Overview

Dataset statistics

Number of variables3
Number of observations60
Missing cells10
Missing cells (%)5.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory26.2 B

Variable types

Text3

Dataset

Description부산광역시 연제구 치과기공소 현황입니다.(2023.9.18.기준)명칭, 소재지(도로명주소), 우편번호를 제공합니다.
Author부산광역시 연제구
URLhttps://www.data.go.kr/data/15048092/fileData.do

Alerts

우편번호(도로명) has 10 (16.7%) missing valuesMissing
치과기공소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:32:04.427929
Analysis finished2023-12-12 07:32:04.818989
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

치과기공소명
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T16:32:05.007010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length8.65
Min length2

Characters and Unicode

Total characters519
Distinct characters124
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

Unique60 ?
Unique (%)100.0%

Sample

1st row워너비 디지털 덴탈랩(Wannabe digital dental lab)
2nd row디지털
3rd row플랜에이(Plan-A)치과기공소
4th row에스와이치과기공소
5th row덴탈글로벌
ValueCountFrequency (%)
치과기공소 4
 
5.1%
dental 3
 
3.8%
lab 3
 
3.8%
디지털 2
 
2.6%
digital 2
 
2.6%
one 2
 
2.6%
워너비 1
 
1.3%
zir 1
 
1.3%
b&j 1
 
1.3%
열린치과기공소 1
 
1.3%
Other values (58) 58
74.4%
2023-12-12T16:32:05.438164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
53
 
10.2%
52
 
10.0%
52
 
10.0%
47
 
9.1%
47
 
9.1%
18
 
3.5%
8
 
1.5%
8
 
1.5%
a 8
 
1.5%
7
 
1.3%
Other values (114) 219
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 402
77.5%
Lowercase Letter 42
 
8.1%
Uppercase Letter 42
 
8.1%
Space Separator 18
 
3.5%
Open Punctuation 5
 
1.0%
Close Punctuation 5
 
1.0%
Other Punctuation 3
 
0.6%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
53
13.2%
52
12.9%
52
12.9%
47
11.7%
47
11.7%
8
 
2.0%
8
 
2.0%
7
 
1.7%
6
 
1.5%
5
 
1.2%
Other values (80) 117
29.1%
Uppercase Letter
ValueCountFrequency (%)
A 5
11.9%
O 4
9.5%
N 4
9.5%
L 4
9.5%
E 4
9.5%
B 3
7.1%
D 3
7.1%
T 3
7.1%
C 3
7.1%
J 2
 
4.8%
Other values (6) 7
16.7%
Lowercase Letter
ValueCountFrequency (%)
a 8
19.0%
l 6
14.3%
i 5
11.9%
n 5
11.9%
e 4
9.5%
t 3
 
7.1%
d 3
 
7.1%
b 3
 
7.1%
g 2
 
4.8%
r 1
 
2.4%
Other values (2) 2
 
4.8%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 402
77.5%
Latin 84
 
16.2%
Common 33
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
53
13.2%
52
12.9%
52
12.9%
47
11.7%
47
11.7%
8
 
2.0%
8
 
2.0%
7
 
1.7%
6
 
1.5%
5
 
1.2%
Other values (80) 117
29.1%
Latin
ValueCountFrequency (%)
a 8
 
9.5%
l 6
 
7.1%
A 5
 
6.0%
i 5
 
6.0%
n 5
 
6.0%
O 4
 
4.8%
N 4
 
4.8%
e 4
 
4.8%
L 4
 
4.8%
E 4
 
4.8%
Other values (18) 35
41.7%
Common
ValueCountFrequency (%)
18
54.5%
( 5
 
15.2%
) 5
 
15.2%
& 2
 
6.1%
- 2
 
6.1%
. 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 402
77.5%
ASCII 117
 
22.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
53
13.2%
52
12.9%
52
12.9%
47
11.7%
47
11.7%
8
 
2.0%
8
 
2.0%
7
 
1.7%
6
 
1.5%
5
 
1.2%
Other values (80) 117
29.1%
ASCII
ValueCountFrequency (%)
18
 
15.4%
a 8
 
6.8%
l 6
 
5.1%
( 5
 
4.3%
A 5
 
4.3%
i 5
 
4.3%
) 5
 
4.3%
n 5
 
4.3%
O 4
 
3.4%
N 4
 
3.4%
Other values (24) 52
44.4%
Distinct56
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T16:32:05.764552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length28.833333
Min length21

Characters and Unicode

Total characters1730
Distinct characters76
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)86.7%

Sample

1st row부산광역시 연제구 과정로 203, 3층 (연산동)
2nd row부산광역시 연제구 거제대로118번길 27, 2층 (거제동)
3rd row부산광역시 연제구 연수로 205-1, 2층 (연산동)
4th row부산광역시 연제구 마곡천로 30, 2층 (연산동)
5th row부산광역시 연제구 좌수영로 299, 동성빌딩 4층 (연산동)
ValueCountFrequency (%)
부산광역시 60
17.4%
연제구 60
17.4%
연산동 37
 
10.8%
거제동 16
 
4.7%
2층 12
 
3.5%
3층 10
 
2.9%
연수로 8
 
2.3%
5층 5
 
1.5%
마곡천로 5
 
1.5%
5 4
 
1.2%
Other values (90) 127
36.9%
2023-12-12T16:32:06.229933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
284
 
16.4%
113
 
6.5%
101
 
5.8%
93
 
5.4%
1 68
 
3.9%
64
 
3.7%
62
 
3.6%
) 62
 
3.6%
( 62
 
3.6%
61
 
3.5%
Other values (66) 760
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1004
58.0%
Space Separator 284
 
16.4%
Decimal Number 264
 
15.3%
Close Punctuation 62
 
3.6%
Open Punctuation 62
 
3.6%
Other Punctuation 40
 
2.3%
Dash Punctuation 14
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
113
11.3%
101
 
10.1%
93
 
9.3%
64
 
6.4%
62
 
6.2%
61
 
6.1%
60
 
6.0%
60
 
6.0%
60
 
6.0%
60
 
6.0%
Other values (51) 270
26.9%
Decimal Number
ValueCountFrequency (%)
1 68
25.8%
2 52
19.7%
3 37
14.0%
5 26
 
9.8%
4 26
 
9.8%
0 19
 
7.2%
8 11
 
4.2%
9 10
 
3.8%
7 9
 
3.4%
6 6
 
2.3%
Space Separator
ValueCountFrequency (%)
284
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Other Punctuation
ValueCountFrequency (%)
, 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1004
58.0%
Common 726
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
113
11.3%
101
 
10.1%
93
 
9.3%
64
 
6.4%
62
 
6.2%
61
 
6.1%
60
 
6.0%
60
 
6.0%
60
 
6.0%
60
 
6.0%
Other values (51) 270
26.9%
Common
ValueCountFrequency (%)
284
39.1%
1 68
 
9.4%
) 62
 
8.5%
( 62
 
8.5%
2 52
 
7.2%
, 40
 
5.5%
3 37
 
5.1%
5 26
 
3.6%
4 26
 
3.6%
0 19
 
2.6%
Other values (5) 50
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1004
58.0%
ASCII 726
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
284
39.1%
1 68
 
9.4%
) 62
 
8.5%
( 62
 
8.5%
2 52
 
7.2%
, 40
 
5.5%
3 37
 
5.1%
5 26
 
3.6%
4 26
 
3.6%
0 19
 
2.6%
Other values (5) 50
 
6.9%
Hangul
ValueCountFrequency (%)
113
11.3%
101
 
10.1%
93
 
9.3%
64
 
6.4%
62
 
6.2%
61
 
6.1%
60
 
6.0%
60
 
6.0%
60
 
6.0%
60
 
6.0%
Other values (51) 270
26.9%
Distinct31
Distinct (%)62.0%
Missing10
Missing (%)16.7%
Memory size612.0 B
2023-12-12T16:32:06.396232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters300
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

Unique19 ?
Unique (%)38.0%

Sample

1st row'47558
2nd row'47547
3rd row'47594
4th row'47610
5th row'47569
ValueCountFrequency (%)
47610 5
 
10.0%
47537 4
 
8.0%
47547 3
 
6.0%
47564 3
 
6.0%
47541 2
 
4.0%
47550 2
 
4.0%
47543 2
 
4.0%
47505 2
 
4.0%
47614 2
 
4.0%
47603 2
 
4.0%
Other values (21) 23
46.0%
2023-12-12T16:32:06.677532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 68
22.7%
7 60
20.0%
' 50
16.7%
5 46
15.3%
6 20
 
6.7%
0 16
 
5.3%
1 14
 
4.7%
3 12
 
4.0%
9 7
 
2.3%
8 5
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 250
83.3%
Other Punctuation 50
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 68
27.2%
7 60
24.0%
5 46
18.4%
6 20
 
8.0%
0 16
 
6.4%
1 14
 
5.6%
3 12
 
4.8%
9 7
 
2.8%
8 5
 
2.0%
2 2
 
0.8%
Other Punctuation
ValueCountFrequency (%)
' 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 68
22.7%
7 60
20.0%
' 50
16.7%
5 46
15.3%
6 20
 
6.7%
0 16
 
5.3%
1 14
 
4.7%
3 12
 
4.0%
9 7
 
2.3%
8 5
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 68
22.7%
7 60
20.0%
' 50
16.7%
5 46
15.3%
6 20
 
6.7%
0 16
 
5.3%
1 14
 
4.7%
3 12
 
4.0%
9 7
 
2.3%
8 5
 
1.7%

Correlations

2023-12-12T16:32:06.756962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
치과기공소명소재지(도로명)우편번호(도로명)
치과기공소명1.0001.0001.000
소재지(도로명)1.0001.0001.000
우편번호(도로명)1.0001.0001.000

Missing values

2023-12-12T16:32:04.679354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:32:04.781770image/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

치과기공소명소재지(도로명)우편번호(도로명)
0워너비 디지털 덴탈랩(Wannabe digital dental lab)부산광역시 연제구 과정로 203, 3층 (연산동)'47558
1디지털부산광역시 연제구 거제대로118번길 27, 2층 (거제동)'47547
2플랜에이(Plan-A)치과기공소부산광역시 연제구 연수로 205-1, 2층 (연산동)'47594
3에스와이치과기공소부산광역시 연제구 마곡천로 30, 2층 (연산동)'47610
4덴탈글로벌부산광역시 연제구 좌수영로 299, 동성빌딩 4층 (연산동)'47569
5예잔치과기공소부산광역시 연제구 연수로 205-1, 2층 (연산동)'47594
6양지치과기공소부산광역시 연제구 마곡천로 30, 2층 일부호 (연산동)'47610
7비전치과기공소부산광역시 연제구 연수로 202-1, 3층 (연산동)'47614
8The ONE Digital lab(더원디지털치과기공소)부산광역시 연제구 거제대로214번길 33, 원빌딩 1층 (거제동)'47537
9윤디지털치과기공소부산광역시 연제구 고분로 122, 4층 (연산동)'47583
치과기공소명소재지(도로명)우편번호(도로명)
50지르코쟌기공소부산광역시 연제구 반송로 11 (연산동,4층)<NA>
51조은치과기공소부산광역시 연제구 연수로 102 (연산동)'47608
52유진치과기공소부산광역시 연제구 과정로 333 (연산동)<NA>
53예원치과기공소부산광역시 연제구 여고로 132-1 (거제동)'47504
54영신부산광역시 연제구 중앙대로1134번길 11 (연산동,2층)<NA>
55남영 치과기공소부산광역시 연제구 월드컵대로111번길 6-9, 3층 (연산동)'47596
56삼인치과기공소부산광역시 연제구 거제천로 185-2 (거제동)<NA>
57명성치과기공소부산광역시 연제구 월드컵대로 5 (연산동)<NA>
58다원치과기공소부산광역시 연제구 거제시장로 21 (거제동)<NA>
59대하치과기공소부산광역시 연제구 연수로 127 (연산동)'47603