Overview

Dataset statistics

Number of variables5
Number of observations99
Missing cells44
Missing cells (%)8.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory42.3 B

Variable types

Numeric1
Text4

Dataset

Description부산광역시해운대구_옥외광고업현황_20210808
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3075793

Alerts

영업장전화번호 has 44 (44.4%) missing valuesMissing
순번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:33:13.644725
Analysis finished2023-12-10 16:33:14.507562
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-11T01:33:14.576763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.9
Q125.5
median50
Q374.5
95-th percentile94.1
Maximum99
Range98
Interquartile range (IQR)49

Descriptive statistics

Standard deviation28.722813
Coefficient of variation (CV)0.57445626
Kurtosis-1.2
Mean50
Median Absolute Deviation (MAD)25
Skewness0
Sum4950
Variance825
MonotonicityStrictly increasing
2023-12-11T01:33:14.717977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
64 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
Other values (89) 89
89.9%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%

업소명
Text

UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-11T01:33:15.003378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length6.1616162
Min length2

Characters and Unicode

Total characters610
Distinct characters164
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st row반석애드
2nd row동일애드산업
3rd row메가플러스
4th row오케이플래카드
5th rowTNS
ValueCountFrequency (%)
주식회사 10
 
8.5%
광고기획 2
 
1.7%
디자인 2
 
1.7%
애드클래스 1
 
0.9%
진성아크릴 1
 
0.9%
엔터테이먼트 1
 
0.9%
아미코 1
 
0.9%
공감 1
 
0.9%
디자인마인드플러스 1
 
0.9%
티지엠씨지점 1
 
0.9%
Other values (96) 96
82.1%
2023-12-11T01:33:15.404410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
4.6%
23
 
3.8%
21
 
3.4%
20
 
3.3%
20
 
3.3%
18
 
3.0%
18
 
3.0%
) 18
 
3.0%
( 18
 
3.0%
17
 
2.8%
Other values (154) 409
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 541
88.7%
Space Separator 18
 
3.0%
Close Punctuation 18
 
3.0%
Open Punctuation 18
 
3.0%
Uppercase Letter 15
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
28
 
5.2%
23
 
4.3%
21
 
3.9%
20
 
3.7%
20
 
3.7%
18
 
3.3%
17
 
3.1%
16
 
3.0%
16
 
3.0%
15
 
2.8%
Other values (140) 347
64.1%
Uppercase Letter
ValueCountFrequency (%)
N 3
20.0%
S 3
20.0%
C 1
 
6.7%
K 1
 
6.7%
E 1
 
6.7%
V 1
 
6.7%
A 1
 
6.7%
W 1
 
6.7%
T 1
 
6.7%
M 1
 
6.7%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 541
88.7%
Common 54
 
8.9%
Latin 15
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
28
 
5.2%
23
 
4.3%
21
 
3.9%
20
 
3.7%
20
 
3.7%
18
 
3.3%
17
 
3.1%
16
 
3.0%
16
 
3.0%
15
 
2.8%
Other values (140) 347
64.1%
Latin
ValueCountFrequency (%)
N 3
20.0%
S 3
20.0%
C 1
 
6.7%
K 1
 
6.7%
E 1
 
6.7%
V 1
 
6.7%
A 1
 
6.7%
W 1
 
6.7%
T 1
 
6.7%
M 1
 
6.7%
Common
ValueCountFrequency (%)
18
33.3%
) 18
33.3%
( 18
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 541
88.7%
ASCII 69
 
11.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
28
 
5.2%
23
 
4.3%
21
 
3.9%
20
 
3.7%
20
 
3.7%
18
 
3.3%
17
 
3.1%
16
 
3.0%
16
 
3.0%
15
 
2.8%
Other values (140) 347
64.1%
ASCII
ValueCountFrequency (%)
18
26.1%
) 18
26.1%
( 18
26.1%
N 3
 
4.3%
S 3
 
4.3%
C 1
 
1.4%
K 1
 
1.4%
E 1
 
1.4%
V 1
 
1.4%
A 1
 
1.4%
Other values (4) 4
 
5.8%

영업장전화번호
Text

MISSING 

Distinct55
Distinct (%)100.0%
Missing44
Missing (%)44.4%
Memory size924.0 B
2023-12-11T01:33:15.619512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.709091
Min length9

Characters and Unicode

Total characters754
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

Unique55 ?
Unique (%)100.0%

Sample

1st row051 -742 -1074
2nd row051 -782 -2770
3rd row051 -746 -0906
4th row051 -743 -5595
5th row051 -704 -4006
ValueCountFrequency (%)
051 48
31.8%
747 7
 
4.6%
746 4
 
2.6%
782 4
 
2.6%
744 3
 
2.0%
741 3
 
2.0%
704 3
 
2.0%
740 2
 
1.3%
742 2
 
1.3%
543 2
 
1.3%
Other values (71) 73
48.3%
2023-12-11T01:33:15.960764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 109
14.5%
97
12.9%
0 96
12.7%
5 93
12.3%
1 85
11.3%
7 77
10.2%
4 69
9.2%
2 32
 
4.2%
8 32
 
4.2%
6 25
 
3.3%
Other values (2) 39
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 548
72.7%
Dash Punctuation 109
 
14.5%
Space Separator 97
 
12.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 96
17.5%
5 93
17.0%
1 85
15.5%
7 77
14.1%
4 69
12.6%
2 32
 
5.8%
8 32
 
5.8%
6 25
 
4.6%
3 23
 
4.2%
9 16
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%
Space Separator
ValueCountFrequency (%)
97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 754
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 109
14.5%
97
12.9%
0 96
12.7%
5 93
12.3%
1 85
11.3%
7 77
10.2%
4 69
9.2%
2 32
 
4.2%
8 32
 
4.2%
6 25
 
3.3%
Other values (2) 39
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 754
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 109
14.5%
97
12.9%
0 96
12.7%
5 93
12.3%
1 85
11.3%
7 77
10.2%
4 69
9.2%
2 32
 
4.2%
8 32
 
4.2%
6 25
 
3.3%
Other values (2) 39
 
5.2%
Distinct94
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-11T01:33:16.224986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length34.212121
Min length23

Characters and Unicode

Total characters3387
Distinct characters157
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

Unique89 ?
Unique (%)89.9%

Sample

1st row부산광역시 해운대구 좌동순환로15번길 17-1 (좌동)
2nd row부산광역시 해운대구 해운대로76번길 41 (재송동)
3rd row부산광역시 해운대구 반송동 275번지 7호 2층
4th row부산광역시 해운대구 우동1로20번가길 38 (우동)
5th row부산광역시 해운대구 좌동로53번길 24 (중동)
ValueCountFrequency (%)
부산광역시 99
 
15.9%
해운대구 99
 
15.9%
우동 35
 
5.6%
재송동 22
 
3.5%
좌동 10
 
1.6%
apec로 9
 
1.4%
중동 9
 
1.4%
벡스코 8
 
1.3%
55 8
 
1.3%
센텀중앙로 8
 
1.3%
Other values (212) 317
50.8%
2023-12-11T01:33:16.650918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
535
 
15.8%
136
 
4.0%
120
 
3.5%
1 119
 
3.5%
114
 
3.4%
113
 
3.3%
108
 
3.2%
103
 
3.0%
103
 
3.0%
100
 
3.0%
Other values (147) 1836
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1998
59.0%
Space Separator 535
 
15.8%
Decimal Number 517
 
15.3%
Close Punctuation 95
 
2.8%
Open Punctuation 95
 
2.8%
Other Punctuation 78
 
2.3%
Uppercase Letter 50
 
1.5%
Dash Punctuation 18
 
0.5%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
136
 
6.8%
120
 
6.0%
114
 
5.7%
113
 
5.7%
108
 
5.4%
103
 
5.2%
103
 
5.2%
100
 
5.0%
99
 
5.0%
99
 
5.0%
Other values (123) 903
45.2%
Decimal Number
ValueCountFrequency (%)
1 119
23.0%
2 69
13.3%
0 69
13.3%
5 61
11.8%
6 45
 
8.7%
3 40
 
7.7%
7 40
 
7.7%
4 25
 
4.8%
9 25
 
4.8%
8 24
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
A 12
24.0%
C 10
20.0%
E 9
18.0%
P 9
18.0%
B 6
12.0%
T 2
 
4.0%
I 1
 
2.0%
S 1
 
2.0%
Space Separator
ValueCountFrequency (%)
535
100.0%
Close Punctuation
ValueCountFrequency (%)
) 95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%
Other Punctuation
ValueCountFrequency (%)
, 78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1998
59.0%
Common 1339
39.5%
Latin 50
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
136
 
6.8%
120
 
6.0%
114
 
5.7%
113
 
5.7%
108
 
5.4%
103
 
5.2%
103
 
5.2%
100
 
5.0%
99
 
5.0%
99
 
5.0%
Other values (123) 903
45.2%
Common
ValueCountFrequency (%)
535
40.0%
1 119
 
8.9%
) 95
 
7.1%
( 95
 
7.1%
, 78
 
5.8%
2 69
 
5.2%
0 69
 
5.2%
5 61
 
4.6%
6 45
 
3.4%
3 40
 
3.0%
Other values (6) 133
 
9.9%
Latin
ValueCountFrequency (%)
A 12
24.0%
C 10
20.0%
E 9
18.0%
P 9
18.0%
B 6
12.0%
T 2
 
4.0%
I 1
 
2.0%
S 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1998
59.0%
ASCII 1389
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
535
38.5%
1 119
 
8.6%
) 95
 
6.8%
( 95
 
6.8%
, 78
 
5.6%
2 69
 
5.0%
0 69
 
5.0%
5 61
 
4.4%
6 45
 
3.2%
3 40
 
2.9%
Other values (14) 183
 
13.2%
Hangul
ValueCountFrequency (%)
136
 
6.8%
120
 
6.0%
114
 
5.7%
113
 
5.7%
108
 
5.4%
103
 
5.2%
103
 
5.2%
100
 
5.0%
99
 
5.0%
99
 
5.0%
Other values (123) 903
45.2%
Distinct66
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-11T01:33:16.897916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length18
Mean length8.9191919
Min length4

Characters and Unicode

Total characters883
Distinct characters57
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

Unique56 ?
Unique (%)56.6%

Sample

1st row광고물제조업
2nd row광고물제조
3rd row광고기획, 광고물 제작
4th row현수막실사,간판제작
5th row옥외광고물등 제작
ValueCountFrequency (%)
제작 27
 
13.0%
간판제작등 18
 
8.7%
옥외광고물 17
 
8.2%
설치 15
 
7.2%
13
 
6.3%
간판제작 9
 
4.3%
광고물 8
 
3.9%
광고대행 7
 
3.4%
7
 
3.4%
시공 6
 
2.9%
Other values (50) 80
38.6%
2023-12-11T01:33:17.324990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
109
 
12.3%
77
 
8.7%
72
 
8.2%
72
 
8.2%
72
 
8.2%
37
 
4.2%
37
 
4.2%
36
 
4.1%
36
 
4.1%
36
 
4.1%
Other values (47) 299
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 736
83.4%
Space Separator 109
 
12.3%
Other Punctuation 34
 
3.9%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
77
 
10.5%
72
 
9.8%
72
 
9.8%
72
 
9.8%
37
 
5.0%
37
 
5.0%
36
 
4.9%
36
 
4.9%
36
 
4.9%
30
 
4.1%
Other values (43) 231
31.4%
Space Separator
ValueCountFrequency (%)
109
100.0%
Other Punctuation
ValueCountFrequency (%)
, 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 736
83.4%
Common 147
 
16.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
77
 
10.5%
72
 
9.8%
72
 
9.8%
72
 
9.8%
37
 
5.0%
37
 
5.0%
36
 
4.9%
36
 
4.9%
36
 
4.9%
30
 
4.1%
Other values (43) 231
31.4%
Common
ValueCountFrequency (%)
109
74.1%
, 34
 
23.1%
) 2
 
1.4%
( 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 736
83.4%
ASCII 147
 
16.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
109
74.1%
, 34
 
23.1%
) 2
 
1.4%
( 2
 
1.4%
Hangul
ValueCountFrequency (%)
77
 
10.5%
72
 
9.8%
72
 
9.8%
72
 
9.8%
37
 
5.0%
37
 
5.0%
36
 
4.9%
36
 
4.9%
36
 
4.9%
30
 
4.1%
Other values (43) 231
31.4%

Interactions

2023-12-11T01:33:14.279874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:33:17.440925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업소명영업장전화번호영업장도로명주소영업내용
순번1.0001.0001.0000.6690.763
업소명1.0001.0001.0001.0001.000
영업장전화번호1.0001.0001.0001.0001.000
영업장도로명주소0.6691.0001.0001.0000.955
영업내용0.7631.0001.0000.9551.000

Missing values

2023-12-11T01:33:14.382603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:33:14.473022image/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

순번업소명영업장전화번호영업장도로명주소영업내용
01반석애드051 -742 -1074부산광역시 해운대구 좌동순환로15번길 17-1 (좌동)광고물제조업
12동일애드산업051 -782 -2770부산광역시 해운대구 해운대로76번길 41 (재송동)광고물제조
23메가플러스<NA>부산광역시 해운대구 반송동 275번지 7호 2층광고기획, 광고물 제작
34오케이플래카드051 -746 -0906부산광역시 해운대구 우동1로20번가길 38 (우동)현수막실사,간판제작
45TNS051 -743 -5595부산광역시 해운대구 좌동로53번길 24 (중동)옥외광고물등 제작
56사인포유051 -704 -4006부산광역시 해운대구 좌동로 105, 3층 (좌동)광고물제작, 광고디자인, 실사출력
67(주) 두리컴051 -501 -5240부산광역시 해운대구 센텀중앙로 48, 15층 1513호 (우동, 에이스하이테크21)옥외광고물등제작
78화랑디자인051 -755 -4804부산광역시 해운대구 재반로 20-1 (재송동)광고제작
89마스타광고공사051 -782 -3435부산광역시 해운대구 재반로 46 (재송동)간판제작등
910여명기획<NA>부산광역시 해운대구 재송1로60번길 16, 상가동 1001,1002호 (재송동, 서해재송아파트)간판제작 및 각종기획
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8990SC디자인<NA>부산광역시 해운대구 재반로103번길 17 (재송동)옥외광고 제작, 설치
9091화랑광고시공<NA>부산광역시 해운대구 청사포로 12, 나동 1층 105호 (좌동, 에스케이뷰아파트)옥외광고업(제작 설치 및 옥외광고대행)
9192(주)부광기획<NA>부산광역시 해운대구 재반로 7-1 (재송동)간판제작, 시공, 디자인
9293비아디자인<NA>부산광역시 해운대구 선수촌로207번나길 20-9 (반여동)간판제작
9394해운대미스터종합광고<NA>부산광역시 해운대구 좌동로53번길 9 (중동)옥외광고
9495디자인 우리051 -746 -2142부산광역시 해운대구 좌동순환로249번길 7-20, 2층 (좌동, )간판제작업
9596프로인커뮤니케이션<NA>부산광역시 해운대구 센텀동로 71, 307호 (우동, 벽산이센텀클래스원2차)간판제작, 대행, 광고기획
9697우주간판051 -781 -2444부산광역시 해운대구 재반로 96-2 (재송동)간판제작
9798세명기획051-784 -6088부산광역시 해운대구 재송동 1052번지 5호옥외광고물 제작
9899서울마크광고사051 -744 -1047부산광역시 해운대구 우동 140번지 17 호간판제작등