbalanced (81.7%)Imbalance
등급구분명 is highly imbalanced (77.6%)Imbalance
급수시설구분명 is highly imbalanced (59.6%)Imbalance
총인원 is highly imbalanced (80.3%)Imbalance
보증액 is highly imbalanced (79.4%)Imbalance
월세액 is highly imbalanced (83.5%)Imbalance
시설총규모 is highly imbalanced (75.2%)Imbalance
인허가취소일자 has 426 (100.0%) missing valuesMissing
폐업일자 has 93 (21.8%) missing valuesMissing
휴업시작일자 has 426 (100.0%) missing valuesMissing
휴업종료일자 has 426 (100.0%) missing valuesMissing
재개업일자 has 426 (100.0%) missing valuesMissing
전화번호 has 124 (29.1%) missing valuesMissing
소재지면적 has 100 (23.5%) missing valuesMissing
도로명주소 has 186 (43.7%) missing valuesMissing
도로명우편번호 has 187 (43.9%) missing valuesMissing
좌표정보(X) has 20 (4.7%) missing valuesMissing
좌표정보(Y) has 20 (4.7%) missing valuesMissing
다중이용업소여부 has 54 (12.7%) missing valuesMissing
전통업소지정번호 has 426 (100.0%) missing valuesMissing
전통업소주된음식 has 426 (100.0%) missing valuesMissing
홈페이지 has 426 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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

Reproduction

Analysis started2024-05-11 01:45:36.106030
Analysis finished2024-05-11 01:45:38.431050
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
3150000
426 

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 426
100.0%

Length

2024-05-11T01:45:38.646524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:39.093933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 426
100.0%

관리번호
Text

UNIQUE 

Distinct426
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-05-11T01:45:39.736532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters9372
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

Unique426 ?
Unique (%)100.0%

Sample

1st row3150000-109-1987-00712
2nd row3150000-109-1990-00009
3rd row3150000-109-1992-00010
4th row3150000-109-1995-00713
5th row3150000-109-1996-00011
ValueCountFrequency (%)
3150000-109-1987-00712 1
 
0.2%
3150000-109-2013-00007 1
 
0.2%
3150000-109-2013-00005 1
 
0.2%
3150000-109-2013-00004 1
 
0.2%
3150000-109-2013-00003 1
 
0.2%
3150000-109-2013-00002 1
 
0.2%
3150000-109-2013-00001 1
 
0.2%
3150000-109-2012-00015 1
 
0.2%
3150000-109-2012-00014 1
 
0.2%
3150000-109-2012-00013 1
 
0.2%
Other values (416) 416
97.7%
2024-05-11T01:45:40.968737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4234
45.2%
- 1278
 
13.6%
1 1267
 
13.5%
2 587
 
6.3%
9 584
 
6.2%
3 557
 
5.9%
5 513
 
5.5%
7 107
 
1.1%
4 95
 
1.0%
6 81
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8094
86.4%
Dash Punctuation 1278
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4234
52.3%
1 1267
 
15.7%
2 587
 
7.3%
9 584
 
7.2%
3 557
 
6.9%
5 513
 
6.3%
7 107
 
1.3%
4 95
 
1.2%
6 81
 
1.0%
8 69
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1278
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9372
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4234
45.2%
- 1278
 
13.6%
1 1267
 
13.5%
2 587
 
6.3%
9 584
 
6.2%
3 557
 
5.9%
5 513
 
5.5%
7 107
 
1.1%
4 95
 
1.0%
6 81
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4234
45.2%
- 1278
 
13.6%
1 1267
 
13.5%
2 587
 
6.3%
9 584
 
6.2%
3 557
 
5.9%
5 513
 
5.5%
7 107
 
1.1%
4 95
 
1.0%
6 81
 
0.9%
Distinct382
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum1987-03-18 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T01:45:41.541759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:45:42.250323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing426
Missing (%)100.0%
Memory size3.9 KiB
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
3
333 
1
93 

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 (%)
3 333
78.2%
1 93
 
21.8%

Length

2024-05-11T01:45:42.723500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:43.217113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 333
78.2%
1 93
 
21.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
폐업
333 
영업/정상
93 

Length

Max length5
Median length2
Mean length2.6549296
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 333
78.2%
영업/정상 93
 
21.8%

Length

2024-05-11T01:45:43.716270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:44.068300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 333
78.2%
영업/정상 93
 
21.8%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2
333 
1
93 

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 (%)
2 333
78.2%
1 93
 
21.8%

Length

2024-05-11T01:45:44.546357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:45.010958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 333
78.2%
1 93
 
21.8%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
폐업
333 
영업
93 

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 333
78.2%
영업 93
 
21.8%

Length

2024-05-11T01:45:45.580678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:45:46.058675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 333
78.2%
영업 93
 
21.8%

폐업일자
Date

MISSING 

Distinct285
Distinct (%)85.6%
Missing93
Missing (%)21.8%
Memory size3.5 KiB
Minimum1997-05-26 00:00:00
Maximum2024-04-16 00:00:00
2024-05-11T01:45:46.692201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:45:47.352074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing426
Missing (%)100.0%
Memory size3.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing426
Missing (%)100.0%
Memory size3.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing426
Missing (%)100.0%
Memory size3.9 KiB

전화번호
Text

MISSING 

Distinct293
Distinct (%)97.0%
Missing124
Missing (%)29.1%
Memory size3.5 KiB
2024-05-11T01:45:48.224268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9966887
Min length2

Characters and Unicode

Total characters3019
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

Unique284 ?
Unique (%)94.0%

Sample

1st row02 6595907
2nd row02 6468511
3rd row0226613277
4th row0226060101
5th row0236630967
ValueCountFrequency (%)
02 84
 
20.8%
070 4
 
1.0%
0226641838 2
 
0.5%
0226629858 2
 
0.5%
0505 2
 
0.5%
031 2
 
0.5%
0226444222 2
 
0.5%
0221011234 2
 
0.5%
21011234 2
 
0.5%
26699385 2
 
0.5%
Other values (298) 300
74.3%
2024-05-11T01:45:49.847682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 587
19.4%
6 531
17.6%
0 488
16.2%
3 215
 
7.1%
1 196
 
6.5%
7 190
 
6.3%
5 188
 
6.2%
4 168
 
5.6%
8 166
 
5.5%
9 160
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2889
95.7%
Space Separator 130
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 587
20.3%
6 531
18.4%
0 488
16.9%
3 215
 
7.4%
1 196
 
6.8%
7 190
 
6.6%
5 188
 
6.5%
4 168
 
5.8%
8 166
 
5.7%
9 160
 
5.5%
Space Separator
ValueCountFrequency (%)
130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3019
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 587
19.4%
6 531
17.6%
0 488
16.2%
3 215
 
7.1%
1 196
 
6.5%
7 190
 
6.3%
5 188
 
6.2%
4 168
 
5.6%
8 166
 
5.5%
9 160
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 587
19.4%
6 531
17.6%
0 488
16.2%
3 215
 
7.1%
1 196
 
6.5%
7 190
 
6.3%
5 188
 
6.2%
4 168
 
5.6%
8 166
 
5.5%
9 160
 
5.3%

소재지면적
Text

MISSING 

Distinct171
Distinct (%)52.5%
Missing100
Missing (%)23.5%
Memory size3.5 KiB
2024-05-11T01:45:51.004923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.8374233
Min length3

Characters and Unicode

Total characters1577
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

Unique124 ?
Unique (%)38.0%

Sample

1st row195.90
2nd row80.40
3rd row88.24
4th row40.95
5th row14.08
ValueCountFrequency (%)
10.00 22
 
6.7%
3.30 11
 
3.4%
30.00 9
 
2.8%
16.50 9
 
2.8%
6.60 9
 
2.8%
20.00 9
 
2.8%
33.00 8
 
2.5%
15.00 8
 
2.5%
5.00 7
 
2.1%
6.00 7
 
2.1%
Other values (161) 227
69.6%
2024-05-11T01:45:52.824058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 502
31.8%
. 326
20.7%
1 135
 
8.6%
3 108
 
6.8%
2 98
 
6.2%
6 96
 
6.1%
5 84
 
5.3%
4 75
 
4.8%
9 63
 
4.0%
8 55
 
3.5%
Other values (2) 35
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1250
79.3%
Other Punctuation 327
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 502
40.2%
1 135
 
10.8%
3 108
 
8.6%
2 98
 
7.8%
6 96
 
7.7%
5 84
 
6.7%
4 75
 
6.0%
9 63
 
5.0%
8 55
 
4.4%
7 34
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 326
99.7%
, 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1577
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 502
31.8%
. 326
20.7%
1 135
 
8.6%
3 108
 
6.8%
2 98
 
6.2%
6 96
 
6.1%
5 84
 
5.3%
4 75
 
4.8%
9 63
 
4.0%
8 55
 
3.5%
Other values (2) 35
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1577
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 502
31.8%
. 326
20.7%
1 135
 
8.6%
3 108
 
6.8%
2 98
 
6.2%
6 96
 
6.1%
5 84
 
5.3%
4 75
 
4.8%
9 63
 
4.0%
8 55
 
3.5%
Other values (2) 35
 
2.2%
Distinct114
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-05-11T01:45:53.960653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0938967
Min length6

Characters and Unicode

Total characters2596
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

Unique46 ?
Unique (%)10.8%

Sample

1st row157210
2nd row157863
3rd row157290
4th row157927
5th row157838
ValueCountFrequency (%)
157290 33
 
7.7%
157816 27
 
6.3%
157795 22
 
5.2%
157930 18
 
4.2%
157840 15
 
3.5%
157210 13
 
3.1%
157804 11
 
2.6%
157884 10
 
2.3%
157853 9
 
2.1%
157800 9
 
2.1%
Other values (104) 259
60.8%
2024-05-11T01:45:55.180469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 542
20.9%
7 508
19.6%
5 499
19.2%
8 290
11.2%
0 204
 
7.9%
9 173
 
6.7%
2 131
 
5.0%
3 73
 
2.8%
4 72
 
2.8%
6 64
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2556
98.5%
Dash Punctuation 40
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 542
21.2%
7 508
19.9%
5 499
19.5%
8 290
11.3%
0 204
 
8.0%
9 173
 
6.8%
2 131
 
5.1%
3 73
 
2.9%
4 72
 
2.8%
6 64
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2596
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 542
20.9%
7 508
19.6%
5 499
19.2%
8 290
11.2%
0 204
 
7.9%
9 173
 
6.7%
2 131
 
5.0%
3 73
 
2.8%
4 72
 
2.8%
6 64
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 542
20.9%
7 508
19.6%
5 499
19.2%
8 290
11.2%
0 204
 
7.9%
9 173
 
6.7%
2 131
 
5.0%
3 73
 
2.8%
4 72
 
2.8%
6 64
 
2.5%
Distinct385
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-05-11T01:45:55.917213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length42
Mean length25.586854
Min length18

Characters and Unicode

Total characters10900
Distinct characters205
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique358 ?
Unique (%)84.0%

Sample

1st row서울특별시 강서구 마곡동 327-53
2nd row서울특별시 강서구 염창동 275-8
3rd row서울특별시 강서구 외발산동 234-21 (지하 1층)
4th row서울특별시 강서구 화곡동 1095-0
5th row서울특별시 강서구 등촌동 628-24
ValueCountFrequency (%)
서울특별시 426
19.9%
강서구 426
19.9%
화곡동 117
 
5.5%
1층 83
 
3.9%
외발산동 59
 
2.8%
방화동 56
 
2.6%
등촌동 53
 
2.5%
424 43
 
2.0%
공항동 41
 
1.9%
2층 35
 
1.6%
Other values (492) 799
37.4%
2024-05-11T01:45:56.876376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2064
18.9%
869
 
8.0%
1 488
 
4.5%
466
 
4.3%
443
 
4.1%
433
 
4.0%
426
 
3.9%
426
 
3.9%
426
 
3.9%
426
 
3.9%
Other values (195) 4433
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6077
55.8%
Decimal Number 2249
 
20.6%
Space Separator 2064
 
18.9%
Dash Punctuation 351
 
3.2%
Open Punctuation 65
 
0.6%
Close Punctuation 65
 
0.6%
Uppercase Letter 15
 
0.1%
Other Punctuation 11
 
0.1%
Letter Number 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
869
14.3%
466
 
7.7%
443
 
7.3%
433
 
7.1%
426
 
7.0%
426
 
7.0%
426
 
7.0%
426
 
7.0%
181
 
3.0%
175
 
2.9%
Other values (167) 1806
29.7%
Decimal Number
ValueCountFrequency (%)
1 488
21.7%
2 313
13.9%
4 265
11.8%
3 198
8.8%
0 193
 
8.6%
6 180
 
8.0%
7 170
 
7.6%
8 161
 
7.2%
9 151
 
6.7%
5 130
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 5
33.3%
A 5
33.3%
D 2
 
13.3%
W 1
 
6.7%
N 1
 
6.7%
C 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 8
72.7%
. 2
 
18.2%
@ 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 63
96.9%
[ 2
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 63
96.9%
] 2
 
3.1%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
2064
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 351
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6077
55.8%
Common 4806
44.1%
Latin 17
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
869
14.3%
466
 
7.7%
443
 
7.3%
433
 
7.1%
426
 
7.0%
426
 
7.0%
426
 
7.0%
426
 
7.0%
181
 
3.0%
175
 
2.9%
Other values (167) 1806
29.7%
Common
ValueCountFrequency (%)
2064
42.9%
1 488
 
10.2%
- 351
 
7.3%
2 313
 
6.5%
4 265
 
5.5%
3 198
 
4.1%
0 193
 
4.0%
6 180
 
3.7%
7 170
 
3.5%
8 161
 
3.3%
Other values (10) 423
 
8.8%
Latin
ValueCountFrequency (%)
B 5
29.4%
A 5
29.4%
D 2
 
11.8%
1
 
5.9%
W 1
 
5.9%
N 1
 
5.9%
C 1
 
5.9%
1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6077
55.8%
ASCII 4821
44.2%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2064
42.8%
1 488
 
10.1%
- 351
 
7.3%
2 313
 
6.5%
4 265
 
5.5%
3 198
 
4.1%
0 193
 
4.0%
6 180
 
3.7%
7 170
 
3.5%
8 161
 
3.3%
Other values (16) 438
 
9.1%
Hangul
ValueCountFrequency (%)
869
14.3%
466
 
7.7%
443
 
7.3%
433
 
7.1%
426
 
7.0%
426
 
7.0%
426
 
7.0%
426
 
7.0%
181
 
3.0%
175
 
2.9%
Other values (167) 1806
29.7%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct230
Distinct (%)95.8%
Missing186
Missing (%)43.7%
Memory size3.5 KiB
2024-05-11T01:45:57.372237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length48.5
Mean length34.2875
Min length22

Characters and Unicode

Total characters8229
Distinct characters219
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)93.3%

Sample

1st row서울특별시 강서구 남부순환로19길 10, 지하 1층 (외발산동, 1동)
2nd row서울특별시 강서구 등촌로35길 160 (등촌동)
3rd row서울특별시 강서구 남부순환로 210 (외발산동)
4th row서울특별시 강서구 화곡로20길 28, 지하층 (화곡동, 1동)
5th row서울특별시 강서구 발산로 24 (외발산동,(공판장동) 1층)
ValueCountFrequency (%)
서울특별시 240
 
15.2%
강서구 240
 
15.2%
1층 76
 
4.8%
화곡동 62
 
3.9%
발산로 43
 
2.7%
24 41
 
2.6%
2층 27
 
1.7%
방화동 27
 
1.7%
외발산동 26
 
1.6%
등촌동 23
 
1.5%
Other values (448) 777
49.1%
2024-05-11T01:45:58.540178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1343
 
16.3%
526
 
6.4%
1 327
 
4.0%
310
 
3.8%
286
 
3.5%
, 268
 
3.3%
( 260
 
3.2%
) 260
 
3.2%
247
 
3.0%
242
 
2.9%
Other values (209) 4160
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4804
58.4%
Space Separator 1343
 
16.3%
Decimal Number 1218
 
14.8%
Other Punctuation 268
 
3.3%
Open Punctuation 260
 
3.2%
Close Punctuation 260
 
3.2%
Dash Punctuation 47
 
0.6%
Uppercase Letter 26
 
0.3%
Letter Number 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
526
 
10.9%
310
 
6.5%
286
 
6.0%
247
 
5.1%
242
 
5.0%
240
 
5.0%
240
 
5.0%
240
 
5.0%
240
 
5.0%
177
 
3.7%
Other values (181) 2056
42.8%
Decimal Number
ValueCountFrequency (%)
1 327
26.8%
2 201
16.5%
4 149
12.2%
3 108
 
8.9%
0 106
 
8.7%
5 97
 
8.0%
6 73
 
6.0%
7 60
 
4.9%
8 55
 
4.5%
9 42
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
B 9
34.6%
A 6
23.1%
D 4
15.4%
W 1
 
3.8%
F 1
 
3.8%
M 1
 
3.8%
P 1
 
3.8%
C 1
 
3.8%
N 1
 
3.8%
J 1
 
3.8%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
1343
100.0%
Other Punctuation
ValueCountFrequency (%)
, 268
100.0%
Open Punctuation
ValueCountFrequency (%)
( 260
100.0%
Close Punctuation
ValueCountFrequency (%)
) 260
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4804
58.4%
Common 3397
41.3%
Latin 28
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
526
 
10.9%
310
 
6.5%
286
 
6.0%
247
 
5.1%
242
 
5.0%
240
 
5.0%
240
 
5.0%
240
 
5.0%
240
 
5.0%
177
 
3.7%
Other values (181) 2056
42.8%
Common
ValueCountFrequency (%)
1343
39.5%
1 327
 
9.6%
, 268
 
7.9%
( 260
 
7.7%
) 260
 
7.7%
2 201
 
5.9%
4 149
 
4.4%
3 108
 
3.2%
0 106
 
3.1%
5 97
 
2.9%
Other values (6) 278
 
8.2%
Latin
ValueCountFrequency (%)
B 9
32.1%
A 6
21.4%
D 4
14.3%
1
 
3.6%
W 1
 
3.6%
1
 
3.6%
F 1
 
3.6%
M 1
 
3.6%
P 1
 
3.6%
C 1
 
3.6%
Other values (2) 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4804
58.4%
ASCII 3423
41.6%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1343
39.2%
1 327
 
9.6%
, 268
 
7.8%
( 260
 
7.6%
) 260
 
7.6%
2 201
 
5.9%
4 149
 
4.4%
3 108
 
3.2%
0 106
 
3.1%
5 97
 
2.8%
Other values (16) 304
 
8.9%
Hangul
ValueCountFrequency (%)
526
 
10.9%
310
 
6.5%
286
 
6.0%
247
 
5.1%
242
 
5.0%
240
 
5.0%
240
 
5.0%
240
 
5.0%
240
 
5.0%
177
 
3.7%
Other values (181) 2056
42.8%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)42.3%
Missing187
Missing (%)43.9%
Infinite0
Infinite (%)0.0%
Mean7652.1255
Minimum7504
Maximum7808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T01:45:58.967334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7504
5-th percentile7520.1
Q17603
median7644
Q37719
95-th percentile7801
Maximum7808
Range304
Interquartile range (IQR)116

Descriptive statistics

Standard deviation80.148608
Coefficient of variation (CV)0.010474032
Kurtosis-0.63632971
Mean7652.1255
Median Absolute Deviation (MAD)58
Skewness0.18474566
Sum1828858
Variance6423.7993
MonotonicityNot monotonic
2024-05-11T01:45:59.331834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7644 43
 
10.1%
7645 17
 
4.0%
7505 7
 
1.6%
7604 6
 
1.4%
7806 6
 
1.4%
7583 5
 
1.2%
7639 4
 
0.9%
7802 4
 
0.9%
7621 4
 
0.9%
7532 4
 
0.9%
Other values (91) 139
32.6%
(Missing) 187
43.9%
ValueCountFrequency (%)
7504 1
 
0.2%
7505 7
1.6%
7506 2
 
0.5%
7510 1
 
0.2%
7512 1
 
0.2%
7521 1
 
0.2%
7522 1
 
0.2%
7523 1
 
0.2%
7524 1
 
0.2%
7531 1
 
0.2%
ValueCountFrequency (%)
7808 1
 
0.2%
7806 6
1.4%
7802 4
0.9%
7801 3
0.7%
7787 1
 
0.2%
7785 1
 
0.2%
7782 2
 
0.5%
7781 1
 
0.2%
7779 1
 
0.2%
7777 3
0.7%
Distinct408
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-05-11T01:45:59.813974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length6.4366197
Min length2

Characters and Unicode

Total characters2742
Distinct characters410
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique392 ?
Unique (%)92.0%

Sample

1st row영성식품
2nd row(주)선일특산
3rd row찰표식품
4th row그랜드산업개발(주)그랜드마트
5th row신흥물산
ValueCountFrequency (%)
주식회사 13
 
2.8%
주)신세계이마트공항점 3
 
0.6%
청심식품 3
 
0.6%
숭진유통 2
 
0.4%
청해진 2
 
0.4%
강서점 2
 
0.4%
쎄일마트 2
 
0.4%
김포공항점 2
 
0.4%
고유식품 2
 
0.4%
주)예주병과 2
 
0.4%
Other values (423) 435
92.9%
2024-05-11T01:46:00.634525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
 
5.0%
) 131
 
4.8%
( 129
 
4.7%
75
 
2.7%
65
 
2.4%
60
 
2.2%
58
 
2.1%
55
 
2.0%
52
 
1.9%
47
 
1.7%
Other values (400) 1933
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2375
86.6%
Close Punctuation 131
 
4.8%
Open Punctuation 129
 
4.7%
Space Separator 42
 
1.5%
Uppercase Letter 28
 
1.0%
Lowercase Letter 25
 
0.9%
Decimal Number 9
 
0.3%
Dash Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
137
 
5.8%
75
 
3.2%
65
 
2.7%
60
 
2.5%
58
 
2.4%
55
 
2.3%
52
 
2.2%
47
 
2.0%
44
 
1.9%
35
 
1.5%
Other values (357) 1747
73.6%
Uppercase Letter
ValueCountFrequency (%)
S 3
10.7%
N 3
10.7%
T 3
10.7%
A 2
 
7.1%
E 2
 
7.1%
I 2
 
7.1%
O 2
 
7.1%
C 2
 
7.1%
G 1
 
3.6%
H 1
 
3.6%
Other values (7) 7
25.0%
Lowercase Letter
ValueCountFrequency (%)
s 3
12.0%
e 3
12.0%
a 3
12.0%
g 2
 
8.0%
r 2
 
8.0%
o 2
 
8.0%
w 2
 
8.0%
l 1
 
4.0%
t 1
 
4.0%
u 1
 
4.0%
Other values (5) 5
20.0%
Decimal Number
ValueCountFrequency (%)
2 3
33.3%
0 2
22.2%
7 1
 
11.1%
5 1
 
11.1%
9 1
 
11.1%
4 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 131
100.0%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2375
86.6%
Common 314
 
11.5%
Latin 53
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
137
 
5.8%
75
 
3.2%
65
 
2.7%
60
 
2.5%
58
 
2.4%
55
 
2.3%
52
 
2.2%
47
 
2.0%
44
 
1.9%
35
 
1.5%
Other values (357) 1747
73.6%
Latin
ValueCountFrequency (%)
s 3
 
5.7%
e 3
 
5.7%
S 3
 
5.7%
N 3
 
5.7%
T 3
 
5.7%
a 3
 
5.7%
A 2
 
3.8%
E 2
 
3.8%
I 2
 
3.8%
g 2
 
3.8%
Other values (22) 27
50.9%
Common
ValueCountFrequency (%)
) 131
41.7%
( 129
41.1%
42
 
13.4%
2 3
 
1.0%
0 2
 
0.6%
- 2
 
0.6%
7 1
 
0.3%
5 1
 
0.3%
9 1
 
0.3%
4 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2375
86.6%
ASCII 367
 
13.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
137
 
5.8%
75
 
3.2%
65
 
2.7%
60
 
2.5%
58
 
2.4%
55
 
2.3%
52
 
2.2%
47
 
2.0%
44
 
1.9%
35
 
1.5%
Other values (357) 1747
73.6%
ASCII
ValueCountFrequency (%)
) 131
35.7%
( 129
35.1%
42
 
11.4%
s 3
 
0.8%
2 3
 
0.8%
e 3
 
0.8%
S 3
 
0.8%
N 3
 
0.8%
T 3
 
0.8%
a 3
 
0.8%
Other values (33) 44
 
12.0%
Distinct388
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum1999-10-26 00:00:00
Maximum2024-05-02 11:58:07
2024-05-11T01:46:00.984315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:46:01.458366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
I
339 
U
87 

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 339
79.6%
U 87
 
20.4%

Length

2024-05-11T01:46:01.845538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:02.174912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 339
79.6%
u 87
 
20.4%
Distinct101
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T01:46:02.627501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:46:03.063984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
식품소분업
426 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 426
100.0%

Length

2024-05-11T01:46:03.487553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:03.733423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 426
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct267
Distinct (%)65.8%
Missing20
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean185465.08
Minimum182141.21
Maximum189054.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T01:46:04.009152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile183013.95
Q1183914.94
median185652.18
Q3186856.75
95-th percentile187952.56
Maximum189054.12
Range6912.919
Interquartile range (IQR)2941.8105

Descriptive statistics

Standard deviation1707.6312
Coefficient of variation (CV)0.0092072922
Kurtosis-1.2472509
Mean185465.08
Median Absolute Deviation (MAD)1737.2433
Skewness0.069970179
Sum75298823
Variance2916004.3
MonotonicityNot monotonic
2024-05-11T01:46:04.385816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
183914.938310002 48
 
11.3%
187119.948165892 10
 
2.3%
186687.131804431 9
 
2.1%
183307.197874057 8
 
1.9%
187761.194273879 8
 
1.9%
184148.571466974 6
 
1.4%
182524.823835629 6
 
1.4%
185732.424363656 5
 
1.2%
187464.403178638 5
 
1.2%
186800.193947236 4
 
0.9%
Other values (257) 297
69.7%
(Missing) 20
 
4.7%
ValueCountFrequency (%)
182141.205465089 2
 
0.5%
182293.357671337 1
 
0.2%
182524.823835629 6
1.4%
182846.406822134 1
 
0.2%
182876.367858149 1
 
0.2%
182895.668483962 1
 
0.2%
182912.435007001 2
 
0.5%
182933.115073744 1
 
0.2%
182944.731406147 1
 
0.2%
182968.796339956 2
 
0.5%
ValueCountFrequency (%)
189054.124510047 1
0.2%
188917.095297226 1
0.2%
188894.08883472 1
0.2%
188870.663928731 1
0.2%
188692.033242329 1
0.2%
188680.48304204 1
0.2%
188611.328289129 2
0.5%
188543.232024063 1
0.2%
188521.396256996 1
0.2%
188407.319772872 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct267
Distinct (%)65.8%
Missing20
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean450095.51
Minimum447239.55
Maximum452988.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-05-11T01:46:04.763687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447239.55
5-th percentile447691.29
Q1449450.82
median450182.57
Q3450879.96
95-th percentile452206.61
Maximum452988.7
Range5749.1429
Interquartile range (IQR)1429.1372

Descriptive statistics

Standard deviation1326.3058
Coefficient of variation (CV)0.0029467208
Kurtosis-0.39201819
Mean450095.51
Median Absolute Deviation (MAD)701.95703
Skewness-0.29713823
Sum1.8273878 × 108
Variance1759087.1
MonotonicityNot monotonic
2024-05-11T01:46:05.086042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450085.01457343 48
 
11.3%
450691.593173724 10
 
2.3%
451342.773451086 9
 
2.1%
452726.015586166 8
 
1.9%
450640.214509068 8
 
1.9%
450166.360534543 6
 
1.4%
451438.25089679 6
 
1.4%
450884.528795882 5
 
1.2%
447877.710664426 5
 
1.2%
449680.272769723 4
 
0.9%
Other values (257) 297
69.7%
(Missing) 20
 
4.7%
ValueCountFrequency (%)
447239.554007375 1
0.2%
447291.688405525 1
0.2%
447306.401971741 1
0.2%
447326.548615694 1
0.2%
447380.825061783 1
0.2%
447419.741756703 1
0.2%
447456.838723466 1
0.2%
447481.210076355 1
0.2%
447514.56416265 1
0.2%
447527.398068835 1
0.2%
ValueCountFrequency (%)
452988.696877824 1
 
0.2%
452787.432746802 1
 
0.2%
452781.576077741 1
 
0.2%
452726.015586166 8
1.9%
452426.754650691 1
 
0.2%
452336.751564624 1
 
0.2%
452322.965685604 1
 
0.2%
452319.630584878 1
 
0.2%
452293.455519022 1
 
0.2%
452292.338242438 1
 
0.2%

위생업태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
식품소분업
372 
<NA>
54 

Length

Max length5
Median length5
Mean length4.8732394
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 372
87.3%
<NA> 54
 
12.7%

Length

2024-05-11T01:46:05.561904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:05.931965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 372
87.3%
na 54
 
12.7%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
385 
0
 
24
2
 
9
1
 
4
4
 
2

Length

Max length4
Median length4
Mean length3.7112676
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row2
3rd row2
4th row1
5th row4

Common Values

ValueCountFrequency (%)
<NA> 385
90.4%
0 24
 
5.6%
2 9
 
2.1%
1 4
 
0.9%
4 2
 
0.5%
3 2
 
0.5%

Length

2024-05-11T01:46:06.208257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:06.502622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 385
90.4%
0 24
 
5.6%
2 9
 
2.1%
1 4
 
0.9%
4 2
 
0.5%
3 2
 
0.5%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
391 
0
 
26
1
 
6
12
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.7558685
Min length1

Unique

Unique3 ?
Unique (%)0.7%

Sample

1st row12
2nd row4
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
<NA> 391
91.8%
0 26
 
6.1%
1 6
 
1.4%
12 1
 
0.2%
4 1
 
0.2%
2 1
 
0.2%

Length

2024-05-11T01:46:06.847839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:07.205238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 391
91.8%
0 26
 
6.1%
1 6
 
1.4%
12 1
 
0.2%
4 1
 
0.2%
2 1
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
399 
기타
 
16
주택가주변
 
9
유흥업소밀집지역
 
1
아파트지역
 
1

Length

Max length8
Median length4
Mean length3.9577465
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
93.7%
기타 16
 
3.8%
주택가주변 9
 
2.1%
유흥업소밀집지역 1
 
0.2%
아파트지역 1
 
0.2%

Length

2024-05-11T01:46:07.509740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:07.796466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
93.7%
기타 16
 
3.8%
주택가주변 9
 
2.1%
유흥업소밀집지역 1
 
0.2%
아파트지역 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
399 
기타
 
26
 
1

Length

Max length4
Median length4
Mean length3.870892
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
93.7%
기타 26
 
6.1%
1
 
0.2%

Length

2024-05-11T01:46:08.198349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:08.617057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
93.7%
기타 26
 
6.1%
1
 
0.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
360 
상수도전용
65 
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.1549296
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 360
84.5%
상수도전용 65
 
15.3%
지하수전용 1
 
0.2%

Length

2024-05-11T01:46:08.905647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:09.210101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 360
84.5%
상수도전용 65
 
15.3%
지하수전용 1
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
413 
0
 
13

Length

Max length4
Median length4
Mean length3.9084507
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> 413
96.9%
0 13
 
3.1%

Length

2024-05-11T01:46:09.595628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:09.939292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 413
96.9%
0 13
 
3.1%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
321 
0
105 

Length

Max length4
Median length4
Mean length3.2605634
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 321
75.4%
0 105
 
24.6%

Length

2024-05-11T01:46:10.284637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:10.555112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 321
75.4%
0 105
 
24.6%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
321 
0
105 

Length

Max length4
Median length4
Mean length3.2605634
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 321
75.4%
0 105
 
24.6%

Length

2024-05-11T01:46:10.845216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:11.151001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 321
75.4%
0 105
 
24.6%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
321 
0
105 

Length

Max length4
Median length4
Mean length3.2605634
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 321
75.4%
0 105
 
24.6%

Length

2024-05-11T01:46:11.460302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:11.753739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 321
75.4%
0 105
 
24.6%
Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
318 
0
102 
1
 
6

Length

Max length4
Median length4
Mean length3.2394366
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 318
74.6%
0 102
 
23.9%
1 6
 
1.4%

Length

2024-05-11T01:46:12.393891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:12.841741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 318
74.6%
0 102
 
23.9%
1 6
 
1.4%
Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
229 
임대
129 
자가
68 

Length

Max length4
Median length4
Mean length3.0751174
Min length2

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> 229
53.8%
임대 129
30.3%
자가 68
 
16.0%

Length

2024-05-11T01:46:13.386986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:14.062742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 229
53.8%
임대 129
30.3%
자가 68
 
16.0%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
403 
0
 
21
5000000
 
2

Length

Max length7
Median length4
Mean length3.8661972
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> 403
94.6%
0 21
 
4.9%
5000000 2
 
0.5%

Length

2024-05-11T01:46:14.469256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:14.887985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 403
94.6%
0 21
 
4.9%
5000000 2
 
0.5%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
403 
0
 
21
650000
 
1
500000
 
1

Length

Max length6
Median length4
Mean length3.8615023
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 403
94.6%
0 21
 
4.9%
650000 1
 
0.2%
500000 1
 
0.2%

Length

2024-05-11T01:46:15.300050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:15.697866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 403
94.6%
0 21
 
4.9%
650000 1
 
0.2%
500000 1
 
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing54
Missing (%)12.7%
Memory size984.0 B
False
372 
(Missing)
54 
ValueCountFrequency (%)
False 372
87.3%
(Missing) 54
 
12.7%
2024-05-11T01:46:16.013708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
0.0
368 
<NA>
54 
114.56
 
1
182.0
 
1
46.43
 
1

Length

Max length6
Median length3
Mean length3.1431925
Min length3

Unique

Unique4 ?
Unique (%)0.9%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 368
86.4%
<NA> 54
 
12.7%
114.56 1
 
0.2%
182.0 1
 
0.2%
46.43 1
 
0.2%
0.3 1
 
0.2%

Length

2024-05-11T01:46:16.431846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:46:16.930228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 368
86.4%
na 54
 
12.7%
114.56 1
 
0.2%
182.0 1
 
0.2%
46.43 1
 
0.2%
0.3 1
 
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing426
Missing (%)100.0%
Memory size3.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing426
Missing (%)100.0%
Memory size3.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing426
Missing (%)100.0%
Memory size3.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031500003150000-109-1987-0071219870318<NA>3폐업2폐업20050617<NA><NA><NA>02 6595907195.90157210서울특별시 강서구 마곡동 327-53<NA><NA>영성식품2003-07-28 00:00:00I2018-08-31 23:59:59.0식품소분업184343.983715452112.776502식품소분업412기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
131500003150000-109-1990-0000919901022<NA>3폐업2폐업19971216<NA><NA><NA>02 646851180.40157863서울특별시 강서구 염창동 275-8<NA><NA>(주)선일특산2001-09-28 00:00:00I2018-08-31 23:59:59.0식품소분업188306.060758449765.60471식품소분업24주택가주변기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231500003150000-109-1992-0001019920115<NA>3폐업2폐업20160624<NA><NA><NA>022661327788.24157290서울특별시 강서구 외발산동 234-21 (지하 1층)서울특별시 강서구 남부순환로19길 10, 지하 1층 (외발산동, 1동)7641찰표식품2016-01-13 15:19:27I2018-08-31 23:59:59.0식품소분업184189.581331449359.425676식품소분업21주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
331500003150000-109-1995-0071319950502<NA>3폐업2폐업20060317<NA><NA><NA>022606010140.95157927서울특별시 강서구 화곡동 1095-0<NA><NA>그랜드산업개발(주)그랜드마트1999-10-26 00:00:00I2018-08-31 23:59:59.0식품소분업186786.622462450297.702652식품소분업11유흥업소밀집지역기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431500003150000-109-1996-0001119960223<NA>3폐업2폐업20060418<NA><NA><NA>023663096714.08157838서울특별시 강서구 등촌동 628-24<NA><NA>신흥물산1999-10-26 00:00:00I2018-08-31 23:59:59.0식품소분업187282.745177450848.524885식품소분업40기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531500003150000-109-1996-0001219960401<NA>3폐업2폐업19970526<NA><NA><NA>02 666580118.42157220서울특별시 강서구 방화동 0-0 도시개(아) 11동 1.2.호<NA><NA>농어민후계자유통사업소2001-09-28 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업21주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631500003150000-109-1996-0001319960827<NA>3폐업2폐업19980116<NA><NA><NA>02 608138410.50157884서울특별시 강서구 화곡동 373-15<NA><NA>(주)영안유통2001-09-28 00:00:00I2018-08-31 23:59:59.0식품소분업185538.900352448023.692715식품소분업2<NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731500003150000-109-1997-0001419970124<NA>3폐업2폐업20020418<NA><NA><NA>02260490945.89157880서울특별시 강서구 화곡동 342-73<NA><NA>충남제과2001-09-28 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업11기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831500003150000-109-1997-0001519970127<NA>3폐업2폐업20000104<NA><NA><NA>02 69334516.00157910서울특별시 강서구 화곡동 908-8<NA><NA>사임당식품2001-09-28 00:00:00I2018-08-31 23:59:59.0식품소분업186321.586673447291.688406식품소분업31기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931500003150000-109-1997-0001619970623<NA>3폐업2폐업20130312<NA><NA><NA>02 646782743.62157837서울특별시 강서구 등촌동 567-6서울특별시 강서구 등촌로35길 160 (등촌동)7733(주)잠원실업2012-09-27 15:12:00I2018-08-31 23:59:59.0식품소분업187784.855388448197.372109식품소분업31주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
41631500003150000-109-2023-000132023-12-26<NA>1영업/정상1영업<NA><NA><NA><NA>022661036947.80157-210서울특별시 강서구 마곡동 800-1 문영 퀸즈파크11차 5층 512호서울특별시 강서구 공항대로 212, 문영 퀸즈파크11차 5층 512호 (마곡동)7806주식회사 에스에스엠플랜2023-12-26 15:51:46I2022-11-01 22:08:00.0식품소분업184998.704481450740.541211<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41731500003150000-109-2023-000142023-05-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>50.00157-928서울특별시 강서구 화곡동 1115-3 2층서울특별시 강서구 화곡로58길 19-3, 2층 (화곡동)7654제이에이치 페밀리2024-04-23 15:55:47I2023-12-03 22:05:00.0식품소분업186864.89938450110.524094<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41831500003150000-109-2024-000012024-01-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.50157-886서울특별시 강서구 화곡동 395-1서울특별시 강서구 곰달래로27길 91, 지층 (화곡동)7755아이스크림할인마트(빙고푸드까치산점)2024-01-25 13:49:21U2023-11-30 22:07:00.0식품소분업186676.260353448088.187462<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41931500003150000-109-2024-000022024-01-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>11.00157-886서울특별시 강서구 화곡동 395-1서울특별시 강서구 곰달래로27길 91, 지층 (화곡동)7755아이스크림할인마트(까치산점2호점)2024-01-25 13:44:49U2023-11-30 22:07:00.0식품소분업186676.260353448088.187462<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42031500003150000-109-2024-000032024-01-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.48157-918서울특별시 강서구 화곡동 1013서울특별시 강서구 강서로 237, 1층 13호 (화곡동)7705에그플우장산점아슈크림2024-01-15 11:49:16I2023-11-30 23:07:00.0식품소분업185416.850129449408.506403<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42131500003150000-109-2024-000042024-01-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.00157-909서울특별시 강서구 화곡동 902-10서울특별시 강서구 강서로7길 19, 1층 (화곡동)7777어부네간식2024-01-16 11:27:06I2023-11-30 22:00:00.0식품소분업186380.634607447481.210076<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42231500003150000-109-2024-000052024-03-15<NA>1영업/정상1영업<NA><NA><NA><NA>0708252713935.43157-840서울특별시 강서구 등촌동 641-11 청림오피스텔서울특별시 강서구 공항대로45길 44, 청림오피스텔 3층 304호 (등촌동)7569주식회사 점보2024-03-15 14:35:43I2023-12-02 23:07:00.0식품소분업187197.468812450519.999406<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42331500003150000-109-2024-000062024-03-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00157-928서울특별시 강서구 화곡동 1113서울특별시 강서구 공항대로46길 25, 314호 (화곡동)7654김SE House2024-03-26 15:30:10I2023-12-02 22:08:00.0식품소분업186943.796834450238.665562<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42431500003150000-109-2024-000072024-04-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30157-863서울특별시 강서구 염창동 274-1서울특별시 강서구 공항대로61길 6, 1층 가운데호 (염창동)7562푸디팝2024-04-11 17:11:58I2023-12-03 23:03:00.0식품소분업188038.92881449905.981569<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42531500003150000-109-2024-000082024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00157-872서울특별시 강서구 화곡동 105-80서울특별시 강서구 까치산로 14, 2층 202호 (화곡동)7726얌얌2024-05-02 11:58:07I2023-12-05 00:05:00.0식품소분업186011.03965448793.443875<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>