Overview

Dataset statistics

Number of variables44
Number of observations59
Missing cells687
Missing cells (%)26.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.0 KiB
Average record size in memory381.2 B

Variable types

Categorical19
Text6
DateTime4
Unsupported10
Numeric4
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-18062/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (71.0%)Imbalance
여성종사자수 is highly imbalanced (71.0%)Imbalance
총인원 is highly imbalanced (71.0%)Imbalance
보증액 is highly imbalanced (71.0%)Imbalance
월세액 is highly imbalanced (71.0%)Imbalance
인허가취소일자 has 59 (100.0%) missing valuesMissing
폐업일자 has 21 (35.6%) missing valuesMissing
휴업시작일자 has 59 (100.0%) missing valuesMissing
휴업종료일자 has 59 (100.0%) missing valuesMissing
재개업일자 has 59 (100.0%) missing valuesMissing
전화번호 has 24 (40.7%) missing valuesMissing
소재지면적 has 15 (25.4%) missing valuesMissing
소재지우편번호 has 1 (1.7%) missing valuesMissing
지번주소 has 1 (1.7%) missing valuesMissing
도로명주소 has 8 (13.6%) missing valuesMissing
도로명우편번호 has 8 (13.6%) missing valuesMissing
영업장주변구분명 has 59 (100.0%) missing valuesMissing
등급구분명 has 59 (100.0%) missing valuesMissing
급수시설구분명 has 59 (100.0%) missing valuesMissing
다중이용업소여부 has 19 (32.2%) missing valuesMissing
전통업소지정번호 has 59 (100.0%) missing valuesMissing
전통업소주된음식 has 59 (100.0%) missing valuesMissing
홈페이지 has 59 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
급수시설구분명 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 1 (1.7%) zerosZeros

Reproduction

Analysis started2024-05-11 06:50:53.094460
Analysis finished2024-05-11 06:50:54.054651
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size604.0 B
3100000
59 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 59
100.0%

Length

2024-05-11T15:50:54.157998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:54.320932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 59
100.0%

관리번호
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2024-05-11T15:50:54.576098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1298
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

Unique59 ?
Unique (%)100.0%

Sample

1st row3100000-135-2005-00001
2nd row3100000-135-2005-00002
3rd row3100000-135-2005-00003
4th row3100000-135-2005-00004
5th row3100000-135-2006-00001
ValueCountFrequency (%)
3100000-135-2005-00001 1
 
1.7%
3100000-135-2017-00001 1
 
1.7%
3100000-135-2017-00003 1
 
1.7%
3100000-135-2017-00004 1
 
1.7%
3100000-135-2018-00001 1
 
1.7%
3100000-135-2018-00002 1
 
1.7%
3100000-135-2018-00003 1
 
1.7%
3100000-135-2018-00004 1
 
1.7%
3100000-135-2019-00001 1
 
1.7%
3100000-135-2019-00002 1
 
1.7%
Other values (49) 49
83.1%
2024-05-11T15:50:55.062548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 611
47.1%
- 177
 
13.6%
1 172
 
13.3%
3 136
 
10.5%
2 96
 
7.4%
5 69
 
5.3%
4 16
 
1.2%
6 6
 
0.5%
8 6
 
0.5%
9 5
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1121
86.4%
Dash Punctuation 177
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 611
54.5%
1 172
 
15.3%
3 136
 
12.1%
2 96
 
8.6%
5 69
 
6.2%
4 16
 
1.4%
6 6
 
0.5%
8 6
 
0.5%
9 5
 
0.4%
7 4
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 177
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1298
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 611
47.1%
- 177
 
13.6%
1 172
 
13.3%
3 136
 
10.5%
2 96
 
7.4%
5 69
 
5.3%
4 16
 
1.2%
6 6
 
0.5%
8 6
 
0.5%
9 5
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1298
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 611
47.1%
- 177
 
13.6%
1 172
 
13.3%
3 136
 
10.5%
2 96
 
7.4%
5 69
 
5.3%
4 16
 
1.2%
6 6
 
0.5%
8 6
 
0.5%
9 5
 
0.4%

인허가일자
Date

Distinct56
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size604.0 B
Minimum2005-02-16 00:00:00
Maximum2024-01-29 00:00:00
2024-05-11T15:50:55.279177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:50:55.520999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
3
38 
1
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 38
64.4%
1 21
35.6%

Length

2024-05-11T15:50:55.727582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:56.196208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 38
64.4%
1 21
35.6%

영업상태명
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
폐업
38 
영업/정상
21 

Length

Max length5
Median length2
Mean length3.0677966
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 38
64.4%
영업/정상 21
35.6%

Length

2024-05-11T15:50:56.394886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:56.546787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 38
64.4%
영업/정상 21
35.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
2
38 
1
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 38
64.4%
1 21
35.6%

Length

2024-05-11T15:50:56.714213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:56.878220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 38
64.4%
1 21
35.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
폐업
38 
영업
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 38
64.4%
영업 21
35.6%

Length

2024-05-11T15:50:57.038472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:50:57.199723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 38
64.4%
영업 21
35.6%

폐업일자
Date

MISSING 

Distinct37
Distinct (%)97.4%
Missing21
Missing (%)35.6%
Memory size604.0 B
Minimum2005-12-05 00:00:00
Maximum2024-03-19 00:00:00
2024-05-11T15:50:57.353467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:50:57.551223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

전화번호
Text

MISSING 

Distinct33
Distinct (%)94.3%
Missing24
Missing (%)40.7%
Memory size604.0 B
2024-05-11T15:50:57.846934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.085714
Min length8

Characters and Unicode

Total characters388
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

Unique32 ?
Unique (%)91.4%

Sample

1st row02 3736160
2nd row02 9773995
3rd row02 9307085
4th row02 9690045
5th row02 9730767
ValueCountFrequency (%)
02 28
36.8%
4476 3
 
3.9%
462 3
 
3.9%
070 3
 
3.9%
2585 1
 
1.3%
15442795 1
 
1.3%
0269305755 1
 
1.3%
9399111 1
 
1.3%
51738581 1
 
1.3%
34468884 1
 
1.3%
Other values (33) 33
43.4%
2024-05-11T15:50:58.399205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 67
17.3%
58
14.9%
2 48
12.4%
9 35
9.0%
4 33
8.5%
3 28
7.2%
1 28
7.2%
7 26
 
6.7%
6 25
 
6.4%
5 24
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 330
85.1%
Space Separator 58
 
14.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 67
20.3%
2 48
14.5%
9 35
10.6%
4 33
10.0%
3 28
8.5%
1 28
8.5%
7 26
 
7.9%
6 25
 
7.6%
5 24
 
7.3%
8 16
 
4.8%
Space Separator
ValueCountFrequency (%)
58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 67
17.3%
58
14.9%
2 48
12.4%
9 35
9.0%
4 33
8.5%
3 28
7.2%
1 28
7.2%
7 26
 
6.7%
6 25
 
6.4%
5 24
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 67
17.3%
58
14.9%
2 48
12.4%
9 35
9.0%
4 33
8.5%
3 28
7.2%
1 28
7.2%
7 26
 
6.7%
6 25
 
6.4%
5 24
 
6.2%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct40
Distinct (%)90.9%
Missing15
Missing (%)25.4%
Infinite0
Infinite (%)0.0%
Mean53.382045
Minimum0
Maximum322.1
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-05-11T15:50:58.625915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.83
Q18
median31.84
Q372.76
95-th percentile167.2945
Maximum322.1
Range322.1
Interquartile range (IQR)64.76

Descriptive statistics

Standard deviation63.099686
Coefficient of variation (CV)1.1820395
Kurtosis6.8184758
Mean53.382045
Median Absolute Deviation (MAD)28.405
Skewness2.2631141
Sum2348.81
Variance3981.5703
MonotonicityNot monotonic
2024-05-11T15:50:58.870946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
72.76 2
 
3.4%
8.0 2
 
3.4%
33.0 2
 
3.4%
3.3 2
 
3.4%
7.59 1
 
1.7%
66.6 1
 
1.7%
13.2 1
 
1.7%
118.64 1
 
1.7%
170.74 1
 
1.7%
30.0 1
 
1.7%
Other values (30) 30
50.8%
(Missing) 15
25.4%
ValueCountFrequency (%)
0.0 1
1.7%
1.65 1
1.7%
1.8 1
1.7%
2.0 1
1.7%
3.3 2
3.4%
3.57 1
1.7%
4.0 1
1.7%
5.0 1
1.7%
7.59 1
1.7%
8.0 2
3.4%
ValueCountFrequency (%)
322.1 1
1.7%
187.44 1
1.7%
170.74 1
1.7%
147.77 1
1.7%
128.7 1
1.7%
118.64 1
1.7%
99.0 1
1.7%
91.12 1
1.7%
86.43 1
1.7%
79.2 1
1.7%

소재지우편번호
Text

MISSING 

Distinct34
Distinct (%)58.6%
Missing1
Missing (%)1.7%
Memory size604.0 B
2024-05-11T15:50:59.216843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1551724
Min length6

Characters and Unicode

Total characters357
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

Unique23 ?
Unique (%)39.7%

Sample

1st row139230
2nd row139240
3rd row139836
4th row139816
5th row139240
ValueCountFrequency (%)
139240 7
 
12.1%
139860 4
 
6.9%
139815 4
 
6.9%
139821 4
 
6.9%
139838 3
 
5.2%
139808 3
 
5.2%
139230 2
 
3.4%
139876 2
 
3.4%
139-240 2
 
3.4%
139800 2
 
3.4%
Other values (24) 25
43.1%
2024-05-11T15:50:59.754936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 72
20.2%
3 69
19.3%
9 64
17.9%
8 47
13.2%
0 30
8.4%
2 25
 
7.0%
4 16
 
4.5%
6 12
 
3.4%
- 9
 
2.5%
5 7
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 348
97.5%
Dash Punctuation 9
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 72
20.7%
3 69
19.8%
9 64
18.4%
8 47
13.5%
0 30
8.6%
2 25
 
7.2%
4 16
 
4.6%
6 12
 
3.4%
5 7
 
2.0%
7 6
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 357
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 72
20.2%
3 69
19.3%
9 64
17.9%
8 47
13.2%
0 30
8.4%
2 25
 
7.0%
4 16
 
4.5%
6 12
 
3.4%
- 9
 
2.5%
5 7
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 357
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 72
20.2%
3 69
19.3%
9 64
17.9%
8 47
13.2%
0 30
8.4%
2 25
 
7.0%
4 16
 
4.5%
6 12
 
3.4%
- 9
 
2.5%
5 7
 
2.0%

지번주소
Text

MISSING 

Distinct53
Distinct (%)91.4%
Missing1
Missing (%)1.7%
Memory size604.0 B
2024-05-11T15:51:00.208361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length33
Mean length27.206897
Min length17

Characters and Unicode

Total characters1578
Distinct characters118
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

Unique49 ?
Unique (%)84.5%

Sample

1st row서울특별시 노원구 하계동 ***-*번지 삼익선경@상가 ***호
2nd row서울특별시 노원구 공릉동 ***-*번지 드림데시앙 ***호
3rd row서울특별시 노원구 상계동 ***번지 명안빌딩 ***호
4th row서울특별시 노원구 상계동 ***-**번지
5th row서울특별시 노원구 공릉동 ***-**번지 (*층)
ValueCountFrequency (%)
서울특별시 58
19.2%
노원구 58
19.2%
번지 29
9.6%
상계동 28
9.3%
28
9.3%
공릉동 17
 
5.6%
호 16
 
5.3%
중계동 7
 
2.3%
지하*층 4
 
1.3%
층 3
 
1.0%
Other values (44) 54
17.9%
2024-05-11T15:51:01.072775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 298
18.9%
277
17.6%
동 63
 
4.0%
노 62
 
3.9%
원 62
 
3.9%
울 61
 
3.9%
서 60
 
3.8%
시 59
 
3.7%
특 58
 
3.7%
별 58
 
3.7%
Other values (108) 520
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 941
59.6%
Other Punctuation 301
 
19.1%
Space Separator 277
 
17.6%
Dash Punctuation 45
 
2.9%
Decimal Number 6
 
0.4%
Uppercase Letter 4
 
0.3%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 63
 
6.7%
노 62
 
6.6%
원 62
 
6.6%
울 61
 
6.5%
서 60
 
6.4%
시 59
 
6.3%
특 58
 
6.2%
별 58
 
6.2%
구 58
 
6.2%
계 46
 
4.9%
Other values (91) 354
37.6%
Decimal Number
ValueCountFrequency (%)
4 1
16.7%
0 1
16.7%
5 1
16.7%
9 1
16.7%
6 1
16.7%
1 1
16.7%
Other Punctuation
ValueCountFrequency (%)
* 298
99.0%
@ 1
 
0.3%
, 1
 
0.3%
/ 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
D 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
277
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 941
59.6%
Common 633
40.1%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 63
 
6.7%
노 62
 
6.6%
원 62
 
6.6%
울 61
 
6.5%
서 60
 
6.4%
시 59
 
6.3%
특 58
 
6.2%
별 58
 
6.2%
구 58
 
6.2%
계 46
 
4.9%
Other values (91) 354
37.6%
Common
ValueCountFrequency (%)
* 298
47.1%
277
43.8%
- 45
 
7.1%
( 2
 
0.3%
) 2
 
0.3%
@ 1
 
0.2%
4 1
 
0.2%
0 1
 
0.2%
5 1
 
0.2%
9 1
 
0.2%
Other values (4) 4
 
0.6%
Latin
ValueCountFrequency (%)
B 2
50.0%
D 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 941
59.6%
ASCII 637
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 298
46.8%
277
43.5%
- 45
 
7.1%
( 2
 
0.3%
) 2
 
0.3%
B 2
 
0.3%
@ 1
 
0.2%
4 1
 
0.2%
0 1
 
0.2%
5 1
 
0.2%
Other values (7) 7
 
1.1%
Hangul
ValueCountFrequency (%)
동 63
 
6.7%
노 62
 
6.6%
원 62
 
6.6%
울 61
 
6.5%
서 60
 
6.4%
시 59
 
6.3%
특 58
 
6.2%
별 58
 
6.2%
구 58
 
6.2%
계 46
 
4.9%
Other values (91) 354
37.6%

도로명주소
Text

MISSING 

Distinct47
Distinct (%)92.2%
Missing8
Missing (%)13.6%
Memory size604.0 B
2024-05-11T15:51:01.554604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length38
Min length26

Characters and Unicode

Total characters1938
Distinct characters120
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

Unique43 ?
Unique (%)84.3%

Sample

1st row서울특별시 노원구 동일로***길 ** (상계동,명안빌딩 ***호)
2nd row서울특별시 노원구 상계로**길 **, *층 (상계동)
3rd row서울특별시 노원구 동일로***길 ** (상계동,***호-*)
4th row서울특별시 노원구 동일로***길 ** (공릉동, 지하*층)
5th row서울특별시 노원구 동일로 ****, ***호 (상계동, 주공*단지상가)
ValueCountFrequency (%)
55
14.5%
서울특별시 51
13.5%
노원구 51
13.5%
호 35
 
9.2%
상계동 25
 
6.6%
층 24
 
6.3%
공릉동 15
 
4.0%
동일로 11
 
2.9%
동일로***길 8
 
2.1%
한글비석로 6
 
1.6%
Other values (65) 98
25.9%
2024-05-11T15:51:02.325770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 356
18.4%
328
16.9%
동 86
 
4.4%
, 69
 
3.6%
노 62
 
3.2%
원 55
 
2.8%
울 55
 
2.8%
서 54
 
2.8%
) 53
 
2.7%
( 53
 
2.7%
Other values (110) 767
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1053
54.3%
Other Punctuation 426
22.0%
Space Separator 328
 
16.9%
Close Punctuation 53
 
2.7%
Open Punctuation 53
 
2.7%
Dash Punctuation 11
 
0.6%
Uppercase Letter 8
 
0.4%
Decimal Number 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 86
 
8.2%
노 62
 
5.9%
원 55
 
5.2%
울 55
 
5.2%
서 54
 
5.1%
시 51
 
4.8%
구 51
 
4.8%
로 51
 
4.8%
별 51
 
4.8%
특 51
 
4.8%
Other values (95) 486
46.2%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
2 1
16.7%
3 1
16.7%
9 1
16.7%
6 1
16.7%
Other Punctuation
ValueCountFrequency (%)
* 356
83.6%
, 69
 
16.2%
/ 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
B 5
62.5%
A 2
 
25.0%
D 1
 
12.5%
Space Separator
ValueCountFrequency (%)
328
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1053
54.3%
Common 877
45.3%
Latin 8
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 86
 
8.2%
노 62
 
5.9%
원 55
 
5.2%
울 55
 
5.2%
서 54
 
5.1%
시 51
 
4.8%
구 51
 
4.8%
로 51
 
4.8%
별 51
 
4.8%
특 51
 
4.8%
Other values (95) 486
46.2%
Common
ValueCountFrequency (%)
* 356
40.6%
328
37.4%
, 69
 
7.9%
) 53
 
6.0%
( 53
 
6.0%
- 11
 
1.3%
1 2
 
0.2%
2 1
 
0.1%
3 1
 
0.1%
9 1
 
0.1%
Other values (2) 2
 
0.2%
Latin
ValueCountFrequency (%)
B 5
62.5%
A 2
 
25.0%
D 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1053
54.3%
ASCII 885
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 356
40.2%
328
37.1%
, 69
 
7.8%
) 53
 
6.0%
( 53
 
6.0%
- 11
 
1.2%
B 5
 
0.6%
A 2
 
0.2%
1 2
 
0.2%
2 1
 
0.1%
Other values (5) 5
 
0.6%
Hangul
ValueCountFrequency (%)
동 86
 
8.2%
노 62
 
5.9%
원 55
 
5.2%
울 55
 
5.2%
서 54
 
5.1%
시 51
 
4.8%
구 51
 
4.8%
로 51
 
4.8%
별 51
 
4.8%
특 51
 
4.8%
Other values (95) 486
46.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)60.8%
Missing8
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean1747.4902
Minimum1604
Maximum1905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-05-11T15:51:02.584395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1604
5-th percentile1624
Q11668
median1743
Q31846
95-th percentile1880.5
Maximum1905
Range301
Interquartile range (IQR)178

Descriptive statistics

Standard deviation91.20074
Coefficient of variation (CV)0.052189557
Kurtosis-1.3258108
Mean1747.4902
Median Absolute Deviation (MAD)81
Skewness0.13147539
Sum89122
Variance8317.5749
MonotonicityNot monotonic
2024-05-11T15:51:02.875596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1695 6
 
10.2%
1856 3
 
5.1%
1743 3
 
5.1%
1624 3
 
5.1%
1849 2
 
3.4%
1662 2
 
3.4%
1668 2
 
3.4%
1811 2
 
3.4%
1844 2
 
3.4%
1604 2
 
3.4%
Other values (21) 24
40.7%
(Missing) 8
 
13.6%
ValueCountFrequency (%)
1604 2
3.4%
1624 3
5.1%
1629 1
 
1.7%
1630 1
 
1.7%
1640 1
 
1.7%
1657 1
 
1.7%
1662 2
3.4%
1663 1
 
1.7%
1668 2
3.4%
1681 1
 
1.7%
ValueCountFrequency (%)
1905 2
3.4%
1900 1
 
1.7%
1861 1
 
1.7%
1857 1
 
1.7%
1856 3
5.1%
1852 1
 
1.7%
1849 2
3.4%
1848 2
3.4%
1844 2
3.4%
1811 2
3.4%

사업장명
Text

Distinct57
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size604.0 B
2024-05-11T15:51:03.246900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length7.8983051
Min length2

Characters and Unicode

Total characters466
Distinct characters155
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

Unique55 ?
Unique (%)93.2%

Sample

1st row씨엔엘코리아
2nd row(주)나야리브앤허브
3rd row넥스트 팜
4th row(주)천잠바이오
5th row(주)바이오메디팜
ValueCountFrequency (%)
주식회사 9
 
11.8%
주)올데이즈 2
 
2.6%
어니스트아워 2
 
2.6%
이터널글로우 1
 
1.3%
지큐브스페이스(주 1
 
1.3%
비어니스트 1
 
1.3%
뉴데이라이프 1
 
1.3%
더식스6 1
 
1.3%
아이비웰니스 1
 
1.3%
엠엠엠(mmm 1
 
1.3%
Other values (56) 56
73.7%
2024-05-11T15:51:03.889727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 30
 
6.4%
( 26
 
5.6%
이 26
 
5.6%
) 26
 
5.6%
스 20
 
4.3%
17
 
3.6%
리 12
 
2.6%
사 11
 
2.4%
식 11
 
2.4%
회 10
 
2.1%
Other values (145) 277
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 369
79.2%
Open Punctuation 26
 
5.6%
Close Punctuation 26
 
5.6%
Uppercase Letter 22
 
4.7%
Space Separator 17
 
3.6%
Other Punctuation 3
 
0.6%
Lowercase Letter 2
 
0.4%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 30
 
8.1%
이 26
 
7.0%
스 20
 
5.4%
리 12
 
3.3%
사 11
 
3.0%
식 11
 
3.0%
회 10
 
2.7%
아 10
 
2.7%
에 8
 
2.2%
니 6
 
1.6%
Other values (123) 225
61.0%
Uppercase Letter
ValueCountFrequency (%)
E 3
13.6%
M 3
13.6%
K 3
13.6%
A 2
9.1%
L 2
9.1%
I 1
 
4.5%
T 1
 
4.5%
N 1
 
4.5%
B 1
 
4.5%
H 1
 
4.5%
Other values (4) 4
18.2%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
& 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
h 1
50.0%
p 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 369
79.2%
Common 73
 
15.7%
Latin 24
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 30
 
8.1%
이 26
 
7.0%
스 20
 
5.4%
리 12
 
3.3%
사 11
 
3.0%
식 11
 
3.0%
회 10
 
2.7%
아 10
 
2.7%
에 8
 
2.2%
니 6
 
1.6%
Other values (123) 225
61.0%
Latin
ValueCountFrequency (%)
E 3
12.5%
M 3
12.5%
K 3
12.5%
A 2
 
8.3%
L 2
 
8.3%
I 1
 
4.2%
T 1
 
4.2%
h 1
 
4.2%
p 1
 
4.2%
N 1
 
4.2%
Other values (6) 6
25.0%
Common
ValueCountFrequency (%)
( 26
35.6%
) 26
35.6%
17
23.3%
. 2
 
2.7%
6 1
 
1.4%
& 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 369
79.2%
ASCII 97
 
20.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 30
 
8.1%
이 26
 
7.0%
스 20
 
5.4%
리 12
 
3.3%
사 11
 
3.0%
식 11
 
3.0%
회 10
 
2.7%
아 10
 
2.7%
에 8
 
2.2%
니 6
 
1.6%
Other values (123) 225
61.0%
ASCII
ValueCountFrequency (%)
( 26
26.8%
) 26
26.8%
17
17.5%
E 3
 
3.1%
M 3
 
3.1%
K 3
 
3.1%
A 2
 
2.1%
. 2
 
2.1%
L 2
 
2.1%
I 1
 
1.0%
Other values (12) 12
12.4%

최종수정일자
Date

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
Minimum2005-02-16 00:00:00
Maximum2024-04-03 16:52:46
2024-05-11T15:51:04.150330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:51:04.408133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
I
30 
U
29 

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 30
50.8%
U 29
49.2%

Length

2024-05-11T15:51:04.777118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:04.946928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 30
50.8%
u 29
49.2%

데이터갱신일자
Date

Distinct38
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-05-11T15:51:05.148770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:51:05.385483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size604.0 B
건강기능식품유통전문판매업
59 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 59
100.0%

Length

2024-05-11T15:51:05.604369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:05.767260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 59
100.0%

좌표정보(X)
Real number (ℝ)

Distinct49
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206056.17
Minimum204772.37
Maximum209288.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-05-11T15:51:05.940644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum204772.37
5-th percentile204855.56
Q1205367.75
median206219.44
Q3206591.08
95-th percentile207003.88
Maximum209288.47
Range4516.1052
Interquartile range (IQR)1223.3268

Descriptive statistics

Standard deviation817.63924
Coefficient of variation (CV)0.0039680405
Kurtosis2.6715795
Mean206056.17
Median Absolute Deviation (MAD)509.79024
Skewness0.8251713
Sum12157314
Variance668533.93
MonotonicityNot monotonic
2024-05-11T15:51:06.167684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
204855.557180678 3
 
5.1%
206670.816544196 3
 
5.1%
205457.262344455 2
 
3.4%
205316.296326505 2
 
3.4%
205394.112077124 2
 
3.4%
206981.454072644 2
 
3.4%
206167.818533363 2
 
3.4%
205539.051712379 2
 
3.4%
206398.704431349 1
 
1.7%
206270.823086152 1
 
1.7%
Other values (39) 39
66.1%
ValueCountFrequency (%)
204772.367380466 1
 
1.7%
204772.500639238 1
 
1.7%
204855.557180678 3
5.1%
204925.644547521 1
 
1.7%
205050.277652595 1
 
1.7%
205088.642066605 1
 
1.7%
205164.054482331 1
 
1.7%
205280.620692797 1
 
1.7%
205316.296326505 2
3.4%
205320.28476675 1
 
1.7%
ValueCountFrequency (%)
209288.472624641 1
 
1.7%
207416.586869686 1
 
1.7%
207205.750980015 1
 
1.7%
206981.454072644 2
3.4%
206780.476887016 1
 
1.7%
206778.450736384 1
 
1.7%
206729.227612118 1
 
1.7%
206691.97251787 1
 
1.7%
206670.816544196 3
5.1%
206664.089750683 1
 
1.7%

좌표정보(Y)
Real number (ℝ)

Distinct49
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean460503.04
Minimum457247.57
Maximum464208.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-05-11T15:51:06.421043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum457247.57
5-th percentile457395.84
Q1458212.84
median460875.73
Q3461986.89
95-th percentile464199.05
Maximum464208.31
Range6960.7346
Interquartile range (IQR)3774.053

Descriptive statistics

Standard deviation2133.5985
Coefficient of variation (CV)0.004633191
Kurtosis-1.112947
Mean460503.04
Median Absolute Deviation (MAD)1613.9816
Skewness-0.024385818
Sum27169679
Variance4552242.7
MonotonicityNot monotonic
2024-05-11T15:51:06.666910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
464199.048415229 3
 
5.1%
460805.152066849 3
 
5.1%
461407.049044413 2
 
3.4%
458732.958771992 2
 
3.4%
461283.511494133 2
 
3.4%
458960.471391303 2
 
3.4%
462148.356096392 2
 
3.4%
461429.301858351 2
 
3.4%
461941.994104029 1
 
1.7%
462123.792297709 1
 
1.7%
Other values (39) 39
66.1%
ValueCountFrequency (%)
457247.570869701 1
1.7%
457328.101115098 1
1.7%
457367.50332357 1
1.7%
457398.993186325 1
1.7%
457527.664831153 1
1.7%
457630.323773339 1
1.7%
457642.18199673 1
1.7%
457713.125160651 1
1.7%
457731.027183726 1
1.7%
457732.697234044 1
1.7%
ValueCountFrequency (%)
464208.305428933 1
 
1.7%
464199.048415229 3
5.1%
464080.593904719 1
 
1.7%
463511.788573322 1
 
1.7%
463253.973796138 1
 
1.7%
462737.128135561 1
 
1.7%
462714.188504333 1
 
1.7%
462489.71350395 1
 
1.7%
462163.419948214 1
 
1.7%
462148.356096392 2
3.4%

위생업태명
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
건강기능식품유통전문판매업
40 
<NA>
19 

Length

Max length13
Median length13
Mean length10.101695
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 40
67.8%
<NA> 19
32.2%

Length

2024-05-11T15:51:06.915663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:07.103050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 40
67.8%
na 19
32.2%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
56 
0
 
3

Length

Max length4
Median length4
Mean length3.8474576
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> 56
94.9%
0 3
 
5.1%

Length

2024-05-11T15:51:07.298342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:07.507527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
94.9%
0 3
 
5.1%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
56 
0
 
3

Length

Max length4
Median length4
Mean length3.8474576
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> 56
94.9%
0 3
 
5.1%

Length

2024-05-11T15:51:07.670281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:07.846557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
94.9%
0 3
 
5.1%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

급수시설구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
56 
0
 
3

Length

Max length4
Median length4
Mean length3.8474576
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> 56
94.9%
0 3
 
5.1%

Length

2024-05-11T15:51:08.028688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:08.204010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
94.9%
0 3
 
5.1%

본사종업원수
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
52 
0
7 

Length

Max length4
Median length4
Mean length3.6440678
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
88.1%
0 7
 
11.9%

Length

2024-05-11T15:51:08.375631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:08.533823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
88.1%
0 7
 
11.9%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
52 
0
7 

Length

Max length4
Median length4
Mean length3.6440678
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
88.1%
0 7
 
11.9%

Length

2024-05-11T15:51:08.723460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:09.315415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
88.1%
0 7
 
11.9%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
52 
0
7 

Length

Max length4
Median length4
Mean length3.6440678
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
88.1%
0 7
 
11.9%

Length

2024-05-11T15:51:09.509138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:09.691332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
88.1%
0 7
 
11.9%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
52 
0
7 

Length

Max length4
Median length4
Mean length3.6440678
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
88.1%
0 7
 
11.9%

Length

2024-05-11T15:51:09.879703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:10.084709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
88.1%
0 7
 
11.9%

건물소유구분명
Categorical

Distinct3
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
38 
자가
16 
임대
5 

Length

Max length4
Median length4
Mean length3.2881356
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> 38
64.4%
자가 16
27.1%
임대 5
 
8.5%

Length

2024-05-11T15:51:10.293719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:10.498049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 38
64.4%
자가 16
27.1%
임대 5
 
8.5%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
56 
0
 
3

Length

Max length4
Median length4
Mean length3.8474576
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> 56
94.9%
0 3
 
5.1%

Length

2024-05-11T15:51:10.724123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:10.907403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
94.9%
0 3
 
5.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
56 
0
 
3

Length

Max length4
Median length4
Mean length3.8474576
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> 56
94.9%
0 3
 
5.1%

Length

2024-05-11T15:51:11.114366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:11.295380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
94.9%
0 3
 
5.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.5%
Missing19
Missing (%)32.2%
Memory size250.0 B
False
40 
(Missing)
19 
ValueCountFrequency (%)
False 40
67.8%
(Missing) 19
32.2%
2024-05-11T15:51:11.453952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
0
40 
<NA>
19 

Length

Max length4
Median length1
Mean length1.9661017
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 40
67.8%
<NA> 19
32.2%

Length

2024-05-11T15:51:11.652427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:51:11.839964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 40
67.8%
na 19
32.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-135-2005-0000120050216<NA>3폐업2폐업20120402<NA><NA><NA>02 3736160<NA>139230서울특별시 노원구 하계동 ***-*번지 삼익선경@상가 ***호<NA><NA>씨엔엘코리아2005-02-16 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업206729.227612459636.254942건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
131000003100000-135-2005-0000220050318<NA>3폐업2폐업20051205<NA><NA><NA>02 9773995<NA>139240서울특별시 노원구 공릉동 ***-*번지 드림데시앙 ***호<NA><NA>(주)나야리브앤허브2005-03-18 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업206593.924069457642.181997건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
231000003100000-135-2005-0000320050511<NA>1영업/정상1영업<NA><NA><NA><NA>02 9307085<NA>139836서울특별시 노원구 상계동 ***번지 명안빌딩 ***호서울특별시 노원구 동일로***길 ** (상계동,명안빌딩 ***호)1629넥스트 팜2005-05-11 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업205050.277653463253.973796건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
331000003100000-135-2005-0000420050802<NA>1영업/정상1영업<NA><NA><NA><NA>02 96900453.57139816서울특별시 노원구 상계동 ***-**번지서울특별시 노원구 상계로**길 **, *층 (상계동)1697(주)천잠바이오2017-12-27 16:47:25I2018-08-31 23:59:59.0건강기능식품유통전문판매업206008.802538461631.464671건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0<NA><NA><NA>
431000003100000-135-2006-0000120060221<NA>3폐업2폐업20080526<NA><NA><NA>02 9730767<NA>139240서울특별시 노원구 공릉동 ***-**번지 (*층)<NA><NA>(주)바이오메디팜2006-02-21 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업206588.226679457527.664831건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
531000003100000-135-2006-0000220060524<NA>3폐업2폐업20080514<NA><NA><NA>02 9360380<NA>139820서울특별시 노원구 상계동 ***번지 한신*차상가 ***호<NA><NA>엔.에치.엘(NHL)2006-05-24 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업205934.06261462489.713504건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
631000003100000-135-2006-0000320061020<NA>1영업/정상1영업<NA><NA><NA><NA>02 930078129.7139832서울특별시 노원구 상계동 ***-*번지 ***호-*서울특별시 노원구 동일로***길 ** (상계동,***호-*)1751비타민하우스KB2014-07-21 09:13:50I2018-08-31 23:59:59.0건강기능식품유통전문판매업205394.112077461283.511494건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
731000003100000-135-2006-0000420060111<NA>3폐업2폐업20190603<NA><NA><NA><NA>91.12139808서울특별시 노원구 공릉동 ***-*번지 지하*층서울특별시 노원구 동일로***길 ** (공릉동, 지하*층)1861훼미리팜2019-06-03 13:41:06U2019-06-05 02:40:00.0건강기능식품유통전문판매업206478.998792457328.101115건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0<NA><NA><NA>
831000003100000-135-2008-0000120080305<NA>3폐업2폐업20220419<NA><NA><NA>02 9319700<NA>139831서울특별시 노원구 상계동 ***-* ***호서울특별시 노원구 동일로 ****, ***호 (상계동, 주공*단지상가)1763(주)글라이코엔텍2022-04-19 10:04:27U2021-12-03 22:01:00.0건강기능식품유통전문판매업205341.384983460838.369137<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
931000003100000-135-2008-0000220081210<NA>3폐업2폐업20110817<NA><NA><NA>02 933054527.26139860서울특별시 노원구 중계동 ***-**번지 새롬스타빌 ***호<NA><NA>(주)하원통상2010-01-22 13:23:59I2018-08-31 23:59:59.0건강기능식품유통전문판매업206664.089751460682.866029건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
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5331000003100000-135-2022-000022022-07-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-832서울특별시 노원구 상계동 ***-* 일신상가서울특별시 노원구 동일로***길 **, 일신상가 *층 *호 (상계동)1751탑셀프라임2024-04-03 16:52:46U2023-12-04 00:05:00.0건강기능식품유통전문판매업205394.112077461283.511494<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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