Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells103915
Missing cells (%)23.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 MiB
Average record size in memory382.0 B

Variable types

Categorical18
Text9
DateTime4
Unsupported6
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-18670/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
전통업소주된음식 has constant value ""Constant
다중이용업소여부 is highly imbalanced (75.0%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2341 (23.4%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 3528 (35.3%) missing valuesMissing
소재지면적 has 532 (5.3%) missing valuesMissing
도로명주소 has 5034 (50.3%) missing valuesMissing
도로명우편번호 has 5169 (51.7%) missing valuesMissing
좌표정보(X) has 422 (4.2%) missing valuesMissing
좌표정보(Y) has 422 (4.2%) missing valuesMissing
남성종사자수 has 1616 (16.2%) missing valuesMissing
여성종사자수 has 1616 (16.2%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1616 (16.2%) missing valuesMissing
시설총규모 has 1616 (16.2%) missing valuesMissing
전통업소지정번호 has 9996 (> 99.9%) missing valuesMissing
전통업소주된음식 has 9999 (> 99.9%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = -22.7888603)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 7124 (71.2%) zerosZeros
여성종사자수 has 6597 (66.0%) zerosZeros
시설총규모 has 544 (5.4%) zerosZeros

Reproduction

Analysis started2024-05-11 06:36:38.280697
Analysis finished2024-05-11 06:36:43.018224
Duration4.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3180000
10000 

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 10000
100.0%

Length

2024-05-11T15:36:43.170497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:43.334509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:36:43.627291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row3180000-101-1996-08978
2nd row3180000-101-1997-00076
3rd row3180000-101-1999-12026
4th row3180000-101-1996-00089
5th row3180000-101-2003-00450
ValueCountFrequency (%)
3180000-101-1996-08978 1
 
< 0.1%
3180000-101-2002-00345 1
 
< 0.1%
3180000-101-1985-04530 1
 
< 0.1%
3180000-101-1986-05782 1
 
< 0.1%
3180000-101-2013-00141 1
 
< 0.1%
3180000-101-2000-14146 1
 
< 0.1%
3180000-101-2019-00577 1
 
< 0.1%
3180000-101-1995-09068 1
 
< 0.1%
3180000-101-2009-00124 1
 
< 0.1%
3180000-101-2012-00214 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T15:36:44.239368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 77362
35.2%
1 43064
19.6%
- 30000
 
13.6%
3 14936
 
6.8%
8 14877
 
6.8%
2 11937
 
5.4%
9 10293
 
4.7%
4 4920
 
2.2%
5 4415
 
2.0%
6 4142
 
1.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 77362
40.7%
1 43064
22.7%
3 14936
 
7.9%
8 14877
 
7.8%
2 11937
 
6.3%
9 10293
 
5.4%
4 4920
 
2.6%
5 4415
 
2.3%
6 4142
 
2.2%
7 4054
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 77362
35.2%
1 43064
19.6%
- 30000
 
13.6%
3 14936
 
6.8%
8 14877
 
6.8%
2 11937
 
5.4%
9 10293
 
4.7%
4 4920
 
2.2%
5 4415
 
2.0%
6 4142
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 77362
35.2%
1 43064
19.6%
- 30000
 
13.6%
3 14936
 
6.8%
8 14877
 
6.8%
2 11937
 
5.4%
9 10293
 
4.7%
4 4920
 
2.2%
5 4415
 
2.0%
6 4142
 
1.9%

인허가일자
Date

Distinct6201
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1909-02-10 00:00:00
Maximum2023-02-21 00:00:00
2024-05-11T15:36:44.571660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:44.932161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
7659 
1
2341 

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 7659
76.6%
1 2341
 
23.4%

Length

2024-05-11T15:36:45.276049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:45.479267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7659
76.6%
1 2341
 
23.4%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7659 
영업/정상
2341 

Length

Max length5
Median length2
Mean length2.7023
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7659
76.6%
영업/정상 2341
 
23.4%

Length

2024-05-11T15:36:45.706504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:45.929717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7659
76.6%
영업/정상 2341
 
23.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7659 
1
2341 

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 7659
76.6%
1 2341
 
23.4%

Length

2024-05-11T15:36:46.191340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:46.413694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7659
76.6%
1 2341
 
23.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7659 
영업
2341 

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 7659
76.6%
영업 2341
 
23.4%

Length

2024-05-11T15:36:46.650696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:46.938339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7659
76.6%
영업 2341
 
23.4%

폐업일자
Date

MISSING 

Distinct4263
Distinct (%)55.7%
Missing2341
Missing (%)23.4%
Memory size156.2 KiB
Minimum1984-12-05 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:36:47.240979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:47.705655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전화번호
Text

MISSING 

Distinct5678
Distinct (%)87.7%
Missing3528
Missing (%)35.3%
Memory size156.2 KiB
2024-05-11T15:36:48.390344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.473733
Min length2

Characters and Unicode

Total characters61314
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5569 ?
Unique (%)86.0%

Sample

1st row02 6793813
2nd row0208474619
3rd row02 6310266
4th row0226776601
5th row02
ValueCountFrequency (%)
02 3217
33.6%
0200000000 108
 
1.1%
831 32
 
0.3%
070 27
 
0.3%
761 25
 
0.3%
833 21
 
0.2%
780 20
 
0.2%
842 18
 
0.2%
844 16
 
0.2%
832 15
 
0.2%
Other values (5757) 6078
63.5%
2024-05-11T15:36:49.353160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11996
19.6%
2 10858
17.7%
8 5950
9.7%
6 5633
9.2%
7 5133
8.4%
3 5108
8.3%
4 3913
 
6.4%
3827
 
6.2%
5 3187
 
5.2%
1 3023
 
4.9%
Other values (3) 2686
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57480
93.7%
Space Separator 3827
 
6.2%
Dash Punctuation 6
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11996
20.9%
2 10858
18.9%
8 5950
10.4%
6 5633
9.8%
7 5133
8.9%
3 5108
8.9%
4 3913
 
6.8%
5 3187
 
5.5%
1 3023
 
5.3%
9 2679
 
4.7%
Space Separator
ValueCountFrequency (%)
3827
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61314
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11996
19.6%
2 10858
17.7%
8 5950
9.7%
6 5633
9.2%
7 5133
8.4%
3 5108
8.3%
4 3913
 
6.4%
3827
 
6.2%
5 3187
 
5.2%
1 3023
 
4.9%
Other values (3) 2686
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61314
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11996
19.6%
2 10858
17.7%
8 5950
9.7%
6 5633
9.2%
7 5133
8.4%
3 5108
8.3%
4 3913
 
6.4%
3827
 
6.2%
5 3187
 
5.2%
1 3023
 
4.9%
Other values (3) 2686
 
4.4%

소재지면적
Text

MISSING 

Distinct4964
Distinct (%)52.4%
Missing532
Missing (%)5.3%
Memory size156.2 KiB
2024-05-11T15:36:50.220426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1591677
Min length3

Characters and Unicode

Total characters48847
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

Unique3366 ?
Unique (%)35.6%

Sample

1st row36.75
2nd row47.99
3rd row47.30
4th row155.37
5th row17.06
ValueCountFrequency (%)
33.00 85
 
0.9%
26.40 79
 
0.8%
66.00 73
 
0.8%
30.00 68
 
0.7%
23.10 51
 
0.5%
24.00 50
 
0.5%
19.80 46
 
0.5%
16.50 45
 
0.5%
49.50 44
 
0.5%
27.00 43
 
0.5%
Other values (4954) 8884
93.8%
2024-05-11T15:36:51.183778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9468
19.4%
0 7141
14.6%
2 5079
10.4%
1 4461
9.1%
3 3817
7.8%
4 3681
 
7.5%
6 3448
 
7.1%
5 3435
 
7.0%
8 2953
 
6.0%
9 2754
 
5.6%
Other values (2) 2610
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39358
80.6%
Other Punctuation 9489
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7141
18.1%
2 5079
12.9%
1 4461
11.3%
3 3817
9.7%
4 3681
9.4%
6 3448
8.8%
5 3435
8.7%
8 2953
7.5%
9 2754
 
7.0%
7 2589
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 9468
99.8%
, 21
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 48847
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9468
19.4%
0 7141
14.6%
2 5079
10.4%
1 4461
9.1%
3 3817
7.8%
4 3681
 
7.5%
6 3448
 
7.1%
5 3435
 
7.0%
8 2953
 
6.0%
9 2754
 
5.6%
Other values (2) 2610
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48847
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9468
19.4%
0 7141
14.6%
2 5079
10.4%
1 4461
9.1%
3 3817
7.8%
4 3681
 
7.5%
6 3448
 
7.1%
5 3435
 
7.0%
8 2953
 
6.0%
9 2754
 
5.6%
Other values (2) 2610
 
5.3%

소재지우편번호
Text

Distinct333
Distinct (%)3.3%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T15:36:51.891226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1047419
Min length6

Characters and Unicode

Total characters61023
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

Unique49 ?
Unique (%)0.5%

Sample

1st row150800
2nd row150070
3rd row150106
4th row150-033
5th row150837
ValueCountFrequency (%)
150033 438
 
4.4%
150841 372
 
3.7%
150803 241
 
2.4%
150070 223
 
2.2%
150890 205
 
2.1%
150800 202
 
2.0%
150034 185
 
1.9%
150037 177
 
1.8%
150815 171
 
1.7%
150899 167
 
1.7%
Other values (323) 7615
76.2%
2024-05-11T15:36:52.977379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15447
25.3%
1 12258
20.1%
5 11772
19.3%
8 7592
12.4%
3 3710
 
6.1%
9 2300
 
3.8%
4 2107
 
3.5%
7 1772
 
2.9%
6 1520
 
2.5%
2 1498
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59976
98.3%
Dash Punctuation 1047
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15447
25.8%
1 12258
20.4%
5 11772
19.6%
8 7592
12.7%
3 3710
 
6.2%
9 2300
 
3.8%
4 2107
 
3.5%
7 1772
 
3.0%
6 1520
 
2.5%
2 1498
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 1047
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61023
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15447
25.3%
1 12258
20.1%
5 11772
19.3%
8 7592
12.4%
3 3710
 
6.1%
9 2300
 
3.8%
4 2107
 
3.5%
7 1772
 
2.9%
6 1520
 
2.5%
2 1498
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61023
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15447
25.3%
1 12258
20.1%
5 11772
19.3%
8 7592
12.4%
3 3710
 
6.1%
9 2300
 
3.8%
4 2107
 
3.5%
7 1772
 
2.9%
6 1520
 
2.5%
2 1498
 
2.5%

지번주소
Text

Distinct8077
Distinct (%)80.8%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T15:36:53.495893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length57
Mean length27.609744
Min length18

Characters and Unicode

Total characters275987
Distinct characters440
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6935 ?
Unique (%)69.4%

Sample

1st row서울특별시 영등포구 당산동1가 90-0번지
2nd row서울특별시 영등포구 대림동 1081-0번지 33
3rd row서울특별시 영등포구 양평동6가 73-0번지
4th row서울특별시 영등포구 영등포동3가 15
5th row서울특별시 영등포구 신길동 2-3번지 삼두아파트상가1층1호
ValueCountFrequency (%)
서울특별시 9996
20.7%
영등포구 9995
20.7%
여의도동 1928
 
4.0%
대림동 1561
 
3.2%
신길동 1548
 
3.2%
1층 1043
 
2.2%
지상1층 543
 
1.1%
영등포동3가 481
 
1.0%
지하1층 390
 
0.8%
당산동3가 383
 
0.8%
Other values (6826) 20389
42.3%
2024-05-11T15:36:54.468777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46674
 
16.9%
1 12550
 
4.5%
영 11939
 
4.3%
포 11918
 
4.3%
등 11888
 
4.3%
동 10571
 
3.8%
시 10146
 
3.7%
서 10082
 
3.7%
울 10045
 
3.6%
구 10017
 
3.6%
Other values (430) 130157
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167066
60.5%
Decimal Number 51680
 
18.7%
Space Separator 46674
 
16.9%
Dash Punctuation 8731
 
3.2%
Uppercase Letter 611
 
0.2%
Other Punctuation 478
 
0.2%
Open Punctuation 297
 
0.1%
Close Punctuation 296
 
0.1%
Lowercase Letter 82
 
< 0.1%
Math Symbol 72
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 11939
 
7.1%
포 11918
 
7.1%
등 11888
 
7.1%
동 10571
 
6.3%
시 10146
 
6.1%
서 10082
 
6.0%
울 10045
 
6.0%
구 10017
 
6.0%
별 10002
 
6.0%
특 9996
 
6.0%
Other values (373) 60462
36.2%
Uppercase Letter
ValueCountFrequency (%)
B 167
27.3%
C 69
11.3%
S 61
 
10.0%
K 54
 
8.8%
A 39
 
6.4%
F 31
 
5.1%
E 26
 
4.3%
I 24
 
3.9%
T 24
 
3.9%
L 20
 
3.3%
Other values (12) 96
15.7%
Lowercase Letter
ValueCountFrequency (%)
e 21
25.6%
n 15
18.3%
r 10
12.2%
k 8
 
9.8%
c 7
 
8.5%
t 5
 
6.1%
o 4
 
4.9%
u 3
 
3.7%
i 2
 
2.4%
a 2
 
2.4%
Other values (3) 5
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 12550
24.3%
2 7218
14.0%
3 6536
12.6%
4 5397
10.4%
0 4475
 
8.7%
5 3971
 
7.7%
6 3526
 
6.8%
7 2889
 
5.6%
8 2600
 
5.0%
9 2518
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 404
84.5%
? 33
 
6.9%
. 33
 
6.9%
@ 4
 
0.8%
/ 2
 
0.4%
& 1
 
0.2%
: 1
 
0.2%
Space Separator
ValueCountFrequency (%)
46674
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8731
100.0%
Open Punctuation
ValueCountFrequency (%)
( 297
100.0%
Close Punctuation
ValueCountFrequency (%)
) 296
100.0%
Math Symbol
ValueCountFrequency (%)
~ 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167059
60.5%
Common 108228
39.2%
Latin 693
 
0.3%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 11939
 
7.1%
포 11918
 
7.1%
등 11888
 
7.1%
동 10571
 
6.3%
시 10146
 
6.1%
서 10082
 
6.0%
울 10045
 
6.0%
구 10017
 
6.0%
별 10002
 
6.0%
특 9996
 
6.0%
Other values (370) 60455
36.2%
Latin
ValueCountFrequency (%)
B 167
24.1%
C 69
 
10.0%
S 61
 
8.8%
K 54
 
7.8%
A 39
 
5.6%
F 31
 
4.5%
E 26
 
3.8%
I 24
 
3.5%
T 24
 
3.5%
e 21
 
3.0%
Other values (25) 177
25.5%
Common
ValueCountFrequency (%)
46674
43.1%
1 12550
 
11.6%
- 8731
 
8.1%
2 7218
 
6.7%
3 6536
 
6.0%
4 5397
 
5.0%
0 4475
 
4.1%
5 3971
 
3.7%
6 3526
 
3.3%
7 2889
 
2.7%
Other values (12) 6261
 
5.8%
Han
ValueCountFrequency (%)
罐 3
42.9%
紵 3
42.9%
平 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167057
60.5%
ASCII 108921
39.5%
CJK 7
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46674
42.9%
1 12550
 
11.5%
- 8731
 
8.0%
2 7218
 
6.6%
3 6536
 
6.0%
4 5397
 
5.0%
0 4475
 
4.1%
5 3971
 
3.6%
6 3526
 
3.2%
7 2889
 
2.7%
Other values (47) 6954
 
6.4%
Hangul
ValueCountFrequency (%)
영 11939
 
7.1%
포 11918
 
7.1%
등 11888
 
7.1%
동 10571
 
6.3%
시 10146
 
6.1%
서 10082
 
6.0%
울 10045
 
6.0%
구 10017
 
6.0%
별 10002
 
6.0%
특 9996
 
6.0%
Other values (368) 60453
36.2%
CJK
ValueCountFrequency (%)
罐 3
42.9%
紵 3
42.9%
平 1
 
14.3%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
50.0%
ㅡ 1
50.0%

도로명주소
Text

MISSING 

Distinct4667
Distinct (%)94.0%
Missing5034
Missing (%)50.3%
Memory size156.2 KiB
2024-05-11T15:36:54.994828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length62
Mean length35.908578
Min length23

Characters and Unicode

Total characters178322
Distinct characters428
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4436 ?
Unique (%)89.3%

Sample

1st row서울특별시 영등포구 영등포로46길 5, 1층 (영등포동3가)
2nd row서울특별시 영등포구 도신로29가길 11 (도림동)
3rd row서울특별시 영등포구 선유로 63, EEU동신타워 203호 (문래동6가)
4th row서울특별시 영등포구 시흥대로183길 8 (대림동)
5th row서울특별시 영등포구 신길로39길 1 (신길동)
ValueCountFrequency (%)
서울특별시 4966
 
15.5%
영등포구 4965
 
15.5%
1층 1635
 
5.1%
여의도동 826
 
2.6%
대림동 613
 
1.9%
지하1층 551
 
1.7%
신길동 539
 
1.7%
2층 325
 
1.0%
영등포로 193
 
0.6%
당산동3가 178
 
0.6%
Other values (3376) 17215
53.8%
2024-05-11T15:36:56.107456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27086
 
15.2%
1 9008
 
5.1%
영 6756
 
3.8%
포 6278
 
3.5%
등 6252
 
3.5%
동 5417
 
3.0%
, 5275
 
3.0%
( 5176
 
2.9%
) 5173
 
2.9%
시 5131
 
2.9%
Other values (418) 96770
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105292
59.0%
Decimal Number 28466
 
16.0%
Space Separator 27086
 
15.2%
Other Punctuation 5332
 
3.0%
Open Punctuation 5177
 
2.9%
Close Punctuation 5174
 
2.9%
Dash Punctuation 958
 
0.5%
Uppercase Letter 675
 
0.4%
Lowercase Letter 90
 
0.1%
Math Symbol 71
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 6756
 
6.4%
포 6278
 
6.0%
등 6252
 
5.9%
동 5417
 
5.1%
시 5131
 
4.9%
서 5126
 
4.9%
울 5046
 
4.8%
로 5022
 
4.8%
구 4980
 
4.7%
별 4972
 
4.7%
Other values (355) 50312
47.8%
Uppercase Letter
ValueCountFrequency (%)
B 216
32.0%
S 64
 
9.5%
C 59
 
8.7%
K 53
 
7.9%
A 48
 
7.1%
F 34
 
5.0%
E 28
 
4.1%
I 26
 
3.9%
T 22
 
3.3%
L 22
 
3.3%
Other values (13) 103
15.3%
Lowercase Letter
ValueCountFrequency (%)
e 24
26.7%
n 16
17.8%
r 11
12.2%
c 9
 
10.0%
k 8
 
8.9%
t 6
 
6.7%
u 5
 
5.6%
w 2
 
2.2%
o 2
 
2.2%
a 2
 
2.2%
Other values (4) 5
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 9008
31.6%
2 4108
14.4%
3 3306
 
11.6%
0 2398
 
8.4%
4 2133
 
7.5%
5 1744
 
6.1%
7 1678
 
5.9%
6 1652
 
5.8%
8 1363
 
4.8%
9 1076
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 5275
98.9%
? 25
 
0.5%
. 24
 
0.5%
# 3
 
0.1%
/ 2
 
< 0.1%
& 1
 
< 0.1%
@ 1
 
< 0.1%
* 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5176
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 5173
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
27086
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 958
100.0%
Math Symbol
ValueCountFrequency (%)
~ 71
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105288
59.0%
Common 72265
40.5%
Latin 765
 
0.4%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 6756
 
6.4%
포 6278
 
6.0%
등 6252
 
5.9%
동 5417
 
5.1%
시 5131
 
4.9%
서 5126
 
4.9%
울 5046
 
4.8%
로 5022
 
4.8%
구 4980
 
4.7%
별 4972
 
4.7%
Other values (353) 50308
47.8%
Latin
ValueCountFrequency (%)
B 216
28.2%
S 64
 
8.4%
C 59
 
7.7%
K 53
 
6.9%
A 48
 
6.3%
F 34
 
4.4%
E 28
 
3.7%
I 26
 
3.4%
e 24
 
3.1%
T 22
 
2.9%
Other values (27) 191
25.0%
Common
ValueCountFrequency (%)
27086
37.5%
1 9008
 
12.5%
, 5275
 
7.3%
( 5176
 
7.2%
) 5173
 
7.2%
2 4108
 
5.7%
3 3306
 
4.6%
0 2398
 
3.3%
4 2133
 
3.0%
5 1744
 
2.4%
Other values (16) 6858
 
9.5%
Han
ValueCountFrequency (%)
罐 2
50.0%
紵 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105288
59.0%
ASCII 73030
41.0%
CJK 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27086
37.1%
1 9008
 
12.3%
, 5275
 
7.2%
( 5176
 
7.1%
) 5173
 
7.1%
2 4108
 
5.6%
3 3306
 
4.5%
0 2398
 
3.3%
4 2133
 
2.9%
5 1744
 
2.4%
Other values (53) 7623
 
10.4%
Hangul
ValueCountFrequency (%)
영 6756
 
6.4%
포 6278
 
6.0%
등 6252
 
5.9%
동 5417
 
5.1%
시 5131
 
4.9%
서 5126
 
4.9%
울 5046
 
4.8%
로 5022
 
4.8%
구 4980
 
4.7%
별 4972
 
4.7%
Other values (353) 50308
47.8%
CJK
ValueCountFrequency (%)
罐 2
50.0%
紵 2
50.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct238
Distinct (%)4.9%
Missing5169
Missing (%)51.7%
Infinite0
Infinite (%)0.0%
Mean7314.9874
Minimum2857
Maximum7448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:36:56.351085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2857
5-th percentile7213
Q17259
median7306
Q37366
95-th percentile7431
Maximum7448
Range4591
Interquartile range (IQR)107

Descriptive statistics

Standard deviation92.884394
Coefficient of variation (CV)0.01269782
Kurtosis1097.5272
Mean7314.9874
Median Absolute Deviation (MAD)49
Skewness-22.78886
Sum35338704
Variance8627.5106
MonotonicityNot monotonic
2024-05-11T15:36:56.642592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7333 249
 
2.5%
7238 126
 
1.3%
7305 92
 
0.9%
7257 91
 
0.9%
7299 90
 
0.9%
7304 85
 
0.9%
7290 75
 
0.8%
7237 70
 
0.7%
7250 66
 
0.7%
7302 64
 
0.6%
Other values (228) 3823
38.2%
(Missing) 5169
51.7%
ValueCountFrequency (%)
2857 1
 
< 0.1%
7200 4
 
< 0.1%
7201 4
 
< 0.1%
7202 7
 
0.1%
7203 9
 
0.1%
7204 8
 
0.1%
7205 27
0.3%
7206 42
0.4%
7207 16
 
0.2%
7208 57
0.6%
ValueCountFrequency (%)
7448 9
 
0.1%
7447 12
 
0.1%
7446 5
 
0.1%
7445 18
0.2%
7444 13
0.1%
7443 29
0.3%
7442 32
0.3%
7441 4
 
< 0.1%
7440 8
 
0.1%
7439 11
 
0.1%

사업장명
Text

Distinct8562
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:36:57.246897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length5.4184
Min length1

Characters and Unicode

Total characters54184
Distinct characters1111
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7738 ?
Unique (%)77.4%

Sample

1st row양남식당
2nd row선희네숯불돼지갈비
3rd row돈바우식당
4th row카오스(chaos)
5th row이웃사랑
ValueCountFrequency (%)
영등포점 56
 
0.5%
여의도점 47
 
0.4%
전주식당 37
 
0.3%
문래점 23
 
0.2%
coffee 21
 
0.2%
여의도 18
 
0.2%
실내포장마차 15
 
0.1%
명동칼국수 13
 
0.1%
시골집 13
 
0.1%
호남식당 12
 
0.1%
Other values (9059) 10841
97.7%
2024-05-11T15:36:58.007782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 1577
 
2.9%
당 1299
 
2.4%
1110
 
2.0%
이 967
 
1.8%
점 953
 
1.8%
스 918
 
1.7%
리 678
 
1.3%
호 596
 
1.1%
) 577
 
1.1%
( 575
 
1.1%
Other values (1101) 44934
82.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48346
89.2%
Uppercase Letter 1776
 
3.3%
Space Separator 1110
 
2.0%
Lowercase Letter 1094
 
2.0%
Close Punctuation 577
 
1.1%
Open Punctuation 575
 
1.1%
Decimal Number 524
 
1.0%
Other Punctuation 156
 
0.3%
Dash Punctuation 15
 
< 0.1%
Letter Number 4
 
< 0.1%
Other values (4) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 1577
 
3.3%
당 1299
 
2.7%
이 967
 
2.0%
점 953
 
2.0%
스 918
 
1.9%
리 678
 
1.4%
호 596
 
1.2%
프 557
 
1.2%
마 555
 
1.1%
치 524
 
1.1%
Other values (1022) 39722
82.2%
Uppercase Letter
ValueCountFrequency (%)
E 157
 
8.8%
A 155
 
8.7%
O 147
 
8.3%
B 118
 
6.6%
S 111
 
6.2%
C 109
 
6.1%
R 98
 
5.5%
T 92
 
5.2%
I 91
 
5.1%
L 75
 
4.2%
Other values (16) 623
35.1%
Lowercase Letter
ValueCountFrequency (%)
e 158
14.4%
a 109
 
10.0%
o 98
 
9.0%
i 66
 
6.0%
n 65
 
5.9%
l 65
 
5.9%
r 61
 
5.6%
t 55
 
5.0%
f 53
 
4.8%
s 51
 
4.7%
Other values (15) 313
28.6%
Decimal Number
ValueCountFrequency (%)
2 99
18.9%
1 87
16.6%
0 60
11.5%
3 54
10.3%
9 44
8.4%
4 40
7.6%
5 39
 
7.4%
6 36
 
6.9%
8 34
 
6.5%
7 31
 
5.9%
Other Punctuation
ValueCountFrequency (%)
& 59
37.8%
. 49
31.4%
, 20
 
12.8%
' 11
 
7.1%
! 6
 
3.8%
? 6
 
3.8%
/ 3
 
1.9%
: 1
 
0.6%
# 1
 
0.6%
Space Separator
ValueCountFrequency (%)
1110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 577
100.0%
Open Punctuation
ValueCountFrequency (%)
( 575
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48294
89.1%
Common 2964
 
5.5%
Latin 2874
 
5.3%
Han 52
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 1577
 
3.3%
당 1299
 
2.7%
이 967
 
2.0%
점 953
 
2.0%
스 918
 
1.9%
리 678
 
1.4%
호 596
 
1.2%
프 557
 
1.2%
마 555
 
1.1%
치 524
 
1.1%
Other values (977) 39670
82.1%
Latin
ValueCountFrequency (%)
e 158
 
5.5%
E 157
 
5.5%
A 155
 
5.4%
O 147
 
5.1%
B 118
 
4.1%
S 111
 
3.9%
C 109
 
3.8%
a 109
 
3.8%
o 98
 
3.4%
R 98
 
3.4%
Other values (42) 1614
56.2%
Han
ValueCountFrequency (%)
大 4
 
7.7%
美 2
 
3.8%
香 2
 
3.8%
店 2
 
3.8%
食 2
 
3.8%
鮮 1
 
1.9%
馬 1
 
1.9%
酒 1
 
1.9%
記 1
 
1.9%
天 1
 
1.9%
Other values (35) 35
67.3%
Common
ValueCountFrequency (%)
1110
37.4%
) 577
19.5%
( 575
19.4%
2 99
 
3.3%
1 87
 
2.9%
0 60
 
2.0%
& 59
 
2.0%
3 54
 
1.8%
. 49
 
1.7%
9 44
 
1.5%
Other values (17) 250
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48292
89.1%
ASCII 5833
 
10.8%
CJK 52
 
0.1%
Number Forms 4
 
< 0.1%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 1577
 
3.3%
당 1299
 
2.7%
이 967
 
2.0%
점 953
 
2.0%
스 918
 
1.9%
리 678
 
1.4%
호 596
 
1.2%
프 557
 
1.2%
마 555
 
1.1%
치 524
 
1.1%
Other values (975) 39668
82.1%
ASCII
ValueCountFrequency (%)
1110
19.0%
) 577
 
9.9%
( 575
 
9.9%
e 158
 
2.7%
E 157
 
2.7%
A 155
 
2.7%
O 147
 
2.5%
B 118
 
2.0%
S 111
 
1.9%
C 109
 
1.9%
Other values (67) 2616
44.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
100.0%
CJK
ValueCountFrequency (%)
大 4
 
7.7%
美 2
 
3.8%
香 2
 
3.8%
店 2
 
3.8%
食 2
 
3.8%
鮮 1
 
1.9%
馬 1
 
1.9%
酒 1
 
1.9%
記 1
 
1.9%
天 1
 
1.9%
Other values (35) 35
67.3%
Compat Jamo
ValueCountFrequency (%)
ㅁ 1
50.0%
ㅎ 1
50.0%
None
ValueCountFrequency (%)
² 1
100.0%

최종수정일자
Date

Distinct6948
Distinct (%)69.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-07 00:00:00
Maximum2024-05-09 16:50:56
2024-05-11T15:36:58.304250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:58.599011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7086 
U
2914 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7086
70.9%
U 2914
29.1%

Length

2024-05-11T15:36:58.895650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:59.083359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7086
70.9%
u 2914
29.1%

데이터갱신일자
Date

Distinct1299
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:36:59.307812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:59.587629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4473 
분식
1800 
경양식
761 
호프/통닭
692 
기타
672 
Other values (21)
1602 

Length

Max length15
Median length2
Mean length2.621
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row한식
3rd row한식
4th row한식
5th row분식

Common Values

ValueCountFrequency (%)
한식 4473
44.7%
분식 1800
18.0%
경양식 761
 
7.6%
호프/통닭 692
 
6.9%
기타 672
 
6.7%
중국식 522
 
5.2%
일식 415
 
4.2%
통닭(치킨) 158
 
1.6%
정종/대포집/소주방 144
 
1.4%
까페 106
 
1.1%
Other values (16) 257
 
2.6%

Length

2024-05-11T15:36:59.881970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4473
44.7%
분식 1800
18.0%
경양식 761
 
7.6%
호프/통닭 692
 
6.9%
기타 672
 
6.7%
중국식 522
 
5.2%
일식 415
 
4.2%
통닭(치킨 158
 
1.6%
정종/대포집/소주방 144
 
1.4%
까페 106
 
1.1%
Other values (16) 257
 
2.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4056
Distinct (%)42.3%
Missing422
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean191754.75
Minimum189549.85
Maximum202157.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:37:00.144214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189549.85
5-th percentile190199.23
Q1190904.22
median191555.73
Q3192580.75
95-th percentile193818.18
Maximum202157.39
Range12607.546
Interquartile range (IQR)1676.5378

Descriptive statistics

Standard deviation1121.33
Coefficient of variation (CV)0.0058477301
Kurtosis0.19325089
Mean191754.75
Median Absolute Deviation (MAD)689.36903
Skewness0.62311027
Sum1.836627 × 109
Variance1257381
MonotonicityNot monotonic
2024-05-11T15:37:00.446973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193798.948251805 63
 
0.6%
190996.357288859 61
 
0.6%
191385.057392247 61
 
0.6%
193592.000380036 59
 
0.6%
191741.345847708 57
 
0.6%
193306.330043669 51
 
0.5%
193844.169062846 50
 
0.5%
193026.875747265 47
 
0.5%
193469.554731741 43
 
0.4%
194370.32715363 42
 
0.4%
Other values (4046) 9044
90.4%
(Missing) 422
 
4.2%
ValueCountFrequency (%)
189549.847307536 1
 
< 0.1%
189552.021760333 1
 
< 0.1%
189570.401236233 2
< 0.1%
189574.962072527 3
< 0.1%
189586.236800721 4
< 0.1%
189600.906705305 2
< 0.1%
189602.767582543 1
 
< 0.1%
189607.598899153 1
 
< 0.1%
189635.487139725 1
 
< 0.1%
189641.475801911 3
< 0.1%
ValueCountFrequency (%)
202157.393393252 1
 
< 0.1%
194794.056976261 1
 
< 0.1%
194632.526367463 13
 
0.1%
194599.854707059 1
 
< 0.1%
194592.276750438 13
 
0.1%
194561.746032498 26
0.3%
194530.535390096 12
 
0.1%
194504.656267957 17
0.2%
194370.32715363 42
0.4%
194300.993650029 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4056
Distinct (%)42.3%
Missing422
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean445933.95
Minimum442605.7
Maximum453086.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:37:00.732582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442605.7
5-th percentile443306.35
Q1444973.16
median446332.09
Q3446843.53
95-th percentile448052.9
Maximum453086.01
Range10480.301
Interquartile range (IQR)1870.3667

Descriptive statistics

Standard deviation1392.3945
Coefficient of variation (CV)0.0031224232
Kurtosis-0.46543639
Mean445933.95
Median Absolute Deviation (MAD)758.05815
Skewness-0.48678653
Sum4.2711554 × 109
Variance1938762.5
MonotonicityNot monotonic
2024-05-11T15:37:01.067568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446579.652565611 63
 
0.6%
445841.377603245 61
 
0.6%
446098.555926507 61
 
0.6%
447092.629432527 59
 
0.6%
445970.307641467 57
 
0.6%
446582.782311218 51
 
0.5%
446511.783285705 50
 
0.5%
447427.783375434 47
 
0.5%
446508.068667777 43
 
0.4%
446497.523930335 42
 
0.4%
Other values (4046) 9044
90.4%
(Missing) 422
 
4.2%
ValueCountFrequency (%)
442605.70463744 4
< 0.1%
442653.958507 1
 
< 0.1%
442715.143228546 3
< 0.1%
442730.370876742 2
< 0.1%
442744.165176674 1
 
< 0.1%
442756.531513655 4
< 0.1%
442782.832508026 2
< 0.1%
442809.244656606 1
 
< 0.1%
442829.231926853 1
 
< 0.1%
442857.316211443 1
 
< 0.1%
ValueCountFrequency (%)
453086.005564526 1
 
< 0.1%
449199.038668984 3
< 0.1%
449107.834531278 1
 
< 0.1%
449033.097215692 2
< 0.1%
448980.024828564 1
 
< 0.1%
448975.695843598 1
 
< 0.1%
448971.217992424 1
 
< 0.1%
448967.058989224 2
< 0.1%
448961.408642 1
 
< 0.1%
448954.417480004 1
 
< 0.1%

위생업태명
Categorical

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3770 
분식
1682 
<NA>
1616 
경양식
673 
호프/통닭
554 
Other values (22)
1705 

Length

Max length15
Median length2
Mean length2.8197
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 3770
37.7%
분식 1682
16.8%
<NA> 1616
16.2%
경양식 673
 
6.7%
호프/통닭 554
 
5.5%
기타 426
 
4.3%
중국식 410
 
4.1%
일식 335
 
3.4%
통닭(치킨) 144
 
1.4%
정종/대포집/소주방 117
 
1.2%
Other values (17) 273
 
2.7%

Length

2024-05-11T15:37:01.377573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3770
37.7%
분식 1682
16.8%
na 1616
16.2%
경양식 673
 
6.7%
호프/통닭 554
 
5.5%
기타 426
 
4.3%
중국식 410
 
4.1%
일식 335
 
3.4%
통닭(치킨 144
 
1.4%
정종/대포집/소주방 117
 
1.2%
Other values (17) 273
 
2.7%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.1%
Missing1616
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean0.2471374
Minimum0
Maximum20
Zeros7124
Zeros (%)71.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:37:01.660715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.78409662
Coefficient of variation (CV)3.1727153
Kurtosis84.495721
Mean0.2471374
Median Absolute Deviation (MAD)0
Skewness6.6328782
Sum2072
Variance0.6148075
MonotonicityNot monotonic
2024-05-11T15:37:01.910631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 7124
71.2%
1 842
 
8.4%
2 226
 
2.3%
3 107
 
1.1%
4 40
 
0.4%
5 28
 
0.3%
10 9
 
0.1%
7 5
 
0.1%
6 2
 
< 0.1%
20 1
 
< 0.1%
(Missing) 1616
 
16.2%
ValueCountFrequency (%)
0 7124
71.2%
1 842
 
8.4%
2 226
 
2.3%
3 107
 
1.1%
4 40
 
0.4%
5 28
 
0.3%
6 2
 
< 0.1%
7 5
 
0.1%
10 9
 
0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
10 9
 
0.1%
7 5
 
0.1%
6 2
 
< 0.1%
5 28
 
0.3%
4 40
 
0.4%
3 107
 
1.1%
2 226
 
2.3%
1 842
 
8.4%
0 7124
71.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.1%
Missing1616
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean0.39503817
Minimum0
Maximum10
Zeros6597
Zeros (%)66.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:37:02.151142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.92712086
Coefficient of variation (CV)2.3469146
Kurtosis20.078586
Mean0.39503817
Median Absolute Deviation (MAD)0
Skewness3.5436443
Sum3312
Variance0.85955309
MonotonicityNot monotonic
2024-05-11T15:37:02.362721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 6597
66.0%
1 814
 
8.1%
2 644
 
6.4%
3 222
 
2.2%
4 63
 
0.6%
5 23
 
0.2%
10 10
 
0.1%
7 7
 
0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
(Missing) 1616
 
16.2%
ValueCountFrequency (%)
0 6597
66.0%
1 814
 
8.1%
2 644
 
6.4%
3 222
 
2.2%
4 63
 
0.6%
5 23
 
0.2%
6 2
 
< 0.1%
7 7
 
0.1%
8 2
 
< 0.1%
10 10
 
0.1%
ValueCountFrequency (%)
10 10
 
0.1%
8 2
 
< 0.1%
7 7
 
0.1%
6 2
 
< 0.1%
5 23
 
0.2%
4 63
 
0.6%
3 222
 
2.2%
2 644
 
6.4%
1 814
 
8.1%
0 6597
66.0%

영업장주변구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5575 
기타
2723 
주택가주변
1128 
유흥업소밀집지역
 
377
아파트지역
 
160
Other values (3)
 
37

Length

Max length8
Median length4
Mean length3.7471
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5575
55.8%
기타 2723
27.2%
주택가주변 1128
 
11.3%
유흥업소밀집지역 377
 
3.8%
아파트지역 160
 
1.6%
결혼예식장주변 27
 
0.3%
학교정화(절대) 7
 
0.1%
학교정화(상대) 3
 
< 0.1%

Length

2024-05-11T15:37:02.624676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:02.867147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5575
55.8%
기타 2723
27.2%
주택가주변 1128
 
11.3%
유흥업소밀집지역 377
 
3.8%
아파트지역 160
 
1.6%
결혼예식장주변 27
 
0.3%
학교정화(절대 7
 
0.1%
학교정화(상대 3
 
< 0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5661 
지도
1370 
기타
1177 
자율
1082 
을
 
524
Other values (3)
 
186

Length

Max length4
Median length4
Mean length3.0721
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5661
56.6%
지도 1370
 
13.7%
기타 1177
 
11.8%
자율 1082
 
10.8%
을 524
 
5.2%
우수 84
 
0.8%
갑 77
 
0.8%
관리 25
 
0.2%

Length

2024-05-11T15:37:03.128003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:03.350011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5661
56.6%
지도 1370
 
13.7%
기타 1177
 
11.8%
자율 1082
 
10.8%
을 524
 
5.2%
우수 84
 
0.8%
갑 77
 
0.8%
관리 25
 
0.2%

급수시설구분명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5626 
상수도전용
4297 
상수도(음용)지하수(주방용)겸용
 
77

Length

Max length17
Median length4
Mean length4.5298
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5626
56.3%
상수도전용 4297
43.0%
상수도(음용)지하수(주방용)겸용 77
 
0.8%

Length

2024-05-11T15:37:03.600221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:03.805493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5626
56.3%
상수도전용 4297
43.0%
상수도(음용)지하수(주방용)겸용 77
 
0.8%

총인원
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8384 
<NA>
1616 

Length

Max length4
Median length1
Mean length1.4848
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 8384
83.8%
<NA> 1616
 
16.2%

Length

2024-05-11T15:37:04.069004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:04.349627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8384
83.8%
na 1616
 
16.2%

본사종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8384 
<NA>
1616 

Length

Max length4
Median length1
Mean length1.4848
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 8384
83.8%
<NA> 1616
 
16.2%

Length

2024-05-11T15:37:04.565820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:04.757200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8384
83.8%
na 1616
 
16.2%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8384 
<NA>
1616 

Length

Max length4
Median length1
Mean length1.4848
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 8384
83.8%
<NA> 1616
 
16.2%

Length

2024-05-11T15:37:04.971349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:05.135623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8384
83.8%
na 1616
 
16.2%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8384 
<NA>
1616 

Length

Max length4
Median length1
Mean length1.4848
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 8384
83.8%
<NA> 1616
 
16.2%

Length

2024-05-11T15:37:05.299477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:05.462785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8384
83.8%
na 1616
 
16.2%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8384 
<NA>
1616 

Length

Max length4
Median length1
Mean length1.4848
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 8384
83.8%
<NA> 1616
 
16.2%

Length

2024-05-11T15:37:05.660075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:05.837167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8384
83.8%
na 1616
 
16.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

보증액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8384 
<NA>
1616 

Length

Max length4
Median length1
Mean length1.4848
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 8384
83.8%
<NA> 1616
 
16.2%

Length

2024-05-11T15:37:05.989794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:06.150551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8384
83.8%
na 1616
 
16.2%

월세액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8384 
<NA>
1616 

Length

Max length4
Median length1
Mean length1.4848
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 8384
83.8%
<NA> 1616
 
16.2%

Length

2024-05-11T15:37:06.372653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:37:06.674421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8384
83.8%
na 1616
 
16.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1616
Missing (%)16.2%
Memory size97.7 KiB
False
8034 
True
 
350
(Missing)
1616 
ValueCountFrequency (%)
False 8034
80.3%
True 350
 
3.5%
(Missing) 1616
 
16.2%
2024-05-11T15:37:06.891201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct4360
Distinct (%)52.0%
Missing1616
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean65.309751
Minimum0
Maximum1840.8
Zeros544
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:37:07.187054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123.1
median37.13
Q370.79
95-th percentile198
Maximum1840.8
Range1840.8
Interquartile range (IQR)47.69

Descriptive statistics

Standard deviation103.87536
Coefficient of variation (CV)1.5905031
Kurtosis81.904003
Mean65.309751
Median Absolute Deviation (MAD)18.87
Skewness7.3403462
Sum547556.95
Variance10790.091
MonotonicityNot monotonic
2024-05-11T15:37:07.497207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 544
 
5.4%
26.4 67
 
0.7%
33.0 65
 
0.7%
66.0 60
 
0.6%
30.0 47
 
0.5%
24.0 43
 
0.4%
19.8 40
 
0.4%
23.1 40
 
0.4%
49.5 36
 
0.4%
18.0 35
 
0.4%
Other values (4350) 7407
74.1%
(Missing) 1616
 
16.2%
ValueCountFrequency (%)
0.0 544
5.4%
2.0 2
 
< 0.1%
3.0 1
 
< 0.1%
3.91 1
 
< 0.1%
4.34 1
 
< 0.1%
4.96 1
 
< 0.1%
5.0 1
 
< 0.1%
5.04 1
 
< 0.1%
5.87 1
 
< 0.1%
5.94 1
 
< 0.1%
ValueCountFrequency (%)
1840.8 1
< 0.1%
1777.12 1
< 0.1%
1655.94 1
< 0.1%
1647.08 1
< 0.1%
1644.43 1
< 0.1%
1450.0 1
< 0.1%
1430.48 1
< 0.1%
1429.08 1
< 0.1%
1411.56 1
< 0.1%
1381.35 1
< 0.1%

전통업소지정번호
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing9996
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-11T15:37:07.750816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.5
Min length1

Characters and Unicode

Total characters10
Distinct characters5
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

Unique4 ?
Unique (%)100.0%

Sample

1st row1
2nd row108
3rd row.
4th row14.08
ValueCountFrequency (%)
1 1
25.0%
108 1
25.0%
1
25.0%
14.08 1
25.0%
2024-05-11T15:37:08.730422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
30.0%
0 2
20.0%
8 2
20.0%
. 2
20.0%
4 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
80.0%
Other Punctuation 2
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
37.5%
0 2
25.0%
8 2
25.0%
4 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
30.0%
0 2
20.0%
8 2
20.0%
. 2
20.0%
4 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
30.0%
0 2
20.0%
8 2
20.0%
. 2
20.0%
4 1
 
10.0%

전통업소주된음식
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-11T15:37:08.993553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row00000000000000
ValueCountFrequency (%)
00000000000000 1
100.0%
2024-05-11T15:37:09.460959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
100.0%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
717631800003180000-101-1996-0897819960321<NA>3폐업2폐업19980511<NA><NA><NA>02 679381336.75150800서울특별시 영등포구 당산동1가 90-0번지<NA><NA>양남식당2001-08-02 00:00:00I2018-08-31 23:59:59.0한식<NA><NA>한식00기타자율상수도전용00000<NA>00N36.75<NA><NA><NA>
735131800003180000-101-1997-0007619970325<NA>3폐업2폐업20030603<NA><NA><NA>020847461947.99150070서울특별시 영등포구 대림동 1081-0번지 33<NA><NA>선희네숯불돼지갈비2002-12-24 00:00:00I2018-08-31 23:59:59.0한식<NA><NA>한식00주택가주변자율상수도전용00000<NA>00N47.99<NA><NA><NA>
883831800003180000-101-1999-1202619990316<NA>3폐업2폐업20030801<NA><NA><NA>02 631026647.30150106서울특별시 영등포구 양평동6가 73-0번지<NA><NA>돈바우식당2000-04-11 00:00:00I2018-08-31 23:59:59.0한식190262.164946448936.418388한식00주택가주변관리<NA>00000<NA>00N47.3<NA><NA><NA>
659231800003180000-101-1996-000891996-09-18<NA>3폐업2폐업2023-06-23<NA><NA><NA>0226776601155.37150-033서울특별시 영등포구 영등포동3가 15서울특별시 영등포구 영등포로46길 5, 1층 (영등포동3가)7304카오스(chaos)2023-06-23 14:01:44U2022-12-05 22:06:00.0한식191797.023182446281.373909<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1301131800003180000-101-2003-0045020030826<NA>3폐업2폐업20050321<NA><NA><NA><NA>17.06150837서울특별시 영등포구 신길동 2-3번지 삼두아파트상가1층1호<NA><NA>이웃사랑2003-08-26 00:00:00I2018-08-31 23:59:59.0분식193198.641479445791.109947분식00<NA><NA><NA>00000<NA>00N17.06<NA><NA><NA>
172031800003180000-101-1986-0731219860501<NA>3폐업2폐업20020109<NA><NA><NA>0241.40150033서울특별시 영등포구 영등포동3가 20-5번지<NA><NA>홍릉갈비2000-03-27 00:00:00I2018-08-31 23:59:59.0한식191702.874122446136.568692한식21유흥업소밀집지역지도상수도전용00000<NA>00N41.4<NA><NA><NA>
532231800003180000-101-1994-0452819940720<NA>3폐업2폐업20091216<NA><NA><NA>020834828135.41150899서울특별시 영등포구 영등포동 645-10번지<NA><NA>정읍식당2009-12-16 20:19:06I2018-08-31 23:59:59.0분식191414.619949445274.887766분식00기타기타상수도전용00000<NA>00N35.41<NA><NA><NA>
659631800003180000-101-1996-0009319960725<NA>3폐업2폐업20120904<NA><NA><NA>02 864185519.70150829서울특별시 영등포구 도림동 109-5번지서울특별시 영등포구 도신로29가길 11 (도림동)7368당진정육숯불갈비2004-04-23 00:00:00I2018-08-31 23:59:59.0한식191653.424434445264.261736한식00주택가주변자율상수도전용00000<NA>00N19.7<NA><NA><NA>
763131800003180000-101-1997-0354619970708<NA>3폐업2폐업20010619<NA><NA><NA>0226.60150815서울특별시 영등포구 대림동 756-5번지<NA><NA>에이스2001-06-19 00:00:00I2018-08-31 23:59:59.0분식191301.284742443775.242881분식11주택가주변자율상수도전용00000<NA>00N26.6<NA><NA><NA>
2235531800003180000-101-2019-0015320190408<NA>1영업/정상1영업<NA><NA><NA><NA><NA>97.84150096서울특별시 영등포구 문래동6가 5 EEU동신타워 203호서울특별시 영등포구 선유로 63, EEU동신타워 203호 (문래동6가)7281도심포차2022-09-01 10:59:58U2021-12-09 00:03:00.0호프/통닭190121.308342446385.284135<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
972831800003180000-101-2000-1305920000118<NA>3폐업2폐업20010305<NA><NA><NA>025.94150899서울특별시 영등포구 영등포동 618-181번지<NA><NA>달구지2001-03-05 00:00:00I2018-08-31 23:59:59.0분식191830.383729445696.83482분식01기타기타<NA>00000<NA>00N5.94<NA><NA><NA>
804531800003180000-101-1997-1144819970321<NA>3폐업2폐업19971103<NA><NA><NA>020845482923.17150832서울특별시 영등포구 도림동 216-2번지<NA><NA>김가호프2001-08-02 00:00:00I2018-08-31 23:59:59.0한식190789.720924445203.749466한식00주택가주변을상수도전용00000<NA>00N23.17<NA><NA><NA>
194631800003180000-101-1987-0279019871120<NA>3폐업2폐업19950208<NA><NA><NA>020635466723.09150042서울특별시 영등포구 당산동2가 58-0번지<NA><NA>목화2001-08-02 00:00:00I2018-08-31 23:59:59.0정종/대포집/소주방190373.644105446719.919026정종/대포집/소주방02기타지도상수도전용00000<NA>00N23.09<NA><NA><NA>
762731800003180000-101-1997-0339119970110<NA>3폐업2폐업19980704<NA><NA><NA>02 654554739.78150042서울특별시 영등포구 당산동2가 146-0번지<NA><NA>목화2001-08-02 00:00:00I2018-08-31 23:59:59.0분식190471.589192446801.984194분식00기타자율상수도전용00000<NA>00N39.78<NA><NA><NA>
578131800003180000-101-1994-0962919940926<NA>3폐업2폐업20060530<NA><NA><NA>020679591019.39150036서울특별시 영등포구 영등포동6가 95-14번지<NA><NA>여정식당2001-08-02 00:00:00I2018-08-31 23:59:59.0한식191223.895988446513.776992한식00기타기타상수도전용00000<NA>00N19.39<NA><NA><NA>
1158431800003180000-101-2001-1477520010117<NA>3폐업2폐업20091216<NA><NA><NA><NA>16.50150035서울특별시 영등포구 영등포동5가 24번지<NA><NA>우동열차2009-12-17 09:21:40I2018-08-31 23:59:59.0분식191590.878296446489.419538분식00주택가주변자율상수도전용00000<NA>00N16.5<NA><NA><NA>
1647331800003180000-101-2009-0007820090318<NA>3폐업2폐업20091005<NA><NA><NA><NA>65.72150803서울특별시 영등포구 당산동3가 147번지 지하1층<NA><NA>지니2009-10-05 13:37:50I2018-08-31 23:59:59.0경양식190883.960591447227.170864경양식00<NA><NA><NA>00000<NA>00N65.72<NA><NA><NA>
2248831800003180000-101-2019-0028720190624<NA>1영업/정상1영업<NA><NA><NA><NA>1644215355.00150034서울특별시 영등포구 영등포동4가 442 타임스퀘어 5층서울특별시 영등포구 영중로 15, 타임스퀘어 5층 (영등포동4가)7305홈볼트해적단2021-05-17 10:52:58U2021-05-19 02:40:00.0기타191385.057392446098.555927기타00<NA><NA><NA>00000<NA>00N55.0<NA><NA><NA>
1097831800003180000-101-2001-1413220010607<NA>1영업/정상1영업<NA><NA><NA><NA>023775199560.00150744서울특별시 영등포구 여의도동 44-27 하남빌딩117.118호서울특별시 영등포구 의사당대로1길 25 (여의도동,하남빌딩117.118호)7333교동전선생 (여의도점)2022-12-28 13:59:00U2021-11-01 21:00:00.0기타193737.480224446434.303266<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1476431800003180000-101-2006-0012020060317<NA>3폐업2폐업20120426<NA><NA><NA><NA><NA>150889서울특별시 영등포구 여의도동 43-4번지 롯데캐슬아이비 B121호서울특별시 영등포구 국제금융로 86 (여의도동,롯데캐슬아이비 B121호)7333이키2012-04-26 13:33:39I2018-08-31 23:59:59.0정종/대포집/소주방193896.282065446442.571421정종/대포집/소주방00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>