Overview

Dataset statistics

Number of variables25
Number of observations73
Missing cells224
Missing cells (%)12.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.5 KiB
Average record size in memory216.8 B

Variable types

Text5
DateTime2
Categorical10
Numeric8

Dataset

Description이 데이터는 서울특별시 동작구의 전염병 및 각종 세균이나 유해 해충의 소독을 목적으로 만들어진 업소정보를 표현하고 있습니다. 좌표안내 : 중부원점 TM(EPSG:2097) 좌표계에 따른 해당위치의 좌표정보이며 위경도 좌표는 제공하고 있지 않습니다. 본 데이터는 3일전 자료를 제공합니다.
Author서울특별시 동작구
URLhttps://www.data.go.kr/data/15094598/fileData.do

Alerts

폐업일자 has 50 (68.5%) missing valuesMissing
전화번호 has 25 (34.2%) missing valuesMissing
소재지우편번호 has 44 (60.3%) missing valuesMissing
지번주소 has 4 (5.5%) missing valuesMissing
도로명주소 has 2 (2.7%) missing valuesMissing
최종수정일자 has 3 (4.1%) missing valuesMissing
좌표정보(X) has 1 (1.4%) missing valuesMissing
소독차량차고면적 has 25 (34.2%) missing valuesMissing
초미립자살포기수 has 24 (32.9%) missing valuesMissing
수동식분무기수 has 23 (31.5%) missing valuesMissing
진공청소기수 has 23 (31.5%) missing valuesMissing
관리번호 has unique valuesUnique
수동식분무기수 has 13 (17.8%) zerosZeros

Reproduction

Analysis started2023-12-12 10:11:36.390096
Analysis finished2023-12-12 10:11:36.912138
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-12T19:11:37.097875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1825
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

Unique73 ?
Unique (%)100.0%

Sample

1st rowPHMB519873190033042500003
2nd rowPHMB519873190033042500004
3rd rowPHMB519873190033042500005
4th rowPHMB519943190033042500001
5th rowPHMB519973190033042500001
ValueCountFrequency (%)
phmb519873190033042500003 1
 
1.4%
phmb520153190033042500001 1
 
1.4%
phmb520203190033042500007 1
 
1.4%
phmb520203190033042500006 1
 
1.4%
phmb520203190033042500005 1
 
1.4%
phmb520203190033042500004 1
 
1.4%
phmb520203190033042500003 1
 
1.4%
phmb520203190033042500002 1
 
1.4%
phmb520203190033042500001 1
 
1.4%
phmb520193190033042500001 1
 
1.4%
Other values (63) 63
86.3%
2023-12-12T19:11:37.457429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 615
33.7%
3 233
 
12.8%
2 186
 
10.2%
5 153
 
8.4%
1 138
 
7.6%
9 91
 
5.0%
4 84
 
4.6%
P 73
 
4.0%
H 73
 
4.0%
M 73
 
4.0%
Other values (4) 106
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1533
84.0%
Uppercase Letter 292
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 615
40.1%
3 233
 
15.2%
2 186
 
12.1%
5 153
 
10.0%
1 138
 
9.0%
9 91
 
5.9%
4 84
 
5.5%
7 14
 
0.9%
8 11
 
0.7%
6 8
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
P 73
25.0%
H 73
25.0%
M 73
25.0%
B 73
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1533
84.0%
Latin 292
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 615
40.1%
3 233
 
15.2%
2 186
 
12.1%
5 153
 
10.0%
1 138
 
9.0%
9 91
 
5.9%
4 84
 
5.5%
7 14
 
0.9%
8 11
 
0.7%
6 8
 
0.5%
Latin
ValueCountFrequency (%)
P 73
25.0%
H 73
25.0%
M 73
25.0%
B 73
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 615
33.7%
3 233
 
12.8%
2 186
 
10.2%
5 153
 
8.4%
1 138
 
7.6%
9 91
 
5.0%
4 84
 
4.6%
P 73
 
4.0%
H 73
 
4.0%
M 73
 
4.0%
Other values (4) 106
 
5.8%

인허가일자
Date

Distinct72
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size716.0 B
Minimum1987-01-23 00:00:00
Maximum2021-10-15 00:00:00
2023-12-12T19:11:37.645533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:11:37.793192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태코드
Categorical

Distinct4
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
1
48 
3
18 
4
5 
5
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row1
3rd row3
4th row1
5th row4

Common Values

ValueCountFrequency (%)
1 48
65.8%
3 18
 
24.7%
4 5
 
6.8%
5 2
 
2.7%

Length

2023-12-12T19:11:37.920958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:38.044595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 48
65.8%
3 18
 
24.7%
4 5
 
6.8%
5 2
 
2.7%

영업상태명
Categorical

Distinct4
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
영업/정상
48 
폐업
18 
취소/말소/만료/정지/중지
5 
제외/삭제/전출
 
2

Length

Max length14
Median length5
Mean length4.9589041
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제외/삭제/전출
2nd row영업/정상
3rd row폐업
4th row영업/정상
5th row취소/말소/만료/정지/중지

Common Values

ValueCountFrequency (%)
영업/정상 48
65.8%
폐업 18
 
24.7%
취소/말소/만료/정지/중지 5
 
6.8%
제외/삭제/전출 2
 
2.7%

Length

2023-12-12T19:11:38.153861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:38.259644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 48
65.8%
폐업 18
 
24.7%
취소/말소/만료/정지/중지 5
 
6.8%
제외/삭제/전출 2
 
2.7%

상세영업상태코드
Categorical

Distinct4
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
13
48 
3
18 
24
5 
15
 
2

Length

Max length2
Median length2
Mean length1.7534247
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15
2nd row13
3rd row3
4th row13
5th row24

Common Values

ValueCountFrequency (%)
13 48
65.8%
3 18
 
24.7%
24 5
 
6.8%
15 2
 
2.7%

Length

2023-12-12T19:11:38.381963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:38.486429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 48
65.8%
3 18
 
24.7%
24 5
 
6.8%
15 2
 
2.7%

상세영업상태명
Categorical

Distinct4
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
영업중
48 
폐업
18 
직권폐업
5 
전출
 
2

Length

Max length4
Median length3
Mean length2.7945205
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 48
65.8%
폐업 18
 
24.7%
직권폐업 5
 
6.8%
전출 2
 
2.7%

Length

2023-12-12T19:11:38.610075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:38.751022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 48
65.8%
폐업 18
 
24.7%
직권폐업 5
 
6.8%
전출 2
 
2.7%

폐업일자
Date

MISSING 

Distinct22
Distinct (%)95.7%
Missing50
Missing (%)68.5%
Memory size716.0 B
Minimum2010-01-11 00:00:00
Maximum2021-04-08 00:00:00
2023-12-12T19:11:38.857351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:11:38.974757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

전화번호
Text

MISSING 

Distinct47
Distinct (%)97.9%
Missing25
Missing (%)34.2%
Memory size716.0 B
2023-12-12T19:11:39.205161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.229167
Min length11

Characters and Unicode

Total characters539
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

Unique46 ?
Unique (%)95.8%

Sample

1st row02-826-0055
2nd row02-823-1311
3rd row02-812-5167
4th row02-816-3107
5th row02-813-7092
ValueCountFrequency (%)
02-3471-7535 2
 
4.2%
02-3280-7350 1
 
2.1%
02-826-0055 1
 
2.1%
02-3473-1280 1
 
2.1%
02-822-7707 1
 
2.1%
02-823-8635 1
 
2.1%
02-583-4653 1
 
2.1%
02-883-5951 1
 
2.1%
02-828-3945 1
 
2.1%
02-2217-2181 1
 
2.1%
Other values (37) 37
77.1%
2023-12-12T19:11:39.620593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 96
17.8%
2 88
16.3%
0 82
15.2%
8 59
10.9%
1 42
7.8%
5 40
7.4%
3 38
 
7.1%
7 28
 
5.2%
4 27
 
5.0%
9 21
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 443
82.2%
Dash Punctuation 96
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 88
19.9%
0 82
18.5%
8 59
13.3%
1 42
9.5%
5 40
9.0%
3 38
8.6%
7 28
 
6.3%
4 27
 
6.1%
9 21
 
4.7%
6 18
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 539
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 96
17.8%
2 88
16.3%
0 82
15.2%
8 59
10.9%
1 42
7.8%
5 40
7.4%
3 38
 
7.1%
7 28
 
5.2%
4 27
 
5.0%
9 21
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 539
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 96
17.8%
2 88
16.3%
0 82
15.2%
8 59
10.9%
1 42
7.8%
5 40
7.4%
3 38
 
7.1%
7 28
 
5.2%
4 27
 
5.0%
9 21
 
3.9%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)82.8%
Missing44
Missing (%)60.3%
Infinite0
Infinite (%)0.0%
Mean156314.83
Minimum156010
Maximum156879
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T19:11:39.851868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum156010
5-th percentile156012
Q1156033
median156090
Q3156808
95-th percentile156834.8
Maximum156879
Range869
Interquartile range (IQR)775

Descriptive statistics

Standard deviation369.95927
Coefficient of variation (CV)0.0023667574
Kurtosis-1.6038947
Mean156314.83
Median Absolute Deviation (MAD)70
Skewness0.68507934
Sum4533130
Variance136869.86
MonotonicityNot monotonic
2023-12-12T19:11:40.008752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
156090 3
 
4.1%
156020 3
 
4.1%
156012 2
 
2.7%
156033 1
 
1.4%
156095 1
 
1.4%
156823 1
 
1.4%
156713 1
 
1.4%
156093 1
 
1.4%
156840 1
 
1.4%
156800 1
 
1.4%
Other values (14) 14
 
19.2%
(Missing) 44
60.3%
ValueCountFrequency (%)
156010 1
 
1.4%
156012 2
2.7%
156020 3
4.1%
156030 1
 
1.4%
156033 1
 
1.4%
156035 1
 
1.4%
156051 1
 
1.4%
156052 1
 
1.4%
156070 1
 
1.4%
156080 1
 
1.4%
ValueCountFrequency (%)
156879 1
1.4%
156840 1
1.4%
156827 1
1.4%
156823 1
1.4%
156819 1
1.4%
156816 1
1.4%
156811 1
1.4%
156808 1
1.4%
156800 1
1.4%
156713 1
1.4%

지번주소
Text

MISSING 

Distinct68
Distinct (%)98.6%
Missing4
Missing (%)5.5%
Memory size716.0 B
2023-12-12T19:11:40.306200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length26.26087
Min length18

Characters and Unicode

Total characters1812
Distinct characters103
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)97.1%

Sample

1st row서울특별시 동작구 흑석동 98번지 1호
2nd row서울특별시 동작구 대방동 339번지 1호 솔표빌딩 3층
3rd row서울특별시 동작구 상도5동 175번지 9호
4th row서울특별시 동작구 상도동 363번지 142호
5th row서울특별시 동작구 노량진2동 240번지 25호
ValueCountFrequency (%)
서울특별시 69
 
18.4%
동작구 69
 
18.4%
대방동 14
 
3.7%
사당동 11
 
2.9%
신대방동 8
 
2.1%
상도동 8
 
2.1%
2호 6
 
1.6%
6
 
1.6%
1호 5
 
1.3%
노량진동 5
 
1.3%
Other values (135) 175
46.5%
2023-12-12T19:11:40.796211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
309
 
17.1%
동 140
 
7.7%
2 73
 
4.0%
구 70
 
3.9%
작 70
 
3.9%
울 70
 
3.9%
시 70
 
3.9%
별 69
 
3.8%
특 69
 
3.8%
서 69
 
3.8%
Other values (93) 803
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1101
60.8%
Decimal Number 349
 
19.3%
Space Separator 309
 
17.1%
Other Punctuation 31
 
1.7%
Dash Punctuation 17
 
0.9%
Open Punctuation 3
 
0.2%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 140
 
12.7%
구 70
 
6.4%
작 70
 
6.4%
울 70
 
6.4%
시 70
 
6.4%
별 69
 
6.3%
특 69
 
6.3%
서 69
 
6.3%
호 57
 
5.2%
지 57
 
5.2%
Other values (78) 360
32.7%
Decimal Number
ValueCountFrequency (%)
2 73
20.9%
1 68
19.5%
3 46
13.2%
4 39
11.2%
0 27
 
7.7%
9 25
 
7.2%
6 24
 
6.9%
5 24
 
6.9%
7 13
 
3.7%
8 10
 
2.9%
Space Separator
ValueCountFrequency (%)
309
100.0%
Other Punctuation
ValueCountFrequency (%)
* 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1101
60.8%
Common 711
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 140
 
12.7%
구 70
 
6.4%
작 70
 
6.4%
울 70
 
6.4%
시 70
 
6.4%
별 69
 
6.3%
특 69
 
6.3%
서 69
 
6.3%
호 57
 
5.2%
지 57
 
5.2%
Other values (78) 360
32.7%
Common
ValueCountFrequency (%)
309
43.5%
2 73
 
10.3%
1 68
 
9.6%
3 46
 
6.5%
4 39
 
5.5%
* 31
 
4.4%
0 27
 
3.8%
9 25
 
3.5%
6 24
 
3.4%
5 24
 
3.4%
Other values (5) 45
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1101
60.8%
ASCII 711
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
309
43.5%
2 73
 
10.3%
1 68
 
9.6%
3 46
 
6.5%
4 39
 
5.5%
* 31
 
4.4%
0 27
 
3.8%
9 25
 
3.5%
6 24
 
3.4%
5 24
 
3.4%
Other values (5) 45
 
6.3%
Hangul
ValueCountFrequency (%)
동 140
 
12.7%
구 70
 
6.4%
작 70
 
6.4%
울 70
 
6.4%
시 70
 
6.4%
별 69
 
6.3%
특 69
 
6.3%
서 69
 
6.3%
호 57
 
5.2%
지 57
 
5.2%
Other values (78) 360
32.7%

도로명주소
Text

MISSING 

Distinct69
Distinct (%)97.2%
Missing2
Missing (%)2.7%
Memory size716.0 B
2023-12-12T19:11:41.189458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length22.549296
Min length8

Characters and Unicode

Total characters1601
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

Unique67 ?
Unique (%)94.4%

Sample

1st row서울특별시 동작구 서달로14가길 20 (흑석동)
2nd row서울특별시 동작구 노량진로 26 (대방동솔표빌딩 3층)
3rd row서울특별시 동작구 장승배기로10가길 15 (상도동)
4th row서울특별시 동작구 상도로15길 143 4층 408호 (상도동)
5th row 서울특별시 동작구 국사봉길 74 (상도동 지하1층)
ValueCountFrequency (%)
서울특별시 70
21.3%
동작구 70
21.3%
사당동 10
 
3.0%
7
 
2.1%
신대방동 6
 
1.8%
상도동 5
 
1.5%
사당로 4
 
1.2%
9 3
 
0.9%
장승배기로 3
 
0.9%
26 3
 
0.9%
Other values (118) 147
44.8%
2023-12-12T19:11:41.746545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
258
 
16.1%
동 114
 
7.1%
작 77
 
4.8%
서 73
 
4.6%
구 70
 
4.4%
울 70
 
4.4%
시 70
 
4.4%
별 70
 
4.4%
특 70
 
4.4%
로 66
 
4.1%
Other values (73) 663
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1029
64.3%
Space Separator 258
 
16.1%
Decimal Number 222
 
13.9%
Open Punctuation 34
 
2.1%
Other Punctuation 26
 
1.6%
Close Punctuation 22
 
1.4%
Dash Punctuation 7
 
0.4%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 114
 
11.1%
작 77
 
7.5%
서 73
 
7.1%
구 70
 
6.8%
울 70
 
6.8%
시 70
 
6.8%
별 70
 
6.8%
특 70
 
6.8%
로 66
 
6.4%
길 43
 
4.2%
Other values (55) 306
29.7%
Decimal Number
ValueCountFrequency (%)
2 50
22.5%
1 41
18.5%
4 25
11.3%
8 21
9.5%
6 19
 
8.6%
3 16
 
7.2%
0 15
 
6.8%
5 13
 
5.9%
9 13
 
5.9%
7 9
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
258
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Other Punctuation
ValueCountFrequency (%)
* 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1029
64.3%
Common 569
35.5%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 114
 
11.1%
작 77
 
7.5%
서 73
 
7.1%
구 70
 
6.8%
울 70
 
6.8%
시 70
 
6.8%
별 70
 
6.8%
특 70
 
6.8%
로 66
 
6.4%
길 43
 
4.2%
Other values (55) 306
29.7%
Common
ValueCountFrequency (%)
258
45.3%
2 50
 
8.8%
1 41
 
7.2%
( 34
 
6.0%
* 26
 
4.6%
4 25
 
4.4%
) 22
 
3.9%
8 21
 
3.7%
6 19
 
3.3%
3 16
 
2.8%
Other values (5) 57
 
10.0%
Latin
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1029
64.3%
ASCII 572
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
258
45.1%
2 50
 
8.7%
1 41
 
7.2%
( 34
 
5.9%
* 26
 
4.5%
4 25
 
4.4%
) 22
 
3.8%
8 21
 
3.7%
6 19
 
3.3%
3 16
 
2.8%
Other values (8) 60
 
10.5%
Hangul
ValueCountFrequency (%)
동 114
 
11.1%
작 77
 
7.5%
서 73
 
7.1%
구 70
 
6.8%
울 70
 
6.8%
시 70
 
6.8%
별 70
 
6.8%
특 70
 
6.8%
로 66
 
6.4%
길 43
 
4.2%
Other values (55) 306
29.7%

사업장명
Text

Distinct69
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-12T19:11:42.022313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.5342466
Min length2

Characters and Unicode

Total characters550
Distinct characters167
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)89.0%

Sample

1st row홍익시설관리(주)
2nd row(주)순일기업
3rd row삼진방역공사
4th row대성방역공사
5th row(주)우신씨앤에스
ValueCountFrequency (%)
주식회사 7
 
8.0%
사단법인 2
 
2.3%
주)그린피아산업 2
 
2.3%
주)대명비엔엠 2
 
2.3%
디버그 2
 
2.3%
환경안전보건협회 2
 
2.3%
브라더크린 1
 
1.1%
주)와이즈비젼 1
 
1.1%
주)오케이빌스 1
 
1.1%
m&g환경개발 1
 
1.1%
Other values (67) 67
76.1%
2023-12-12T19:11:42.532024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 40
 
7.3%
( 32
 
5.8%
) 32
 
5.8%
사 17
 
3.1%
16
 
2.9%
스 15
 
2.7%
이 12
 
2.2%
회 11
 
2.0%
경 10
 
1.8%
린 10
 
1.8%
Other values (157) 355
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 453
82.4%
Open Punctuation 32
 
5.8%
Close Punctuation 32
 
5.8%
Space Separator 16
 
2.9%
Uppercase Letter 7
 
1.3%
Decimal Number 5
 
0.9%
Lowercase Letter 3
 
0.5%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 40
 
8.8%
사 17
 
3.8%
스 15
 
3.3%
이 12
 
2.6%
회 11
 
2.4%
경 10
 
2.2%
린 10
 
2.2%
환 9
 
2.0%
식 9
 
2.0%
리 8
 
1.8%
Other values (138) 312
68.9%
Uppercase Letter
ValueCountFrequency (%)
G 1
14.3%
M 1
14.3%
C 1
14.3%
N 1
14.3%
S 1
14.3%
F 1
14.3%
P 1
14.3%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
4 1
20.0%
5 1
20.0%
9 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
p 1
33.3%
i 1
33.3%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
＆ 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 453
82.4%
Common 87
 
15.8%
Latin 10
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 40
 
8.8%
사 17
 
3.8%
스 15
 
3.3%
이 12
 
2.6%
회 11
 
2.4%
경 10
 
2.2%
린 10
 
2.2%
환 9
 
2.0%
식 9
 
2.0%
리 8
 
1.8%
Other values (138) 312
68.9%
Latin
ValueCountFrequency (%)
G 1
10.0%
M 1
10.0%
C 1
10.0%
N 1
10.0%
S 1
10.0%
F 1
10.0%
e 1
10.0%
p 1
10.0%
i 1
10.0%
P 1
10.0%
Common
ValueCountFrequency (%)
( 32
36.8%
) 32
36.8%
16
18.4%
1 2
 
2.3%
& 1
 
1.1%
4 1
 
1.1%
5 1
 
1.1%
＆ 1
 
1.1%
9 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 453
82.4%
ASCII 96
 
17.5%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 40
 
8.8%
사 17
 
3.8%
스 15
 
3.3%
이 12
 
2.6%
회 11
 
2.4%
경 10
 
2.2%
린 10
 
2.2%
환 9
 
2.0%
식 9
 
2.0%
리 8
 
1.8%
Other values (138) 312
68.9%
ASCII
ValueCountFrequency (%)
( 32
33.3%
) 32
33.3%
16
16.7%
1 2
 
2.1%
G 1
 
1.0%
& 1
 
1.0%
M 1
 
1.0%
4 1
 
1.0%
C 1
 
1.0%
N 1
 
1.0%
Other values (8) 8
 
8.3%
None
ValueCountFrequency (%)
＆ 1
100.0%

최종수정일자
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)100.0%
Missing3
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean2.0175833 × 1013
Minimum2.0090204 × 1013
Maximum2.021111 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T19:11:42.726244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0090204 × 1013
5-th percentile2.0100242 × 1013
Q12.0151079 × 1013
median2.0191069 × 1013
Q32.0200888 × 1013
95-th percentile2.0210969 × 1013
Maximum2.021111 × 1013
Range1.2090598 × 1011
Interquartile range (IQR)4.9809482 × 1010

Descriptive statistics

Standard deviation3.6047357 × 1010
Coefficient of variation (CV)0.0017866601
Kurtosis-0.10547132
Mean2.0175833 × 1013
Median Absolute Deviation (MAD)1.9288 × 1010
Skewness-1.0276092
Sum1.4123083 × 1015
Variance1.299412 × 1021
MonotonicityNot monotonic
2023-12-12T19:11:42.914279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200319174839 1
 
1.4%
20200515153159 1
 
1.4%
20200425160133 1
 
1.4%
20200329105027 1
 
1.4%
20200326143221 1
 
1.4%
20200325161055 1
 
1.4%
20200325111055 1
 
1.4%
20200306093947 1
 
1.4%
20200708140706 1
 
1.4%
20191112143312 1
 
1.4%
Other values (60) 60
82.2%
(Missing) 3
 
4.1%
ValueCountFrequency (%)
20090204130824 1
1.4%
20090204132826 1
1.4%
20090204145246 1
1.4%
20100111150116 1
1.4%
20100401112833 1
1.4%
20110105161906 1
1.4%
20110624163442 1
1.4%
20120427120400 1
1.4%
20120803152820 1
1.4%
20130312161955 1
1.4%
ValueCountFrequency (%)
20211110110611 1
1.4%
20211103182722 1
1.4%
20211022142410 1
1.4%
20211007092052 1
1.4%
20210923112448 1
1.4%
20210913154528 1
1.4%
20210909154019 1
1.4%
20210823141806 1
1.4%
20210408174501 1
1.4%
20210305135243 1
1.4%

데이터갱신구분
Categorical

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size716.0 B
I
49 
U
20 
<NA>
 
4

Length

Max length4
Median length1
Mean length1.1643836
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 49
67.1%
U 20
27.4%
<NA> 4
 
5.5%

Length

2023-12-12T19:11:43.073788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:43.187549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 49
67.1%
u 20
27.4%
na 4
 
5.5%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)90.3%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean195056.97
Minimum191932.05
Maximum198366.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T19:11:43.640839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191932.05
5-th percentile192917.97
Q1193308.22
median194605.06
Q3197052.88
95-th percentile198130.14
Maximum198366.23
Range6434.1748
Interquartile range (IQR)3744.6685

Descriptive statistics

Standard deviation1929.1541
Coefficient of variation (CV)0.0098902082
Kurtosis-1.3180451
Mean195056.97
Median Absolute Deviation (MAD)1449.0837
Skewness0.31621232
Sum14044102
Variance3721635.4
MonotonicityNot monotonic
2023-12-12T19:11:43.829159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193639.3327 3
 
4.1%
194348.7253 3
 
4.1%
198259.0425 2
 
2.7%
191932.0539 2
 
2.7%
192917.9686 2
 
2.7%
197263.7432 1
 
1.4%
194772.9754 1
 
1.4%
191988.0342 1
 
1.4%
194346.1567 1
 
1.4%
193202.2067 1
 
1.4%
Other values (55) 55
75.3%
ValueCountFrequency (%)
191932.0539 2
2.7%
191988.0342 1
1.4%
192917.9686 2
2.7%
192955.0809 1
1.4%
192958.1816 1
1.4%
193008.7656 1
1.4%
193101.4926 1
1.4%
193140.0523 1
1.4%
193154.9163 1
1.4%
193157.0389 1
1.4%
ValueCountFrequency (%)
198366.2287 1
1.4%
198264.3051 1
1.4%
198259.0425 2
2.7%
198024.6679 1
1.4%
197872.6314 1
1.4%
197813.1895 1
1.4%
197790.2576 1
1.4%
197784.459 1
1.4%
197678.4133 1
1.4%
197567.7795 1
1.4%

좌표정보(Y)
Real number (ℝ)

Distinct66
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean440535.05
Minimum197448.03
Maximum445901.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T19:11:43.980911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum197448.03
5-th percentile441696.15
Q1442794.09
median444095.39
Q3444821.74
95-th percentile445637.88
Maximum445901.41
Range248453.38
Interquartile range (IQR)2027.6453

Descriptive statistics

Standard deviation28870.111
Coefficient of variation (CV)0.065534199
Kurtosis72.749704
Mean440535.05
Median Absolute Deviation (MAD)916.7159
Skewness-8.5223357
Sum32159058
Variance8.3348332 × 108
MonotonicityNot monotonic
2023-12-12T19:11:44.169831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445637.8782 3
 
4.1%
445270.7662 3
 
4.1%
441696.1456 2
 
2.7%
442799.9374 2
 
2.7%
444095.3906 2
 
2.7%
444821.7398 1
 
1.4%
445623.0802 1
 
1.4%
442794.0945 1
 
1.4%
445823.5009 1
 
1.4%
444065.2241 1
 
1.4%
Other values (56) 56
76.7%
ValueCountFrequency (%)
197448.03 1
1.4%
441605.4682 1
1.4%
441679.71 1
1.4%
441696.1456 2
2.7%
442015.8013 1
1.4%
442159.52 1
1.4%
442261.6158 1
1.4%
442291.9539 1
1.4%
442473.6244 1
1.4%
442485.2434 1
1.4%
ValueCountFrequency (%)
445901.4134 1
 
1.4%
445823.5009 1
 
1.4%
445637.8782 3
4.1%
445623.0802 1
 
1.4%
445537.4606 1
 
1.4%
445500.2747 1
 
1.4%
445456.1157 1
 
1.4%
445358.7948 1
 
1.4%
445270.7662 3
4.1%
445190.5126 1
 
1.4%

소독차량차고면적
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)93.8%
Missing25
Missing (%)34.2%
Infinite0
Infinite (%)0.0%
Mean38.049583
Minimum3.1
Maximum327.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T19:11:44.378035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1
5-th percentile6.28
Q114.4225
median20.695
Q334.9775
95-th percentile136.255
Maximum327.2
Range324.1
Interquartile range (IQR)20.555

Descriptive statistics

Standard deviation59.314986
Coefficient of variation (CV)1.5588866
Kurtosis14.950674
Mean38.049583
Median Absolute Deviation (MAD)9.18
Skewness3.7854821
Sum1826.38
Variance3518.2676
MonotonicityNot monotonic
2023-12-12T19:11:44.557703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
12.0 2
 
2.7%
33.0 2
 
2.7%
20.0 2
 
2.7%
58.32 1
 
1.4%
20.52 1
 
1.4%
8.28 1
 
1.4%
46.59 1
 
1.4%
14.44 1
 
1.4%
6.8 1
 
1.4%
27.36 1
 
1.4%
Other values (35) 35
47.9%
(Missing) 25
34.2%
ValueCountFrequency (%)
3.1 1
1.4%
5.6 1
1.4%
6.0 1
1.4%
6.8 1
1.4%
7.29 1
1.4%
8.28 1
1.4%
8.41 1
1.4%
8.75 1
1.4%
11.7 1
1.4%
12.0 2
2.7%
ValueCountFrequency (%)
327.2 1
1.4%
247.9 1
1.4%
175.0 1
1.4%
64.3 1
1.4%
60.0 1
1.4%
58.32 1
1.4%
48.88 1
1.4%
46.59 1
1.4%
41.9 1
1.4%
38.41 1
1.4%

초미립자살포기수
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)63.3%
Missing24
Missing (%)32.9%
Infinite0
Infinite (%)0.0%
Mean12.371224
Minimum1
Maximum110.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T19:11:44.740276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3.9
Q312.8
95-th percentile39.932
Maximum110.36
Range109.36
Interquartile range (IQR)11.8

Descriptive statistics

Standard deviation20.644901
Coefficient of variation (CV)1.668784
Kurtosis12.119561
Mean12.371224
Median Absolute Deviation (MAD)2.9
Skewness3.2320991
Sum606.19
Variance426.21194
MonotonicityNot monotonic
2023-12-12T19:11:44.905643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1.0 18
24.7%
6.6 2
 
2.7%
12.0 1
 
1.4%
110.36 1
 
1.4%
30.0 1
 
1.4%
39.35 1
 
1.4%
2.4 1
 
1.4%
5.6 1
 
1.4%
11.25 1
 
1.4%
15.0 1
 
1.4%
Other values (21) 21
28.8%
(Missing) 24
32.9%
ValueCountFrequency (%)
1.0 18
24.7%
1.1 1
 
1.4%
1.66 1
 
1.4%
2.37 1
 
1.4%
2.4 1
 
1.4%
2.43 1
 
1.4%
3.64 1
 
1.4%
3.9 1
 
1.4%
5.6 1
 
1.4%
6.6 2
 
2.7%
ValueCountFrequency (%)
110.36 1
1.4%
82.2 1
1.4%
40.32 1
1.4%
39.35 1
1.4%
33.43 1
1.4%
30.0 1
1.4%
25.97 1
1.4%
25.0 1
1.4%
23.0 1
1.4%
18.43 1
1.4%

휴대용소독기수
Categorical

Distinct4
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
1
29 
<NA>
23 
2
20 
3
 
1

Length

Max length4
Median length1
Mean length1.9452055
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 29
39.7%
<NA> 23
31.5%
2 20
27.4%
3 1
 
1.4%

Length

2023-12-12T19:11:45.081440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:45.219453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 29
39.7%
na 23
31.5%
2 20
27.4%
3 1
 
1.4%

동력분무기수
Categorical

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size716.0 B
2
30 
<NA>
23 
1
15 
0
 
3
3
 
2

Length

Max length4
Median length1
Mean length1.9452055
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row3
3rd row<NA>
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 30
41.1%
<NA> 23
31.5%
1 15
20.5%
0 3
 
4.1%
3 2
 
2.7%

Length

2023-12-12T19:11:45.348474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:45.475483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 30
41.1%
na 23
31.5%
1 15
20.5%
0 3
 
4.1%
3 2
 
2.7%

수동식분무기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)12.0%
Missing23
Missing (%)31.5%
Infinite0
Infinite (%)0.0%
Mean2.24
Minimum0
Maximum7
Zeros13
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T19:11:45.596072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.25
median1
Q35
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation2.1718045
Coefficient of variation (CV)0.96955557
Kurtosis-1.4066198
Mean2.24
Median Absolute Deviation (MAD)1
Skewness0.49993281
Sum112
Variance4.7167347
MonotonicityNot monotonic
2023-12-12T19:11:45.709020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 17
23.3%
5 14
19.2%
0 13
17.8%
4 3
 
4.1%
3 2
 
2.7%
7 1
 
1.4%
(Missing) 23
31.5%
ValueCountFrequency (%)
0 13
17.8%
1 17
23.3%
3 2
 
2.7%
4 3
 
4.1%
5 14
19.2%
7 1
 
1.4%
ValueCountFrequency (%)
7 1
 
1.4%
5 14
19.2%
4 3
 
4.1%
3 2
 
2.7%
1 17
23.3%
0 13
17.8%

방독면수
Categorical

Distinct6
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size716.0 B
5
35 
<NA>
23 
3
12 
7
 
1
4
 
1

Length

Max length4
Median length1
Mean length1.9452055
Min length1

Unique

Unique3 ?
Unique (%)4.1%

Sample

1st row<NA>
2nd row7
3rd row<NA>
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 35
47.9%
<NA> 23
31.5%
3 12
 
16.4%
7 1
 
1.4%
4 1
 
1.4%
6 1
 
1.4%

Length

2023-12-12T19:11:45.843992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:45.972781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 35
47.9%
na 23
31.5%
3 12
 
16.4%
7 1
 
1.4%
4 1
 
1.4%
6 1
 
1.4%

보호안경수
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
5
50 
<NA>
23 

Length

Max length4
Median length1
Mean length1.9452055
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
5 50
68.5%
<NA> 23
31.5%

Length

2023-12-12T19:11:46.108409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:46.230218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 50
68.5%
na 23
31.5%

보호용의복수
Categorical

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size716.0 B
5
47 
<NA>
23 
10
 
1
1
 
1
2
 
1

Length

Max length4
Median length1
Mean length1.9589041
Min length1

Unique

Unique3 ?
Unique (%)4.1%

Sample

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

Common Values

ValueCountFrequency (%)
5 47
64.4%
<NA> 23
31.5%
10 1
 
1.4%
1 1
 
1.4%
2 1
 
1.4%

Length

2023-12-12T19:11:46.398793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:46.570968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 47
64.4%
na 23
31.5%
10 1
 
1.4%
1 1
 
1.4%
2 1
 
1.4%

진공청소기수
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)12.0%
Missing23
Missing (%)31.5%
Infinite0
Infinite (%)0.0%
Mean4.02
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T19:11:46.729455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q35
95-th percentile5
Maximum10
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9429622
Coefficient of variation (CV)0.48332393
Kurtosis0.51488616
Mean4.02
Median Absolute Deviation (MAD)0
Skewness-0.22055644
Sum201
Variance3.775102
MonotonicityNot monotonic
2023-12-12T19:11:46.874061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 33
45.2%
1 11
 
15.1%
2 3
 
4.1%
3 1
 
1.4%
6 1
 
1.4%
10 1
 
1.4%
(Missing) 23
31.5%
ValueCountFrequency (%)
1 11
 
15.1%
2 3
 
4.1%
3 1
 
1.4%
5 33
45.2%
6 1
 
1.4%
10 1
 
1.4%
ValueCountFrequency (%)
10 1
 
1.4%
6 1
 
1.4%
5 33
45.2%
3 1
 
1.4%
2 3
 
4.1%
1 11
 
15.1%

Sample

관리번호인허가일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자전화번호소재지우편번호지번주소도로명주소사업장명최종수정일자데이터갱신구분좌표정보(X)좌표정보(Y)소독차량차고면적초미립자살포기수휴대용소독기수동력분무기수수동식분무기수방독면수보호안경수보호용의복수진공청소기수
0PHMB5198731900330425000031987-01-235제외/삭제/전출15전출<NA>02-826-0055<NA>서울특별시 동작구 흑석동 98번지 1호서울특별시 동작구 서달로14가길 20 (흑석동)홍익시설관리(주)20201029084014U196619.5929444995.2829<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1PHMB5198731900330425000041987-08-061영업/정상13영업중<NA>02-823-1311156020서울특별시 동작구 대방동 339번지 1호 솔표빌딩 3층서울특별시 동작구 노량진로 26 (대방동솔표빌딩 3층)(주)순일기업20200408173546U193639.3327445637.87828.418.391317555
2PHMB5198731900330425000051987-12-093폐업3폐업2021-04-0802-812-5167156035서울특별시 동작구 상도5동 175번지 9호서울특별시 동작구 장승배기로10가길 15 (상도동)삼진방역공사20210408174501U194632.9976444617.2807<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3PHMB5199431900330425000011994-02-081영업/정상13영업중<NA>02-816-3107<NA>서울특별시 동작구 상도동 363번지 142호서울특별시 동작구 상도로15길 143 4층 408호 (상도동)대성방역공사20190307173311U194741.3148444218.824416.56.61215555
4PHMB5199731900330425000011997-08-264취소/말소/만료/정지/중지24직권폐업2012-01-3002-813-7092156052서울특별시 동작구 노량진2동 240번지 25호<NA>(주)우신씨앤에스20141201103515I194588.4968445500.274738.411.02155551
5PHMB5199731900330425000021997-07-291영업/정상13영업중<NA>02-813-9700156033서울특별시 동작구 상도3동 299번지 58호 1층서울특별시 동작구 국사봉길 74 (상도동 지하1층)거양실업<NA><NA>193790.5229443823.89120.71.02155551
6PHMB5200031900330425000012000-10-071영업/정상13영업중<NA>02-824-3834156051서울특별시 동작구 노량진1동 231번지 4호 3층서울특별시 동작구 장승배기로 128 (노량진동3층)(주)프리엠환경20110624163442I194674.0205445190.512648.8825.971215555
7PHMB5200131900330425000012001-03-173폐업3폐업2014-10-2202-585-2811156080서울특별시 동작구 동작동 102번지 32호 태경빌딩 5층서울특별시 동작구 동작대로43길 1-1 (동작동)(주)태광엠에스20141023101611I198366.2287443784.047820.81.02155551
8PHMB5200231900330425000012002-03-251영업/정상13영업중<NA>02-817-1019156020서울특별시 동작구 대방동 417번지 2호 봉림빌딩 403호서울특별시 동작구 여의대방로 134-1 (대방동봉림빌딩 403호)(주)윈윈메인터넌스20090204130824I192917.9686444095.390629.7533.431215555
9PHMB5200431900330425000012004-09-151영업/정상13영업중<NA>02-3472-5041156090서울특별시 동작구 사당동 1013번지 19호서울특별시 동작구 동작대로15길 88 (사당동)이레환경사업20090204132826I197872.6314442261.61583.11.02155551
관리번호인허가일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자전화번호소재지우편번호지번주소도로명주소사업장명최종수정일자데이터갱신구분좌표정보(X)좌표정보(Y)소독차량차고면적초미립자살포기수휴대용소독기수동력분무기수수동식분무기수방독면수보호안경수보호용의복수진공청소기수
63PHMB5202031900330425000172020-09-221영업/정상13영업중<NA><NA><NA>서울특별시 동작구 사당동 169-8 대림아파트서울특별시 동작구 사당로17길 8그린F5 동작본부20200925163613I197545.9854442685.8869<NA><NA><NA><NA><NA><NA><NA><NA><NA>
64PHMB5202031900330425000182019-11-081영업/정상13영업중<NA>02-877-9452<NA>서울특별시 동작구 대방동 **-**서울특별시 동작구 등용로 ***그린행복주식회사20210823141806U193904.6188445358.7948<NA><NA><NA><NA><NA><NA><NA><NA><NA>
65PHMB5202031900330425000192020-10-123폐업3폐업2020-12-17<NA><NA>서울특별시 동작구 상도동 195-20서울특별시 동작구 상도로22가길 1스타클린 방역20210305135243U194340.7705444458.3335<NA><NA><NA><NA><NA><NA><NA><NA><NA>
66PHMB5202031900330425000202020-10-271영업/정상13영업중<NA><NA><NA>서울특별시 동작구 신대방동 395-73 캐릭터 그린빌서울특별시 동작구 보라매로5가길 7(주)양지SNC20201027172752I193300.8325443302.4177<NA><NA><NA><NA><NA><NA><NA><NA><NA>
67PHMB5202031900330425000212011-12-091영업/정상13영업중<NA>02-2088-5061<NA>서울특별시 동작구 대방동 339-1 솔표빌딩서울특별시 동작구 노량진로 26(주)다림엔지니어링20201221170804I193639.3327445637.8782<NA><NA><NA><NA><NA><NA><NA><NA><NA>
68PHMB5202131900330425000012021-01-191영업/정상13영업중<NA><NA><NA>서울특별시 동작구 대방동 395-8 세경빌딩 202호서울특별시 동작구 대방동1길 19동원환경기업20210125081812U193347.403444223.1717<NA><NA><NA><NA><NA><NA><NA><NA><NA>
69PHMB5202131900330425000022021-09-091영업/정상13영업중<NA><NA><NA>서울특별시 동작구 노량진동 ***-*서울특별시 동작구 노량진로*길 **도깨비소독방역20210913154528I194348.7253445270.7662<NA><NA><NA><NA><NA><NA><NA><NA><NA>
70PHMB5202131900330425000032021-09-171영업/정상13영업중<NA><NA><NA><NA>서울특별시 동작구 노량진로**길 *-*바로본20210923112448I195907.1506445537.4606<NA><NA><NA><NA><NA><NA><NA><NA><NA>
71PHMB5202131900330425000042021-02-051영업/정상13영업중<NA>02-750-0724<NA>서울특별시 동작구 신대방동 ***-** 파크스퀘어보라매현대APT파크스퀘어20211007092052I193167.0499443326.0604<NA><NA><NA><NA><NA><NA><NA><NA><NA>
72PHMB5202131900330425000052021-10-151영업/정상13영업중<NA><NA><NA>서울특별시 동작구 노량진동 ***-*서울특별시 동작구 노량진로*길 **주식회사 가가원20211022142410I194348.7253445270.7662<NA><NA><NA><NA><NA><NA><NA><NA><NA>