Overview

Dataset statistics

Number of variables3
Number of observations35
Missing cells18
Missing cells (%)17.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory972.0 B
Average record size in memory27.8 B

Variable types

Text3

Dataset

Description부산광역시남구_치과기공소현황_20220621
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15051587

Alerts

전화번호 has 18 (51.4%) missing valuesMissing
치과기공소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:37:50.370541
Analysis finished2023-12-10 16:37:50.687074
Duration0.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

치과기공소명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-11T01:37:50.831514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length7.6571429
Min length4

Characters and Unicode

Total characters268
Distinct characters86
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row토마토기공소
2nd row이지디지털치과기공소
3rd row에이티기공소
4th row예담치과기공소
5th row하나치과기공소
ValueCountFrequency (%)
치과기공소 4
 
9.3%
토마토기공소 1
 
2.3%
정치과기공소 1
 
2.3%
선한치과기공소 1
 
2.3%
허브치과기공소 1
 
2.3%
하이치과기공소 1
 
2.3%
새로운치과기공소 1
 
2.3%
엘림치과기공소 1
 
2.3%
하이얀치과기공소 1
 
2.3%
은혜치과기공소 1
 
2.3%
Other values (30) 30
69.8%
2023-12-11T01:37:51.318700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 30
 
11.2%
공 30
 
11.2%
소 30
 
11.2%
치 28
 
10.4%
과 28
 
10.4%
8
 
3.0%
이 6
 
2.2%
덴 5
 
1.9%
랩 5
 
1.9%
탈 5
 
1.9%
Other values (76) 93
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 234
87.3%
Lowercase Letter 18
 
6.7%
Space Separator 8
 
3.0%
Uppercase Letter 6
 
2.2%
Decimal Number 1
 
0.4%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 30
12.8%
공 30
12.8%
소 30
12.8%
치 28
12.0%
과 28
12.0%
이 6
 
2.6%
덴 5
 
2.1%
랩 5
 
2.1%
탈 5
 
2.1%
하 3
 
1.3%
Other values (56) 64
27.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
22.2%
l 3
16.7%
i 2
11.1%
n 2
11.1%
m 1
 
5.6%
g 1
 
5.6%
c 1
 
5.6%
t 1
 
5.6%
r 1
 
5.6%
s 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
M 1
16.7%
W 1
16.7%
P 1
16.7%
C 1
16.7%
Y 1
16.7%
B 1
16.7%
Space Separator
ValueCountFrequency (%)
8
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 234
87.3%
Latin 24
 
9.0%
Common 10
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 30
12.8%
공 30
12.8%
소 30
12.8%
치 28
12.0%
과 28
12.0%
이 6
 
2.6%
덴 5
 
2.1%
랩 5
 
2.1%
탈 5
 
2.1%
하 3
 
1.3%
Other values (56) 64
27.4%
Latin
ValueCountFrequency (%)
e 4
16.7%
l 3
12.5%
i 2
 
8.3%
n 2
 
8.3%
M 1
 
4.2%
m 1
 
4.2%
g 1
 
4.2%
c 1
 
4.2%
t 1
 
4.2%
r 1
 
4.2%
Other values (7) 7
29.2%
Common
ValueCountFrequency (%)
8
80.0%
1 1
 
10.0%
& 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 234
87.3%
ASCII 34
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 30
12.8%
공 30
12.8%
소 30
12.8%
치 28
12.0%
과 28
12.0%
이 6
 
2.6%
덴 5
 
2.1%
랩 5
 
2.1%
탈 5
 
2.1%
하 3
 
1.3%
Other values (56) 64
27.4%
ASCII
ValueCountFrequency (%)
8
23.5%
e 4
 
11.8%
l 3
 
8.8%
i 2
 
5.9%
n 2
 
5.9%
M 1
 
2.9%
1 1
 
2.9%
m 1
 
2.9%
g 1
 
2.9%
c 1
 
2.9%
Other values (10) 10
29.4%

소재지(도로명)
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-11T01:37:51.711929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length26.914286
Min length21

Characters and Unicode

Total characters942
Distinct characters71
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

Unique35 ?
Unique (%)100.0%

Sample

1st row부산광역시 남구 지게골로 17-7, 금호빌딩 2층 201호 (문현동)
2nd row부산광역시 남구 장고개로93번길 34, 1층 (문현동)
3rd row부산광역시 남구 용소로 7, 청라빌딩 5층 (대연동)
4th row부산광역시 남구 고동골로59번길 49, 2층 (문현동)
5th row부산광역시 남구 전포대로40번길 19, 3층 (문현동)
ValueCountFrequency (%)
부산광역시 35
17.2%
남구 35
17.2%
문현동 16
 
7.8%
대연동 14
 
6.9%
2층 9
 
4.4%
3층 7
 
3.4%
못골로 5
 
2.5%
수영로 5
 
2.5%
금호빌딩 3
 
1.5%
8 3
 
1.5%
Other values (57) 72
35.3%
2023-12-11T01:37:52.201423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
169
 
17.9%
동 39
 
4.1%
남 38
 
4.0%
( 36
 
3.8%
) 36
 
3.8%
부 35
 
3.7%
광 35
 
3.7%
역 35
 
3.7%
시 35
 
3.7%
구 35
 
3.7%
Other values (61) 449
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 539
57.2%
Space Separator 169
 
17.9%
Decimal Number 128
 
13.6%
Open Punctuation 36
 
3.8%
Close Punctuation 36
 
3.8%
Other Punctuation 25
 
2.7%
Dash Punctuation 9
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 39
 
7.2%
남 38
 
7.1%
부 35
 
6.5%
광 35
 
6.5%
역 35
 
6.5%
시 35
 
6.5%
구 35
 
6.5%
산 35
 
6.5%
로 35
 
6.5%
층 21
 
3.9%
Other values (46) 196
36.4%
Decimal Number
ValueCountFrequency (%)
2 22
17.2%
1 20
15.6%
3 15
11.7%
9 13
10.2%
7 13
10.2%
4 13
10.2%
6 10
7.8%
8 8
 
6.2%
5 7
 
5.5%
0 7
 
5.5%
Space Separator
ValueCountFrequency (%)
169
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 539
57.2%
Common 403
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 39
 
7.2%
남 38
 
7.1%
부 35
 
6.5%
광 35
 
6.5%
역 35
 
6.5%
시 35
 
6.5%
구 35
 
6.5%
산 35
 
6.5%
로 35
 
6.5%
층 21
 
3.9%
Other values (46) 196
36.4%
Common
ValueCountFrequency (%)
169
41.9%
( 36
 
8.9%
) 36
 
8.9%
, 25
 
6.2%
2 22
 
5.5%
1 20
 
5.0%
3 15
 
3.7%
9 13
 
3.2%
7 13
 
3.2%
4 13
 
3.2%
Other values (5) 41
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 539
57.2%
ASCII 403
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
169
41.9%
( 36
 
8.9%
) 36
 
8.9%
, 25
 
6.2%
2 22
 
5.5%
1 20
 
5.0%
3 15
 
3.7%
9 13
 
3.2%
7 13
 
3.2%
4 13
 
3.2%
Other values (5) 41
 
10.2%
Hangul
ValueCountFrequency (%)
동 39
 
7.2%
남 38
 
7.1%
부 35
 
6.5%
광 35
 
6.5%
역 35
 
6.5%
시 35
 
6.5%
구 35
 
6.5%
산 35
 
6.5%
로 35
 
6.5%
층 21
 
3.9%
Other values (46) 196
36.4%

전화번호
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing18
Missing (%)51.4%
Memory size412.0 B
2023-12-11T01:37:52.407218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters204
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

Unique17 ?
Unique (%)100.0%

Sample

1st row051-919-9160
2nd row051-636-2804
3rd row051-506-2801
4th row051-627-6680
5th row051-631-2887
ValueCountFrequency (%)
051-919-9160 1
 
5.9%
051-635-8226 1
 
5.9%
051-626-9639 1
 
5.9%
051-851-5275 1
 
5.9%
051-621-6207 1
 
5.9%
051-632-8688 1
 
5.9%
051-633-2832 1
 
5.9%
051-627-2871 1
 
5.9%
051-638-2326 1
 
5.9%
051-636-2804 1
 
5.9%
Other values (7) 7
41.2%
2023-12-11T01:37:52.737530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 34
16.7%
1 28
13.7%
6 25
12.3%
0 24
11.8%
2 23
11.3%
5 22
10.8%
8 16
7.8%
3 12
 
5.9%
9 9
 
4.4%
7 8
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 170
83.3%
Dash Punctuation 34
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 28
16.5%
6 25
14.7%
0 24
14.1%
2 23
13.5%
5 22
12.9%
8 16
9.4%
3 12
7.1%
9 9
 
5.3%
7 8
 
4.7%
4 3
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 204
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 34
16.7%
1 28
13.7%
6 25
12.3%
0 24
11.8%
2 23
11.3%
5 22
10.8%
8 16
7.8%
3 12
 
5.9%
9 9
 
4.4%
7 8
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 34
16.7%
1 28
13.7%
6 25
12.3%
0 24
11.8%
2 23
11.3%
5 22
10.8%
8 16
7.8%
3 12
 
5.9%
9 9
 
4.4%
7 8
 
3.9%

Correlations

2023-12-11T01:37:52.830705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
치과기공소명소재지(도로명)전화번호
치과기공소명1.0001.0001.000
소재지(도로명)1.0001.0001.000
전화번호1.0001.0001.000

Missing values

2023-12-11T01:37:50.561502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:37:50.656442image/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)전화번호
0토마토기공소부산광역시 남구 지게골로 17-7, 금호빌딩 2층 201호 (문현동)<NA>
1이지디지털치과기공소부산광역시 남구 장고개로93번길 34, 1층 (문현동)<NA>
2에이티기공소부산광역시 남구 용소로 7, 청라빌딩 5층 (대연동)<NA>
3예담치과기공소부산광역시 남구 고동골로59번길 49, 2층 (문현동)<NA>
4하나치과기공소부산광역시 남구 전포대로40번길 19, 3층 (문현동)<NA>
5W덴탈랩부산광역시 남구 수영로196번길 103, 2층 (대연동)<NA>
6진치과기공소부산광역시 남구 남동천로 4, 일진정밀 2층 (문현동)<NA>
7라온덴탈랩부산광역시 남구 못골로 49-8, 2층 (대연동)<NA>
8Blue 치과기공소부산광역시 남구 고동골로 8, 3층 (문현동)051-919-9160
9올빚치과기공소부산광역시 남구 지게골로 17-7, 금호빌딩 4층 (문현동)051-636-2804
치과기공소명소재지(도로명)전화번호
25은혜치과기공소부산광역시 남구 우암로 63 (감만동)051-638-2326
26혼치과기공소부산광역시 남구 진남로 202-1, 4층 (문현동)<NA>
27선한치과기공소부산광역시 남구 수영로 195-8 (대연동)051-635-8226
28신흥세라믹치과기공소부산광역시 남구 유엔평화로9번길 8 (대연동)051-627-2871
29동광치과기공소부산광역시 남구 전포대로 74 (문현동)051-633-2832
30청조치과기공소부산광역시 남구 못골로 76, 2층 (대연동)051-632-8688
31메이존치과기공소부산광역시 남구 수영로 256 (대연동)051-621-6207
32팔팔덴탈랩 치과기공소부산광역시 남구 전포대로 88-4, 2층 (문현동)051-851-5275
33한마음치과기공소부산광역시 남구 못골로 77-1 (대연동)051-626-9639
34대동치과기공소부산광역시 남구 용소로28번길 16 (대연동)051-627-9922