Overview

Dataset statistics

Number of variables4
Number of observations65
Missing cells9
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory35.0 B

Variable types

Numeric1
Text3

Dataset

Description익산시 전체 읍면동에 있는 안경업소에 대한 상호, 도로명주소, 전화번호 등 현황을 확인 하고 할 수 있습니다. 한경업소 현황
Author전북특별자치도 익산시
URLhttps://www.data.go.kr/data/3078956/fileData.do

Alerts

전화번호 has 9 (13.8%) missing valuesMissing
순번 has unique valuesUnique
안경업소명칭 has unique valuesUnique

Reproduction

Analysis started2024-03-14 23:28:12.862822
Analysis finished2024-03-14 23:28:14.026780
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33
Minimum1
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size713.0 B
2024-03-15T08:28:14.226713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.2
Q117
median33
Q349
95-th percentile61.8
Maximum65
Range64
Interquartile range (IQR)32

Descriptive statistics

Standard deviation18.90767
Coefficient of variation (CV)0.57295971
Kurtosis-1.2
Mean33
Median Absolute Deviation (MAD)16
Skewness0
Sum2145
Variance357.5
MonotonicityStrictly increasing
2024-03-15T08:28:14.554734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
50 1
 
1.5%
36 1
 
1.5%
37 1
 
1.5%
38 1
 
1.5%
39 1
 
1.5%
40 1
 
1.5%
41 1
 
1.5%
42 1
 
1.5%
43 1
 
1.5%
Other values (55) 55
84.6%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%
58 1
1.5%
57 1
1.5%
56 1
1.5%

안경업소명칭
Text

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size648.0 B
2024-03-15T08:28:15.722537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length8.2
Min length4

Characters and Unicode

Total characters533
Distinct characters127
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

Unique65 ?
Unique (%)100.0%

Sample

1st row안경창고 싸군 익산점
2nd row아이눈안경원
3rd rowEYESAVER 안경콘택트 영등점
4th row아인안경콘택트
5th row글라스 스토리안경원
ValueCountFrequency (%)
익산점 3
 
3.3%
안경나라 3
 
3.3%
안경 3
 
3.3%
안경매니져 3
 
3.3%
익산모현점 2
 
2.2%
안경원 2
 
2.2%
영등점 2
 
2.2%
오렌즈 2
 
2.2%
잘베네안경원 1
 
1.1%
서독안경원 1
 
1.1%
Other values (70) 70
76.1%
2024-03-15T08:28:17.031907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 61
 
11.4%
경 61
 
11.4%
원 30
 
5.6%
27
 
5.1%
점 26
 
4.9%
트 14
 
2.6%
콘 11
 
2.1%
산 11
 
2.1%
택 11
 
2.1%
아 10
 
1.9%
Other values (117) 271
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 454
85.2%
Space Separator 27
 
5.1%
Uppercase Letter 22
 
4.1%
Decimal Number 18
 
3.4%
Close Punctuation 4
 
0.8%
Open Punctuation 4
 
0.8%
Other Punctuation 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 61
 
13.4%
경 61
 
13.4%
원 30
 
6.6%
점 26
 
5.7%
트 14
 
3.1%
콘 11
 
2.4%
산 11
 
2.4%
택 11
 
2.4%
아 10
 
2.2%
스 9
 
2.0%
Other values (99) 210
46.3%
Uppercase Letter
ValueCountFrequency (%)
E 7
31.8%
C 2
 
9.1%
I 2
 
9.1%
R 2
 
9.1%
A 2
 
9.1%
S 2
 
9.1%
Y 2
 
9.1%
F 1
 
4.5%
V 1
 
4.5%
K 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 9
50.0%
0 8
44.4%
2 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
, 1
 
25.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 454
85.2%
Common 57
 
10.7%
Latin 22
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 61
 
13.4%
경 61
 
13.4%
원 30
 
6.6%
점 26
 
5.7%
트 14
 
3.1%
콘 11
 
2.4%
산 11
 
2.4%
택 11
 
2.4%
아 10
 
2.2%
스 9
 
2.0%
Other values (99) 210
46.3%
Latin
ValueCountFrequency (%)
E 7
31.8%
C 2
 
9.1%
I 2
 
9.1%
R 2
 
9.1%
A 2
 
9.1%
S 2
 
9.1%
Y 2
 
9.1%
F 1
 
4.5%
V 1
 
4.5%
K 1
 
4.5%
Common
ValueCountFrequency (%)
27
47.4%
1 9
 
15.8%
0 8
 
14.0%
) 4
 
7.0%
( 4
 
7.0%
. 3
 
5.3%
2 1
 
1.8%
, 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 454
85.2%
ASCII 79
 
14.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 61
 
13.4%
경 61
 
13.4%
원 30
 
6.6%
점 26
 
5.7%
트 14
 
3.1%
콘 11
 
2.4%
산 11
 
2.4%
택 11
 
2.4%
아 10
 
2.2%
스 9
 
2.0%
Other values (99) 210
46.3%
ASCII
ValueCountFrequency (%)
27
34.2%
1 9
 
11.4%
0 8
 
10.1%
E 7
 
8.9%
) 4
 
5.1%
( 4
 
5.1%
. 3
 
3.8%
C 2
 
2.5%
I 2
 
2.5%
R 2
 
2.5%
Other values (8) 11
13.9%

소재지(도로명)
Text

Distinct64
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size648.0 B
2024-03-15T08:28:18.111876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length29
Mean length17.876923
Min length11

Characters and Unicode

Total characters1162
Distinct characters88
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

Unique63 ?
Unique (%)96.9%

Sample

1st row 고봉로 307, 1층 (영등동)
2nd row 고봉로18길 101 (어양동)
3rd row 고봉로30길 28 (영등동)
4th row 고봉로30길 3, 109동 101호 (영등동, 제일상가 )
5th row 고봉로32길 18 (영등동)
ValueCountFrequency (%)
영등동 14
 
6.1%
모현동1가 11
 
4.8%
1층 9
 
3.9%
무왕로 8
 
3.5%
신동 8
 
3.5%
부송동 6
 
2.6%
고현로 5
 
2.2%
창인동1가 5
 
2.2%
남중동 4
 
1.7%
익산대로 4
 
1.7%
Other values (121) 157
68.0%
2024-03-15T08:28:19.792513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
231
19.9%
1 101
 
8.7%
동 70
 
6.0%
로 63
 
5.4%
( 60
 
5.2%
) 60
 
5.2%
0 35
 
3.0%
3 27
 
2.3%
, 26
 
2.2%
길 24
 
2.1%
Other values (78) 465
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 494
42.5%
Decimal Number 280
24.1%
Space Separator 231
19.9%
Open Punctuation 60
 
5.2%
Close Punctuation 60
 
5.2%
Other Punctuation 26
 
2.2%
Dash Punctuation 10
 
0.9%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 70
 
14.2%
로 63
 
12.8%
길 24
 
4.9%
가 22
 
4.5%
등 18
 
3.6%
현 17
 
3.4%
산 15
 
3.0%
영 14
 
2.8%
중 13
 
2.6%
송 13
 
2.6%
Other values (62) 225
45.5%
Decimal Number
ValueCountFrequency (%)
1 101
36.1%
0 35
 
12.5%
3 27
 
9.6%
2 24
 
8.6%
4 20
 
7.1%
5 17
 
6.1%
9 16
 
5.7%
8 15
 
5.4%
6 13
 
4.6%
7 12
 
4.3%
Space Separator
ValueCountFrequency (%)
231
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 667
57.4%
Hangul 494
42.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 70
 
14.2%
로 63
 
12.8%
길 24
 
4.9%
가 22
 
4.5%
등 18
 
3.6%
현 17
 
3.4%
산 15
 
3.0%
영 14
 
2.8%
중 13
 
2.6%
송 13
 
2.6%
Other values (62) 225
45.5%
Common
ValueCountFrequency (%)
231
34.6%
1 101
15.1%
( 60
 
9.0%
) 60
 
9.0%
0 35
 
5.2%
3 27
 
4.0%
, 26
 
3.9%
2 24
 
3.6%
4 20
 
3.0%
5 17
 
2.5%
Other values (5) 66
 
9.9%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 668
57.5%
Hangul 494
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
34.6%
1 101
15.1%
( 60
 
9.0%
) 60
 
9.0%
0 35
 
5.2%
3 27
 
4.0%
, 26
 
3.9%
2 24
 
3.6%
4 20
 
3.0%
5 17
 
2.5%
Other values (6) 67
 
10.0%
Hangul
ValueCountFrequency (%)
동 70
 
14.2%
로 63
 
12.8%
길 24
 
4.9%
가 22
 
4.5%
등 18
 
3.6%
현 17
 
3.4%
산 15
 
3.0%
영 14
 
2.8%
중 13
 
2.6%
송 13
 
2.6%
Other values (62) 225
45.5%

전화번호
Text

MISSING 

Distinct54
Distinct (%)96.4%
Missing9
Missing (%)13.8%
Memory size648.0 B
2024-03-15T08:28:20.807192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters672
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

Unique52 ?
Unique (%)92.9%

Sample

1st row063-843-2585
2nd row063-836-6544
3rd row063-832-0233
4th row063-833-4411
5th row063-842-3734
ValueCountFrequency (%)
063-842-3993 2
 
3.6%
063-834-2332 2
 
3.6%
063-855-8297 1
 
1.8%
063-861-0427 1
 
1.8%
063-843-2585 1
 
1.8%
063-842-0670 1
 
1.8%
063-852-5788 1
 
1.8%
063-854-1110 1
 
1.8%
063-852-7744 1
 
1.8%
063-835-6630 1
 
1.8%
Other values (44) 44
78.6%
2024-03-15T08:28:22.091410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 112
16.7%
3 110
16.4%
0 97
14.4%
6 82
12.2%
8 82
12.2%
5 44
 
6.5%
2 37
 
5.5%
1 32
 
4.8%
4 30
 
4.5%
7 29
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 560
83.3%
Dash Punctuation 112
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 110
19.6%
0 97
17.3%
6 82
14.6%
8 82
14.6%
5 44
 
7.9%
2 37
 
6.6%
1 32
 
5.7%
4 30
 
5.4%
7 29
 
5.2%
9 17
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 672
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 112
16.7%
3 110
16.4%
0 97
14.4%
6 82
12.2%
8 82
12.2%
5 44
 
6.5%
2 37
 
5.5%
1 32
 
4.8%
4 30
 
4.5%
7 29
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 112
16.7%
3 110
16.4%
0 97
14.4%
6 82
12.2%
8 82
12.2%
5 44
 
6.5%
2 37
 
5.5%
1 32
 
4.8%
4 30
 
4.5%
7 29
 
4.3%

Interactions

2024-03-15T08:28:13.298710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T08:28:22.300805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번안경업소명칭소재지(도로명)전화번호
순번1.0001.0001.0000.826
안경업소명칭1.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.000
전화번호0.8261.0001.0001.000

Missing values

2024-03-15T08:28:13.627303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T08:28:13.916873image/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

순번안경업소명칭소재지(도로명)전화번호
01안경창고 싸군 익산점고봉로 307, 1층 (영등동)063-843-2585
12아이눈안경원고봉로18길 101 (어양동)063-836-6544
23EYESAVER 안경콘택트 영등점고봉로30길 28 (영등동)063-832-0233
34아인안경콘택트고봉로30길 3, 109동 101호 (영등동, 제일상가 )063-833-4411
45글라스 스토리안경원고봉로32길 18 (영등동)063-842-3734
56수정안경원고현로 104 (모현동1가)063-852-5763
67K비젼안경 익산모현점고현로 105, 1층 (모현동1가)063-837-7900
78안경매니져 모현점고현로 110 (모현동1가)063-842-0707
89레옹안경콘택트모현점고현로 90 (모현동1가)063-858-4985
9101001안경콘택트모현점고현로 93, 111호 (모현동1가, 현대마트 )063-858-6001
순번안경업소명칭소재지(도로명)전화번호
5556다비치안경익산역점중앙로 50 (갈산동)063-841-8220
5657유진안경원중앙로3길 13-1 (창인동1가)063-851-8576
5758금강안경원중앙로5길 17-4 (창인동1가)063-854-5130
5859마트안경콘택트평동로 705, 1층 (동산동, 이마트)063-852-9123
59601001안경,콘택트동산점평동로12길 2 (동산동)063-857-9001
6061안경만들기 익산어양점하나로 426 (어양동)063-835-0708
6162해바라기안경원함열읍 와리3길 19-1063-861-0427
6263리스안경원함열읍 함열중앙로 22063-862-1988
6364안경나라(황등점)황등면 황등로 115<NA>
6465크로바안경황등면 황등로 137063-855-6618