Overview

Dataset statistics

Number of variables44
Number of observations82
Missing cells786
Missing cells (%)21.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.2 KiB
Average record size in memory376.6 B

Variable types

Categorical21
Text8
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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-18320/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
급수시설구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업장주변구분명 is highly imbalanced (57.9%)Imbalance
등급구분명 is highly imbalanced (68.8%)Imbalance
인허가취소일자 has 82 (100.0%) missing valuesMissing
폐업일자 has 30 (36.6%) missing valuesMissing
휴업시작일자 has 82 (100.0%) missing valuesMissing
휴업종료일자 has 82 (100.0%) missing valuesMissing
재개업일자 has 82 (100.0%) missing valuesMissing
전화번호 has 20 (24.4%) missing valuesMissing
소재지면적 has 2 (2.4%) missing valuesMissing
소재지우편번호 has 2 (2.4%) missing valuesMissing
지번주소 has 2 (2.4%) missing valuesMissing
도로명주소 has 22 (26.8%) missing valuesMissing
도로명우편번호 has 23 (28.0%) missing valuesMissing
좌표정보(X) has 3 (3.7%) missing valuesMissing
좌표정보(Y) has 3 (3.7%) missing valuesMissing
급수시설구분명 has 80 (97.6%) missing valuesMissing
다중이용업소여부 has 25 (30.5%) missing valuesMissing
전통업소지정번호 has 82 (100.0%) missing valuesMissing
전통업소주된음식 has 82 (100.0%) missing valuesMissing
홈페이지 has 82 (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 started2024-04-06 10:18:10.739056
Analysis finished2024-04-06 10:18:11.723377
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
3180000
82 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 82
100.0%

Length

2024-04-06T19:18:11.834556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:11.996476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 82
100.0%

관리번호
Text

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
2024-04-06T19:18:12.279917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1804
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

Unique82 ?
Unique (%)100.0%

Sample

1st row3180000-114-1990-00001
2nd row3180000-114-1991-00001
3rd row3180000-114-1994-00638
4th row3180000-114-1994-00639
5th row3180000-114-1996-00492
ValueCountFrequency (%)
3180000-114-1990-00001 1
 
1.2%
3180000-114-2015-00003 1
 
1.2%
3180000-114-2015-00001 1
 
1.2%
3180000-114-2014-00002 1
 
1.2%
3180000-114-2014-00001 1
 
1.2%
3180000-114-2012-00003 1
 
1.2%
3180000-114-2012-00002 1
 
1.2%
3180000-114-2012-00001 1
 
1.2%
3180000-114-2011-00001 1
 
1.2%
3180000-114-2010-00004 1
 
1.2%
Other values (72) 72
87.8%
2024-04-06T19:18:12.817892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 737
40.9%
1 330
18.3%
- 246
 
13.6%
2 103
 
5.7%
3 99
 
5.5%
8 99
 
5.5%
4 98
 
5.4%
9 49
 
2.7%
6 20
 
1.1%
5 14
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1558
86.4%
Dash Punctuation 246
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 737
47.3%
1 330
21.2%
2 103
 
6.6%
3 99
 
6.4%
8 99
 
6.4%
4 98
 
6.3%
9 49
 
3.1%
6 20
 
1.3%
5 14
 
0.9%
7 9
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 737
40.9%
1 330
18.3%
- 246
 
13.6%
2 103
 
5.7%
3 99
 
5.5%
8 99
 
5.5%
4 98
 
5.4%
9 49
 
2.7%
6 20
 
1.1%
5 14
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 737
40.9%
1 330
18.3%
- 246
 
13.6%
2 103
 
5.7%
3 99
 
5.5%
8 99
 
5.5%
4 98
 
5.4%
9 49
 
2.7%
6 20
 
1.1%
5 14
 
0.8%

인허가일자
Date

Distinct79
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum1990-08-20 00:00:00
Maximum2023-08-31 00:00:00
2024-04-06T19:18:13.087958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:18:13.354539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
3
52 
1
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 52
63.4%
1 30
36.6%

Length

2024-04-06T19:18:13.588056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:13.781828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 52
63.4%
1 30
36.6%

영업상태명
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
폐업
52 
영업/정상
30 

Length

Max length5
Median length2
Mean length3.097561
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 52
63.4%
영업/정상 30
36.6%

Length

2024-04-06T19:18:13.994056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:14.197403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
63.4%
영업/정상 30
36.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
2
52 
1
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 52
63.4%
1 30
36.6%

Length

2024-04-06T19:18:14.369360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:14.564308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 52
63.4%
1 30
36.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
폐업
52 
영업
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 52
63.4%
영업 30
36.6%

Length

2024-04-06T19:18:14.717389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:14.878752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
63.4%
영업 30
36.6%

폐업일자
Date

MISSING 

Distinct50
Distinct (%)96.2%
Missing30
Missing (%)36.6%
Memory size788.0 B
Minimum2000-06-03 00:00:00
Maximum2023-08-22 00:00:00
2024-04-06T19:18:15.097913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:18:15.800868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

전화번호
Text

MISSING 

Distinct55
Distinct (%)88.7%
Missing20
Missing (%)24.4%
Memory size788.0 B
2024-04-06T19:18:16.156133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.3709677
Min length2

Characters and Unicode

Total characters581
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

Unique48 ?
Unique (%)77.4%

Sample

1st row6761234
2nd row26708010
3rd row0226306000
4th row0218999900
5th row02
ValueCountFrequency (%)
02 28
30.4%
0226366003 2
 
2.2%
3805678 2
 
2.2%
0226778877 2
 
2.2%
834 2
 
2.2%
26778877 2
 
2.2%
8311270 2
 
2.2%
8454455 2
 
2.2%
8450301 1
 
1.1%
8350018 1
 
1.1%
Other values (48) 48
52.2%
2024-04-06T19:18:16.823581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 112
19.3%
2 98
16.9%
8 59
10.2%
3 51
8.8%
6 50
8.6%
7 45
7.7%
1 39
 
6.7%
38
 
6.5%
5 35
 
6.0%
4 35
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 543
93.5%
Space Separator 38
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 112
20.6%
2 98
18.0%
8 59
10.9%
3 51
9.4%
6 50
9.2%
7 45
8.3%
1 39
 
7.2%
5 35
 
6.4%
4 35
 
6.4%
9 19
 
3.5%
Space Separator
ValueCountFrequency (%)
38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 581
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 112
19.3%
2 98
16.9%
8 59
10.2%
3 51
8.8%
6 50
8.6%
7 45
7.7%
1 39
 
6.7%
38
 
6.5%
5 35
 
6.0%
4 35
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 581
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 112
19.3%
2 98
16.9%
8 59
10.2%
3 51
8.8%
6 50
8.6%
7 45
7.7%
1 39
 
6.7%
38
 
6.5%
5 35
 
6.0%
4 35
 
6.0%

소재지면적
Text

MISSING 

Distinct74
Distinct (%)92.5%
Missing2
Missing (%)2.4%
Memory size788.0 B
2024-04-06T19:18:17.287419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.4625
Min length3

Characters and Unicode

Total characters517
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

Unique68 ?
Unique (%)85.0%

Sample

1st row950.44
2nd row1,709.10
3rd row3,741.43
4th row3,859.31
5th row367.88
ValueCountFrequency (%)
458.85 2
 
2.5%
495.00 2
 
2.5%
462.39 2
 
2.5%
396.00 2
 
2.5%
330.00 2
 
2.5%
528.00 2
 
2.5%
484.00 1
 
1.2%
679.64 1
 
1.2%
663.00 1
 
1.2%
1,150.00 1
 
1.2%
Other values (64) 64
80.0%
2024-04-06T19:18:18.110798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 118
22.8%
. 80
15.5%
3 46
 
8.9%
5 40
 
7.7%
9 38
 
7.4%
4 37
 
7.2%
1 33
 
6.4%
6 32
 
6.2%
2 27
 
5.2%
8 25
 
4.8%
Other values (2) 41
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 421
81.4%
Other Punctuation 96
 
18.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 118
28.0%
3 46
 
10.9%
5 40
 
9.5%
9 38
 
9.0%
4 37
 
8.8%
1 33
 
7.8%
6 32
 
7.6%
2 27
 
6.4%
8 25
 
5.9%
7 25
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 80
83.3%
, 16
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 517
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 118
22.8%
. 80
15.5%
3 46
 
8.9%
5 40
 
7.7%
9 38
 
7.4%
4 37
 
7.2%
1 33
 
6.4%
6 32
 
6.2%
2 27
 
5.2%
8 25
 
4.8%
Other values (2) 41
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 118
22.8%
. 80
15.5%
3 46
 
8.9%
5 40
 
7.7%
9 38
 
7.4%
4 37
 
7.2%
1 33
 
6.4%
6 32
 
6.2%
2 27
 
5.2%
8 25
 
4.8%
Other values (2) 41
 
7.9%

소재지우편번호
Text

MISSING 

Distinct50
Distinct (%)62.5%
Missing2
Missing (%)2.4%
Memory size788.0 B
2024-04-06T19:18:18.476235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.225
Min length6

Characters and Unicode

Total characters498
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

Unique34 ?
Unique (%)42.5%

Sample

1st row150034
2nd row150899
3rd row150034
4th row150103
5th row150849
ValueCountFrequency (%)
150045 6
 
7.5%
150034 4
 
5.0%
150096 3
 
3.8%
150822 3
 
3.8%
150102 3
 
3.8%
150820 3
 
3.8%
150050 3
 
3.8%
150816 3
 
3.8%
150103 3
 
3.8%
150841 3
 
3.8%
Other values (40) 46
57.5%
2024-04-06T19:18:19.143668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 133
26.7%
1 101
20.3%
5 99
19.9%
8 45
 
9.0%
4 24
 
4.8%
9 20
 
4.0%
3 18
 
3.6%
- 18
 
3.6%
2 17
 
3.4%
6 13
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 480
96.4%
Dash Punctuation 18
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 133
27.7%
1 101
21.0%
5 99
20.6%
8 45
 
9.4%
4 24
 
5.0%
9 20
 
4.2%
3 18
 
3.8%
2 17
 
3.5%
6 13
 
2.7%
7 10
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 498
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 133
26.7%
1 101
20.3%
5 99
19.9%
8 45
 
9.0%
4 24
 
4.8%
9 20
 
4.0%
3 18
 
3.6%
- 18
 
3.6%
2 17
 
3.4%
6 13
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 133
26.7%
1 101
20.3%
5 99
19.9%
8 45
 
9.0%
4 24
 
4.8%
9 20
 
4.0%
3 18
 
3.6%
- 18
 
3.6%
2 17
 
3.4%
6 13
 
2.6%

지번주소
Text

MISSING 

Distinct76
Distinct (%)95.0%
Missing2
Missing (%)2.4%
Memory size788.0 B
2024-04-06T19:18:19.608564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length36
Mean length25.7875
Min length18

Characters and Unicode

Total characters2063
Distinct characters120
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

Unique73 ?
Unique (%)91.2%

Sample

1st row서울특별시 영등포구 영등포동4가 434-5
2nd row서울특별시 영등포구 영등포동 618-496
3rd row서울특별시 영등포구 영등포동4가 441-21
4th row서울특별시 영등포구 양평동3가 65
5th row서울특별시 영등포구 신길동 364-0
ValueCountFrequency (%)
서울특별시 80
20.9%
영등포구 80
20.9%
대림동 16
 
4.2%
신길동 16
 
4.2%
1층 9
 
2.3%
여의도동 8
 
2.1%
당산동5가 6
 
1.6%
지하1층 6
 
1.6%
영등포동4가 5
 
1.3%
909-2 4
 
1.0%
Other values (119) 153
39.9%
2024-04-06T19:18:20.319617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
359
 
17.4%
1 92
 
4.5%
포 92
 
4.5%
등 91
 
4.4%
영 91
 
4.4%
동 83
 
4.0%
울 81
 
3.9%
서 81
 
3.9%
시 80
 
3.9%
구 80
 
3.9%
Other values (110) 933
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1225
59.4%
Decimal Number 398
 
19.3%
Space Separator 359
 
17.4%
Dash Punctuation 49
 
2.4%
Other Punctuation 15
 
0.7%
Uppercase Letter 7
 
0.3%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 92
 
7.5%
등 91
 
7.4%
영 91
 
7.4%
동 83
 
6.8%
울 81
 
6.6%
서 81
 
6.6%
시 80
 
6.5%
구 80
 
6.5%
별 80
 
6.5%
특 80
 
6.5%
Other values (89) 386
31.5%
Decimal Number
ValueCountFrequency (%)
1 92
23.1%
4 48
12.1%
3 47
11.8%
2 47
11.8%
5 39
9.8%
6 33
 
8.3%
0 28
 
7.0%
7 26
 
6.5%
9 25
 
6.3%
8 13
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 3
42.9%
A 2
28.6%
P 1
 
14.3%
T 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 13
86.7%
? 2
 
13.3%
Space Separator
ValueCountFrequency (%)
359
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1225
59.4%
Common 831
40.3%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 92
 
7.5%
등 91
 
7.4%
영 91
 
7.4%
동 83
 
6.8%
울 81
 
6.6%
서 81
 
6.6%
시 80
 
6.5%
구 80
 
6.5%
별 80
 
6.5%
특 80
 
6.5%
Other values (89) 386
31.5%
Common
ValueCountFrequency (%)
359
43.2%
1 92
 
11.1%
- 49
 
5.9%
4 48
 
5.8%
3 47
 
5.7%
2 47
 
5.7%
5 39
 
4.7%
6 33
 
4.0%
0 28
 
3.4%
7 26
 
3.1%
Other values (7) 63
 
7.6%
Latin
ValueCountFrequency (%)
B 3
42.9%
A 2
28.6%
P 1
 
14.3%
T 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1225
59.4%
ASCII 838
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
359
42.8%
1 92
 
11.0%
- 49
 
5.8%
4 48
 
5.7%
3 47
 
5.6%
2 47
 
5.6%
5 39
 
4.7%
6 33
 
3.9%
0 28
 
3.3%
7 26
 
3.1%
Other values (11) 70
 
8.4%
Hangul
ValueCountFrequency (%)
포 92
 
7.5%
등 91
 
7.4%
영 91
 
7.4%
동 83
 
6.8%
울 81
 
6.6%
서 81
 
6.6%
시 80
 
6.5%
구 80
 
6.5%
별 80
 
6.5%
특 80
 
6.5%
Other values (89) 386
31.5%

도로명주소
Text

MISSING 

Distinct59
Distinct (%)98.3%
Missing22
Missing (%)26.8%
Memory size788.0 B
2024-04-06T19:18:20.728023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length49
Mean length32.716667
Min length23

Characters and Unicode

Total characters1963
Distinct characters123
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)96.7%

Sample

1st row서울특별시 영등포구 경인로 862 (영등포동)
2nd row서울특별시 영등포구 선유로 156 (양평동3가)
3rd row서울특별시 영등포구 가마산로69가길 17 (신길동)
4th row서울특별시 영등포구 대방천로 180 (신길동, 우성2차아파트)
5th row서울특별시 영등포구 국제금융로7길 15 (여의도동)
ValueCountFrequency (%)
서울특별시 60
 
16.9%
영등포구 60
 
16.9%
1층 16
 
4.5%
신길동 9
 
2.5%
대림동 8
 
2.3%
당산로 7
 
2.0%
여의도동 6
 
1.7%
지하1층 5
 
1.4%
영중로 5
 
1.4%
당산동5가 4
 
1.1%
Other values (133) 174
49.2%
2024-04-06T19:18:21.428895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
294
 
15.0%
1 93
 
4.7%
영 82
 
4.2%
포 75
 
3.8%
등 74
 
3.8%
동 65
 
3.3%
로 62
 
3.2%
( 62
 
3.2%
시 62
 
3.2%
서 61
 
3.1%
Other values (113) 1033
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1180
60.1%
Space Separator 294
 
15.0%
Decimal Number 293
 
14.9%
Open Punctuation 62
 
3.2%
Close Punctuation 61
 
3.1%
Other Punctuation 58
 
3.0%
Uppercase Letter 12
 
0.6%
Math Symbol 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 82
 
6.9%
포 75
 
6.4%
등 74
 
6.3%
동 65
 
5.5%
로 62
 
5.3%
시 62
 
5.3%
서 61
 
5.2%
구 60
 
5.1%
별 60
 
5.1%
울 60
 
5.1%
Other values (92) 519
44.0%
Decimal Number
ValueCountFrequency (%)
1 93
31.7%
2 46
15.7%
3 33
 
11.3%
0 26
 
8.9%
6 20
 
6.8%
4 18
 
6.1%
5 17
 
5.8%
9 16
 
5.5%
8 13
 
4.4%
7 11
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 8
66.7%
I 1
 
8.3%
F 1
 
8.3%
C 1
 
8.3%
A 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 56
96.6%
? 2
 
3.4%
Space Separator
ValueCountFrequency (%)
294
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1180
60.1%
Common 771
39.3%
Latin 12
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 82
 
6.9%
포 75
 
6.4%
등 74
 
6.3%
동 65
 
5.5%
로 62
 
5.3%
시 62
 
5.3%
서 61
 
5.2%
구 60
 
5.1%
별 60
 
5.1%
울 60
 
5.1%
Other values (92) 519
44.0%
Common
ValueCountFrequency (%)
294
38.1%
1 93
 
12.1%
( 62
 
8.0%
) 61
 
7.9%
, 56
 
7.3%
2 46
 
6.0%
3 33
 
4.3%
0 26
 
3.4%
6 20
 
2.6%
4 18
 
2.3%
Other values (6) 62
 
8.0%
Latin
ValueCountFrequency (%)
B 8
66.7%
I 1
 
8.3%
F 1
 
8.3%
C 1
 
8.3%
A 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1180
60.1%
ASCII 783
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
294
37.5%
1 93
 
11.9%
( 62
 
7.9%
) 61
 
7.8%
, 56
 
7.2%
2 46
 
5.9%
3 33
 
4.2%
0 26
 
3.3%
6 20
 
2.6%
4 18
 
2.3%
Other values (11) 74
 
9.5%
Hangul
ValueCountFrequency (%)
영 82
 
6.9%
포 75
 
6.4%
등 74
 
6.3%
동 65
 
5.5%
로 62
 
5.3%
시 62
 
5.3%
서 61
 
5.2%
구 60
 
5.1%
별 60
 
5.1%
울 60
 
5.1%
Other values (92) 519
44.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)76.3%
Missing23
Missing (%)28.0%
Infinite0
Infinite (%)0.0%
Mean7316.5254
Minimum7207
Maximum7442
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-06T19:18:21.665407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7207
5-th percentile7213.9
Q17267
median7305
Q37371.5
95-th percentile7435.5
Maximum7442
Range235
Interquartile range (IQR)104.5

Descriptive statistics

Standard deviation71.041114
Coefficient of variation (CV)0.0097096791
Kurtosis-1.0359792
Mean7316.5254
Median Absolute Deviation (MAD)55
Skewness0.25373585
Sum431675
Variance5046.8399
MonotonicityNot monotonic
2024-04-06T19:18:21.970574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
7214 4
 
4.9%
7275 3
 
3.7%
7305 3
 
3.7%
7440 2
 
2.4%
7264 2
 
2.4%
7297 2
 
2.4%
7255 2
 
2.4%
7280 2
 
2.4%
7366 2
 
2.4%
7387 2
 
2.4%
Other values (35) 35
42.7%
(Missing) 23
28.0%
ValueCountFrequency (%)
7207 1
 
1.2%
7212 1
 
1.2%
7213 1
 
1.2%
7214 4
4.9%
7228 1
 
1.2%
7233 1
 
1.2%
7236 1
 
1.2%
7246 1
 
1.2%
7255 2
2.4%
7264 2
2.4%
ValueCountFrequency (%)
7442 1
1.2%
7440 2
2.4%
7435 1
1.2%
7434 1
1.2%
7424 1
1.2%
7420 1
1.2%
7413 1
1.2%
7412 1
1.2%
7411 1
1.2%
7403 1
1.2%

사업장명
Text

Distinct81
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size788.0 B
2024-04-06T19:18:22.351534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length9.195122
Min length3

Characters and Unicode

Total characters754
Distinct characters173
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)97.6%

Sample

1st row(주)신세계(영등포점)
2nd row롯데백화점영등포점
3rd row(주)경방유통필마트
4th row(주)코스트코코리아
5th row삼미마트
ValueCountFrequency (%)
기흥할인마트 2
 
1.8%
영등포점 2
 
1.8%
아크로리마트 2
 
1.8%
홈플러스 2
 
1.8%
영등포농협 2
 
1.8%
주)이마트 2
 
1.8%
익스프레스 2
 
1.8%
씨티대형할인마트 1
 
0.9%
미래로마트 1
 
0.9%
타임스퀘어점 1
 
0.9%
Other values (93) 93
84.5%
2024-04-06T19:18:23.059772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 49
 
6.5%
트 48
 
6.4%
( 38
 
5.0%
) 38
 
5.0%
주 35
 
4.6%
점 28
 
3.7%
28
 
3.7%
스 20
 
2.7%
로 14
 
1.9%
인 13
 
1.7%
Other values (163) 443
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 622
82.5%
Open Punctuation 38
 
5.0%
Close Punctuation 38
 
5.0%
Space Separator 28
 
3.7%
Uppercase Letter 19
 
2.5%
Decimal Number 7
 
0.9%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 49
 
7.9%
트 48
 
7.7%
주 35
 
5.6%
점 28
 
4.5%
스 20
 
3.2%
로 14
 
2.3%
인 13
 
2.1%
리 13
 
2.1%
영 12
 
1.9%
포 11
 
1.8%
Other values (141) 379
60.9%
Uppercase Letter
ValueCountFrequency (%)
S 3
15.8%
E 2
10.5%
U 2
10.5%
H 2
10.5%
G 2
10.5%
Y 1
 
5.3%
L 1
 
5.3%
O 1
 
5.3%
I 1
 
5.3%
A 1
 
5.3%
Other values (3) 3
15.8%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
0 2
28.6%
4 1
14.3%
3 1
14.3%
1 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 622
82.5%
Common 113
 
15.0%
Latin 19
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 49
 
7.9%
트 48
 
7.7%
주 35
 
5.6%
점 28
 
4.5%
스 20
 
3.2%
로 14
 
2.3%
인 13
 
2.1%
리 13
 
2.1%
영 12
 
1.9%
포 11
 
1.8%
Other values (141) 379
60.9%
Latin
ValueCountFrequency (%)
S 3
15.8%
E 2
10.5%
U 2
10.5%
H 2
10.5%
G 2
10.5%
Y 1
 
5.3%
L 1
 
5.3%
O 1
 
5.3%
I 1
 
5.3%
A 1
 
5.3%
Other values (3) 3
15.8%
Common
ValueCountFrequency (%)
( 38
33.6%
) 38
33.6%
28
24.8%
2 2
 
1.8%
0 2
 
1.8%
- 2
 
1.8%
4 1
 
0.9%
3 1
 
0.9%
1 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 622
82.5%
ASCII 132
 
17.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 49
 
7.9%
트 48
 
7.7%
주 35
 
5.6%
점 28
 
4.5%
스 20
 
3.2%
로 14
 
2.3%
인 13
 
2.1%
리 13
 
2.1%
영 12
 
1.9%
포 11
 
1.8%
Other values (141) 379
60.9%
ASCII
ValueCountFrequency (%)
( 38
28.8%
) 38
28.8%
28
21.2%
S 3
 
2.3%
E 2
 
1.5%
U 2
 
1.5%
H 2
 
1.5%
G 2
 
1.5%
2 2
 
1.5%
0 2
 
1.5%
Other values (12) 13
 
9.8%

최종수정일자
Date

Distinct81
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2000-06-03 00:00:00
Maximum2024-03-22 15:54:25
2024-04-06T19:18:23.421473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:18:23.696133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
I
41 
U
41 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 41
50.0%
U 41
50.0%

Length

2024-04-06T19:18:23.928445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:24.101002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 41
50.0%
u 41
50.0%

데이터갱신일자
Date

Distinct38
Distinct (%)46.3%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 22:04:00
2024-04-06T19:18:24.278288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:18:24.493399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
기타식품판매업
82 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 82
100.0%

Length

2024-04-06T19:18:24.702834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:24.899831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 82
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)74.7%
Missing3
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean191389.38
Minimum189682.02
Maximum194037.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-06T19:18:25.103198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189682.02
5-th percentile189774.62
Q1190721.42
median191292.1
Q3191936.25
95-th percentile193333.55
Maximum194037.75
Range4355.7281
Interquartile range (IQR)1214.8364

Descriptive statistics

Standard deviation1040.053
Coefficient of variation (CV)0.0054342251
Kurtosis-0.11376527
Mean191389.38
Median Absolute Deviation (MAD)618.68625
Skewness0.4180891
Sum15119761
Variance1081710.2
MonotonicityNot monotonic
2024-04-06T19:18:25.387410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189682.022243843 4
 
4.9%
191800.728214995 3
 
3.7%
191695.825238839 3
 
3.7%
191292.095160096 2
 
2.4%
190026.251961332 2
 
2.4%
189825.743146319 2
 
2.4%
190023.489432904 2
 
2.4%
191186.037189337 2
 
2.4%
192702.306288108 2
 
2.4%
191936.254364904 2
 
2.4%
Other values (49) 55
67.1%
(Missing) 3
 
3.7%
ValueCountFrequency (%)
189682.022243843 4
4.9%
189784.908763399 1
 
1.2%
189825.743146319 2
2.4%
190023.489432904 2
2.4%
190026.251961332 2
2.4%
190094.718810574 1
 
1.2%
190352.321686588 1
 
1.2%
190408.509134733 1
 
1.2%
190441.438606274 1
 
1.2%
190517.537006329 1
 
1.2%
ValueCountFrequency (%)
194037.750337785 1
1.2%
193882.109246282 1
1.2%
193592.000380036 1
1.2%
193393.096553574 1
1.2%
193326.931018911 1
1.2%
193209.283508484 1
1.2%
193034.345962851 1
1.2%
192912.017339528 1
1.2%
192702.306288108 2
2.4%
192643.702398007 1
1.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)74.7%
Missing3
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean445785.48
Minimum443228.35
Maximum448446.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-06T19:18:25.667795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum443228.35
5-th percentile443236.06
Q1444684.07
median446108.81
Q3446848.31
95-th percentile447892.08
Maximum448446.99
Range5218.6386
Interquartile range (IQR)2164.2375

Descriptive statistics

Standard deviation1419.1342
Coefficient of variation (CV)0.0031834465
Kurtosis-1.0168507
Mean445785.48
Median Absolute Deviation (MAD)993.29255
Skewness-0.24368649
Sum35217053
Variance2013942
MonotonicityNot monotonic
2024-04-06T19:18:25.975330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446823.857632163 4
 
4.9%
443809.773854649 3
 
3.7%
443228.349006844 3
 
3.7%
447892.078672003 2
 
2.4%
447067.240942159 2
 
2.4%
446574.176568125 2
 
2.4%
445809.666850503 2
 
2.4%
447739.896956998 2
 
2.4%
445115.514647066 2
 
2.4%
444885.168731883 2
 
2.4%
Other values (49) 55
67.1%
(Missing) 3
 
3.7%
ValueCountFrequency (%)
443228.349006844 3
3.7%
443236.05842825 2
2.4%
443681.766720649 2
2.4%
443809.773854649 3
3.7%
443878.031701894 1
 
1.2%
443891.073398846 1
 
1.2%
443960.892847166 1
 
1.2%
443978.484843886 1
 
1.2%
444009.578984371 1
 
1.2%
444095.513999748 1
 
1.2%
ValueCountFrequency (%)
448446.987591306 1
1.2%
448011.260506161 1
1.2%
447965.645513185 1
1.2%
447892.078672003 2
2.4%
447776.853735474 1
1.2%
447739.896956998 2
2.4%
447649.476828035 1
1.2%
447298.022173646 1
1.2%
447295.194165729 1
1.2%
447289.548355449 1
1.2%

위생업태명
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
기타식품판매업
57 
<NA>
25 

Length

Max length7
Median length7
Mean length6.0853659
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 57
69.5%
<NA> 25
30.5%

Length

2024-04-06T19:18:26.258041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:26.446922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 57
69.5%
na 25
30.5%

남성종사자수
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
57 
<NA>
25 

Length

Max length4
Median length1
Mean length1.9146341
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 57
69.5%
<NA> 25
30.5%

Length

2024-04-06T19:18:26.667314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:26.834916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 57
69.5%
na 25
30.5%

여성종사자수
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
57 
<NA>
25 

Length

Max length4
Median length1
Mean length1.9146341
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 57
69.5%
<NA> 25
30.5%

Length

2024-04-06T19:18:27.012330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:27.228445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 57
69.5%
na 25
30.5%

영업장주변구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
<NA>
75 
기타
 
7

Length

Max length4
Median length4
Mean length3.8292683
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 75
91.5%
기타 7
 
8.5%

Length

2024-04-06T19:18:27.437974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:27.671823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 75
91.5%
기타 7
 
8.5%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
<NA>
75 
기타
 
5
자율
 
2

Length

Max length4
Median length4
Mean length3.8292683
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 75
91.5%
기타 5
 
6.1%
자율 2
 
2.4%

Length

2024-04-06T19:18:27.939181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:28.208584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 75
91.5%
기타 5
 
6.1%
자율 2
 
2.4%

급수시설구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing80
Missing (%)97.6%
Memory size788.0 B
2024-04-06T19:18:28.411395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상수도전용
2nd row상수도전용
ValueCountFrequency (%)
상수도전용 2
100.0%
2024-04-06T19:18:28.954123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 2
20.0%
수 2
20.0%
도 2
20.0%
전 2
20.0%
용 2
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 2
20.0%
수 2
20.0%
도 2
20.0%
전 2
20.0%
용 2
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 2
20.0%
수 2
20.0%
도 2
20.0%
전 2
20.0%
용 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 2
20.0%
수 2
20.0%
도 2
20.0%
전 2
20.0%
용 2
20.0%

총인원
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
57 
<NA>
25 

Length

Max length4
Median length1
Mean length1.9146341
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 57
69.5%
<NA> 25
30.5%

Length

2024-04-06T19:18:29.195609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:29.380696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 57
69.5%
na 25
30.5%

본사종업원수
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
57 
<NA>
25 

Length

Max length4
Median length1
Mean length1.9146341
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 57
69.5%
<NA> 25
30.5%

Length

2024-04-06T19:18:29.578036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:29.815270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 57
69.5%
na 25
30.5%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
57 
<NA>
25 

Length

Max length4
Median length1
Mean length1.9146341
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 57
69.5%
<NA> 25
30.5%

Length

2024-04-06T19:18:30.031025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:30.222193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 57
69.5%
na 25
30.5%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
57 
<NA>
25 

Length

Max length4
Median length1
Mean length1.9146341
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 57
69.5%
<NA> 25
30.5%

Length

2024-04-06T19:18:30.381021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:30.567875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 57
69.5%
na 25
30.5%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
57 
<NA>
25 

Length

Max length4
Median length1
Mean length1.9146341
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 57
69.5%
<NA> 25
30.5%

Length

2024-04-06T19:18:31.126513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:31.304214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 57
69.5%
na 25
30.5%

건물소유구분명
Categorical

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
<NA>
50 
자가
17 
임대
15 

Length

Max length4
Median length4
Mean length3.2195122
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> 50
61.0%
자가 17
 
20.7%
임대 15
 
18.3%

Length

2024-04-06T19:18:31.556063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:31.759077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
61.0%
자가 17
 
20.7%
임대 15
 
18.3%

보증액
Categorical

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
56 
<NA>
25 
300000000
 
1

Length

Max length9
Median length1
Mean length2.0121951
Min length1

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 56
68.3%
<NA> 25
30.5%
300000000 1
 
1.2%

Length

2024-04-06T19:18:31.964195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:32.163345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 56
68.3%
na 25
30.5%
300000000 1
 
1.2%

월세액
Categorical

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
56 
<NA>
25 
12000000
 
1

Length

Max length8
Median length1
Mean length2
Min length1

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 56
68.3%
<NA> 25
30.5%
12000000 1
 
1.2%

Length

2024-04-06T19:18:32.381027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:32.570262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 56
68.3%
na 25
30.5%
12000000 1
 
1.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.8%
Missing25
Missing (%)30.5%
Memory size296.0 B
False
57 
(Missing)
25 
ValueCountFrequency (%)
False 57
69.5%
(Missing) 25
30.5%
2024-04-06T19:18:32.704392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

Distinct4
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
55 
<NA>
25 
330
 
1
363
 
1

Length

Max length4
Median length1
Mean length1.9634146
Min length1

Unique

Unique2 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 55
67.1%
<NA> 25
30.5%
330 1
 
1.2%
363 1
 
1.2%

Length

2024-04-06T19:18:32.892507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:18:33.103722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 55
67.1%
na 25
30.5%
330 1
 
1.2%
363 1
 
1.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031800003180000-114-1990-0000119900820<NA>3폐업2폐업20081208<NA><NA><NA>6761234950.44150034서울특별시 영등포구 영등포동4가 434-5<NA><NA>(주)신세계(영등포점)2004-03-23 00:00:00I2018-08-31 23:59:59.0기타식품판매업191581.500266446108.807193기타식품판매업00<NA><NA><NA>00000<NA>00N0<NA><NA><NA>
131800003180000-114-1991-0000119910503<NA>1영업/정상1영업<NA><NA><NA><NA>267080101,709.10150899서울특별시 영등포구 영등포동 618-496서울특별시 영등포구 경인로 862 (영등포동)7306롯데백화점영등포점2022-04-06 16:46:21U2021-12-04 00:08:00.0기타식품판매업191741.345848445970.307641<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231800003180000-114-1994-0063819940826<NA>3폐업2폐업20080307<NA><NA><NA>02263060003,741.43150034서울특별시 영등포구 영등포동4가 441-21<NA><NA>(주)경방유통필마트2005-05-30 00:00:00I2018-08-31 23:59:59.0기타식품판매업<NA><NA>기타식품판매업00기타기타<NA>00000<NA>00N0<NA><NA><NA>
331800003180000-114-1994-0063919941007<NA>1영업/정상1영업<NA><NA><NA><NA>02189999003,859.31150103서울특별시 영등포구 양평동3가 65서울특별시 영등포구 선유로 156 (양평동3가)7255(주)코스트코코리아2015-12-02 14:55:47I2018-08-31 23:59:59.0기타식품판매업190408.509135447298.022174기타식품판매업00<NA><NA><NA>00000<NA>00N0<NA><NA><NA>
431800003180000-114-1996-0049219960628<NA>3폐업2폐업20061208<NA><NA><NA><NA>367.88150849서울특별시 영등포구 신길동 364-0<NA><NA>삼미마트2006-12-11 00:00:00I2018-08-31 23:59:59.0기타식품판매업191202.282286444841.059497기타식품판매업00기타자율<NA>00000<NA>00N0<NA><NA><NA>
531800003180000-114-1996-0050919960830<NA>3폐업2폐업20000603<NA><NA><NA>02534.28150814서울특별시 영등포구 대림동 717-0<NA><NA>삼양유통싱싱마트대리점2000-06-03 00:00:00I2018-08-31 23:59:59.0기타식품판매업190916.911378443681.766721기타식품판매업00기타자율상수도전용00000<NA>00N0<NA><NA><NA>
631800003180000-114-1996-0053119960528<NA>3폐업2폐업20190416<NA><NA><NA>02 8320058894.64150841서울특별시 영등포구 신길동 255-9서울특별시 영등포구 가마산로69가길 17 (신길동)7387(주)사러가2019-04-16 15:33:40U2019-04-18 02:40:00.0기타식품판매업191994.505087444933.158732기타식품판매업00기타기타<NA>00000<NA>00N0<NA><NA><NA>
731800003180000-114-1996-0066019960416<NA>3폐업2폐업20080103<NA><NA><NA>02 8358363653.97150816서울특별시 영등포구 대림동 784-0 784-2<NA><NA>(주)비에스마트2006-03-15 00:00:00I2018-08-31 23:59:59.0기타식품판매업190721.417932444571.769294기타식품판매업00기타기타<NA>00000<NA>00N0<NA><NA><NA>
831800003180000-114-1996-0081719960628<NA>3폐업2폐업20221017<NA><NA><NA>02462.39150860서울특별시 영등포구 신길동 4518 우성2차아파트서울특별시 영등포구 대방천로 180 (신길동, 우성2차아파트)7435우성마트2022-10-17 20:43:57U2021-10-30 23:09:00.0기타식품판매업192197.464636444009.578984<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
931800003180000-114-1996-0081819960528<NA>1영업/정상1영업<NA><NA><NA><NA>0220062356561.18150882서울특별시 영등포구 여의도동 30-3서울특별시 영등포구 국제금융로7길 15 (여의도동)7338(주)지에스리테일GS수퍼여의도점2020-08-27 09:21:33U2020-08-29 02:40:00.0기타식품판매업193882.109246446872.758718기타식품판매업00<NA><NA><NA>00000<NA>00N0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
7231800003180000-114-2020-000012020-02-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>463.35150-092서울특별시 영등포구 문래동2가 26서울특별시 영등포구 경인로 719, 1층 (문래동2가)7289영등포농협 하나로마트 경인로지점2023-03-30 15:28:21U2022-12-04 00:01:00.0기타식품판매업190517.537006445552.828151<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7331800003180000-114-2020-0000220200311<NA>1영업/정상1영업<NA><NA><NA><NA>0226366003603.45150045서울특별시 영등포구 당산동5가 11-33 당산디오빌서울특별시 영등포구 당산로 222, 지하1층 B102~B109호 (당산동5가, 당산디오빌)7214아크로리마트 당산점2022-01-20 11:17:26U2022-01-22 02:40:00.0기타식품판매업191292.09516447892.078672기타식품판매업00<NA><NA><NA>00000<NA>00N0<NA><NA><NA>
7431800003180000-114-2020-0000320200831<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2,310.00150820서울특별시 영등포구 대림동 909-2 썬프라자서울특별시 영등포구 신길로 39, 썬프라자 1,2층 (대림동)7440뉴썬프라자마트2022-09-27 14:38:49U2021-12-08 22:09:00.0기타식품판매업191800.728215443809.773855<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7531800003180000-114-2021-000012021-02-15<NA>1영업/정상1영업<NA><NA><NA><NA>02327707231637.00150-875서울특별시 영등포구 여의도동 22 파크원(백화점) 지1층서울특별시 영등포구 여의대로 108, 파크원(백화점) 지1층 (여의도동)7335THE HYUNDAI SEOUL(더현대서울)2024-03-22 15:54:25U2023-12-02 22:04:00.0기타식품판매업193592.00038447092.629433<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7631800003180000-114-2021-000022021-08-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>439.90150-899서울특별시 영등포구 영등포동 621서울특별시 영등포구 영신로9라길 2, 1층 (영등포동)7366홈마트2023-08-31 10:17:40U2022-12-09 00:02:00.0기타식품판매업191629.915867445606.119529<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7731800003180000-114-2021-0000320211020<NA>1영업/정상1영업<NA><NA><NA><NA>0226331700720.00150042서울특별시 영등포구 당산동2가 1서울특별시 영등포구 당산로 63, 1층 (당산동2가)7291(주)대하식자재마트2022-11-28 10:18:59U2021-10-31 21:00:00.0기타식품판매업190649.273834446497.29923<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7831800003180000-114-2021-000042021-10-25<NA>3폐업2폐업2023-03-21<NA><NA><NA><NA>327.52150-945서울특별시 영등포구 여의도동 23 서울 국제금융 센터서울특별시 영등포구 국제금융로 10, IFC몰 지하3층 309호 (여의도동)7326씨제이더마켓(그로서리)2023-03-21 14:21:16U2022-12-02 22:03:00.0기타식품판매업193326.931019446973.91457<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7931800003180000-114-2022-000012022-01-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>561.40150-861서울특별시 영등포구 신길동 4902-6서울특별시 영등포구 신길로 162, 1층 (신길동)7362(주)지에스리테일 GS더프레시 신길사러가점2023-11-27 20:15:28U2022-10-31 22:09:00.0기타식품판매업192108.925859444944.153786<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8031800003180000-114-2023-000012023-04-10<NA>1영업/정상1영업<NA><NA><NA><NA>0226778877350.00150-102서울특별시 영등포구 양평동2가 37-2서울특별시 영등포구 영등포로 21, 1층 (양평동2가)7275대흥할인마트2023-04-10 13:35:03I2022-12-03 23:02:00.0기타식품판매업189682.022244446823.857632<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8131800003180000-114-2023-000022023-08-31<NA>1영업/정상1영업<NA><NA><NA><NA>02 38058941075.82150-042서울특별시 영등포구 당산동2가 165 한화포레나당산서울특별시 영등포구 당산로 83, 판매시설동 B1층 B102,B103호 (당산동2가, 한화포레나당산)7264(주)이마트에브리데이 영등포구청역점2023-08-31 09:43:17I2022-12-09 00:02:00.0기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>