Overview

Dataset statistics

Number of variables5
Number of observations62
Missing cells16
Missing cells (%)5.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory43.1 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description인천광역시 남동구 조명판매업소 현황에 대한 데이터로 연번, 업체명, 소재지, 전화번호, 데이터기준일자 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/15091359/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 16 (25.8%) missing valuesMissing
연번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:58:55.428472
Analysis finished2023-12-12 15:58:55.954659
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.5
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-13T00:58:56.048335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.05
Q116.25
median31.5
Q346.75
95-th percentile58.95
Maximum62
Range61
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation18.041619
Coefficient of variation (CV)0.5727498
Kurtosis-1.2
Mean31.5
Median Absolute Deviation (MAD)15.5
Skewness0
Sum1953
Variance325.5
MonotonicityStrictly increasing
2023-12-13T00:58:56.187313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
48 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (52) 52
83.9%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%
53 1
1.6%

업체명
Text

Distinct61
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-13T00:58:56.491208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length5.7741935
Min length2

Characters and Unicode

Total characters358
Distinct characters107
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)96.8%

Sample

1st row명인조명
2nd row대경LED
3rd row대원전기조명
4th row루이데코
5th row효성 노엘갤럭시아 LED조명
ValueCountFrequency (%)
효성 2
 
3.0%
led조명 2
 
3.0%
노엘갤럭시아 2
 
3.0%
영동조명 1
 
1.5%
인천조명서비스센타 1
 
1.5%
명인조명 1
 
1.5%
디케이조명 1
 
1.5%
우성전기조명 1
 
1.5%
엘이디시대 1
 
1.5%
유로조명 1
 
1.5%
Other values (54) 54
80.6%
2023-12-13T00:58:57.111702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
명 37
 
10.3%
조 36
 
10.1%
이 19
 
5.3%
전 17
 
4.7%
기 16
 
4.5%
엘 11
 
3.1%
D 8
 
2.2%
스 8
 
2.2%
디 8
 
2.2%
L 8
 
2.2%
Other values (97) 190
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 326
91.1%
Uppercase Letter 24
 
6.7%
Space Separator 5
 
1.4%
Lowercase Letter 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
명 37
 
11.3%
조 36
 
11.0%
이 19
 
5.8%
전 17
 
5.2%
기 16
 
4.9%
엘 11
 
3.4%
스 8
 
2.5%
디 8
 
2.5%
라 7
 
2.1%
대 6
 
1.8%
Other values (89) 161
49.4%
Uppercase Letter
ValueCountFrequency (%)
D 8
33.3%
L 8
33.3%
E 7
29.2%
S 1
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
l 1
33.3%
e 1
33.3%
d 1
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 326
91.1%
Latin 27
 
7.5%
Common 5
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
명 37
 
11.3%
조 36
 
11.0%
이 19
 
5.8%
전 17
 
5.2%
기 16
 
4.9%
엘 11
 
3.4%
스 8
 
2.5%
디 8
 
2.5%
라 7
 
2.1%
대 6
 
1.8%
Other values (89) 161
49.4%
Latin
ValueCountFrequency (%)
D 8
29.6%
L 8
29.6%
E 7
25.9%
S 1
 
3.7%
l 1
 
3.7%
e 1
 
3.7%
d 1
 
3.7%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 326
91.1%
ASCII 32
 
8.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
명 37
 
11.3%
조 36
 
11.0%
이 19
 
5.8%
전 17
 
5.2%
기 16
 
4.9%
엘 11
 
3.4%
스 8
 
2.5%
디 8
 
2.5%
라 7
 
2.1%
대 6
 
1.8%
Other values (89) 161
49.4%
ASCII
ValueCountFrequency (%)
D 8
25.0%
L 8
25.0%
E 7
21.9%
5
15.6%
S 1
 
3.1%
l 1
 
3.1%
e 1
 
3.1%
d 1
 
3.1%

소재지
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-13T00:58:57.560007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length28
Mean length21.548387
Min length15

Characters and Unicode

Total characters1336
Distinct characters102
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 인주대로 509
2nd row인천광역시 남동구 인주대로 890 2층
3rd row인천광역시 남동구 인주대로 655 대원전기조명
4th row인천광역시 남동구 경인로 586-1
5th row인천광역시 남동구 에코중앙로156번길 13-3
ValueCountFrequency (%)
인천광역시 62
22.5%
남동구 62
22.5%
백범로 7
 
2.5%
인주대로 5
 
1.8%
1층 5
 
1.8%
경인로 3
 
1.1%
호구포로 3
 
1.1%
201호 2
 
0.7%
31 2
 
0.7%
4 2
 
0.7%
Other values (118) 123
44.6%
2023-12-13T00:58:58.294653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
214
16.0%
동 73
 
5.5%
인 72
 
5.4%
남 72
 
5.4%
구 70
 
5.2%
천 63
 
4.7%
광 62
 
4.6%
역 62
 
4.6%
시 62
 
4.6%
로 61
 
4.6%
Other values (92) 525
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 832
62.3%
Decimal Number 274
 
20.5%
Space Separator 214
 
16.0%
Dash Punctuation 12
 
0.9%
Uppercase Letter 2
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 73
 
8.8%
인 72
 
8.7%
남 72
 
8.7%
구 70
 
8.4%
천 63
 
7.6%
광 62
 
7.5%
역 62
 
7.5%
시 62
 
7.5%
로 61
 
7.3%
길 26
 
3.1%
Other values (76) 209
25.1%
Decimal Number
ValueCountFrequency (%)
1 52
19.0%
5 38
13.9%
3 33
12.0%
2 31
11.3%
6 27
9.9%
0 25
9.1%
4 21
7.7%
8 19
 
6.9%
7 16
 
5.8%
9 12
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
J 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
214
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 832
62.3%
Common 502
37.6%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 73
 
8.8%
인 72
 
8.7%
남 72
 
8.7%
구 70
 
8.4%
천 63
 
7.6%
광 62
 
7.5%
역 62
 
7.5%
시 62
 
7.5%
로 61
 
7.3%
길 26
 
3.1%
Other values (76) 209
25.1%
Common
ValueCountFrequency (%)
214
42.6%
1 52
 
10.4%
5 38
 
7.6%
3 33
 
6.6%
2 31
 
6.2%
6 27
 
5.4%
0 25
 
5.0%
4 21
 
4.2%
8 19
 
3.8%
7 16
 
3.2%
Other values (4) 26
 
5.2%
Latin
ValueCountFrequency (%)
J 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 832
62.3%
ASCII 504
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
214
42.5%
1 52
 
10.3%
5 38
 
7.5%
3 33
 
6.5%
2 31
 
6.2%
6 27
 
5.4%
0 25
 
5.0%
4 21
 
4.2%
8 19
 
3.8%
7 16
 
3.2%
Other values (6) 28
 
5.6%
Hangul
ValueCountFrequency (%)
동 73
 
8.8%
인 72
 
8.7%
남 72
 
8.7%
구 70
 
8.4%
천 63
 
7.6%
광 62
 
7.5%
역 62
 
7.5%
시 62
 
7.5%
로 61
 
7.3%
길 26
 
3.1%
Other values (76) 209
25.1%

전화번호
Text

MISSING 

Distinct46
Distinct (%)100.0%
Missing16
Missing (%)25.8%
Memory size628.0 B
2023-12-13T00:58:58.644864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length11

Characters and Unicode

Total characters552
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 (%)100.0%

Sample

1st row032-433-0455
2nd row032-424-5666
3rd row032-468-3988
4th row032-424-7461
5th row032-433-1659
ValueCountFrequency (%)
032-422-7577 1
 
2.2%
032-859-0006 1
 
2.2%
032-572-4940 1
 
2.2%
032-428-3431 1
 
2.2%
032-464-3988 1
 
2.2%
032-473-7720 1
 
2.2%
032-462-1346 1
 
2.2%
02-540-5577 1
 
2.2%
032-463-2007 1
 
2.2%
032-815-2588 1
 
2.2%
Other values (36) 36
78.3%
2023-12-13T00:58:59.217826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 92
16.7%
2 82
14.9%
0 81
14.7%
3 70
12.7%
4 49
8.9%
1 36
 
6.5%
7 34
 
6.2%
5 34
 
6.2%
8 31
 
5.6%
6 28
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 460
83.3%
Dash Punctuation 92
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 82
17.8%
0 81
17.6%
3 70
15.2%
4 49
10.7%
1 36
7.8%
7 34
7.4%
5 34
7.4%
8 31
 
6.7%
6 28
 
6.1%
9 15
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 552
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 92
16.7%
2 82
14.9%
0 81
14.7%
3 70
12.7%
4 49
8.9%
1 36
 
6.5%
7 34
 
6.2%
5 34
 
6.2%
8 31
 
5.6%
6 28
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 92
16.7%
2 82
14.9%
0 81
14.7%
3 70
12.7%
4 49
8.9%
1 36
 
6.5%
7 34
 
6.2%
5 34
 
6.2%
8 31
 
5.6%
6 28
 
5.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-09-04
62 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-04
2nd row2023-09-04
3rd row2023-09-04
4th row2023-09-04
5th row2023-09-04

Common Values

ValueCountFrequency (%)
2023-09-04 62
100.0%

Length

2023-12-13T00:58:59.408664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:58:59.902962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-04 62
100.0%

Interactions

2023-12-13T00:58:55.691337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:59:00.003933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명소재지전화번호
연번1.0000.9421.0001.000
업체명0.9421.0001.0001.000
소재지1.0001.0001.0001.000
전화번호1.0001.0001.0001.000

Missing values

2023-12-13T00:58:55.808114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:58:55.900943image/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

연번업체명소재지전화번호데이터기준일자
01명인조명인천광역시 남동구 인주대로 509032-433-04552023-09-04
12대경LED인천광역시 남동구 인주대로 890 2층032-424-56662023-09-04
23대원전기조명인천광역시 남동구 인주대로 655 대원전기조명032-468-39882023-09-04
34루이데코인천광역시 남동구 경인로 586-1032-424-74612023-09-04
45효성 노엘갤럭시아 LED조명인천광역시 남동구 에코중앙로156번길 13-3032-433-16592023-09-04
56리빙라이트 조명전시장인천광역시 남동구 백범로 164-1032-471-11992023-09-04
67엘이디앤조명인천광역시 남동구 백범로 249032-503-80002023-09-04
78신광전기조명인천광역시 남동구 청능대로 559032-834-71002023-09-04
89토리조명인천광역시 남동구 호구포로 524 토리조명032-427-51112023-09-04
910우영전기인천광역시 남동구 인주대로 689032-473-10122023-09-04
연번업체명소재지전화번호데이터기준일자
5253엠에스라이트인천광역시 남동구 호구포로764번길 17-1<NA>2023-09-04
5354세원에프엘인천광역시 남동구 앵고개로654번길 15032-421-35532023-09-04
5455지엘인천광역시 남동구 백범로 258032-466-27782023-09-04
5556등불조명인천광역시 남동구 문화서로3번길 31032-438-22052023-09-04
5657부경전기조명인천광역시 남동구 석촌로36번길 25032-435-46102023-09-04
5758유성조명인천광역시 남동구 석정로461번길 50032-875-10022023-09-04
5859인천조명서비스센타인천광역시 남동구 구월로372번길 21-7 201호032-433-79192023-09-04
5960영동조명인천광역시 남동구 백범로 147-1032-466-98042023-09-04
6061디케이조명인천광역시 남동구 만월북로44번길 8-26<NA>2023-09-04
6162이노렉스테크놀러지인천광역시 남동구 남동동로277번길 24032-810-96002023-09-04