Overview

Dataset statistics

Number of variables44
Number of observations76
Missing cells817
Missing cells (%)24.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.2 KiB
Average record size in memory379.7 B

Variable types

Categorical20
Text6
DateTime4
Unsupported9
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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-18058/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (55.7%)Imbalance
여성종사자수 is highly imbalanced (55.7%)Imbalance
급수시설구분명 is highly imbalanced (60.2%)Imbalance
총인원 is highly imbalanced (60.2%)Imbalance
보증액 is highly imbalanced (56.2%)Imbalance
월세액 is highly imbalanced (56.2%)Imbalance
인허가취소일자 has 76 (100.0%) missing valuesMissing
폐업일자 has 24 (31.6%) missing valuesMissing
휴업시작일자 has 76 (100.0%) missing valuesMissing
휴업종료일자 has 76 (100.0%) missing valuesMissing
재개업일자 has 76 (100.0%) missing valuesMissing
전화번호 has 28 (36.8%) missing valuesMissing
소재지면적 has 37 (48.7%) missing valuesMissing
도로명주소 has 11 (14.5%) missing valuesMissing
도로명우편번호 has 11 (14.5%) missing valuesMissing
영업장주변구분명 has 76 (100.0%) missing valuesMissing
등급구분명 has 76 (100.0%) missing valuesMissing
다중이용업소여부 has 22 (28.9%) missing valuesMissing
전통업소지정번호 has 76 (100.0%) missing valuesMissing
전통업소주된음식 has 76 (100.0%) missing valuesMissing
홈페이지 has 76 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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 2 (2.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:44:07.060274
Analysis finished2024-05-11 06:44:07.827535
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
3060000
76 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 76
100.0%

Length

2024-05-11T15:44:07.927931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:08.067278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 76
100.0%

관리번호
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2024-05-11T15:44:08.291315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1672
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

Unique76 ?
Unique (%)100.0%

Sample

1st row3060000-135-2004-00001
2nd row3060000-135-2004-00002
3rd row3060000-135-2004-00003
4th row3060000-135-2004-00004
5th row3060000-135-2004-00005
ValueCountFrequency (%)
3060000-135-2004-00001 1
 
1.3%
3060000-135-2017-00002 1
 
1.3%
3060000-135-2020-00002 1
 
1.3%
3060000-135-2020-00001 1
 
1.3%
3060000-135-2019-00004 1
 
1.3%
3060000-135-2019-00003 1
 
1.3%
3060000-135-2019-00002 1
 
1.3%
3060000-135-2019-00001 1
 
1.3%
3060000-135-2018-00002 1
 
1.3%
3060000-135-2004-00002 1
 
1.3%
Other values (66) 66
86.8%
2024-05-11T15:44:08.727657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 796
47.6%
- 228
 
13.6%
3 172
 
10.3%
1 131
 
7.8%
2 119
 
7.1%
5 93
 
5.6%
6 86
 
5.1%
4 30
 
1.8%
8 7
 
0.4%
9 5
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1444
86.4%
Dash Punctuation 228
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 796
55.1%
3 172
 
11.9%
1 131
 
9.1%
2 119
 
8.2%
5 93
 
6.4%
6 86
 
6.0%
4 30
 
2.1%
8 7
 
0.5%
9 5
 
0.3%
7 5
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1672
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 796
47.6%
- 228
 
13.6%
3 172
 
10.3%
1 131
 
7.8%
2 119
 
7.1%
5 93
 
5.6%
6 86
 
5.1%
4 30
 
1.8%
8 7
 
0.4%
9 5
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 796
47.6%
- 228
 
13.6%
3 172
 
10.3%
1 131
 
7.8%
2 119
 
7.1%
5 93
 
5.6%
6 86
 
5.1%
4 30
 
1.8%
8 7
 
0.4%
9 5
 
0.3%

인허가일자
Date

Distinct73
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum2004-04-13 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T15:44:08.907583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:44:09.085988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing76
Missing (%)100.0%
Memory size816.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
3
52 
1
24 

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 52
68.4%
1 24
31.6%

Length

2024-05-11T15:44:09.299804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:09.519408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 52
68.4%
1 24
31.6%

영업상태명
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
폐업
52 
영업/정상
24 

Length

Max length5
Median length2
Mean length2.9473684
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 52
68.4%
영업/정상 24
31.6%

Length

2024-05-11T15:44:10.007447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:10.155364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
68.4%
영업/정상 24
31.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
2
52 
1
24 

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 52
68.4%
1 24
31.6%

Length

2024-05-11T15:44:10.305058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:10.458738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 52
68.4%
1 24
31.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
폐업
52 
영업
24 

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 52
68.4%
영업 24
31.6%

Length

2024-05-11T15:44:10.622494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:10.788395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
68.4%
영업 24
31.6%

폐업일자
Date

MISSING 

Distinct50
Distinct (%)96.2%
Missing24
Missing (%)31.6%
Memory size740.0 B
Minimum2004-12-29 00:00:00
Maximum2023-11-28 00:00:00
2024-05-11T15:44:10.946308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:44:11.185432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing76
Missing (%)100.0%
Memory size816.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing76
Missing (%)100.0%
Memory size816.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing76
Missing (%)100.0%
Memory size816.0 B

전화번호
Text

MISSING 

Distinct45
Distinct (%)93.8%
Missing28
Missing (%)36.8%
Memory size740.0 B
2024-05-11T15:44:11.515904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.75
Min length7

Characters and Unicode

Total characters516
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

Unique42 ?
Unique (%)87.5%

Sample

1st row02 20945800
2nd row02 4384461
3rd row02 9767588
4th row02 4940572
5th row02 4334472
ValueCountFrequency (%)
02 34
36.2%
496 3
 
3.2%
8776 2
 
2.1%
462 2
 
2.1%
4476 2
 
2.1%
20945800 2
 
2.1%
22209500 1
 
1.1%
1076 1
 
1.1%
02495 1
 
1.1%
1199 1
 
1.1%
Other values (45) 45
47.9%
2024-05-11T15:44:12.120726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 94
18.2%
2 81
15.7%
64
12.4%
4 58
11.2%
7 42
8.1%
8 38
7.4%
9 37
 
7.2%
6 31
 
6.0%
3 30
 
5.8%
1 25
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 452
87.6%
Space Separator 64
 
12.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 94
20.8%
2 81
17.9%
4 58
12.8%
7 42
9.3%
8 38
8.4%
9 37
 
8.2%
6 31
 
6.9%
3 30
 
6.6%
1 25
 
5.5%
5 16
 
3.5%
Space Separator
ValueCountFrequency (%)
64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 516
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 94
18.2%
2 81
15.7%
64
12.4%
4 58
11.2%
7 42
8.1%
8 38
7.4%
9 37
 
7.2%
6 31
 
6.0%
3 30
 
5.8%
1 25
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 94
18.2%
2 81
15.7%
64
12.4%
4 58
11.2%
7 42
8.1%
8 38
7.4%
9 37
 
7.2%
6 31
 
6.0%
3 30
 
5.8%
1 25
 
4.8%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct28
Distinct (%)71.8%
Missing37
Missing (%)48.7%
Infinite0
Infinite (%)0.0%
Mean59.241026
Minimum0
Maximum200
Zeros2
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-05-11T15:44:12.418370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.97
Q125
median36
Q380.015
95-th percentile188.496
Maximum200
Range200
Interquartile range (IQR)55.015

Descriptive statistics

Standard deviation52.719539
Coefficient of variation (CV)0.88991604
Kurtosis1.4231425
Mean59.241026
Median Absolute Deviation (MAD)26
Skewness1.3633428
Sum2310.4
Variance2779.3498
MonotonicityNot monotonic
2024-05-11T15:44:12.619158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
33.0 5
 
6.6%
60.0 3
 
3.9%
10.0 3
 
3.9%
0.0 2
 
2.6%
30.0 2
 
2.6%
132.0 2
 
2.6%
89.06 1
 
1.3%
198.0 1
 
1.3%
66.0 1
 
1.3%
45.36 1
 
1.3%
Other values (18) 18
23.7%
(Missing) 37
48.7%
ValueCountFrequency (%)
0.0 2
 
2.6%
3.3 1
 
1.3%
10.0 3
3.9%
15.0 1
 
1.3%
16.0 1
 
1.3%
18.0 1
 
1.3%
20.0 1
 
1.3%
30.0 2
 
2.6%
33.0 5
6.6%
33.06 1
 
1.3%
ValueCountFrequency (%)
200.0 1
1.3%
198.0 1
1.3%
187.44 1
1.3%
132.0 2
2.6%
108.9 1
1.3%
100.0 1
1.3%
99.0 1
1.3%
89.06 1
1.3%
85.49 1
1.3%
74.54 1
1.3%

소재지우편번호
Text

Distinct46
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Memory size740.0 B
2024-05-11T15:44:12.947898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2368421
Min length6

Characters and Unicode

Total characters474
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

Unique35 ?
Unique (%)46.1%

Sample

1st row131863
2nd row131875
3rd row131878
4th row131859
5th row131859
ValueCountFrequency (%)
131824 9
 
11.8%
131859 7
 
9.2%
131-865 6
 
7.9%
131802 4
 
5.3%
131880 3
 
3.9%
131806 2
 
2.6%
131-848 2
 
2.6%
131881 2
 
2.6%
131846 2
 
2.6%
131853 2
 
2.6%
Other values (36) 37
48.7%
2024-05-11T15:44:13.513689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 160
33.8%
8 90
19.0%
3 87
18.4%
2 24
 
5.1%
5 24
 
5.1%
- 18
 
3.8%
4 17
 
3.6%
6 16
 
3.4%
0 16
 
3.4%
9 12
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 456
96.2%
Dash Punctuation 18
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 160
35.1%
8 90
19.7%
3 87
19.1%
2 24
 
5.3%
5 24
 
5.3%
4 17
 
3.7%
6 16
 
3.5%
0 16
 
3.5%
9 12
 
2.6%
7 10
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 474
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 160
33.8%
8 90
19.0%
3 87
18.4%
2 24
 
5.1%
5 24
 
5.1%
- 18
 
3.8%
4 17
 
3.6%
6 16
 
3.4%
0 16
 
3.4%
9 12
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 474
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 160
33.8%
8 90
19.0%
3 87
18.4%
2 24
 
5.1%
5 24
 
5.1%
- 18
 
3.8%
4 17
 
3.6%
6 16
 
3.4%
0 16
 
3.4%
9 12
 
2.5%

지번주소
Text

Distinct58
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
2024-05-11T15:44:13.824970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30.5
Mean length24.407895
Min length18

Characters and Unicode

Total characters1855
Distinct characters83
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

Unique48 ?
Unique (%)63.2%

Sample

1st row서울특별시 중랑구 상봉동 ***번지 신내테크노타운 *층
2nd row서울특별시 중랑구 중화동 ***-*번지 지하*층
3rd row서울특별시 중랑구 중화동 ***-*번지 가나안빌딩***호
4th row서울특별시 중랑구 상봉동 **-*번지
5th row서울특별시 중랑구 상봉동 ***-* 대상빌딩 *층
ValueCountFrequency (%)
서울특별시 76
21.3%
중랑구 76
21.3%
번지 43
12.1%
33
9.3%
면목동 18
 
5.1%
상봉동 14
 
3.9%
묵동 14
 
3.9%
층 13
 
3.7%
중화동 12
 
3.4%
망우동 11
 
3.1%
Other values (29) 46
12.9%
2024-05-11T15:44:14.445760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 387
20.9%
331
17.8%
중 88
 
4.7%
동 79
 
4.3%
시 77
 
4.2%
서 76
 
4.1%
구 76
 
4.1%
울 76
 
4.1%
랑 76
 
4.1%
별 76
 
4.1%
Other values (73) 513
27.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1057
57.0%
Other Punctuation 387
 
20.9%
Space Separator 331
 
17.8%
Dash Punctuation 68
 
3.7%
Lowercase Letter 6
 
0.3%
Uppercase Letter 4
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 88
 
8.3%
동 79
 
7.5%
시 77
 
7.3%
서 76
 
7.2%
구 76
 
7.2%
울 76
 
7.2%
랑 76
 
7.2%
별 76
 
7.2%
특 76
 
7.2%
지 47
 
4.4%
Other values (59) 310
29.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
r 1
16.7%
n 1
16.7%
t 1
16.7%
c 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
S 1
25.0%
K 1
25.0%
V 1
25.0%
Other Punctuation
ValueCountFrequency (%)
* 387
100.0%
Space Separator
ValueCountFrequency (%)
331
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1057
57.0%
Common 788
42.5%
Latin 10
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 88
 
8.3%
동 79
 
7.5%
시 77
 
7.3%
서 76
 
7.2%
구 76
 
7.2%
울 76
 
7.2%
랑 76
 
7.2%
별 76
 
7.2%
특 76
 
7.2%
지 47
 
4.4%
Other values (59) 310
29.3%
Latin
ValueCountFrequency (%)
e 2
20.0%
r 1
10.0%
n 1
10.0%
t 1
10.0%
c 1
10.0%
B 1
10.0%
S 1
10.0%
K 1
10.0%
V 1
10.0%
Common
ValueCountFrequency (%)
* 387
49.1%
331
42.0%
- 68
 
8.6%
( 1
 
0.1%
) 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1057
57.0%
ASCII 798
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 387
48.5%
331
41.5%
- 68
 
8.5%
e 2
 
0.3%
r 1
 
0.1%
( 1
 
0.1%
n 1
 
0.1%
t 1
 
0.1%
) 1
 
0.1%
c 1
 
0.1%
Other values (4) 4
 
0.5%
Hangul
ValueCountFrequency (%)
중 88
 
8.3%
동 79
 
7.5%
시 77
 
7.3%
서 76
 
7.2%
구 76
 
7.2%
울 76
 
7.2%
랑 76
 
7.2%
별 76
 
7.2%
특 76
 
7.2%
지 47
 
4.4%
Other values (59) 310
29.3%

도로명주소
Text

MISSING 

Distinct62
Distinct (%)95.4%
Missing11
Missing (%)14.5%
Memory size740.0 B
2024-05-11T15:44:14.846117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length33
Min length23

Characters and Unicode

Total characters2145
Distinct characters114
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

Unique60 ?
Unique (%)92.3%

Sample

1st row서울특별시 중랑구 봉화산로 *** (상봉동,신내테크노타운 *층)
2nd row서울특별시 중랑구 면목로 *** (상봉동, 대상빌딩 *층)
3rd row서울특별시 중랑구 동일로 *** (면목동,화성빌딩 지층)
4th row서울특별시 중랑구 용마산로***길 * (망우동,(***호))
5th row서울특별시 중랑구 봉화산로*길 ** (중화동)
ValueCountFrequency (%)
67
15.8%
서울특별시 65
15.4%
중랑구 65
15.4%
층 27
 
6.4%
호 21
 
5.0%
상봉동 11
 
2.6%
면목동 11
 
2.6%
망우동 10
 
2.4%
묵동 9
 
2.1%
중화동 8
 
1.9%
Other values (73) 129
30.5%
2024-05-11T15:44:15.521564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
358
16.7%
* 350
16.3%
동 86
 
4.0%
중 78
 
3.6%
, 71
 
3.3%
랑 69
 
3.2%
시 67
 
3.1%
) 66
 
3.1%
( 66
 
3.1%
서 65
 
3.0%
Other values (104) 869
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1202
56.0%
Other Punctuation 421
 
19.6%
Space Separator 358
 
16.7%
Close Punctuation 66
 
3.1%
Open Punctuation 66
 
3.1%
Dash Punctuation 14
 
0.7%
Uppercase Letter 12
 
0.6%
Lowercase Letter 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 86
 
7.2%
중 78
 
6.5%
랑 69
 
5.7%
시 67
 
5.6%
서 65
 
5.4%
울 65
 
5.4%
특 65
 
5.4%
별 65
 
5.4%
구 65
 
5.4%
로 65
 
5.4%
Other values (85) 512
42.6%
Uppercase Letter
ValueCountFrequency (%)
B 4
33.3%
R 2
16.7%
S 1
 
8.3%
K 1
 
8.3%
V 1
 
8.3%
D 1
 
8.3%
E 1
 
8.3%
A 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
c 1
16.7%
n 1
16.7%
t 1
16.7%
r 1
16.7%
Other Punctuation
ValueCountFrequency (%)
* 350
83.1%
, 71
 
16.9%
Space Separator
ValueCountFrequency (%)
358
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1202
56.0%
Common 925
43.1%
Latin 18
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 86
 
7.2%
중 78
 
6.5%
랑 69
 
5.7%
시 67
 
5.6%
서 65
 
5.4%
울 65
 
5.4%
특 65
 
5.4%
별 65
 
5.4%
구 65
 
5.4%
로 65
 
5.4%
Other values (85) 512
42.6%
Latin
ValueCountFrequency (%)
B 4
22.2%
e 2
11.1%
R 2
11.1%
S 1
 
5.6%
K 1
 
5.6%
V 1
 
5.6%
c 1
 
5.6%
n 1
 
5.6%
t 1
 
5.6%
r 1
 
5.6%
Other values (3) 3
16.7%
Common
ValueCountFrequency (%)
358
38.7%
* 350
37.8%
, 71
 
7.7%
) 66
 
7.1%
( 66
 
7.1%
- 14
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1202
56.0%
ASCII 943
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
358
38.0%
* 350
37.1%
, 71
 
7.5%
) 66
 
7.0%
( 66
 
7.0%
- 14
 
1.5%
B 4
 
0.4%
e 2
 
0.2%
R 2
 
0.2%
S 1
 
0.1%
Other values (9) 9
 
1.0%
Hangul
ValueCountFrequency (%)
동 86
 
7.2%
중 78
 
6.5%
랑 69
 
5.7%
시 67
 
5.6%
서 65
 
5.4%
울 65
 
5.4%
특 65
 
5.4%
별 65
 
5.4%
구 65
 
5.4%
로 65
 
5.4%
Other values (85) 512
42.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)69.2%
Missing11
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean2107.9692
Minimum2004
Maximum2262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-05-11T15:44:15.800618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2004
5-th percentile2010.4
Q12048
median2127
Q32154
95-th percentile2216.8
Maximum2262
Range258
Interquartile range (IQR)106

Descriptive statistics

Standard deviation66.742736
Coefficient of variation (CV)0.031662102
Kurtosis-0.73863614
Mean2107.9692
Median Absolute Deviation (MAD)49
Skewness0.12714966
Sum137018
Variance4454.5928
MonotonicityNot monotonic
2024-05-11T15:44:16.047984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
2132 5
 
6.6%
2154 4
 
5.3%
2076 3
 
3.9%
2176 3
 
3.9%
2127 3
 
3.9%
2103 2
 
2.6%
2055 2
 
2.6%
2148 2
 
2.6%
2188 2
 
2.6%
2086 2
 
2.6%
Other values (35) 37
48.7%
(Missing) 11
 
14.5%
ValueCountFrequency (%)
2004 1
1.3%
2006 1
1.3%
2010 2
2.6%
2012 1
1.3%
2015 1
1.3%
2016 1
1.3%
2017 2
2.6%
2021 1
1.3%
2022 1
1.3%
2030 1
1.3%
ValueCountFrequency (%)
2262 1
 
1.3%
2252 1
 
1.3%
2236 1
 
1.3%
2224 1
 
1.3%
2188 2
2.6%
2183 1
 
1.3%
2181 1
 
1.3%
2176 3
3.9%
2175 1
 
1.3%
2163 1
 
1.3%

사업장명
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2024-05-11T15:44:16.487751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length7.4473684
Min length3

Characters and Unicode

Total characters566
Distinct characters182
Distinct categories7 ?
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 (%)100.0%

Sample

1st row(주)늘푸른유통
2nd row가람인터내셔날
3rd row(주)바이오젠코리아
4th row헬스엠(주)
5th row대상(주)건강사업본부
ValueCountFrequency (%)
주식회사 11
 
11.6%
씨엠솔나라 2
 
2.1%
가람인터내셔날 1
 
1.1%
바이오 1
 
1.1%
케앤지(kng)산삼 1
 
1.1%
리얼리프이앤아이 1
 
1.1%
쌘언니 1
 
1.1%
낫자닷컴 1
 
1.1%
비알엠바이오 1
 
1.1%
포미바이오 1
 
1.1%
Other values (74) 74
77.9%
2024-05-11T15:44:17.157232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 40
 
7.1%
( 32
 
5.7%
) 32
 
5.7%
이 31
 
5.5%
19
 
3.4%
사 16
 
2.8%
스 16
 
2.8%
식 12
 
2.1%
회 11
 
1.9%
리 10
 
1.8%
Other values (172) 347
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 461
81.4%
Open Punctuation 32
 
5.7%
Close Punctuation 32
 
5.7%
Space Separator 19
 
3.4%
Uppercase Letter 10
 
1.8%
Lowercase Letter 10
 
1.8%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 40
 
8.7%
이 31
 
6.7%
사 16
 
3.5%
스 16
 
3.5%
식 12
 
2.6%
회 11
 
2.4%
리 10
 
2.2%
오 10
 
2.2%
에 9
 
2.0%
아 9
 
2.0%
Other values (151) 297
64.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
20.0%
K 2
20.0%
N 1
10.0%
P 1
10.0%
G 1
10.0%
H 1
10.0%
O 1
10.0%
I 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
i 2
20.0%
n 2
20.0%
l 1
10.0%
t 1
10.0%
d 1
10.0%
e 1
10.0%
a 1
10.0%
o 1
10.0%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
6 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 461
81.4%
Common 85
 
15.0%
Latin 20
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 40
 
8.7%
이 31
 
6.7%
사 16
 
3.5%
스 16
 
3.5%
식 12
 
2.6%
회 11
 
2.4%
리 10
 
2.2%
오 10
 
2.2%
에 9
 
2.0%
아 9
 
2.0%
Other values (151) 297
64.4%
Latin
ValueCountFrequency (%)
B 2
 
10.0%
K 2
 
10.0%
i 2
 
10.0%
n 2
 
10.0%
N 1
 
5.0%
l 1
 
5.0%
t 1
 
5.0%
d 1
 
5.0%
e 1
 
5.0%
a 1
 
5.0%
Other values (6) 6
30.0%
Common
ValueCountFrequency (%)
( 32
37.6%
) 32
37.6%
19
22.4%
3 1
 
1.2%
6 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 461
81.4%
ASCII 105
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 40
 
8.7%
이 31
 
6.7%
사 16
 
3.5%
스 16
 
3.5%
식 12
 
2.6%
회 11
 
2.4%
리 10
 
2.2%
오 10
 
2.2%
에 9
 
2.0%
아 9
 
2.0%
Other values (151) 297
64.4%
ASCII
ValueCountFrequency (%)
( 32
30.5%
) 32
30.5%
19
18.1%
B 2
 
1.9%
K 2
 
1.9%
i 2
 
1.9%
n 2
 
1.9%
N 1
 
1.0%
l 1
 
1.0%
t 1
 
1.0%
Other values (11) 11
 
10.5%

최종수정일자
Date

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum2004-04-13 00:00:00
Maximum2024-05-03 13:49:26
2024-05-11T15:44:17.412591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:44:17.654986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
I
51 
U
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 51
67.1%
U 25
32.9%

Length

2024-05-11T15:44:17.893032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:18.070177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 51
67.1%
u 25
32.9%

데이터갱신일자
Date

Distinct39
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T15:44:18.244474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:44:18.442843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
건강기능식품유통전문판매업
76 

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 76
100.0%

Length

2024-05-11T15:44:18.699548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:18.853030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 76
100.0%

좌표정보(X)
Real number (ℝ)

Distinct59
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean207446.86
Minimum206419.75
Maximum209856.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-05-11T15:44:19.018893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206419.75
5-th percentile206448.31
Q1206775.2
median207234.58
Q3208124.77
95-th percentile208903.52
Maximum209856.12
Range3436.366
Interquartile range (IQR)1349.5709

Descriptive statistics

Standard deviation861.90421
Coefficient of variation (CV)0.0041548192
Kurtosis-0.33098286
Mean207446.86
Median Absolute Deviation (MAD)554.86525
Skewness0.74603096
Sum15765962
Variance742878.86
MonotonicityNot monotonic
2024-05-11T15:44:19.265888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206448.314200373 5
 
6.6%
207590.031147049 4
 
5.3%
208295.099818379 3
 
3.9%
206463.443740034 3
 
3.9%
208581.951105745 2
 
2.6%
208842.713556665 2
 
2.6%
206821.108967706 2
 
2.6%
206956.392278972 2
 
2.6%
206804.57585151 2
 
2.6%
209085.926142332 2
 
2.6%
Other values (49) 49
64.5%
ValueCountFrequency (%)
206419.750099001 1
 
1.3%
206448.314200373 5
6.6%
206463.443740034 3
3.9%
206472.310820027 1
 
1.3%
206490.785290292 1
 
1.3%
206541.220027071 1
 
1.3%
206566.844957559 1
 
1.3%
206567.427928044 1
 
1.3%
206670.831526915 1
 
1.3%
206682.913960529 1
 
1.3%
ValueCountFrequency (%)
209856.1161416 1
1.3%
209475.230649494 1
1.3%
209085.926142332 2
2.6%
208842.713556665 2
2.6%
208833.579870232 1
1.3%
208812.481157845 1
1.3%
208764.403577945 1
1.3%
208581.951105745 2
2.6%
208490.019432559 1
1.3%
208310.254611281 1
1.3%

좌표정보(Y)
Real number (ℝ)

Distinct59
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean455135.24
Minimum452081.67
Maximum457462.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-05-11T15:44:19.520042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452081.67
5-th percentile453364.31
Q1454259.26
median455126.12
Q3455944.68
95-th percentile457220.31
Maximum457462.77
Range5381.1003
Interquartile range (IQR)1685.4202

Descriptive statistics

Standard deviation1132.7765
Coefficient of variation (CV)0.0024888789
Kurtosis-0.10203498
Mean455135.24
Median Absolute Deviation (MAD)870.16355
Skewness0.015895979
Sum34590278
Variance1283182.6
MonotonicityNot monotonic
2024-05-11T15:44:19.788507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454078.749529697 5
 
6.6%
454599.632823069 4
 
5.3%
456014.999180519 3
 
3.9%
454151.215335609 3
 
3.9%
454249.349207815 2
 
2.6%
455205.504339797 2
 
2.6%
456096.359567266 2
 
2.6%
455196.971910524 2
 
2.6%
455570.897293619 2
 
2.6%
457283.215342184 2
 
2.6%
Other values (49) 49
64.5%
ValueCountFrequency (%)
452081.666398687 1
 
1.3%
452870.127321316 1
 
1.3%
452952.386171853 1
 
1.3%
453074.476763597 1
 
1.3%
453460.919335911 1
 
1.3%
453594.509785172 1
 
1.3%
453943.415358175 1
 
1.3%
454078.749529697 5
6.6%
454151.215335609 3
3.9%
454213.759698731 1
 
1.3%
ValueCountFrequency (%)
457462.766652935 1
1.3%
457370.707767405 1
1.3%
457283.215342184 2
2.6%
457199.343836097 1
1.3%
456889.880188471 1
1.3%
456761.921129526 1
1.3%
456686.933363648 1
1.3%
456666.569490725 1
1.3%
456604.826307224 1
1.3%
456472.216329929 1
1.3%

위생업태명
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
건강기능식품유통전문판매업
54 
<NA>
22 

Length

Max length13
Median length13
Mean length10.394737
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 54
71.1%
<NA> 22
28.9%

Length

2024-05-11T15:44:20.014676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:20.177768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 54
71.1%
na 22
28.9%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
69 
0
7 

Length

Max length4
Median length4
Mean length3.7236842
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 69
90.8%
0 7
 
9.2%

Length

2024-05-11T15:44:20.375753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:20.560734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 69
90.8%
0 7
 
9.2%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
69 
0
7 

Length

Max length4
Median length4
Mean length3.7236842
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 69
90.8%
0 7
 
9.2%

Length

2024-05-11T15:44:20.765569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:20.993290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 69
90.8%
0 7
 
9.2%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing76
Missing (%)100.0%
Memory size816.0 B

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing76
Missing (%)100.0%
Memory size816.0 B

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
70 
상수도전용
 
6

Length

Max length5
Median length4
Mean length4.0789474
Min length4

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> 70
92.1%
상수도전용 6
 
7.9%

Length

2024-05-11T15:44:21.188413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:21.773124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
92.1%
상수도전용 6
 
7.9%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
70 
0
 
6

Length

Max length4
Median length4
Mean length3.7631579
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 70
92.1%
0 6
 
7.9%

Length

2024-05-11T15:44:21.977391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:22.165549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
92.1%
0 6
 
7.9%

본사종업원수
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
59 
0
17 

Length

Max length4
Median length4
Mean length3.3289474
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
77.6%
0 17
 
22.4%

Length

2024-05-11T15:44:22.352579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:22.548432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
77.6%
0 17
 
22.4%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
59 
0
16 
85
 
1

Length

Max length4
Median length4
Mean length3.3421053
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
77.6%
0 16
 
21.1%
85 1
 
1.3%

Length

2024-05-11T15:44:22.716099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:22.884351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
77.6%
0 16
 
21.1%
85 1
 
1.3%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
59 
0
16 
8
 
1

Length

Max length4
Median length4
Mean length3.3289474
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
77.6%
0 16
 
21.1%
8 1
 
1.3%

Length

2024-05-11T15:44:23.107515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:23.340385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
77.6%
0 16
 
21.1%
8 1
 
1.3%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
59 
0
17 

Length

Max length4
Median length4
Mean length3.3289474
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
77.6%
0 17
 
22.4%

Length

2024-05-11T15:44:23.550750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:23.724962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
77.6%
0 17
 
22.4%

건물소유구분명
Categorical

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
52 
자가
13 
임대
11 

Length

Max length4
Median length4
Mean length3.3684211
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> 52
68.4%
자가 13
 
17.1%
임대 11
 
14.5%

Length

2024-05-11T15:44:23.940861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:24.141759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
68.4%
자가 13
 
17.1%
임대 11
 
14.5%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
64 
0
11 
102804500
 
1

Length

Max length9
Median length4
Mean length3.6315789
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 64
84.2%
0 11
 
14.5%
102804500 1
 
1.3%

Length

2024-05-11T15:44:24.331541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:24.540848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 64
84.2%
0 11
 
14.5%
102804500 1
 
1.3%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
64 
0
11 
10280450
 
1

Length

Max length8
Median length4
Mean length3.6184211
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 64
84.2%
0 11
 
14.5%
10280450 1
 
1.3%

Length

2024-05-11T15:44:24.744708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:24.913908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 64
84.2%
0 11
 
14.5%
10280450 1
 
1.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.9%
Missing22
Missing (%)28.9%
Memory size284.0 B
False
54 
(Missing)
22 
ValueCountFrequency (%)
False 54
71.1%
(Missing) 22
28.9%
2024-05-11T15:44:25.049766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

Distinct6
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
0.0
49 
<NA>
22 
33.0
 
2
60.0
 
1
18.68
 
1

Length

Max length5
Median length3
Mean length3.3815789
Min length3

Unique

Unique3 ?
Unique (%)3.9%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 49
64.5%
<NA> 22
28.9%
33.0 2
 
2.6%
60.0 1
 
1.3%
18.68 1
 
1.3%
33.59 1
 
1.3%

Length

2024-05-11T15:44:25.221371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:25.451983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 49
64.5%
na 22
28.9%
33.0 2
 
2.6%
60.0 1
 
1.3%
18.68 1
 
1.3%
33.59 1
 
1.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing76
Missing (%)100.0%
Memory size816.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing76
Missing (%)100.0%
Memory size816.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing76
Missing (%)100.0%
Memory size816.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030600003060000-135-2004-0000120040413<NA>3폐업2폐업20160726<NA><NA><NA><NA><NA>131863서울특별시 중랑구 상봉동 ***번지 신내테크노타운 *층서울특별시 중랑구 봉화산로 *** (상봉동,신내테크노타운 *층)2048(주)늘푸른유통2008-03-31 15:52:19I2018-08-31 23:59:59.0건강기능식품유통전문판매업207681.184228455748.84875건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
130600003060000-135-2004-0000220040413<NA>3폐업2폐업20061019<NA><NA><NA><NA><NA>131875서울특별시 중랑구 중화동 ***-*번지 지하*층<NA><NA>가람인터내셔날2004-04-13 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업207167.558217455500.272419건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230600003060000-135-2004-0000320040413<NA>3폐업2폐업20050719<NA><NA><NA><NA><NA>131878서울특별시 중랑구 중화동 ***-*번지 가나안빌딩***호<NA><NA>(주)바이오젠코리아2005-07-20 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업206899.050411454761.723685건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330600003060000-135-2004-0000420040423<NA>3폐업2폐업20050707<NA><NA><NA><NA><NA>131859서울특별시 중랑구 상봉동 **-*번지<NA><NA>헬스엠(주)2005-05-13 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업207824.338502454726.714115건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430600003060000-135-2004-0000520040615<NA>3폐업2폐업20211105<NA><NA><NA>02 20945800<NA>131859서울특별시 중랑구 상봉동 ***-* 대상빌딩 *층서울특별시 중랑구 면목로 *** (상봉동, 대상빌딩 *층)2154대상(주)건강사업본부2021-11-05 11:46:26U2021-11-07 02:40:00.0건강기능식품유통전문판매업207590.031147454599.632823건강기능식품유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
530600003060000-135-2004-0000620040720<NA>3폐업2폐업20140304<NA><NA><NA>02 438446115.0131821서울특별시 중랑구 면목동 ***-**번지 화성빌딩 지층서울특별시 중랑구 동일로 *** (면목동,화성빌딩 지층)2224(주)건아에이치앤피2007-01-15 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업207008.826567453594.509785건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630600003060000-135-2004-0000820040923<NA>3폐업2폐업20041229<NA><NA><NA>02 9767588132.0131853서울특별시 중랑구 묵동 ***-**번지<NA><NA>씨엠솔나라2004-09-23 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업206780.792913455900.774375건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730600003060000-135-2004-0000920041014<NA>3폐업2폐업20050428<NA><NA><NA>02 4940572<NA>131828서울특별시 중랑구 면목동 ***-*번지 *층<NA><NA>씨엠솔나라 면목지점2004-10-14 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업207509.876516452952.386172건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830600003060000-135-2004-0001020041019<NA>3폐업2폐업20181219<NA><NA><NA>02 4334472<NA>131802서울특별시 중랑구 망우동 ***-**번지 (***호)서울특별시 중랑구 용마산로***길 * (망우동,(***호))2176파워36(주)2018-12-26 14:41:04U2018-12-28 02:40:00.0건강기능식품유통전문판매업208842.713557455205.50434건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930600003060000-135-2005-0000120050121<NA>3폐업2폐업20061012<NA><NA><NA>02 4338200<NA>131880서울특별시 중랑구 중화동 ***-**번지<NA><NA>이엠에스코리아2005-01-21 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업206956.392279455196.971911건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
6630600003060000-135-2023-000012023-02-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>198.0131-805서울특별시 중랑구 망우동 ***-** 호키태권도서울특별시 중랑구 용마공원로 *, 호키태권도 *층 (망우동)2181키사모2023-02-16 10:10:37I2022-12-01 23:08:00.0건강기능식품유통전문판매업208833.57987454752.674412<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6730600003060000-135-2023-000022023-07-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-865서울특별시 중랑구 신내동 *** 신아타운서울특별시 중랑구 봉화산로 ***, 신아타운 *층 ***-***호 (신내동)2076주식회사 인빅투스2023-07-24 16:22:27I2022-12-06 22:06:00.0건강기능식품유통전문판매업208295.099818456014.999181<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6830600003060000-135-2023-000032023-08-29<NA>1영업/정상1영업<NA><NA><NA><NA>7770602<NA>131-848서울특별시 중랑구 묵동 ***-**서울특별시 중랑구 공릉로 **, ***호 (묵동)2034퓨더마2023-08-29 14:43:24I2022-12-07 21:01:00.0건강기능식품유통전문판매업206823.165967456686.933364<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6930600003060000-135-2023-000042023-09-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-852서울특별시 중랑구 묵동 ***-** 블루포스서울특별시 중랑구 동일로 ***, 블루포스 *층 ***호 (묵동)2006플랜드잇 Plannedit2023-09-05 14:43:45I2022-12-09 00:07:00.0건강기능식품유통전문판매업206758.41039456472.21633<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7030600003060000-135-2023-000052023-11-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-865서울특별시 중랑구 신내동 *** 신아타운서울특별시 중랑구 봉화산로 ***, 신아타운 *층 ***-***호 (신내동)2076웰메이커2023-11-01 15:22:24I2022-11-01 00:03:00.0건강기능식품유통전문판매업208295.099818456014.999181<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7130600003060000-135-2024-000012024-01-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-882서울특별시 중랑구 중화동 ***-**서울특별시 중랑구 동일로***다길 *, 위드짚센터 ***에이 (중화동)2015주식회사 말러2024-05-03 11:29:02U2023-12-05 00:05:00.0건강기능식품유통전문판매업206682.913961455698.02779<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7230600003060000-135-2024-000022024-01-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-860서울특별시 중랑구 상봉동 ***-**서울특별시 중랑구 봉우재로 **, *층 (상봉동)2139센시블리2024-01-17 11:02:34I2023-11-30 23:09:00.0건강기능식품유통전문판매업207169.501342454408.54343<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7330600003060000-135-2024-000032024-02-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-859서울특별시 중랑구 상봉동 ***-** 상봉베스트원아파트서울특별시 중랑구 망우로 ***, ***호 (상봉동, 상봉베스트원아파트)2148주식회사 혜당인터내셔널2024-02-20 11:23:11I2023-12-01 22:02:00.0건강기능식품유통전문판매업207566.976888454857.881211<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7430600003060000-135-2024-000042024-02-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-865서울특별시 중랑구 신내동 *** 신아타운서울특별시 중랑구 봉화산로 ***, 신아타운 *층 ***-***호 (신내동)2076건강편의점2024-02-21 13:08:10I2023-12-01 22:03:00.0건강기능식품유통전문판매업208295.099818456014.999181<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7530600003060000-135-2024-000052024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>131-848서울특별시 중랑구 묵동 ***-** 칼튼테라스서울특별시 중랑구 공릉로*길 *-*, *층 (묵동, 칼튼테라스)2037보룡약국2024-05-03 13:49:26I2023-12-05 00:05:00.0건강기능식품유통전문판매업206859.335695456604.826307<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>