Overview

Dataset statistics

Number of variables44
Number of observations102
Missing cells1230
Missing cells (%)27.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.8 KiB
Average record size in memory379.3 B

Variable types

Categorical19
Text6
DateTime4
Unsupported9
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18066/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
급수시설구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (63.9%)Imbalance
여성종사자수 is highly imbalanced (63.9%)Imbalance
총인원 is highly imbalanced (67.7%)Imbalance
보증액 is highly imbalanced (55.6%)Imbalance
월세액 is highly imbalanced (55.6%)Imbalance
인허가취소일자 has 102 (100.0%) missing valuesMissing
폐업일자 has 36 (35.3%) missing valuesMissing
휴업시작일자 has 102 (100.0%) missing valuesMissing
휴업종료일자 has 102 (100.0%) missing valuesMissing
재개업일자 has 102 (100.0%) missing valuesMissing
전화번호 has 36 (35.3%) missing valuesMissing
소재지면적 has 40 (39.2%) missing valuesMissing
도로명주소 has 17 (16.7%) missing valuesMissing
도로명우편번호 has 17 (16.7%) missing valuesMissing
영업장주변구분명 has 102 (100.0%) missing valuesMissing
등급구분명 has 102 (100.0%) missing valuesMissing
급수시설구분명 has 100 (98.0%) missing valuesMissing
다중이용업소여부 has 32 (31.4%) missing valuesMissing
시설총규모 has 32 (31.4%) missing valuesMissing
전통업소지정번호 has 102 (100.0%) missing valuesMissing
전통업소주된음식 has 102 (100.0%) missing valuesMissing
홈페이지 has 102 (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
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 16 (15.7%) zerosZeros
시설총규모 has 62 (60.8%) zerosZeros

Reproduction

Analysis started2024-05-11 00:41:10.459274
Analysis finished2024-05-11 00:41:12.268567
Duration1.81 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
3140000
102 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 102
100.0%

Length

2024-05-11T00:41:12.473956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:12.917489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 102
100.0%

관리번호
Text

UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2024-05-11T00:41:13.488969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2244
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

Unique102 ?
Unique (%)100.0%

Sample

1st row3140000-135-2004-00001
2nd row3140000-135-2004-00002
3rd row3140000-135-2004-00003
4th row3140000-135-2004-00004
5th row3140000-135-2004-00005
ValueCountFrequency (%)
3140000-135-2004-00001 1
 
1.0%
3140000-135-2018-00003 1
 
1.0%
3140000-135-2020-00007 1
 
1.0%
3140000-135-2020-00006 1
 
1.0%
3140000-135-2020-00005 1
 
1.0%
3140000-135-2020-00004 1
 
1.0%
3140000-135-2020-00003 1
 
1.0%
3140000-135-2020-00002 1
 
1.0%
3140000-135-2019-00004 1
 
1.0%
3140000-135-2019-00003 1
 
1.0%
Other values (92) 92
90.2%
2024-05-11T00:41:14.550851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 954
42.5%
- 306
 
13.6%
1 276
 
12.3%
3 236
 
10.5%
2 176
 
7.8%
4 129
 
5.7%
5 124
 
5.5%
6 16
 
0.7%
8 10
 
0.4%
9 9
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1938
86.4%
Dash Punctuation 306
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 954
49.2%
1 276
 
14.2%
3 236
 
12.2%
2 176
 
9.1%
4 129
 
6.7%
5 124
 
6.4%
6 16
 
0.8%
8 10
 
0.5%
9 9
 
0.5%
7 8
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 306
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2244
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 954
42.5%
- 306
 
13.6%
1 276
 
12.3%
3 236
 
10.5%
2 176
 
7.8%
4 129
 
5.7%
5 124
 
5.5%
6 16
 
0.7%
8 10
 
0.4%
9 9
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 954
42.5%
- 306
 
13.6%
1 276
 
12.3%
3 236
 
10.5%
2 176
 
7.8%
4 129
 
5.7%
5 124
 
5.5%
6 16
 
0.7%
8 10
 
0.4%
9 9
 
0.4%

인허가일자
Date

Distinct99
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size948.0 B
Minimum2004-04-07 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T00:41:14.963260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:15.367605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing102
Missing (%)100.0%
Memory size1.0 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
3
66 
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 66
64.7%
1 36
35.3%

Length

2024-05-11T00:41:15.773253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:16.214357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 66
64.7%
1 36
35.3%

영업상태명
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
폐업
66 
영업/정상
36 

Length

Max length5
Median length2
Mean length3.0588235
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 66
64.7%
영업/정상 36
35.3%

Length

2024-05-11T00:41:16.527881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:16.753525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 66
64.7%
영업/정상 36
35.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2
66 
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 66
64.7%
1 36
35.3%

Length

2024-05-11T00:41:17.050707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:17.272848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 66
64.7%
1 36
35.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
폐업
66 
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 66
64.7%
영업 36
35.3%

Length

2024-05-11T00:41:17.481208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:17.718591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 66
64.7%
영업 36
35.3%

폐업일자
Date

MISSING 

Distinct60
Distinct (%)90.9%
Missing36
Missing (%)35.3%
Memory size948.0 B
Minimum2004-12-02 00:00:00
Maximum2024-04-11 00:00:00
2024-05-11T00:41:17.970467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:18.379271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing102
Missing (%)100.0%
Memory size1.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing102
Missing (%)100.0%
Memory size1.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing102
Missing (%)100.0%
Memory size1.0 KiB

전화번호
Text

MISSING 

Distinct64
Distinct (%)97.0%
Missing36
Missing (%)35.3%
Memory size948.0 B
2024-05-11T00:41:18.898354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.015152
Min length8

Characters and Unicode

Total characters661
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

Unique62 ?
Unique (%)93.9%

Sample

1st row0226583652
2nd row0226435644
3rd row0226486835
4th row0221677791
5th row0226963832
ValueCountFrequency (%)
02 14
 
16.3%
26088981 2
 
2.3%
0226950260 2
 
2.3%
0226422337 1
 
1.2%
070 1
 
1.2%
0226583652 1
 
1.2%
0226970529 1
 
1.2%
0232198107 1
 
1.2%
0226908529 1
 
1.2%
585 1
 
1.2%
Other values (61) 61
70.9%
2024-05-11T00:41:19.935033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 142
21.5%
0 102
15.4%
6 83
12.6%
5 58
8.8%
8 56
 
8.5%
9 44
 
6.7%
4 40
 
6.1%
1 38
 
5.7%
3 38
 
5.7%
32
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 629
95.2%
Space Separator 32
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 142
22.6%
0 102
16.2%
6 83
13.2%
5 58
9.2%
8 56
 
8.9%
9 44
 
7.0%
4 40
 
6.4%
1 38
 
6.0%
3 38
 
6.0%
7 28
 
4.5%
Space Separator
ValueCountFrequency (%)
32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 661
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 142
21.5%
0 102
15.4%
6 83
12.6%
5 58
8.8%
8 56
 
8.5%
9 44
 
6.7%
4 40
 
6.1%
1 38
 
5.7%
3 38
 
5.7%
32
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 661
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 142
21.5%
0 102
15.4%
6 83
12.6%
5 58
8.8%
8 56
 
8.5%
9 44
 
6.7%
4 40
 
6.1%
1 38
 
5.7%
3 38
 
5.7%
32
 
4.8%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct45
Distinct (%)72.6%
Missing40
Missing (%)39.2%
Infinite0
Infinite (%)0.0%
Mean68.93629
Minimum0
Maximum607
Zeros16
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-11T00:41:20.378906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.75
median32.67
Q368.475
95-th percentile250.15
Maximum607
Range607
Interquartile range (IQR)67.725

Descriptive statistics

Standard deviation115.42919
Coefficient of variation (CV)1.6744328
Kurtosis12.162395
Mean68.93629
Median Absolute Deviation (MAD)32.67
Skewness3.2717465
Sum4274.05
Variance13323.897
MonotonicityNot monotonic
2024-05-11T00:41:21.496206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0.0 16
 
15.7%
66.0 3
 
2.9%
25.76 1
 
1.0%
3.5 1
 
1.0%
100.0 1
 
1.0%
51.2 1
 
1.0%
23.8 1
 
1.0%
58.0 1
 
1.0%
10.79 1
 
1.0%
45.51 1
 
1.0%
Other values (35) 35
34.3%
(Missing) 40
39.2%
ValueCountFrequency (%)
0.0 16
15.7%
3.0 1
 
1.0%
3.3 1
 
1.0%
3.5 1
 
1.0%
6.6 1
 
1.0%
7.0 1
 
1.0%
10.79 1
 
1.0%
12.0 1
 
1.0%
13.29 1
 
1.0%
15.0 1
 
1.0%
ValueCountFrequency (%)
607.0 1
1.0%
565.76 1
1.0%
301.7 1
1.0%
252.0 1
1.0%
215.0 1
1.0%
200.0 1
1.0%
192.13 1
1.0%
124.08 1
1.0%
119.75 1
1.0%
115.5 1
1.0%

소재지우편번호
Categorical

Distinct50
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
158050
21 
158806
 
5
158856
 
4
158-050
 
4
158849
 
3
Other values (45)
65 

Length

Max length7
Median length6
Mean length6.2254902
Min length6

Unique

Unique30 ?
Unique (%)29.4%

Sample

1st row158850
2nd row158818
3rd row158815
4th row158806
5th row158827

Common Values

ValueCountFrequency (%)
158050 21
20.6%
158806 5
 
4.9%
158856 4
 
3.9%
158-050 4
 
3.9%
158849 3
 
2.9%
158827 3
 
2.9%
158070 3
 
2.9%
158860 3
 
2.9%
158831 3
 
2.9%
158859 3
 
2.9%
Other values (40) 50
49.0%

Length

2024-05-11T00:41:22.227919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
158050 21
20.6%
158806 5
 
4.9%
158856 4
 
3.9%
158-050 4
 
3.9%
158849 3
 
2.9%
158827 3
 
2.9%
158070 3
 
2.9%
158860 3
 
2.9%
158831 3
 
2.9%
158859 3
 
2.9%
Other values (40) 50
49.0%

지번주소
Text

Distinct83
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Memory size948.0 B
2024-05-11T00:41:23.121082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32
Mean length27.431373
Min length18

Characters and Unicode

Total characters2798
Distinct characters119
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

Unique67 ?
Unique (%)65.7%

Sample

1st row서울특별시 양천구 신정동 ***-***번지 (지상*층)
2nd row서울특별시 양천구 목동 ***-**번지 *층
3rd row서울특별시 양천구 목동 ***-**번지
4th row서울특별시 양천구 목동 ***-***번지 *층
5th row서울특별시 양천구 신월동 ***-**번지 *층
ValueCountFrequency (%)
서울특별시 101
18.9%
양천구 100
18.7%
번지 57
10.7%
목동 50
9.4%
47
8.8%
신정동 31
 
5.8%
호 29
 
5.4%
층 22
 
4.1%
신월동 19
 
3.6%
현대**타워 11
 
2.1%
Other values (57) 67
12.5%
2024-05-11T00:41:25.148019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 631
22.6%
483
17.3%
동 113
 
4.0%
시 103
 
3.7%
천 103
 
3.7%
서 102
 
3.6%
양 102
 
3.6%
구 101
 
3.6%
울 101
 
3.6%
특 101
 
3.6%
Other values (109) 858
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1572
56.2%
Other Punctuation 633
22.6%
Space Separator 483
 
17.3%
Dash Punctuation 92
 
3.3%
Decimal Number 9
 
0.3%
Uppercase Letter 5
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 113
 
7.2%
시 103
 
6.6%
천 103
 
6.6%
서 102
 
6.5%
양 102
 
6.5%
구 101
 
6.4%
울 101
 
6.4%
특 101
 
6.4%
별 101
 
6.4%
지 60
 
3.8%
Other values (95) 585
37.2%
Decimal Number
ValueCountFrequency (%)
3 3
33.3%
6 2
22.2%
1 2
22.2%
2 1
 
11.1%
9 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
* 631
99.7%
, 1
 
0.2%
/ 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
B 4
80.0%
D 1
 
20.0%
Space Separator
ValueCountFrequency (%)
483
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1572
56.2%
Common 1221
43.6%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 113
 
7.2%
시 103
 
6.6%
천 103
 
6.6%
서 102
 
6.5%
양 102
 
6.5%
구 101
 
6.4%
울 101
 
6.4%
특 101
 
6.4%
별 101
 
6.4%
지 60
 
3.8%
Other values (95) 585
37.2%
Common
ValueCountFrequency (%)
* 631
51.7%
483
39.6%
- 92
 
7.5%
3 3
 
0.2%
6 2
 
0.2%
( 2
 
0.2%
1 2
 
0.2%
) 2
 
0.2%
2 1
 
0.1%
, 1
 
0.1%
Other values (2) 2
 
0.2%
Latin
ValueCountFrequency (%)
B 4
80.0%
D 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1572
56.2%
ASCII 1226
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 631
51.5%
483
39.4%
- 92
 
7.5%
B 4
 
0.3%
3 3
 
0.2%
6 2
 
0.2%
( 2
 
0.2%
1 2
 
0.2%
) 2
 
0.2%
2 1
 
0.1%
Other values (4) 4
 
0.3%
Hangul
ValueCountFrequency (%)
동 113
 
7.2%
시 103
 
6.6%
천 103
 
6.6%
서 102
 
6.5%
양 102
 
6.5%
구 101
 
6.4%
울 101
 
6.4%
특 101
 
6.4%
별 101
 
6.4%
지 60
 
3.8%
Other values (95) 585
37.2%

도로명주소
Text

MISSING 

Distinct80
Distinct (%)94.1%
Missing17
Missing (%)16.7%
Memory size948.0 B
2024-05-11T00:41:25.943271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length40
Mean length35.270588
Min length23

Characters and Unicode

Total characters2998
Distinct characters137
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

Unique76 ?
Unique (%)89.4%

Sample

1st row서울특별시 양천구 목동남로*길 ** (신정동,(지상*층))
2nd row서울특별시 양천구 목동중앙서로 ** (목동,*층)
3rd row서울특별시 양천구 오목로 *** (목동, *층)
4th row서울특별시 양천구 신월로 *** (신월동,로즈가든***)
5th row서울특별시 양천구 신목로 ** (신정동,*층)
ValueCountFrequency (%)
87
15.1%
서울특별시 84
14.6%
양천구 83
14.4%
호 46
 
8.0%
층 37
 
6.4%
목동 35
 
6.1%
신정동 24
 
4.2%
목동동로 14
 
2.4%
신월동 12
 
2.1%
목동서로 10
 
1.7%
Other values (106) 143
24.9%
2024-05-11T00:41:27.410437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 528
17.6%
490
16.3%
동 156
 
5.2%
, 112
 
3.7%
목 98
 
3.3%
서 96
 
3.2%
로 88
 
2.9%
천 86
 
2.9%
시 86
 
2.9%
( 86
 
2.9%
Other values (127) 1172
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1650
55.0%
Other Punctuation 641
 
21.4%
Space Separator 490
 
16.3%
Open Punctuation 86
 
2.9%
Close Punctuation 86
 
2.9%
Dash Punctuation 20
 
0.7%
Decimal Number 19
 
0.6%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 156
 
9.5%
목 98
 
5.9%
서 96
 
5.8%
로 88
 
5.3%
천 86
 
5.2%
시 86
 
5.2%
양 85
 
5.2%
구 84
 
5.1%
별 84
 
5.1%
울 84
 
5.1%
Other values (112) 703
42.6%
Decimal Number
ValueCountFrequency (%)
1 6
31.6%
5 5
26.3%
3 4
21.1%
2 2
 
10.5%
0 2
 
10.5%
Other Punctuation
ValueCountFrequency (%)
* 528
82.4%
, 112
 
17.5%
/ 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
B 4
66.7%
A 1
 
16.7%
D 1
 
16.7%
Space Separator
ValueCountFrequency (%)
490
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1650
55.0%
Common 1342
44.8%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 156
 
9.5%
목 98
 
5.9%
서 96
 
5.8%
로 88
 
5.3%
천 86
 
5.2%
시 86
 
5.2%
양 85
 
5.2%
구 84
 
5.1%
별 84
 
5.1%
울 84
 
5.1%
Other values (112) 703
42.6%
Common
ValueCountFrequency (%)
* 528
39.3%
490
36.5%
, 112
 
8.3%
( 86
 
6.4%
) 86
 
6.4%
- 20
 
1.5%
1 6
 
0.4%
5 5
 
0.4%
3 4
 
0.3%
2 2
 
0.1%
Other values (2) 3
 
0.2%
Latin
ValueCountFrequency (%)
B 4
66.7%
A 1
 
16.7%
D 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1650
55.0%
ASCII 1348
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 528
39.2%
490
36.4%
, 112
 
8.3%
( 86
 
6.4%
) 86
 
6.4%
- 20
 
1.5%
1 6
 
0.4%
5 5
 
0.4%
B 4
 
0.3%
3 4
 
0.3%
Other values (5) 7
 
0.5%
Hangul
ValueCountFrequency (%)
동 156
 
9.5%
목 98
 
5.9%
서 96
 
5.8%
로 88
 
5.3%
천 86
 
5.2%
시 86
 
5.2%
양 85
 
5.2%
구 84
 
5.1%
별 84
 
5.1%
울 84
 
5.1%
Other values (112) 703
42.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct53
Distinct (%)62.4%
Missing17
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean8137.4706
Minimum4089
Maximum24387
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-11T00:41:27.937791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4089
5-th percentile7911.8
Q17949
median7995
Q38017
95-th percentile8087
Maximum24387
Range20298
Interquartile range (IQR)68

Descriptive statistics

Standard deviation1833.6257
Coefficient of variation (CV)0.22533116
Kurtosis76.055505
Mean8137.4706
Median Absolute Deviation (MAD)31
Skewness8.3530959
Sum691685
Variance3362183.2
MonotonicityNot monotonic
2024-05-11T00:41:28.535029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7997 11
 
10.8%
7995 7
 
6.9%
7938 4
 
3.9%
8006 3
 
2.9%
8021 3
 
2.9%
7926 3
 
2.9%
7903 2
 
2.0%
7949 2
 
2.0%
8015 2
 
2.0%
8087 2
 
2.0%
Other values (43) 46
45.1%
(Missing) 17
 
16.7%
ValueCountFrequency (%)
4089 1
 
1.0%
7903 2
2.0%
7907 1
 
1.0%
7910 1
 
1.0%
7919 1
 
1.0%
7922 1
 
1.0%
7926 3
2.9%
7935 1
 
1.0%
7936 1
 
1.0%
7938 4
3.9%
ValueCountFrequency (%)
24387 1
1.0%
8104 1
1.0%
8093 1
1.0%
8092 1
1.0%
8087 2
2.0%
8086 1
1.0%
8079 1
1.0%
8064 1
1.0%
8061 1
1.0%
8053 1
1.0%

사업장명
Text

Distinct100
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2024-05-11T00:41:29.385997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length7.5882353
Min length2

Characters and Unicode

Total characters774
Distinct characters220
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

Unique98 ?
Unique (%)96.1%

Sample

1st row해외개발(주)
2nd row전국농산물유통상사
3rd row노블라이프
4th row소망화장품(주)
5th row청산유통
ValueCountFrequency (%)
주식회사 18
 
14.1%
주 2
 
1.6%
가포생활건강 2
 
1.6%
주)강화홍삼공사 2
 
1.6%
코리아 1
 
0.8%
필로메디 1
 
0.8%
주)지안바이오 1
 
0.8%
코드네이처 1
 
0.8%
준스퀘어 1
 
0.8%
지앤건강생활 1
 
0.8%
Other values (98) 98
76.6%
2024-05-11T00:41:30.745138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 62
 
8.0%
( 45
 
5.8%
) 45
 
5.8%
이 37
 
4.8%
26
 
3.4%
사 24
 
3.1%
식 23
 
3.0%
스 22
 
2.8%
회 20
 
2.6%
리 12
 
1.6%
Other values (210) 458
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 639
82.6%
Open Punctuation 45
 
5.8%
Close Punctuation 45
 
5.8%
Space Separator 26
 
3.4%
Uppercase Letter 14
 
1.8%
Decimal Number 2
 
0.3%
Lowercase Letter 2
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 62
 
9.7%
이 37
 
5.8%
사 24
 
3.8%
식 23
 
3.6%
스 22
 
3.4%
회 20
 
3.1%
리 12
 
1.9%
에 12
 
1.9%
아 10
 
1.6%
프 9
 
1.4%
Other values (192) 408
63.8%
Uppercase Letter
ValueCountFrequency (%)
M 3
21.4%
B 2
14.3%
G 2
14.3%
S 1
 
7.1%
C 1
 
7.1%
T 1
 
7.1%
R 1
 
7.1%
I 1
 
7.1%
J 1
 
7.1%
F 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
5 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
50.0%
a 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 639
82.6%
Common 119
 
15.4%
Latin 16
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 62
 
9.7%
이 37
 
5.8%
사 24
 
3.8%
식 23
 
3.6%
스 22
 
3.4%
회 20
 
3.1%
리 12
 
1.9%
에 12
 
1.9%
아 10
 
1.6%
프 9
 
1.4%
Other values (192) 408
63.8%
Latin
ValueCountFrequency (%)
M 3
18.8%
B 2
12.5%
G 2
12.5%
S 1
 
6.2%
C 1
 
6.2%
T 1
 
6.2%
R 1
 
6.2%
b 1
 
6.2%
a 1
 
6.2%
I 1
 
6.2%
Other values (2) 2
12.5%
Common
ValueCountFrequency (%)
( 45
37.8%
) 45
37.8%
26
21.8%
4 1
 
0.8%
5 1
 
0.8%
& 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 639
82.6%
ASCII 135
 
17.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 62
 
9.7%
이 37
 
5.8%
사 24
 
3.8%
식 23
 
3.6%
스 22
 
3.4%
회 20
 
3.1%
리 12
 
1.9%
에 12
 
1.9%
아 10
 
1.6%
프 9
 
1.4%
Other values (192) 408
63.8%
ASCII
ValueCountFrequency (%)
( 45
33.3%
) 45
33.3%
26
19.3%
M 3
 
2.2%
B 2
 
1.5%
G 2
 
1.5%
4 1
 
0.7%
5 1
 
0.7%
S 1
 
0.7%
C 1
 
0.7%
Other values (8) 8
 
5.9%

최종수정일자
Date

UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
Minimum2004-06-18 00:00:00
Maximum2024-04-26 16:15:19
2024-05-11T00:41:31.162019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:31.577254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
I
69 
U
33 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 69
67.6%
U 33
32.4%

Length

2024-05-11T00:41:32.028295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:32.302137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 69
67.6%
u 33
32.4%

데이터갱신일자
Date

Distinct57
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:03:00
2024-05-11T00:41:32.630427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:33.037747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
건강기능식품유통전문판매업
102 

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 102
100.0%

Length

2024-05-11T00:41:33.581088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:33.885458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 102
100.0%

좌표정보(X)
Real number (ℝ)

Distinct73
Distinct (%)72.3%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean188578.68
Minimum184817.12
Maximum265468.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-11T00:41:34.229352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184817.12
5-th percentile185186.01
Q1187197.31
median188297.23
Q3188854.78
95-th percentile189042.5
Maximum265468.35
Range80651.231
Interquartile range (IQR)1657.4648

Descriptive statistics

Standard deviation7861.7732
Coefficient of variation (CV)0.041689619
Kurtosis94.068312
Mean188578.68
Median Absolute Deviation (MAD)655.83944
Skewness9.5338279
Sum19046446
Variance61807478
MonotonicityNot monotonic
2024-05-11T00:41:34.828190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188953.066831076 11
 
10.8%
188584.345447275 6
 
5.9%
188871.512837973 4
 
3.9%
187733.374753349 3
 
2.9%
187728.969922 2
 
2.0%
188673.621700524 2
 
2.0%
188831.750761554 2
 
2.0%
185093.846989196 2
 
2.0%
188493.762740612 2
 
2.0%
185741.39 2
 
2.0%
Other values (63) 65
63.7%
ValueCountFrequency (%)
184817.116668717 1
1.0%
184848.217797927 1
1.0%
184971.290324023 1
1.0%
185093.846989196 2
2.0%
185186.010706235 1
1.0%
185356.872847257 1
1.0%
185399.184692182 1
1.0%
185414.236203575 1
1.0%
185418.220336086 1
1.0%
185482.024322984 1
1.0%
ValueCountFrequency (%)
265468.347701022 1
 
1.0%
194301.304865904 1
 
1.0%
189415.269803933 1
 
1.0%
189151.208015925 1
 
1.0%
189042.496526196 2
 
2.0%
189020.44799481 1
 
1.0%
189011.488403267 1
 
1.0%
188953.066831076 11
10.8%
188879.448572755 1
 
1.0%
188871.512837973 4
 
3.9%

좌표정보(Y)
Real number (ℝ)

Distinct73
Distinct (%)72.3%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean447682.02
Minimum445205.66
Maximum484357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-11T00:41:35.447348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445205.66
5-th percentile445939.68
Q1446714.54
median447255.07
Q3447777.84
95-th percentile449388.05
Maximum484357
Range39151.336
Interquartile range (IQR)1063.2922

Descriptive statistics

Standard deviation3808.9481
Coefficient of variation (CV)0.0085081551
Kurtosis88.189273
Mean447682.02
Median Absolute Deviation (MAD)540.52691
Skewness9.0971657
Sum45215884
Variance14508086
MonotonicityNot monotonic
2024-05-11T00:41:36.096586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447333.569187997 11
 
10.8%
447255.070457495 6
 
5.9%
447348.13213342 4
 
3.9%
446695.979979397 3
 
2.9%
446595.053008998 2
 
2.0%
446914.537078345 2
 
2.0%
446527.594125122 2
 
2.0%
448837.877509607 2
 
2.0%
447213.539278579 2
 
2.0%
447168.274999999 2
 
2.0%
Other values (63) 65
63.7%
ValueCountFrequency (%)
445205.65952284 1
1.0%
445569.639465968 1
1.0%
445601.995865959 1
1.0%
445686.321341807 1
1.0%
445825.399064037 1
1.0%
445939.679152444 1
1.0%
446011.223154189 1
1.0%
446030.714521005 1
1.0%
446169.555330517 1
1.0%
446172.463078691 1
1.0%
ValueCountFrequency (%)
484356.995863933 1
1.0%
449649.016215774 1
1.0%
449418.483631523 1
1.0%
449390.943275 1
1.0%
449390.11431197 1
1.0%
449388.053900946 1
1.0%
449335.572121211 1
1.0%
449326.923464238 1
1.0%
449259.403232523 1
1.0%
449201.16645888 1
1.0%

위생업태명
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
건강기능식품유통전문판매업
70 
<NA>
32 

Length

Max length13
Median length13
Mean length10.176471
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 70
68.6%
<NA> 32
31.4%

Length

2024-05-11T00:41:36.922256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:37.210207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 70
68.6%
na 32
31.4%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
95 
0
 
7

Length

Max length4
Median length4
Mean length3.7941176
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 95
93.1%
0 7
 
6.9%

Length

2024-05-11T00:41:37.557244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:37.945920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
93.1%
0 7
 
6.9%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
95 
0
 
7

Length

Max length4
Median length4
Mean length3.7941176
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 95
93.1%
0 7
 
6.9%

Length

2024-05-11T00:41:38.639377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:39.109577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
93.1%
0 7
 
6.9%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing102
Missing (%)100.0%
Memory size1.0 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing102
Missing (%)100.0%
Memory size1.0 KiB

급수시설구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing100
Missing (%)98.0%
Memory size948.0 B
2024-05-11T00:41:39.426831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상수도전용
2nd row상수도전용
ValueCountFrequency (%)
상수도전용 2
100.0%
2024-05-11T00:41:40.408013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 2
20.0%
수 2
20.0%
도 2
20.0%
전 2
20.0%
용 2
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 2
20.0%
수 2
20.0%
도 2
20.0%
전 2
20.0%
용 2
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 2
20.0%
수 2
20.0%
도 2
20.0%
전 2
20.0%
용 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 2
20.0%
수 2
20.0%
도 2
20.0%
전 2
20.0%
용 2
20.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
96 
0
 
6

Length

Max length4
Median length4
Mean length3.8235294
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> 96
94.1%
0 6
 
5.9%

Length

2024-05-11T00:41:41.101777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:41.564373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 96
94.1%
0 6
 
5.9%

본사종업원수
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
66 
0
36 

Length

Max length4
Median length4
Mean length2.9411765
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 66
64.7%
0 36
35.3%

Length

2024-05-11T00:41:42.054025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:42.566278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 66
64.7%
0 36
35.3%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
66 
0
36 

Length

Max length4
Median length4
Mean length2.9411765
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 66
64.7%
0 36
35.3%

Length

2024-05-11T00:41:42.969183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:43.333631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 66
64.7%
0 36
35.3%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
66 
0
36 

Length

Max length4
Median length4
Mean length2.9411765
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 66
64.7%
0 36
35.3%

Length

2024-05-11T00:41:43.720840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:44.096499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 66
64.7%
0 36
35.3%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
66 
0
36 

Length

Max length4
Median length4
Mean length2.9411765
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 66
64.7%
0 36
35.3%

Length

2024-05-11T00:41:44.596444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:44.971953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 66
64.7%
0 36
35.3%

건물소유구분명
Categorical

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
58 
임대
24 
자가
20 

Length

Max length4
Median length4
Mean length3.1372549
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 58
56.9%
임대 24
23.5%
자가 20
 
19.6%

Length

2024-05-11T00:41:45.370745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:45.873467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
56.9%
임대 24
23.5%
자가 20
 
19.6%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
85 
0
16 
10000000
 
1

Length

Max length8
Median length4
Mean length3.5686275
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 85
83.3%
0 16
 
15.7%
10000000 1
 
1.0%

Length

2024-05-11T00:41:46.344653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:46.792392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 85
83.3%
0 16
 
15.7%
10000000 1
 
1.0%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
<NA>
85 
0
16 
750000
 
1

Length

Max length6
Median length4
Mean length3.5490196
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 85
83.3%
0 16
 
15.7%
750000 1
 
1.0%

Length

2024-05-11T00:41:47.196931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:47.555725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 85
83.3%
0 16
 
15.7%
750000 1
 
1.0%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.4%
Missing32
Missing (%)31.4%
Memory size336.0 B
False
70 
(Missing)
32 
ValueCountFrequency (%)
False 70
68.6%
(Missing) 32
31.4%
2024-05-11T00:41:48.105927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)12.9%
Missing32
Missing (%)31.4%
Infinite0
Infinite (%)0.0%
Mean8.2231429
Minimum0
Maximum215
Zeros62
Zeros (%)60.8%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-11T00:41:48.365716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile51.2715
Maximum215
Range215
Interquartile range (IQR)0

Descriptive statistics

Standard deviation31.258098
Coefficient of variation (CV)3.801235
Kurtosis30.012921
Mean8.2231429
Median Absolute Deviation (MAD)0
Skewness5.1623118
Sum575.62
Variance977.06872
MonotonicityNot monotonic
2024-05-11T00:41:48.673662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 62
60.8%
66.0 1
 
1.0%
119.75 1
 
1.0%
32.34 1
 
1.0%
51.33 1
 
1.0%
28.0 1
 
1.0%
12.0 1
 
1.0%
215.0 1
 
1.0%
51.2 1
 
1.0%
(Missing) 32
31.4%
ValueCountFrequency (%)
0.0 62
60.8%
12.0 1
 
1.0%
28.0 1
 
1.0%
32.34 1
 
1.0%
51.2 1
 
1.0%
51.33 1
 
1.0%
66.0 1
 
1.0%
119.75 1
 
1.0%
215.0 1
 
1.0%
ValueCountFrequency (%)
215.0 1
 
1.0%
119.75 1
 
1.0%
66.0 1
 
1.0%
51.33 1
 
1.0%
51.2 1
 
1.0%
32.34 1
 
1.0%
28.0 1
 
1.0%
12.0 1
 
1.0%
0.0 62
60.8%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing102
Missing (%)100.0%
Memory size1.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing102
Missing (%)100.0%
Memory size1.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing102
Missing (%)100.0%
Memory size1.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031400003140000-135-2004-0000120040407<NA>3폐업2폐업20170925<NA><NA><NA>0226583652<NA>158850서울특별시 양천구 신정동 ***-***번지 (지상*층)서울특별시 양천구 목동남로*길 ** (신정동,(지상*층))8104해외개발(주)2017-09-25 15:01:28I2018-08-31 23:59:59.0건강기능식품유통전문판매업188183.910851445205.659523건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
131400003140000-135-2004-0000220040609<NA>3폐업2폐업20190905<NA><NA><NA>0226435644<NA>158818서울특별시 양천구 목동 ***-**번지 *층서울특별시 양천구 목동중앙서로 ** (목동,*층)7964전국농산물유통상사2019-09-05 14:16:52U2019-09-07 02:40:00.0건강기능식품유통전문판매업188128.60919447857.55058건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
231400003140000-135-2004-0000320040614<NA>3폐업2폐업20080728<NA><NA><NA>0226486835<NA>158815서울특별시 양천구 목동 ***-**번지<NA><NA>노블라이프2007-03-07 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업188297.227392448528.513536건강기능식품유통전문판매업00<NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
331400003140000-135-2004-0000420040617<NA>3폐업2폐업20151207<NA><NA><NA>0221677791<NA>158806서울특별시 양천구 목동 ***-***번지 *층서울특별시 양천구 오목로 *** (목동, *층)8006소망화장품(주)2014-09-30 15:38:04I2018-08-31 23:59:59.0건강기능식품유통전문판매업188854.777756446887.247767건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
431400003140000-135-2004-0000520040618<NA>3폐업2폐업20101202<NA><NA><NA>0226963832<NA>158827서울특별시 양천구 신월동 ***-**번지 *층<NA><NA>청산유통2004-09-03 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업185356.872847448099.895949건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
531400003140000-135-2004-0000620040618<NA>3폐업2폐업20110822<NA><NA><NA>0226049280<NA>158833서울특별시 양천구 신월동 ***-**번지 서륭타운 ***-*호<NA><NA>그린무역2004-06-18 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업185756.491474446614.298655건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
631400003140000-135-2004-0000720040701<NA>3폐업2폐업20171023<NA><NA><NA>0220659814<NA>158838서울특별시 양천구 신월동 ***-**번지 로즈가든***서울특별시 양천구 신월로 *** (신월동,로즈가든***)8028(주)동화고객감동2017-10-23 15:54:38I2018-08-31 23:59:59.0건강기능식품유통전문판매업186764.573882446714.543551건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
731400003140000-135-2004-0000820040713<NA>3폐업2폐업20070411<NA><NA><NA>0221667883<NA>158806서울특별시 양천구 목동 ***-***번지 *층<NA><NA>소망라이프(주)2005-03-25 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업188854.777756446887.247767건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
831400003140000-135-2004-0000920040827<NA>3폐업2폐업20180110<NA><NA><NA>0226548414<NA>158852서울특별시 양천구 신정동 ***-*번지 *층서울특별시 양천구 신목로 ** (신정동,*층)8017(주)케이지유2018-01-10 17:37:37I2018-08-31 23:59:59.0건강기능식품유통전문판매업188827.890646446169.555331건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
931400003140000-135-2004-0001020040921<NA>3폐업2폐업20180206<NA><NA><NA>0226481870<NA>158050서울특별시 양천구 목동 ***-**번지 현대드림타워 ****호서울특별시 양천구 목동동로 ***-* (목동,현대드림타워 ****호)7995아이비푸드(주)2018-02-06 14:10:17I2018-08-31 23:59:59.0건강기능식품유통전문판매업188584.345447447255.070457건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
9231400003140000-135-2023-000022023-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-050서울특별시 양천구 목동 *** 신한이모르젠서울특별시 양천구 목동중앙북로 *, *층 ***호 (목동, 신한이모르젠)7946생기보력2023-04-03 14:41:47I2022-12-04 00:05:00.0건강기능식품유통전문판매업187955.121455449649.016216<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9331400003140000-135-2023-000032023-05-24<NA>1영업/정상1영업<NA><NA><NA><NA>02264880900.0158-861서울특별시 양천구 신정동 ****-* 남부빌딩서울특별시 양천구 은행정로*길 **, 남부빌딩 *,*층 (신정동)8087주식회사 갓생2023-05-24 11:28:08I2022-12-04 22:06:00.0건강기능식품유통전문판매업187728.969922446595.053009<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9431400003140000-135-2023-000042023-06-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-806서울특별시 양천구 목동 ***-***서울특별시 양천구 오목로 ***-*, *층 ***호 (목동)8005케이에이치헬스케어2023-06-30 10:26:14I2022-12-07 00:02:00.0건강기능식품유통전문판매업188673.621701446914.537078<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9531400003140000-135-2023-000052023-07-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.0158-090서울특별시 양천구 신월동 **** 신도신월*차아파트서울특별시 양천구 신월로**길 **, ***동 ****호 (신월동, 신도신월*차아파트)8061조이 인셀덤2023-07-21 10:17:47I2022-12-06 22:03:00.0건강기능식품유통전문판매업186357.175917446213.732643<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9631400003140000-135-2023-000062023-08-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-090서울특별시 양천구 신월동 **** 동도 센트리움 아파트서울특별시 양천구 오목로**길 *, ***동 ***호 (신월동, 동도 센트리움 아파트)7935케이케이 트레이딩2023-08-16 16:34:49I2022-12-07 23:08:00.0건강기능식품유통전문판매업186347.225849446845.380484<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9731400003140000-135-2023-000072023-08-29<NA>1영업/정상1영업<NA><NA><NA><NA>02323192456.73158-807서울특별시 양천구 목동 ***-* 신화타워아파트서울특별시 양천구 목동중앙북로 **, *층 ***호 (목동, 신화타워아파트)7949주식회사 더원쇼핑2023-08-29 13:43:55I2022-12-07 21:01:00.0건강기능식품유통전문판매업188417.626362449418.483632<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9831400003140000-135-2023-000082023-09-05<NA>3폐업2폐업2023-09-05<NA><NA><NA><NA>0.0158-858서울특별시 양천구 신정동 ***-** 로즈가든서울특별시 양천구 오목로**길 * (신정동, 로즈가든)7943리송송2023-09-05 20:10:32I2022-12-09 00:07:00.0건강기능식품유통전문판매업187197.313003447029.760381<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9931400003140000-135-2024-000012024-02-02<NA>3폐업2폐업2024-03-19<NA><NA><NA><NA><NA>158-766서울특별시 양천구 목동 *** 목동트라팰리스서울특별시 양천구 오목로 ***, *층 (목동, 목동트라팰리스)8001지큐브스페이스주식회사(주) 목동점2024-03-19 16:37:52U2023-12-02 22:01:00.0건강기능식품유통전문판매업188472.759197447091.855964<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
10031400003140000-135-2024-000022024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-856서울특별시 양천구 신정동 ***-*서울특별시 양천구 신정중앙로 **, *층 **호 (신정동)7938블립2024-04-19 09:49:02I2023-12-03 22:01:00.0건강기능식품유통전문판매업187587.553793447206.02622<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
10131400003140000-135-2024-000032024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-861서울특별시 양천구 신정동 ****-* 남부빌딩서울특별시 양천구 은행정로*길 **, 남부빌딩 ***-*호 (신정동)8087주식회사 스테디스트2024-04-26 16:15:19I2023-12-03 22:08:00.0건강기능식품유통전문판매업187728.969922446595.053009<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>