Overview

Dataset statistics

Number of variables44
Number of observations30
Missing cells417
Missing cells (%)31.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.1 KiB
Average record size in memory380.4 B

Variable types

Categorical18
Text8
DateTime3
Unsupported10
Numeric4
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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-18302/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
남성종사자수 is highly imbalanced (53.1%)Imbalance
여성종사자수 is highly imbalanced (53.1%)Imbalance
급수시설구분명 is highly imbalanced (53.1%)Imbalance
다중이용업소여부 is highly imbalanced (74.2%)Imbalance
인허가취소일자 has 30 (100.0%) missing valuesMissing
폐업일자 has 11 (36.7%) missing valuesMissing
휴업시작일자 has 30 (100.0%) missing valuesMissing
휴업종료일자 has 30 (100.0%) missing valuesMissing
재개업일자 has 30 (100.0%) missing valuesMissing
전화번호 has 2 (6.7%) missing valuesMissing
소재지면적 has 22 (73.3%) missing valuesMissing
도로명주소 has 10 (33.3%) missing valuesMissing
도로명우편번호 has 11 (36.7%) missing valuesMissing
영업장주변구분명 has 27 (90.0%) missing valuesMissing
등급구분명 has 27 (90.0%) missing valuesMissing
총인원 has 30 (100.0%) missing valuesMissing
보증액 has 30 (100.0%) missing valuesMissing
월세액 has 30 (100.0%) missing valuesMissing
다중이용업소여부 has 7 (23.3%) missing valuesMissing
전통업소지정번호 has 30 (100.0%) missing valuesMissing
전통업소주된음식 has 30 (100.0%) missing valuesMissing
홈페이지 has 30 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 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
총인원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
보증액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
월세액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 06:55:54.653651
Analysis finished2024-05-11 06:55:55.472235
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
3000000
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 30
100.0%

Length

2024-05-11T15:55:55.585626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:55.769119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 30
100.0%

관리번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-05-11T15:55:56.190070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters660
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

Unique30 ?
Unique (%)100.0%

Sample

1st row3000000-114-1996-00089
2nd row3000000-114-1996-00090
3rd row3000000-114-1999-00140
4th row3000000-114-2000-00230
5th row3000000-114-2002-00001
ValueCountFrequency (%)
3000000-114-1996-00089 1
 
3.3%
3000000-114-1996-00090 1
 
3.3%
3000000-114-2023-00001 1
 
3.3%
3000000-114-2021-00001 1
 
3.3%
3000000-114-2019-00001 1
 
3.3%
3000000-114-2017-00001 1
 
3.3%
3000000-114-2016-00004 1
 
3.3%
3000000-114-2016-00003 1
 
3.3%
3000000-114-2016-00002 1
 
3.3%
3000000-114-2016-00001 1
 
3.3%
Other values (20) 20
66.7%
2024-05-11T15:55:56.794328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 341
51.7%
- 90
 
13.6%
1 90
 
13.6%
3 40
 
6.1%
2 39
 
5.9%
4 36
 
5.5%
9 10
 
1.5%
6 6
 
0.9%
7 4
 
0.6%
5 3
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 570
86.4%
Dash Punctuation 90
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 341
59.8%
1 90
 
15.8%
3 40
 
7.0%
2 39
 
6.8%
4 36
 
6.3%
9 10
 
1.8%
6 6
 
1.1%
7 4
 
0.7%
5 3
 
0.5%
8 1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 660
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 341
51.7%
- 90
 
13.6%
1 90
 
13.6%
3 40
 
6.1%
2 39
 
5.9%
4 36
 
5.5%
9 10
 
1.5%
6 6
 
0.9%
7 4
 
0.6%
5 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 341
51.7%
- 90
 
13.6%
1 90
 
13.6%
3 40
 
6.1%
2 39
 
5.9%
4 36
 
5.5%
9 10
 
1.5%
6 6
 
0.9%
7 4
 
0.6%
5 3
 
0.5%

인허가일자
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum1996-06-21 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:55:57.056797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:55:57.280481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
3
19 
1
11 

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 19
63.3%
1 11
36.7%

Length

2024-05-11T15:55:57.466204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:57.590107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 19
63.3%
1 11
36.7%

영업상태명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
폐업
19 
영업/정상
11 

Length

Max length5
Median length2
Mean length3.1
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 19
63.3%
영업/정상 11
36.7%

Length

2024-05-11T15:55:57.743098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:57.899019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 19
63.3%
영업/정상 11
36.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2
19 
1
11 

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 19
63.3%
1 11
36.7%

Length

2024-05-11T15:55:58.048849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:58.227215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 19
63.3%
1 11
36.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
폐업
19 
영업
11 

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 19
63.3%
영업 11
36.7%

Length

2024-05-11T15:55:58.431103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:58.579705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 19
63.3%
영업 11
36.7%

폐업일자
Date

MISSING 

Distinct19
Distinct (%)100.0%
Missing11
Missing (%)36.7%
Memory size372.0 B
Minimum2002-08-02 00:00:00
Maximum2023-10-27 00:00:00
2024-05-11T15:55:58.739430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:55:58.957789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

전화번호
Text

MISSING 

Distinct27
Distinct (%)96.4%
Missing2
Missing (%)6.7%
Memory size372.0 B
2024-05-11T15:55:59.221145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11
Min length8

Characters and Unicode

Total characters308
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

Unique26 ?
Unique (%)92.9%

Sample

1st row02 4400783
2nd row02 737 9994
3rd row02 1001000
4th row02 7392360
5th row02 3914480
ValueCountFrequency (%)
02 21
36.8%
34170051 2
 
3.5%
0236769244 2
 
3.5%
4400783 1
 
1.8%
8545 1
 
1.8%
764 1
 
1.8%
22724980 1
 
1.8%
36722231 1
 
1.8%
738 1
 
1.8%
000222905618 1
 
1.8%
Other values (25) 25
43.9%
2024-05-11T15:55:59.731321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 61
19.8%
2 51
16.6%
43
14.0%
7 25
8.1%
3 24
 
7.8%
1 20
 
6.5%
6 19
 
6.2%
9 18
 
5.8%
4 18
 
5.8%
5 15
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 265
86.0%
Space Separator 43
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 61
23.0%
2 51
19.2%
7 25
9.4%
3 24
 
9.1%
1 20
 
7.5%
6 19
 
7.2%
9 18
 
6.8%
4 18
 
6.8%
5 15
 
5.7%
8 14
 
5.3%
Space Separator
ValueCountFrequency (%)
43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 308
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 61
19.8%
2 51
16.6%
43
14.0%
7 25
8.1%
3 24
 
7.8%
1 20
 
6.5%
6 19
 
6.2%
9 18
 
5.8%
4 18
 
5.8%
5 15
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 61
19.8%
2 51
16.6%
43
14.0%
7 25
8.1%
3 24
 
7.8%
1 20
 
6.5%
6 19
 
6.2%
9 18
 
5.8%
4 18
 
5.8%
5 15
 
4.9%

소재지면적
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing22
Missing (%)73.3%
Infinite0
Infinite (%)0.0%
Mean613.76
Minimum314
Maximum1388.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-11T15:55:59.931509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum314
5-th percentile339.354
Q1389.11
median494.25
Q3689.645
95-th percentile1177.132
Maximum1388.28
Range1074.28
Interquartile range (IQR)300.535

Descriptive statistics

Standard deviation352.78758
Coefficient of variation (CV)0.57479729
Kurtosis3.4286654
Mean613.76
Median Absolute Deviation (MAD)135.71
Skewness1.7755601
Sum4910.08
Variance124459.08
MonotonicityNot monotonic
2024-05-11T15:56:00.136273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
657.86 1
 
3.3%
785.0 1
 
3.3%
390.0 1
 
3.3%
594.0 1
 
3.3%
386.44 1
 
3.3%
1388.28 1
 
3.3%
314.0 1
 
3.3%
394.5 1
 
3.3%
(Missing) 22
73.3%
ValueCountFrequency (%)
314.0 1
3.3%
386.44 1
3.3%
390.0 1
3.3%
394.5 1
3.3%
594.0 1
3.3%
657.86 1
3.3%
785.0 1
3.3%
1388.28 1
3.3%
ValueCountFrequency (%)
1388.28 1
3.3%
785.0 1
3.3%
657.86 1
3.3%
594.0 1
3.3%
394.5 1
3.3%
390.0 1
3.3%
386.44 1
3.3%
314.0 1
3.3%

소재지우편번호
Text

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-05-11T15:56:00.418187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2333333
Min length6

Characters and Unicode

Total characters187
Distinct characters10
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

Unique11 ?
Unique (%)36.7%

Sample

1st row110847
2nd row110-061
3rd row110522
4th row110080
5th row110847
ValueCountFrequency (%)
110847 5
16.7%
110522 5
16.7%
110530 3
10.0%
110837 3
10.0%
110-847 3
10.0%
110-061 1
 
3.3%
110080 1
 
3.3%
110420 1
 
3.3%
110054 1
 
3.3%
110-522 1
 
3.3%
Other values (6) 6
20.0%
2024-05-11T15:56:00.998852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 63
33.7%
0 43
23.0%
2 15
 
8.0%
8 14
 
7.5%
4 12
 
6.4%
7 11
 
5.9%
5 10
 
5.3%
3 9
 
4.8%
- 7
 
3.7%
6 3
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 180
96.3%
Dash Punctuation 7
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 63
35.0%
0 43
23.9%
2 15
 
8.3%
8 14
 
7.8%
4 12
 
6.7%
7 11
 
6.1%
5 10
 
5.6%
3 9
 
5.0%
6 3
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 187
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 63
33.7%
0 43
23.0%
2 15
 
8.0%
8 14
 
7.5%
4 12
 
6.4%
7 11
 
5.9%
5 10
 
5.3%
3 9
 
4.8%
- 7
 
3.7%
6 3
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 187
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 63
33.7%
0 43
23.0%
2 15
 
8.0%
8 14
 
7.5%
4 12
 
6.4%
7 11
 
5.9%
5 10
 
5.3%
3 9
 
4.8%
- 7
 
3.7%
6 3
 
1.6%

지번주소
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-05-11T15:56:01.446521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length30
Mean length26.333333
Min length18

Characters and Unicode

Total characters790
Distinct characters96
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

Unique28 ?
Unique (%)93.3%

Sample

1st row서울특별시 종로구 평창동 331-0
2nd row서울특별시 종로구 신문로1가 24
3rd row서울특별시 종로구 명륜2가 41-9
4th row서울특별시 종로구 무악동 82 무악현대아파트상가 지하1층 (지하101호)
5th row서울특별시 종로구 평창동 182-2 창계빌딩 지1층
ValueCountFrequency (%)
서울특별시 30
18.4%
종로구 30
18.4%
평창동 8
 
4.9%
명륜2가 6
 
3.7%
1층 5
 
3.1%
지하1층 5
 
3.1%
창신동 3
 
1.8%
혜화동 3
 
1.8%
4 2
 
1.2%
20 2
 
1.2%
Other values (59) 69
42.3%
2024-05-11T15:56:02.246308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
19.7%
1 46
 
5.8%
구 31
 
3.9%
로 31
 
3.9%
종 30
 
3.8%
울 30
 
3.8%
서 30
 
3.8%
시 30
 
3.8%
별 30
 
3.8%
특 30
 
3.8%
Other values (86) 346
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 480
60.8%
Space Separator 156
 
19.7%
Decimal Number 134
 
17.0%
Dash Punctuation 13
 
1.6%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Other Punctuation 2
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 31
 
6.5%
로 31
 
6.5%
종 30
 
6.2%
울 30
 
6.2%
서 30
 
6.2%
시 30
 
6.2%
별 30
 
6.2%
특 30
 
6.2%
동 26
 
5.4%
층 15
 
3.1%
Other values (69) 197
41.0%
Decimal Number
ValueCountFrequency (%)
1 46
34.3%
2 24
17.9%
3 19
14.2%
4 10
 
7.5%
0 10
 
7.5%
8 10
 
7.5%
5 5
 
3.7%
9 4
 
3.0%
7 3
 
2.2%
6 3
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
@ 1
50.0%
Space Separator
ValueCountFrequency (%)
156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 480
60.8%
Common 309
39.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 31
 
6.5%
로 31
 
6.5%
종 30
 
6.2%
울 30
 
6.2%
서 30
 
6.2%
시 30
 
6.2%
별 30
 
6.2%
특 30
 
6.2%
동 26
 
5.4%
층 15
 
3.1%
Other values (69) 197
41.0%
Common
ValueCountFrequency (%)
156
50.5%
1 46
 
14.9%
2 24
 
7.8%
3 19
 
6.1%
- 13
 
4.2%
4 10
 
3.2%
0 10
 
3.2%
8 10
 
3.2%
5 5
 
1.6%
9 4
 
1.3%
Other values (6) 12
 
3.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 480
60.8%
ASCII 310
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
50.3%
1 46
 
14.8%
2 24
 
7.7%
3 19
 
6.1%
- 13
 
4.2%
4 10
 
3.2%
0 10
 
3.2%
8 10
 
3.2%
5 5
 
1.6%
9 4
 
1.3%
Other values (7) 13
 
4.2%
Hangul
ValueCountFrequency (%)
구 31
 
6.5%
로 31
 
6.5%
종 30
 
6.2%
울 30
 
6.2%
서 30
 
6.2%
시 30
 
6.2%
별 30
 
6.2%
특 30
 
6.2%
동 26
 
5.4%
층 15
 
3.1%
Other values (69) 197
41.0%

도로명주소
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing10
Missing (%)33.3%
Memory size372.0 B
2024-05-11T15:56:02.778635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length36.5
Mean length33.05
Min length23

Characters and Unicode

Total characters661
Distinct characters102
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

Unique18 ?
Unique (%)90.0%

Sample

1st row서울특별시 종로구 새문안로 91 (신문로1가)
2nd row서울특별시 종로구 통일로 246-20, 지하1층 (무악동, 무악현대아파트상가)
3rd row서울특별시 종로구 대학로 144 (혜화동)
4th row서울특별시 종로구 지봉로 87 (창신동,이수아파트상가1층)
5th row서울특별시 종로구 성균관로 12 (명륜2가)
ValueCountFrequency (%)
서울특별시 20
 
15.6%
종로구 20
 
15.6%
1층 4
 
3.1%
평창동 4
 
3.1%
지하1층 4
 
3.1%
39 3
 
2.3%
명륜2가 3
 
2.3%
혜화동 2
 
1.6%
지하 2
 
1.6%
301동 2
 
1.6%
Other values (56) 64
50.0%
2024-05-11T15:56:03.550643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
 
16.3%
로 38
 
5.7%
1 30
 
4.5%
, 21
 
3.2%
구 21
 
3.2%
서 20
 
3.0%
특 20
 
3.0%
별 20
 
3.0%
시 20
 
3.0%
종 20
 
3.0%
Other values (92) 343
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 403
61.0%
Space Separator 108
 
16.3%
Decimal Number 86
 
13.0%
Other Punctuation 21
 
3.2%
Close Punctuation 20
 
3.0%
Open Punctuation 20
 
3.0%
Math Symbol 1
 
0.2%
Uppercase Letter 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 38
 
9.4%
구 21
 
5.2%
서 20
 
5.0%
특 20
 
5.0%
별 20
 
5.0%
시 20
 
5.0%
종 20
 
5.0%
울 20
 
5.0%
동 19
 
4.7%
층 13
 
3.2%
Other values (75) 192
47.6%
Decimal Number
ValueCountFrequency (%)
1 30
34.9%
3 11
 
12.8%
4 10
 
11.6%
2 9
 
10.5%
0 8
 
9.3%
9 5
 
5.8%
5 4
 
4.7%
6 3
 
3.5%
7 3
 
3.5%
8 3
 
3.5%
Space Separator
ValueCountFrequency (%)
108
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 403
61.0%
Common 257
38.9%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 38
 
9.4%
구 21
 
5.2%
서 20
 
5.0%
특 20
 
5.0%
별 20
 
5.0%
시 20
 
5.0%
종 20
 
5.0%
울 20
 
5.0%
동 19
 
4.7%
층 13
 
3.2%
Other values (75) 192
47.6%
Common
ValueCountFrequency (%)
108
42.0%
1 30
 
11.7%
, 21
 
8.2%
) 20
 
7.8%
( 20
 
7.8%
3 11
 
4.3%
4 10
 
3.9%
2 9
 
3.5%
0 8
 
3.1%
9 5
 
1.9%
Other values (6) 15
 
5.8%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 403
61.0%
ASCII 258
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
108
41.9%
1 30
 
11.6%
, 21
 
8.1%
) 20
 
7.8%
( 20
 
7.8%
3 11
 
4.3%
4 10
 
3.9%
2 9
 
3.5%
0 8
 
3.1%
9 5
 
1.9%
Other values (7) 16
 
6.2%
Hangul
ValueCountFrequency (%)
로 38
 
9.4%
구 21
 
5.2%
서 20
 
5.0%
특 20
 
5.0%
별 20
 
5.0%
시 20
 
5.0%
종 20
 
5.0%
울 20
 
5.0%
동 19
 
4.7%
층 13
 
3.2%
Other values (75) 192
47.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)73.7%
Missing11
Missing (%)36.7%
Infinite0
Infinite (%)0.0%
Mean3072.5263
Minimum3008
Maximum3192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-11T15:56:03.811705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3008
5-th percentile3008
Q13014.5
median3074
Q33089.5
95-th percentile3183
Maximum3192
Range184
Interquartile range (IQR)75

Descriptive statistics

Standard deviation62.674085
Coefficient of variation (CV)0.020398226
Kurtosis-0.60426591
Mean3072.5263
Median Absolute Deviation (MAD)57
Skewness0.75402329
Sum58378
Variance3928.0409
MonotonicityNot monotonic
2024-05-11T15:56:04.031870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3008 4
 
13.3%
3084 2
 
6.7%
3074 2
 
6.7%
3182 1
 
3.3%
3025 1
 
3.3%
3095 1
 
3.3%
3168 1
 
3.3%
3075 1
 
3.3%
3012 1
 
3.3%
3042 1
 
3.3%
Other values (4) 4
 
13.3%
(Missing) 11
36.7%
ValueCountFrequency (%)
3008 4
13.3%
3012 1
 
3.3%
3017 1
 
3.3%
3025 1
 
3.3%
3042 1
 
3.3%
3061 1
 
3.3%
3074 2
6.7%
3075 1
 
3.3%
3084 2
6.7%
3095 1
 
3.3%
ValueCountFrequency (%)
3192 1
3.3%
3182 1
3.3%
3168 1
3.3%
3161 1
3.3%
3095 1
3.3%
3084 2
6.7%
3075 1
3.3%
3074 2
6.7%
3061 1
3.3%
3042 1
3.3%

사업장명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-05-11T15:56:04.431697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.9666667
Min length4

Characters and Unicode

Total characters269
Distinct characters107
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row주)해태유통
2nd row홈플러스 익스프레스 광화문점
3rd row주)농심가후레쉬마켓명륜점
4th row현대후레쉬마트
5th row코사마트 평창점
ValueCountFrequency (%)
종로평창점 2
 
4.8%
롯데쇼핑(주)롯데슈퍼 2
 
4.8%
홈플러스 1
 
2.4%
하나로마트 1
 
2.4%
사직점 1
 
2.4%
홈플러스익스프레스명륜2점 1
 
2.4%
대학로점 1
 
2.4%
주)지에스리테일gs수퍼종로구기점 1
 
2.4%
주)지에스리테일 1
 
2.4%
gs수퍼 1
 
2.4%
Other values (30) 30
71.4%
2024-05-11T15:56:05.128196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 16
 
5.9%
트 15
 
5.6%
12
 
4.5%
스 11
 
4.1%
점 11
 
4.1%
주 10
 
3.7%
) 10
 
3.7%
( 8
 
3.0%
로 5
 
1.9%
레 5
 
1.9%
Other values (97) 166
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 231
85.9%
Space Separator 12
 
4.5%
Close Punctuation 10
 
3.7%
Open Punctuation 8
 
3.0%
Uppercase Letter 4
 
1.5%
Decimal Number 4
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 16
 
6.9%
트 15
 
6.5%
스 11
 
4.8%
점 11
 
4.8%
주 10
 
4.3%
로 5
 
2.2%
레 5
 
2.2%
롯 4
 
1.7%
유 4
 
1.7%
서 4
 
1.7%
Other values (88) 146
63.2%
Decimal Number
ValueCountFrequency (%)
3 1
25.0%
6 1
25.0%
5 1
25.0%
2 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
G 2
50.0%
S 2
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 231
85.9%
Common 34
 
12.6%
Latin 4
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 16
 
6.9%
트 15
 
6.5%
스 11
 
4.8%
점 11
 
4.8%
주 10
 
4.3%
로 5
 
2.2%
레 5
 
2.2%
롯 4
 
1.7%
유 4
 
1.7%
서 4
 
1.7%
Other values (88) 146
63.2%
Common
ValueCountFrequency (%)
12
35.3%
) 10
29.4%
( 8
23.5%
3 1
 
2.9%
6 1
 
2.9%
5 1
 
2.9%
2 1
 
2.9%
Latin
ValueCountFrequency (%)
G 2
50.0%
S 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 231
85.9%
ASCII 38
 
14.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 16
 
6.9%
트 15
 
6.5%
스 11
 
4.8%
점 11
 
4.8%
주 10
 
4.3%
로 5
 
2.2%
레 5
 
2.2%
롯 4
 
1.7%
유 4
 
1.7%
서 4
 
1.7%
Other values (88) 146
63.2%
ASCII
ValueCountFrequency (%)
12
31.6%
) 10
26.3%
( 8
21.1%
G 2
 
5.3%
S 2
 
5.3%
3 1
 
2.6%
6 1
 
2.6%
5 1
 
2.6%
2 1
 
2.6%

최종수정일자
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2000-01-03 00:00:00
Maximum2024-05-09 17:19:43
2024-05-11T15:56:05.447631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:56:05.695847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
I
21 
U
9 

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 21
70.0%
U 9
30.0%

Length

2024-05-11T15:56:05.995917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:06.156498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 21
70.0%
u 9
30.0%

데이터갱신일자
Categorical

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2018-08-31 23:59:59.0
19 
2023-12-02 22:00:00.0
2 
2020-03-25 02:40:00.0
 
1
2019-02-05 02:40:00.0
 
1
2018-12-14 02:40:00.0
 
1
Other values (6)
6 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique9 ?
Unique (%)30.0%

Sample

1st row2018-08-31 23:59:59.0
2nd row2023-12-02 22:00:00.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 19
63.3%
2023-12-02 22:00:00.0 2
 
6.7%
2020-03-25 02:40:00.0 1
 
3.3%
2019-02-05 02:40:00.0 1
 
3.3%
2018-12-14 02:40:00.0 1
 
3.3%
2022-12-04 22:01:00.0 1
 
3.3%
2022-10-30 22:09:00.0 1
 
3.3%
2019-08-08 02:40:00.0 1
 
3.3%
2022-12-05 22:01:00.0 1
 
3.3%
2022-12-04 22:06:00.0 1
 
3.3%

Length

2024-05-11T15:56:06.348133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 19
31.7%
23:59:59.0 19
31.7%
02:40:00.0 4
 
6.7%
22:01:00.0 2
 
3.3%
2022-12-04 2
 
3.3%
22:00:00.0 2
 
3.3%
2023-12-02 2
 
3.3%
2020-03-25 1
 
1.7%
2019-02-05 1
 
1.7%
2018-12-14 1
 
1.7%
Other values (7) 7
 
11.7%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
기타식품판매업
30 

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 30
100.0%

Length

2024-05-11T15:56:06.568634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:06.752730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 30
100.0%

좌표정보(X)
Real number (ℝ)

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198526.62
Minimum196278.55
Maximum201258.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-11T15:56:06.918684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196278.55
5-th percentile196507.09
Q1196970.61
median198519.23
Q3199907.29
95-th percentile201228.58
Maximum201258.06
Range4979.508
Interquartile range (IQR)2936.6862

Descriptive statistics

Standard deviation1629.7991
Coefficient of variation (CV)0.0082094741
Kurtosis-1.4652916
Mean198526.62
Median Absolute Deviation (MAD)1532.2969
Skewness0.21047047
Sum5955798.5
Variance2656245.2
MonotonicityNot monotonic
2024-05-11T15:56:07.161370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
196965.164175084 3
 
10.0%
196986.931657005 2
 
6.7%
199878.668537625 2
 
6.7%
200121.813720325 2
 
6.7%
201228.579823795 2
 
6.7%
199769.96511678 2
 
6.7%
199045.043602772 2
 
6.7%
196896.329082976 2
 
6.7%
196278.554670262 1
 
3.3%
198507.437120234 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
196278.554670262 1
 
3.3%
196467.975088253 1
 
3.3%
196554.899209998 1
 
3.3%
196896.329082976 2
6.7%
196965.164175084 3
10.0%
196986.931657005 2
6.7%
197181.393301659 1
 
3.3%
197212.364862058 1
 
3.3%
197371.887812909 1
 
3.3%
197700.034013631 1
 
3.3%
ValueCountFrequency (%)
201258.062657124 1
3.3%
201228.579823795 2
6.7%
200121.813720325 2
6.7%
200113.874740135 1
3.3%
199954.044722095 1
3.3%
199916.833506015 1
3.3%
199878.668537625 2
6.7%
199769.96511678 2
6.7%
199045.043602772 2
6.7%
198531.019987857 1
3.3%

좌표정보(Y)
Real number (ℝ)

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean453958.12
Minimum451939.68
Maximum456055.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-11T15:56:07.421671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451939.68
5-th percentile451976.95
Q1452804.16
median453520.43
Q3455893.23
95-th percentile456046.96
Maximum456055.21
Range4115.5285
Interquartile range (IQR)3089.0662

Descriptive statistics

Standard deviation1497.2404
Coefficient of variation (CV)0.0032981906
Kurtosis-1.4048725
Mean453958.12
Median Absolute Deviation (MAD)1007.947
Skewness0.37186651
Sum13618743
Variance2241728.7
MonotonicityNot monotonic
2024-05-11T15:56:07.672155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
455959.269196762 3
 
10.0%
456038.650926234 2
 
6.7%
453693.071412414 2
 
6.7%
453518.007319338 2
 
6.7%
452855.249637866 2
 
6.7%
453520.42735819 2
 
6.7%
451939.677286976 2
 
6.7%
455893.228194817 2
 
6.7%
456053.759563793 1
 
3.3%
452641.178441629 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
451939.677286976 2
6.7%
452022.503467072 1
3.3%
452166.91560057 1
3.3%
452458.826651573 1
3.3%
452566.134030104 1
3.3%
452641.178441629 1
3.3%
452787.132831042 1
3.3%
452855.249637866 2
6.7%
453324.664252139 1
3.3%
453462.420943009 1
3.3%
ValueCountFrequency (%)
456055.205802855 1
 
3.3%
456053.759563793 1
 
3.3%
456038.650926234 2
6.7%
455959.269196762 3
10.0%
455893.228194817 2
6.7%
455159.209918255 1
 
3.3%
453701.572334399 1
 
3.3%
453693.071412414 2
6.7%
453549.526436303 1
 
3.3%
453520.42735819 2
6.7%

위생업태명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
기타식품판매업
23 
<NA>
7 

Length

Max length7
Median length7
Mean length6.3
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 23
76.7%
<NA> 7
 
23.3%

Length

2024-05-11T15:56:07.928886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:08.147574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 23
76.7%
na 7
 
23.3%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
27 
0
3 

Length

Max length4
Median length4
Mean length3.7
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
90.0%
0 3
 
10.0%

Length

2024-05-11T15:56:08.357913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:08.550002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
90.0%
0 3
 
10.0%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
27 
0
3 

Length

Max length4
Median length4
Mean length3.7
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
90.0%
0 3
 
10.0%

Length

2024-05-11T15:56:08.761628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:09.314935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
90.0%
0 3
 
10.0%

영업장주변구분명
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing27
Missing (%)90.0%
Memory size372.0 B
2024-05-11T15:56:09.494557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length3
Min length2

Characters and Unicode

Total characters9
Distinct characters7
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 (%)33.3%

Sample

1st row기타
2nd row기타
3rd row아파트지역
ValueCountFrequency (%)
기타 2
66.7%
아파트지역 1
33.3%
2024-05-11T15:56:09.951175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 2
22.2%
타 2
22.2%
아 1
11.1%
파 1
11.1%
트 1
11.1%
지 1
11.1%
역 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 2
22.2%
타 2
22.2%
아 1
11.1%
파 1
11.1%
트 1
11.1%
지 1
11.1%
역 1
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 2
22.2%
타 2
22.2%
아 1
11.1%
파 1
11.1%
트 1
11.1%
지 1
11.1%
역 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 2
22.2%
타 2
22.2%
아 1
11.1%
파 1
11.1%
트 1
11.1%
지 1
11.1%
역 1
11.1%

등급구분명
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing27
Missing (%)90.0%
Memory size372.0 B
2024-05-11T15:56:10.216741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters6
Distinct characters4
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 (%)33.3%

Sample

1st row기타
2nd row기타
3rd row자율
ValueCountFrequency (%)
기타 2
66.7%
자율 1
33.3%
2024-05-11T15:56:10.673198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 2
33.3%
타 2
33.3%
자 1
16.7%
율 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 2
33.3%
타 2
33.3%
자 1
16.7%
율 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 2
33.3%
타 2
33.3%
자 1
16.7%
율 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 2
33.3%
타 2
33.3%
자 1
16.7%
율 1
16.7%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
27 
상수도전용
3 

Length

Max length5
Median length4
Mean length4.1
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
90.0%
상수도전용 3
 
10.0%

Length

2024-05-11T15:56:10.948952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:11.152821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
90.0%
상수도전용 3
 
10.0%

총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

본사종업원수
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
25 
0
5 

Length

Max length4
Median length4
Mean length3.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
83.3%
0 5
 
16.7%

Length

2024-05-11T15:56:11.359398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:11.579597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
83.3%
0 5
 
16.7%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
25 
0
5 

Length

Max length4
Median length4
Mean length3.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
83.3%
0 5
 
16.7%

Length

2024-05-11T15:56:11.772648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:11.986787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
83.3%
0 5
 
16.7%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
25 
0
5 

Length

Max length4
Median length4
Mean length3.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
83.3%
0 5
 
16.7%

Length

2024-05-11T15:56:12.184554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:12.467450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
83.3%
0 5
 
16.7%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
25 
0
5 

Length

Max length4
Median length4
Mean length3.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
83.3%
0 5
 
16.7%

Length

2024-05-11T15:56:12.667037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:12.884067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
83.3%
0 5
 
16.7%

건물소유구분명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
20 
임대
7 
자가
3 

Length

Max length4
Median length4
Mean length3.3333333
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> 20
66.7%
임대 7
 
23.3%
자가 3
 
10.0%

Length

2024-05-11T15:56:13.097992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:13.318787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
66.7%
임대 7
 
23.3%
자가 3
 
10.0%

보증액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

월세액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)8.7%
Missing7
Missing (%)23.3%
Memory size192.0 B
False
22 
True
 
1
(Missing)
7 
ValueCountFrequency (%)
False 22
73.3%
True 1
 
3.3%
(Missing) 7
 
23.3%
2024-05-11T15:56:13.495678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
23 
<NA>
7 

Length

Max length4
Median length1
Mean length1.7
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 23
76.7%
<NA> 7
 
23.3%

Length

2024-05-11T15:56:13.731017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:56:13.901553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
76.7%
na 7
 
23.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030000003000000-114-1996-0008919960701<NA>3폐업2폐업20050415<NA><NA><NA>02 4400783<NA>110847서울특별시 종로구 평창동 331-0<NA><NA>주)해태유통2002-09-03 00:00:00I2018-08-31 23:59:59.0기타식품판매업196965.164175455959.269197기타식품판매업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
130000003000000-114-1996-000901996-06-21<NA>1영업/정상1영업<NA><NA><NA><NA>02 737 9994657.86110-061서울특별시 종로구 신문로1가 24서울특별시 종로구 새문안로 91 (신문로1가)3182홈플러스 익스프레스 광화문점2024-03-18 14:20:26U2023-12-02 22:00:00.0기타식품판매업197700.034014452022.503467<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230000003000000-114-1999-0014019991201<NA>3폐업2폐업20020802<NA><NA><NA>02 1001000<NA>110522서울특별시 종로구 명륜2가 41-9<NA><NA>주)농심가후레쉬마켓명륜점2000-01-03 00:00:00I2018-08-31 23:59:59.0기타식품판매업199916.833506453462.420943기타식품판매업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
330000003000000-114-2000-0023020000407<NA>1영업/정상1영업<NA><NA><NA><NA>02 7392360<NA>110080서울특별시 종로구 무악동 82 무악현대아파트상가 지하1층 (지하101호)서울특별시 종로구 통일로 246-20, 지하1층 (무악동, 무악현대아파트상가)3025현대후레쉬마트2015-06-19 16:49:31I2018-08-31 23:59:59.0기타식품판매업196467.975088452566.13403기타식품판매업00아파트지역자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
430000003000000-114-2002-0000120020117<NA>3폐업2폐업20051010<NA><NA><NA>02 3914480<NA>110847서울특별시 종로구 평창동 182-2 창계빌딩 지1층<NA><NA>코사마트 평창점2002-01-17 00:00:00I2018-08-31 23:59:59.0기타식품판매업196986.931657456038.650926기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
530000003000000-114-2003-0000120030324<NA>3폐업2폐업20070913<NA><NA><NA>0236750628<NA>110522서울특별시 종로구 명륜2가 4 아남상가 지층<NA><NA>퀸할인매장2004-02-02 00:00:00I2018-08-31 23:59:59.0기타식품판매업199878.668538453693.071412기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0<NA><NA><NA>
630000003000000-114-2003-0000220030404<NA>3폐업2폐업20171106<NA><NA><NA>0236722239<NA>110530서울특별시 종로구 혜화동 185서울특별시 종로구 대학로 144 (혜화동)3084(주)서린유통2017-11-06 09:22:42I2018-08-31 23:59:59.0기타식품판매업200121.81372453518.007319기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
730000003000000-114-2004-0000120040213<NA>3폐업2폐업20040831<NA><NA><NA>0236769244<NA>110837서울특별시 종로구 창신동 23-816 이수@101동1호<NA><NA>진성마트2004-02-13 00:00:00I2018-08-31 23:59:59.0기타식품판매업201228.579824452855.249638기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
830000003000000-114-2004-0000220040819<NA>3폐업2폐업20200323<NA><NA><NA>0236769244<NA>110837서울특별시 종로구 창신동 23-816 이수아파트상가1층서울특별시 종로구 지봉로 87 (창신동,이수아파트상가1층)3095그랜드마트 창신점2020-03-23 15:35:16U2020-03-25 02:40:00.0기타식품판매업201228.579824452855.249638기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
930000003000000-114-2004-0000320041231<NA>3폐업2폐업20151019<NA><NA><NA>02 7650050<NA>110522서울특별시 종로구 명륜2가 211서울특별시 종로구 성균관로 12 (명륜2가)3074코아마트2015-11-24 13:59:23I2018-08-31 23:59:59.0기타식품판매업199769.965117453520.427358기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
2030000003000000-114-2013-0000120130318<NA>3폐업2폐업20190201<NA><NA><NA>02 3386009<NA>110033서울특별시 종로구 효자동 54 효자빌딩서울특별시 종로구 자하문로 70, 효자빌딩 (효자동)3042한국익간보2019-02-01 12:14:55U2019-02-05 02:40:00.0기타식품판매업197371.887813453324.664252기타식품판매업<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0<NA><NA><NA>
2130000003000000-114-2016-0000120160104<NA>3폐업2폐업20181212<NA><NA><NA>02 21271352<NA>110160서울특별시 종로구 공평동 1 하나투어빌딩 4층서울특별시 종로구 인사동5길 41, 4층 (공평동, 하나투어빌딩)3161(주)에스엠면세점2018-12-12 13:41:21U2018-12-14 02:40:00.0기타식품판매업198531.019988452166.915601기타식품판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>임대<NA><NA>Y0<NA><NA><NA>
2230000003000000-114-2016-000022016-02-23<NA>3폐업2폐업2023-05-19<NA><NA><NA>02 32179151390.0110-847서울특별시 종로구 평창동 323-4 1층서울특별시 종로구 평창문화로 39, 1층 (평창동)3008롯데쇼핑(주)롯데슈퍼 종로평창점2023-05-19 16:00:58U2022-12-04 22:01:00.0기타식품판매업196896.329083455893.228195<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2330000003000000-114-2016-000032016-06-23<NA>3폐업2폐업2023-10-27<NA><NA><NA>02 34170051594.0110-847서울특별시 종로구 평창동 331 지하1층서울특별시 종로구 평창11길 3, 지하1층 (평창동, 뉴본빌딩)3008365할인마트2023-10-27 10:10:49U2022-10-30 22:09:00.0기타식품판매업196965.164175455959.269197<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2430000003000000-114-2016-0000420160921<NA>1영업/정상1영업<NA><NA><NA><NA>02 395 1688<NA>110816서울특별시 종로구 부암동 182-1 청하빌딩 3,4층서울특별시 종로구 자하문로 280, 3,4층 (부암동, 청하빌딩)3017청하고려인삼(주)2018-05-01 15:49:48I2018-08-31 23:59:59.0기타식품판매업196554.89921455159.209918기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0<NA><NA><NA>
2530000003000000-114-2017-0000120171207<NA>1영업/정상1영업<NA><NA><NA><NA>02 36722231<NA>110530서울특별시 종로구 혜화동 185 중원빌딩서울특별시 종로구 대학로 144, 지하1층 (혜화동)3084레몬마트2017-12-07 14:29:42I2018-08-31 23:59:59.0기타식품판매업200121.81372453518.007319기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0<NA><NA><NA>
2630000003000000-114-2019-0000120190611<NA>1영업/정상1영업<NA><NA><NA><NA><NA>386.44110522서울특별시 종로구 명륜2가 211 유니지오서울특별시 종로구 성균관로 12, 유니지오 지상1층 101~102호 (명륜2가)3074성대마트2019-08-06 15:03:41U2019-08-08 02:40:00.0기타식품판매업199769.965117453520.427358기타식품판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0<NA><NA><NA>
2730000003000000-114-2021-000012021-07-27<NA>3폐업2폐업2023-06-19<NA><NA><NA>02 227249801388.28110-420서울특별시 종로구 관수동 20 국일관드림펠리스 지하1층서울특별시 종로구 수표로 96, 국일관드림펠리스 지하1층 (관수동)3192국일관식자재마트2023-06-19 10:49:43U2022-12-05 22:01:00.0기타식품판매업199045.043603451939.677287<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2830000003000000-114-2023-000012023-05-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>314.0110-847서울특별시 종로구 평창동 323-4 1층서울특별시 종로구 평창문화로 39, 1층 (평창동)3008(주)럭키할인마트2023-05-24 16:42:20I2022-12-04 22:06:00.0기타식품판매업196896.329083455893.228195<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2930000003000000-114-2024-000012024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA>02 738 1010394.5110-240서울특별시 종로구 안국동 175-3서울특별시 종로구 율곡로 39, 1층 (안국동)3061서울동행상회2024-05-09 17:19:43I2023-12-04 23:01:00.0기타식품판매업198507.43712452641.178442<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>