Overview

Dataset statistics

Number of variables4
Number of observations90
Missing cells49
Missing cells (%)13.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory33.5 B

Variable types

Categorical1
Text3

Dataset

Description인천광역시 부평구 동물 미용업체 현황 데이터입니다.(종류,사업장명칭,소재지주소(도로명),소재지전화)ex) 미용,릴리네 애견미용실,인천광역시 부평구 경인로1118번길 38-14, 1층 (일신동),
Author인천광역시 부평구
URLhttps://www.data.go.kr/data/15089244/fileData.do

Alerts

종류 has constant value ""Constant
소재지전화 has 49 (54.4%) missing valuesMissing
사업장명칭 has unique valuesUnique
소재지주소(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:54:28.073278
Analysis finished2023-12-12 04:54:28.675465
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
미용
90 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미용
2nd row미용
3rd row미용
4th row미용
5th row미용

Common Values

ValueCountFrequency (%)
미용 90
100.0%

Length

2023-12-12T13:54:28.754016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:28.892347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미용 90
100.0%

사업장명칭
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-12T13:54:29.207523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length6.3888889
Min length2

Characters and Unicode

Total characters575
Distinct characters184
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

Unique90 ?
Unique (%)100.0%

Sample

1st row릴리네 애견미용실
2nd row현대동물병원 애견용품
3rd row아콩하우스
4th row까까몽 애견미용실
5th row하이슈슈
ValueCountFrequency (%)
동물병원 7
 
4.8%
펫 3
 
2.0%
그루밍 2
 
1.4%
더 2
 
1.4%
댕댕이 2
 
1.4%
귀엽개 2
 
1.4%
pet 2
 
1.4%
고양이 2
 
1.4%
미용실 2
 
1.4%
강아지 2
 
1.4%
Other values (120) 121
82.3%
2023-12-12T13:54:29.785038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
57
 
9.9%
이 20
 
3.5%
동 17
 
3.0%
물 16
 
2.8%
원 15
 
2.6%
병 15
 
2.6%
개 12
 
2.1%
펫 12
 
2.1%
댕 11
 
1.9%
아 10
 
1.7%
Other values (174) 390
67.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
82.6%
Space Separator 57
 
9.9%
Lowercase Letter 21
 
3.7%
Uppercase Letter 11
 
1.9%
Open Punctuation 4
 
0.7%
Close Punctuation 4
 
0.7%
Other Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 20
 
4.2%
동 17
 
3.6%
물 16
 
3.4%
원 15
 
3.2%
병 15
 
3.2%
개 12
 
2.5%
펫 12
 
2.5%
댕 11
 
2.3%
아 10
 
2.1%
미 10
 
2.1%
Other values (149) 337
70.9%
Lowercase Letter
ValueCountFrequency (%)
o 4
19.0%
m 3
14.3%
e 3
14.3%
g 2
9.5%
t 2
9.5%
p 2
9.5%
d 1
 
4.8%
s 1
 
4.8%
a 1
 
4.8%
l 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
D 2
18.2%
G 2
18.2%
A 1
9.1%
O 1
9.1%
E 1
9.1%
L 1
9.1%
Y 1
9.1%
T 1
9.1%
S 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
' 1
33.3%
Space Separator
ValueCountFrequency (%)
57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 475
82.6%
Common 68
 
11.8%
Latin 32
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 20
 
4.2%
동 17
 
3.6%
물 16
 
3.4%
원 15
 
3.2%
병 15
 
3.2%
개 12
 
2.5%
펫 12
 
2.5%
댕 11
 
2.3%
아 10
 
2.1%
미 10
 
2.1%
Other values (149) 337
70.9%
Latin
ValueCountFrequency (%)
o 4
 
12.5%
m 3
 
9.4%
e 3
 
9.4%
g 2
 
6.2%
D 2
 
6.2%
t 2
 
6.2%
p 2
 
6.2%
G 2
 
6.2%
d 1
 
3.1%
A 1
 
3.1%
Other values (10) 10
31.2%
Common
ValueCountFrequency (%)
57
83.8%
( 4
 
5.9%
) 4
 
5.9%
, 2
 
2.9%
' 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
82.6%
ASCII 100
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57
57.0%
( 4
 
4.0%
o 4
 
4.0%
) 4
 
4.0%
m 3
 
3.0%
e 3
 
3.0%
g 2
 
2.0%
D 2
 
2.0%
, 2
 
2.0%
t 2
 
2.0%
Other values (15) 17
 
17.0%
Hangul
ValueCountFrequency (%)
이 20
 
4.2%
동 17
 
3.6%
물 16
 
3.4%
원 15
 
3.2%
병 15
 
3.2%
개 12
 
2.5%
펫 12
 
2.5%
댕 11
 
2.3%
아 10
 
2.1%
미 10
 
2.1%
Other values (149) 337
70.9%

소재지주소(도로명)
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-12T13:54:30.157304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39.5
Mean length32.411111
Min length22

Characters and Unicode

Total characters2917
Distinct characters162
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

Unique90 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 경인로1118번길 38-14, 1층 (일신동)
2nd row인천광역시 부평구 경원대로 1286, 부평메디아나센터 1층 (부평동)
3rd row인천광역시 부평구 부평문화로 45, 201호 (부평동)
4th row인천광역시 부평구 부개로 61-6, 신성프라자 107호 (부개동)
5th row인천광역시 부평구 원적로471번길 3 (부평동)
ValueCountFrequency (%)
인천광역시 90
 
15.5%
부평구 90
 
15.5%
부평동 30
 
5.2%
1층 27
 
4.6%
부개동 14
 
2.4%
2층 11
 
1.9%
갈산동 10
 
1.7%
삼산동 10
 
1.7%
십정동 9
 
1.5%
101호 8
 
1.4%
Other values (205) 282
48.5%
2023-12-12T13:54:30.704011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
492
 
16.9%
부 163
 
5.6%
1 147
 
5.0%
평 137
 
4.7%
동 101
 
3.5%
천 99
 
3.4%
인 95
 
3.3%
시 93
 
3.2%
로 91
 
3.1%
광 91
 
3.1%
Other values (152) 1408
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1671
57.3%
Space Separator 492
 
16.9%
Decimal Number 464
 
15.9%
Open Punctuation 90
 
3.1%
Close Punctuation 90
 
3.1%
Other Punctuation 82
 
2.8%
Dash Punctuation 15
 
0.5%
Uppercase Letter 11
 
0.4%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 163
 
9.8%
평 137
 
8.2%
동 101
 
6.0%
천 99
 
5.9%
인 95
 
5.7%
시 93
 
5.6%
로 91
 
5.4%
광 91
 
5.4%
구 90
 
5.4%
역 90
 
5.4%
Other values (125) 621
37.2%
Decimal Number
ValueCountFrequency (%)
1 147
31.7%
2 57
 
12.3%
0 49
 
10.6%
3 47
 
10.1%
4 46
 
9.9%
5 33
 
7.1%
6 30
 
6.5%
8 24
 
5.2%
7 19
 
4.1%
9 12
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
A 2
18.2%
R 1
9.1%
K 1
9.1%
U 1
9.1%
F 1
9.1%
P 1
9.1%
I 1
9.1%
M 1
9.1%
T 1
9.1%
S 1
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
h 1
50.0%
Space Separator
ValueCountFrequency (%)
492
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Other Punctuation
ValueCountFrequency (%)
, 82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1671
57.3%
Common 1233
42.3%
Latin 13
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 163
 
9.8%
평 137
 
8.2%
동 101
 
6.0%
천 99
 
5.9%
인 95
 
5.7%
시 93
 
5.6%
로 91
 
5.4%
광 91
 
5.4%
구 90
 
5.4%
역 90
 
5.4%
Other values (125) 621
37.2%
Common
ValueCountFrequency (%)
492
39.9%
1 147
 
11.9%
( 90
 
7.3%
) 90
 
7.3%
, 82
 
6.7%
2 57
 
4.6%
0 49
 
4.0%
3 47
 
3.8%
4 46
 
3.7%
5 33
 
2.7%
Other values (5) 100
 
8.1%
Latin
ValueCountFrequency (%)
A 2
15.4%
R 1
7.7%
K 1
7.7%
U 1
7.7%
F 1
7.7%
P 1
7.7%
I 1
7.7%
M 1
7.7%
e 1
7.7%
h 1
7.7%
Other values (2) 2
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1671
57.3%
ASCII 1246
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
492
39.5%
1 147
 
11.8%
( 90
 
7.2%
) 90
 
7.2%
, 82
 
6.6%
2 57
 
4.6%
0 49
 
3.9%
3 47
 
3.8%
4 46
 
3.7%
5 33
 
2.6%
Other values (17) 113
 
9.1%
Hangul
ValueCountFrequency (%)
부 163
 
9.8%
평 137
 
8.2%
동 101
 
6.0%
천 99
 
5.9%
인 95
 
5.7%
시 93
 
5.6%
로 91
 
5.4%
광 91
 
5.4%
구 90
 
5.4%
역 90
 
5.4%
Other values (125) 621
37.2%

소재지전화
Text

MISSING 

Distinct41
Distinct (%)100.0%
Missing49
Missing (%)54.4%
Memory size852.0 B
2023-12-12T13:54:31.009162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.04878
Min length12

Characters and Unicode

Total characters494
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

Unique41 ?
Unique (%)100.0%

Sample

1st row032-521-6578
2nd row032-505-7900
3rd row032-524-6959
4th row032-228-0202
5th row032-512-7007
ValueCountFrequency (%)
032-517-7517 1
 
2.4%
070-7808-9303 1
 
2.4%
032-631-3311 1
 
2.4%
032-511-2610 1
 
2.4%
032-678-3945 1
 
2.4%
032-521-0003 1
 
2.4%
032-516-2655 1
 
2.4%
032-515-1321 1
 
2.4%
032-503-2211 1
 
2.4%
032-710-6402 1
 
2.4%
Other values (31) 31
75.6%
2023-12-12T13:54:31.346870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 83
16.8%
- 82
16.6%
2 74
15.0%
3 63
12.8%
5 59
11.9%
1 36
7.3%
7 31
 
6.3%
8 25
 
5.1%
4 14
 
2.8%
9 14
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 412
83.4%
Dash Punctuation 82
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 83
20.1%
2 74
18.0%
3 63
15.3%
5 59
14.3%
1 36
8.7%
7 31
 
7.5%
8 25
 
6.1%
4 14
 
3.4%
9 14
 
3.4%
6 13
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 494
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 83
16.8%
- 82
16.6%
2 74
15.0%
3 63
12.8%
5 59
11.9%
1 36
7.3%
7 31
 
6.3%
8 25
 
5.1%
4 14
 
2.8%
9 14
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 83
16.8%
- 82
16.6%
2 74
15.0%
3 63
12.8%
5 59
11.9%
1 36
7.3%
7 31
 
6.3%
8 25
 
5.1%
4 14
 
2.8%
9 14
 
2.8%

Correlations

2023-12-12T13:54:31.459465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명칭소재지주소(도로명)소재지전화
사업장명칭1.0001.0001.000
소재지주소(도로명)1.0001.0001.000
소재지전화1.0001.0001.000

Missing values

2023-12-12T13:54:28.525535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:54:28.632402image/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

종류사업장명칭소재지주소(도로명)소재지전화
0미용릴리네 애견미용실인천광역시 부평구 경인로1118번길 38-14, 1층 (일신동)<NA>
1미용현대동물병원 애견용품인천광역시 부평구 경원대로 1286, 부평메디아나센터 1층 (부평동)032-521-6578
2미용아콩하우스인천광역시 부평구 부평문화로 45, 201호 (부평동)<NA>
3미용까까몽 애견미용실인천광역시 부평구 부개로 61-6, 신성프라자 107호 (부개동)032-505-7900
4미용하이슈슈인천광역시 부평구 원적로471번길 3 (부평동)<NA>
5미용보비동물병원인천광역시 부평구 원적로 407 (산곡동)032-524-6959
6미용산곡 애견사랑인천광역시 부평구 부흥로123번길 24 (산곡동)032-228-0202
7미용도날드 도그(Dog)인천광역시 부평구 영성중로36번길 3 (삼산동)032-512-7007
8미용서울종합동물병원인천광역시 부평구 굴포로 42, 세광빌딩 2층 (갈산동)032-508-7571
9미용아트펫인천광역시 부평구 영성중로 18, 삼산주공미래타운아파트상가동 102호 (삼산동)<NA>
종류사업장명칭소재지주소(도로명)소재지전화
80미용모모이 펫 (momoi pet)인천광역시 부평구 부평대로 118, 1층 (부평동)<NA>
81미용로또애견미용실인천광역시 부평구 경원대로 1288, 102호 (부평동)032-511-5922
82미용멍뭉이인천광역시 부평구 마장로 18, 1층 104호 (십정동, 이레하이니스)032-505-7898
83미용아 건인천광역시 부평구 길주남로 112, 1층 (부개동)<NA>
84미용몽발관인천광역시 부평구 길주로595번길 7-10, 1층 (갈산동)<NA>
85미용쁨쁨인천광역시 부평구 후정로 33, 상가 106호 (삼산동, 부평삼산 신원아침도시)<NA>
86미용그루밍 하니인천광역시 부평구 경원대로1240번길 5-4, 1층 101호 (부평동)<NA>
87미용발라당냥인천광역시 부평구 장제로205번길 54, 1층 (부평동)<NA>
88미용망고펫살롱인천광역시 부평구 열우물로 113, 1층 (십정동)<NA>
89미용러브썸그루밍샵인천광역시 부평구 이규보로 38, 1층 1호 (십정동)<NA>