Overview

Dataset statistics

Number of variables4
Number of observations69
Missing cells16
Missing cells (%)5.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory34.9 B

Variable types

Numeric1
Text3

Dataset

Description인천광역시 계양구 관내 옥외광고업 현황에 대한 데이터로, 업소명, 성명, 영업장 전화번호, 영업장 주소 등을 제공합니다.
Author인천광역시 계양구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15038927&srcSe=7661IVAWM27C61E190

Alerts

영업장전화번호 has 16 (23.2%) missing valuesMissing
순번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 08:24:18.158489
Analysis finished2024-01-28 08:24:18.573597
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35
Minimum1
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-01-28T17:24:18.638116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q118
median35
Q352
95-th percentile65.6
Maximum69
Range68
Interquartile range (IQR)34

Descriptive statistics

Standard deviation20.062403
Coefficient of variation (CV)0.5732115
Kurtosis-1.2
Mean35
Median Absolute Deviation (MAD)17
Skewness0
Sum2415
Variance402.5
MonotonicityStrictly increasing
2024-01-28T17:24:18.759338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
45 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
46 1
 
1.4%
44 1
 
1.4%
53 1
 
1.4%
Other values (59) 59
85.5%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%
60 1
1.4%

업소명
Text

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size684.0 B
2024-01-28T17:24:19.013895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length5.7826087
Min length2

Characters and Unicode

Total characters399
Distinct characters131
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)100.0%

Sample

1st row간판숍
2nd row포토애드
3rd row다힘건축디자인
4th row이성광고
5th row애드핏사인
ValueCountFrequency (%)
주식회사 4
 
5.2%
디자인 2
 
2.6%
애드원 1
 
1.3%
교대간판 1
 
1.3%
주)청풍 1
 
1.3%
푸른기획 1
 
1.3%
인천광고 1
 
1.3%
헤라클레스광고 1
 
1.3%
한진기업 1
 
1.3%
현대현수막 1
 
1.3%
Other values (63) 63
81.8%
2024-01-28T17:24:19.472484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 26
 
6.5%
고 22
 
5.5%
인 19
 
4.8%
주 18
 
4.5%
디 15
 
3.8%
( 14
 
3.5%
) 14
 
3.5%
드 14
 
3.5%
자 14
 
3.5%
애 13
 
3.3%
Other values (121) 230
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 362
90.7%
Open Punctuation 14
 
3.5%
Close Punctuation 14
 
3.5%
Space Separator 8
 
2.0%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 26
 
7.2%
고 22
 
6.1%
인 19
 
5.2%
주 18
 
5.0%
디 15
 
4.1%
드 14
 
3.9%
자 14
 
3.9%
애 13
 
3.6%
사 10
 
2.8%
스 6
 
1.7%
Other values (117) 205
56.6%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Decimal Number
ValueCountFrequency (%)
9 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 362
90.7%
Common 37
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 26
 
7.2%
고 22
 
6.1%
인 19
 
5.2%
주 18
 
5.0%
디 15
 
4.1%
드 14
 
3.9%
자 14
 
3.9%
애 13
 
3.6%
사 10
 
2.8%
스 6
 
1.7%
Other values (117) 205
56.6%
Common
ValueCountFrequency (%)
( 14
37.8%
) 14
37.8%
8
21.6%
9 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 362
90.7%
ASCII 37
 
9.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 26
 
7.2%
고 22
 
6.1%
인 19
 
5.2%
주 18
 
5.0%
디 15
 
4.1%
드 14
 
3.9%
자 14
 
3.9%
애 13
 
3.6%
사 10
 
2.8%
스 6
 
1.7%
Other values (117) 205
56.6%
ASCII
ValueCountFrequency (%)
( 14
37.8%
) 14
37.8%
8
21.6%
9 1
 
2.7%

영업장전화번호
Text

MISSING 

Distinct53
Distinct (%)100.0%
Missing16
Missing (%)23.2%
Memory size684.0 B
2024-01-28T17:24:19.741705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length9

Characters and Unicode

Total characters636
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

Unique53 ?
Unique (%)100.0%

Sample

1st row032-555-5900
2nd row032-543-6710
3rd row032-543-8470
4th row032-322-3960
5th row032-555-8823
ValueCountFrequency (%)
032-544-7445 1
 
1.9%
032-207-8989 1
 
1.9%
032-545-0156 1
 
1.9%
032-545-0900 1
 
1.9%
032-542-6100 1
 
1.9%
032-543-6863 1
 
1.9%
032-551-7390 1
 
1.9%
032-549-8242 1
 
1.9%
032-544-6618 1
 
1.9%
032-553-7000 1
 
1.9%
Other values (43) 43
81.1%
2024-01-28T17:24:20.110973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 105
16.5%
0 91
14.3%
5 85
13.4%
2 83
13.1%
3 79
12.4%
4 50
7.9%
9 34
 
5.3%
7 30
 
4.7%
6 28
 
4.4%
1 27
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 531
83.5%
Dash Punctuation 105
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91
17.1%
5 85
16.0%
2 83
15.6%
3 79
14.9%
4 50
9.4%
9 34
 
6.4%
7 30
 
5.6%
6 28
 
5.3%
1 27
 
5.1%
8 24
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 636
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 105
16.5%
0 91
14.3%
5 85
13.4%
2 83
13.1%
3 79
12.4%
4 50
7.9%
9 34
 
5.3%
7 30
 
4.7%
6 28
 
4.4%
1 27
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 636
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 105
16.5%
0 91
14.3%
5 85
13.4%
2 83
13.1%
3 79
12.4%
4 50
7.9%
9 34
 
5.3%
7 30
 
4.7%
6 28
 
4.4%
1 27
 
4.2%

영업장도로명주소
Text

Distinct68
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size684.0 B
2024-01-28T17:24:20.398477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length38
Mean length28.681159
Min length22

Characters and Unicode

Total characters1979
Distinct characters110
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 (%)97.1%

Sample

1st row인천광역시 계양구 오류길 2, 2동 (오류동)
2nd row인천광역시 계양구 마장로512번길 13, 효성동하나빌딩 2층 (효성동)
3rd row인천광역시 계양구 계양산로 5-1, 1층 101호 (계산동)
4th row인천광역시 계양구 봉오대로691번길 4, 103동 1층 112호 (작전동, 코오롱아파트)
5th row인천광역시 계양구 계산새로 71, 하이베라스 B동 3층 12호 (계산동)
ValueCountFrequency (%)
인천광역시 69
 
17.6%
계양구 69
 
17.6%
계산동 21
 
5.3%
작전동 17
 
4.3%
효성동 10
 
2.5%
2층 5
 
1.3%
주부토로 5
 
1.3%
계산새로 4
 
1.0%
71 4
 
1.0%
서운동 4
 
1.0%
Other values (139) 185
47.1%
2024-01-28T17:24:20.781762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
325
 
16.4%
계 108
 
5.5%
1 81
 
4.1%
동 80
 
4.0%
양 77
 
3.9%
인 70
 
3.5%
광 70
 
3.5%
천 70
 
3.5%
( 69
 
3.5%
역 69
 
3.5%
Other values (100) 960
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1176
59.4%
Space Separator 325
 
16.4%
Decimal Number 298
 
15.1%
Open Punctuation 69
 
3.5%
Close Punctuation 69
 
3.5%
Other Punctuation 30
 
1.5%
Dash Punctuation 8
 
0.4%
Uppercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 108
 
9.2%
동 80
 
6.8%
양 77
 
6.5%
인 70
 
6.0%
광 70
 
6.0%
천 70
 
6.0%
역 69
 
5.9%
시 69
 
5.9%
구 69
 
5.9%
로 66
 
5.6%
Other values (83) 428
36.4%
Decimal Number
ValueCountFrequency (%)
1 81
27.2%
2 35
11.7%
4 34
11.4%
5 30
 
10.1%
3 27
 
9.1%
6 22
 
7.4%
0 21
 
7.0%
9 18
 
6.0%
8 15
 
5.0%
7 15
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
D 1
 
25.0%
Space Separator
ValueCountFrequency (%)
325
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1176
59.4%
Common 799
40.4%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 108
 
9.2%
동 80
 
6.8%
양 77
 
6.5%
인 70
 
6.0%
광 70
 
6.0%
천 70
 
6.0%
역 69
 
5.9%
시 69
 
5.9%
구 69
 
5.9%
로 66
 
5.6%
Other values (83) 428
36.4%
Common
ValueCountFrequency (%)
325
40.7%
1 81
 
10.1%
( 69
 
8.6%
) 69
 
8.6%
2 35
 
4.4%
4 34
 
4.3%
5 30
 
3.8%
, 30
 
3.8%
3 27
 
3.4%
6 22
 
2.8%
Other values (5) 77
 
9.6%
Latin
ValueCountFrequency (%)
B 3
75.0%
D 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1176
59.4%
ASCII 803
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
325
40.5%
1 81
 
10.1%
( 69
 
8.6%
) 69
 
8.6%
2 35
 
4.4%
4 34
 
4.2%
5 30
 
3.7%
, 30
 
3.7%
3 27
 
3.4%
6 22
 
2.7%
Other values (7) 81
 
10.1%
Hangul
ValueCountFrequency (%)
계 108
 
9.2%
동 80
 
6.8%
양 77
 
6.5%
인 70
 
6.0%
광 70
 
6.0%
천 70
 
6.0%
역 69
 
5.9%
시 69
 
5.9%
구 69
 
5.9%
로 66
 
5.6%
Other values (83) 428
36.4%

Interactions

2024-01-28T17:24:18.366544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T17:24:20.861156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업소명영업장전화번호영업장도로명주소
순번1.0001.0001.0000.939
업소명1.0001.0001.0001.000
영업장전화번호1.0001.0001.0001.000
영업장도로명주소0.9391.0001.0001.000

Missing values

2024-01-28T17:24:18.470980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:24:18.543981image/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

순번업소명영업장전화번호영업장도로명주소
01간판숍<NA>인천광역시 계양구 오류길 2, 2동 (오류동)
12포토애드032-555-5900인천광역시 계양구 마장로512번길 13, 효성동하나빌딩 2층 (효성동)
23다힘건축디자인<NA>인천광역시 계양구 계양산로 5-1, 1층 101호 (계산동)
34이성광고<NA>인천광역시 계양구 봉오대로691번길 4, 103동 1층 112호 (작전동, 코오롱아파트)
45애드핏사인<NA>인천광역시 계양구 계산새로 71, 하이베라스 B동 3층 12호 (계산동)
56애드포스트032-543-6710인천광역시 계양구 벌말로565번길 34-1, 204호 (평동)
67싸다9광고시장<NA>인천광역시 계양구 까치말로15번길 12 (작전동)
78핫디자인<NA>인천광역시 계양구 선주로34번길 15, 4동 (선주지동)
89오시드 디자인<NA>인천광역시 계양구 계양대로 106, 덕인빌딩 2층 (작전동)
910(주)이에스디자인032-543-8470인천광역시 계양구 선주로 48-17, 가동 (선주지동)
순번업소명영업장전화번호영업장도로명주소
5960영광현수막032-545-2450인천광역시 계양구 주부토로 394 (작전동)
6061금손032-553-9500인천광역시 계양구 아나지로 413 (작전동)
6162태경기획032-548-8031인천광역시 계양구 계산로 55-1 (계산동)
6263영풍광고032-544-3666인천광역시 계양구 봉오대로 683 (작전동)
6364까치광고사032-551-7900인천광역시 계양구 주부토로 512 (계산동,1층)
6465오뚜기 디자인032-547-2321인천광역시 계양구 봉오대로677번길 26 (작전동)
6566혜성광고032-549-3430인천광역시 계양구 효서로 351 (작전동)
6667성실기업<NA>인천광역시 계양구 계양산로134번길 33 (계산동)
6768(주)늘푸른광고산업1661-7399인천광역시 계양구 대보로 102 (작전동)
6869점보광고032-542-6455인천광역시 계양구 경명대로 993 (계산동, 정광아파트)