Overview

Dataset statistics

Number of variables35
Number of observations112
Missing cells972
Missing cells (%)24.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.2 KiB
Average record size in memory303.2 B

Variable types

Categorical15
Text5
DateTime3
Unsupported6
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-19441/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
보호안경수 is highly imbalanced (50.2%)Imbalance
보호용의복수 is highly imbalanced (52.7%)Imbalance
인허가취소일자 has 112 (100.0%) missing valuesMissing
폐업일자 has 56 (50.0%) missing valuesMissing
휴업시작일자 has 112 (100.0%) missing valuesMissing
휴업종료일자 has 112 (100.0%) missing valuesMissing
재개업일자 has 112 (100.0%) missing valuesMissing
전화번호 has 31 (27.7%) missing valuesMissing
소재지면적 has 112 (100.0%) missing valuesMissing
지번주소 has 5 (4.5%) missing valuesMissing
도로명주소 has 33 (29.5%) missing valuesMissing
도로명우편번호 has 33 (29.5%) missing valuesMissing
업태구분명 has 112 (100.0%) missing valuesMissing
좌표정보(X) has 2 (1.8%) missing valuesMissing
좌표정보(Y) has 2 (1.8%) missing valuesMissing
사무실면적 has 48 (42.9%) missing valuesMissing
소독차량차고면적 has 48 (42.9%) missing valuesMissing
초미립자살포기수 has 42 (37.5%) 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
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

Reproduction

Analysis started2024-05-18 02:17:37.721385
Analysis finished2024-05-18 02:17:38.627805
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
3140000
112 

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 112
100.0%

Length

2024-05-18T11:17:38.812069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:17:39.172624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 112
100.0%

관리번호
Text

UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-05-18T11:17:39.578161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2800
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

Unique112 ?
Unique (%)100.0%

Sample

1st rowPHMB519993140033042500001
2nd rowPHMB519993140033042500002
3rd rowPHMB519993140033042500003
4th rowPHMB519993140033042500004
5th rowPHMB519993140033042500005
ValueCountFrequency (%)
phmb519993140033042500001 1
 
0.9%
phmb519993140033042500002 1
 
0.9%
phmb520203140033042500013 1
 
0.9%
phmb520203140033042500012 1
 
0.9%
phmb520203140033042500011 1
 
0.9%
phmb520203140033042500010 1
 
0.9%
phmb520203140033042500009 1
 
0.9%
phmb520203140033042500008 1
 
0.9%
phmb520203140033042500006 1
 
0.9%
phmb520203140033042500005 1
 
0.9%
Other values (102) 102
91.1%
2024-05-18T11:17:40.427794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 931
33.2%
3 365
 
13.0%
2 292
 
10.4%
4 244
 
8.7%
5 237
 
8.5%
1 203
 
7.2%
P 112
 
4.0%
H 112
 
4.0%
M 112
 
4.0%
B 112
 
4.0%
Other values (4) 80
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2352
84.0%
Uppercase Letter 448
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 931
39.6%
3 365
 
15.5%
2 292
 
12.4%
4 244
 
10.4%
5 237
 
10.1%
1 203
 
8.6%
9 38
 
1.6%
6 15
 
0.6%
7 15
 
0.6%
8 12
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
P 112
25.0%
H 112
25.0%
M 112
25.0%
B 112
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2352
84.0%
Latin 448
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 931
39.6%
3 365
 
15.5%
2 292
 
12.4%
4 244
 
10.4%
5 237
 
10.1%
1 203
 
8.6%
9 38
 
1.6%
6 15
 
0.6%
7 15
 
0.6%
8 12
 
0.5%
Latin
ValueCountFrequency (%)
P 112
25.0%
H 112
25.0%
M 112
25.0%
B 112
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 931
33.2%
3 365
 
13.0%
2 292
 
10.4%
4 244
 
8.7%
5 237
 
8.5%
1 203
 
7.2%
P 112
 
4.0%
H 112
 
4.0%
M 112
 
4.0%
B 112
 
4.0%
Other values (4) 80
 
2.9%

인허가일자
Date

Distinct109
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum1986-10-20 00:00:00
Maximum2024-04-18 00:00:00
2024-05-18T11:17:40.868246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:17:41.526842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing112
Missing (%)100.0%
Memory size1.1 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
1
54 
3
53 
4
 
3
5
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 54
48.2%
3 53
47.3%
4 3
 
2.7%
5 2
 
1.8%

Length

2024-05-18T11:17:41.923100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:17:42.360785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 54
48.2%
3 53
47.3%
4 3
 
2.7%
5 2
 
1.8%

영업상태명
Categorical

Distinct4
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
영업/정상
54 
폐업
53 
취소/말소/만료/정지/중지
 
3
제외/삭제/전출
 
2

Length

Max length14
Median length8
Mean length3.875
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 54
48.2%
폐업 53
47.3%
취소/말소/만료/정지/중지 3
 
2.7%
제외/삭제/전출 2
 
1.8%

Length

2024-05-18T11:17:42.663119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:17:42.947907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 54
48.2%
폐업 53
47.3%
취소/말소/만료/정지/중지 3
 
2.7%
제외/삭제/전출 2
 
1.8%

상세영업상태코드
Categorical

Distinct5
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
13
53 
3
53 
24
 
3
15
 
2
1
 
1

Length

Max length2
Median length2
Mean length1.5178571
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
13 53
47.3%
3 53
47.3%
24 3
 
2.7%
15 2
 
1.8%
1 1
 
0.9%

Length

2024-05-18T11:17:43.285475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:17:43.620759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 53
47.3%
3 53
47.3%
24 3
 
2.7%
15 2
 
1.8%
1 1
 
0.9%

상세영업상태명
Categorical

Distinct5
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
영업중
53 
폐업
53 
직권폐업
 
3
전출
 
2
신규
 
1

Length

Max length4
Median length3.5
Mean length2.5267857
Min length2

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 53
47.3%
폐업 53
47.3%
직권폐업 3
 
2.7%
전출 2
 
1.8%
신규 1
 
0.9%

Length

2024-05-18T11:17:44.014493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:17:44.360570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 53
47.3%
폐업 53
47.3%
직권폐업 3
 
2.7%
전출 2
 
1.8%
신규 1
 
0.9%

폐업일자
Date

MISSING 

Distinct54
Distinct (%)96.4%
Missing56
Missing (%)50.0%
Memory size1.0 KiB
Minimum1999-09-15 00:00:00
Maximum2023-05-04 00:00:00
2024-05-18T11:17:44.731963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:17:45.190683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing112
Missing (%)100.0%
Memory size1.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing112
Missing (%)100.0%
Memory size1.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing112
Missing (%)100.0%
Memory size1.1 KiB

전화번호
Text

MISSING 

Distinct78
Distinct (%)96.3%
Missing31
Missing (%)27.7%
Memory size1.0 KiB
2024-05-18T11:17:45.931680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.802469
Min length8

Characters and Unicode

Total characters875
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)92.6%

Sample

1st row02-2607-1125
2nd row2646 0700
3rd row2646 3957
4th row2651 2780
5th row2654 4394
ValueCountFrequency (%)
2646 3
 
2.9%
2651 2
 
1.9%
2692 2
 
1.9%
02-2654-0725 2
 
1.9%
02-2645-0845 2
 
1.9%
1599-2678 2
 
1.9%
2602 2
 
1.9%
9226 1
 
1.0%
02 1
 
1.0%
02-2604-6008 1
 
1.0%
Other values (85) 85
82.5%
2024-05-18T11:17:47.056995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 142
16.2%
0 125
14.3%
6 115
13.1%
- 99
11.3%
1 63
7.2%
4 58
6.6%
7 57
6.5%
5 55
 
6.3%
9 53
 
6.1%
8 45
 
5.1%
Other values (4) 63
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 749
85.6%
Dash Punctuation 99
 
11.3%
Space Separator 22
 
2.5%
Close Punctuation 4
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 142
19.0%
0 125
16.7%
6 115
15.4%
1 63
8.4%
4 58
7.7%
7 57
7.6%
5 55
 
7.3%
9 53
 
7.1%
8 45
 
6.0%
3 36
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 875
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 142
16.2%
0 125
14.3%
6 115
13.1%
- 99
11.3%
1 63
7.2%
4 58
6.6%
7 57
6.5%
5 55
 
6.3%
9 53
 
6.1%
8 45
 
5.1%
Other values (4) 63
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 875
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 142
16.2%
0 125
14.3%
6 115
13.1%
- 99
11.3%
1 63
7.2%
4 58
6.6%
7 57
6.5%
5 55
 
6.3%
9 53
 
6.1%
8 45
 
5.1%
Other values (4) 63
7.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing112
Missing (%)100.0%
Memory size1.1 KiB

소재지우편번호
Categorical

Distinct23
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
65 
158090
14 
158050
7 
158070
 
6
158841
 
2
Other values (18)
18 

Length

Max length7
Median length4
Mean length4.8660714
Min length4

Unique

Unique18 ?
Unique (%)16.1%

Sample

1st row<NA>
2nd row158050
3rd row158050
4th row158050
5th row158050

Common Values

ValueCountFrequency (%)
<NA> 65
58.0%
158090 14
 
12.5%
158050 7
 
6.2%
158070 6
 
5.4%
158841 2
 
1.8%
158860 1
 
0.9%
158-814 1
 
0.9%
158829 1
 
0.9%
158-838 1
 
0.9%
158840 1
 
0.9%
Other values (13) 13
 
11.6%

Length

2024-05-18T11:17:47.522175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 65
58.0%
158090 14
 
12.5%
158050 7
 
6.2%
158070 6
 
5.4%
158841 2
 
1.8%
158847 1
 
0.9%
158846 1
 
0.9%
158848 1
 
0.9%
158827 1
 
0.9%
158-860 1
 
0.9%
Other values (13) 13
 
11.6%

지번주소
Text

MISSING 

Distinct105
Distinct (%)98.1%
Missing5
Missing (%)4.5%
Memory size1.0 KiB
2024-05-18T11:17:48.341955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32
Mean length25.261682
Min length13

Characters and Unicode

Total characters2703
Distinct characters94
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

Unique103 ?
Unique (%)96.3%

Sample

1st row서울특별시 양천구 신월동 507번지 11호 2층
2nd row서울특별시 양천구 목동 405번지 222호
3rd row서울특별시 양천구 목동 404번지 108호
4th row서울특별시 양천구 목동 794번지 14호
5th row서울특별시 양천구 목동 775번지 25호
ValueCountFrequency (%)
서울특별시 107
18.1%
양천구 107
18.1%
신월동 41
 
6.9%
신정동 29
 
4.9%
목동 27
 
4.6%
1호 12
 
2.0%
1층 12
 
2.0%
2층 11
 
1.9%
5호 7
 
1.2%
11호 5
 
0.8%
Other values (183) 233
39.4%
2024-05-18T11:17:49.529300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
487
 
18.0%
1 132
 
4.9%
천 110
 
4.1%
양 109
 
4.0%
동 108
 
4.0%
서 108
 
4.0%
시 108
 
4.0%
별 107
 
4.0%
구 107
 
4.0%
울 107
 
4.0%
Other values (84) 1220
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1584
58.6%
Decimal Number 586
 
21.7%
Space Separator 487
 
18.0%
Dash Punctuation 32
 
1.2%
Uppercase Letter 7
 
0.3%
Other Punctuation 3
 
0.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 110
 
6.9%
양 109
 
6.9%
동 108
 
6.8%
서 108
 
6.8%
시 108
 
6.8%
별 107
 
6.8%
구 107
 
6.8%
울 107
 
6.8%
특 107
 
6.8%
호 92
 
5.8%
Other values (64) 521
32.9%
Decimal Number
ValueCountFrequency (%)
1 132
22.5%
5 73
12.5%
2 69
11.8%
4 66
11.3%
9 54
9.2%
0 49
 
8.4%
7 40
 
6.8%
6 37
 
6.3%
3 35
 
6.0%
8 31
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 3
42.9%
L 1
 
14.3%
D 1
 
14.3%
K 1
 
14.3%
T 1
 
14.3%
Space Separator
ValueCountFrequency (%)
487
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1584
58.6%
Common 1112
41.1%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 110
 
6.9%
양 109
 
6.9%
동 108
 
6.8%
서 108
 
6.8%
시 108
 
6.8%
별 107
 
6.8%
구 107
 
6.8%
울 107
 
6.8%
특 107
 
6.8%
호 92
 
5.8%
Other values (64) 521
32.9%
Common
ValueCountFrequency (%)
487
43.8%
1 132
 
11.9%
5 73
 
6.6%
2 69
 
6.2%
4 66
 
5.9%
9 54
 
4.9%
0 49
 
4.4%
7 40
 
3.6%
6 37
 
3.3%
3 35
 
3.1%
Other values (5) 70
 
6.3%
Latin
ValueCountFrequency (%)
B 3
42.9%
L 1
 
14.3%
D 1
 
14.3%
K 1
 
14.3%
T 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1584
58.6%
ASCII 1119
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
487
43.5%
1 132
 
11.8%
5 73
 
6.5%
2 69
 
6.2%
4 66
 
5.9%
9 54
 
4.8%
0 49
 
4.4%
7 40
 
3.6%
6 37
 
3.3%
3 35
 
3.1%
Other values (10) 77
 
6.9%
Hangul
ValueCountFrequency (%)
천 110
 
6.9%
양 109
 
6.9%
동 108
 
6.8%
서 108
 
6.8%
시 108
 
6.8%
별 107
 
6.8%
구 107
 
6.8%
울 107
 
6.8%
특 107
 
6.8%
호 92
 
5.8%
Other values (64) 521
32.9%

도로명주소
Text

MISSING 

Distinct77
Distinct (%)97.5%
Missing33
Missing (%)29.5%
Memory size1.0 KiB
2024-05-18T11:17:50.184578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37
Mean length31.050633
Min length21

Characters and Unicode

Total characters2453
Distinct characters105
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

Unique75 ?
Unique (%)94.9%

Sample

1st row서울특별시 양천구 신월로27길 6, 2층 (신월동)
2nd row서울특별시 양천구 등촌로 88 (목동)
3rd row서울특별시 양천구 공항대로 538, 3층 303호 (목동)
4th row서울특별시 양천구 신월로27길 6, 1층 (신월동)
5th row서울특별시 양천구 등촌로 172 (목동, 등촌빌딩)
ValueCountFrequency (%)
서울특별시 79
 
15.6%
양천구 79
 
15.6%
신정동 29
 
5.7%
신월동 29
 
5.7%
2층 21
 
4.1%
목동 21
 
4.1%
1층 11
 
2.2%
3층 8
 
1.6%
신정중앙로 5
 
1.0%
중앙로 5
 
1.0%
Other values (149) 220
43.4%
2024-05-18T11:17:51.380515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
428
 
17.4%
동 106
 
4.3%
양 85
 
3.5%
서 82
 
3.3%
천 81
 
3.3%
, 81
 
3.3%
로 81
 
3.3%
) 79
 
3.2%
( 79
 
3.2%
울 79
 
3.2%
Other values (95) 1272
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1406
57.3%
Space Separator 428
 
17.4%
Decimal Number 368
 
15.0%
Other Punctuation 81
 
3.3%
Close Punctuation 79
 
3.2%
Open Punctuation 79
 
3.2%
Dash Punctuation 10
 
0.4%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 106
 
7.5%
양 85
 
6.0%
서 82
 
5.8%
천 81
 
5.8%
로 81
 
5.8%
울 79
 
5.6%
구 79
 
5.6%
시 79
 
5.6%
별 79
 
5.6%
특 79
 
5.6%
Other values (79) 576
41.0%
Decimal Number
ValueCountFrequency (%)
2 79
21.5%
1 63
17.1%
3 41
11.1%
0 41
11.1%
5 38
10.3%
6 30
 
8.2%
7 23
 
6.2%
4 22
 
6.0%
8 19
 
5.2%
9 12
 
3.3%
Space Separator
ValueCountFrequency (%)
428
100.0%
Other Punctuation
ValueCountFrequency (%)
, 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1406
57.3%
Common 1045
42.6%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 106
 
7.5%
양 85
 
6.0%
서 82
 
5.8%
천 81
 
5.8%
로 81
 
5.8%
울 79
 
5.6%
구 79
 
5.6%
시 79
 
5.6%
별 79
 
5.6%
특 79
 
5.6%
Other values (79) 576
41.0%
Common
ValueCountFrequency (%)
428
41.0%
, 81
 
7.8%
) 79
 
7.6%
( 79
 
7.6%
2 79
 
7.6%
1 63
 
6.0%
3 41
 
3.9%
0 41
 
3.9%
5 38
 
3.6%
6 30
 
2.9%
Other values (5) 86
 
8.2%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1406
57.3%
ASCII 1047
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
428
40.9%
, 81
 
7.7%
) 79
 
7.5%
( 79
 
7.5%
2 79
 
7.5%
1 63
 
6.0%
3 41
 
3.9%
0 41
 
3.9%
5 38
 
3.6%
6 30
 
2.9%
Other values (6) 88
 
8.4%
Hangul
ValueCountFrequency (%)
동 106
 
7.5%
양 85
 
6.0%
서 82
 
5.8%
천 81
 
5.8%
로 81
 
5.8%
울 79
 
5.6%
구 79
 
5.6%
시 79
 
5.6%
별 79
 
5.6%
특 79
 
5.6%
Other values (79) 576
41.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct49
Distinct (%)62.0%
Missing33
Missing (%)29.5%
Infinite0
Infinite (%)0.0%
Mean11798.861
Minimum7904
Maximum158860
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-18T11:17:51.911972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7904
5-th percentile7908.7
Q17943
median7968
Q38025.5
95-th percentile8068.5
Maximum158860
Range150956
Interquartile range (IQR)82.5

Descriptive statistics

Standard deviation23851.491
Coefficient of variation (CV)2.021508
Kurtosis36.894753
Mean11798.861
Median Absolute Deviation (MAD)46
Skewness6.1612398
Sum932110
Variance5.6889362 × 108
MonotonicityNot monotonic
2024-05-18T11:17:52.535041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
7945 4
 
3.6%
7968 4
 
3.6%
7951 3
 
2.7%
8044 3
 
2.7%
8019 3
 
2.7%
8047 3
 
2.7%
7966 2
 
1.8%
7923 2
 
1.8%
7944 2
 
1.8%
7959 2
 
1.8%
Other values (39) 51
45.5%
(Missing) 33
29.5%
ValueCountFrequency (%)
7904 2
1.8%
7906 2
1.8%
7909 1
0.9%
7911 1
0.9%
7912 1
0.9%
7913 1
0.9%
7915 1
0.9%
7918 1
0.9%
7921 1
0.9%
7923 2
1.8%
ValueCountFrequency (%)
158860 1
 
0.9%
158847 1
 
0.9%
8073 2
1.8%
8068 1
 
0.9%
8067 1
 
0.9%
8047 3
2.7%
8045 1
 
0.9%
8044 3
2.7%
8040 2
1.8%
8031 1
 
0.9%

사업장명
Text

Distinct105
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-05-18T11:17:53.243396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length14
Mean length7.6696429
Min length2

Characters and Unicode

Total characters859
Distinct characters215
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

Unique99 ?
Unique (%)88.4%

Sample

1st row신양환경
2nd row청우환경엔지니어링
3rd row신목실업
4th row대성기업
5th row서광엔지니어링
ValueCountFrequency (%)
주식회사 9
 
6.5%
제로벅스 3
 
2.2%
인터폴라인 2
 
1.4%
대성산업 2
 
1.4%
보눔172 2
 
1.4%
하은장애인보호작업장 2
 
1.4%
드림장애인 2
 
1.4%
드림장애인보호작업장 2
 
1.4%
주)바이오미스트테크놀로지 2
 
1.4%
엘 1
 
0.7%
Other values (111) 111
80.4%
2024-05-18T11:17:54.606179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 43
 
5.0%
) 38
 
4.4%
( 37
 
4.3%
스 28
 
3.3%
26
 
3.0%
이 19
 
2.2%
에 18
 
2.1%
경 17
 
2.0%
환 17
 
2.0%
업 15
 
1.7%
Other values (205) 601
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 701
81.6%
Close Punctuation 38
 
4.4%
Open Punctuation 37
 
4.3%
Space Separator 26
 
3.0%
Lowercase Letter 23
 
2.7%
Uppercase Letter 21
 
2.4%
Decimal Number 10
 
1.2%
Other Punctuation 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 43
 
6.1%
스 28
 
4.0%
이 19
 
2.7%
에 18
 
2.6%
경 17
 
2.4%
환 17
 
2.4%
업 15
 
2.1%
사 13
 
1.9%
인 13
 
1.9%
장 13
 
1.9%
Other values (170) 505
72.0%
Uppercase Letter
ValueCountFrequency (%)
S 5
23.8%
C 4
19.0%
O 2
 
9.5%
F 2
 
9.5%
H 1
 
4.8%
E 1
 
4.8%
T 1
 
4.8%
V 1
 
4.8%
L 1
 
4.8%
I 1
 
4.8%
Other values (2) 2
 
9.5%
Lowercase Letter
ValueCountFrequency (%)
n 4
17.4%
e 3
13.0%
a 3
13.0%
o 3
13.0%
t 2
8.7%
l 2
8.7%
s 1
 
4.3%
i 1
 
4.3%
u 1
 
4.3%
y 1
 
4.3%
Other values (2) 2
8.7%
Decimal Number
ValueCountFrequency (%)
1 4
40.0%
2 2
20.0%
7 2
20.0%
9 1
 
10.0%
5 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
, 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 701
81.6%
Common 114
 
13.3%
Latin 44
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 43
 
6.1%
스 28
 
4.0%
이 19
 
2.7%
에 18
 
2.6%
경 17
 
2.4%
환 17
 
2.4%
업 15
 
2.1%
사 13
 
1.9%
인 13
 
1.9%
장 13
 
1.9%
Other values (170) 505
72.0%
Latin
ValueCountFrequency (%)
S 5
 
11.4%
n 4
 
9.1%
C 4
 
9.1%
e 3
 
6.8%
a 3
 
6.8%
o 3
 
6.8%
O 2
 
4.5%
t 2
 
4.5%
F 2
 
4.5%
l 2
 
4.5%
Other values (14) 14
31.8%
Common
ValueCountFrequency (%)
) 38
33.3%
( 37
32.5%
26
22.8%
1 4
 
3.5%
2 2
 
1.8%
7 2
 
1.8%
- 1
 
0.9%
9 1
 
0.9%
& 1
 
0.9%
, 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 701
81.6%
ASCII 158
 
18.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 43
 
6.1%
스 28
 
4.0%
이 19
 
2.7%
에 18
 
2.6%
경 17
 
2.4%
환 17
 
2.4%
업 15
 
2.1%
사 13
 
1.9%
인 13
 
1.9%
장 13
 
1.9%
Other values (170) 505
72.0%
ASCII
ValueCountFrequency (%)
) 38
24.1%
( 37
23.4%
26
16.5%
S 5
 
3.2%
n 4
 
2.5%
1 4
 
2.5%
C 4
 
2.5%
e 3
 
1.9%
a 3
 
1.9%
o 3
 
1.9%
Other values (25) 31
19.6%

최종수정일자
Date

UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2009-02-04 14:36:23
Maximum2024-05-03 09:19:36
2024-05-18T11:17:55.153028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:17:55.602082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
I
62 
U
50 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 62
55.4%
U 50
44.6%

Length

2024-05-18T11:17:56.142893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:17:56.547490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 62
55.4%
u 50
44.6%

데이터갱신일자
Categorical

Distinct50
Distinct (%)44.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2018-08-31 23:59:59.0
48 
2023-12-01 23:07:00.0
8 
2020-05-17 02:40:00.0
 
4
2022-10-31 22:02:00.0
 
3
2021-12-06 21:01:00.0
 
3
Other values (45)
46 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique44 ?
Unique (%)39.3%

Sample

1st row2020-05-17 02:40:00.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 48
42.9%
2023-12-01 23:07:00.0 8
 
7.1%
2020-05-17 02:40:00.0 4
 
3.6%
2022-10-31 22:02:00.0 3
 
2.7%
2021-12-06 21:01:00.0 3
 
2.7%
2022-12-04 00:01:00.0 2
 
1.8%
2019-12-20 02:40:00.0 1
 
0.9%
2022-12-04 22:00:00.0 1
 
0.9%
2020-07-11 02:40:00.0 1
 
0.9%
2022-11-01 00:09:00.0 1
 
0.9%
Other values (40) 40
35.7%

Length

2024-05-18T11:17:56.849432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 48
21.4%
23:59:59.0 48
21.4%
02:40:00.0 17
 
7.6%
2023-12-01 9
 
4.0%
23:07:00.0 8
 
3.6%
2022-12-04 7
 
3.1%
2020-05-17 4
 
1.8%
2022-10-31 4
 
1.8%
00:03:00.0 3
 
1.3%
21:01:00.0 3
 
1.3%
Other values (57) 73
32.6%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing112
Missing (%)100.0%
Memory size1.1 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct93
Distinct (%)84.5%
Missing2
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean186871.37
Minimum184480.43
Maximum189471.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-18T11:17:57.279476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184480.43
5-th percentile184674.21
Q1185585.99
median186959.44
Q3188043.22
95-th percentile189006.47
Maximum189471.31
Range4990.8756
Interquartile range (IQR)2457.2332

Descriptive statistics

Standard deviation1436.5783
Coefficient of variation (CV)0.0076875248
Kurtosis-1.3501891
Mean186871.37
Median Absolute Deviation (MAD)1249.086
Skewness-0.037802329
Sum20555850
Variance2063757.1
MonotonicityNot monotonic
2024-05-18T11:17:57.929579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186190.93277167 3
 
2.7%
186815.334742178 3
 
2.7%
185585.990207369 3
 
2.7%
186404.624501079 2
 
1.8%
187823.500716444 2
 
1.8%
188500.733025206 2
 
1.8%
188461.516715604 2
 
1.8%
188856.382588409 2
 
1.8%
186990.07041522 2
 
1.8%
185709.027776001 2
 
1.8%
Other values (83) 87
77.7%
ValueCountFrequency (%)
184480.430654989 1
0.9%
184487.420583541 1
0.9%
184534.619036954 1
0.9%
184597.4496425 1
0.9%
184600.000868726 1
0.9%
184660.287184411 1
0.9%
184691.221778064 1
0.9%
184740.746613572 1
0.9%
184817.116668717 1
0.9%
184829.306182525 1
0.9%
ValueCountFrequency (%)
189471.306217651 1
0.9%
189111.004325166 1
0.9%
189086.853406906 1
0.9%
189055.134431663 1
0.9%
189040.442771323 1
0.9%
189039.009553549 1
0.9%
188966.690254394 1
0.9%
188953.066831076 1
0.9%
188868.78715669 1
0.9%
188856.382588409 2
1.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct93
Distinct (%)84.5%
Missing2
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean447324.57
Minimum445142.77
Maximum449789.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-18T11:17:58.522684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445142.77
5-th percentile445951.7
Q1446433.05
median447165.24
Q3448159.48
95-th percentile449366.63
Maximum449789.61
Range4646.8484
Interquartile range (IQR)1726.4316

Descriptive statistics

Standard deviation1081.8133
Coefficient of variation (CV)0.0024184079
Kurtosis-0.62882741
Mean447324.57
Median Absolute Deviation (MAD)809.04982
Skewness0.44930042
Sum49205703
Variance1170320
MonotonicityNot monotonic
2024-05-18T11:17:59.022996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447184.78769802 3
 
2.7%
446802.011933695 3
 
2.7%
446145.094734253 3
 
2.7%
446729.087344494 2
 
1.8%
447457.457884414 2
 
1.8%
446194.793236919 2
 
1.8%
448558.954668746 2
 
1.8%
446521.667758735 2
 
1.8%
446176.810389121 2
 
1.8%
445951.697820822 2
 
1.8%
Other values (83) 87
77.7%
ValueCountFrequency (%)
445142.765 1
0.9%
445524.71062635 1
0.9%
445569.639465968 1
0.9%
445825.399064037 1
0.9%
445919.573406457 1
0.9%
445951.697820822 2
1.8%
445963.474381391 1
0.9%
445983.252020472 1
0.9%
446031.910289416 1
0.9%
446070.262510721 1
0.9%
ValueCountFrequency (%)
449789.613381329 1
0.9%
449774.340142666 1
0.9%
449450.025953076 1
0.9%
449386.014108408 1
0.9%
449383.141430143 1
0.9%
449368.064325061 1
0.9%
449364.88554612 1
0.9%
449338.07750047 1
0.9%
449204.635182585 2
1.8%
449058.137600103 1
0.9%

사무실면적
Real number (ℝ)

MISSING 

Distinct58
Distinct (%)90.6%
Missing48
Missing (%)42.9%
Infinite0
Infinite (%)0.0%
Mean45.645781
Minimum2.9
Maximum215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-18T11:17:59.591143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.9
5-th percentile9.762
Q117.5
median30.625
Q355.3375
95-th percentile121.35
Maximum215
Range212.1
Interquartile range (IQR)37.8375

Descriptive statistics

Standard deviation42.569647
Coefficient of variation (CV)0.93260858
Kurtosis4.500877
Mean45.645781
Median Absolute Deviation (MAD)18.75
Skewness2.0076035
Sum2921.33
Variance1812.1749
MonotonicityNot monotonic
2024-05-18T11:18:00.103865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51.0 2
 
1.8%
25.35 2
 
1.8%
20.0 2
 
1.8%
25.0 2
 
1.8%
30.0 2
 
1.8%
16.0 2
 
1.8%
59.5 1
 
0.9%
8.0 1
 
0.9%
50.0 1
 
0.9%
10.26 1
 
0.9%
Other values (48) 48
42.9%
(Missing) 48
42.9%
ValueCountFrequency (%)
2.9 1
0.9%
4.35 1
0.9%
8.0 1
0.9%
9.72 1
0.9%
10.0 1
0.9%
10.24 1
0.9%
10.26 1
0.9%
10.6 1
0.9%
10.97 1
0.9%
12.0 1
0.9%
ValueCountFrequency (%)
215.0 1
0.9%
176.0 1
0.9%
165.0 1
0.9%
123.0 1
0.9%
112.0 1
0.9%
108.9 1
0.9%
105.0 1
0.9%
92.62 1
0.9%
87.0 1
0.9%
85.0 1
0.9%

소독차량차고면적
Real number (ℝ)

MISSING 

Distinct51
Distinct (%)79.7%
Missing48
Missing (%)42.9%
Infinite0
Infinite (%)0.0%
Mean24.222344
Minimum1.02
Maximum165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-18T11:18:00.580585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.02
5-th percentile2.4875
Q16.95
median15
Q321.1825
95-th percentile73.34
Maximum165
Range163.98
Interquartile range (IQR)14.2325

Descriptive statistics

Standard deviation33.759507
Coefficient of variation (CV)1.3937341
Kurtosis9.1833901
Mean24.222344
Median Absolute Deviation (MAD)7.86
Skewness2.9858006
Sum1550.23
Variance1139.7043
MonotonicityNot monotonic
2024-05-18T11:18:01.093074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.0 3
 
2.7%
3.6 3
 
2.7%
21.0 2
 
1.8%
7.28 2
 
1.8%
17.0 2
 
1.8%
15.0 2
 
1.8%
19.0 2
 
1.8%
30.0 2
 
1.8%
150.0 2
 
1.8%
20.0 2
 
1.8%
Other values (41) 42
37.5%
(Missing) 48
42.9%
ValueCountFrequency (%)
1.02 1
 
0.9%
1.95 1
 
0.9%
2.32 1
 
0.9%
2.45 1
 
0.9%
2.7 1
 
0.9%
2.8 1
 
0.9%
3.1 1
 
0.9%
3.12 1
 
0.9%
3.6 3
2.7%
3.78 1
 
0.9%
ValueCountFrequency (%)
165.0 1
0.9%
150.0 2
1.8%
73.4 1
0.9%
73.0 2
1.8%
66.0 1
0.9%
42.9 1
0.9%
38.62 1
0.9%
32.5 1
0.9%
32.0 1
0.9%
30.75 1
0.9%

초미립자살포기수
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)10.0%
Missing42
Missing (%)37.5%
Infinite0
Infinite (%)0.0%
Mean1.6428571
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-18T11:18:01.462718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile4.65
Maximum20
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.6045429
Coefficient of variation (CV)1.585374
Kurtosis37.298039
Mean1.6428571
Median Absolute Deviation (MAD)0
Skewness5.7500691
Sum115
Variance6.7836439
MonotonicityNot monotonic
2024-05-18T11:18:02.263948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 61
54.5%
2 3
 
2.7%
3 2
 
1.8%
20 1
 
0.9%
9 1
 
0.9%
6 1
 
0.9%
7 1
 
0.9%
(Missing) 42
37.5%
ValueCountFrequency (%)
1 61
54.5%
2 3
 
2.7%
3 2
 
1.8%
6 1
 
0.9%
7 1
 
0.9%
9 1
 
0.9%
20 1
 
0.9%
ValueCountFrequency (%)
20 1
 
0.9%
9 1
 
0.9%
7 1
 
0.9%
6 1
 
0.9%
3 2
 
1.8%
2 3
 
2.7%
1 61
54.5%

휴대용소독기수
Categorical

Distinct5
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2
66 
<NA>
42 
10
 
2
3
 
1
4
 
1

Length

Max length4
Median length1
Mean length2.1428571
Min length1

Unique

Unique2 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
2 66
58.9%
<NA> 42
37.5%
10 2
 
1.8%
3 1
 
0.9%
4 1
 
0.9%

Length

2024-05-18T11:18:03.119533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:18:03.560837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 66
58.9%
na 42
37.5%
10 2
 
1.8%
3 1
 
0.9%
4 1
 
0.9%

동력분무기수
Categorical

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
1
49 
<NA>
42 
0
21 

Length

Max length4
Median length1
Mean length2.125
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 49
43.8%
<NA> 42
37.5%
0 21
18.8%

Length

2024-05-18T11:18:04.032180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:18:04.426496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 49
43.8%
na 42
37.5%
0 21
18.8%

수동식분무기수
Categorical

Distinct6
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
5
48 
<NA>
42 
3
15 
10
 
3
4
 
3

Length

Max length4
Median length1
Mean length2.1517857
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
5 48
42.9%
<NA> 42
37.5%
3 15
 
13.4%
10 3
 
2.7%
4 3
 
2.7%
7 1
 
0.9%

Length

2024-05-18T11:18:04.998280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:18:05.466705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 48
42.9%
na 42
37.5%
3 15
 
13.4%
10 3
 
2.7%
4 3
 
2.7%
7 1
 
0.9%

방독면수
Categorical

Distinct5
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
5
66 
<NA>
42 
6
 
2
10
 
1
11
 
1

Length

Max length4
Median length1
Mean length2.1428571
Min length1

Unique

Unique2 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
5 66
58.9%
<NA> 42
37.5%
6 2
 
1.8%
10 1
 
0.9%
11 1
 
0.9%

Length

2024-05-18T11:18:06.007342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:18:06.423552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 66
58.9%
na 42
37.5%
6 2
 
1.8%
10 1
 
0.9%
11 1
 
0.9%

보호안경수
Categorical

IMBALANCE 

Distinct5
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
5
67 
<NA>
42 
6
 
1
10
 
1
11
 
1

Length

Max length4
Median length1
Mean length2.1428571
Min length1

Unique

Unique3 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
5 67
59.8%
<NA> 42
37.5%
6 1
 
0.9%
10 1
 
0.9%
11 1
 
0.9%

Length

2024-05-18T11:18:06.972603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:18:07.359114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 67
59.8%
na 42
37.5%
6 1
 
0.9%
10 1
 
0.9%
11 1
 
0.9%

보호용의복수
Categorical

IMBALANCE 

Distinct6
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
5
66 
<NA>
42 
7
 
1
11
 
1
6
 
1

Length

Max length4
Median length1
Mean length2.1428571
Min length1

Unique

Unique4 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
5 66
58.9%
<NA> 42
37.5%
7 1
 
0.9%
11 1
 
0.9%
6 1
 
0.9%
40 1
 
0.9%

Length

2024-05-18T11:18:07.872262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:18:08.366252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 66
58.9%
na 42
37.5%
7 1
 
0.9%
11 1
 
0.9%
6 1
 
0.9%
40 1
 
0.9%

진공청소기수
Categorical

Distinct4
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
1
64 
<NA>
42 
2
 
5
3
 
1

Length

Max length4
Median length1
Mean length2.125
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
1 64
57.1%
<NA> 42
37.5%
2 5
 
4.5%
3 1
 
0.9%

Length

2024-05-18T11:18:08.788161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:18:09.356440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 64
57.1%
na 42
37.5%
2 5
 
4.5%
3 1
 
0.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무실면적소독차량차고면적초미립자살포기수휴대용소독기수동력분무기수수동식분무기수방독면수보호안경수보호용의복수진공청소기수
03140000PHMB51999314003304250000119961118<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2607-1125<NA><NA>서울특별시 양천구 신월동 507번지 11호 2층서울특별시 양천구 신월로27길 6, 2층 (신월동)8028신양환경2020-05-15 16:16:40U2020-05-17 02:40:00.0<NA>186404.624501446729.08734420.016.012155551
13140000PHMB51999314003304250000219991206<NA>3폐업3폐업20101021<NA><NA><NA>2646 0700<NA>158050서울특별시 양천구 목동 405번지 222호<NA><NA>청우환경엔지니어링2012-02-20 19:19:10I2018-08-31 23:59:59.0<NA>188630.994729446833.8660130.7530.7512155551
23140000PHMB51999314003304250000319861020<NA>3폐업3폐업20020116<NA><NA><NA>2646 3957<NA>158050서울특별시 양천구 목동 404번지 108호<NA><NA>신목실업2009-02-05 13:07:51I2018-08-31 23:59:59.0<NA>189086.853407446779.943272<NA><NA>12155551
33140000PHMB51999314003304250000419901207<NA>3폐업3폐업20040726<NA><NA><NA>2651 2780<NA>158050서울특별시 양천구 목동 794번지 14호<NA><NA>대성기업2009-02-05 13:09:16I2018-08-31 23:59:59.0<NA>187964.653965447726.90939830.019.012155551
43140000PHMB51999314003304250000519921030<NA>3폐업3폐업19990915<NA><NA><NA>2654 4394<NA>158050서울특별시 양천구 목동 775번지 25호<NA><NA>서광엔지니어링2009-02-05 13:11:05I2018-08-31 23:59:59.0<NA>188188.85048447909.48399116.019.012155551
53140000PHMB51999314003304250000619990519<NA>3폐업3폐업20001020<NA><NA><NA>2692 7052<NA>158090서울특별시 양천구 신월동 547번지 10호<NA><NA>대양기업2009-02-05 13:11:51I2018-08-31 23:59:59.0<NA>185762.865323446144.142326176.021.012155551
63140000PHMB51999314003304250000719931214<NA>3폐업3폐업20001127<NA><NA><NA>2648 3070<NA>158070서울특별시 양천구 신정동 294번지 5호<NA><NA>영보환경2009-02-05 13:12:49I2018-08-31 23:59:59.0<NA>188655.224736446191.18010434.4515.3612155551
73140000PHMB51999314003304250000819970203<NA>3폐업3폐업20010919<NA><NA><NA>2602 0340<NA>158090서울특별시 양천구 신월동 28번지 6호<NA><NA>한그린환경2009-02-05 13:15:49I2018-08-31 23:59:59.0<NA>184597.449642448604.97702418.017.012155551
83140000PHMB51999314003304250000919970620<NA>3폐업3폐업20060406<NA><NA><NA>2692-8706<NA>158090서울특별시 양천구 신월동 22번지 19호<NA><NA>수림방역2009-02-05 13:16:41I2018-08-31 23:59:59.0<NA>185203.15421448733.20885516.015.012155551
93140000PHMB51999314003304250001019991117<NA>3폐업3폐업20060220<NA><NA><NA>2602 4178<NA>158070서울특별시 양천구 신정동 743번지 3호 2층1호<NA><NA>대양환경개발2009-02-04 14:36:23I2018-08-31 23:59:59.0<NA>185915.21445142.76526.014.012155551
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