Overview

Dataset statistics

Number of variables6
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory51.2 B

Variable types

Categorical4
Text2

Dataset

Description인천광역시 서구의 동물운송업체 사업장 명칭, 소재지주소, 데이터 기준일, 데이터 담당부서, 부서 전화번호 등의 데이터를 포함하고 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15084784&srcSe=7661IVAWM27C61E190

Alerts

구분 has constant value ""Constant
데이터담당부서 has constant value ""Constant
부서전화번호 is highly overall correlated with 데이터기준일자High correlation
데이터기준일자 is highly overall correlated with 부서전화번호High correlation
데이터기준일자 is highly imbalanced (83.5%)Imbalance
부서전화번호 is highly imbalanced (83.5%)Imbalance

Reproduction

Analysis started2024-01-28 15:14:29.842172
Analysis finished2024-01-28 15:14:30.203326
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
동물 ( 운송 )
41 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동물 ( 운송 )
2nd row동물 ( 운송 )
3rd row동물 ( 운송 )
4th row동물 ( 운송 )
5th row동물 ( 운송 )

Common Values

ValueCountFrequency (%)
동물 ( 운송 ) 41
100.0%

Length

2024-01-29T00:14:30.249325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:14:30.320752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
82
50.0%
동물 41
25.0%
운송 41
25.0%

사업장명칭
Text

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2024-01-29T00:14:30.482053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.6585366
Min length3

Characters and Unicode

Total characters355
Distinct characters65
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

Unique39 ?
Unique (%)95.1%

Sample

1st row스퀘어독스
2nd row메시네
3rd row멍's
4th row강윤펫택시
5th row이너크 펫택시
ValueCountFrequency (%)
pet151어8012 2
 
4.7%
pet110누5050 1
 
2.3%
pet388버6966 1
 
2.3%
pet42노7852 1
 
2.3%
pet154로8498 1
 
2.3%
pet345서4155 1
 
2.3%
몰리네 1
 
2.3%
pet28부2302 1
 
2.3%
pet176나8690 1
 
2.3%
pet141버4785 1
 
2.3%
Other values (32) 32
74.4%
2024-01-29T00:14:30.792550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 30
 
8.5%
p 29
 
8.2%
t 29
 
8.2%
e 29
 
8.2%
0 22
 
6.2%
4 22
 
6.2%
2 20
 
5.6%
5 19
 
5.4%
8 19
 
5.4%
3 18
 
5.1%
Other values (55) 118
33.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 188
53.0%
Lowercase Letter 89
25.1%
Other Letter 74
 
20.8%
Space Separator 2
 
0.6%
Modifier Symbol 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 4
 
5.4%
서 4
 
5.4%
버 3
 
4.1%
나 3
 
4.1%
펫 3
 
4.1%
시 3
 
4.1%
이 3
 
4.1%
수 3
 
4.1%
루 2
 
2.7%
댕 2
 
2.7%
Other values (38) 44
59.5%
Decimal Number
ValueCountFrequency (%)
1 30
16.0%
0 22
11.7%
4 22
11.7%
2 20
10.6%
5 19
10.1%
8 19
10.1%
3 18
9.6%
7 15
8.0%
6 14
7.4%
9 9
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
p 29
32.6%
t 29
32.6%
e 29
32.6%
s 2
 
2.2%
Space Separator
ValueCountFrequency (%)
2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 192
54.1%
Latin 89
25.1%
Hangul 74
 
20.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 4
 
5.4%
서 4
 
5.4%
버 3
 
4.1%
나 3
 
4.1%
펫 3
 
4.1%
시 3
 
4.1%
이 3
 
4.1%
수 3
 
4.1%
루 2
 
2.7%
댕 2
 
2.7%
Other values (38) 44
59.5%
Common
ValueCountFrequency (%)
1 30
15.6%
0 22
11.5%
4 22
11.5%
2 20
10.4%
5 19
9.9%
8 19
9.9%
3 18
9.4%
7 15
7.8%
6 14
7.3%
9 9
 
4.7%
Other values (3) 4
 
2.1%
Latin
ValueCountFrequency (%)
p 29
32.6%
t 29
32.6%
e 29
32.6%
s 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 281
79.2%
Hangul 74
 
20.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 30
10.7%
p 29
10.3%
t 29
10.3%
e 29
10.3%
0 22
7.8%
4 22
7.8%
2 20
7.1%
5 19
6.8%
8 19
6.8%
3 18
6.4%
Other values (7) 44
15.7%
Hangul
ValueCountFrequency (%)
어 4
 
5.4%
서 4
 
5.4%
버 3
 
4.1%
나 3
 
4.1%
펫 3
 
4.1%
시 3
 
4.1%
이 3
 
4.1%
수 3
 
4.1%
루 2
 
2.7%
댕 2
 
2.7%
Other values (38) 44
59.5%

소재지주소
Text

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2024-01-29T00:14:30.987396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length47
Mean length40.780488
Min length26

Characters and Unicode

Total characters1672
Distinct characters165
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

Unique39 ?
Unique (%)95.1%

Sample

1st row인천광역시 서구 담지로8번길 13, 1층 (연희동)
2nd row인천광역시 서구 승학로506번안길 55-6, 402호 (검암동, 검암동 리치빌)
3rd row인천광역시 서구 보석로18번안길 11, 1층 (청라동)
4th row인천광역시 서구 청라라임로 85, 201동 606호 (청라동, 청라린스트라우스)
5th row인천광역시 서구 청라에메랄드로133번길 21, 인아웃커스텀 1층 (청라동)
ValueCountFrequency (%)
인천광역시 41
 
13.3%
서구 41
 
13.3%
청라동 16
 
5.2%
가정동 5
 
1.6%
심곡동 4
 
1.3%
1층 4
 
1.3%
301호 4
 
1.3%
검암동 3
 
1.0%
11 3
 
1.0%
청라커낼로 2
 
0.6%
Other values (158) 185
60.1%
2024-01-29T00:14:31.301104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
267
 
16.0%
1 74
 
4.4%
동 72
 
4.3%
0 69
 
4.1%
, 66
 
3.9%
2 54
 
3.2%
서 46
 
2.8%
로 43
 
2.6%
시 43
 
2.6%
인 42
 
2.5%
Other values (155) 896
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 877
52.5%
Decimal Number 359
21.5%
Space Separator 267
 
16.0%
Other Punctuation 67
 
4.0%
Close Punctuation 41
 
2.5%
Open Punctuation 41
 
2.5%
Dash Punctuation 7
 
0.4%
Uppercase Letter 7
 
0.4%
Lowercase Letter 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 72
 
8.2%
서 46
 
5.2%
로 43
 
4.9%
시 43
 
4.9%
인 42
 
4.8%
천 41
 
4.7%
구 41
 
4.7%
역 41
 
4.7%
광 41
 
4.7%
호 36
 
4.1%
Other values (127) 431
49.1%
Decimal Number
ValueCountFrequency (%)
1 74
20.6%
0 69
19.2%
2 54
15.0%
4 38
10.6%
3 32
8.9%
6 24
 
6.7%
5 23
 
6.4%
7 21
 
5.8%
8 12
 
3.3%
9 12
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
W 1
14.3%
E 1
14.3%
I 1
14.3%
V 1
14.3%
L 1
14.3%
K 1
14.3%
S 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
a 1
16.7%
s 1
16.7%
r 1
16.7%
d 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 66
98.5%
' 1
 
1.5%
Space Separator
ValueCountFrequency (%)
267
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 877
52.5%
Common 782
46.8%
Latin 13
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 72
 
8.2%
서 46
 
5.2%
로 43
 
4.9%
시 43
 
4.9%
인 42
 
4.8%
천 41
 
4.7%
구 41
 
4.7%
역 41
 
4.7%
광 41
 
4.7%
호 36
 
4.1%
Other values (127) 431
49.1%
Common
ValueCountFrequency (%)
267
34.1%
1 74
 
9.5%
0 69
 
8.8%
, 66
 
8.4%
2 54
 
6.9%
) 41
 
5.2%
( 41
 
5.2%
4 38
 
4.9%
3 32
 
4.1%
6 24
 
3.1%
Other values (6) 76
 
9.7%
Latin
ValueCountFrequency (%)
e 2
15.4%
W 1
7.7%
a 1
7.7%
E 1
7.7%
I 1
7.7%
V 1
7.7%
s 1
7.7%
r 1
7.7%
d 1
7.7%
L 1
7.7%
Other values (2) 2
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 877
52.5%
ASCII 795
47.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
267
33.6%
1 74
 
9.3%
0 69
 
8.7%
, 66
 
8.3%
2 54
 
6.8%
) 41
 
5.2%
( 41
 
5.2%
4 38
 
4.8%
3 32
 
4.0%
6 24
 
3.0%
Other values (18) 89
 
11.2%
Hangul
ValueCountFrequency (%)
동 72
 
8.2%
서 46
 
5.2%
로 43
 
4.9%
시 43
 
4.9%
인 42
 
4.8%
천 41
 
4.7%
구 41
 
4.7%
역 41
 
4.7%
광 41
 
4.7%
호 36
 
4.1%
Other values (127) 431
49.1%

데이터기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-07-04
40 
2022-07-25
 
1

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row2023-07-04
2nd row2023-07-04
3rd row2023-07-04
4th row2023-07-04
5th row2023-07-04

Common Values

ValueCountFrequency (%)
2023-07-04 40
97.6%
2022-07-25 1
 
2.4%

Length

2024-01-29T00:14:31.409289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:14:31.483888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-04 40
97.6%
2022-07-25 1
 
2.4%

데이터담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
경제정책과
41 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경제정책과 41
100.0%

Length

2024-01-29T00:14:31.565355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:14:31.642776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경제정책과 41
100.0%

부서전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
032-560-1904
40 
<NA>
 
1

Length

Max length12
Median length12
Mean length11.804878
Min length4

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row032-560-1904
2nd row032-560-1904
3rd row032-560-1904
4th row032-560-1904
5th row032-560-1904

Common Values

ValueCountFrequency (%)
032-560-1904 40
97.6%
<NA> 1
 
2.4%

Length

2024-01-29T00:14:31.729841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:14:31.817511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
032-560-1904 40
97.6%
na 1
 
2.4%

Correlations

2024-01-29T00:14:31.870569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명칭소재지주소데이터기준일자
사업장명칭1.0001.0000.000
소재지주소1.0001.0000.000
데이터기준일자0.0000.0001.000
2024-01-29T00:14:31.938254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서전화번호데이터기준일자
부서전화번호1.0001.000
데이터기준일자1.0001.000
2024-01-29T00:14:32.009880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터기준일자부서전화번호
데이터기준일자1.0001.000
부서전화번호1.0001.000

Missing values

2024-01-29T00:14:30.088429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:14:30.172679image/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

구분사업장명칭소재지주소데이터기준일자데이터담당부서부서전화번호
0동물 ( 운송 )스퀘어독스인천광역시 서구 담지로8번길 13, 1층 (연희동)2023-07-04경제정책과032-560-1904
1동물 ( 운송 )메시네인천광역시 서구 승학로506번안길 55-6, 402호 (검암동, 검암동 리치빌)2023-07-04경제정책과032-560-1904
2동물 ( 운송 )멍's인천광역시 서구 보석로18번안길 11, 1층 (청라동)2023-07-04경제정책과032-560-1904
3동물 ( 운송 )강윤펫택시인천광역시 서구 청라라임로 85, 201동 606호 (청라동, 청라린스트라우스)2023-07-04경제정책과032-560-1904
4동물 ( 운송 )이너크 펫택시인천광역시 서구 청라에메랄드로133번길 21, 인아웃커스텀 1층 (청라동)2023-07-04경제정책과032-560-1904
5동물 ( 운송 )멍`s인천광역시 서구 보석로18번안길 11 (청라동)2023-07-04경제정책과032-560-1904
6동물 ( 운송 )돌봐줄개인천광역시 서구 탁옥로 21, 영성상가 2층 (심곡동)2023-07-04경제정책과032-560-1904
7동물 ( 운송 )고양이 유치원인천광역시 서구 길주로 79, 604호 (석남동)2023-07-04경제정책과032-560-1904
8동물 ( 운송 )pet53노0964인천광역시 서구 경서로 90-14, 2동 202호 (경서동, 강남프라임)2023-07-04경제정책과032-560-1904
9동물 ( 운송 )pet01서4221인천광역시 서구 서로3로 49, 1305동 2407호 (당하동)2023-07-04경제정책과032-560-1904
구분사업장명칭소재지주소데이터기준일자데이터담당부서부서전화번호
31동물 ( 운송 )pet41라3876인천광역시 서구 건지로 404, 216동 2304호 (가좌동, 가좌한신휴플러스)2023-07-04경제정책과032-560-1904
32동물 ( 운송 )pet100보2872인천광역시 서구 청라한울로 96, 326동 101호 (청라동, 청라제일풍경채2차에듀앤파크)2023-07-04경제정책과032-560-1904
33동물 ( 운송 )pet15마1643인천광역시 서구 이음5로 15, 3101동 302호 (원당동, 호반써밋 1차)2023-07-04경제정책과032-560-1904
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