Overview

Dataset statistics

Number of variables44
Number of observations167
Missing cells1445
Missing cells (%)19.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory61.4 KiB
Average record size in memory376.8 B

Variable types

Categorical22
Text6
DateTime4
Unsupported7
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
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-18185/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (63.7%)Imbalance
여성종사자수 is highly imbalanced (64.8%)Imbalance
영업장주변구분명 is highly imbalanced (73.1%)Imbalance
등급구분명 is highly imbalanced (65.3%)Imbalance
총인원 is highly imbalanced (56.4%)Imbalance
보증액 is highly imbalanced (52.5%)Imbalance
월세액 is highly imbalanced (52.5%)Imbalance
시설총규모 is highly imbalanced (55.6%)Imbalance
인허가취소일자 has 167 (100.0%) missing valuesMissing
폐업일자 has 35 (21.0%) missing valuesMissing
휴업시작일자 has 167 (100.0%) missing valuesMissing
휴업종료일자 has 167 (100.0%) missing valuesMissing
재개업일자 has 167 (100.0%) missing valuesMissing
전화번호 has 60 (35.9%) missing valuesMissing
소재지면적 has 33 (19.8%) missing valuesMissing
도로명주소 has 53 (31.7%) missing valuesMissing
도로명우편번호 has 55 (32.9%) missing valuesMissing
좌표정보(X) has 6 (3.6%) missing valuesMissing
좌표정보(Y) has 6 (3.6%) missing valuesMissing
다중이용업소여부 has 28 (16.8%) missing valuesMissing
전통업소지정번호 has 167 (100.0%) missing valuesMissing
전통업소주된음식 has 167 (100.0%) missing valuesMissing
홈페이지 has 167 (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 3 (1.8%) zerosZeros

Reproduction

Analysis started2024-05-11 06:55:14.994839
Analysis finished2024-05-11 06:55:15.993471
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3080000
167 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 167
100.0%

Length

2024-05-11T15:55:16.160539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:16.372035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 167
100.0%

관리번호
Text

UNIQUE 

Distinct167
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:55:16.637244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3674
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

Unique167 ?
Unique (%)100.0%

Sample

1st row3080000-109-1993-00002
2nd row3080000-109-1994-00003
3rd row3080000-109-1994-00004
4th row3080000-109-1995-00005
5th row3080000-109-1996-00006
ValueCountFrequency (%)
3080000-109-1993-00002 1
 
0.6%
3080000-109-2017-00005 1
 
0.6%
3080000-109-2014-00001 1
 
0.6%
3080000-109-2014-00002 1
 
0.6%
3080000-109-2014-00003 1
 
0.6%
3080000-109-2015-00001 1
 
0.6%
3080000-109-2015-00002 1
 
0.6%
3080000-109-2015-00003 1
 
0.6%
3080000-109-2015-00004 1
 
0.6%
3080000-109-2015-00005 1
 
0.6%
Other values (157) 157
94.0%
2024-05-11T15:55:17.196861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1887
51.4%
- 501
 
13.6%
1 290
 
7.9%
2 225
 
6.1%
9 221
 
6.0%
3 213
 
5.8%
8 189
 
5.1%
5 44
 
1.2%
6 37
 
1.0%
4 35
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3173
86.4%
Dash Punctuation 501
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1887
59.5%
1 290
 
9.1%
2 225
 
7.1%
9 221
 
7.0%
3 213
 
6.7%
8 189
 
6.0%
5 44
 
1.4%
6 37
 
1.2%
4 35
 
1.1%
7 32
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 501
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3674
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1887
51.4%
- 501
 
13.6%
1 290
 
7.9%
2 225
 
6.1%
9 221
 
6.0%
3 213
 
5.8%
8 189
 
5.1%
5 44
 
1.2%
6 37
 
1.0%
4 35
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3674
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1887
51.4%
- 501
 
13.6%
1 290
 
7.9%
2 225
 
6.1%
9 221
 
6.0%
3 213
 
5.8%
8 189
 
5.1%
5 44
 
1.2%
6 37
 
1.0%
4 35
 
1.0%

인허가일자
Date

Distinct164
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum1993-05-25 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T15:55:17.441683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:55:17.683333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3
132 
1
35 

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 (%)
3 132
79.0%
1 35
 
21.0%

Length

2024-05-11T15:55:17.944400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:18.158519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 132
79.0%
1 35
 
21.0%

영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
132 
영업/정상
35 

Length

Max length5
Median length2
Mean length2.6287425
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 132
79.0%
영업/정상 35
 
21.0%

Length

2024-05-11T15:55:18.334689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:18.570602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 132
79.0%
영업/정상 35
 
21.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2
132 
1
35 

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 (%)
2 132
79.0%
1 35
 
21.0%

Length

2024-05-11T15:55:18.745729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:18.911651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 132
79.0%
1 35
 
21.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
132 
영업
35 

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 132
79.0%
영업 35
 
21.0%

Length

2024-05-11T15:55:19.115196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:19.305195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 132
79.0%
영업 35
 
21.0%

폐업일자
Date

MISSING 

Distinct118
Distinct (%)89.4%
Missing35
Missing (%)21.0%
Memory size1.4 KiB
Minimum1996-04-18 00:00:00
Maximum2023-12-28 00:00:00
2024-05-11T15:55:19.489691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:55:19.717729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

전화번호
Text

MISSING 

Distinct105
Distinct (%)98.1%
Missing60
Missing (%)35.9%
Memory size1.4 KiB
2024-05-11T15:55:20.090702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.785047
Min length7

Characters and Unicode

Total characters1154
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

Unique103 ?
Unique (%)96.3%

Sample

1st row02 9985151
2nd row02 9906100
3rd row02 9805783
4th row02 9865274
5th row02 9908206
ValueCountFrequency (%)
02 89
38.0%
070 4
 
1.7%
903 3
 
1.3%
982 2
 
0.9%
9885103 2
 
0.9%
989 2
 
0.9%
944 2
 
0.9%
986 2
 
0.9%
984 2
 
0.9%
9959390 2
 
0.9%
Other values (120) 124
53.0%
2024-05-11T15:55:20.795181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 201
17.4%
173
15.0%
9 165
14.3%
2 151
13.1%
8 91
7.9%
3 75
 
6.5%
1 65
 
5.6%
6 61
 
5.3%
5 60
 
5.2%
7 57
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 981
85.0%
Space Separator 173
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 201
20.5%
9 165
16.8%
2 151
15.4%
8 91
9.3%
3 75
 
7.6%
1 65
 
6.6%
6 61
 
6.2%
5 60
 
6.1%
7 57
 
5.8%
4 55
 
5.6%
Space Separator
ValueCountFrequency (%)
173
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1154
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 201
17.4%
173
15.0%
9 165
14.3%
2 151
13.1%
8 91
7.9%
3 75
 
6.5%
1 65
 
5.6%
6 61
 
5.3%
5 60
 
5.2%
7 57
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1154
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 201
17.4%
173
15.0%
9 165
14.3%
2 151
13.1%
8 91
7.9%
3 75
 
6.5%
1 65
 
5.6%
6 61
 
5.3%
5 60
 
5.2%
7 57
 
4.9%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct90
Distinct (%)67.2%
Missing33
Missing (%)19.8%
Infinite0
Infinite (%)0.0%
Mean31.002612
Minimum0
Maximum570.95
Zeros3
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:55:21.130105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.8425
Q18.09
median19.9
Q333
95-th percentile82.512
Maximum570.95
Range570.95
Interquartile range (IQR)24.91

Descriptive statistics

Standard deviation52.956935
Coefficient of variation (CV)1.7081443
Kurtosis82.125538
Mean31.002612
Median Absolute Deviation (MAD)13.1
Skewness8.1885966
Sum4154.35
Variance2804.437
MonotonicityNot monotonic
2024-05-11T15:55:21.373363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 11
 
6.6%
15.0 5
 
3.0%
3.3 5
 
3.0%
24.0 5
 
3.0%
6.6 5
 
3.0%
66.0 4
 
2.4%
0.0 3
 
1.8%
16.5 3
 
1.8%
6.0 3
 
1.8%
35.0 3
 
1.8%
Other values (80) 87
52.1%
(Missing) 33
 
19.8%
ValueCountFrequency (%)
0.0 3
1.8%
1.7 1
 
0.6%
2.3 2
 
1.2%
2.55 1
 
0.6%
3.0 1
 
0.6%
3.3 5
3.0%
4.2 1
 
0.6%
4.5 1
 
0.6%
4.56 1
 
0.6%
5.0 1
 
0.6%
ValueCountFrequency (%)
570.95 1
0.6%
107.2 1
0.6%
102.6 1
0.6%
100.0 2
1.2%
99.0 1
0.6%
93.9 1
0.6%
76.38 1
0.6%
73.9 1
0.6%
72.1 1
0.6%
70.64 1
0.6%

소재지우편번호
Text

Distinct59
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:55:21.787140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1017964
Min length6

Characters and Unicode

Total characters1019
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

Unique19 ?
Unique (%)11.4%

Sample

1st row142884
2nd row142884
3rd row142800
4th row142060
5th row142877
ValueCountFrequency (%)
142804 12
 
7.2%
142877 9
 
5.4%
142872 8
 
4.8%
142812 6
 
3.6%
142810 6
 
3.6%
142070 6
 
3.6%
142874 6
 
3.6%
142876 5
 
3.0%
142864 5
 
3.0%
142821 5
 
3.0%
Other values (49) 99
59.3%
2024-05-11T15:55:22.433396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 206
20.2%
2 206
20.2%
4 201
19.7%
8 168
16.5%
0 85
8.3%
7 68
 
6.7%
6 36
 
3.5%
- 17
 
1.7%
3 14
 
1.4%
9 10
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1002
98.3%
Dash Punctuation 17
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 206
20.6%
2 206
20.6%
4 201
20.1%
8 168
16.8%
0 85
8.5%
7 68
 
6.8%
6 36
 
3.6%
3 14
 
1.4%
9 10
 
1.0%
5 8
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1019
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 206
20.2%
2 206
20.2%
4 201
19.7%
8 168
16.5%
0 85
8.3%
7 68
 
6.7%
6 36
 
3.5%
- 17
 
1.7%
3 14
 
1.4%
9 10
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 206
20.2%
2 206
20.2%
4 201
19.7%
8 168
16.5%
0 85
8.3%
7 68
 
6.7%
6 36
 
3.5%
- 17
 
1.7%
3 14
 
1.4%
9 10
 
1.0%

지번주소
Text

Distinct158
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:55:22.936554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length39
Mean length24.508982
Min length17

Characters and Unicode

Total characters4093
Distinct characters125
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

Unique151 ?
Unique (%)90.4%

Sample

1st row서울특별시 강북구 수유동 394-46 (우이동길 46)
2nd row서울특별시 강북구 수유동 394-46
3rd row서울특별시 강북구 미아동 80-61
4th row서울특별시 강북구 번동 산 148-387
5th row서울특별시 강북구 수유동 205-0
ValueCountFrequency (%)
서울특별시 167
20.5%
강북구 166
20.4%
미아동 75
 
9.2%
수유동 66
 
8.1%
번동 22
 
2.7%
1층 13
 
1.6%
70-6 10
 
1.2%
지하1층 9
 
1.1%
2층 6
 
0.7%
롯데백화점 5
 
0.6%
Other values (230) 274
33.7%
2024-05-11T15:55:23.823201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
780
19.1%
동 175
 
4.3%
시 172
 
4.2%
서 167
 
4.1%
특 167
 
4.1%
별 167
 
4.1%
강 167
 
4.1%
북 167
 
4.1%
구 167
 
4.1%
울 167
 
4.1%
Other values (115) 1797
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2243
54.8%
Decimal Number 865
 
21.1%
Space Separator 780
 
19.1%
Dash Punctuation 153
 
3.7%
Open Punctuation 19
 
0.5%
Close Punctuation 19
 
0.5%
Other Punctuation 6
 
0.1%
Uppercase Letter 5
 
0.1%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 175
 
7.8%
시 172
 
7.7%
서 167
 
7.4%
특 167
 
7.4%
별 167
 
7.4%
강 167
 
7.4%
북 167
 
7.4%
구 167
 
7.4%
울 167
 
7.4%
아 94
 
4.2%
Other values (93) 633
28.2%
Decimal Number
ValueCountFrequency (%)
1 164
19.0%
2 123
14.2%
3 97
11.2%
0 93
10.8%
4 85
9.8%
7 75
8.7%
5 71
8.2%
6 71
8.2%
8 49
 
5.7%
9 37
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
/ 1
 
16.7%
. 1
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
40.0%
B 2
40.0%
D 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
66.7%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
780
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 153
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2243
54.8%
Common 1842
45.0%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 175
 
7.8%
시 172
 
7.7%
서 167
 
7.4%
특 167
 
7.4%
별 167
 
7.4%
강 167
 
7.4%
북 167
 
7.4%
구 167
 
7.4%
울 167
 
7.4%
아 94
 
4.2%
Other values (93) 633
28.2%
Common
ValueCountFrequency (%)
780
42.3%
1 164
 
8.9%
- 153
 
8.3%
2 123
 
6.7%
3 97
 
5.3%
0 93
 
5.0%
4 85
 
4.6%
7 75
 
4.1%
5 71
 
3.9%
6 71
 
3.9%
Other values (7) 130
 
7.1%
Latin
ValueCountFrequency (%)
b 2
25.0%
A 2
25.0%
B 2
25.0%
D 1
12.5%
c 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2243
54.8%
ASCII 1850
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
780
42.2%
1 164
 
8.9%
- 153
 
8.3%
2 123
 
6.6%
3 97
 
5.2%
0 93
 
5.0%
4 85
 
4.6%
7 75
 
4.1%
5 71
 
3.8%
6 71
 
3.8%
Other values (12) 138
 
7.5%
Hangul
ValueCountFrequency (%)
동 175
 
7.8%
시 172
 
7.7%
서 167
 
7.4%
특 167
 
7.4%
별 167
 
7.4%
강 167
 
7.4%
북 167
 
7.4%
구 167
 
7.4%
울 167
 
7.4%
아 94
 
4.2%
Other values (93) 633
28.2%

도로명주소
Text

MISSING 

Distinct111
Distinct (%)97.4%
Missing53
Missing (%)31.7%
Memory size1.4 KiB
2024-05-11T15:55:24.429219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length43
Mean length30.473684
Min length22

Characters and Unicode

Total characters3474
Distinct characters127
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

Unique108 ?
Unique (%)94.7%

Sample

1st row서울특별시 강북구 삼양로 450 (수유동)
2nd row서울특별시 강북구 덕릉로 176 (번동)
3rd row서울특별시 강북구 삼양로80나길 72 (수유동)
4th row서울특별시 강북구 한천로 1187 (수유동)
5th row서울특별시 강북구 오현로32길 18 (번동)
ValueCountFrequency (%)
서울특별시 114
 
16.8%
강북구 113
 
16.6%
미아동 40
 
5.9%
수유동 38
 
5.6%
1층 23
 
3.4%
도봉로 14
 
2.1%
번동 11
 
1.6%
62 7
 
1.0%
2층 7
 
1.0%
지하1층 7
 
1.0%
Other values (218) 306
45.0%
2024-05-11T15:55:25.304840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
566
 
16.3%
1 155
 
4.5%
) 120
 
3.5%
( 120
 
3.5%
동 119
 
3.4%
시 118
 
3.4%
구 114
 
3.3%
울 114
 
3.3%
서 114
 
3.3%
강 114
 
3.3%
Other values (117) 1820
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1993
57.4%
Space Separator 566
 
16.3%
Decimal Number 565
 
16.3%
Close Punctuation 120
 
3.5%
Open Punctuation 120
 
3.5%
Other Punctuation 91
 
2.6%
Dash Punctuation 13
 
0.4%
Uppercase Letter 3
 
0.1%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 119
 
6.0%
시 118
 
5.9%
구 114
 
5.7%
울 114
 
5.7%
서 114
 
5.7%
강 114
 
5.7%
별 114
 
5.7%
특 114
 
5.7%
로 114
 
5.7%
북 113
 
5.7%
Other values (96) 845
42.4%
Decimal Number
ValueCountFrequency (%)
1 155
27.4%
2 90
15.9%
3 60
 
10.6%
4 49
 
8.7%
5 40
 
7.1%
7 39
 
6.9%
0 39
 
6.9%
6 37
 
6.5%
9 28
 
5.0%
8 28
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 89
97.8%
. 1
 
1.1%
/ 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
D 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
b 2
66.7%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
566
100.0%
Close Punctuation
ValueCountFrequency (%)
) 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1993
57.4%
Common 1475
42.5%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 119
 
6.0%
시 118
 
5.9%
구 114
 
5.7%
울 114
 
5.7%
서 114
 
5.7%
강 114
 
5.7%
별 114
 
5.7%
특 114
 
5.7%
로 114
 
5.7%
북 113
 
5.7%
Other values (96) 845
42.4%
Common
ValueCountFrequency (%)
566
38.4%
1 155
 
10.5%
) 120
 
8.1%
( 120
 
8.1%
2 90
 
6.1%
, 89
 
6.0%
3 60
 
4.1%
4 49
 
3.3%
5 40
 
2.7%
7 39
 
2.6%
Other values (7) 147
 
10.0%
Latin
ValueCountFrequency (%)
B 2
33.3%
b 2
33.3%
D 1
16.7%
c 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1993
57.4%
ASCII 1481
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
566
38.2%
1 155
 
10.5%
) 120
 
8.1%
( 120
 
8.1%
2 90
 
6.1%
, 89
 
6.0%
3 60
 
4.1%
4 49
 
3.3%
5 40
 
2.7%
7 39
 
2.6%
Other values (11) 153
 
10.3%
Hangul
ValueCountFrequency (%)
동 119
 
6.0%
시 118
 
5.9%
구 114
 
5.7%
울 114
 
5.7%
서 114
 
5.7%
강 114
 
5.7%
별 114
 
5.7%
특 114
 
5.7%
로 114
 
5.7%
북 113
 
5.7%
Other values (96) 845
42.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct79
Distinct (%)70.5%
Missing55
Missing (%)32.9%
Infinite0
Infinite (%)0.0%
Mean1163.7411
Minimum1006
Maximum5376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:55:25.592751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1006
5-th percentile1024.3
Q11065.25
median1125
Q31193.25
95-th percentile1227.9
Maximum5376
Range4370
Interquartile range (IQR)128

Descriptive statistics

Standard deviation407.56393
Coefficient of variation (CV)0.35021874
Kurtosis105.42083
Mean1163.7411
Median Absolute Deviation (MAD)64.5
Skewness10.117294
Sum130339
Variance166108.36
MonotonicityNot monotonic
2024-05-11T15:55:25.856027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1170 5
 
3.0%
1215 5
 
3.0%
1076 3
 
1.8%
1006 3
 
1.8%
1055 3
 
1.8%
1041 3
 
1.8%
1117 3
 
1.8%
1039 2
 
1.2%
1118 2
 
1.2%
1081 2
 
1.2%
Other values (69) 81
48.5%
(Missing) 55
32.9%
ValueCountFrequency (%)
1006 3
1.8%
1014 2
1.2%
1021 1
 
0.6%
1027 1
 
0.6%
1030 2
1.2%
1035 1
 
0.6%
1037 1
 
0.6%
1038 1
 
0.6%
1039 2
1.2%
1041 3
1.8%
ValueCountFrequency (%)
5376 1
 
0.6%
1237 1
 
0.6%
1234 1
 
0.6%
1233 2
 
1.2%
1229 1
 
0.6%
1227 1
 
0.6%
1224 2
 
1.2%
1223 2
 
1.2%
1218 1
 
0.6%
1215 5
3.0%

사업장명
Text

Distinct163
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-11T15:55:26.332033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length6.1317365
Min length2

Characters and Unicode

Total characters1024
Distinct characters265
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

Unique159 ?
Unique (%)95.2%

Sample

1st row(주)제원인터내쇼날
2nd row(주)유코머천트
3rd row국제유통
4th row송학식품
5th row영신식품
ValueCountFrequency (%)
주식회사 3
 
1.6%
케이앤푸드 2
 
1.1%
번동점 2
 
1.1%
수유점 2
 
1.1%
기준인터내셔날 2
 
1.1%
선우에프아이 2
 
1.1%
뻥튀기공작소 2
 
1.1%
내츄럴팜 1
 
0.5%
태정 1
 
0.5%
써니 1
 
0.5%
Other values (169) 169
90.4%
2024-05-11T15:55:27.078070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 33
 
3.2%
) 29
 
2.8%
( 29
 
2.8%
트 27
 
2.6%
마 25
 
2.4%
식 24
 
2.3%
이 24
 
2.3%
20
 
2.0%
유 19
 
1.9%
아 16
 
1.6%
Other values (255) 778
76.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 910
88.9%
Close Punctuation 29
 
2.8%
Open Punctuation 29
 
2.8%
Space Separator 20
 
2.0%
Lowercase Letter 17
 
1.7%
Uppercase Letter 14
 
1.4%
Decimal Number 4
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 33
 
3.6%
트 27
 
3.0%
마 25
 
2.7%
식 24
 
2.6%
이 24
 
2.6%
유 19
 
2.1%
아 16
 
1.8%
리 16
 
1.8%
인 16
 
1.8%
품 15
 
1.6%
Other values (231) 695
76.4%
Lowercase Letter
ValueCountFrequency (%)
o 4
23.5%
n 3
17.6%
a 2
11.8%
r 2
11.8%
m 1
 
5.9%
e 1
 
5.9%
i 1
 
5.9%
t 1
 
5.9%
p 1
 
5.9%
c 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
S 4
28.6%
G 2
14.3%
E 2
14.3%
T 2
14.3%
D 1
 
7.1%
N 1
 
7.1%
B 1
 
7.1%
K 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
0 3
75.0%
2 1
 
25.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 910
88.9%
Common 83
 
8.1%
Latin 31
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 33
 
3.6%
트 27
 
3.0%
마 25
 
2.7%
식 24
 
2.6%
이 24
 
2.6%
유 19
 
2.1%
아 16
 
1.8%
리 16
 
1.8%
인 16
 
1.8%
품 15
 
1.6%
Other values (231) 695
76.4%
Latin
ValueCountFrequency (%)
o 4
12.9%
S 4
12.9%
n 3
 
9.7%
a 2
 
6.5%
r 2
 
6.5%
G 2
 
6.5%
E 2
 
6.5%
T 2
 
6.5%
m 1
 
3.2%
e 1
 
3.2%
Other values (8) 8
25.8%
Common
ValueCountFrequency (%)
) 29
34.9%
( 29
34.9%
20
24.1%
0 3
 
3.6%
- 1
 
1.2%
2 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 910
88.9%
ASCII 114
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 33
 
3.6%
트 27
 
3.0%
마 25
 
2.7%
식 24
 
2.6%
이 24
 
2.6%
유 19
 
2.1%
아 16
 
1.8%
리 16
 
1.8%
인 16
 
1.8%
품 15
 
1.6%
Other values (231) 695
76.4%
ASCII
ValueCountFrequency (%)
) 29
25.4%
( 29
25.4%
20
17.5%
o 4
 
3.5%
S 4
 
3.5%
n 3
 
2.6%
0 3
 
2.6%
a 2
 
1.8%
r 2
 
1.8%
G 2
 
1.8%
Other values (14) 16
14.0%

최종수정일자
Date

Distinct151
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2001-11-16 00:00:00
Maximum2024-05-09 11:31:36
2024-05-11T15:55:27.314826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:55:27.552631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
I
102 
U
65 

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 102
61.1%
U 65
38.9%

Length

2024-05-11T15:55:27.805646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:28.035728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 102
61.1%
u 65
38.9%

데이터갱신일자
Date

Distinct70
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T15:55:28.274742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:55:28.921773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
식품소분업
167 

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 167
100.0%

Length

2024-05-11T15:55:29.164698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:29.326985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 167
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct131
Distinct (%)81.4%
Missing6
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean202068.65
Minimum200664.95
Maximum212016.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:55:29.513409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200664.95
5-th percentile201051.84
Q1201567.68
median201918.92
Q3202518.54
95-th percentile203224.54
Maximum212016.92
Range11351.963
Interquartile range (IQR)950.86072

Descriptive statistics

Standard deviation1026.545
Coefficient of variation (CV)0.0050801794
Kurtosis54.646498
Mean202068.65
Median Absolute Deviation (MAD)480.21631
Skewness5.8149288
Sum32533052
Variance1053794.6
MonotonicityNot monotonic
2024-05-11T15:55:29.777021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202625.646264572 10
 
6.0%
201606.445832012 4
 
2.4%
201589.777957863 4
 
2.4%
201956.180985499 3
 
1.8%
201354.553491054 3
 
1.8%
203932.991517795 2
 
1.2%
201805.089270683 2
 
1.2%
202228.431717714 2
 
1.2%
203015.499785445 2
 
1.2%
203224.539337907 2
 
1.2%
Other values (121) 127
76.0%
(Missing) 6
 
3.6%
ValueCountFrequency (%)
200664.95320546 1
0.6%
200857.510964399 1
0.6%
200913.430678583 1
0.6%
200916.861545971 1
0.6%
201001.127377487 1
0.6%
201008.572386836 1
0.6%
201028.099477749 1
0.6%
201049.029062927 1
0.6%
201051.839134539 1
0.6%
201056.297923916 1
0.6%
ValueCountFrequency (%)
212016.915921852 1
0.6%
203932.991517795 2
1.2%
203480.440498484 1
0.6%
203407.529404484 1
0.6%
203405.728060301 1
0.6%
203299.090419064 1
0.6%
203284.596562608 1
0.6%
203224.539337907 2
1.2%
203155.475763688 1
0.6%
203093.488566 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct131
Distinct (%)81.4%
Missing6
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean458606.34
Minimum447600.54
Maximum461507.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-05-11T15:55:30.039408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447600.54
5-th percentile456875.97
Q1457545.1
median458608.27
Q3459760.02
95-th percentile460422.59
Maximum461507.4
Range13906.851
Interquartile range (IQR)2214.9211

Descriptive statistics

Standard deviation1489.6974
Coefficient of variation (CV)0.003248314
Kurtosis17.165612
Mean458606.34
Median Absolute Deviation (MAD)1073.2964
Skewness-2.4004044
Sum73835621
Variance2219198.3
MonotonicityNot monotonic
2024-05-11T15:55:30.329434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456875.973976242 10
 
6.0%
460001.632075829 4
 
2.4%
457545.100871485 4
 
2.4%
458714.365820521 3
 
1.8%
459317.583083716 3
 
1.8%
458247.431674005 2
 
1.2%
459288.875727108 2
 
1.2%
458158.105668456 2
 
1.2%
457013.857800111 2
 
1.2%
457978.637753845 2
 
1.2%
Other values (121) 127
76.0%
(Missing) 6
 
3.6%
ValueCountFrequency (%)
447600.544562582 1
 
0.6%
456733.542887647 1
 
0.6%
456758.813670659 1
 
0.6%
456808.972105684 1
 
0.6%
456819.726998441 1
 
0.6%
456875.973976242 10
6.0%
456884.270296575 1
 
0.6%
456909.363722543 1
 
0.6%
457007.703275778 1
 
0.6%
457013.857800111 2
 
1.2%
ValueCountFrequency (%)
461507.395349107 1
0.6%
461383.338586109 1
0.6%
461366.546648147 1
0.6%
460651.772909553 1
0.6%
460618.343099783 1
0.6%
460614.717300913 1
0.6%
460529.986472321 1
0.6%
460526.093627763 1
0.6%
460422.588470874 1
0.6%
460413.63254848 1
0.6%

위생업태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
식품소분업
139 
<NA>
28 

Length

Max length5
Median length5
Mean length4.8323353
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 139
83.2%
<NA> 28
 
16.8%

Length

2024-05-11T15:55:30.570655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:30.761158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 139
83.2%
na 28
 
16.8%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
139 
0
26 
4
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.497006
Min length1

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st row4
2nd row2
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 139
83.2%
0 26
 
15.6%
4 1
 
0.6%
2 1
 
0.6%

Length

2024-05-11T15:55:30.980025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:31.195684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 139
83.2%
0 26
 
15.6%
4 1
 
0.6%
2 1
 
0.6%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
137 
0
26 
1
 
2
7
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.4610778
Min length1

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st row7
2nd row1
3rd row0
4th row1
5th row2

Common Values

ValueCountFrequency (%)
<NA> 137
82.0%
0 26
 
15.6%
1 2
 
1.2%
7 1
 
0.6%
2 1
 
0.6%

Length

2024-05-11T15:55:31.447250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:31.672812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
82.0%
0 26
 
15.6%
1 2
 
1.2%
7 1
 
0.6%
2 1
 
0.6%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
151 
주택가주변
 
13
기타
 
2
아파트지역
 
1

Length

Max length5
Median length4
Mean length4.0598802
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
90.4%
주택가주변 13
 
7.8%
기타 2
 
1.2%
아파트지역 1
 
0.6%

Length

2024-05-11T15:55:31.922011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:32.164266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
90.4%
주택가주변 13
 
7.8%
기타 2
 
1.2%
아파트지역 1
 
0.6%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
151 
기타
 
9
자율
 
7

Length

Max length4
Median length4
Mean length3.8083832
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
90.4%
기타 9
 
5.4%
자율 7
 
4.2%

Length

2024-05-11T15:55:32.419446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:32.650594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
90.4%
기타 9
 
5.4%
자율 7
 
4.2%

급수시설구분명
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
124 
상수도전용
42 
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.257485
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 124
74.3%
상수도전용 42
 
25.1%
지하수전용 1
 
0.6%

Length

2024-05-11T15:55:32.955888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:33.150727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 124
74.3%
상수도전용 42
 
25.1%
지하수전용 1
 
0.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
152 
0
 
15

Length

Max length4
Median length4
Mean length3.7305389
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> 152
91.0%
0 15
 
9.0%

Length

2024-05-11T15:55:33.371528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:33.529033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
91.0%
0 15
 
9.0%

본사종업원수
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
107 
0
59 
1
 
1

Length

Max length4
Median length4
Mean length2.9221557
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 107
64.1%
0 59
35.3%
1 1
 
0.6%

Length

2024-05-11T15:55:33.710744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:33.900662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 107
64.1%
0 59
35.3%
1 1
 
0.6%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
106 
0
60 
1
 
1

Length

Max length4
Median length4
Mean length2.9041916
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 106
63.5%
0 60
35.9%
1 1
 
0.6%

Length

2024-05-11T15:55:34.096586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:34.315817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 106
63.5%
0 60
35.9%
1 1
 
0.6%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
106 
0
59 
1
 
2

Length

Max length4
Median length4
Mean length2.9041916
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 106
63.5%
0 59
35.3%
1 2
 
1.2%

Length

2024-05-11T15:55:34.552922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:34.772939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 106
63.5%
0 59
35.3%
1 2
 
1.2%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
107 
0
60 

Length

Max length4
Median length4
Mean length2.9221557
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 107
64.1%
0 60
35.9%

Length

2024-05-11T15:55:35.110058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:35.316750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 107
64.1%
0 60
35.9%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
98 
자가
37 
임대
32 

Length

Max length4
Median length4
Mean length3.1736527
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> 98
58.7%
자가 37
 
22.2%
임대 32
 
19.2%

Length

2024-05-11T15:55:35.524323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:35.743551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
58.7%
자가 37
 
22.2%
임대 32
 
19.2%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
150 
0
17 

Length

Max length4
Median length4
Mean length3.6946108
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> 150
89.8%
0 17
 
10.2%

Length

2024-05-11T15:55:35.969993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:36.156912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
89.8%
0 17
 
10.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
150 
0
17 

Length

Max length4
Median length4
Mean length3.6946108
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> 150
89.8%
0 17
 
10.2%

Length

2024-05-11T15:55:36.338629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:36.517121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
89.8%
0 17
 
10.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.7%
Missing28
Missing (%)16.8%
Memory size466.0 B
False
139 
(Missing)
28 
ValueCountFrequency (%)
False 139
83.2%
(Missing) 28
 
16.8%
2024-05-11T15:55:36.660721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0.0
138 
<NA>
28 
8.19
 
1

Length

Max length4
Median length3
Mean length3.1736527
Min length3

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row8.19
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 138
82.6%
<NA> 28
 
16.8%
8.19 1
 
0.6%

Length

2024-05-11T15:55:36.829920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:37.019460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 138
82.6%
na 28
 
16.8%
8.19 1
 
0.6%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030800003080000-109-1993-0000219930525<NA>3폐업2폐업20110929<NA><NA><NA>02 998515121.05142884서울특별시 강북구 수유동 394-46 (우이동길 46)<NA><NA>(주)제원인터내쇼날2010-10-19 17:13:05I2018-08-31 23:59:59.0식품소분업201462.866607459570.869762식품소분업47주택가주변기타상수도전용<NA>0000<NA><NA><NA>N8.19<NA><NA><NA>
130800003080000-109-1994-0000319940119<NA>3폐업2폐업19980506<NA><NA><NA>02 990610017.25142884서울특별시 강북구 수유동 394-46<NA><NA>(주)유코머천트2002-08-01 00:00:00I2018-08-31 23:59:59.0식품소분업201462.866607459570.869762식품소분업21주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230800003080000-109-1994-0000419940125<NA>3폐업2폐업20050927<NA><NA><NA>02 980578341.7142800서울특별시 강북구 미아동 80-61<NA><NA>국제유통2002-08-01 00:00:00I2018-08-31 23:59:59.0식품소분업202928.185017456884.270297식품소분업00주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
330800003080000-109-1995-0000519951208<NA>3폐업2폐업19960418<NA><NA><NA>02 986527473.9142060서울특별시 강북구 번동 산 148-387<NA><NA>송학식품2002-01-09 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업<NA>1주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430800003080000-109-1996-0000619960702<NA>3폐업2폐업20020108<NA><NA><NA>02 990820615.95142877서울특별시 강북구 수유동 205-0<NA><NA>영신식품2002-08-01 00:00:00I2018-08-31 23:59:59.0식품소분업201606.445832460001.632076식품소분업<NA>2아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530800003080000-109-1998-0000719980326<NA>3폐업2폐업19990729<NA><NA><NA>02 987770713.6142823서울특별시 강북구 미아동 777-6<NA><NA>재향경우회삼양매장2002-08-01 00:00:00I2018-08-31 23:59:59.0식품소분업201578.382565458114.726446식품소분업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630800003080000-109-1999-0021419990107<NA>3폐업2폐업20040305<NA><NA><NA>02 98691100.0142808서울특별시 강북구 미아동 127-1<NA><NA>다산식품2002-08-01 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업00주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
730800003080000-109-1999-0022719990419<NA>3폐업2폐업20110708<NA><NA><NA>02 98660484.56142810서울특별시 강북구 미아동 215-32<NA><NA>(주)거하산2002-11-13 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업00기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
830800003080000-109-1999-0024019990519<NA>3폐업2폐업20001206<NA><NA><NA>02 989032225.5142809서울특별시 강북구 미아동 137-22<NA><NA>한과마을2002-08-01 00:00:00I2018-08-31 23:59:59.0식품소분업202540.438492457366.860361식품소분업00주택가주변자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930800003080000-109-1999-0026619990806<NA>1영업/정상1영업<NA><NA><NA><NA>02 990879115.65142877서울특별시 강북구 수유동 332-34서울특별시 강북구 삼양로 450 (수유동)1041(주)삼주국민마트2002-08-16 00:00:00I2018-08-31 23:59:59.0식품소분업201391.668033460122.465435식품소분업00주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
15730800003080000-109-2021-0000720211230<NA>1영업/정상1영업<NA><NA><NA><NA>02 904036529.98142883서울특별시 강북구 수유동 524-39 지하1층서울특별시 강북구 인수봉로 243-1, 지하1층 (수유동)1021홈앤쿡주식회사2021-12-30 10:53:19I2022-01-01 00:22:41.0식품소분업200913.430679459786.981427식품소분업00<NA><NA><NA>00000임대00N0.0<NA><NA><NA>
15830800003080000-109-2022-0000120220322<NA>3폐업2폐업20221026<NA><NA><NA>02529533233.0142891서울특별시 강북구 수유동 7-7 유일빌딩서울특별시 강북구 수유로 68-1, 유일빌딩 5층 (수유동)1081선우에프아이2022-10-26 14:35:31U2021-10-30 22:09:00.0식품소분업201805.089271459288.875727<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15930800003080000-109-2022-000022022-04-20<NA>1영업/정상1영업<NA><NA><NA><NA>02983 335813.0142-874서울특별시 강북구 수유동 54-5 수유시장 2층서울특별시 강북구 도봉로67길 18, 수유시장 2층 (수유동)1117엠마트2023-02-15 16:13:54U2022-12-01 23:07:00.0식품소분업201956.180985458714.365821<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16030800003080000-109-2022-0000320221212<NA>1영업/정상1영업<NA><NA><NA><NA><NA>39.6142070서울특별시 강북구 수유동 279-74 아트리체서울특별시 강북구 한천로 1174, 제1층 제103호 (수유동, 아트리체)1044뻥튀기공작소2022-12-12 11:30:42I2021-11-01 23:04:00.0식품소분업201282.367639460651.77291<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16130800003080000-109-2023-000012023-03-08<NA>1영업/정상1영업<NA><NA><NA><NA>02 865 06957.4142-874서울특별시 강북구 수유동 50-75 수유대림쇼핑아파트서울특별시 강북구 도봉로71가길 11, 수유대림쇼핑아파트 323호 (수유동)1114주식회사 이너스케어2023-03-08 10:12:41I2022-12-02 23:00:00.0식품소분업201892.114537458840.846635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16230800003080000-109-2023-000022023-08-24<NA>1영업/정상1영업<NA><NA><NA><NA>02 945 30018.36142-803서울특별시 강북구 미아동 197-11서울특별시 강북구 솔매로 131, 1층 (미아동)1133두눈2023-08-24 18:27:13I2022-12-07 22:06:00.0식품소분업202288.119416458240.045867<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16330800003080000-109-2024-000012024-02-27<NA>1영업/정상1영업<NA><NA><NA><NA>02 980829216.48142-100서울특별시 강북구 미아동 1357-6 미아프라자서울특별시 강북구 삼양로27길 35-21, 미아프라자 1층 104호 (미아동)1196꼬숩숯불김2024-02-27 18:08:45I2023-12-01 22:09:00.0식품소분업201602.577531457290.100695<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16430800003080000-109-2024-000022024-03-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>70.64142-812서울특별시 강북구 미아동 304-9서울특별시 강북구 도봉로45길 10, 2층 (미아동)1170노네임(noname)2024-03-08 15:46:47I2023-12-02 23:00:00.0식품소분업202248.520448458006.275116<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16530800003080000-109-2024-000032024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.0142-886서울특별시 강북구 수유동 472-8서울특별시 강북구 덕릉로 42, 1층 (수유동)1111두원2024-04-02 11:40:11I2023-12-04 00:04:00.0식품소분업201539.246535459078.257462<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16630800003080000-109-2024-000042024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0142-803서울특별시 강북구 미아동 162-3 유성빌딩서울특별시 강북구 도봉로78길 28, 유성빌딩 102호 (미아동)1129포도쉬즈 모2024-05-02 17:12:49I2023-12-05 00:04:00.0식품소분업202141.821568459031.778778<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>