Overview

Dataset statistics

Number of variables4
Number of observations57
Missing cells14
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory35.2 B

Variable types

Numeric1
Text3

Dataset

Description인천광역시 계양구 관내 소독업소 현황에 대한 데이터로, 순번, 소독업소 명칭, 사무실 소재지(도로명주소), 영업소 전화번호 등을 제공합니다.
Author인천광역시 계양구
URLhttps://www.data.go.kr/data/15039242/fileData.do

Alerts

영업소전화번호 has 14 (24.6%) missing valuesMissing
순번 has unique valuesUnique
소독업소명칭 has unique valuesUnique
사무실소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:35:34.202888
Analysis finished2024-03-15 00:35:35.200086
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size641.0 B
2024-03-15T09:35:35.417895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2024-03-15T09:35:35.773891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

소독업소명칭
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
2024-03-15T09:35:36.510002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length8.4210526
Min length3

Characters and Unicode

Total characters480
Distinct characters164
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

Unique57 ?
Unique (%)100.0%

Sample

1st row인천계양지역자활센터
2nd row상록토탈
3rd row자바드림 경기서북지사
4th row지구방역
5th row주식회사 동명문화유산
ValueCountFrequency (%)
주식회사 6
 
8.0%
인천계양지역자활센터 1
 
1.3%
대신종합관리(주 1
 
1.3%
중진공산업 1
 
1.3%
케이피엠 1
 
1.3%
지엘홀딩스 1
 
1.3%
주)조흥환경 1
 
1.3%
두천산업(주 1
 
1.3%
주)우리비젼 1
 
1.3%
주)엠에스종합관리 1
 
1.3%
Other values (60) 60
80.0%
2024-03-15T09:35:37.788025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 31
 
6.5%
) 27
 
5.6%
( 27
 
5.6%
18
 
3.8%
스 15
 
3.1%
사 11
 
2.3%
리 11
 
2.3%
산 9
 
1.9%
인 8
 
1.7%
이 8
 
1.7%
Other values (154) 315
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 394
82.1%
Close Punctuation 27
 
5.6%
Open Punctuation 27
 
5.6%
Space Separator 18
 
3.8%
Uppercase Letter 5
 
1.0%
Lowercase Letter 4
 
0.8%
Decimal Number 3
 
0.6%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 31
 
7.9%
스 15
 
3.8%
사 11
 
2.8%
리 11
 
2.8%
산 9
 
2.3%
인 8
 
2.0%
이 8
 
2.0%
에 8
 
2.0%
회 7
 
1.8%
업 7
 
1.8%
Other values (137) 279
70.8%
Uppercase Letter
ValueCountFrequency (%)
S 1
20.0%
H 1
20.0%
D 1
20.0%
K 1
20.0%
V 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
25.0%
o 1
25.0%
c 1
25.0%
w 1
25.0%
Decimal Number
ValueCountFrequency (%)
5 1
33.3%
6 1
33.3%
3 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 394
82.1%
Common 77
 
16.0%
Latin 9
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 31
 
7.9%
스 15
 
3.8%
사 11
 
2.8%
리 11
 
2.8%
산 9
 
2.3%
인 8
 
2.0%
이 8
 
2.0%
에 8
 
2.0%
회 7
 
1.8%
업 7
 
1.8%
Other values (137) 279
70.8%
Latin
ValueCountFrequency (%)
S 1
11.1%
H 1
11.1%
m 1
11.1%
o 1
11.1%
c 1
11.1%
w 1
11.1%
D 1
11.1%
K 1
11.1%
V 1
11.1%
Common
ValueCountFrequency (%)
) 27
35.1%
( 27
35.1%
18
23.4%
- 1
 
1.3%
5 1
 
1.3%
6 1
 
1.3%
3 1
 
1.3%
. 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 394
82.1%
ASCII 86
 
17.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 31
 
7.9%
스 15
 
3.8%
사 11
 
2.8%
리 11
 
2.8%
산 9
 
2.3%
인 8
 
2.0%
이 8
 
2.0%
에 8
 
2.0%
회 7
 
1.8%
업 7
 
1.8%
Other values (137) 279
70.8%
ASCII
ValueCountFrequency (%)
) 27
31.4%
( 27
31.4%
18
20.9%
- 1
 
1.2%
5 1
 
1.2%
6 1
 
1.2%
3 1
 
1.2%
S 1
 
1.2%
H 1
 
1.2%
m 1
 
1.2%
Other values (7) 7
 
8.1%

사무실소재지(도로명)
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
2024-03-15T09:35:38.753145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41
Mean length34.789474
Min length23

Characters and Unicode

Total characters1983
Distinct characters128
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

Unique57 ?
Unique (%)100.0%

Sample

1st row인천광역시 계양구 효서로 460, 1층 (서운동)
2nd row인천광역시 계양구 살라리로 13, 서운동 경남아너스빌 상가동 3층 301-90호 (서운동)
3rd row인천광역시 계양구 아나지로 405, 1층 105호 (작전동)
4th row인천광역시 계양구 봉오대로463번길 7, 상가동 2층 2호 (효성동, 경남아파트)
5th row인천광역시 계양구 계양산로 171, 2층 (임학동)
ValueCountFrequency (%)
인천광역시 57
 
14.8%
계양구 57
 
14.8%
계산동 19
 
4.9%
작전동 13
 
3.4%
2층 12
 
3.1%
1층 5
 
1.3%
주부토로 5
 
1.3%
상가동 5
 
1.3%
임학동 5
 
1.3%
계양대로 5
 
1.3%
Other values (160) 202
52.5%
2024-03-15T09:35:40.240864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
328
 
16.5%
계 91
 
4.6%
1 81
 
4.1%
동 70
 
3.5%
양 68
 
3.4%
, 64
 
3.2%
인 59
 
3.0%
( 59
 
3.0%
) 59
 
3.0%
시 58
 
2.9%
Other values (118) 1046
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1138
57.4%
Space Separator 328
 
16.5%
Decimal Number 326
 
16.4%
Other Punctuation 64
 
3.2%
Open Punctuation 59
 
3.0%
Close Punctuation 59
 
3.0%
Dash Punctuation 5
 
0.3%
Uppercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 91
 
8.0%
동 70
 
6.2%
양 68
 
6.0%
인 59
 
5.2%
시 58
 
5.1%
천 58
 
5.1%
구 57
 
5.0%
역 57
 
5.0%
광 57
 
5.0%
로 57
 
5.0%
Other values (100) 506
44.5%
Decimal Number
ValueCountFrequency (%)
1 81
24.8%
2 48
14.7%
0 46
14.1%
4 31
 
9.5%
5 30
 
9.2%
3 27
 
8.3%
7 22
 
6.7%
6 17
 
5.2%
9 13
 
4.0%
8 11
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
E 1
25.0%
D 1
25.0%
Space Separator
ValueCountFrequency (%)
328
100.0%
Other Punctuation
ValueCountFrequency (%)
, 64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1138
57.4%
Common 841
42.4%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 91
 
8.0%
동 70
 
6.2%
양 68
 
6.0%
인 59
 
5.2%
시 58
 
5.1%
천 58
 
5.1%
구 57
 
5.0%
역 57
 
5.0%
광 57
 
5.0%
로 57
 
5.0%
Other values (100) 506
44.5%
Common
ValueCountFrequency (%)
328
39.0%
1 81
 
9.6%
, 64
 
7.6%
( 59
 
7.0%
) 59
 
7.0%
2 48
 
5.7%
0 46
 
5.5%
4 31
 
3.7%
5 30
 
3.6%
3 27
 
3.2%
Other values (5) 68
 
8.1%
Latin
ValueCountFrequency (%)
B 2
50.0%
E 1
25.0%
D 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1138
57.4%
ASCII 845
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
328
38.8%
1 81
 
9.6%
, 64
 
7.6%
( 59
 
7.0%
) 59
 
7.0%
2 48
 
5.7%
0 46
 
5.4%
4 31
 
3.7%
5 30
 
3.6%
3 27
 
3.2%
Other values (8) 72
 
8.5%
Hangul
ValueCountFrequency (%)
계 91
 
8.0%
동 70
 
6.2%
양 68
 
6.0%
인 59
 
5.2%
시 58
 
5.1%
천 58
 
5.1%
구 57
 
5.0%
역 57
 
5.0%
광 57
 
5.0%
로 57
 
5.0%
Other values (100) 506
44.5%

영업소전화번호
Text

MISSING 

Distinct43
Distinct (%)100.0%
Missing14
Missing (%)24.6%
Memory size584.0 B
2024-03-15T09:35:41.110837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.418605
Min length9

Characters and Unicode

Total characters491
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

Unique43 ?
Unique (%)100.0%

Sample

1st row032-543-3370
2nd row1688-0248
3rd row070-4727-2936
4th row032-551-7939
5th row032-547-1007
ValueCountFrequency (%)
032-543-3370 1
 
2.3%
032-555-8110 1
 
2.3%
032-551-0450 1
 
2.3%
032-554-0016 1
 
2.3%
032-502-6636 1
 
2.3%
032-862-0222 1
 
2.3%
032-553-5778 1
 
2.3%
032-544-1112 1
 
2.3%
032-541-5561 1
 
2.3%
1577-9515 1
 
2.3%
Other values (33) 33
76.7%
2024-03-15T09:35:42.434211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 78
15.9%
- 77
15.7%
0 66
13.4%
2 60
12.2%
3 55
11.2%
1 39
7.9%
7 27
 
5.5%
4 25
 
5.1%
6 24
 
4.9%
9 23
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 414
84.3%
Dash Punctuation 77
 
15.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 78
18.8%
0 66
15.9%
2 60
14.5%
3 55
13.3%
1 39
9.4%
7 27
 
6.5%
4 25
 
6.0%
6 24
 
5.8%
9 23
 
5.6%
8 17
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 491
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 78
15.9%
- 77
15.7%
0 66
13.4%
2 60
12.2%
3 55
11.2%
1 39
7.9%
7 27
 
5.5%
4 25
 
5.1%
6 24
 
4.9%
9 23
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 491
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 78
15.9%
- 77
15.7%
0 66
13.4%
2 60
12.2%
3 55
11.2%
1 39
7.9%
7 27
 
5.5%
4 25
 
5.1%
6 24
 
4.9%
9 23
 
4.7%

Interactions

2024-03-15T09:35:34.599304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:35:42.698627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번소독업소명칭사무실소재지(도로명)영업소전화번호
순번1.0001.0001.0001.000
소독업소명칭1.0001.0001.0001.000
사무실소재지(도로명)1.0001.0001.0001.000
영업소전화번호1.0001.0001.0001.000

Missing values

2024-03-15T09:35:34.799013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:35:35.087360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

순번소독업소명칭사무실소재지(도로명)영업소전화번호
01인천계양지역자활센터인천광역시 계양구 효서로 460, 1층 (서운동)032-543-3370
12상록토탈인천광역시 계양구 살라리로 13, 서운동 경남아너스빌 상가동 3층 301-90호 (서운동)<NA>
23자바드림 경기서북지사인천광역시 계양구 아나지로 405, 1층 105호 (작전동)1688-0248
34지구방역인천광역시 계양구 봉오대로463번길 7, 상가동 2층 2호 (효성동, 경남아파트)<NA>
45주식회사 동명문화유산인천광역시 계양구 계양산로 171, 2층 (임학동)070-4727-2936
56페스탑인천광역시 계양구 안남로551번길 21, 우정2상가 2층 (효성동)<NA>
67(주)빛나크린인천광역시 계양구 계산천동로7번길 3, 지층 (계산동)032-551-7939
78오시드디자인인천광역시 계양구 계양대로 106, 덕인빌딩 2층 201호 (작전동)032-547-1007
89청솔시앤시인천광역시 계양구 봉오대로706번길 15, 지하1층 (작전동)<NA>
910(주)한국피씨오인천광역시 계양구 도두리로6번길 14, 701호 (작전동)<NA>
순번소독업소명칭사무실소재지(도로명)영업소전화번호
4748(주)코리아 시스템인천광역시 계양구 주부토로 394 (작전동,3층)032-555-0025
4849(주)청명산업개발인천광역시 계양구 주부토로 540, 302호 (계산동)032-555-7795
4950대아산업 주식회사인천광역시 계양구 계양문화로 54 (계산동,502호)032-551-3400
5051(주)고산실업인천광역시 계양구 효서로 300 (작전동,삼호프라자 203호)032-556-4503
5152(주)부안 안전시스템인천광역시 계양구 아나지로247번길 11 (효성동,모닝프라자 207호)032-555-5277
5253(주)백산 휴레텍인천광역시 계양구 오조산로45번길 12, 유연프라자 707호 (계산동)032-542-4946
5354대성종합개발인천광역시 계양구 주부토로 540, 한국아파트 상가 B108호 (계산동)032-546-1776
5455(주)코리아종합관리인천광역시 계양구 도두리로 21, 704호 (계산동, E-프라자)032-555-2134
5556성진환경공사인천광역시 계양구 병방시장로61번길 10, 진달래아파트 상가동 103호 (병방동)032-552-1300
5657(주)현대종합관리인천광역시 계양구 오조산로57번길 15, 명동빌딩 5층 505호 (계산동)032-549-1700