Overview

Dataset statistics

Number of variables4
Number of observations76
Missing cells2
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory34.7 B

Variable types

Numeric1
Text3

Dataset

Description안경업소현황_20200622
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3075589

Alerts

전화번호 has 2 (2.6%) missing valuesMissing
순번 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:06:45.768099
Analysis finished2023-12-10 17:06:46.610285
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.5
Minimum1
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-11T02:06:46.807373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.75
Q119.75
median38.5
Q357.25
95-th percentile72.25
Maximum76
Range75
Interquartile range (IQR)37.5

Descriptive statistics

Standard deviation22.083176
Coefficient of variation (CV)0.57358899
Kurtosis-1.2
Mean38.5
Median Absolute Deviation (MAD)19
Skewness0
Sum2926
Variance487.66667
MonotonicityStrictly increasing
2023-12-11T02:06:47.051703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
50 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
49 1
 
1.3%
Other values (66) 66
86.8%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%
67 1
1.3%

업소명
Text

Distinct69
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-11T02:06:47.492331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length7.1973684
Min length4

Characters and Unicode

Total characters547
Distinct characters139
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

Unique64 ?
Unique (%)84.2%

Sample

1st row으뜸50안경 해운대역점
2nd row포레 안경원
3rd row으뜸50안경 장산역점
4th row눈사랑안경 해운대점
5th row아이프레임
ValueCountFrequency (%)
비추미안경 5
 
5.1%
눈사랑안경 3
 
3.1%
갤러리안경 3
 
3.1%
안경나라 3
 
3.1%
해운대점 3
 
3.1%
센텀점 2
 
2.0%
다비치안경 2
 
2.0%
으뜸50안경 2
 
2.0%
오렌즈 2
 
2.0%
아이젠트리 2
 
2.0%
Other values (71) 71
72.4%
2023-12-11T02:06:48.259423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 59
 
10.8%
경 59
 
10.8%
22
 
4.0%
점 19
 
3.5%
이 18
 
3.3%
원 15
 
2.7%
아 14
 
2.6%
비 11
 
2.0%
스 11
 
2.0%
눈 10
 
1.8%
Other values (129) 309
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
86.8%
Space Separator 22
 
4.0%
Lowercase Letter 19
 
3.5%
Uppercase Letter 17
 
3.1%
Open Punctuation 5
 
0.9%
Close Punctuation 5
 
0.9%
Decimal Number 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 59
 
12.4%
경 59
 
12.4%
점 19
 
4.0%
이 18
 
3.8%
원 15
 
3.2%
아 14
 
2.9%
비 11
 
2.3%
스 11
 
2.3%
눈 10
 
2.1%
대 9
 
1.9%
Other values (102) 250
52.6%
Lowercase Letter
ValueCountFrequency (%)
e 4
21.1%
c 3
15.8%
n 2
10.5%
a 2
10.5%
o 2
10.5%
f 1
 
5.3%
d 1
 
5.3%
s 1
 
5.3%
h 1
 
5.3%
m 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
O 3
17.6%
C 2
11.8%
E 2
11.8%
S 2
11.8%
M 2
11.8%
N 1
 
5.9%
D 1
 
5.9%
F 1
 
5.9%
A 1
 
5.9%
K 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
5 2
50.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 475
86.8%
Common 36
 
6.6%
Latin 36
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 59
 
12.4%
경 59
 
12.4%
점 19
 
4.0%
이 18
 
3.8%
원 15
 
3.2%
아 14
 
2.9%
비 11
 
2.3%
스 11
 
2.3%
눈 10
 
2.1%
대 9
 
1.9%
Other values (102) 250
52.6%
Latin
ValueCountFrequency (%)
e 4
 
11.1%
c 3
 
8.3%
O 3
 
8.3%
n 2
 
5.6%
C 2
 
5.6%
E 2
 
5.6%
S 2
 
5.6%
a 2
 
5.6%
o 2
 
5.6%
M 2
 
5.6%
Other values (12) 12
33.3%
Common
ValueCountFrequency (%)
22
61.1%
( 5
 
13.9%
) 5
 
13.9%
0 2
 
5.6%
5 2
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
86.8%
ASCII 72
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 59
 
12.4%
경 59
 
12.4%
점 19
 
4.0%
이 18
 
3.8%
원 15
 
3.2%
아 14
 
2.9%
비 11
 
2.3%
스 11
 
2.3%
눈 10
 
2.1%
대 9
 
1.9%
Other values (102) 250
52.6%
ASCII
ValueCountFrequency (%)
22
30.6%
( 5
 
6.9%
) 5
 
6.9%
e 4
 
5.6%
c 3
 
4.2%
O 3
 
4.2%
n 2
 
2.8%
C 2
 
2.8%
0 2
 
2.8%
5 2
 
2.8%
Other values (17) 22
30.6%

소재지(도로명)
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-11T02:06:48.683188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length38
Mean length33.526316
Min length22

Characters and Unicode

Total characters2548
Distinct characters145
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

Unique76 ?
Unique (%)100.0%

Sample

1st row부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 226호 (우동)
2nd row부산광역시 해운대구 좌동순환로 505, 센트럴메디타워 1101호 (중동)
3rd row부산광역시 해운대구 해운대로 794, 엘리움 206호 (좌동)
4th row부산광역시 해운대구 구남로29번길 35, 1층 (중동)
5th row부산광역시 해운대구 해운대로 723, 해운대타워마브러스 103동 113호 (중동)
ValueCountFrequency (%)
부산광역시 76
 
16.0%
해운대구 76
 
16.0%
우동 21
 
4.4%
1층 16
 
3.4%
해운대로 13
 
2.7%
좌동 11
 
2.3%
반여동 11
 
2.3%
2층 8
 
1.7%
재반로 8
 
1.7%
반송동 8
 
1.7%
Other values (160) 227
47.8%
2023-12-11T02:06:49.340631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
399
 
15.7%
대 106
 
4.2%
1 105
 
4.1%
해 100
 
3.9%
운 100
 
3.9%
동 97
 
3.8%
시 92
 
3.6%
, 81
 
3.2%
구 81
 
3.2%
산 80
 
3.1%
Other values (135) 1307
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1541
60.5%
Space Separator 399
 
15.7%
Decimal Number 362
 
14.2%
Other Punctuation 81
 
3.2%
Open Punctuation 76
 
3.0%
Close Punctuation 76
 
3.0%
Dash Punctuation 10
 
0.4%
Uppercase Letter 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 106
 
6.9%
해 100
 
6.5%
운 100
 
6.5%
동 97
 
6.3%
시 92
 
6.0%
구 81
 
5.3%
산 80
 
5.2%
부 77
 
5.0%
로 76
 
4.9%
역 76
 
4.9%
Other values (117) 656
42.6%
Decimal Number
ValueCountFrequency (%)
1 105
29.0%
2 59
16.3%
0 46
12.7%
3 38
 
10.5%
5 23
 
6.4%
4 22
 
6.1%
8 20
 
5.5%
7 17
 
4.7%
9 17
 
4.7%
6 15
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
E 1
50.0%
Space Separator
ValueCountFrequency (%)
399
100.0%
Other Punctuation
ValueCountFrequency (%)
, 81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1541
60.5%
Common 1005
39.4%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 106
 
6.9%
해 100
 
6.5%
운 100
 
6.5%
동 97
 
6.3%
시 92
 
6.0%
구 81
 
5.3%
산 80
 
5.2%
부 77
 
5.0%
로 76
 
4.9%
역 76
 
4.9%
Other values (117) 656
42.6%
Common
ValueCountFrequency (%)
399
39.7%
1 105
 
10.4%
, 81
 
8.1%
( 76
 
7.6%
) 76
 
7.6%
2 59
 
5.9%
0 46
 
4.6%
3 38
 
3.8%
5 23
 
2.3%
4 22
 
2.2%
Other values (6) 80
 
8.0%
Latin
ValueCountFrequency (%)
C 1
50.0%
E 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1541
60.5%
ASCII 1007
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
399
39.6%
1 105
 
10.4%
, 81
 
8.0%
( 76
 
7.5%
) 76
 
7.5%
2 59
 
5.9%
0 46
 
4.6%
3 38
 
3.8%
5 23
 
2.3%
4 22
 
2.2%
Other values (8) 82
 
8.1%
Hangul
ValueCountFrequency (%)
대 106
 
6.9%
해 100
 
6.5%
운 100
 
6.5%
동 97
 
6.3%
시 92
 
6.0%
구 81
 
5.3%
산 80
 
5.2%
부 77
 
5.0%
로 76
 
4.9%
역 76
 
4.9%
Other values (117) 656
42.6%

전화번호
Text

MISSING 

Distinct73
Distinct (%)98.6%
Missing2
Missing (%)2.6%
Memory size740.0 B
2023-12-11T02:06:49.774534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.891892
Min length1

Characters and Unicode

Total characters880
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)97.3%

Sample

1st row051-731-1536
2nd row051-746-1530
3rd row051-743-1001
4th row051-742-6151
5th row051-720-8401
ValueCountFrequency (%)
051-784-4042 2
 
2.7%
051-784-1095 1
 
1.4%
051-782-0539 1
 
1.4%
051-527-4040 1
 
1.4%
051-701-0440 1
 
1.4%
051-528-0770 1
 
1.4%
051-744-4884 1
 
1.4%
051-744-4144 1
 
1.4%
051-524-4042 1
 
1.4%
051-543-2888 1
 
1.4%
Other values (63) 63
85.1%
2023-12-11T02:06:50.473419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 149
16.9%
- 147
16.7%
5 119
13.5%
1 117
13.3%
7 89
10.1%
4 79
9.0%
2 49
 
5.6%
8 46
 
5.2%
3 45
 
5.1%
9 21
 
2.4%
Other values (2) 19
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 732
83.2%
Dash Punctuation 147
 
16.7%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 149
20.4%
5 119
16.3%
1 117
16.0%
7 89
12.2%
4 79
10.8%
2 49
 
6.7%
8 46
 
6.3%
3 45
 
6.1%
9 21
 
2.9%
6 18
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 880
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 149
16.9%
- 147
16.7%
5 119
13.5%
1 117
13.3%
7 89
10.1%
4 79
9.0%
2 49
 
5.6%
8 46
 
5.2%
3 45
 
5.1%
9 21
 
2.4%
Other values (2) 19
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 149
16.9%
- 147
16.7%
5 119
13.5%
1 117
13.3%
7 89
10.1%
4 79
9.0%
2 49
 
5.6%
8 46
 
5.2%
3 45
 
5.1%
9 21
 
2.4%
Other values (2) 19
 
2.2%

Interactions

2023-12-11T02:06:46.208683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:06:50.671747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업소명소재지(도로명)전화번호
순번1.0000.4281.0000.938
업소명0.4281.0001.0001.000
소재지(도로명)1.0001.0001.0001.000
전화번호0.9381.0001.0001.000

Missing values

2023-12-11T02:06:46.396125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:06:46.555094image/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

순번업소명소재지(도로명)전화번호
01으뜸50안경 해운대역점부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 226호 (우동)051-731-1536
12포레 안경원부산광역시 해운대구 좌동순환로 505, 센트럴메디타워 1101호 (중동)<NA>
23으뜸50안경 장산역점부산광역시 해운대구 해운대로 794, 엘리움 206호 (좌동)051-746-1530
34눈사랑안경 해운대점부산광역시 해운대구 구남로29번길 35, 1층 (중동)051-743-1001
45아이프레임부산광역시 해운대구 해운대로 723, 해운대타워마브러스 103동 113호 (중동)051-742-6151
56카멜레옹(chameleon)부산광역시 해운대구 마린시티2로 33, 104동 1층 113호 (우동, 해운대두산위브더제니스)<NA>
67지오엠(GOM)부산광역시 해운대구 센텀3로 20, 벡스코 비지니스호텔 2층 211-3호 (우동)051-720-8401
78마린키즈안경부산광역시 해운대구 마린시티2로 2, 마린파크 710호 (우동)051-747-4311
89알로뷰안경 센텀점부산광역시 해운대구 센텀4로 15, 지하2층 (우동, 센텀시티몰)051-745-2160
910시호비전 센텀부산광역시 해운대구 센텀동로 6, 2층 (우동, 홈플러스센템시티점)051-746-9916
순번업소명소재지(도로명)전화번호
6667굿모닝안경부산광역시 해운대구 우동2로 53 (우동, 굿모닝안경)051-741-4848
6768SM안경원부산광역시 해운대구 해운대로 409 (우동,,10 굿팀메디칼 1층)051-742-6323
6869산타클로스부산광역시 해운대구 좌동로 152 (좌동)051-704-2662
6970아이젠트리 마린시티점부산광역시 해운대구 마린시티2로 33, 104동 101,102호 (우동, 해운대두산위브더제니스)051-747-8833
7071아이비젼안경원부산광역시 해운대구 구남로29번길 16 (중동)051-731-3900
7172현대콘텍트안경부산광역시 해운대구 구남로29번길 38 (중동, 혜천빌딩)051-742-5910
7273현대안경부산광역시 해운대구 해운대로81번길 12 (재송동)051-781-4104
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