Overview

Dataset statistics

Number of variables6
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory53.0 B

Variable types

Numeric1
Text3
Categorical2

Dataset

Description관내 안경업소 현황에 대한 데이터로 안경업소명칭, 사업장소재지(도로명), 사업장전화번호 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/3079896/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
순번 has unique valuesUnique
안경업소명칭 has unique valuesUnique
사업장소재지(도로명) has unique valuesUnique
사업장전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:22:17.454751
Analysis finished2023-12-12 06:22:18.091838
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T15:22:18.165470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q19
median17
Q325
95-th percentile31.4
Maximum33
Range32
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.6695398
Coefficient of variation (CV)0.56879646
Kurtosis-1.2
Mean17
Median Absolute Deviation (MAD)8
Skewness0
Sum561
Variance93.5
MonotonicityStrictly increasing
2023-12-12T15:22:18.297950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 1
 
3.0%
26 1
 
3.0%
20 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
23 1
 
3.0%
24 1
 
3.0%
25 1
 
3.0%
27 1
 
3.0%
2 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1 1
3.0%
2 1
3.0%
3 1
3.0%
4 1
3.0%
5 1
3.0%
6 1
3.0%
7 1
3.0%
8 1
3.0%
9 1
3.0%
10 1
3.0%
ValueCountFrequency (%)
33 1
3.0%
32 1
3.0%
31 1
3.0%
30 1
3.0%
29 1
3.0%
28 1
3.0%
27 1
3.0%
26 1
3.0%
25 1
3.0%
24 1
3.0%

안경업소명칭
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T15:22:18.544074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length11
Mean length8.0909091
Min length4

Characters and Unicode

Total characters267
Distinct characters103
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row으뜸플러스 양주옥정점
2nd row아이데코 양주옥정점
3rd row뉴아이안경
4th row이노티안경(옥정타운점)
5th row으뜸플러스 양주덕정점
ValueCountFrequency (%)
양주옥정점 3
 
6.0%
으뜸플러스 2
 
4.0%
안경 2
 
4.0%
한글라스안경 1
 
2.0%
안경원 1
 
2.0%
그랑프리 1
 
2.0%
콘텍트 1
 
2.0%
덕계 1
 
2.0%
실로암 1
 
2.0%
자이안경.렌즈아이 1
 
2.0%
Other values (36) 36
72.0%
2023-12-12T15:22:18.969531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 26
 
9.7%
경 26
 
9.7%
17
 
6.4%
이 12
 
4.5%
점 11
 
4.1%
아 9
 
3.4%
양 8
 
3.0%
주 8
 
3.0%
정 7
 
2.6%
옥 6
 
2.2%
Other values (93) 137
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 228
85.4%
Space Separator 17
 
6.4%
Lowercase Letter 9
 
3.4%
Decimal Number 4
 
1.5%
Uppercase Letter 3
 
1.1%
Other Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%
Close Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 26
 
11.4%
경 26
 
11.4%
이 12
 
5.3%
점 11
 
4.8%
아 9
 
3.9%
양 8
 
3.5%
주 8
 
3.5%
정 7
 
3.1%
옥 6
 
2.6%
스 5
 
2.2%
Other values (78) 110
48.2%
Lowercase Letter
ValueCountFrequency (%)
e 3
33.3%
n 2
22.2%
c 1
 
11.1%
h 1
 
11.1%
a 1
 
11.1%
l 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
F 1
33.3%
L 1
33.3%
S 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 227
85.0%
Common 27
 
10.1%
Latin 12
 
4.5%
Han 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 26
 
11.5%
경 26
 
11.5%
이 12
 
5.3%
점 11
 
4.8%
아 9
 
4.0%
양 8
 
3.5%
주 8
 
3.5%
정 7
 
3.1%
옥 6
 
2.6%
스 5
 
2.2%
Other values (77) 109
48.0%
Latin
ValueCountFrequency (%)
e 3
25.0%
n 2
16.7%
F 1
 
8.3%
L 1
 
8.3%
S 1
 
8.3%
c 1
 
8.3%
h 1
 
8.3%
a 1
 
8.3%
l 1
 
8.3%
Common
ValueCountFrequency (%)
17
63.0%
. 2
 
7.4%
1 2
 
7.4%
( 2
 
7.4%
0 2
 
7.4%
) 2
 
7.4%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 227
85.0%
ASCII 39
 
14.6%
CJK 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 26
 
11.5%
경 26
 
11.5%
이 12
 
5.3%
점 11
 
4.8%
아 9
 
4.0%
양 8
 
3.5%
주 8
 
3.5%
정 7
 
3.1%
옥 6
 
2.6%
스 5
 
2.2%
Other values (77) 109
48.0%
ASCII
ValueCountFrequency (%)
17
43.6%
e 3
 
7.7%
. 2
 
5.1%
n 2
 
5.1%
1 2
 
5.1%
( 2
 
5.1%
0 2
 
5.1%
) 2
 
5.1%
F 1
 
2.6%
L 1
 
2.6%
Other values (5) 5
 
12.8%
CJK
ValueCountFrequency (%)
家 1
100.0%

사업장소재지(도로명)
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T15:22:19.209486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length29.666667
Min length18

Characters and Unicode

Total characters979
Distinct characters112
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row경기도 양주시 옥정로 200 (옥정동)
2nd row경기도 양주시 옥정로 139, 디올스퀘어빌딩 (옥정동)
3rd row경기도 양주시 옥정동로7다길 62, 대길프라자 107호 (옥정동)
4th row경기도 양주시 회천남로 76, 한덕타워 114호 (옥정동)
5th row경기도 양주시 화합로 1355 (덕정동)
ValueCountFrequency (%)
경기도 33
 
15.6%
양주시 33
 
15.6%
1층 9
 
4.3%
옥정동 8
 
3.8%
덕정동 5
 
2.4%
평화로 5
 
2.4%
덕계동 4
 
1.9%
회정로 4
 
1.9%
옥정로 3
 
1.4%
백석읍 3
 
1.4%
Other values (89) 104
49.3%
2023-12-12T15:22:19.559539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
 
18.2%
1 53
 
5.4%
주 40
 
4.1%
양 39
 
4.0%
경 33
 
3.4%
도 33
 
3.4%
시 33
 
3.4%
기 33
 
3.4%
동 29
 
3.0%
) 29
 
3.0%
Other values (102) 479
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 557
56.9%
Space Separator 178
 
18.2%
Decimal Number 156
 
15.9%
Close Punctuation 29
 
3.0%
Open Punctuation 29
 
3.0%
Other Punctuation 25
 
2.6%
Uppercase Letter 3
 
0.3%
Letter Number 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 40
 
7.2%
양 39
 
7.0%
경 33
 
5.9%
도 33
 
5.9%
시 33
 
5.9%
기 33
 
5.9%
동 29
 
5.2%
로 29
 
5.2%
정 27
 
4.8%
호 15
 
2.7%
Other values (83) 246
44.2%
Decimal Number
ValueCountFrequency (%)
1 53
34.0%
0 22
14.1%
4 16
 
10.3%
2 11
 
7.1%
3 11
 
7.1%
8 11
 
7.1%
7 9
 
5.8%
5 9
 
5.8%
6 8
 
5.1%
9 6
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
F 1
33.3%
M 1
33.3%
Space Separator
ValueCountFrequency (%)
178
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Letter Number
ValueCountFrequency (%)
Ⅳ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 557
56.9%
Common 418
42.7%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 40
 
7.2%
양 39
 
7.0%
경 33
 
5.9%
도 33
 
5.9%
시 33
 
5.9%
기 33
 
5.9%
동 29
 
5.2%
로 29
 
5.2%
정 27
 
4.8%
호 15
 
2.7%
Other values (83) 246
44.2%
Common
ValueCountFrequency (%)
178
42.6%
1 53
 
12.7%
) 29
 
6.9%
( 29
 
6.9%
, 25
 
6.0%
0 22
 
5.3%
4 16
 
3.8%
2 11
 
2.6%
3 11
 
2.6%
8 11
 
2.6%
Other values (5) 33
 
7.9%
Latin
ValueCountFrequency (%)
Ⅳ 1
25.0%
L 1
25.0%
F 1
25.0%
M 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 557
56.9%
ASCII 421
43.0%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
178
42.3%
1 53
 
12.6%
) 29
 
6.9%
( 29
 
6.9%
, 25
 
5.9%
0 22
 
5.2%
4 16
 
3.8%
2 11
 
2.6%
3 11
 
2.6%
8 11
 
2.6%
Other values (8) 36
 
8.6%
Hangul
ValueCountFrequency (%)
주 40
 
7.2%
양 39
 
7.0%
경 33
 
5.9%
도 33
 
5.9%
시 33
 
5.9%
기 33
 
5.9%
동 29
 
5.2%
로 29
 
5.2%
정 27
 
4.8%
호 15
 
2.7%
Other values (83) 246
44.2%
Number Forms
ValueCountFrequency (%)
Ⅳ 1
100.0%

사업장전화번호
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T15:22:19.773495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.030303
Min length12

Characters and Unicode

Total characters397
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

Unique33 ?
Unique (%)100.0%

Sample

1st row031-868-6009
2nd row031-8083-8090
3rd row031-858-3001
4th row031-867-7798
5th row031-859-5036
ValueCountFrequency (%)
031-868-6009 1
 
3.0%
031-856-4047 1
 
3.0%
031-864-5581 1
 
3.0%
031-836-2263 1
 
3.0%
031-864-4520 1
 
3.0%
031-836-3773 1
 
3.0%
031-863-5808 1
 
3.0%
031-859-8835 1
 
3.0%
031-859-1009 1
 
3.0%
031-859-2312 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T15:22:20.133601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 66
16.6%
3 59
14.9%
0 54
13.6%
8 50
12.6%
1 42
10.6%
6 24
 
6.0%
5 23
 
5.8%
2 22
 
5.5%
9 20
 
5.0%
4 20
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 331
83.4%
Dash Punctuation 66
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 59
17.8%
0 54
16.3%
8 50
15.1%
1 42
12.7%
6 24
7.3%
5 23
 
6.9%
2 22
 
6.6%
9 20
 
6.0%
4 20
 
6.0%
7 17
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 397
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 66
16.6%
3 59
14.9%
0 54
13.6%
8 50
12.6%
1 42
10.6%
6 24
 
6.0%
5 23
 
5.8%
2 22
 
5.5%
9 20
 
5.0%
4 20
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 397
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 66
16.6%
3 59
14.9%
0 54
13.6%
8 50
12.6%
1 42
10.6%
6 24
 
6.0%
5 23
 
5.8%
2 22
 
5.5%
9 20
 
5.0%
4 20
 
5.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
양주시 감염병관리과
33 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양주시 감염병관리과
2nd row양주시 감염병관리과
3rd row양주시 감염병관리과
4th row양주시 감염병관리과
5th row양주시 감염병관리과

Common Values

ValueCountFrequency (%)
양주시 감염병관리과 33
100.0%

Length

2023-12-12T15:22:20.269371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:22:20.366057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양주시 33
50.0%
감염병관리과 33
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-08-01
33 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-01
2nd row2023-08-01
3rd row2023-08-01
4th row2023-08-01
5th row2023-08-01

Common Values

ValueCountFrequency (%)
2023-08-01 33
100.0%

Length

2023-12-12T15:22:20.460788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:22:20.556893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-01 33
100.0%

Interactions

2023-12-12T15:22:17.732237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:22:20.614852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번안경업소명칭사업장소재지(도로명)사업장전화번호
순번1.0001.0001.0001.000
안경업소명칭1.0001.0001.0001.000
사업장소재지(도로명)1.0001.0001.0001.000
사업장전화번호1.0001.0001.0001.000

Missing values

2023-12-12T15:22:17.900195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:22:18.045666image/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

순번안경업소명칭사업장소재지(도로명)사업장전화번호관리기관명데이터기준일자
01으뜸플러스 양주옥정점경기도 양주시 옥정로 200 (옥정동)031-868-6009양주시 감염병관리과2023-08-01
12아이데코 양주옥정점경기도 양주시 옥정로 139, 디올스퀘어빌딩 (옥정동)031-8083-8090양주시 감염병관리과2023-08-01
23뉴아이안경경기도 양주시 옥정동로7다길 62, 대길프라자 107호 (옥정동)031-858-3001양주시 감염병관리과2023-08-01
34이노티안경(옥정타운점)경기도 양주시 회천남로 76, 한덕타워 114호 (옥정동)031-867-7798양주시 감염병관리과2023-08-01
45으뜸플러스 양주덕정점경기도 양주시 화합로 1355 (덕정동)031-859-5036양주시 감염병관리과2023-08-01
56안경家(가)경기도 양주시 옥정동로7다길 46, 폴리프라자Ⅳ 1층 105호 (옥정동)031-928-6466양주시 감염병관리과2023-08-01
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