Overview

Dataset statistics

Number of variables35
Number of observations62
Missing cells417
Missing cells (%)19.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.5 KiB
Average record size in memory305.1 B

Variable types

Categorical16
Text5
DateTime4
Unsupported4
Numeric6

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),사무실면적,소독차량차고면적,초미립자살포기수,휴대용소독기수,동력분무기수,수동식분무기수,방독면수,보호안경수,보호용의복수,진공청소기수
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-19435/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (88.1%)Imbalance
휴업종료일자 is highly imbalanced (88.1%)Imbalance
인허가취소일자 has 62 (100.0%) missing valuesMissing
폐업일자 has 32 (51.6%) missing valuesMissing
재개업일자 has 62 (100.0%) missing valuesMissing
전화번호 has 21 (33.9%) missing valuesMissing
소재지면적 has 62 (100.0%) missing valuesMissing
소재지우편번호 has 38 (61.3%) missing valuesMissing
지번주소 has 4 (6.5%) missing valuesMissing
도로명주소 has 4 (6.5%) missing valuesMissing
도로명우편번호 has 20 (32.3%) missing valuesMissing
업태구분명 has 62 (100.0%) missing valuesMissing
좌표정보(X) has 1 (1.6%) missing valuesMissing
좌표정보(Y) has 1 (1.6%) missing valuesMissing
사무실면적 has 24 (38.7%) missing valuesMissing
소독차량차고면적 has 24 (38.7%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
사무실면적 has 1 (1.6%) zerosZeros
소독차량차고면적 has 1 (1.6%) zerosZeros

Reproduction

Analysis started2024-04-29 19:55:17.568417
Analysis finished2024-04-29 19:55:18.276267
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
3080000
62 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3080000 62
100.0%

Length

2024-04-30T04:55:18.337536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:18.410351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 62
100.0%

관리번호
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2024-04-30T04:55:18.552730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1550
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)100.0%

Sample

1st rowPHMB520003080033042500001
2nd rowPHMB520013080033042500001
3rd rowPHMB520023080033042500001
4th rowPHMB520023080033042500002
5th rowPHMB520053080033042500001
ValueCountFrequency (%)
phmb520003080033042500001 1
 
1.6%
phmb520203080033042500007 1
 
1.6%
phmb520233080033042500003 1
 
1.6%
phmb520153080033042500003 1
 
1.6%
phmb520153080033042500004 1
 
1.6%
phmb520163080033042500001 1
 
1.6%
phmb520163080033042500003 1
 
1.6%
phmb520173080033042500002 1
 
1.6%
phmb520183080033042500001 1
 
1.6%
phmb520193080033042500001 1
 
1.6%
Other values (52) 52
83.9%
2024-04-30T04:55:18.844285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 589
38.0%
3 202
 
13.0%
2 169
 
10.9%
5 132
 
8.5%
4 69
 
4.5%
8 66
 
4.3%
P 62
 
4.0%
H 62
 
4.0%
M 62
 
4.0%
B 62
 
4.0%
Other values (4) 75
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1302
84.0%
Uppercase Letter 248
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 589
45.2%
3 202
 
15.5%
2 169
 
13.0%
5 132
 
10.1%
4 69
 
5.3%
8 66
 
5.1%
1 58
 
4.5%
6 7
 
0.5%
7 6
 
0.5%
9 4
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
P 62
25.0%
H 62
25.0%
M 62
25.0%
B 62
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1302
84.0%
Latin 248
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 589
45.2%
3 202
 
15.5%
2 169
 
13.0%
5 132
 
10.1%
4 69
 
5.3%
8 66
 
5.1%
1 58
 
4.5%
6 7
 
0.5%
7 6
 
0.5%
9 4
 
0.3%
Latin
ValueCountFrequency (%)
P 62
25.0%
H 62
25.0%
M 62
25.0%
B 62
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 589
38.0%
3 202
 
13.0%
2 169
 
10.9%
5 132
 
8.5%
4 69
 
4.5%
8 66
 
4.3%
P 62
 
4.0%
H 62
 
4.0%
M 62
 
4.0%
B 62
 
4.0%
Other values (4) 75
 
4.8%

인허가일자
Date

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
Minimum2000-06-23 00:00:00
Maximum2023-10-23 00:00:00
2024-04-30T04:55:18.983952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:55:19.108697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

영업상태코드
Categorical

Distinct5
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
3
28 
1
26 
5
5 
4
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row3
2nd row5
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 28
45.2%
1 26
41.9%
5 5
 
8.1%
4 2
 
3.2%
2 1
 
1.6%

Length

2024-04-30T04:55:19.233871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:19.332381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 28
45.2%
1 26
41.9%
5 5
 
8.1%
4 2
 
3.2%
2 1
 
1.6%

영업상태명
Categorical

Distinct5
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
폐업
28 
영업/정상
26 
제외/삭제/전출
5 
취소/말소/만료/정지/중지
 
2
휴업
 
1

Length

Max length14
Median length8
Mean length4.1290323
Min length2

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 28
45.2%
영업/정상 26
41.9%
제외/삭제/전출 5
 
8.1%
취소/말소/만료/정지/중지 2
 
3.2%
휴업 1
 
1.6%

Length

2024-04-30T04:55:19.442723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:19.551278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 28
45.2%
영업/정상 26
41.9%
제외/삭제/전출 5
 
8.1%
취소/말소/만료/정지/중지 2
 
3.2%
휴업 1
 
1.6%

상세영업상태코드
Categorical

Distinct5
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
3
28 
13
26 
15
5 
24
 
2
2
 
1

Length

Max length2
Median length2
Mean length1.5322581
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row3
2nd row15
3rd row3
4th row13
5th row13

Common Values

ValueCountFrequency (%)
3 28
45.2%
13 26
41.9%
15 5
 
8.1%
24 2
 
3.2%
2 1
 
1.6%

Length

2024-04-30T04:55:19.668368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:19.754980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 28
45.2%
13 26
41.9%
15 5
 
8.1%
24 2
 
3.2%
2 1
 
1.6%

상세영업상태명
Categorical

Distinct5
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
폐업
28 
영업중
26 
전출
5 
직권폐업
 
2
휴업
 
1

Length

Max length4
Median length2
Mean length2.483871
Min length2

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 28
45.2%
영업중 26
41.9%
전출 5
 
8.1%
직권폐업 2
 
3.2%
휴업 1
 
1.6%

Length

2024-04-30T04:55:19.858041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:19.954542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 28
45.2%
영업중 26
41.9%
전출 5
 
8.1%
직권폐업 2
 
3.2%
휴업 1
 
1.6%

폐업일자
Date

MISSING 

Distinct30
Distinct (%)100.0%
Missing32
Missing (%)51.6%
Memory size628.0 B
Minimum2010-01-30 00:00:00
Maximum2023-11-29 00:00:00
2024-04-30T04:55:20.051935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:55:20.155972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
61 
20191212
 
1

Length

Max length8
Median length4
Mean length4.0645161
Min length4

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 61
98.4%
20191212 1
 
1.6%

Length

2024-04-30T04:55:20.262485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:20.346566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 61
98.4%
20191212 1
 
1.6%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
61 
20201211
 
1

Length

Max length8
Median length4
Mean length4.0645161
Min length4

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 61
98.4%
20201211 1
 
1.6%

Length

2024-04-30T04:55:20.444618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:20.541003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 61
98.4%
20201211 1
 
1.6%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

전화번호
Text

MISSING 

Distinct41
Distinct (%)100.0%
Missing21
Missing (%)33.9%
Memory size628.0 B
2024-04-30T04:55:20.706522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.073171
Min length8

Characters and Unicode

Total characters413
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row02-997-2391
2nd row990-6401
3rd row02-999-3412
4th row02-997-4402
5th row02-906-3086
ValueCountFrequency (%)
994-5854 1
 
2.4%
02-719-9451 1
 
2.4%
02-988-8245 1
 
2.4%
029890911 1
 
2.4%
906-0058 1
 
2.4%
982-1414 1
 
2.4%
02-929-8060 1
 
2.4%
1577-4813 1
 
2.4%
02-989-1415 1
 
2.4%
3394-7865 1
 
2.4%
Other values (32) 32
76.2%
2024-04-30T04:55:21.013198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 67
16.2%
- 56
13.6%
2 56
13.6%
9 55
13.3%
8 36
8.7%
1 31
7.5%
4 29
7.0%
3 24
 
5.8%
5 21
 
5.1%
7 21
 
5.1%
Other values (3) 17
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 355
86.0%
Dash Punctuation 56
 
13.6%
Close Punctuation 1
 
0.2%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 67
18.9%
2 56
15.8%
9 55
15.5%
8 36
10.1%
1 31
8.7%
4 29
8.2%
3 24
 
6.8%
5 21
 
5.9%
7 21
 
5.9%
6 15
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 413
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 67
16.2%
- 56
13.6%
2 56
13.6%
9 55
13.3%
8 36
8.7%
1 31
7.5%
4 29
7.0%
3 24
 
5.8%
5 21
 
5.1%
7 21
 
5.1%
Other values (3) 17
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 67
16.2%
- 56
13.6%
2 56
13.6%
9 55
13.3%
8 36
8.7%
1 31
7.5%
4 29
7.0%
3 24
 
5.8%
5 21
 
5.1%
7 21
 
5.1%
Other values (3) 17
 
4.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)62.5%
Missing38
Missing (%)61.3%
Infinite0
Infinite (%)0.0%
Mean160873.75
Minimum142060
Maximum585873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-04-30T04:55:21.133536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum142060
5-th percentile142060
Q1142070
median142100
Q3142803.25
95-th percentile142884.8
Maximum585873
Range443813
Interquartile range (IQR)733.25

Descriptive statistics

Standard deviation90525.19
Coefficient of variation (CV)0.56270952
Kurtosis23.999121
Mean160873.75
Median Absolute Deviation (MAD)40
Skewness4.8988503
Sum3860970
Variance8.1948101 × 109
MonotonicityNot monotonic
2024-04-30T04:55:21.216004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
142100 5
 
8.1%
142060 3
 
4.8%
142070 3
 
4.8%
142803 2
 
3.2%
142703 1
 
1.6%
142804 1
 
1.6%
142771 1
 
1.6%
142061 1
 
1.6%
142807 1
 
1.6%
142071 1
 
1.6%
Other values (5) 5
 
8.1%
(Missing) 38
61.3%
ValueCountFrequency (%)
142060 3
4.8%
142061 1
 
1.6%
142070 3
4.8%
142071 1
 
1.6%
142100 5
8.1%
142703 1
 
1.6%
142752 1
 
1.6%
142771 1
 
1.6%
142803 2
 
3.2%
142804 1
 
1.6%
ValueCountFrequency (%)
585873 1
1.6%
142886 1
1.6%
142878 1
1.6%
142868 1
1.6%
142807 1
1.6%
142804 1
1.6%
142803 2
3.2%
142771 1
1.6%
142752 1
1.6%
142703 1
1.6%

지번주소
Text

MISSING 

Distinct58
Distinct (%)100.0%
Missing4
Missing (%)6.5%
Memory size628.0 B
2024-04-30T04:55:21.476474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length24.844828
Min length15

Characters and Unicode

Total characters1441
Distinct characters81
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

Unique58 ?
Unique (%)100.0%

Sample

1st row서울특별시 강북구 번동 415번지 19호 2층
2nd row서울특별시 강북구 미아동 158번지 95호 (지상2층)
3rd row서울특별시 강북구 미아동 189번지 14호
4th row서울특별시 강북구 미아동 329번지 46호
5th row서울특별시 강북구 수유동 178번지 2호 동보빌딩
ValueCountFrequency (%)
서울특별시 57
18.8%
강북구 57
18.8%
미아동 24
 
7.9%
수유동 19
 
6.2%
번동 9
 
3.0%
2호 4
 
1.3%
1호 3
 
1.0%
205번지 3
 
1.0%
상가 3
 
1.0%
11호 3
 
1.0%
Other values (113) 122
40.1%
2024-04-30T04:55:21.858516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
 
17.1%
1 63
 
4.4%
동 62
 
4.3%
북 58
 
4.0%
서 57
 
4.0%
특 57
 
4.0%
별 57
 
4.0%
시 57
 
4.0%
강 57
 
4.0%
구 57
 
4.0%
Other values (71) 669
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 868
60.2%
Decimal Number 299
 
20.7%
Space Separator 247
 
17.1%
Dash Punctuation 22
 
1.5%
Other Punctuation 2
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 62
 
7.1%
북 58
 
6.7%
서 57
 
6.6%
특 57
 
6.6%
별 57
 
6.6%
시 57
 
6.6%
강 57
 
6.6%
구 57
 
6.6%
울 57
 
6.6%
번 45
 
5.2%
Other values (55) 304
35.0%
Decimal Number
ValueCountFrequency (%)
1 63
21.1%
2 47
15.7%
3 34
11.4%
0 27
9.0%
4 26
8.7%
5 22
 
7.4%
8 22
 
7.4%
6 21
 
7.0%
7 19
 
6.4%
9 18
 
6.0%
Space Separator
ValueCountFrequency (%)
247
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 868
60.2%
Common 572
39.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 62
 
7.1%
북 58
 
6.7%
서 57
 
6.6%
특 57
 
6.6%
별 57
 
6.6%
시 57
 
6.6%
강 57
 
6.6%
구 57
 
6.6%
울 57
 
6.6%
번 45
 
5.2%
Other values (55) 304
35.0%
Common
ValueCountFrequency (%)
247
43.2%
1 63
 
11.0%
2 47
 
8.2%
3 34
 
5.9%
0 27
 
4.7%
4 26
 
4.5%
5 22
 
3.8%
- 22
 
3.8%
8 22
 
3.8%
6 21
 
3.7%
Other values (5) 41
 
7.2%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 868
60.2%
ASCII 573
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
43.1%
1 63
 
11.0%
2 47
 
8.2%
3 34
 
5.9%
0 27
 
4.7%
4 26
 
4.5%
5 22
 
3.8%
- 22
 
3.8%
8 22
 
3.8%
6 21
 
3.7%
Other values (6) 42
 
7.3%
Hangul
ValueCountFrequency (%)
동 62
 
7.1%
북 58
 
6.7%
서 57
 
6.6%
특 57
 
6.6%
별 57
 
6.6%
시 57
 
6.6%
강 57
 
6.6%
구 57
 
6.6%
울 57
 
6.6%
번 45
 
5.2%
Other values (55) 304
35.0%

도로명주소
Text

MISSING 

Distinct56
Distinct (%)96.6%
Missing4
Missing (%)6.5%
Memory size628.0 B
2024-04-30T04:55:22.106647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length38
Mean length31.068966
Min length22

Characters and Unicode

Total characters1802
Distinct characters99
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)93.1%

Sample

1st row서울특별시 강북구 오패산로 396-1 (번동,2층)
2nd row서울특별시 강북구 도봉로78길 41 (미아동,(지상2층))
3rd row서울특별시 강북구 도봉로 260 (미아동)
4th row서울특별시 강북구 도봉로23가길 18 (미아동)
5th row서울특별시 강북구 한천로 1072, 동보빌딩 1층 (수유동)
ValueCountFrequency (%)
서울특별시 58
 
16.2%
강북구 58
 
16.2%
미아동 25
 
7.0%
수유동 20
 
5.6%
1층 16
 
4.5%
3층 6
 
1.7%
번동 6
 
1.7%
1호 4
 
1.1%
2층 4
 
1.1%
41 3
 
0.8%
Other values (131) 159
44.3%
2024-04-30T04:55:22.499223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
301
 
16.7%
1 82
 
4.6%
동 63
 
3.5%
) 59
 
3.3%
( 59
 
3.3%
구 58
 
3.2%
로 58
 
3.2%
서 58
 
3.2%
북 58
 
3.2%
강 58
 
3.2%
Other values (89) 948
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1021
56.7%
Decimal Number 302
 
16.8%
Space Separator 301
 
16.7%
Close Punctuation 59
 
3.3%
Open Punctuation 59
 
3.3%
Other Punctuation 49
 
2.7%
Dash Punctuation 8
 
0.4%
Uppercase Letter 2
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 63
 
6.2%
구 58
 
5.7%
로 58
 
5.7%
서 58
 
5.7%
북 58
 
5.7%
강 58
 
5.7%
시 58
 
5.7%
별 58
 
5.7%
특 58
 
5.7%
울 58
 
5.7%
Other values (70) 436
42.7%
Decimal Number
ValueCountFrequency (%)
1 82
27.2%
2 41
13.6%
3 32
 
10.6%
0 30
 
9.9%
4 28
 
9.3%
6 22
 
7.3%
7 21
 
7.0%
8 20
 
6.6%
5 16
 
5.3%
9 10
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 46
93.9%
. 3
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
E 1
50.0%
Space Separator
ValueCountFrequency (%)
301
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1021
56.7%
Common 779
43.2%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 63
 
6.2%
구 58
 
5.7%
로 58
 
5.7%
서 58
 
5.7%
북 58
 
5.7%
강 58
 
5.7%
시 58
 
5.7%
별 58
 
5.7%
특 58
 
5.7%
울 58
 
5.7%
Other values (70) 436
42.7%
Common
ValueCountFrequency (%)
301
38.6%
1 82
 
10.5%
) 59
 
7.6%
( 59
 
7.6%
, 46
 
5.9%
2 41
 
5.3%
3 32
 
4.1%
0 30
 
3.9%
4 28
 
3.6%
6 22
 
2.8%
Other values (7) 79
 
10.1%
Latin
ValueCountFrequency (%)
A 1
50.0%
E 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1021
56.7%
ASCII 781
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
301
38.5%
1 82
 
10.5%
) 59
 
7.6%
( 59
 
7.6%
, 46
 
5.9%
2 41
 
5.2%
3 32
 
4.1%
0 30
 
3.8%
4 28
 
3.6%
6 22
 
2.8%
Other values (9) 81
 
10.4%
Hangul
ValueCountFrequency (%)
동 63
 
6.2%
구 58
 
5.7%
로 58
 
5.7%
서 58
 
5.7%
북 58
 
5.7%
강 58
 
5.7%
시 58
 
5.7%
별 58
 
5.7%
특 58
 
5.7%
울 58
 
5.7%
Other values (70) 436
42.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)81.0%
Missing20
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean7852.1905
Minimum1006
Maximum142810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-04-30T04:55:22.602530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1006
5-th percentile1021.25
Q11053
median1130
Q31208.5
95-th percentile1236.9
Maximum142810
Range141804
Interquartile range (IQR)155.5

Descriptive statistics

Standard deviation30463.134
Coefficient of variation (CV)3.8795714
Kurtosis18.296608
Mean7852.1905
Median Absolute Deviation (MAD)78
Skewness4.4075338
Sum329792
Variance9.2800253 × 108
MonotonicityNot monotonic
2024-04-30T04:55:22.700899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1132 4
 
6.5%
1053 3
 
4.8%
1161 2
 
3.2%
1026 2
 
3.2%
1224 2
 
3.2%
1035 1
 
1.6%
1209 1
 
1.6%
1229 1
 
1.6%
1214 1
 
1.6%
1040 1
 
1.6%
Other values (24) 24
38.7%
(Missing) 20
32.3%
ValueCountFrequency (%)
1006 1
 
1.6%
1014 1
 
1.6%
1021 1
 
1.6%
1026 2
3.2%
1035 1
 
1.6%
1040 1
 
1.6%
1042 1
 
1.6%
1043 1
 
1.6%
1044 1
 
1.6%
1053 3
4.8%
ValueCountFrequency (%)
142810 1
1.6%
142100 1
1.6%
1237 1
1.6%
1235 1
1.6%
1233 1
1.6%
1229 1
1.6%
1226 1
1.6%
1224 2
3.2%
1214 1
1.6%
1209 1
1.6%

사업장명
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2024-04-30T04:55:22.911021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length12
Mean length7.4677419
Min length2

Characters and Unicode

Total characters463
Distinct characters159
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)100.0%

Sample

1st row(주)대공엔지니어링
2nd row(주)이산아이엔씨
3rd row인덕종합관리(주)
4th row신유환경주식회사
5th row전원방제
ValueCountFrequency (%)
주식회사 5
 
6.6%
주)대공엔지니어링 1
 
1.3%
산호크린환경 1
 
1.3%
와이앤제이클린유한회사 1
 
1.3%
주)서울엔지니어링 1
 
1.3%
해방플러스 1
 
1.3%
초록나무 1
 
1.3%
크린베드 1
 
1.3%
샐룩스아이피씨 1
 
1.3%
동행 1
 
1.3%
Other values (62) 62
81.6%
2024-04-30T04:55:23.231606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 23
 
5.0%
( 17
 
3.7%
) 17
 
3.7%
이 14
 
3.0%
14
 
3.0%
린 14
 
3.0%
스 12
 
2.6%
사 11
 
2.4%
크 11
 
2.4%
경 10
 
2.2%
Other values (149) 320
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 394
85.1%
Open Punctuation 17
 
3.7%
Close Punctuation 17
 
3.7%
Space Separator 14
 
3.0%
Lowercase Letter 13
 
2.8%
Uppercase Letter 3
 
0.6%
Decimal Number 3
 
0.6%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 23
 
5.8%
이 14
 
3.6%
린 14
 
3.6%
스 12
 
3.0%
사 11
 
2.8%
크 11
 
2.8%
경 10
 
2.5%
환 9
 
2.3%
회 8
 
2.0%
서 7
 
1.8%
Other values (131) 275
69.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
23.1%
k 2
15.4%
a 2
15.4%
b 2
15.4%
i 1
 
7.7%
g 1
 
7.7%
n 1
 
7.7%
h 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
6 1
33.3%
3 1
33.3%
5 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
66.7%
T 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 394
85.1%
Common 53
 
11.4%
Latin 16
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 23
 
5.8%
이 14
 
3.6%
린 14
 
3.6%
스 12
 
3.0%
사 11
 
2.8%
크 11
 
2.8%
경 10
 
2.5%
환 9
 
2.3%
회 8
 
2.0%
서 7
 
1.8%
Other values (131) 275
69.8%
Latin
ValueCountFrequency (%)
e 3
18.8%
k 2
12.5%
a 2
12.5%
b 2
12.5%
C 2
12.5%
i 1
 
6.2%
g 1
 
6.2%
n 1
 
6.2%
h 1
 
6.2%
T 1
 
6.2%
Common
ValueCountFrequency (%)
( 17
32.1%
) 17
32.1%
14
26.4%
- 1
 
1.9%
& 1
 
1.9%
6 1
 
1.9%
3 1
 
1.9%
5 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 394
85.1%
ASCII 69
 
14.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 23
 
5.8%
이 14
 
3.6%
린 14
 
3.6%
스 12
 
3.0%
사 11
 
2.8%
크 11
 
2.8%
경 10
 
2.5%
환 9
 
2.3%
회 8
 
2.0%
서 7
 
1.8%
Other values (131) 275
69.8%
ASCII
ValueCountFrequency (%)
( 17
24.6%
) 17
24.6%
14
20.3%
e 3
 
4.3%
k 2
 
2.9%
a 2
 
2.9%
b 2
 
2.9%
C 2
 
2.9%
- 1
 
1.4%
i 1
 
1.4%
Other values (8) 8
11.6%

최종수정일자
Date

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
Minimum2009-02-10 15:24:29
Maximum2024-02-27 15:58:31
2024-04-30T04:55:23.514522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:55:23.657621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
I
31 
U
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 31
50.0%
U 31
50.0%

Length

2024-04-30T04:55:23.773500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:23.863617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 31
50.0%
u 31
50.0%

데이터갱신일자
Date

Distinct36
Distinct (%)58.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 00:04:00
2024-04-30T04:55:23.960556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:55:24.081527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)90.2%
Missing1
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean201400.98
Minimum159289.04
Maximum203932.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-04-30T04:55:24.200393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum159289.04
5-th percentile200913.6
Q1201606.45
median202105.01
Q3202449.69
95-th percentile203492.11
Maximum203932.99
Range44643.949
Interquartile range (IQR)843.24625

Descriptive statistics

Standard deviation5529.6761
Coefficient of variation (CV)0.027456054
Kurtosis58.807575
Mean201400.98
Median Absolute Deviation (MAD)445.00814
Skewness-7.6014036
Sum12285459
Variance30577317
MonotonicityNot monotonic
2024-04-30T04:55:24.313458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202207.298690472 3
 
4.8%
201606.445832012 3
 
4.8%
202679.424116174 2
 
3.2%
200982.852755764 2
 
3.2%
201504.717521514 1
 
1.6%
201174.242411566 1
 
1.6%
203669.523246302 1
 
1.6%
200913.604923265 1
 
1.6%
202380.177716119 1
 
1.6%
202914.612782425 1
 
1.6%
Other values (45) 45
72.6%
ValueCountFrequency (%)
159289.042739 1
1.6%
200551.0 1
1.6%
200902.806414022 1
1.6%
200913.604923265 1
1.6%
200982.852755764 2
3.2%
201048.037522189 1
1.6%
201058.051614302 1
1.6%
201136.569175116 1
1.6%
201174.242411566 1
1.6%
201420.082756941 1
1.6%
ValueCountFrequency (%)
203932.991517795 1
1.6%
203669.523246302 1
1.6%
203627.347902029 1
1.6%
203492.107858432 1
1.6%
203452.54250506 1
1.6%
203160.153576134 1
1.6%
203037.157333911 1
1.6%
202914.612782425 1
1.6%
202683.690697496 1
1.6%
202679.424116174 2
3.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)90.2%
Missing1
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean454763.43
Minimum206290.93
Maximum461449.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-04-30T04:55:24.443733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206290.93
5-th percentile456614.81
Q1457803.1
median459021.58
Q3459973.5
95-th percentile460570.95
Maximum461449.07
Range255158.14
Interquartile range (IQR)2170.4011

Descriptive statistics

Standard deviation32366.898
Coefficient of variation (CV)0.071173045
Kurtosis60.817772
Mean454763.43
Median Absolute Deviation (MAD)971.49915
Skewness-7.793043
Sum27740569
Variance1.0476161 × 109
MonotonicityNot monotonic
2024-04-30T04:55:24.579837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
458714.538497673 3
 
4.8%
460001.632075829 3
 
4.8%
456516.997283985 2
 
3.2%
460570.946389165 2
 
3.2%
460208.625827068 1
 
1.6%
459619.783172795 1
 
1.6%
458396.308289928 1
 
1.6%
461449.073521991 1
 
1.6%
459264.560163741 1
 
1.6%
456953.650681144 1
 
1.6%
Other values (45) 45
72.6%
ValueCountFrequency (%)
206290.928809 1
1.6%
456516.997283985 2
3.2%
456614.805805491 1
1.6%
456729.488442967 1
1.6%
456943.819705953 1
1.6%
456953.650681144 1
1.6%
457098.242432148 1
1.6%
457225.229186641 1
1.6%
457296.446151636 1
1.6%
457550.749590718 1
1.6%
ValueCountFrequency (%)
461449.073521991 1
 
1.6%
460687.105046948 1
 
1.6%
460617.802817112 1
 
1.6%
460570.946389165 2
3.2%
460343.0 1
 
1.6%
460208.625827068 1
 
1.6%
460169.579712466 1
 
1.6%
460118.308378499 1
 
1.6%
460108.899759692 1
 
1.6%
460001.632075829 3
4.8%

사무실면적
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)92.1%
Missing24
Missing (%)38.7%
Infinite0
Infinite (%)0.0%
Mean28.815263
Minimum0
Maximum75.59
Zeros1
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-04-30T04:55:24.701001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.7
Q112.97
median20.4
Q340.8375
95-th percentile75
Maximum75.59
Range75.59
Interquartile range (IQR)27.8675

Descriptive statistics

Standard deviation23.007207
Coefficient of variation (CV)0.79843819
Kurtosis-0.37990732
Mean28.815263
Median Absolute Deviation (MAD)9.78
Skewness0.96794143
Sum1094.98
Variance529.33156
MonotonicityNot monotonic
2024-04-30T04:55:24.829302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
13.2 2
 
3.2%
75.0 2
 
3.2%
18.0 2
 
3.2%
62.03 1
 
1.6%
16.28 1
 
1.6%
0.0 1
 
1.6%
6.6 1
 
1.6%
6.0 1
 
1.6%
22.9 1
 
1.6%
20.0 1
 
1.6%
Other values (25) 25
40.3%
(Missing) 24
38.7%
ValueCountFrequency (%)
0.0 1
1.6%
4.0 1
1.6%
6.0 1
1.6%
6.6 1
1.6%
7.0 1
1.6%
7.5 1
1.6%
10.74 1
1.6%
12.0 1
1.6%
12.9 1
1.6%
12.96 1
1.6%
ValueCountFrequency (%)
75.59 1
1.6%
75.0 2
3.2%
74.7 1
1.6%
63.8 1
1.6%
62.03 1
1.6%
60.0 1
1.6%
55.56 1
1.6%
50.0 1
1.6%
42.15 1
1.6%
36.9 1
1.6%

소독차량차고면적
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)65.8%
Missing24
Missing (%)38.7%
Infinite0
Infinite (%)0.0%
Mean14.108158
Minimum0
Maximum55.12
Zeros1
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-04-30T04:55:24.969909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q15.25
median9.45
Q319.65
95-th percentile42.498
Maximum55.12
Range55.12
Interquartile range (IQR)14.4

Descriptive statistics

Standard deviation13.397448
Coefficient of variation (CV)0.94962418
Kurtosis2.945929
Mean14.108158
Median Absolute Deviation (MAD)5.45
Skewness1.7959814
Sum536.11
Variance179.49161
MonotonicityNot monotonic
2024-04-30T04:55:25.061284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
10.0 4
 
6.5%
20.0 3
 
4.8%
3.3 3
 
4.8%
4.0 3
 
4.8%
6.0 2
 
3.2%
6.6 2
 
3.2%
5.0 2
 
3.2%
9.0 2
 
3.2%
53.82 1
 
1.6%
8.0 1
 
1.6%
Other values (15) 15
24.2%
(Missing) 24
38.7%
ValueCountFrequency (%)
0.0 1
 
1.6%
3.3 3
4.8%
3.78 1
 
1.6%
4.0 3
4.8%
5.0 2
3.2%
6.0 2
3.2%
6.48 1
 
1.6%
6.6 2
3.2%
7.22 1
 
1.6%
8.0 1
 
1.6%
ValueCountFrequency (%)
55.12 1
 
1.6%
53.82 1
 
1.6%
40.5 1
 
1.6%
35.0 1
 
1.6%
33.0 1
 
1.6%
21.0 1
 
1.6%
20.0 3
4.8%
19.8 1
 
1.6%
19.2 1
 
1.6%
18.8 1
 
1.6%

초미립자살포기수
Categorical

Distinct5
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
1
34 
<NA>
22 
2
4 
3
 
1
7
 
1

Length

Max length4
Median length1
Mean length2.0645161
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row1
2nd row<NA>
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
1 34
54.8%
<NA> 22
35.5%
2 4
 
6.5%
3 1
 
1.6%
7 1
 
1.6%

Length

2024-04-30T04:55:25.162681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:25.256775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 34
54.8%
na 22
35.5%
2 4
 
6.5%
3 1
 
1.6%
7 1
 
1.6%

휴대용소독기수
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
2
40 
<NA>
22 

Length

Max length4
Median length1
Mean length2.0645161
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 40
64.5%
<NA> 22
35.5%

Length

2024-04-30T04:55:25.370430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:25.465950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 40
64.5%
na 22
35.5%

동력분무기수
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
1
28 
<NA>
22 
0
12 

Length

Max length4
Median length1
Mean length2.0645161
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
1 28
45.2%
<NA> 22
35.5%
0 12
19.4%

Length

2024-04-30T04:55:25.550523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:25.637090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
45.2%
na 22
35.5%
0 12
19.4%

수동식분무기수
Categorical

Distinct6
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size628.0 B
5
26 
<NA>
22 
3
11 
6
 
1
19
 
1

Length

Max length4
Median length1
Mean length2.0806452
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row5
2nd row<NA>
3rd row5
4th row5
5th row<NA>

Common Values

ValueCountFrequency (%)
5 26
41.9%
<NA> 22
35.5%
3 11
17.7%
6 1
 
1.6%
19 1
 
1.6%
4 1
 
1.6%

Length

2024-04-30T04:55:25.724824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:25.813817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 26
41.9%
na 22
35.5%
3 11
17.7%
6 1
 
1.6%
19 1
 
1.6%
4 1
 
1.6%

방독면수
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
5
39 
<NA>
22 
10
 
1

Length

Max length4
Median length1
Mean length2.0806452
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row5
2nd row<NA>
3rd row5
4th row5
5th row<NA>

Common Values

ValueCountFrequency (%)
5 39
62.9%
<NA> 22
35.5%
10 1
 
1.6%

Length

2024-04-30T04:55:25.918140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:26.027548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 39
62.9%
na 22
35.5%
10 1
 
1.6%

보호안경수
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
5
40 
<NA>
22 

Length

Max length4
Median length1
Mean length2.0645161
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row<NA>
3rd row5
4th row5
5th row<NA>

Common Values

ValueCountFrequency (%)
5 40
64.5%
<NA> 22
35.5%

Length

2024-04-30T04:55:26.141114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:26.234029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 40
64.5%
na 22
35.5%

보호용의복수
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
5
39 
<NA>
22 
8
 
1

Length

Max length4
Median length1
Mean length2.0645161
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row5
2nd row<NA>
3rd row5
4th row5
5th row<NA>

Common Values

ValueCountFrequency (%)
5 39
62.9%
<NA> 22
35.5%
8 1
 
1.6%

Length

2024-04-30T04:55:26.342901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:26.431758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 39
62.9%
na 22
35.5%
8 1
 
1.6%

진공청소기수
Categorical

Distinct5
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
1
36 
<NA>
22 
2
 
2
4
 
1
9
 
1

Length

Max length4
Median length1
Mean length2.0645161
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row1
2nd row<NA>
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
1 36
58.1%
<NA> 22
35.5%
2 2
 
3.2%
4 1
 
1.6%
9 1
 
1.6%

Length

2024-04-30T04:55:26.519498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:55:26.605228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 36
58.1%
na 22
35.5%
2 2
 
3.2%
4 1
 
1.6%
9 1
 
1.6%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무실면적소독차량차고면적초미립자살포기수휴대용소독기수동력분무기수수동식분무기수방독면수보호안경수보호용의복수진공청소기수
03080000PHMB52000308003304250000120000623<NA>3폐업3폐업20120314<NA><NA><NA>02-997-2391<NA>142060서울특별시 강북구 번동 415번지 19호 2층서울특별시 강북구 오패산로 396-1 (번동,2층)<NA>(주)대공엔지니어링2017-03-02 17:54:02I2018-08-31 23:59:59.0<NA>202387.637187459370.39216718.021.012155551
13080000PHMB52001308003304250000120010811<NA>5제외/삭제/전출15전출<NA><NA><NA><NA><NA><NA>142803서울특별시 강북구 미아동 158번지 95호 (지상2층)서울특별시 강북구 도봉로78길 41 (미아동,(지상2층))<NA>(주)이산아이엔씨2022-05-19 09:21:48U2021-12-04 22:01:00.0<NA>202218.928904459060.733453<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23080000PHMB52002308003304250000120020624<NA>3폐업3폐업20100511<NA><NA><NA><NA><NA>142100서울특별시 강북구 미아동 189번지 14호서울특별시 강북구 도봉로 260 (미아동)<NA>인덕종합관리(주)2010-05-11 13:45:16I2018-08-31 23:59:59.0<NA>202092.181818458818.03410475.597.2212155551
33080000PHMB52002308003304250000220020220<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>142100서울특별시 강북구 미아동 329번지 46호서울특별시 강북구 도봉로23가길 18 (미아동)<NA>신유환경주식회사2009-02-10 15:24:29I2018-08-31 23:59:59.0<NA>202285.613242457296.44615214.0616.4912155551
43080000PHMB5200530800330425000012005-04-21<NA>1영업/정상13영업중<NA><NA><NA><NA>990-6401<NA><NA>서울특별시 강북구 수유동 178번지 2호 동보빌딩서울특별시 강북구 한천로 1072, 동보빌딩 1층 (수유동)1053전원방제2023-09-19 15:17:00U2022-12-08 22:01:00.0<NA>202056.977848459994.129721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53080000PHMB52006308003304250000120060914<NA>3폐업3폐업20110107<NA><NA><NA><NA><NA>142070서울특별시 강북구 수유동 270번지 126호 지하1층서울특별시 강북구 노해로23길 138 (수유동,지하1층)<NA>(주)신동양시스템2017-03-02 17:55:34I2018-08-31 23:59:59.0<NA>201420.082757460617.80281762.0319.212155551
63080000PHMB52006308003304250000220060418<NA>1영업/정상13영업중<NA><NA><NA><NA>02-999-3412<NA><NA>서울특별시 강북구 미아동 129번지 19호서울특별시 강북구 삼양로68길 26 (미아동, 현대장여관)1121고려종합환경2017-06-28 16:50:18I2018-08-31 23:59:59.0<NA>202662.791152457801.42124813.29.912155551
73080000PHMB52006308003304250000320060328<NA>3폐업3폐업20161212<NA><NA><NA>02-997-4402<NA>142070서울특별시 강북구 수유동 220번지 13호 2층서울특별시 강북구 삼각산로 149-1 (수유동,2층)<NA>(주)동아씨에스2016-12-12 17:52:09I2018-08-31 23:59:59.0<NA>201756.493628459912.07837416.283.7812155551
83080000PHMB52007308003304250000120070816<NA>3폐업3폐업20120713<NA><NA><NA>02-906-3086<NA>142100서울특별시 강북구 미아동 209번지 8호 우원빌딩 304호서울특별시 강북구 도봉로53길 7 (미아동,우원빌딩 304호)<NA>서울환경시스템2012-07-13 17:42:32I2018-08-31 23:59:59.0<NA>202175.049469458252.77652375.010.012155551
93080000PHMB5200730800330425000022007-04-27<NA>1영업/정상13영업중<NA><NA><NA><NA>02-900-2526<NA><NA>서울특별시 강북구 수유동 95-7 수유동 이테크밸리 오피스텔서울특별시 강북구 도봉로77길 6, 수유동 이테크밸리 오피스텔 3층 301~306호 (수유동)1113하나로엠지엠(주)2023-11-23 09:02:22U2022-10-31 22:05:00.0<NA>201942.872329459046.12554<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무실면적소독차량차고면적초미립자살포기수휴대용소독기수동력분무기수수동식분무기수방독면수보호안경수보호용의복수진공청소기수
523080000PHMB52021308003304250000320210315<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강북구 수유동 702-8서울특별시 강북구 노해로33길 107, 1층 (수유동)1044닥터 클린2021-03-15 17:44:01I2021-03-17 00:22:59.0<NA>201660.777627460687.1050476.66.612035551
533080000PHMB52021308003304250000420210329<NA>5제외/삭제/전출15전출<NA><NA><NA><NA><NA><NA><NA>서울특별시 강북구 수유동 359-12서울특별시 강북구 인수봉로68길 41, 1층 (수유동)1035스마트 크린2022-06-07 09:14:02U2021-12-06 00:09:00.0<NA>201136.569175459884.049087<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
543080000PHMB5202130800330425000052021-05-28<NA>3폐업3폐업2023-06-22<NA><NA><NA><NA><NA><NA>서울특별시 강북구 미아동 130-51서울특별시 강북구 도봉로34길 17, 1층 1호 (미아동)1160조이 C&C2023-06-22 10:21:29U2022-12-05 22:04:00.0<NA>202498.28903457749.334491<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
553080000PHMB52021308003304250000620211130<NA>3폐업3폐업20220926<NA><NA><NA><NA><NA><NA>서울특별시 강북구 미아동 8서울특별시 강북구 오패산로 118-11, 1층 (미아동)1237미렌토 특수방역2022-09-26 15:34:32U2021-12-08 22:08:00.0<NA>203037.157334456729.488443<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
563080000PHMB52022308003304250000120220110<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강북구 미아동 437-10서울특별시 강북구 솔샘로64나길 55, 지층1호 (미아동)1207맑은나라2022-01-12 14:58:21I2022-01-14 00:22:40.0<NA>202105.012428457098.2424320.00.012035551
573080000PHMB52022308003304250000220220405<NA>1영업/정상13영업중<NA><NA><NA><NA>02-988-4247<NA><NA>서울특별시 강북구 수유동 188-6 현광빌딩서울특별시 강북구 한천로 1077, 현광빌딩 3층 11호 (수유동)1070글로리아2022-04-05 17:55:04I2021-12-04 00:07:00.0<NA>201977.364158459993.074907<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
583080000PHMB5202330800330425000012023-02-10<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강북구 미아동 131-6서울특별시 강북구 도봉로 144, 4층 E-80호 (미아동)1161투썬클린텍2023-02-13 09:32:35U2022-12-01 23:05:00.0<NA>202443.441398457708.146945<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
593080000PHMB5202330800330425000022021-09-06<NA>1영업/정상13영업중<NA><NA><NA><NA>02-988-8245<NA><NA>서울특별시 강북구 미아동 742-2서울특별시 강북구 삼양로46길 12, 1층 (미아동)1173한국인력공사2023-11-28 09:06:57U2022-10-31 21:00:00.0<NA>201742.958929457803.097126<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
603080000PHMB5202330800330425000032023-08-28<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강북구 수유동 181-40 1호서울특별시 강북구 한천로150길 20, 1층 1호 (수유동)1053종합건물관리 쉬작2024-02-02 15:46:29U2023-12-02 00:04:00.0<NA>202021.254583460118.308378<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
613080000PHMB5202330800330425000042023-10-23<NA>1영업/정상13영업중<NA><NA><NA><NA>02-992-9173<NA><NA>서울특별시 강북구 수유동 524-5서울특별시 강북구 인수봉로 245, 1층 (수유동)1021신세계통상개발2024-02-14 15:15:29U2023-12-01 23:06:00.0<NA>200902.806414459803.243746<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>