Overview

Dataset statistics

Number of variables44
Number of observations252
Missing cells2297
Missing cells (%)20.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory92.7 KiB
Average record size in memory376.5 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric5
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
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-18186/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (67.9%)Imbalance
여성종사자수 is highly imbalanced (61.0%)Imbalance
영업장주변구분명 is highly imbalanced (78.0%)Imbalance
등급구분명 is highly imbalanced (78.1%)Imbalance
총인원 is highly imbalanced (75.9%)Imbalance
월세액 is highly imbalanced (56.3%)Imbalance
인허가취소일자 has 252 (100.0%) missing valuesMissing
폐업일자 has 36 (14.3%) missing valuesMissing
휴업시작일자 has 252 (100.0%) missing valuesMissing
휴업종료일자 has 252 (100.0%) missing valuesMissing
재개업일자 has 252 (100.0%) missing valuesMissing
전화번호 has 124 (49.2%) missing valuesMissing
소재지면적 has 51 (20.2%) missing valuesMissing
도로명주소 has 125 (49.6%) missing valuesMissing
도로명우편번호 has 127 (50.4%) missing valuesMissing
좌표정보(X) has 3 (1.2%) missing valuesMissing
좌표정보(Y) has 3 (1.2%) missing valuesMissing
다중이용업소여부 has 31 (12.3%) missing valuesMissing
시설총규모 has 31 (12.3%) missing valuesMissing
전통업소지정번호 has 252 (100.0%) missing valuesMissing
전통업소주된음식 has 252 (100.0%) missing valuesMissing
홈페이지 has 252 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 5 (2.0%) zerosZeros
시설총규모 has 189 (75.0%) zerosZeros

Reproduction

Analysis started2024-04-29 19:38:10.500792
Analysis finished2024-04-29 19:38:11.403137
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3090000
252 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 252
100.0%

Length

2024-04-30T04:38:11.469560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:11.550597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 252
100.0%

관리번호
Text

UNIQUE 

Distinct252
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-30T04:38:11.736418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5544
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

Unique252 ?
Unique (%)100.0%

Sample

1st row3090000-109-1988-00282
2nd row3090000-109-1996-00183
3rd row3090000-109-1997-00184
4th row3090000-109-1997-00185
5th row3090000-109-1997-00186
ValueCountFrequency (%)
3090000-109-1988-00282 1
 
0.4%
3090000-109-2010-00010 1
 
0.4%
3090000-109-2012-00005 1
 
0.4%
3090000-109-2009-00007 1
 
0.4%
3090000-109-2009-00008 1
 
0.4%
3090000-109-2009-00009 1
 
0.4%
3090000-109-2010-00001 1
 
0.4%
3090000-109-2010-00002 1
 
0.4%
3090000-109-2010-00003 1
 
0.4%
3090000-109-2010-00004 1
 
0.4%
Other values (242) 242
96.0%
2024-04-30T04:38:12.142764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2838
51.2%
- 756
 
13.6%
9 565
 
10.2%
1 443
 
8.0%
2 349
 
6.3%
3 325
 
5.9%
5 69
 
1.2%
4 66
 
1.2%
8 46
 
0.8%
6 45
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4788
86.4%
Dash Punctuation 756
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2838
59.3%
9 565
 
11.8%
1 443
 
9.3%
2 349
 
7.3%
3 325
 
6.8%
5 69
 
1.4%
4 66
 
1.4%
8 46
 
1.0%
6 45
 
0.9%
7 42
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5544
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2838
51.2%
- 756
 
13.6%
9 565
 
10.2%
1 443
 
8.0%
2 349
 
6.3%
3 325
 
5.9%
5 69
 
1.2%
4 66
 
1.2%
8 46
 
0.8%
6 45
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2838
51.2%
- 756
 
13.6%
9 565
 
10.2%
1 443
 
8.0%
2 349
 
6.3%
3 325
 
5.9%
5 69
 
1.2%
4 66
 
1.2%
8 46
 
0.8%
6 45
 
0.8%

인허가일자
Date

Distinct244
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1988-02-04 00:00:00
Maximum2024-04-03 00:00:00
2024-04-30T04:38:12.264089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:38:12.376920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing252
Missing (%)100.0%
Memory size2.3 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3
216 
1
36 

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 (%)
3 216
85.7%
1 36
 
14.3%

Length

2024-04-30T04:38:12.481670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:12.555189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 216
85.7%
1 36
 
14.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
216 
영업/정상
36 

Length

Max length5
Median length2
Mean length2.4285714
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 216
85.7%
영업/정상 36
 
14.3%

Length

2024-04-30T04:38:12.646849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:12.734079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 216
85.7%
영업/정상 36
 
14.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2
216 
1
36 

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 (%)
2 216
85.7%
1 36
 
14.3%

Length

2024-04-30T04:38:12.813938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:12.907660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 216
85.7%
1 36
 
14.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
216 
영업
36 

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 216
85.7%
영업 36
 
14.3%

Length

2024-04-30T04:38:12.984544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:13.083729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 216
85.7%
영업 36
 
14.3%

폐업일자
Date

MISSING 

Distinct192
Distinct (%)88.9%
Missing36
Missing (%)14.3%
Memory size2.1 KiB
Minimum1998-09-15 00:00:00
Maximum2023-12-28 00:00:00
2024-04-30T04:38:13.176902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:38:13.303174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing252
Missing (%)100.0%
Memory size2.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing252
Missing (%)100.0%
Memory size2.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing252
Missing (%)100.0%
Memory size2.3 KiB

전화번호
Text

MISSING 

Distinct116
Distinct (%)90.6%
Missing124
Missing (%)49.2%
Memory size2.1 KiB
2024-04-30T04:38:13.531634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.1875
Min length2

Characters and Unicode

Total characters1304
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

Unique107 ?
Unique (%)83.6%

Sample

1st row02 9050374
2nd row02
3rd row02 9553595
4th row02 9549081
5th row02 9924848
ValueCountFrequency (%)
02 70
29.5%
0234996000 5
 
2.1%
997 4
 
1.7%
031 4
 
1.7%
907 4
 
1.7%
956 3
 
1.3%
903 3
 
1.3%
6041 2
 
0.8%
990 2
 
0.8%
033 2
 
0.8%
Other values (129) 138
58.2%
2024-04-30T04:38:13.886399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 238
18.3%
9 190
14.6%
2 180
13.8%
138
10.6%
3 101
7.7%
4 93
 
7.1%
6 81
 
6.2%
5 80
 
6.1%
1 78
 
6.0%
8 69
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1166
89.4%
Space Separator 138
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 238
20.4%
9 190
16.3%
2 180
15.4%
3 101
8.7%
4 93
 
8.0%
6 81
 
6.9%
5 80
 
6.9%
1 78
 
6.7%
8 69
 
5.9%
7 56
 
4.8%
Space Separator
ValueCountFrequency (%)
138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 238
18.3%
9 190
14.6%
2 180
13.8%
138
10.6%
3 101
7.7%
4 93
 
7.1%
6 81
 
6.2%
5 80
 
6.1%
1 78
 
6.0%
8 69
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 238
18.3%
9 190
14.6%
2 180
13.8%
138
10.6%
3 101
7.7%
4 93
 
7.1%
6 81
 
6.2%
5 80
 
6.1%
1 78
 
6.0%
8 69
 
5.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct102
Distinct (%)50.7%
Missing51
Missing (%)20.2%
Infinite0
Infinite (%)0.0%
Mean39.614826
Minimum0
Maximum726
Zeros5
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T04:38:14.020458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q16.6
median15
Q339
95-th percentile123
Maximum726
Range726
Interquartile range (IQR)32.4

Descriptive statistics

Standard deviation81.766951
Coefficient of variation (CV)2.0640492
Kurtosis44.106536
Mean39.614826
Median Absolute Deviation (MAD)11.7
Skewness6.0659309
Sum7962.58
Variance6685.8343
MonotonicityNot monotonic
2024-04-30T04:38:14.146621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.6 14
 
5.6%
3.3 11
 
4.4%
10.0 10
 
4.0%
6.0 9
 
3.6%
3.0 8
 
3.2%
33.0 6
 
2.4%
15.0 6
 
2.4%
9.0 5
 
2.0%
0.0 5
 
2.0%
8.0 4
 
1.6%
Other values (92) 123
48.8%
(Missing) 51
20.2%
ValueCountFrequency (%)
0.0 5
2.0%
1.0 1
 
0.4%
1.6 1
 
0.4%
2.0 2
 
0.8%
3.0 8
3.2%
3.21 1
 
0.4%
3.3 11
4.4%
4.0 3
 
1.2%
4.4 1
 
0.4%
4.5 1
 
0.4%
ValueCountFrequency (%)
726.0 1
0.4%
669.74 1
0.4%
442.0 1
0.4%
230.0 1
0.4%
218.29 1
0.4%
155.0 1
0.4%
150.0 1
0.4%
135.0 1
0.4%
132.0 1
0.4%
126.84 1
0.4%

소재지우편번호
Text

Distinct83
Distinct (%)33.1%
Missing1
Missing (%)0.4%
Memory size2.1 KiB
2024-04-30T04:38:14.368479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0836653
Min length6

Characters and Unicode

Total characters1527
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 (%)19.5%

Sample

1st row132822
2nd row132851
3rd row132833
4th row132820
5th row132896
ValueCountFrequency (%)
132898 51
20.3%
132854 37
 
14.7%
132864 9
 
3.6%
132904 9
 
3.6%
132820 7
 
2.8%
132918 6
 
2.4%
132821 5
 
2.0%
132920 5
 
2.0%
132924 5
 
2.0%
132720 5
 
2.0%
Other values (73) 112
44.6%
2024-04-30T04:38:14.695824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 302
19.8%
1 300
19.6%
3 272
17.8%
8 261
17.1%
9 133
8.7%
4 73
 
4.8%
5 62
 
4.1%
0 56
 
3.7%
6 30
 
2.0%
- 21
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1506
98.6%
Dash Punctuation 21
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 302
20.1%
1 300
19.9%
3 272
18.1%
8 261
17.3%
9 133
8.8%
4 73
 
4.8%
5 62
 
4.1%
0 56
 
3.7%
6 30
 
2.0%
7 17
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1527
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 302
19.8%
1 300
19.6%
3 272
17.8%
8 261
17.1%
9 133
8.7%
4 73
 
4.8%
5 62
 
4.1%
0 56
 
3.7%
6 30
 
2.0%
- 21
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1527
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 302
19.8%
1 300
19.6%
3 272
17.8%
8 261
17.1%
9 133
8.7%
4 73
 
4.8%
5 62
 
4.1%
0 56
 
3.7%
6 30
 
2.0%
- 21
 
1.4%

지번주소
Text

Distinct193
Distinct (%)76.9%
Missing1
Missing (%)0.4%
Memory size2.1 KiB
2024-04-30T04:38:15.016597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length23.760956
Min length17

Characters and Unicode

Total characters5964
Distinct characters143
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

Unique169 ?
Unique (%)67.3%

Sample

1st row서울특별시 도봉구 도봉동 633-8
2nd row서울특별시 도봉구 방학동 695-8
3rd row서울특별시 도봉구 방학동 397-15
4th row서울특별시 도봉구 도봉동 617-25
5th row서울특별시 도봉구 쌍문동 707-1
ValueCountFrequency (%)
서울특별시 250
20.6%
도봉구 250
20.6%
창동 115
 
9.5%
방학동 63
 
5.2%
1-10 57
 
4.7%
쌍문동 39
 
3.2%
도봉동 34
 
2.8%
1층 29
 
2.4%
지하1층 25
 
2.1%
717-6 21
 
1.7%
Other values (236) 330
27.2%
2024-04-30T04:38:15.400801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1172
19.7%
1 333
 
5.6%
도 291
 
4.9%
봉 290
 
4.9%
동 277
 
4.6%
시 252
 
4.2%
서 250
 
4.2%
울 250
 
4.2%
특 250
 
4.2%
별 250
 
4.2%
Other values (133) 2349
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3418
57.3%
Space Separator 1172
 
19.7%
Decimal Number 1138
 
19.1%
Dash Punctuation 225
 
3.8%
Uppercase Letter 6
 
0.1%
Other Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 291
 
8.5%
봉 290
 
8.5%
동 277
 
8.1%
시 252
 
7.4%
서 250
 
7.3%
울 250
 
7.3%
특 250
 
7.3%
별 250
 
7.3%
구 250
 
7.3%
창 133
 
3.9%
Other values (114) 925
27.1%
Decimal Number
ValueCountFrequency (%)
1 333
29.3%
7 141
12.4%
0 129
 
11.3%
6 123
 
10.8%
2 93
 
8.2%
3 85
 
7.5%
5 83
 
7.3%
4 58
 
5.1%
8 50
 
4.4%
9 43
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
G 2
33.3%
L 2
33.3%
B 2
33.3%
Space Separator
ValueCountFrequency (%)
1172
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 225
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3418
57.3%
Common 2540
42.6%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 291
 
8.5%
봉 290
 
8.5%
동 277
 
8.1%
시 252
 
7.4%
서 250
 
7.3%
울 250
 
7.3%
특 250
 
7.3%
별 250
 
7.3%
구 250
 
7.3%
창 133
 
3.9%
Other values (114) 925
27.1%
Common
ValueCountFrequency (%)
1172
46.1%
1 333
 
13.1%
- 225
 
8.9%
7 141
 
5.6%
0 129
 
5.1%
6 123
 
4.8%
2 93
 
3.7%
3 85
 
3.3%
5 83
 
3.3%
4 58
 
2.3%
Other values (6) 98
 
3.9%
Latin
ValueCountFrequency (%)
G 2
33.3%
L 2
33.3%
B 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3418
57.3%
ASCII 2546
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1172
46.0%
1 333
 
13.1%
- 225
 
8.8%
7 141
 
5.5%
0 129
 
5.1%
6 123
 
4.8%
2 93
 
3.7%
3 85
 
3.3%
5 83
 
3.3%
4 58
 
2.3%
Other values (9) 104
 
4.1%
Hangul
ValueCountFrequency (%)
도 291
 
8.5%
봉 290
 
8.5%
동 277
 
8.1%
시 252
 
7.4%
서 250
 
7.3%
울 250
 
7.3%
특 250
 
7.3%
별 250
 
7.3%
구 250
 
7.3%
창 133
 
3.9%
Other values (114) 925
27.1%

도로명주소
Text

MISSING 

Distinct112
Distinct (%)88.2%
Missing125
Missing (%)49.6%
Memory size2.1 KiB
2024-04-30T04:38:15.673414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length42
Mean length30.551181
Min length23

Characters and Unicode

Total characters3880
Distinct characters143
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

Unique107 ?
Unique (%)84.3%

Sample

1st row서울특별시 도봉구 시루봉로15라길 33 (방학동)
2nd row서울특별시 도봉구 도봉로127길 22-5 (쌍문동)
3rd row서울특별시 도봉구 도봉로170길 16 (도봉동)
4th row서울특별시 도봉구 해등로 166 (쌍문동)
5th row서울특별시 도봉구 마들로11길 20 (창동)
ValueCountFrequency (%)
서울특별시 126
 
16.6%
도봉구 126
 
16.6%
창동 44
 
5.8%
쌍문동 26
 
3.4%
1층 25
 
3.3%
도봉동 24
 
3.2%
마들로11길 21
 
2.8%
20 21
 
2.8%
방학동 19
 
2.5%
2층 11
 
1.5%
Other values (211) 315
41.6%
2024-04-30T04:38:16.070912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
631
 
16.3%
도 206
 
5.3%
봉 202
 
5.2%
1 195
 
5.0%
동 141
 
3.6%
시 135
 
3.5%
로 130
 
3.4%
) 128
 
3.3%
( 128
 
3.3%
구 127
 
3.3%
Other values (133) 1857
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2239
57.7%
Decimal Number 635
 
16.4%
Space Separator 631
 
16.3%
Close Punctuation 128
 
3.3%
Open Punctuation 128
 
3.3%
Other Punctuation 98
 
2.5%
Dash Punctuation 13
 
0.3%
Uppercase Letter 7
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 206
 
9.2%
봉 202
 
9.0%
동 141
 
6.3%
시 135
 
6.0%
로 130
 
5.8%
구 127
 
5.7%
서 126
 
5.6%
울 126
 
5.6%
별 126
 
5.6%
특 126
 
5.6%
Other values (114) 794
35.5%
Decimal Number
ValueCountFrequency (%)
1 195
30.7%
2 88
13.9%
0 72
 
11.3%
3 59
 
9.3%
5 47
 
7.4%
6 42
 
6.6%
4 38
 
6.0%
7 36
 
5.7%
8 31
 
4.9%
9 27
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 3
42.9%
G 2
28.6%
L 2
28.6%
Space Separator
ValueCountFrequency (%)
631
100.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 128
100.0%
Other Punctuation
ValueCountFrequency (%)
, 98
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2239
57.7%
Common 1634
42.1%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 206
 
9.2%
봉 202
 
9.0%
동 141
 
6.3%
시 135
 
6.0%
로 130
 
5.8%
구 127
 
5.7%
서 126
 
5.6%
울 126
 
5.6%
별 126
 
5.6%
특 126
 
5.6%
Other values (114) 794
35.5%
Common
ValueCountFrequency (%)
631
38.6%
1 195
 
11.9%
) 128
 
7.8%
( 128
 
7.8%
, 98
 
6.0%
2 88
 
5.4%
0 72
 
4.4%
3 59
 
3.6%
5 47
 
2.9%
6 42
 
2.6%
Other values (6) 146
 
8.9%
Latin
ValueCountFrequency (%)
B 3
42.9%
G 2
28.6%
L 2
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2239
57.7%
ASCII 1641
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
631
38.5%
1 195
 
11.9%
) 128
 
7.8%
( 128
 
7.8%
, 98
 
6.0%
2 88
 
5.4%
0 72
 
4.4%
3 59
 
3.6%
5 47
 
2.9%
6 42
 
2.6%
Other values (9) 153
 
9.3%
Hangul
ValueCountFrequency (%)
도 206
 
9.2%
봉 202
 
9.0%
동 141
 
6.3%
시 135
 
6.0%
로 130
 
5.8%
구 127
 
5.7%
서 126
 
5.6%
울 126
 
5.6%
별 126
 
5.6%
특 126
 
5.6%
Other values (114) 794
35.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)55.2%
Missing127
Missing (%)50.4%
Infinite0
Infinite (%)0.0%
Mean1470.6
Minimum1302
Maximum11159
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T04:38:16.222639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1302
5-th percentile1307
Q11334
median1405
Q31446
95-th percentile1478.8
Maximum11159
Range9857
Interquartile range (IQR)112

Descriptive statistics

Standard deviation875.36665
Coefficient of variation (CV)0.59524456
Kurtosis123.93759
Mean1470.6
Median Absolute Deviation (MAD)48
Skewness11.109542
Sum183825
Variance766266.77
MonotonicityNot monotonic
2024-04-30T04:38:16.353657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1413 21
 
8.3%
1452 4
 
1.6%
1471 3
 
1.2%
1329 3
 
1.2%
1332 3
 
1.2%
1321 3
 
1.2%
1334 3
 
1.2%
1391 3
 
1.2%
1315 3
 
1.2%
1405 3
 
1.2%
Other values (59) 76
30.2%
(Missing) 127
50.4%
ValueCountFrequency (%)
1302 1
 
0.4%
1303 3
1.2%
1306 2
0.8%
1307 2
0.8%
1308 1
 
0.4%
1310 2
0.8%
1314 2
0.8%
1315 3
1.2%
1318 1
 
0.4%
1319 1
 
0.4%
ValueCountFrequency (%)
11159 1
 
0.4%
1487 1
 
0.4%
1486 2
0.8%
1483 1
 
0.4%
1482 1
 
0.4%
1479 1
 
0.4%
1478 1
 
0.4%
1476 1
 
0.4%
1472 1
 
0.4%
1471 3
1.2%

사업장명
Text

Distinct236
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-30T04:38:16.570660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length6.1507937
Min length2

Characters and Unicode

Total characters1550
Distinct characters314
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique221 ?
Unique (%)87.7%

Sample

1st row영우식품
2nd row삼원마트
3rd row정림유통
4th row진원식품
5th row노송식품
ValueCountFrequency (%)
주 4
 
1.4%
농협유통창동농산물종합유통센타 3
 
1.1%
안흥식품 2
 
0.7%
롯데마트 2
 
0.7%
주식회사 2
 
0.7%
럭키마트 2
 
0.7%
주)한미연 2
 
0.7%
서울식연사업부 2
 
0.7%
광천토굴전통식품 2
 
0.7%
전주한과 2
 
0.7%
Other values (247) 256
91.8%
2024-04-30T04:38:16.939377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 63
 
4.1%
) 55
 
3.5%
( 54
 
3.5%
식 52
 
3.4%
품 47
 
3.0%
마 36
 
2.3%
농 34
 
2.2%
트 33
 
2.1%
이 29
 
1.9%
유 29
 
1.9%
Other values (304) 1118
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1382
89.2%
Close Punctuation 55
 
3.5%
Open Punctuation 54
 
3.5%
Space Separator 27
 
1.7%
Uppercase Letter 18
 
1.2%
Decimal Number 11
 
0.7%
Lowercase Letter 2
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 63
 
4.6%
식 52
 
3.8%
품 47
 
3.4%
마 36
 
2.6%
농 34
 
2.5%
트 33
 
2.4%
이 29
 
2.1%
유 29
 
2.1%
통 27
 
2.0%
한 25
 
1.8%
Other values (280) 1007
72.9%
Uppercase Letter
ValueCountFrequency (%)
K 3
16.7%
N 2
11.1%
S 2
11.1%
H 2
11.1%
T 2
11.1%
C 1
 
5.6%
I 1
 
5.6%
U 1
 
5.6%
B 1
 
5.6%
A 1
 
5.6%
Other values (2) 2
11.1%
Decimal Number
ValueCountFrequency (%)
2 3
27.3%
7 2
18.2%
1 2
18.2%
4 2
18.2%
3 1
 
9.1%
6 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
i 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1381
89.1%
Common 148
 
9.5%
Latin 20
 
1.3%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 63
 
4.6%
식 52
 
3.8%
품 47
 
3.4%
마 36
 
2.6%
농 34
 
2.5%
트 33
 
2.4%
이 29
 
2.1%
유 29
 
2.1%
통 27
 
2.0%
한 25
 
1.8%
Other values (279) 1006
72.8%
Latin
ValueCountFrequency (%)
K 3
15.0%
N 2
10.0%
S 2
10.0%
H 2
10.0%
T 2
10.0%
C 1
 
5.0%
I 1
 
5.0%
s 1
 
5.0%
U 1
 
5.0%
i 1
 
5.0%
Other values (4) 4
20.0%
Common
ValueCountFrequency (%)
) 55
37.2%
( 54
36.5%
27
18.2%
2 3
 
2.0%
7 2
 
1.4%
1 2
 
1.4%
4 2
 
1.4%
- 1
 
0.7%
3 1
 
0.7%
6 1
 
0.7%
Han
ValueCountFrequency (%)
茶 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1381
89.1%
ASCII 168
 
10.8%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 63
 
4.6%
식 52
 
3.8%
품 47
 
3.4%
마 36
 
2.6%
농 34
 
2.5%
트 33
 
2.4%
이 29
 
2.1%
유 29
 
2.1%
통 27
 
2.0%
한 25
 
1.8%
Other values (279) 1006
72.8%
ASCII
ValueCountFrequency (%)
) 55
32.7%
( 54
32.1%
27
16.1%
2 3
 
1.8%
K 3
 
1.8%
N 2
 
1.2%
S 2
 
1.2%
H 2
 
1.2%
T 2
 
1.2%
7 2
 
1.2%
Other values (14) 16
 
9.5%
CJK
ValueCountFrequency (%)
茶 1
100.0%

최종수정일자
Date

Distinct248
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1999-03-12 00:00:00
Maximum2024-04-03 14:51:16
2024-04-30T04:38:17.233020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:38:17.353790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
I
177 
U
75 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 177
70.2%
U 75
29.8%

Length

2024-04-30T04:38:17.463888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:17.540135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 177
70.2%
u 75
29.8%

데이터갱신일자
Date

Distinct72
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-30T04:38:17.640800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:38:17.749295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
식품소분업
252 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 252
100.0%

Length

2024-04-30T04:38:17.852247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:17.925088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 252
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct139
Distinct (%)55.8%
Missing3
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean203675.47
Minimum201249.69
Maximum213662.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T04:38:18.013144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201249.69
5-th percentile202479.6
Q1203121.47
median203790.01
Q3204199.16
95-th percentile204413.62
Maximum213662.18
Range12412.491
Interquartile range (IQR)1077.6917

Descriptive statistics

Standard deviation922.74936
Coefficient of variation (CV)0.0045304884
Kurtosis54.5964
Mean203675.47
Median Absolute Deviation (MAD)623.60301
Skewness4.7974444
Sum50715193
Variance851466.39
MonotonicityNot monotonic
2024-04-30T04:38:18.154294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204413.616574592 57
22.6%
203920.444016775 21
 
8.3%
203790.013568785 13
 
5.2%
204107.090272108 6
 
2.4%
203104.375371508 3
 
1.2%
203567.981260191 2
 
0.8%
203327.70552998 2
 
0.8%
203090.117343106 2
 
0.8%
204199.156989282 2
 
0.8%
203348.810465629 2
 
0.8%
Other values (129) 139
55.2%
(Missing) 3
 
1.2%
ValueCountFrequency (%)
201249.685996509 1
0.4%
201317.612596564 1
0.4%
201939.391046019 1
0.4%
201952.133207596 1
0.4%
202081.861176179 1
0.4%
202147.52144553 1
0.4%
202164.919977603 2
0.8%
202199.679730999 1
0.4%
202237.410410982 1
0.4%
202416.898467468 2
0.8%
ValueCountFrequency (%)
213662.177362742 1
 
0.4%
204414.113861369 1
 
0.4%
204413.616574592 57
22.6%
204372.245062863 1
 
0.4%
204357.382835077 1
 
0.4%
204258.587772043 1
 
0.4%
204199.156989282 2
 
0.8%
204169.847670316 1
 
0.4%
204136.58447783 1
 
0.4%
204107.090272108 6
 
2.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct139
Distinct (%)55.8%
Missing3
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean461857.86
Minimum459022.55
Maximum485365.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T04:38:18.285075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum459022.55
5-th percentile459649.7
Q1461072.64
median461378.59
Q3462830.48
95-th percentile464092.19
Maximum485365.54
Range26342.985
Interquartile range (IQR)1757.8425

Descriptive statistics

Standard deviation1960.7389
Coefficient of variation (CV)0.0042453296
Kurtosis82.802697
Mean461857.86
Median Absolute Deviation (MAD)1035.0545
Skewness6.9842504
Sum1.1500261 × 108
Variance3844496.9
MonotonicityNot monotonic
2024-04-30T04:38:18.416591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461378.588676784 57
22.6%
462830.484935873 21
 
8.3%
462495.417040876 13
 
5.2%
461072.642448925 6
 
2.4%
462460.664149857 3
 
1.2%
463097.692108604 2
 
0.8%
461663.551651071 2
 
0.8%
460093.406417139 2
 
0.8%
464552.486156478 2
 
0.8%
459757.634551893 2
 
0.8%
Other values (129) 139
55.2%
(Missing) 3
 
1.2%
ValueCountFrequency (%)
459022.55170921 1
0.4%
459038.222873743 1
0.4%
459047.53542317 1
0.4%
459130.893656814 1
0.4%
459161.469084389 1
0.4%
459286.989226971 1
0.4%
459334.795917304 1
0.4%
459499.0514426 1
0.4%
459518.895773039 1
0.4%
459539.955753725 1
0.4%
ValueCountFrequency (%)
485365.536453517 1
0.4%
464907.896951126 1
0.4%
464814.717432497 1
0.4%
464788.847055332 2
0.8%
464664.845668554 1
0.4%
464633.761055876 1
0.4%
464552.486156478 2
0.8%
464215.186872943 1
0.4%
464212.297931928 1
0.4%
464208.266258174 1
0.4%

위생업태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
식품소분업
221 
<NA>
31 

Length

Max length5
Median length5
Mean length4.8769841
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 221
87.7%
<NA> 31
 
12.3%

Length

2024-04-30T04:38:18.533238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:18.621145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 221
87.7%
na 31
 
12.3%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
219 
0
29 
1
 
3
2
 
1

Length

Max length4
Median length4
Mean length3.6071429
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row1
2nd row0
3rd row1
4th row2
5th row0

Common Values

ValueCountFrequency (%)
<NA> 219
86.9%
0 29
 
11.5%
1 3
 
1.2%
2 1
 
0.4%

Length

2024-04-30T04:38:18.703395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:18.788853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
86.9%
0 29
 
11.5%
1 3
 
1.2%
2 1
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
219 
0
30 
1
 
3

Length

Max length4
Median length4
Mean length3.6071429
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 219
86.9%
0 30
 
11.9%
1 3
 
1.2%

Length

2024-04-30T04:38:18.879469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:18.960781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
86.9%
0 30
 
11.9%
1 3
 
1.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
235 
기타
 
9
주택가주변
 
7
아파트지역
 
1

Length

Max length5
Median length4
Mean length3.9603175
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 235
93.3%
기타 9
 
3.6%
주택가주변 7
 
2.8%
아파트지역 1
 
0.4%

Length

2024-04-30T04:38:19.050295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:19.132340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 235
93.3%
기타 9
 
3.6%
주택가주변 7
 
2.8%
아파트지역 1
 
0.4%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
235 
기타
 
10
자율
 
6
지도
 
1

Length

Max length4
Median length4
Mean length3.8650794
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 235
93.3%
기타 10
 
4.0%
자율 6
 
2.4%
지도 1
 
0.4%

Length

2024-04-30T04:38:19.230531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:19.320145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 235
93.3%
기타 10
 
4.0%
자율 6
 
2.4%
지도 1
 
0.4%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
211 
상수도전용
41 

Length

Max length5
Median length4
Mean length4.1626984
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 211
83.7%
상수도전용 41
 
16.3%

Length

2024-04-30T04:38:19.408934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:19.485707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 211
83.7%
상수도전용 41
 
16.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
242 
0
 
10

Length

Max length4
Median length4
Mean length3.8809524
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> 242
96.0%
0 10
 
4.0%

Length

2024-04-30T04:38:19.578602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:19.667905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 242
96.0%
0 10
 
4.0%

본사종업원수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
153 
0
99 

Length

Max length4
Median length4
Mean length2.8214286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 153
60.7%
0 99
39.3%

Length

2024-04-30T04:38:19.762445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:19.848801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 153
60.7%
0 99
39.3%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
152 
0
98 
1
 
2

Length

Max length4
Median length4
Mean length2.8095238
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
60.3%
0 98
38.9%
1 2
 
0.8%

Length

2024-04-30T04:38:19.936886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:20.023069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
60.3%
0 98
38.9%
1 2
 
0.8%

공장판매직종업원수
Categorical

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
150 
0
93 
1
 
7
2
 
2

Length

Max length4
Median length4
Mean length2.7857143
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 150
59.5%
0 93
36.9%
1 7
 
2.8%
2 2
 
0.8%

Length

2024-04-30T04:38:20.112226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:20.200060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
59.5%
0 93
36.9%
1 7
 
2.8%
2 2
 
0.8%

공장생산직종업원수
Categorical

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
151 
0
95 
1
 
5
2
 
1

Length

Max length4
Median length4
Mean length2.797619
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
59.9%
0 95
37.7%
1 5
 
2.0%
2 1
 
0.4%

Length

2024-04-30T04:38:20.295348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:20.389100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
59.9%
0 95
37.7%
1 5
 
2.0%
2 1
 
0.4%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
100 
임대
100 
자가
52 

Length

Max length4
Median length2
Mean length2.7936508
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> 100
39.7%
임대 100
39.7%
자가 52
20.6%

Length

2024-04-30T04:38:20.502875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:20.602157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 100
39.7%
임대 100
39.7%
자가 52
20.6%

보증액
Categorical

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
167 
0
82 
5000000
 
2
15000000
 
1

Length

Max length8
Median length4
Mean length3.0634921
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 167
66.3%
0 82
32.5%
5000000 2
 
0.8%
15000000 1
 
0.4%

Length

2024-04-30T04:38:20.710884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:20.806093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 167
66.3%
0 82
32.5%
5000000 2
 
0.8%
15000000 1
 
0.4%

월세액
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
167 
0
82 
450000
 
1
1100000
 
1
400000
 
1

Length

Max length7
Median length4
Mean length3.0515873
Min length1

Unique

Unique3 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 167
66.3%
0 82
32.5%
450000 1
 
0.4%
1100000 1
 
0.4%
400000 1
 
0.4%

Length

2024-04-30T04:38:20.916205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:21.023668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 167
66.3%
0 82
32.5%
450000 1
 
0.4%
1100000 1
 
0.4%
400000 1
 
0.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing31
Missing (%)12.3%
Memory size636.0 B
False
221 
(Missing)
31 
ValueCountFrequency (%)
False 221
87.7%
(Missing) 31
 
12.3%
2024-04-30T04:38:21.115594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)13.1%
Missing31
Missing (%)12.3%
Infinite0
Infinite (%)0.0%
Mean4.8659729
Minimum0
Maximum135
Zeros189
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T04:38:21.199712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile33.5
Maximum135
Range135
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.026736
Coefficient of variation (CV)3.704652
Kurtosis25.166869
Mean4.8659729
Median Absolute Deviation (MAD)0
Skewness4.7983157
Sum1075.38
Variance324.96321
MonotonicityNot monotonic
2024-04-30T04:38:21.330755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 189
75.0%
6.0 2
 
0.8%
9.0 2
 
0.8%
33.0 2
 
0.8%
3.3 2
 
0.8%
70.0 1
 
0.4%
4.5 1
 
0.4%
52.8 1
 
0.4%
12.25 1
 
0.4%
9.9 1
 
0.4%
Other values (19) 19
 
7.5%
(Missing) 31
 
12.3%
ValueCountFrequency (%)
0.0 189
75.0%
1.0 1
 
0.4%
2.0 1
 
0.4%
3.3 2
 
0.8%
4.0 1
 
0.4%
4.5 1
 
0.4%
5.0 1
 
0.4%
6.0 2
 
0.8%
6.6 1
 
0.4%
9.0 2
 
0.8%
ValueCountFrequency (%)
135.0 1
0.4%
118.29 1
0.4%
98.04 1
0.4%
88.0 1
0.4%
70.62 1
0.4%
70.0 1
0.4%
66.0 1
0.4%
52.8 1
0.4%
39.88 1
0.4%
39.0 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing252
Missing (%)100.0%
Memory size2.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing252
Missing (%)100.0%
Memory size2.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing252
Missing (%)100.0%
Memory size2.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030900003090000-109-1988-0028219880204<NA>3폐업2폐업19980915<NA><NA><NA>02 905037487.6132822서울특별시 도봉구 도봉동 633-8<NA><NA>영우식품1999-03-12 00:00:00I2018-08-31 23:59:59.0식품소분업204082.239583463501.095157식품소분업11기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
130900003090000-109-1996-0018319960306<NA>3폐업2폐업20060209<NA><NA><NA>0214.7132851서울특별시 도봉구 방학동 695-8<NA><NA>삼원마트2001-01-10 00:00:00I2018-08-31 23:59:59.0식품소분업203104.375372462460.66415식품소분업00주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
230900003090000-109-1997-0018419970317<NA>3폐업2폐업20140623<NA><NA><NA>02 955359521.77132833서울특별시 도봉구 방학동 397-15서울특별시 도봉구 시루봉로15라길 33 (방학동)1314정림유통1999-03-12 00:00:00I2018-08-31 23:59:59.0식품소분업202849.341485463001.574574식품소분업11주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330900003090000-109-1997-0018519970331<NA>3폐업2폐업20000626<NA><NA><NA>02 954908174.74132820서울특별시 도봉구 도봉동 617-25<NA><NA>진원식품2000-06-26 00:00:00I2018-08-31 23:59:59.0식품소분업203744.673212463223.219482식품소분업21주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430900003090000-109-1997-0018619970623<NA>3폐업2폐업20040701<NA><NA><NA>02 992484811.22132896서울특별시 도봉구 쌍문동 707-1<NA><NA>노송식품2000-06-17 00:00:00I2018-08-31 23:59:59.0식품소분업203559.138332462128.049315식품소분업00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530900003090000-109-1998-0018219980416<NA>3폐업2폐업19990907<NA><NA><NA>02349960000.0132898서울특별시 도봉구 창동 1-10<NA><NA>농협창동농산물물류2002-01-18 00:00:00I2018-08-31 23:59:59.0식품소분업204413.616575461378.588677식품소분업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630900003090000-109-1998-0018719980416<NA>3폐업2폐업19990907<NA><NA><NA>0234996000442.0132898서울특별시 도봉구 창동 1-10<NA><NA>농협창동농산물물류1999-09-07 00:00:00I2018-08-31 23:59:59.0식품소분업204413.616575461378.588677식품소분업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730900003090000-109-1998-0018819980424<NA>3폐업2폐업19991015<NA><NA><NA>02 956252622.39132856서울특별시 도봉구 방학동 736-0 신동아타워 13호호<NA><NA>델리스홈베이킹1999-10-15 00:00:00I2018-08-31 23:59:59.0식품소분업202474.809555462204.722701식품소분업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830900003090000-109-1998-0018919981021<NA>3폐업2폐업19990929<NA><NA><NA>02 998973531.08132959서울특별시 도봉구 창동 578-140<NA><NA>승원상회1999-09-29 00:00:00I2018-08-31 23:59:59.0식품소분업203193.561698459539.955754식품소분업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930900003090000-109-1998-0019019980224<NA>3폐업2폐업19981029<NA><NA><NA>02 998043133.06132924서울특별시 도봉구 창동 659-4 우성빌딩 3층동<NA><NA>조양월드2002-01-18 00:00:00I2018-08-31 23:59:59.0식품소분업203036.992887460670.50882식품소분업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
24230900003090000-109-2022-000052022-10-06<NA>3폐업2폐업2023-11-24<NA><NA><NA><NA>11.0132-801서울특별시 도봉구 도봉동 89-148 102호서울특별시 도봉구 도봉로170길 8, 102호 (도봉동)1321반찬is남도반찬2023-11-24 17:07:57U2022-10-31 22:06:00.0식품소분업203985.566277464212.297932<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24330900003090000-109-2022-000062022-12-08<NA>3폐업2폐업2023-12-28<NA><NA><NA><NA>60.0132-889서울특별시 도봉구 쌍문동 494-1서울특별시 도봉구 해등로36길 7, 104동 B02호 (쌍문동)1365강과 산들2023-12-28 09:49:41U2022-11-01 21:00:00.0식품소분업201249.685997461718.49689<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24430900003090000-109-2023-0000120230109<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.21132920서울특별시 도봉구 창동 621-52 1층서울특별시 도봉구 도봉로110라길 5, 1층 (창동)1458휴인(HUIN)2023-01-09 10:55:26I2022-11-30 23:01:00.0식품소분업203094.747268460389.538702<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24530900003090000-109-2023-000022023-05-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.0132-913서울특별시 도봉구 창동 443-6서울특별시 도봉구 덕릉로 272, 3층 301호 (창동)1487(주) 끼친2023-05-17 14:40:21I2022-12-04 23:09:00.0식품소분업203553.135407459890.855841<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24630900003090000-109-2023-000032023-07-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>100.74132-815서울특별시 도봉구 도봉동 570-24서울특별시 도봉구 도봉산3길 41, 2층 (도봉동)1303라익푸드2023-07-07 16:55:27I2022-12-07 00:09:00.0식품소분업203802.844835464788.847055<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24730900003090000-109-2023-000042023-09-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3132-916서울특별시 도봉구 창동 471-9 신창빌라트서울특별시 도봉구 우이천로8길 57, 1층 (창동, 신창빌라트)1479케이엘씨2023-09-01 14:48:57I2022-12-09 00:03:00.0식품소분업203582.478678459286.989227<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24830900003090000-109-2023-000052023-12-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.0132-884서울특별시 도봉구 쌍문동 372-7서울특별시 도봉구 우이천로 349, 1층 (쌍문동)1370대박만두 쌍문2023-12-27 14:17:43I2022-11-01 22:09:00.0식품소분업202147.521446460565.733976<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24930900003090000-109-2024-000012024-01-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0132-863서울특별시 도봉구 쌍문동 85-32서울특별시 도봉구 노해로 235-1, 1층 (쌍문동)1440사자한2024-01-19 16:09:57I2023-11-30 22:01:00.0식품소분업202965.661242461002.249466<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25030900003090000-109-2024-000022024-02-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.0132-728서울특별시 도봉구 창동 338 신원리베르텔 201호서울특별시 도봉구 노해로 341, 신원리베르텔 201호 (창동)1405티하우스 다茶드림2024-02-06 10:46:54I2023-12-02 00:08:00.0식품소분업203984.137173461008.91401<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25130900003090000-109-2024-000032024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>78.0132-819서울특별시 도봉구 도봉동 596-7 도봉미성빌 101호서울특별시 도봉구 도봉로165길 18, 도봉미성빌 101호 (도봉동)1307꾸꾸까까2024-04-03 14:51:16I2023-12-04 00:05:00.0식품소분업203803.544943463870.559914<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>